%0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e66301 %T Evaluating User Engagement With a Real-Time, Text-Based Digital Mental Health Support App: Cross-Sectional, Retrospective Study %A Coffield,Edward %A Kausar,Khadeja %+ , Department of Population Health, Hofstra University, 255 Hofstra University, 101 Oak Street Center, Room 100A, Hempstead, NY, 11549, United States, 1 516 463 7019, edward.coffield@hofstra.edu %K mental health support %K text %K app %K utilization %K mobile %K on demand %K scheduled %K mHealth %K mobile health %K app %K student %K university %K college %K mental health %K employee %K job %K work %K occupational health %K counselor %K counseling %K usage %K engagement %K self-reported %D 2025 %7 14.4.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Approximately 20% of US adults identify as having a mental illness. Structural and other barriers prevent many people from receiving mental health services. Digital mental health apps that provide 24-hour, real-time access to human support may improve access to mental health services. However, information is needed regarding how and why people engage with licensed counselors through a digital, real-time, text-based mental health support app in nonexperimental settings. Objective: This study aimed to evaluate how people engage with Counslr, a 24-hour, digital, mental health support app where users communicate in real time with human counselors through text messaging. Specifically, access patterns (eg, day of the week and time of session) and reasons for accessing the platform were examined. Furthermore, whether differences existed between session types (on-demand or scheduled) and membership types (education or noneducation) in regard to access patterns and why people accessed the platform were evaluated. Methods: The study population (users) consisted of students whose schools, universities, or colleges partnered with Counslr and employees whose organizations also partnered with Counslr. Users participated in text-based mental health support sessions. In these sessions, users engaged with licensed counselors through digital, text-based messaging in real time. Users could initiate an on-demand session or schedule a session 24 hours a day. User engagement patterns were evaluated through session length, session day, session time, and self-reported reasons for initiating the session. The data were stratified by membership type (education [students] or noneducation [employees]) and session type (on-demand or scheduled) to evaluate whether differences existed in usage patterns and self-reported reasons for initiating sessions by membership and session types. Results: Most students (178/283, 62.9%) and employees (28/44, 63.6%) accessed Counslr through on-demand sessions. The average and median session times were 40 (SD 15.3) and 45 minutes. On-demand sessions (37.9 minutes) were shorter (P=.001) than scheduled sessions (43.5 minutes). Most users (262/327, 80.1%) accessed Counslr between 7 PM and 5 AM. The hours that users accessed Counslr did not statistically differ by membership type (P=.19) or session type (P=.10). Primary self-reported reasons for accessing Counslr were relationship reasons, depression, and anxiety; however, users initiated sessions for a variety of reasons. Statistically significant differences existed between membership and session types (P<.05) for some of the reasons why people initiated sessions. Conclusions: The novel findings of this study illustrate that real-time, digital mental health support apps, which offer people the opportunity to engage with licensed counselors outside of standard office hours for a variety of mental health conditions, may help address structural barriers to accessing mental health support services. Additional research is needed to evaluate the effectiveness of human-based apps such as Counslr and whether such apps can also address disparities in access to mental health support services among different demographic groups. %M 40228290 %R 10.2196/66301 %U https://formative.jmir.org/2025/1/e66301 %U https://doi.org/10.2196/66301 %U http://www.ncbi.nlm.nih.gov/pubmed/40228290 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 11 %N %P e66062 %T Evaluation of a Digital Media Campaign to Promote Knowledge and Awareness of the GPFirst Program for Nonurgent Conditions: Repeated Survey Study %A Ong Hui Shan,Rebecca %A Oh,Hong Choon %A Goh Sook Kheng,Priscilla %A Lee Sze Hui,Lyndia %A Riza Bte Mohd Razali,Mas %A Ahmad,Edris Atikah %A Raghuram,Jagadesan %A How,Choon How %A Lim Hoon Chin,Steven %+ Health Services Research, Changi General Hospital, SingHealth, 2 Simei Street 3, Singapore, 529889, Singapore, 65 64267479, rebecca.ong.h.s@singhealth.com.sg %K digital media campaign %K public awareness campaign %K primary care partnership %K social media %K nonurgent emergency department visits %K Andersen model %D 2025 %7 14.4.2025 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: GPFirst is a primary care partnership program designed to encourage patients with nonurgent conditions to seek care at participating general practitioner clinics instead of visiting the emergency department. In 2019, a digital media campaign (DMC) was launched to raise awareness and knowledge about GPFirst among residents in eastern Singapore. Objective: This study aims to assess the DMC’s impact on awareness and knowledge of GPFirst across different age groups, and the acceptability and satisfaction of GPFirst. Methods: The DMC, comprising Facebook posts and a website designed using the Andersen behavioral model, was evaluated through 2 repeated cross-sectional surveys. The first cross-sectional survey (CS1) was conducted with eastern Singapore residents aged 21 years and older, 2 1 year before the campaign’s launch, and the second survey (CS2) 4 months after. Satisfaction was measured on a 5-point Likert scale (very poor to excellent) about GPFirst experiences. Acceptability was assessed with 3 yes or no questions on decisions to visit or recommend GPFirst clinics. Analyses used tests of proportions, adjusted multiregression models, and age-stratified secondary analyses. Results: The Facebook posts generated 38,404 engagements within 5 months, with “#ThankYourGP” posts being the most viewed (n=24,602) and engaged (n=2618). Overall, 1191 and 1161 participants completed CS1 and CS2 respectively. Compared to CS1, CS2 participants were more aware (odds ratio [OR] 2.64, 95% CI 2.11-3.31; P<.001) and knowledgeable of GPFirst (OR 4.20, 95% CI 2.62-6.73; P<.001). Awareness was higher among married individuals (OR 1.31, 95% CI 1.04-1.66; P=.03), those without a regular primary care physician (OR 1.79, 95% CI 1.44-2.22; P<.001), and with higher education levels. Similarly, knowledge was greater among individuals with secondary (OR 2.88, 95% CI 1.35-6.17; P=.006) and preuniversity education (OR 2.56, 95% CI 1.14-5.70; P=.02), and those without a regular primary care physician (OR 1.54, 95% CI 1.02-2.34; P=.04). For acceptability, among participants who visited a GPFirst clinic, 98.2% (163/166) reported they would continue to visit a GPFirst clinic before the emergency department in the future, 95.2% (158/166) would recommend the clinic, 60.2% (100/166) cited the clinic’s participation in GPFirst as a factor in their provider’s choice and 87.3% (145/166) were satisfied with GPFirst. Among those unaware of GPFirst, 88.3% (1680/1903) would consider visiting a GPFirst clinic before the emergency department in the future. Conclusions: The DMC improved awareness and knowledge of GPFirst, with high satisfaction and acceptability among participants. Age-dependent strategies may improve GPFirst participation. The “#ThankYourGP” campaign demonstrated the potential of user-generated content to boost social media engagement, a strategy that international health systems could adopt. %M 40228291 %R 10.2196/66062 %U https://publichealth.jmir.org/2025/1/e66062 %U https://doi.org/10.2196/66062 %U http://www.ncbi.nlm.nih.gov/pubmed/40228291 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 13 %N %P e57018 %T Understanding the Relationship Between Ecological Momentary Assessment Methods, Sensed Behavior, and Responsiveness: Cross-Study Analysis %A Cook,Diane %A Walker,Aiden %A Minor,Bryan %A Luna,Catherine %A Tomaszewski Farias,Sarah %A Wiese,Lisa %A Weaver,Raven %A Schmitter-Edgecombe,Maureen %K ecological momentary assessment %K smart home %K smartwatch %K cognitive assessment %K well-being %K monitoring %K monitoring behavior %K machine learning %K artificial intelligence %K app %K wearables %K sensor %K effectiveness %K accuracy %D 2025 %7 10.4.2025 %9 %J JMIR Mhealth Uhealth %G English %X Background: Ecological momentary assessment (EMA) offers an effective method to collect frequent, real-time data on an individual’s well-being. However, challenges exist in response consistency, completeness, and accuracy. Objective: This study examines EMA response patterns and their relationship with sensed behavior for data collected from diverse studies. We hypothesize that EMA response rate (RR) will vary with prompt time of day, number of questions, and behavior context. In addition, we postulate that response quality will decrease over the study duration and that relationships will exist between EMA responses, participant demographics, behavior context, and study purpose. Methods: Data from 454 participants in 9 clinical studies were analyzed, comprising 146,753 EMA mobile prompts over study durations ranging from 2 weeks to 16 months. Concurrently, sensor data were collected using smartwatch or smart home sensors. Digital markers, such as activity level, time spent at home, and proximity to activity transitions (change points), were extracted to provide context for the EMA responses. All studies used the same data collection software and EMA interface but varied in participant groups, study length, and the number of EMA questions and tasks. We analyzed RR, completeness, quality, alignment with sensor-observed behavior, impact of study design, and ability to model the series of responses. Results: The average RR was 79.95%. Of those prompts that received a response, the proportion of fully completed response and task sessions was 88.37%. Participants were most responsive in the evening (82.31%) and on weekdays (80.43%), although results varied by study demographics. While overall RRs were similar for weekday and weekend prompts, older adults were more responsive during the week (an increase of 0.27), whereas younger adults responded less during the week (a decrease of 3.25). RR was negatively correlated with the number of EMA questions (r=−0.433, P<.001). Additional correlations were observed between RR and sensor-detected activity level (r=0.045, P<.001), time spent at home (r=0.174, P<.001), and proximity to change points (r=0.124, P<.001). Response quality showed a decline over time, with careless responses increasing by 0.022 (P<.001) and response variance decreasing by 0.363 (P<.001). The within-study dynamic time warping distance between response sequences averaged 14.141 (SD 11.957), compared with the 33.246 (SD 4.971) between-study average distance. ARIMA (Autoregressive Integrated Moving Average) models fit the aggregated time series with high log-likelihood values, indicating strong model fit with low complexity. Conclusions: EMA response patterns are significantly influenced by participant demographics and study parameters. Tailoring EMA prompt strategies to specific participant characteristics can improve RRs and quality. Findings from this analysis suggest that timing EMA prompts close to detected activity transitions and minimizing the duration of EMA interactions may improve RR. Similarly, strategies such as gamification may be introduced to maintain participant engagement and retain response variance. %R 10.2196/57018 %U https://mhealth.jmir.org/2025/1/e57018 %U https://doi.org/10.2196/57018 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 12 %N %P e67190 %T Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications %A Zhang,Zheyuan %A Sun,Sijin %A Moradbakhti,Laura %A Hall,Andrew %A Mougenot,Celine %A Chen,Juan %A Calvo,Rafael A %K burnout %K digital mental health interventions %K engagement %K eHealth %K design %K health care professional %K health care workers %K United Kingdom %K UK %K China %K Chinese %K occupational stress %K mixed-methods %K stigma %K well-being %K mental health %K digital health %K occupational health %D 2025 %7 4.4.2025 %9 %J JMIR Ment Health %G English %X Background: Mental health issues like occupational stress and burnout, compounded with the after-effects of COVID-19, have affected health care professionals (HCPs) around the world. Digital mental health interventions (DMHIs) can be accessible and effective in supporting well-being among HCPs. However, low engagement rates of DMHIs are frequently reported, limiting the potential effectiveness. More evidence is needed to reveal the factors that impact HCPs’ decision to adopt and engage with DMHIs. Objective: This study aims to explore HCPs’ motivation to engage with DMHIs and identify key factors affecting their engagement. Amongst these, we include cultural factors impacting DMHI perception and engagement among HCPs. Methods: We used a mixed method approach, with a cross-sectional survey (n=438) and semistructured interviews (n=25) with HCPs from the United Kingdom and China. Participants were recruited from one major public hospital in each country. Results: Our results demonstrated a generally low engagement rate with DMHIs among HCPs from the 2 countries. Several key factors that affect DMHI engagement were identified, including belonging to underrepresented cultural and ethnic groups, limited mental health knowledge, low perceived need, lack of time, needs for relevance and personal-based support, and cultural elements like self-stigma. The results support recommendations for DMHIs for HCPs. Conclusions: Although DMHIs can be an ideal alternative mental health support for HCPs, engagement rates among HCPs in China and the United Kingdom are still low due to multiple factors and barriers. More research is needed to develop and evaluate tailored DMHIs with unique designs and content that HCPs can engage from various cultural backgrounds. %R 10.2196/67190 %U https://mental.jmir.org/2025/1/e67190 %U https://doi.org/10.2196/67190 %0 Journal Article %@ 2152-7202 %I JMIR Publications %V 17 %N %P e50225 %T Impact of Platform Design and Usability on Adherence and Retention: Randomized Web- and Mobile-Based Longitudinal Study %A Jiang,Xinrui %A Timmons,Michelle %A Boroda,Elias %A Onakomaiya,Marie %K behavioral science %K electronic patient-reported outcomes %K ePROs %K retention %K adherence %K patient engagement %K clinical trials %K mobile phone %D 2025 %7 27.3.2025 %9 %J J Particip Med %G English %X Background: Low retention and adherence increase clinical trial costs and timelines. Burdens associated with participating in a clinical trial contribute to early study termination. Electronic patient-reported outcome (ePRO) tools reduce participant burden by allowing remote participation, and facilitate communication between researchers and participants. The Datacubed Health (DCH) mobile app is unique among ePRO platforms in its application of behavioral science principles (reward, motivation, identity, etc) in clinical trials to promote engagement, adherence, and retention. Objective: We evaluated the impact of platform design and usability on adherence and retention with a longitudinal study involving repeated patient-facing study instruments. We expected participants assigned to complete instruments in the DCH mobile app to stay in this study longer (increased retention) and complete more surveys while in this study (increased adherence) due to the enhanced motivational elements unique to the participant experience in the DCH app group, and this group’s overall lower burden of participation. Methods: A total of 284 adult participants completed 24 weekly surveys via 1 of 4 modalities (DCH app vs DCH website vs third-party website vs paper) in a web-based and mobile longitudinal study. Participants were recruited from open access websites (eg, Craigslist or Facebook [Meta]), and a closed web-based user group. All participation occurred remotely. Study staff deliberately limited communications with participants to directly assess the main effects of survey administration modality; enrollment and study administration were largely automated. Participants assigned to the DCH app group experienced behavioral science–driven motivational elements related to reward and identity formation throughout their study journey. There was no homolog to this feature in any other tested platform. Participants assigned to the DCH app group accessed study measures using passcodes or smartphone biometrics (face or touch ID). Participants in the DCH website group logged into a website using a username and password. Participants in the third-party website group accessed web-based surveys via personalized emailed links with no need for password authentication. Paper arm participants received paper surveys in the mail. Results: Mode of survey administration (DCH app vs DCH website vs third-party website vs paper) predicted study retention (F9,255=4.22, P<.001) and adherence (F9,162=5.5, P<.001). The DCH app group had greater retention than the paper arm (t=−3.80, P<.001), and comparable retention to the DCH website group. The DCH app group had greater adherence than all other arms (DCH web: t=−2.42, P=.02; third-party web: t=−3.56, P<.001; and paper arm: t=−4.53, P<.001). Conclusions: Using an ePRO platform in a longitudinal study increased retention and adherence in comparison to paper instruments. Incorporating behavioral science design in an ePRO platform resulted in further increase in adherence in a longitudinal study. %R 10.2196/50225 %U https://jopm.jmir.org/2025/1/e50225 %U https://doi.org/10.2196/50225 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e66393 %T Exploring the Discontinuous Usage Behavior of Digital Cognitive Training Among Older Adults With Mild Cognitive Impairment and Their Family Members: Qualitative Study Using the Extended Model of IT Continuance %A Zhang,Shangyang %A Wu,Min %A Sun,Ruini %A Cui,Changjie %A Zhang,Ziqing %A Liao,Jing %A Gong,Ni %+ School of Nursing, Jinan University, No. 601, Huangpu Avenue West, Tianhe District, Guangzhou, 510632, China, 1 15013217344, gongni_1025@163.com %K digital cognitive training %K discontinuous usage behavior %K acceptance %K mild cognitive impairment %K qualitative study %D 2025 %7 25.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital cognitive training (DCT) has been found to be more effective than traditional paper-and-pencil training in enhancing overall cognitive function. However, a significant barrier to its long-term implementation is that older adults with mild cognitive impairment (MCI) do not continue to use it or even show a dropoff in usage after the initial engagement. Such short-term engagement may limit the potential benefits of DCT, as sustained use is required to achieve more pronounced cognitive improvements. Exploring the reasons for the shift in discontinuous usage behavior is crucial for promoting successful DCT implementation and maximizing its positive effects. Objective: This study aimed to explore the intrinsic reasons for the transition from initial acceptance to discontinuous usage behavior among older adults with MCI throughout the DCT process, by employing the extended model of IT continuance (ECM-ITC). Methods: We employed a qualitative research methodology and conducted 38 semistructured interviews before and after the use of DCT (3 times per week over 1 month, with each session lasting 30 minutes) with 19 older adults with MCI (aged 60 years or older) and 4 family members between January and March 2024. Thematic analysis and deductive framework analysis were used to identify the reasons for the discontinuous usage of DCT, with mapping to the ECM-ITC. Results: Most participants failed to complete the standard dosage of DCT. Data analysis revealed the reasons for the shift to discontinuous usage. Despite their need to improve cognitive function, participants found the cognitive training confusing and discovered that DCT did not align with their preferred method of training upon actual use. The disparity between their vague expectations and reality, combined with the contradiction between the “delayed gratification” of DCT and their desire for “immediate gratification,” made it difficult for them to discern the usefulness of DCT. Participants also viewed DCT as an additional financial burden and tended to avoid training under family pressure. They relied on motivational measures, which further weakened their intention to continue DCT, ultimately leading to the inability to develop continuous usage behavior. Conclusions: Continuous usage behavior differs from initial acceptance as it evolves dynamically with user experience over time. To encourage older adults with MCI to persistently engage with DCT, it is essential to not only thoroughly consider their genuine preferences and the potential disruptions DCT may bring to their lives but also bridge the gap between expectations and actual experiences. While ensuring that older adults receive appropriate external incentives and encouragement, it is equally important to foster their intrinsic motivation, thereby gradually cultivating the habit of sustained DCT usage. %M 40132189 %R 10.2196/66393 %U https://www.jmir.org/2025/1/e66393 %U https://doi.org/10.2196/66393 %U http://www.ncbi.nlm.nih.gov/pubmed/40132189 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e63184 %T Smartwatch-Based Ecological Momentary Assessment for High-Temporal-Density, Longitudinal Measurement of Alcohol Use (AlcoWatch): Feasibility Evaluation %A Stone,Chris %A Adams,Sally %A Wootton,Robyn E %A Skinner,Andy %+ School of Psychological Science, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, United Kingdom, 44 07983 317748, cstone2@btinternet.com %K smartwatch %K ecological momentary assessment %K μEMA %K alcohol %K ALSPAC %D 2025 %7 25.3.2025 %9 Original Paper %J JMIR Form Res %G English %X Background: Ecological momentary assessment methods have recently been adapted for use on smartwatches. One particular class of these methods, developed to minimize participant burden and maximize engagement and compliance, is referred to as microinteraction-based ecological momentary assessment (μEMA). Objective: This study explores the feasibility of using these smartwatch-based μEMA methods to capture longitudinal, high-temporal-density self-report data about alcohol consumption in a nonclinical population selected to represent high- and low-socioeconomic position (SEP) groups. Methods: A total of 32 participants from the Avon Longitudinal Study of Parents and Children (13 high and 19 low SEP) wore a smartwatch running a custom-developed μEMA app for 3 months between October 2019 and June 2020. Every day over a 12-week period, participants were asked 5 times a day about any alcoholic drinks they had consumed in the previous 2 hours, and the context in which they were consumed. They were also asked if they had missed recording any alcoholic drinks the day before. As a comparison, participants also completed fortnightly online diaries of alcohol consumed using the Timeline Followback (TLFB) method. At the end of the study, participants completed a semistructured interview about their experiences. Results: The compliance rate for all participants who started the study for the smartwatch μEMA method decreased from around 70% in week 1 to 45% in week 12, compared with the online TLFB method which was flatter at around 50% over the 12 weeks. The compliance for all participants still active for the smartwatch μEMA method was much flatter, around 70% for the whole 12 weeks, while for the online TLFB method, it varied between 50% and 80% over the same period. The completion rate for the smartwatch μEMA method varied around 80% across the 12 weeks. Within high- and low-SEP groups there was considerable variation in compliance and completion at each week of the study for both methods. However, almost all point estimates for both smartwatch μEMA and online TLFB indicated lower levels of engagement for low-SEP participants. All participants scored “experiences of using” the 2 methods equally highly, with “willingness to use again” slightly higher for smartwatch μEMA. Conclusions: Our findings demonstrate the acceptability and potential utility of smartwatch μEMA methods for capturing data on alcohol consumption. These methods have the benefits of capturing higher-temporal-density longitudinal data on alcohol consumption, promoting greater participant engagement with less missing data, and potentially being less susceptible to recall errors than established methods such as TLFB. Future studies should explore the factors impacting participant attrition (the biggest reason for reduced engagement), latency issues, and the validity of alcohol data captured with these methods. The consistent pattern of lower engagement among low-SEP participants than high-SEP participants indicates that further work is warranted to explore the impact and causes of these differences. %M 40131326 %R 10.2196/63184 %U https://formative.jmir.org/2025/1/e63184 %U https://doi.org/10.2196/63184 %U http://www.ncbi.nlm.nih.gov/pubmed/40131326 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e69204 %T Enhancing Digital Health Interventions for Medication Adherence: Considerations for Broader Applicability and Long-Term Impact %A Du,ShanShan %A Zhao,Yining %+ Renhe Rehabilitation Hospital, Renhe Street, Hubei, China, 86 15767853433, 1547838432@qq.com %K mobile apps %K digital health %K atrial fibrillation %K anticoagulants %K medication adherence %K mobile phone %D 2025 %7 14.3.2025 %9 Letter to the Editor %J J Med Internet Res %G English %X %R 10.2196/69204 %U https://www.jmir.org/2025/1/e69204 %U https://doi.org/10.2196/69204 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60102 %T Optimizing Engagement With a Smartphone App to Prevent Violence Against Adolescents: Results From a Cluster Randomized Factorial Trial in Tanzania %A Janowski,Roselinde %A Cluver,Lucie D %A Shenderovich,Yulia %A Wamoyi,Joyce %A Wambura,Mwita %A Stern,David %A Clements,Lily %A Melendez-Torres,G J %A Baerecke,Lauren %A Ornellas,Abigail %A Chetty,Angelique Nicole %A Klapwijk,Jonathan %A Christine,Laetitia %A Mukabana,Ateamate %A Te Winkel,Esmee %A Booij,Anna %A Mbosoli,Gervas %A Lachman,Jamie M %+ Department of Social Policy and Intervention, University of Oxford, Barnett House, 32-37 Wellington Square, Oxford, OX1 2ER, United Kingdom, 44 01865270325, roselinde.janowski@spi.ox.ac.uk %K digital health %K engagement %K parenting %K adolescents %K low- and middle-income country %K violence against children %K Multiphase Optimization Strategy %K randomized factorial experiment %K mobile phone %D 2025 %7 10.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Violence and abuse exert extensive health, social, and economic burdens on adolescents in low- and middle-income countries. Digital parenting interventions are promising for mitigating risks at scale. However, their potential for public health impact hinges on meaningful engagement with the digital platform. Objective: The objective of this study was to evaluate the impact of 3 intervention design and implementation factors aimed at increasing engagement with a noncommercialized, offline-first smartphone app for caregivers of adolescents in Tanzania, in partnership with the United Nations Children’s Fund, the World Health Organization, and the Tanzanian national government. Methods: Following Multiphase Optimization Strategy (MOST) principles, we conducted a 2×2×2 cluster randomized factorial trial involving caregivers of adolescents aged 10 to 17 years. Caregivers were recruited by community representatives from 16 urban and periurban communities (ie, clusters) in the Mwanza region of Tanzania. Each cluster was randomized to 1 of 2 levels of each factor: guidance (self-guided or guided via facilitator-moderated WhatsApp groups), app design (structured or unstructured), and preprogram digital support (basic or enhanced). Primary outcomes were automatically tracked measures of engagement (app launches, modules completed, and home practice activities reviewed), with secondary outcomes including modules started, time spent in the app, and positive behaviors logged. Generalized linear mixed-effects models assessed the impact of experimental factors on engagement. Results: Automatically tracked engagement data from 614 caregivers were analyzed, of which 205 (33.4%) were men. Compared to self-guided participants, receiving guidance alongside the app led to significantly more app launches (mean ratio [MR] 2.93, 95% CI 1.84-4.68; P<.001), modules completed (MR 1.29, 95% CI 1.05-1.58; P=.02), modules started (MR 1.20, 95% CI 1.02-1.42; P=.03), time spent in the app (MR 1.45, 95% CI 1.39-1.51; P<.001), and positive behavior logs (MR 2.73, 95% CI 2.07-3.60; P<.001). Compared to the structured design, unstructured design use resulted in significantly more modules completed (MR 1.49, 95% CI 1.26-1.76; P<.001), home practice activity reviews (MR 7.49, 95% CI 5.19-10.82; P<.001), modules started (MR 1.27, 95% CI 1.06-1.52; P=.01), time spent in the app (MR 1.84, 95% CI 1.70-1.99; P<.001), and positive behavior logs (MR 55.68, 95% CI 16.48-188.14; P<.001). While analyses did not detect an effect of enhanced digital support on directly observed engagement, the combination of enhanced digital support and guidance positively influenced engagement across a range of outcomes. Conclusions: This study is the first to systematically optimize engagement with a digital parenting intervention in a low- and middle-income country. Our findings offer important learnings for developing evidence-based, scalable digital interventions in resource-constrained settings. Trial Registration: Pan-African Clinical Trial Registry PACTR202210657553944; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=24051 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-023-15989-x %M 40063069 %R 10.2196/60102 %U https://www.jmir.org/2025/1/e60102 %U https://doi.org/10.2196/60102 %U http://www.ncbi.nlm.nih.gov/pubmed/40063069 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e72477 %T Authors’ Reply: Advancing Digital Health Integration in Oncology %A Lee,Yura %A Park,Ye-Eun %+ Department of Information Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea, 82 2 3010 1498, haepary@amc.seoul.kr %K mHealth %K user experience %K cancer %K technology acceptance model %K structural equation modeling %K health care app %K mixed-method study %K medical care %K digital health care %K cancer survivors %K disparities %K health status %K behavioral intervention %K clinician %D 2025 %7 7.3.2025 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 40053760 %R 10.2196/72477 %U https://www.jmir.org/2025/1/e72477 %U https://doi.org/10.2196/72477 %U http://www.ncbi.nlm.nih.gov/pubmed/40053760 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e70316 %T Advancing Digital Health Integration in Oncology %A Khan,Rai Muhammad Umar %A Tariq,Hassan %+ Punjab Medical College, Faisalabad Medical University, Sargodha Road, Faisalabad, 38800, Pakistan, 92 41 9210080, raimumerkhan@gmail.com %K mHealth %K user experience %K cancer %K technology acceptance model %K structural equation modeling %K health care app %K mixed-method study %K medical care %K digital health care %K cancer survivors %K disparities %K health status %K behavioral intervention %K clinician %D 2025 %7 7.3.2025 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 40053796 %R 10.2196/70316 %U https://www.jmir.org/2025/1/e70316 %U https://doi.org/10.2196/70316 %U http://www.ncbi.nlm.nih.gov/pubmed/40053796 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 8 %N %P e49507 %T Implementation of a Web-Based Program for Advance Care Planning and Evaluation of its Complexity With the Nonadoption, Abandonment, Scale-Up, Spread, And Sustainability (NASSS) Framework: Qualitative Evaluation Study %A van der Smissen,Doris %A Schreijer,Maud A %A van Gemert-Pijnen,Lisette J E W C %A Verdaasdonk,Rudolf M %A van der Heide,Agnes %A Korfage,Ida J %A Rietjens,Judith A C %+ Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, Rotterdam, 3015 GD, The Netherlands, 31 107038460, i.korfage@erasmusmc.nl %K eHealth %K web-based intervention %K implementation %K sustainability %K advance care planning %K NASSS framework %K nonadoption, abandonment, scale-up, spread, and sustainability framework %K health communication %K patient education %K patient-centered care %D 2025 %7 4.3.2025 %9 Original Paper %J JMIR Aging %G English %X Background: The implementation of eHealth applications often fails. The NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) framework aims to identify complexities in eHealth applications; the more complex, the more risk of implementation failure. Objective: This study aimed to analyze the implementation of the web-based advance care planning (ACP) program “Explore Your Preferences for Treatment and Care” using the NASSS framework. Methods: The NASSS framework enables a systematic approach to improve the implementation of eHealth tools. It is aimed at generating a rich and situated analysis of complexities in multiple domains, based on thematic analysis of existing and newly collected data. It also aims at supporting individuals and organizations to handle these complexities. We used 6 of 7 domains of the NASSS framework (ie, condition, technology, value proposition, adopters, external context, and embedding and adaptation over time) leaving out “organization,” and analyzed the multimodal dataset of a web-based ACP program, its development and evaluation, including peer-reviewed publications, notes of stakeholder group meetings, and interviews with stakeholders. Results: This study showed that the web-based ACP program uses straightforward technology, is embedded in a well-established web-based health platform, and in general appears to generate a positive value for stakeholders. A complexity is the rather broad target population of the program. A potential complexity considers the limited insight into the extent to which health care professionals adopt the program. Awareness of the relevance of the web-based ACP program may still be improved among target populations of ACP and among health care professionals. Furthermore, the program may especially appeal to those who value individual autonomy, self-management, and an explicit and direct communicative approach. Conclusions: Relatively few complexities were identified considering the implementation of the web-based ACP program “Explore Your Preferences for Treatment and Care.” The program is evidence-based, freestanding, and well-maintained, with straightforward, well-understood technology. The program is expected to generate a positive value for different stakeholders. Complexities include the broad target population of the program and sociocultural factors. People with limited digital literacy may need support to use the program. Its uptake might be improved by increasing awareness of ACP and the program among a wider population of potential users and among health care professionals. Addressing these issues may guide future use and sustainability of the program. %M 40053753 %R 10.2196/49507 %U https://aging.jmir.org/2025/1/e49507 %U https://doi.org/10.2196/49507 %U http://www.ncbi.nlm.nih.gov/pubmed/40053753 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 13 %N %P e60811 %T Impact of a Mobile Money–Based Conditional Cash Transfer Intervention on Health Care Utilization in Southern Madagascar: Mixed-Methods Study %A Franke,Mara Anna %A Neumann,Anne %A Nordmann,Kim %A Suleymanova,Daniela %A Ravololohanitra,Onja Gabrielle %A Emmrich,Julius Valentin %A Knauss,Samuel %K cash transfer intervention %K Madagascar %K Sub-Saharan Africa %K health care utilization %K humanitarian assistance %K Africa %K mobile %K mixed methods study %K money %K quantitative %K qualitative %K thematic analysis %K policy %K service %K delivery %K health care system %K cash %K economic %K financial %K payment %K time series %D 2025 %7 3.3.2025 %9 %J JMIR Mhealth Uhealth %G English %X Background: Mobile money–based cash transfer interventions are becoming increasingly utilized, especially in humanitarian settings. southern Madagascar faced a humanitarian emergency in 2021-2022, when the second wave of the COVID-19 pandemic and a severe famine affected the fragile region simultaneously. Objective: This mixed-methods study aims to analyze the impact and factors influencing the success of a mobile money–based conditional cash transfer intervention for health care utilization at 4 primary and 11 secondary facilities in Madagascar. Methods: We obtained quantitative data from 11 facility registers, detailing patient numbers per month, categorized into maternity care, surgical care, pediatric care, outpatient care, and inpatient care. An interrupted time series analysis, without a control group, was conducted using the end of the intervention in July 2022 as the cut off point. For qualitative data, 64 in-depth interviews were conducted with health care providers, NGO staff, policymakers, beneficiaries, and nonbeneficiaries of the intervention, and was interpreted by 4 independent researchers using reflexive thematic analysis to identify facilitators and barriers to implementation. Results: The interrupted time series analysis showed a significant negative impact on health care utilization, indicating a reduction in health care–seeking behavior after the end of the cash transfer intervention. The effect was stronger in the slope change of patient numbers per month (defined as P<.05), which significantly decreased in 39 of 55 (70%) models compared to the step change at the end of the intervention, which showed a significant but lower change (P <.05) in 40% (22/55) of models. The changes were most pronounced in surgical and pediatric care. The key factors that influenced the success of the implementation were grouped across three levels. At the community level, outreach conducted to inform potential beneficiaries about the project by community health workers and using the radio was a decisive factor for success. At participating facilities, high intrinsic staff motivation and strong digital literacy among facility staff positively influenced the intervention. Confusion regarding previous activities by the same implementing NGO and perceptions of unfair bonus payments for health care providers included in the project negatively affected the intervention. Finally, at the NGO-level, the staff present at each facility and the speed and efficiency of administrative processes during the intervention were decisive factors that influenced the intervention. Conclusions: The conditional cash transfer intervention was overarchingly successful in increasing health care utilization in southern Madagascar in a humanitarian setting. However, this success was conditional on key implementation factors at the community, facility, and NGO levels. In the future, similar interventions should proactively consider the key factors identified in this study to optimize the impact. %R 10.2196/60811 %U https://mhealth.jmir.org/2025/1/e60811 %U https://doi.org/10.2196/60811 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e58341 %T Web-Based Application for Reducing Methamphetamine Use Among Aboriginal and Torres Strait Islander People: Randomized Waitlist Controlled Trial %A Reilly,Rachel %A McKetin,Rebecca %A Barzi,Federica %A Degan,Tayla %A Ezard,Nadine %A Conigrave,Katherine %A Butt,Julia %A Roe,Yvette %A Wand,Handan %A Quinn,Brendan %A Longbottom,Wade %A Treloar,Carla %A Dunlop,Adrian %A Ward,James %+ School of Psychology, University of Adelaide, North Terrace, Adelaide, 5005, Australia, 61 881284216, rachel.reilly@sahmri.com %K methamphetamine %K Aboriginal and Torres Strait Islander Health %K web-based intervention %K randomised controlled trial %K therapeutic program %K methamphetamine use %K substance use %K digital interventions %K treatment %K psychosocial wellbeing %K effectiveness %K app %K psychosocial distress %K mobile phone %D 2025 %7 28.2.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital interventions can help to overcome barriers to care, including stigma, geographical distance, and a lack of culturally appropriate treatment options. “We Can Do This” is a web-based app that was designed with input from cultural advisors and end users to support Aboriginal and Torres Strait Islander people seeking to stop or reduce their use of methamphetamine and increase psychosocial well-being. Objective: This study aimed to evaluate the effectiveness of the “We Can Do This” web-based app as a psychosocial treatment for Aboriginal and Torres Strait Islander people who use methamphetamine. Methods: The web app was evaluated using a randomized waitlist controlled parallel group trial. Participants were Aboriginal and Torres Strait Islander people aged 16 years or older who self-identified as having used methamphetamine at least weekly for the past 3 months. Participants were randomized on a 1:1 ratio to receive either access to the web-based app for 6 weeks or a waitlist control group. Both groups received access to a website with harm minimization information. The primary outcome was days of methamphetamine use in the past 4 weeks assessed at 1, 2, and 3 months post randomization. Secondary outcomes included severity of methamphetamine dependence (Severity of Dependence Scale [SDS]), psychological distress (Kessler 10 [K10]), help-seeking behavior, and days spent out of role due to methamphetamine use. Results: Participants (N=210) were randomized to receive either access to the web-based app (n=115) or the waitlist control condition (n=95). Follow-up was 63% at 1 month, 57% at 2 months, and 54% at 3 months. There were no significant group differences in days of methamphetamine use in the past 4 weeks at 1 the month (mean difference 0.2 days, 95% CI –1.5 to –2), 2 months (mean difference 0.6 days, 95% CI –1 to 2.4 days) or 3 months (mean difference 1.4 days, 95% CI –0.3 to 3.3 days) follow-up. There were no significant group differences in K10 scores, SDS scores, days out of role, or help-seeking at any of the 3 follow-up timepoints. There was poor adherence to the web-based app, only 20% of participants in the intervention group returned to the web-based app after their initial log-in. Participants cited personal issues and forgetting about the web-based app as the most common reasons for nonadherence. Conclusions: We found poor engagement with this web-based app. The web-based app had no significant effects on methamphetamine use or psychosocial well-being. Poor adherence and low follow-up hindered our ability to accurately evaluate the effectiveness of the web-based app. Future web-based apps for this population need to consider methods to increase participant engagement. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12619000134123p; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=376088 International Registered Report Identifier (IRRID): RR2-10.2196/14084 %M 40053754 %R 10.2196/58341 %U https://www.jmir.org/2025/1/e58341 %U https://doi.org/10.2196/58341 %U http://www.ncbi.nlm.nih.gov/pubmed/40053754 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 14 %N %P e67981 %T Increasing Participation and Completion Rates in Questionnaire Surveys of Primary Care Patients: Cluster-Randomized Study %A Sebo,Paul %A Tudrej,Benoit %A Bernard,Augustin %A Delaunay,Bruno %A Dupuy,Alexandra %A Malavergne,Claire %A Maisonneuve,Hubert %+ , University Institute for Primary Care (IuMFE), University of Geneva, Rue Michel-Servet 1, Geneva, 1211, Switzerland, 41 22 379 50 61, paulsebo@hotmail.com %K completion rate %K missing data %K mixed mode %K web-based %K participation rate %K primary care %K questionnaire %K QR code %K tablet %K survey %K primary care patients %K randomized study %D 2025 %7 25.2.2025 %9 Original Paper %J Interact J Med Res %G English %X Background: Participation and completion rates in questionnaire-based surveys are often low. Objective: This study aims to assess participation and completion rates for a survey using paper and mixed mode questionnaires with patients recruited by research assistants in primary care waiting rooms. Methods: This cluster-randomized study, conducted in 2023 in France, involved 974 patients from 39 practices randomized into 4 groups: “paper with incentive” (n=251), “paper without incentive” (n=368), “mixed mode with tablet” (n=187), and “mixed mode with QR code” (n=168). Analyses compared the combined paper group with the 2 mixed mode groups and the “paper with incentive” and “paper without incentive” groups. Logistic regressions were used to analyze participation and completion rates. Results: Of the 974 patients recruited, 822 (women: 536/821, 65.3%; median age 52, IQR 37-68 years) agreed to participate (participation rate=84.4%), with no significant differences between groups. Overall, 806 patients (98.1%) answered all 48 questions. Completion rates were highest in the combined paper group (99.8%) compared to mixed mode groups (96.8% for paper or tablet, 93.3% for paper or QR code; P<.001). There was no significant difference in completion rates between the “paper with incentive” and “paper without incentive” groups (100% vs 99.7%). Conclusions: Recruiting patients in waiting rooms with research assistants resulted in high participation and completion rates across all groups. Mixed mode options did not enhance participation or completion rates but may offer logistical advantages. Future research should explore incentives and mixed-mode strategies in diverse settings. %M 39999441 %R 10.2196/67981 %U https://www.i-jmr.org/2025/1/e67981 %U https://doi.org/10.2196/67981 %U http://www.ncbi.nlm.nih.gov/pubmed/39999441 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 12 %N %P e63497 %T Patterns of Skills Review in Smartphone Cognitive Behavioral Therapy for Depression: Observational Study of Intervention Content Use %A Bernstein,Emily E %A Daniel,Katharine E %A Miyares,Peyton E %A Hoeppner,Susanne S %A Bentley,Kate H %A Snorrason,Ivar %A Fisher,Lauren B %A Greenberg,Jennifer L %A Weingarden,Hilary %A Harrison,Oliver %A Wilhelm,Sabine %+ University of Virginia, 560 Ray C Hunt Drive, Charlottesville, 22903, United States, 1 434 924 2495, ked4fd@virginia.edu %K smartphone %K cognitive behavioral therapy %K engagement %K depression %K mental health %K Mindset %K mHealth %K mobile health %K app %K digital health %K mobile phone %D 2025 %7 24.2.2025 %9 Original Paper %J JMIR Ment Health %G English %X Background: Smartphones could enhance access to effective cognitive behavioral therapy (CBT). Users may frequently and flexibly access bite-size CBT content on personal devices, review and practice skills, and thereby achieve better outcomes. Objective: We explored the distribution of actual interactions participants had with therapeutic content in a trial of smartphone CBT for depression and whether interactions were within assigned treatment modules or revisits to prior module content (ie, between-module interactions). Methods: We examined the association between the number of within- and between-module interactions and baseline and end-of-treatment symptom severity during an 8-week, single-arm open trial of a therapist-guided CBT for depression mobile health app. Results: Interactions were more frequent early in treatment and modestly declined in later stages. Within modules, most participants consistently made more interactions than required to progress to the next module and tended to return to all types of content rather than focus on 1 skill. By contrast, only 15 of 26 participants ever revisited prior module content (median number of revisits=1, mode=0, IQR 0-4). More revisits were associated with more severe end-of-treatment symptom severity after controlling for pretreatment symptom severity (P<.05). Conclusions: The results suggest that the frequency of use is an insufficient metric of engagement, lacking the nuance of what users are engaging with and when during treatment. This lens is essential for developing personalized recommendations and yielding better treatment outcomes. Trial Registration: ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329 %M 39993308 %R 10.2196/63497 %U https://mental.jmir.org/2025/1/e63497 %U https://doi.org/10.2196/63497 %U http://www.ncbi.nlm.nih.gov/pubmed/39993308 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e60256 %T Effects of Individualized Follow-Up With an App Postcardiac Rehabilitation: Five-Year Follow-Up of a Randomized Controlled Trial %A Lunde,Pernille %A Bye,Asta %A Grimsmo,Jostein %A Pripp,Are Hugo %A Ritschel,Vibeke %A Jarstad,Even %A Nilsson,Birgitta Blakstad %+ Department of Rehabilitation Science and Health Technology, Faculty of Health Sciences, OsloMet – Oslo Metropolitan University, PB 4, St. Olavs plass, Oslo, 0130, Norway, 47 48063537, plunde@oslomet.no %K mHealth %K cardiac rehabilitation %K mobile phone app %K smartphone %K lifestyle %D 2025 %7 13.2.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Adherence to healthy behaviors initiated or adapted during cardiac rehabilitation (CR) remains a significant challenge, with few patients meeting guideline standards for secondary prevention. The use of mobile health (mHealth) interventions has been proposed as a potential solution to improve adherence to healthy behaviors after CR. In particular, app-based interventions have shown promise due to their ability to provide monitoring and feedback anytime and anywhere. Growing evidence supports the use of apps in post-CR settings to enhance adherence. In 2020, we demonstrated that individualized follow-up via an app increased adherence to healthy behaviors 1 year after CR. However, it remains uncertain whether these effects persist once the follow-up is discontinued. Objective: This study aims to evaluate the long-term effects of individualized follow-up using an app, assessed 4 years after the intervention. Methods: A single-blinded multicenter randomized controlled trial was conducted. Patients were recruited from 2 CR centers in eastern Norway. The intervention group (IG) received individualized follow-up through an app for 1 year, while the control group (CG) received usual care. After the 1-year follow-up, the app-based follow-up was discontinued for the IG, and both groups were encouraged to maintain or improve their healthy behaviors based on their individual risk profiles. The primary outcome was the difference in peak oxygen uptake (VO2peak). The secondary outcomes included exercise performance, body weight, blood pressure, lipid profile, exercise habits, health-related quality of life, health status, cardiac events, and physical activity. Linear mixed models for repeated measurements were used to analyze differences between groups. All tests were 2-sided, and P values ≤0.05 were considered statistically significant. Results: At the 5-year follow-up, 101 out of the initial 113 randomized participants were reassessed. Intention-to-treat analyses, using a mixed model for repeated measurements, revealed a statistically significant difference (P=.04) in exercise habits in favor of the IG, with a mean difference of 0.67 (95% CI 0.04-1.29) exercise sessions per week. Statistically significant differences were also observed in triglycerides (mean difference 0.40, 95% CI 0.00-0.79 mmol/l, P=.048) and walking (P=.03), but these were in favor of the CG. No differences were found between the groups for other evaluated outcomes. Conclusions: Most of the benefits derived from the app-based follow-up diminished by 4 years after the intervention. Although the IG reported statistically significantly higher levels of exercise, this did not translate into improved VO2peak or exercise performance. Our study highlights the need for follow-up from health care providers to enhance adherence to healthy behaviors in the long term following CR. Trial Registration: ClinicalTrials.gov NCT03174106; https://clinicaltrials.gov/ct2/show/NCT03174106 (original study protocol) and NCT05697120; https://clinicaltrials.gov/ct2/show/NCT05697120 (updated study protocol) %M 39946716 %R 10.2196/60256 %U https://www.jmir.org/2025/1/e60256 %U https://doi.org/10.2196/60256 %U http://www.ncbi.nlm.nih.gov/pubmed/39946716 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 8 %N %P e60652 %T Uncovering Specific Navigation Patterns by Assessing User Engagement of People With Dementia and Family Caregivers With an Advance Care Planning Website: Quantitative Analysis of Web Log Data %A Dupont,Charlèss %A Smets,Tinne %A Potts,Courtney %A Monnet,Fanny %A Pivodic,Lara %A De Vleminck,Aline %A Van Audenhove,Chantal %A Mulvenna,Maurice %A Van den Block,Lieve %K dementia %K advance care planning %K user engagement %K web-based tool %K care %K website %K caregiver %K communication %K tool %K online %D 2025 %7 11.2.2025 %9 %J JMIR Aging %G English %X Background: Web-based tools have gained popularity to inform and empower individuals in advance care planning. We have developed an interactive website tailored to the unique needs of people with dementia and their families to support advance care planning. This website aims to break away from the rigid pathways shown in other tools that support advance care planning, in which advance care planning is shown as a linear process from information to reflection, communication, and documentation. Objective: This study aimed to assess the website’s usage by people with dementia and their family caregivers, identify distinct user engagement patterns, and visualize how users navigated the website. Methods: We analyzed the website’s log data obtained from an 8-week evaluation study of the site. Interactions with the website were collected in log data files and included visited web pages or clicked-on hyperlinks. Distinct user engagement patterns were identified using K-means clustering process mining, a technique that extracts insights from log data to model and visualize workflows, was applied to visualize user pathways through the website. Results: A total of 52 participants, 21 individuals with dementia and their family caregivers as dyads and 10 family caregivers were included in the study. Throughout the 8-week study, users spent an average of 35.3 (SD 82.9) minutes over 5.5 (SD 3.4) unique days on the website. Family caregivers mostly used the website (alone or with a person with dementia) throughout the 8-week study. Only 3 people with dementia used it on their own. In total, 3 distinct engagement patterns emerged: low, moderate, and high. Low-engagement participants spent less time on the website during the 8 weeks, following a linear path from information to communication to documentation. Moderate- and high-engagement users showed more dynamic patterns, frequently navigating between information pages and communication tools to facilitate exploration of aspects related to advance care planning. Conclusions: The diverse engagement patterns underscore the need for personalized support in advance care planning and challenge the conventional linear advance care planning representations found in other web-based tools. %R 10.2196/60652 %U https://aging.jmir.org/2025/1/e60652 %U https://doi.org/10.2196/60652 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 13 %N %P e60755 %T Evaluating the Efficacy of a Serious Game to Deliver Health Education About Invasive Meningococcal Disease: Clustered Randomized Controlled Equivalence Trial %A Bloomfield,Lauren %A Boston,Julie %A Masek,Martin %A Andrew,Lesley %A Barwood,Donna %A Devine,Amanda %+ Edith Cowan University, 270 Joondalup Drive, Joondalup, 6027, Australia, 61 0863045702, julie.boston@ecu.edu.au %K serious games %K meningococcal disease %K immersive digital applications %K health promotion %K gaming %K meningitis %K infection %K bacteria %K contagious %K infectious %K immersive %K education %K mHealth %K mobile health %K applications %K youth %K adolescents %D 2025 %7 11.2.2025 %9 Original Paper %J JMIR Serious Games %G English %X Background: Invasive meningococcal disease (IMD) is a serious, vaccine-preventable infectious disease that can be life-threatening. Teaching adolescents about the early detection and prevention of IMD can be challenging in a school environment, with educators reporting they lack confidence or expertise to cover this in the classroom environment. Professional guest educators are an alternative to cover specialist topics such as IMD; however, time and resourcing constraints can mean that these educators are not always available. Serious games may be an alternative to face-to-face education, where complex health information may be delivered via self-directed gameplay. Objective: This study aims to develop a serious game that can replace a face-to-face educator in a classroom setting to educate adolescents aged 12 years to 15 years. This study evaluates the efficacy of the Meningococcal Immunisation Awareness, Prevention and Protection app (MIApp), a serious game designed to replicate the information provided in a 30-minute face-to-face presentation provided by a trained educator. Methods: This clustered, randomized controlled equivalence trial involved students (Years 7-10) from 6 secondary schools across metropolitan Western Australia who completed pre- and postintervention questionnaires with a follow-up at 3 months postintervention to measure the primary outcome of IMD knowledge acquisition following this self-guided intervention. The findings were compared with changes in an active control (comparison) group who received an in-class educational presentation about IMD transmission and protection. A questionnaire was developed to assess 9 key areas of knowledge. Median scores for knowledge pre- and postintervention were collected from a self-administered assessment of this questionnaire and, at 3 months postintervention, were compared between groups. A knowledge score of +/–2/16 was determined a priori to meet the criteria for equivalence. Participants who used MIApp were also asked a series of questions to assess the enjoyment of and engagement with the game. Results: Of the 788 participating students, the median postintervention correct score in both the MIApp and control cohorts was 14/16 (87.5% correct responses), compared with the median pre-intervention correct score of 6/16 (37.5% correct responses), representing a significant (P<.001) increase in IMD knowledge in both groups. Improvements were retained in both groups 3 months after the initial intervention (median correct score: 11/16 in the intervention group; 12/16 in the control group; P=.86), demonstrating the efficacy of MIApp to deliver health education about IMD transmission and protection, although response rates in the follow-up cohort were low (255/788, 32.4%). Conclusions: MIApp met the predetermined threshold for equivalence, demonstrating similar improvements in knowledge posttrial and at the 3-month follow-up. Participating adolescents considered the MIApp game more enjoyable than a presentation, with equivalent improvements in knowledge. Serious games could represent a constructive tool to help teachers impart specialized health education. %M 39932769 %R 10.2196/60755 %U https://games.jmir.org/2025/1/e60755 %U https://doi.org/10.2196/60755 %U http://www.ncbi.nlm.nih.gov/pubmed/39932769 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 11 %N %P e64747 %T An App-Based Intervention With Behavioral Support to Promote Brisk Walking in People Diagnosed With Breast, Prostate, or Colorectal Cancer (APPROACH): Process Evaluation Study %A Kennedy,Fiona %A Smith,Susan %A Beeken,Rebecca J %A Buck,Caroline %A Williams,Sarah %A Martin,Charlene %A Lally,Phillippa %A Fisher,Abi %+ Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London, WC1E7HB, United Kingdom, 44 2076791722, abigail.fisher@ucl.ac.uk %K cancer %K physical activity %K process evaluation %K randomized controlled trial %K intervention %K app %K habit %D 2025 %7 10.2.2025 %9 Original Paper %J JMIR Cancer %G English %X Background: The APPROACH pilot study explored the feasibility and acceptability of an app (NHS Active 10) with brief, habit-based, behavioral support calls and print materials intended to increase brisk walking in people diagnosed with cancer. Objective: Following UK Medical Research Council guidelines, this study assessed the implementation of the intervention, examined the mechanisms of impact, and identified contextual factors influencing engagement. Methods: Adults (aged ≥18 y) with breast, prostate, or colorectal cancer who reported not meeting the UK guidelines for moderate-to-vigorous physical activity (≥150 min/wk) were recruited from a single hospital site in Yorkshire, United Kingdom. They were randomly assigned to the intervention or control (usual care) arm and assessed via quantitative surveys at baseline (time point 0 [T0]) and 3-month follow-up (time point 1 [T1]) and qualitative exit interviews (36/44, 82%) at T1. The process evaluation included intervention participants only (n=44). Implementation was assessed using data from the T1 questionnaire exploring the use of the intervention components. The perceived usefulness of the app, leaflet, and behavioral support call was rated from 0 to 5. Behavioral support calls were recorded, and the fidelity of delivery of 25 planned behavior change techniques was rated from 0 to 5 using an adapted Dreyfus scale. Mechanisms of impact were identified by examining T0 and T1 scores on the Self-Reported Behavioural Automaticity Index and feedback on the leaflet, app, call, and planner in the T1 questionnaire and qualitative interviews. Contextual factors influencing engagement were identified through qualitative interviews. Results: The implementation of the intervention was successful: 98% (43/44) of the participants received a behavioral support call, 78% (32/41) reported reading the leaflet, 95% (39/41) reported downloading the app, and 83% (34/41) reported using the planners. The mean perceived usefulness of the app was 4.3 (SD 0.8) in participants still using the app at T1 (n=33). Participants rated the leaflet (mean 3.9, SD 0.6) and the behavioral support call (mean 4.1, SD 1) as useful. The intended behavior change techniques in the behavioral support calls were proficiently delivered (overall mean 4.2, SD 1.2). Mechanisms of impact included habit formation, behavioral monitoring, and support and reassurance from the intervention facilitator. Contextual factors impacting engagement included barriers, such as the impact of cancer and its treatment, and facilitators, such as social support. Conclusions: The APPROACH intervention was successfully implemented and shows promise for increasing brisk walking, potentially through promoting habit formation and enabling self-monitoring. Contextual factors will be important to consider when interpreting outcomes in the larger APPROACH randomized controlled trial. International Registered Report Identifier (IRRID): RR2-10.1186/s40814-022-01028-w %M 39928926 %R 10.2196/64747 %U https://cancer.jmir.org/2025/1/e64747 %U https://doi.org/10.2196/64747 %U http://www.ncbi.nlm.nih.gov/pubmed/39928926 %0 Journal Article %@ 2152-7202 %I JMIR Publications %V 17 %N %P e50828 %T Value Propositions for Digital Shared Medication Plans to Boost Patient–Health Care Professional Partnerships: Co-Design Study %A Bugnon,Benjamin %A Bosisio,Francesca %A Kaufmann,Alain %A Bonnabry,Pascal %A Geissbuhler,Antoine %A von Plessen,Christian %+ School of pharmaceutical sciences, Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, CMU Bâtiment B, Geneva, 1211, Switzerland, 41 796250180, benjamin.bugnon@gmail.com %K digital shared medication plan %K medication records %K medication list %K e-medication %K interoperability %K electronic patient records %K patient involvement %K partnership %K coproduction %K medication safety %D 2025 %7 28.1.2025 %9 Original Paper %J J Particip Med %G English %X Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems. Concurrently, patient-empowerment tools, such as mobile apps, are often not integrated into health care professional workflows. Leveraging coproduction by allowing patients to update their digital shared medication plans (SMPs) is a promising but underused and challenging approach. Objective: This study aimed to determine the value propositions of a digital tool enabling patients, family caregivers, and health care professionals to coproduce and co-manage medication plans within Switzerland’s national eHealth architecture. Methods: We used an experience-based co-design approach in the French-speaking region of Switzerland. The multidisciplinary research team included 5 patients as co-researchers. We recruited polypharmacy patients, family caregivers, and health care professionals with a broad range of experiences, diseases, and ages. The experience-based co-design had 4 phases: capturing, understanding, and improving experiences, followed by preparing recommendations and next steps. A qualitative, participatory methodology was used to iteratively explore collaborative medication management experiences and identify barriers and enabling mechanisms, including technology. We conducted a thematic analysis of participant interviews to develop value propositions for digital SMPs. Results: In total, 31 persons participated in 9 interviews, 5 focus groups, and 2 co-design workshops. We identified four value propositions for involving patients and family caregivers in digital SMP management: (1) comprehensive, accessible information about patients’ current medication plans and histories, enabling streamlined access and reconciliation on a single platform; (2) patient and health care professional empowerment through the explicit co-ownership of SMPs, fostering coresponsibility, accountability, and transparent collaboration; (3) a means of supporting collaborative interprofessional medication management, including tailored access to information and improved communication across stakeholders; and (4) an opportunity to improve the quality of care and catalyze digital health innovations. Participants discussed types of patient involvement in editing shared information and emphasized the importance of tailoring SMPs to individual abilities and preferences to foster health equity. Integrating co-management into the clinical routine and creating supportive conditions were deemed important. Conclusions: Coproduced SMPs can improve medication management by fostering trust and collaboration between patients and health care professionals. Successful implementation will require eHealth interoperability frameworks that embrace the complexity of medication management and support diverse use configurations. Our findings underscored the shared responsibility of all stakeholders, including policy makers and technology providers, for the effective and safe use of SMPs. The 4 value propositions offer strategic guidance, while highlighting the need for further research in different health care settings. %M 39874569 %R 10.2196/50828 %U https://jopm.jmir.org/2025/1/e50828 %U https://doi.org/10.2196/50828 %U http://www.ncbi.nlm.nih.gov/pubmed/39874569 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 9 %N %P e50693 %T A Medication Management App (Smart-Meds) for Patients After an Acute Coronary Syndrome: Pilot Pre-Post Mixed Methods Study %A Ehrler,Frederic %A Gschwind,Liliane %A Hagberg,Hamdi %A Meyer,Philippe %A Blondon,Katherine %K medication adherence %K gamified app %K narration %K acute coronary syndrome %K beliefs about medication %K self-reported adherence %K pilot study %K usability evaluation %K storytelling component %D 2025 %7 23.1.2025 %9 %J JMIR Cardio %G English %X Background: Medication nonadherence remains a significant challenge in the management of chronic conditions, often leading to suboptimal treatment outcomes and increased health care costs. Innovative interventions that address the underlying factors contributing to nonadherence are needed. Gamified mobile apps have shown promise in promoting behavior change and engagement. Objective: This pilot study aimed to evaluate the efficacy and usability of a gamified mobile app that used a narrative storytelling approach to enhance medication adherence among patients following acute coronary syndrome (ACS). The study aimed to assess changes in participants’ beliefs about medication and self-reported adherence before and after the intervention. Additionally, user feedback regarding the narrative component of the app was gathered. Methods: Overall, 18 patients who recently experienced ACS were recruited for a 1-month intervention using the gamified app. Participants’ beliefs about medication and self-reported adherence were assessed using standardized scales pre- and postintervention. The app’s usability was also evaluated through a postintervention questionnaire. Statistical analyses were performed to determine the significance of changes in belief and adherence scores. Results: Although 33% (6/18) of the participants did not use the intervention more than once, the remaining 12 remained engaged during the 30 days of the study. The results did not indicate a significant improvement in participants’ beliefs about medication following the intervention. However, self-reported adherence significantly improved (P<.05) after the intervention with a mean score going from 29.1 (SD 6.9) to 32.4 (SD 5.6), with participants demonstrating a greater self-efficacy to their prescribed medication regimen. However, the results did not indicate a significant improvement in participants’ beliefs about medication. With a mean average score of 80.6, the usability evaluation indicates a good usability rating for the gamified app. However, the narrative storytelling component of the app was not favored by the participants, as indicated by their feedback. Conclusions: This pilot study suggests that a gamified mobile app using narration may effectively enhance medication self-efficacy and positively influence patients’ beliefs about medication following ACS. However, the narrative component of the app did not receive favorable feedback from participants. Future research should focus on exploring alternative methods to engage participants in the app’s narrative elements while maintaining the positive impact on adherence and beliefs about medication observed in this study. %R 10.2196/50693 %U https://cardio.jmir.org/2025/1/e50693 %U https://doi.org/10.2196/50693 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e57619 %T Studying the Digital Intervention Engagement–Mediated Relationship Between Intrapersonal Measures and Pre-Exposure Prophylaxis Adherence in Sexual and Gender Minority Youth: Secondary Analysis of a Randomized Controlled Trial %A Williams,Michael P %A Manjourides,Justin %A Smith,Louisa H %A Rainer,Crissi B %A Hightow-Weidman,Lisa B %A Haley,Danielle F %+ Bouve College of Health Sciences, Northeastern University, 30 Leon St, Boston, MA, 02115, United States, 1 617 373 3323, mpw144@gmail.com %K engagement %K pre-exposure prophylaxis %K PrEP %K digital health intervention %K adherence %K men who have sex with men %K sexual orientation %K gender minority %K youth %K adolescent %K teenager %K HIV %K randomized controlled trial %K mental health %K sociodemographic %K logistic regression %K health information %K health behavior %K sexual health %D 2025 %7 13.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Improving adherence to pre-exposure prophylaxis (PrEP) via digital health interventions (DHIs) for young sexual and gender minority men who have sex with men (YSGMMSM) is promising for reducing the HIV burden. Measuring and achieving effective engagement (sufficient to solicit PrEP adherence) in YSGMMSM is challenging. Objective: This study is a secondary analysis of the primary efficacy randomized controlled trial (RCT) of Prepared, Protected, Empowered (P3), a digital PrEP adherence intervention that used causal mediation to quantify whether and to what extent intrapersonal behavioral, mental health, and sociodemographic measures were related to effective engagement for PrEP adherence in YSGMMSM. Methods: In May 2019, 264 YSGMMSM were recruited for the primary RCT via social media, community sites, and clinics from 9 study sites across the United States. For this secondary analysis, 140 participants were eligible (retained at follow-up, received DHI condition in primary RCT, and completed trial data). Participants earned US currency for daily use of P3 and lost US currency for nonuse. Dollars accrued at the 3-month follow-up were used to measure engagement. PrEP nonadherence was defined as blood serum concentrations of tenofovir-diphosphate and emtricitabine-triphosphate that correlated with ≤4 doses weekly at the 3-month follow-up. Logistic regression was used to estimate the total effect of baseline intrapersonal measures on PrEP nonadherence, represented as odds ratios (ORs) with a null value of 1. The total OR for each intrapersonal measure was decomposed into direct and indirect effects. Results: For every US $1 earned above the mean (US $96, SD US $35.1), participants had 2% (OR 0.98, 95% CI 0.97-0.99) lower odds of PrEP nonadherence. Frequently using phone apps to track health information was associated with a 71% (OR 0.29, 95% CI 0.06-0.96) lower odds of PrEP nonadherence. This was overwhelmingly a direct effect, not mediated by engagement, with a percentage mediated (PM) of 1%. Non-Hispanic White participants had 83% lower odds of PrEP nonadherence (OR 0.17, 95% CI 0.05-0.48) and had a direct effect (PM=4%). Participants with depressive symptoms and anxiety symptoms had 3.4 (OR 3.42, 95% CI 0.95-12) and 3.5 (OR 3.51, 95% CI 1.06-11.55) times higher odds of PrEP nonadherence, respectively. Anxious symptoms largely operated through P3 engagement (PM=51%). Conclusions: P3 engagement (dollars accrued) was strongly related to lower odds of PrEP nonadherence. Intrapersonal measures operating through P3 engagement (indirect effect, eg, anxious symptoms) suggest possible pathways to improve PrEP adherence DHI efficacy in YSGMMSM via effective engagement. Conversely, the direct effects observed in this study may reflect existing structural disparity (eg, race and ethnicity) or behavioral dispositions toward technology (eg, tracking health via phone apps). Evaluating effective engagement in DHIs with causal mediation approaches provides a clarifying and mechanistic view of how DHIs impact health behavior. Trial Registration: ClinicalTrials.gov; NCT03320512; https://clinicaltrials.gov/study/NCT03320512 %M 39804696 %R 10.2196/57619 %U https://www.jmir.org/2025/1/e57619 %U https://doi.org/10.2196/57619 %U http://www.ncbi.nlm.nih.gov/pubmed/39804696 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57458 %T Use of Extrinsic Motivators to Improve the BMI of Obese or Overweight Adolescents: Systematic Review %A Gonçalves,Ana %A Simões,Pedro Augusto %A Sousa-Pinto,Bernardo %A Taveira-Gomes,Tiago %+ Faculty of Medicine, Universidade do Porto, Alameda Prof. Hernâni Monteiro, Porto, 4200-319, Portugal, 351 225513600, an.goncalves@ubi.pt %K adolescents %K obesity %K overweight %K extrinsic motivators %K body mass index %D 2024 %7 30.12.2024 %9 Review %J J Med Internet Res %G English %X Background: The prevalence of overweight and obesity is increasing at an alarming rate in children and adolescents worldwide. Given the dimensions of the problem, the treatment of childhood obesity is considered extremely important. Current evidence indicates that behavioral and cognitive behavioral strategies combined with diet and physical activity approaches may assist in reducing adolescent obesity. Objective: The purpose of this systematic review was to evaluate the use of extrinsic motivators for improving the BMI of obese or overweight adolescents.  Methods: The inclusion criteria were as follows: (1) overweight or obese adolescents, (2) intervention using extrinsic motivators, and (3) outcome variables related to weight status. The exclusion criterion was the presence of an associated chronic disease. The search process was conducted in PubMed and Web of Science (last searched on April 23, 2023). The risk of bias was evaluated independently by 2 authors using Cochrane tools (RoB2 [randomized controlled trials], ROBINS-I, and ROBINS-E). Results: From 3163 studies identified, 20 articles (corresponding to 18 studies) were included in the analysis. The studies differed in terms of study design, sample size, follow-up duration, outcomes reported, and extrinsic motivators used. Most of the studies had videogames or apps as interventions. Of the 18 studies, 9 (50%) reported a statistically significant decrease in BMI. The most used extrinsic motivators were “motivation” (n=13), “feedback” (n=10), and “rewards” (n=9). Among the motivators, “reminders” (100%) and “peer-support” (80%) appeared to have high impacts on BMI reduction.  Conclusions: The heterogeneity of the included studies made analysis difficult. No study evaluated extrinsic motivators in isolation. Most of the studies had a moderate or high risk of bias. The extrinsic motivators “reminders” and “peer-support” appeared to be useful. Further studies are needed, and these should include well-designed randomized controlled trials and studies involving homogeneity in BMI measures, consistent extrinsic motivator definitions, and longer durations to better understand the long-term impacts of extrinsic motivators on weight management success. %M 39576963 %R 10.2196/57458 %U https://www.jmir.org/2024/1/e57458 %U https://doi.org/10.2196/57458 %U http://www.ncbi.nlm.nih.gov/pubmed/39576963 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53613 %T Using Active and Passive Smartphone Data to Enhance Adolescents’ Emotional Awareness in Forensic Outpatient Setting: A Qualitative Feasibility and Usability Study %A Leijse,Merel M L %A van Dam,Levi %A Jambroes,Tijs %A Timmerman,Amber %A Popma,Arne %+ Child and Adolescent Psychiatry & Psychosocial Care, Amsterdam UMC location Vrije Universiteit Amsterdam, Meibergdreef 9, Amsterdam, 1105 AZ, Netherlands, 31 020 8901000, m.m.l.leijse@amsterdamumc.nl %K emotion regulation %K emotion awareness %K smartphone data %K forensic outpatient youth care %K treatment motivation %K treatment alliance %K emotion %K behavioral %K interview %K mHealth %K app %K forensic %K usability %K feasibility %K delinquent %K pediatrics %K youth %K adolescent %K teenager %K experience %K attitude %K opinion %K perception %K perspective %K acceptance %K emoji %K behavioral data %K mobile phone %D 2024 %7 30.12.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Delinquent behavior in adolescence is a prevalent issue, often associated with difficulties across multiple life domains, which in turn perpetuates negative life outcomes. While current treatment programs show partial success in improving behavioral changes and reducing recidivism, comprehensive conclusions regarding the overall efficacy of these interventions have yet to be established. In forensic outpatient settings, the discrepancy between adolescents’ limited emotional awareness and the predominant emphasis on cognitive reflection, combined with low treatment adherence, may be factors that undermine treatment efficacy. New technologies, such as smartphone apps, may offer a solution by integrating real-life data into treatment to improve emotional and behavioral patterns. The low-threshold use of smartphone data can be useful in addressing these treatment challenges. Objective: This study aimed to explore the feasibility and usability of Feelee (Garage2020), a smartphone app that integrates active emoji and passive behavioral data, as a potential addition to treatment for adolescents in a forensic outpatient setting. Methods: We conducted a prepilot study with adolescents (n=4) who used the Feelee app over a 2-week period. App usage included completing a brief emoji survey 3 times a day (active data) and allowing Feelee to track the call logs, Bluetooth devices in proximity, cell tower IDs, app usage, and phone status (passive data). During treatment sessions, both adolescents and clinicians reviewed and discussed the active and passive data. Semistructured interviews were conducted with adolescents and clinicians (n=7) to gather experiences and feedback on the feasibility and usability of incorporating smartphone data into treatment. Results: The study showed that adolescents (n=3) succeeded in using Feelee for the full 2 weeks, and data were available for discussion in at least 1 session per participant. Both adolescents and clinicians (n=7) stated that Feelee was valuable for viewing, discussing, and gaining insight into their emotions, which facilitated targeted actions based on the Feelee data. However, neither adolescents nor clinicians reported increased engagement in treatment as a result of using Feelee. Despite technical issues, overall feedback on the Feelee app, in addition to treatment, was positive (n=7). However, further improvements are needed to address the high battery consumption and the inaccuracies in the accelerometer. Conclusions: This qualitative study provides an in-depth understanding of the potential benefits of integrating active and passive smartphone data for adolescents in a forensic outpatient setting. Feelee appears to contribute to a better understanding of emotions and behaviors, suggesting its potential value in enhancing emotional awareness in treatment. Further research is needed to assess Feelee’s clinical effectiveness and explore how it enhances emotional awareness. Recommendations from adolescents and clinicians emphasize the need for prepilot studies to address user issues, guiding technical improvements and future research in forensic outpatient settings. %M 39753211 %R 10.2196/53613 %U https://formative.jmir.org/2024/1/e53613 %U https://doi.org/10.2196/53613 %U http://www.ncbi.nlm.nih.gov/pubmed/39753211 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57774 %T mHealth Engagement for Antiretroviral Medication Adherence Among People With HIV and Substance Use Disorders: Observational Study %A Mi,Ranran Z %A Yang,Ellie Fan %A Tahk,Alexander %A Tarfa,Adati %A Cotter,Lynne M %A Lu,Linqi %A Yang,Sijia %A Gustafson Sr,David H %A Westergaard,Ryan %A Shah,Dhavan %+ School of Communication, Illinois State University, 4480 School Of Communication, FEL Fell Hall 434, Normal, IL, 61790, United States, 1 (309) 438 3671, fyang8@ilstu.edu %K information and communication technologies %K ICTs %K mHealth %K medication adherence %K HIV care %K antiretroviral therapy %K substance use %K social support %K patient management %K health disparities %K information technology %K communication technology %K mobile health %K app %K clinic %K United States %K participants %K mobile phone %D 2024 %7 20.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite the increasing popularity of mobile health (mHealth) technologies, little is known about which types of mHealth system engagement might affect the maintenance of antiretroviral therapy among people with HIV and substance use disorders. Objective: This study aimed to use longitudinal and detailed system logs and weekly survey data to test a mediation model, where mHealth engagement indicators were treated as predictors, substance use and confidence in HIV management were treated as joint mediators, and antiretroviral therapy adherence was treated as the outcome. We further distinguished the initiation and intensity of system engagement by mode (expression vs reception) and by communication levels (intraindividual vs dyadic vs network). Methods: Tailored for people with HIV living with substance use disorders, the mHealth app was distributed among 208 participants aged >18 years from 2 US health clinics. Supervised by medical professionals, participants received weekly surveys through the app to report their health status and medication adherence data. System use was passively collected through the app, operationalized as transformed click-level data, aggregated weekly, and connected to survey responses with a 7-day lagged window. Using the weekly check-in record provided by participants as the unit of analysis (N=681), linear regression and structure equation models with cluster-robust SEs were used for analyses, controlling within-person autocorrelation and group-level error correlations. Racial groups were examined as moderators in the structure equation models. Results: We found that (1) intensity, not initiation, of system use; (2) dyadic message expression and reception; and (3) network expression positively predicted medication adherence through joint mediators (substance use and confidence in HIV management). However, intraindividual reception (ie, rereading saved entries for personal motivation) negatively predicts medication adherence through joint mediators. We also found Black participants have distinct usage patterns, suggesting the need to tailor mHealth interventions for this subgroup. Conclusions: These findings highlight the importance of considering the intensity of system engagement, rather than initiation alone, when designing mHealth interventions for people with HIV and tailoring these systems to Black communities. %M 39705693 %R 10.2196/57774 %U https://www.jmir.org/2024/1/e57774 %U https://doi.org/10.2196/57774 %U http://www.ncbi.nlm.nih.gov/pubmed/39705693 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e51567 %T Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study %A Baee,Sonia %A Eberle,Jeremy W %A Baglione,Anna N %A Spears,Tyler %A Lewis,Elijah %A Wang,Hongning %A Funk,Daniel H %A Teachman,Bethany %A E Barnes,Laura %+ Department of Systems and Information Engineering, University of Virginia, 151 Engineer’s Way, Charlottesville, VA, 22904, United States, 1 434 924 1723, lb3dp@virginia.edu %K digital mental health intervention %K attrition prediction %K user engagement %K cognitive bias modification %K CBM-I %K dropout rate %K personalization %D 2024 %7 20.12.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: Digital mental health is a promising paradigm for individualized, patient-driven health care. For example, cognitive bias modification programs that target interpretation biases (cognitive bias modification for interpretation [CBM-I]) can provide practice thinking about ambiguous situations in less threatening ways on the web without requiring a therapist. However, digital mental health interventions, including CBM-I, are often plagued with lack of sustained engagement and high attrition rates. New attrition detection and mitigation strategies are needed to improve these interventions. Objective: This paper aims to identify participants at a high risk of dropout during the early stages of 3 web-based trials of multisession CBM-I and to investigate which self-reported and passively detected feature sets computed from the participants interacting with the intervention and assessments were most informative in making this prediction. Methods: The participants analyzed in this paper were community adults with traits such as anxiety or negative thinking about the future (Study 1: n=252, Study 2: n=326, Study 3: n=699) who had been assigned to CBM-I conditions in 3 efficacy-effectiveness trials on our team’s public research website. To identify participants at a high risk of dropout, we created 4 unique feature sets: self-reported baseline user characteristics (eg, demographics), self-reported user context and reactions to the program (eg, state affect), self-reported user clinical functioning (eg, mental health symptoms), and passively detected user behavior on the website (eg, time spent on a web page of CBM-I training exercises, time of day during which the exercises were completed, latency of completing the assessments, and type of device used). Then, we investigated the feature sets as potential predictors of which participants were at high risk of not starting the second training session of a given program using well-known machine learning algorithms. Results: The extreme gradient boosting algorithm performed the best and identified participants at high risk with macro–F1-scores of .832 (Study 1 with 146 features), .770 (Study 2 with 87 features), and .917 (Study 3 with 127 features). Features involving passive detection of user behavior contributed the most to the prediction relative to other features. The mean Gini importance scores for the passive features were as follows: .033 (95% CI .019-.047) in Study 1; .029 (95% CI .023-.035) in Study 2; and .045 (95% CI .039-.051) in Study 3. However, using all features extracted from a given study led to the best predictive performance. Conclusions: These results suggest that using passive indicators of user behavior, alongside self-reported measures, can improve the accuracy of prediction of participants at a high risk of dropout early during multisession CBM-I programs. Furthermore, our analyses highlight the challenge of generalizability in digital health intervention studies and the need for more personalized attrition prevention strategies. %M 39705068 %R 10.2196/51567 %U https://mental.jmir.org/2024/1/e51567 %U https://doi.org/10.2196/51567 %U http://www.ncbi.nlm.nih.gov/pubmed/39705068 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53187 %T Methodological Challenges in Randomized Controlled Trials of mHealth Interventions: Cross-Sectional Survey Study and Consensus-Based Recommendations %A Lopez-Alcalde,Jesus %A Wieland,L Susan %A Yan,Yuqian %A Barth,Jürgen %A Khami,Mohammad Reza %A Shivalli,Siddharudha %A Lokker,Cynthia %A Rai,Harleen Kaur %A Macharia,Paul %A Yun,Sergi %A Lang,Elvira %A Bwanika Naggirinya,Agnes %A Campos-Asensio,Concepción %A Ahmadian,Leila %A Witt,Claudia M %+ Institute for Complementary and Integrative Medicine, University Hospital Zurich, Sonneggstrasse 6, Zurich, CH-8091, Switzerland, 41 43 253 21 31, jesus.lopez@usz.ch %K digital health %K eHealth %K mobile health %K mHealth %K randomized controlled trial %K survey %K recommendations %K intervention integrity %K adherence %K consensus %K mobile phone %D 2024 %7 19.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health (mHealth) refers to using mobile communication devices such as smartphones to support health, health care, and public health. mHealth interventions have their own nature and characteristics that distinguish them from traditional health care interventions, including drug interventions. Thus, randomized controlled trials (RCTs) of mHealth interventions present specific methodological challenges. Identifying and overcoming those challenges is essential to determine whether mHealth interventions improve health outcomes. Objective: We aimed to identify specific methodological challenges in RCTs testing mHealth interventions’ effects and develop consensus-based recommendations to address selected challenges. Methods: A 2-phase participatory research project was conducted. First, we sent a web-based survey to authors of mHealth RCTs. Survey respondents rated on a 5-point scale how challenging they found 21 methodological aspects in mHealth RCTs compared to non-mHealth RCTs. Nonsystematic searches until June 2022 informed the selection of the methodological challenges listed in the survey. Second, a subset of survey respondents participated in an online workshop to discuss recommendations to address selected methodological aspects identified in the survey. Finally, consensus-based recommendations were developed based on the workshop discussion and email interaction. Results: We contacted 1535 authors of mHealth intervention RCTs, of whom 80 (5.21%) completed the survey. Most respondents (74/80, 92%) identified at least one methodological aspect as more or much more challenging in mHealth RCTs. The aspects most frequently reported as more or much more challenging were those related to mHealth intervention integrity, that is, the degree to which the study intervention was implemented as intended, in particular managing low adherence to the mHealth intervention (43/77, 56%), defining adherence (39/79, 49%), measuring adherence (33/78, 42%), and determining which mHealth intervention components are used or received by the participant (31/75, 41%). Other challenges were also frequent, such as analyzing passive data (eg, data collected from smartphone sensors; 24/58, 41%) and verifying the participants’ identity during recruitment (28/68, 41%). In total, 11 survey respondents participated in the subsequent workshop (n=8, 73% had been involved in at least 2 mHealth RCTs). We developed 17 consensus-based recommendations related to the following four categories: (1) how to measure adherence to the mHealth intervention (7 recommendations), (2) defining adequate adherence (2 recommendations), (3) dealing with low adherence rates (3 recommendations), and (4) addressing mHealth intervention components (5 recommendations). Conclusions: RCTs of mHealth interventions have specific methodological challenges compared to those of non-mHealth interventions, particularly those related to intervention integrity. Following our recommendations for addressing these challenges can lead to more reliable assessments of the effects of mHealth interventions on health outcomes. %M 39700488 %R 10.2196/53187 %U https://www.jmir.org/2024/1/e53187 %U https://doi.org/10.2196/53187 %U http://www.ncbi.nlm.nih.gov/pubmed/39700488 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e56897 %T When and Why Adults Abandon Lifestyle Behavior and Mental Health Mobile Apps: Scoping Review %A Kidman,Patrick G %A Curtis,Rachel G %A Watson,Amanda %A Maher,Carol A %+ Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, GPO Box 2471, Adelaide, 5001, Australia, 61 883026558, carol.maher@unisa.edu.au %K mobile health apps %K smartphone applications %K app abandonment %K app attrition %K user engagement %K health behavior %K user retention %K lifestyle management %K quantitative analysis %K qualitative analysis %K mobile phone %D 2024 %7 18.12.2024 %9 Review %J J Med Internet Res %G English %X Background: With 1 in 3 adults globally living with chronic conditions and the rise in smartphone ownership, mobile health apps have become a prominent tool for managing lifestyle-related health behaviors and mental health. However, high rates of app abandonment pose challenges to their effectiveness. Objective: We explored the abandonment of apps used for managing physical activity, diet, alcohol, smoking, and mental health in free-living conditions, examining the duration of app use before abandonment and the underlying reasons. Methods: A scoping review was conducted based on the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines and eligibility criteria were designed according to the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) framework. In total, 4 databases were searched (MEDLINE, Scopus, Embase, and PsycINFO) to identify quantitative and qualitative studies with outcome measures related to app abandonment in adults with free-living conditions, including reasons for abandonment and duration of use, for mobile apps related to WHO (World Health Organization) modifiable health behaviors and mental health. The included studies’ risk of bias was appraised based on the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and COREQ (Consolidated Criteria for Reporting Qualitative Research) checklists. To enable data synthesis across different methodologies, app domains, demographic data, and outcome measures were categorized. Results are presented in 2 sections: quantitatively in a scatterplot to understand when users abandon apps and qualitatively through basic qualitative content analysis to identify the underlying reasons. Results: Eighteen eligible studies (525,824 participants) published between 2014 and 2022, predominantly from the United States, Canada, the United Kingdom, and Germany, were identified. Findings revealed a curvilinear pattern of app abandonment, with sharper abandonment soon after acquisition, followed by a slowing rate of abandonment over time. Taken together, a median of 70% of users discontinued use within the first 100 days. The abandonment rate appeared to vary by app domain, with apps focusing on alcohol and smoking exhibiting faster abandonment, and physical activity and mental health exhibiting longer usage durations. In total, 22 unique reasons for abandonment were organized into six categories: (1) technical and functional issues, (2) privacy concerns, (3) poor user experience, (4) content and features, (5) time and financial costs, and (6) evolving user needs and goals. Conclusions: This study highlights the complex nature of health app abandonment and the need for an improved understanding of user engagement over time, underscoring the importance of addressing various factors contributing to abandonment, from technical issues to evolving user needs. Our findings also emphasize the need for longitudinal studies and a consistent definition of app abandonment to better understand and mitigate this phenomenon, thereby enhancing the effectiveness of health apps in supporting public health initiatives. %M 39693620 %R 10.2196/56897 %U https://www.jmir.org/2024/1/e56897 %U https://doi.org/10.2196/56897 %U http://www.ncbi.nlm.nih.gov/pubmed/39693620 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55176 %T User Experience and Extended Technology Acceptance Model in Commercial Health Care App Usage Among Patients With Cancer: Mixed Methods Study %A Park,Ye-Eun %A Tak,Yae Won %A Kim,Inhye %A Lee,Hui Jeong %A Lee,Jung Bok %A Lee,Jong Won %A Lee,Yura %+ Department of Information Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea, 82 2 3010 1498, haepary@amc.seoul.kr %K mHealth %K user experience %K cancer %K technology acceptance model %K structural equation modeling %K health care app %K mixed-method study %K medical care %K digital health care %K cancer survivors %K disparities %K health status %K behavioral intervention %K clinician %D 2024 %7 18.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The shift in medical care toward prediction and prevention has led to the emergence of digital health care as a valuable tool for managing health issues. Aiding long-term follow-up care for cancer survivors and contributing to improved survival rates. However, potential barriers to mobile health usage, including age-related disparities and challenges in user retention for commercial health apps, highlight the need to assess the impact of patients’ abilities and health status on the adoption of these interventions. Objective: This study aims to investigate the app adherence and user experience of commercial health care apps among cancer survivors using an extended technology acceptance model (TAM). Methods: The study enrolled 264 cancer survivors. We collected survey results from May to August 2022 and app usage records from the app companies. The survey questions were created based on the TAM. Results: We categorized 264 participants into 3 clusters based on their app usage behavior: short use (n=77), medium use (n=101), and long use (n=86). The mean usage days were 9 (SD 11) days, 58 (SD 20) days, and 84 (SD 176) days, respectively. Analysis revealed significant differences in perceived usefulness (P=.01), interface satisfaction (P<.01), equity (P<.01), and utility (P=.01) among the clusters. Structural equation modeling indicated that perceived ease-of-use significantly influenced perceived usefulness (β=0.387, P<.01), and both perceived usefulness and attitude significantly affected behavioral intention and actual usage. Conclusions: This study showed the importance of positive user experience and clinician recommendations in facilitating the effective usage of digital health care tools among cancer survivors and contributing to the evolving landscape of medical care. %M 39693615 %R 10.2196/55176 %U https://www.jmir.org/2024/1/e55176 %U https://doi.org/10.2196/55176 %U http://www.ncbi.nlm.nih.gov/pubmed/39693615 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 9 %N %P e56917 %T Exploring Opportunities and Challenges for the Spread, Scale-Up, and Sustainability of mHealth Apps for Self-Management of Patients With Type 2 Diabetes Mellitus in the Netherlands: Citizen Science Approach %A van Leersum,Catharina Margaretha %A Bults,Marloes %A Siebrand,Egbert %A Olthuis,Theodorus Johannes Josef %A Bekhuis,Robin Enya Marije %A Konijnendijk,Annemieke Ariënne Johanneke %A den Ouden,Marjolein Elisabeth Maria %+ Department of Technology, Policy, and Society, Faculty of Behavioural, Management, and Social Sciences, University of Twente, Drienerlolaan 5, Enschede, 6419 AT, Netherlands, 31 0534899111, karin.vanleersum@ou.nl %K mHealth %K type 2 diabetes mellitus %K implementation %K self-management %K health care system %K citizen science %K mobile health %K mobile app %K digital health %K digital technology %K digital intervention %K smartphone %K diabetes %K DM %K type 2 diabetes %K type 1 diabetes %D 2024 %7 17.12.2024 %9 Original Paper %J JMIR Diabetes %G English %X Background: Technologies evolve at a breakneck pace, and the success of mobile health (mHealth) for people with type 2 diabetes mellitus (T2DM) depends on whether health care professionals, care management, government regulators, and consumers will adopt the technology as a viable solution to enhance patient self-management. Objective: In this study, we explored the challenges of the implementation of mHealth apps in care for patients with T2DM and determined to what extent these challenges complicate the dissemination, limit scale-up, and influence the sustainability of technological interventions for patients with T2DM. Methods: The nonadoption, abandonment, and challenges to scale-up, spread, and sustainability (NASSS) framework served as the basis for our study. The 7 domains of the NASSS framework were explored with a citizen science approach using questionnaires, semistructured in-depth interviews, and focus groups together with patients with T2DM, care professionals, technology developers, policy officers, and a patient organization. Results: Regarding the domain “condition,” being aware of their condition and changing lifestyle were crucial for patients with T2DM to get to grips with their life. The rapid development of health apps for T2DM was highlighted in the domain “technology.” Users should be aware of these apps and know how to use them. The domain “value proposition” included the patient perspective and elaborated on personal values, as well as care professionals who focus on personalized care and pressure on health care. Regarding the “adopters,” it is crucial to know who needs to use and introduce the apps. Responsibility, a shared vision, and resistance among care professionals were mentioned as important determinants for “organization.” Finally, the domain “wider system” showed the importance of involving multiple institutes, care guidelines, and reimbursements. Conclusions: This study investigated the implementation of mHealth apps in an early stage of the implementation process. Key stakeholders were involved, who attributed to the possibilities and limitations of the implementation. It is crucial to have a clear vision from an organizational perspective and specific prerequisites for implementation strategies at micro, meso, and macro levels. Essential strategies at the national level include guidelines for regulations, privacy, and security; the integration of mHealth into T2DM care guidelines; and sufficient reimbursement by health insurers. %M 39689302 %R 10.2196/56917 %U https://diabetes.jmir.org/2024/1/e56917 %U https://doi.org/10.2196/56917 %U http://www.ncbi.nlm.nih.gov/pubmed/39689302 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 10 %N %P e51536 %T Demographics and Health Characteristics Associated With the Likelihood of Participating in Digitally Delivered Exercise Rehabilitation for Improving Heart Health Among Breast Cancer Survivors: Cross-Sectional Survey Study %A Jones,Tamara %A Edbrooke,Lara %A Rawstorn,Jonathan C %A Denehy,Linda %A Hayes,Sandra %A Maddison,Ralph %A Sverdlov,Aaron L %A Koczwara,Bogda %A Kiss,Nicole %A Short,Camille E %K digital health %K breast cancer %K exercise %K rehabilitation %K cardiotoxicity %K demographic %K cancer survivor %K exercise rehabilitation %K home-based program %K pathologic process %K radiation %K physical phenomena %K heart care %K cardiovascular disease %K diagnosis %K cross-sectional study %K chronic disease %K statistics %D 2024 %7 16.12.2024 %9 %J JMIR Cancer %G English %X Background: Strong evidence supports the benefits of exercise following both cardiovascular disease and cancer diagnoses. However, less than one-third of Australians who are referred to exercise rehabilitation complete a program following a cardiac diagnosis. Technological advances make it increasingly possible to embed real-time supervision, tailored exercise prescription, behavior change, and social support into home-based programs. Objective: This study aimed to explore demographic and health characteristics associated with the likelihood of breast cancer survivors uptaking a digitally delivered cardiac exercise rehabilitation program and to determine whether this differed according to intervention timing (ie, offered generally, before, during, or after treatment). Secondary aims were to explore the knowledge of cardiac-related treatment side-effects, exercise behavior, additional intervention interests (eg, diet, fatigue management), and service fee capabilities. Methods: This cross-sectional study involved a convenience sample of breast cancer survivors recruited via social media. A self-reported questionnaire was used to collect outcomes of interests, including the likelihood of uptaking a digitally delivered cardiac exercise rehabilitation program, and demographic and health characteristics. Descriptive statistics were used to summarize sample characteristics and outcomes. Ordered logistic regression models were used to examine associations between demographic and health characteristics and likelihood of intervention uptake generally, before, during, and after treatment, with odds ratios (ORs) <0.67 or >1.5 defined as clinically meaningful and statistical significance a priori set at P≤.05. Results: A high proportion (194/208, 93%) of the sample (mean age 57, SD 11 years; median BMI=26, IQR 23‐31 kg/m2) met recommended physical activity levels at the time of the survey. Living in an outer regional area (compared with living in a major city) was associated with higher odds of uptake in each model (OR 3.86‐8.57, 95% CI 1.04-68.47; P=.01‐.04). Receiving more cardiotoxic treatments was also associated with higher odds of general uptake (OR 1.42, 95% CI 1.02-1.96; P=.04). There was some evidence that a higher BMI, more comorbid conditions, and lower education (compared with university education) were associated with lower odds of intervention uptake, but findings differed according to intervention timing. Respondents identified the need for better education about the cardiotoxic effects of breast cancer treatment, and the desire for multifaceted rehabilitation interventions that are free or low cost (median Aus $10, IQR 10-15 per session; Aus $1=US $0.69 at time of study). Conclusions: These findings can be used to better inform future research and the development of intervention techniques that are critical to improving the delivery of a digital service model that is effective, equitable, and accessible, specifically, by enhancing digital inclusion, addressing general exercise barriers experienced by chronic disease populations, incorporating multidisciplinary care, and developing affordable delivery models. %R 10.2196/51536 %U https://cancer.jmir.org/2024/1/e51536 %U https://doi.org/10.2196/51536 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e52542 %T Factors Associated With Digital Intervention Engagement and Adherence in Patients With Cancer: Systematic Review %A Montalescot,Lucile %A Baussard,Louise %A Charbonnier,Elodie %+ Laboratoire de Psychopathologie et Processus de Santé, Université Paris-Cité, 71 avenue Edouard Vaillant, Boulogne-Billancourt, 92100, France, 33 1 76 53 29 81, lucile.montalescot@u-paris.fr %K adherence %K engagement %K eHealth %K mHealth %K cancer %K mobile health %K app %K eHealth interventions %K patient %K cancer care %K digital health %K health-related %K intervention-related %K sociodemographic %K behavior %K systematic review %D 2024 %7 11.12.2024 %9 Review %J J Med Internet Res %G English %X Background: Digital interventions offer vital support for patients with cancer through education, behavior change, and monitoring. Despite their potential, patient adherence to and engagement with these self-help interventions is challenging. Factors like user characteristics, technology, and intervention design influence adherence and engagement. Existing reviews have gaps in exploring diverse factors associated with adherence in cancer care. Objective: This systematic review aims to identify factors influencing adherence to and engagement with digital interventions with self-help components in cancer care. It examined sociodemographic, psychosocial, health-related, and intervention-related factors that affect patients’ adherence to and engagement with these digital health solutions. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a search was conducted across PubMed, Embase, Cochrane Library, and PsycINFO to find studies published from January 2010 to September 2021. The studies included in this review focused on adult patients with cancer using digital interventions with self-help features. Data were extracted and synthesized using a standardized approach. Factors associated with adherence were synthesized according to their type—sociodemographic factors, psychosocial factors, health-related factors, technology-related factors, and intervention-related factors. Results: Among 9386 studies initially screened, 61 (0.6%) were eligible for analysis. These studies covered diverse eHealth intervention types, cancer types, and outcome measures. Investigating the determinants of adherence to and engagement with digital interventions was the main objective for 43% (26/61) of the included studies. Adherence and engagement were gauged using varied measures, such as dropout rates, log-ins, and self-reported measures. Results regarding factors associated with adherence and engagement were inconsistent across studies. Most sociodemographic (eg, age) and health-related factors (eg, cancer stage) yielded mixed outcomes. However, comorbidity consistently predicted lower adherence and engagement. Results regarding psychosocial factors were more stable across studies. Specifically, higher social support was associated with lower adherence and engagement. Finally, intervention-related factors like intervention type or human support showed conflicting results. Adopting an intersectional perspective revealed that specificities vary according to intervention goals and the operationalization of adherence versus engagement, with women being more adherent and engaged than men in interventions targeting distress. When focusing on adherence rather than engagement, older patients were more adherent than younger patients. Conclusions: This review highlights the complexity of adherence to and engagement with digital interventions in cancer care. While some factors, notably comorbidities and low social support, were consistently linked to adherence and engagement, others displayed mixed associations. The review underscores the need for standardizing measures, investigating specific intervention features, and enhancing study quality to optimize digital interventions for patients with cancer. Further research is crucial to better understand and improve adherence to digital health solutions in cancer care. Trial Registration: PROSPERO CRD42021281028; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=281028 %R 10.2196/52542 %U https://www.jmir.org/2024/1/e52542 %U https://doi.org/10.2196/52542 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53829 %T An Automated Conversational Agent Self-Help Program: Randomized Controlled Trial %A Foran,Heather M %A Kubb,Christian %A Mueller,Janina %A Poff,Spencer %A Ung,Megan %A Li,Margaret %A Smith,Eric Michael %A Akinyemi,Akinniyi %A Kambadur,Melanie %A Waller,Franziska %A Graf,Mario %A Boureau,Y-Lan %+ Department of Health Psychology, University of Klagenfurt, Universitaetstrasse 65067, Klagenfurt, 9020, Austria, 43 46327001641, Heather.Foran@aau.at %K well-being %K chatbot %K randomized controlled trial %K prevention %K flourishing %D 2024 %7 6.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Health promotion and growth-based interventions can effectively improve individual well-being; however, significant gaps in access and utilization still exist. Objective: This study aims to develop and test the effectiveness and implementation of a new, widely targeted conversational agent prevention program (Zenny) designed to enhance well-being. Methods: A total of 1345 individuals in the United States were recruited online and randomly assigned to either (1) a self-help program intervention delivered via an automated conversational agent on WhatsApp or (2) an active control group that had access to evidence-based wellness resources available online. The primary outcomes were well-being (measured using the 5-item World Health Organization Well-being Scale), psychosocial flourishing (assessed with the Flourishing Scale), and positive psychological health (evaluated with the Mental Health Continuum-Short Form). Outcome measures were collected at baseline and again 1 month postassessment. All analyses were conducted using an intention-to-treat approach. Results: Both groups showed significant improvements in well-being (self-help program intervention group effect size: Cohen d=0.26, P<.001; active control group effect size: d=0.24, P<.001), psychosocial flourishing (intervention: d=0.19, P<.001; active control: d=0.18, P<.001), and positive psychological health (intervention: d=0.17, P=.001; active control: d=0.24, P<.001) at postassessment. However, there were no significant differences in effectiveness between the 2 groups (P ranged from .56 to .92). As hypothesized a priori, a greater number of days spent actively engaging with the conversational agent was associated with larger improvements in well-being at postassessment among participants in the intervention group (β=.109, P=.04). Conclusions: The findings from this study suggest that the free conversational agent wellness self-help program was as effective as evidence-based web resources. Further research should explore strategies to increase participant engagement over time, as only a portion of participants were actively involved, and higher engagement was linked to greater improvements in well-being. Long-term follow-up studies are also necessary to assess whether these effects remain stable over time. Trial Registration: ClinicalTrials.gov NCT06208566; https://clinicaltrials.gov/ct2/show/NCT06208566; OSF Registries osf.io/ahe2r; https://doi.org/10.17605/osf.io/ahe2r %M 39641985 %R 10.2196/53829 %U https://www.jmir.org/2024/1/e53829 %U https://doi.org/10.2196/53829 %U http://www.ncbi.nlm.nih.gov/pubmed/39641985 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 8 %N %P e56763 %T Association Between Video-Based Telemedicine Visits and Medication Adherence Among Patients With Heart Failure: Retrospective Cross-Sectional Study %A Zheng,Yaguang %A Adhikari,Samrachana %A Li,Xiyue %A Zhao,Yunan %A Mukhopadhyay,Amrita %A Hamo,Carine E %A Stokes,Tyrel %A Blecker,Saul %K telemedicine %K medication adherence %K heart failure %K systolic dysfunction %K medical therapy %K telehealth %K remote monitoring %K self-management %D 2024 %7 5.12.2024 %9 %J JMIR Cardio %G English %X Background: Despite the exponential growth in telemedicine visits in clinical practice due to the COVID-19 pandemic, it remains unknown if telemedicine visits achieved similar adherence to prescribed medications as in-person office visits for patients with heart failure. Objective: Our study examined the association between telemedicine visits (vs in-person visits) and medication adherence in patients with heart failure. Methods: This was a retrospective cross-sectional study of adult patients with a diagnosis of heart failure or an ejection fraction of ≤40% using data between April 1 and October 1, 2020. This period was used because New York University approved telemedicine visits for both established and new patients by April 1, 2020. The time zero window was between April 1 and October 1, 2020, then each identified patient was monitored for up to 180 days. Medication adherence was measured by the mean proportion of days covered (PDC) within 180 days, and categorized as adherent if the PDC was ≥0.8. Patients were included in the telemedicine exposure group or in-person group if all encounters were video visits or in-person office visits, respectively. Poisson regression and logistic regression models were used for the analyses. Results: A total of 9521 individuals were included in this analysis (telemedicine visits only: n=830 in-person office visits only: n=8691). Overall, the mean age was 76.7 (SD 12.4) years. Most of the patients were White (n=6996, 73.5%), followed by Black (n=1060, 11.1%) and Asian (n=290, 3%). Over half of the patients were male (n=5383, 56.5%) and over half were married or living with partners (n=4914, 51.6%). Most patients’ health insurance was covered by Medicare (n=7163, 75.2%), followed by commercial insurance (n=1687, 17.7%) and Medicaid (n=639, 6.7%). Overall, the average PDC was 0.81 (SD 0.286) and 71.3% (6793/9521) of patients had a PDC≥0.8. There was no significant difference in mean PDC between the telemedicine and in-person office groups (mean 0.794, SD 0.294 vs mean 0.812, SD 0.285) with a rate ratio of 0.99 (95% CI 0.96-1.02; P=.09). Similarly, there was no significant difference in adherence rates between the telemedicine and in-person office groups (573/830, 69% vs 6220/8691, 71.6%), with an odds ratio of 0.94 (95% CI 0.81-1.11; P=.12). The conclusion remained the same after adjusting for covariates (eg, age, sex, race, marriage, language, and insurance). Conclusions: We found similar rates of medication adherence among patients with heart failure who were being seen via telemedicine or in-person visits. Our findings are important for clinical practice because we provide real-world evidence that telemedicine can be an approach for outpatient visits for patients with heart failure. As telemedicine is more convenient and avoids transportation issues, it may be an alternative way to maintain the same medication adherence as in-person visits for patients with heart failure. %R 10.2196/56763 %U https://cardio.jmir.org/2024/1/e56763 %U https://doi.org/10.2196/56763 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60353 %T Investigating the Best Practices for Engagement in Remote Participatory Design: Mixed Methods Analysis of 4 Remote Studies With Family Caregivers %A Jolliff,Anna %A Holden,Richard J %A Valdez,Rupa %A Coller,Ryan J %A Patel,Himalaya %A Zuraw,Matthew %A Linden,Anna %A Ganci,Aaron %A Elliott,Christian %A Werner,Nicole E %+ Department of Health & Wellness Design, School of Public Health - Bloomington, Indiana University Bloomington, 1025 E. 7th Street, Bloomington, IN, 47405, United States, 1 812 855 1561, annjoll@iu.edu %K user-centered design %K family caregivers %K mobile health %K digital health %K web-based intervention %K stakeholder engagement %K patient engagement %K community-based participatory action research %K community participation %K qualitative evaluation %D 2024 %7 3.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital health interventions are a promising method for delivering timely support to underresourced family caregivers. The uptake of digital health interventions among caregivers may be improved by engaging caregivers in participatory design (PD). In recent years, there has been a shift toward conducting PD remotely, which may enable participation by previously hard-to-reach groups. However, little is known regarding how best to facilitate engagement in remote PD among family caregivers. Objective: This study aims to (1) understand the context, quality, and outcomes of family caregivers’ engagement experiences in remote PD and (2) learn which aspects of the observed PD approach facilitated engagement or need to be improved. Methods: We analyzed qualitative and quantitative data from evaluation and reflection surveys and interviews completed by research and community partners (family caregivers) across 4 remote PD studies. Studies focused on building digital health interventions for family caregivers. For each study, community partners met with research partners for 4 to 5 design sessions across 6 months. After each session, partners completed an evaluation survey. In 1 of the 4 studies, research and community partners completed a reflection survey and interview. Descriptive statistics were used to summarize quantitative evaluation and reflection survey data, while reflexive thematic analysis was used to understand qualitative data. Results: In 62.9% (83/132) of evaluations across projects 1-3, participants described the session as “very effective.” In 74% (28/38) of evaluations for project 4, participants described feeling “extremely satisfied” with the session. Qualitative data relating to the engagement context identified that the identities of partners, the technological context of remote PD, and partners’ understanding of the project and their role all influenced engagement. Within the domain of engagement quality, relationship-building and co-learning; satisfaction with prework, design activities, time allotted, and the final prototype; and inclusivity and the distribution of influence contributed to partners’ experience of engagement. Outcomes of engagement included partners feeling an ongoing interest in the project after its conclusion, gratitude for participation, and a sense of meaning and self-esteem. Conclusions: These results indicate high satisfaction with remote PD processes and few losses specific to remote PD. The results also demonstrate specific ways in which processes can be changed to improve partner engagement and outcomes. Community partners should be involved from study inception in defining the problem to be solved, the approach used, and their roles within the project. Throughout the design process, online tools may be used to check partners’ satisfaction with design processes and perceptions of inclusivity and power-sharing. Emphasis should be placed on increasing the psychosocial benefits of engagement (eg, sense of community and purpose) and increasing opportunities to participate in disseminating findings and in future studies. %R 10.2196/60353 %U https://www.jmir.org/2024/1/e60353 %U https://doi.org/10.2196/60353 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e54248 %T Predicting Early Dropout in a Digital Tobacco Cessation Intervention: Replication and Extension Study %A Yu,Linda Q %A Amato,Michael S %A Papandonatos,George D %A Cha,Sarah %A Graham,Amanda L %+ Innovations Center, Truth Initiative, 900 G St NW Fourth Floor, Washington, DC, 20001, United States, 1 2024545938, agraham@truthinitiative.org %K digital interventions %K attrition %K engagement %K dropout %K tobacco %K smoking %K cessation %K mobile health %K internet %K mobile phone %D 2024 %7 27.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Detecting early dropout from digital interventions is crucial for developing strategies to enhance user retention and improve health-related behavioral outcomes. Bricker and colleagues proposed a single metric that accurately predicted early dropout from 4 digital tobacco cessation interventions based on log-in data in the initial week after registration. Generalization of this method to additional interventions and modalities would strengthen confidence in the approach and facilitate additional research drawing on it to increase user retention. Objective: This study had two research questions (RQ): RQ1—can the study by Bricker and colleagues be replicated using data from a large-scale observational, multimodal intervention to predict early dropout? and RQ2—can first-week engagement patterns identify users at the greatest risk for early dropout, to inform development of potential “rescue” interventions? Methods: Data from web users were drawn from EX, a freely available, multimodal digital intervention for tobacco cessation (N=70,265). First-week engagement was operationalized as any website page views or SMS text message responses within 1 week after registration. Early dropout was defined as having no subsequent engagement after that initial week through 1 year. First, a multivariate regression model was used to predict early dropout. Model predictors were dichotomous measures of engagement in each of the initial 6 days (days 2-7) following registration (day 1). Next, 6 univariate regression models were compared in terms of their discrimination ability to predict early dropout. The sole predictor of each model was a dichotomous measure of whether users had reengaged with the intervention by a particular day of the first week (calculated separately for each of 2-7 days). Results: For RQ1, the area under the receiver operating characteristic curve (AUC) of the multivariate model in predicting dropout after 1 week was 0.72 (95% CI 0.71-0.73), which was within the range of AUC metrics found in the study by Bricker and colleagues. For RQ2, the AUCs of the univariate models increased with each successive day until day 4 (0.66, 95% CI 0.65-0.67). The sensitivity of the models decreased (range 0.79-0.59) and the specificity increased (range 0.48-0.73) with each successive day. Conclusions: This study provides independent validation of the use of first-week engagement to predict early dropout, demonstrating that the method generalizes across intervention modalities and engagement metrics. As digital intervention researchers continue to address the challenges of low engagement and early dropout, these results suggest that first-week engagement is a useful construct with predictive validity that is robust across interventions and definitions. Future research should explore the applicability and efficiency of this model to develop interventions to increase retention and improve health behavioral outcomes. %M 39602788 %R 10.2196/54248 %U https://www.jmir.org/2024/1/e54248 %U https://doi.org/10.2196/54248 %U http://www.ncbi.nlm.nih.gov/pubmed/39602788 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e65010 %T Smartphone App for Improving Self-Awareness of Adherence to Edoxaban Treatment in Patients With Atrial Fibrillation (ADHERE-App Trial): Randomized Controlled Trial %A Yoon,Minjae %A Lee,Ji Hyun %A Kim,In-Cheol %A Lee,Ju-Hee %A Kim,Mi-Na %A Kim,Hack-Lyoung %A Lee,Sunki %A Kim,In Jai %A Choi,Seonghoon %A Park,Sung-Ji %A Hur,Taeho %A Hussain,Musarrat %A Lee,Sungyoung %A Choi,Dong-Ju %+ Division of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173 Beon-gil,, Bundang-gu, Seongnam, 13620, Republic of Korea, 82 31 787 7007, djchoi.snu@gmail.com %K mobile apps %K digital health %K atrial fibrillation %K anticoagulants %K medication adherence %K mobile phone %D 2024 %7 21.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Adherence to oral anticoagulant therapy is essential to prevent ischemic stroke in patients with atrial fibrillation (AF). Objective: This study aimed to evaluate whether smartphone app–based interventions improve medication adherence in patients with AF. Methods: This open-label, multicenter randomized controlled trial (ADHERE-App [Self-Awareness of Drug Adherence to Edoxaban Using an Automatic App Feedback System] study) enrolled patients with AF treated with edoxaban for stroke prevention. They were randomly assigned to app-conditioned feedback (intervention; n=248) and conventional treatment (control; n=250) groups. The intervention group received daily alerts via a smartphone app to take edoxaban and measure blood pressure and heart rate at specific times. The control group received only standard, guideline-recommended care. The primary end point was edoxaban adherence, measured by pill count at 3 or 6 months. Medication adherence and the proportion of adequate medication adherence, which was defined as ≥95% of continuous medication adherence, were evaluated. Results: Medication adherence at 3 or 6 months was not significantly different between the intervention and control groups (median 98%, IQR 95%-100% vs median 98%, IQR 91%-100% at 3 months, P=.06; median 98%, IQR 94.5%-100% vs median 97.5%, IQR 92.8%-100% at 6 months, P=.15). However, the proportion of adequate medication adherence (≥95%) was significantly higher in the intervention group at both time points (76.8% vs 64.7% at 3 months, P=.01; 73.9% vs 61% at 6 months, P=.007). Among patients aged >65 years, the intervention group showed a higher medication adherence value and a higher proportion of adequate medication adherence (≥95%) at 6 months. Conclusions: There was no difference in edoxaban adherence between the groups. However, the proportion of adequate medication adherence was higher in the intervention group, and the benefit of the smartphone app–based intervention on medication adherence was more pronounced among older patients than among younger patients. Given the low adherence to oral anticoagulants, especially among older adults, using a smartphone app may potentially improve medication adherence. Trial Registration: International Clinical Trials Registry Platform KCT0004754; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=28496&search_page=L International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2021-048777 %M 39570659 %R 10.2196/65010 %U https://www.jmir.org/2024/1/e65010 %U https://doi.org/10.2196/65010 %U http://www.ncbi.nlm.nih.gov/pubmed/39570659 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e57109 %T Engagement and Acceptability of Acceptance and Commitment Therapy in Daily Life in Early Psychosis: Secondary Findings From a Multicenter Randomized Controlled Trial %A van Aubel,Evelyne %A Vaessen,Thomas %A Uyttebroek,Lotte %A Steinhart,Henrietta %A Beijer-Klippel,Annelie %A Batink,Tim %A van Winkel,Ruud %A de Haan,Lieuwe %A van der Gaag,Mark %A van Amelsvoort,Thérèse %A Marcelis,Machteld %A Schirmbeck,Frederike %A Reininghaus,Ulrich %A Myin-Germeys,Inez %+ Center for Contextual Psychiatry, Psychiatry Research Group, Department of Neurosciences, KU Leuven, Herestraat 49, ON5B bus 1029, Leuven, 3000, Belgium, 32 16 37 31 74, lotte.uyttebroek@kuleuven.be %K acceptance and commitment therapy %K ACT %K first episode of psychosis %K FEP %K ultrahigh risk for psychosis %K UHR %K ecological momentary intervention %K EMI %K mobile health %K mHealth %K blended care %K mobile phone %D 2024 %7 21.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Acceptance and commitment therapy (ACT) is promising in the treatment of early psychosis. Augmenting face-to-face ACT with mobile health ecological momentary interventions may increase its treatment effects and empower clients to take treatment into their own hands. Objective: This study aimed to investigate and predict treatment engagement with and acceptability of acceptance and commitment therapy in daily life (ACT-DL), a novel ecological momentary intervention for people with an ultrahigh risk state and a first episode of psychosis. Methods: In the multicenter randomized controlled trial, 148 individuals with ultrahigh risk or first-episode psychosis aged 15-65 years were randomized to treatment as usual only (control) or to ACT-DL combined with treatment as usual (experimental), consisting of 8 face-to-face sessions augmented with an ACT-based smartphone app, delivering ACT skills and techniques in daily life. For individuals in the intervention arm, we collected data on treatment engagement with and acceptability of ACT-DL during and after the intervention. Predictors of treatment engagement and acceptability included baseline demographic, clinical, and functional outcomes. Results: Participants who received ACT-DL in addition to treatment as usual (n=71) completed a mean of 6 (SD 3) sessions, with 59% (n=42) of participants completing all sessions. App engagement data (n=58) shows that, on a weekly basis, participants used the app 13 times and were compliant with 6 of 24 (25%) notifications. Distribution plots of debriefing scores (n=46) show that 85%-96% of participants reported usefulness on all acceptability items to at least some extent (scores ≥2; 1=no usefulness) and that 91% (n=42) of participants reported perceived burden by number and length of notifications (scores ≥2; 1=no burden). Multiple linear regression models were fitted to predict treatment engagement and acceptability. Ethnic minority backgrounds predicted lower notification response compliance (B=–4.37; P=.01), yet higher app usefulness (B=1.25; P=.049). Negative (B=–0.26; P=.01) and affective (B=0.14; P=.04) symptom severity predicted lower and higher ACT training usefulness, respectively. Being female (B=–1.03; P=.005) predicted lower usefulness of the ACT metaphor images on the app. Conclusions: Our results corroborate good treatment engagement with and acceptability of ACT-DL in early psychosis. We provide recommendations for future intervention optimization. Trial Registration: OMON NL46439.068.13; https://onderzoekmetmensen.nl/en/trial/24803 %M 39570655 %R 10.2196/57109 %U https://formative.jmir.org/2024/1/e57109 %U https://doi.org/10.2196/57109 %U http://www.ncbi.nlm.nih.gov/pubmed/39570655 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53236 %T Investigating the Effectiveness of Technology-Based Distal Interventions for Postpartum Depression and Anxiety: Systematic Review and Meta-Analysis %A Brocklehurst,Sarah P %A Morse,Alyssa R %A Cruwys,Tegan %A Batterham,Philip J %A Leach,Liana %A Robertson,Alysia M %A Sahib,Aseel %A Burke,Colette T %A Nguyen,Jessica %A Calear,Alison L %+ Centre for Mental Health Research, The Australian National University, 63 Eggleston Road, Acton, Canberra, 2601, Australia, 61 2 6125 8406, alison.calear@anu.edu.au %K postpartum %K depression %K anxiety %K birth %K adoptive %K parents %K mobile phone %D 2024 %7 19.11.2024 %9 Review %J J Med Internet Res %G English %X Background: Postpartum anxiety and depression are common in new parents. While effective interventions exist, they are often delivered in person, which can be a barrier for some parents seeking help. One approach to overcoming these barriers is the delivery of evidence-based self-help interventions via websites, smartphone apps, and other digital media. Objective: This study aims to evaluate the effectiveness of technology-based distal interventions in reducing or preventing symptoms of postpartum depression or anxiety in male and female birth and adoptive parents, explore the effectiveness of technology-based distal interventions in increasing social ties, and determine the level of adherence to and satisfaction with technology-based distal interventions. Methods: A systematic review and series of meta-analyses were conducted. Three electronic bibliographic databases (PsycINFO, PubMed, and Cochrane Library) were searched for randomized controlled trials evaluating technology-based distal interventions for postpartum depression or anxiety in birth and adoptive parents. Searches were updated on August 1, 2023, before conducting the final meta-analyses. Data on trial characteristics, effectiveness, adherence, satisfaction, and quality were extracted. Screening and data extraction were conducted by 2 reviewers. Risk of bias was assessed using the Joanna Briggs Institute quality rating scale for randomized controlled trials. Studies were initially synthesized qualitatively. Where possible, studies were also quantitatively synthesized through 5 meta-analyses. Results: Overall, 18 articles met the inclusion criteria for the systematic review, with 14 (78%) providing sufficient data for a meta-analysis. A small significant between-group effect on depression favored the intervention conditions at the postintervention (Cohen d=–0.28, 95% CI –0.41 to –0.15; P<.001) and follow-up (Cohen d=–0.27, 95% CI –0.52 to –0.02; P=.03) time points. A small significant effect on anxiety also favored the intervention conditions at the postintervention time point (Cohen d=–0.29, 95% CI –0.48 to –0.10; P=.002), with a medium effect at follow-up (Cohen d=–0.47, 95% CI –0.88 to –0.05; P=.03). The effect on social ties was not significant at the postintervention time point (Cohen d=0.04, 95% CI –0.12 to 0.21; P=.61). Effective interventions tended to be web-based cognitive behavioral therapy programs with reminders. Adherence varied considerably between studies, whereas satisfaction tended to be high for most studies. Conclusions: Technology-based distal interventions are effective in reducing symptoms of postpartum depression and anxiety in birth mothers. Key limitations of the reviewed evidence include heterogeneity in outcome measures, studies being underpowered to detect modest effects, and the exclusion of key populations from the evidence base. More research needs to be conducted with birth fathers and adoptive parents to better ascertain the effectiveness of interventions in these populations, as well as to further assess the effect of technology-based distal interventions on social ties. Trial Registration: PROSPERO CRD42021290525; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=290525 %M 39561361 %R 10.2196/53236 %U https://www.jmir.org/2024/1/e53236 %U https://doi.org/10.2196/53236 %U http://www.ncbi.nlm.nih.gov/pubmed/39561361 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e62725 %T Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study %A Dwyer,Bridget %A Flathers,Matthew %A Burns,James %A Mikkelson,Jane %A Perlmutter,Elana %A Chen,Kelly %A Ram,Nanik %A Torous,John %+ Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA, 02115, United States, 1 6176676700, jtorous@bidmc.harvard.edu %K engagement %K mental health %K digital phenotype %K pilot study %K phenotyping %K smartphone sensors %K anxiety %K sleep %K fitness %K depression %K qualitative %K app recommendation %K app use %K mobile phone %D 2024 %7 19.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Low engagement with mental health apps continues to limit their impact. New approaches to help match patients to the right app may increase engagement by ensuring the app they are using is best suited to their mental health needs. Objective: This study aims to pilot how digital phenotyping, using data from smartphone sensors to infer symptom, behavioral, and functional outcomes, could be used to match people to mental health apps and potentially increase engagement Methods: After 1 week of collecting digital phenotyping data with the mindLAMP app (Beth Israel Deaconess Medical Center), participants were randomly assigned to the digital phenotyping arm, receiving feedback and recommendations based on those data to select 1 of 4 predetermined mental health apps (related to mood, anxiety, sleep, and fitness), or the control arm, selecting the same apps but without any feedback or recommendations. All participants used their selected app for 4 weeks with numerous metrics of engagement recorded, including objective screentime measures, self-reported engagement measures, and Digital Working Alliance Inventory scores. Results: A total of 82 participants enrolled in the study; 17 (21%) dropped out of the digital phenotyping arm and 18 (22%) dropped out from the control arm. Across both groups, few participants chose or were recommended the insomnia or fitness app. The majority (39/47, 83%) used a depression or anxiety app. Engagement as measured by objective screen time and Digital Working Alliance Inventory scores were higher in the digital phenotyping arm. There was no correlation between self-reported and objective metrics of app use. Qualitative results highlighted the importance of habit formation in sustained app use. Conclusions: The results suggest that digital phenotyping app recommendation is feasible and may increase engagement. This approach is generalizable to other apps beyond the 4 apps selected for use in this pilot, and practical for real-world use given that the study was conducted without any compensation or external incentives that may have biased results. Advances in digital phenotyping will likely make this method of app recommendation more personalized and thus of even greater interest. %M 39560976 %R 10.2196/62725 %U https://formative.jmir.org/2024/1/e62725 %U https://doi.org/10.2196/62725 %U http://www.ncbi.nlm.nih.gov/pubmed/39560976 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e52435 %T Effectiveness of the Support From Community Health Workers and Health Care Professionals on the Sustained Use of Wearable Monitoring Devices Among Community-Dwelling Older Adults: Feasibility Randomized Controlled Trial %A Wong,Arkers Kwan Ching %A Bayuo,Jonathan %A Su,Jing Jing %A Wong,Frances Kam Yuet %A Chow,Karen Kit Sum %A Wong,Bonnie Po %A Wong,Siu Man %A Hui,Vivian %+ School of Nursing, Hong Kong Polytechnic University, GH 502, Hung Hom, Hong Kong, China (Hong Kong), 852 34003805, arkers.wong@polyu.edu.hk %K wearable monitoring device %K lay worker %K smartwatch %K older adult %K nurse %K engagement %K attrition %K engagement %K wearable %K user experience %D 2024 %7 18.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The wearable monitoring device (WMD) is emerging as a promising tool for community-dwelling older adults to monitor personal health, enhance awareness of their activities, and promote healthy behaviors. However, the sustained use of WMDs among this population remains a significant challenge. Objective: This study aims to implement an interventional program that promotes and motivates the continued use of WMDs among older adults through a peer and professional support approach. This program will facilitate the integration of WMDs into their daily lives. Methods: This feasibility trial examined the following: (1) the usability of the WMD from the users’ perspectives; (2) the feasibility of the Live With Wearable Monitoring Device program; and (3) the effectiveness of the Live With Wearable Monitoring Device program among community-dwelling older adults. The intervention, based on Self-Determination Theory, involved using the Live With Wearable Monitoring Device program over a 3-month period, with ongoing professional and peer support provided by community health workers, aided by a nurse and social workers. This support included 1 home visit and biweekly communication via WhatsApp. Data were collected at baseline and at 1, 3, and 6 months. Results: A total of 39 participants were enrolled in the intervention group, while 37 participants were in the control group. The recruitment rate was high (76/89, 85%), and the attrition rate was low (8/76, 11%), indicating that the program is feasible for older adults. Participants in the intervention group exhibited higher self-efficacy, lower anxiety levels, and used the smartwatch more frequently, in terms of both days and hours, compared with the control group. A between-group difference was observed in self-efficacy between the intervention and control groups (β=3.31, 95% CI 0.36-6.25, P=.03), with statistically significant higher mean values recorded at all 4 time points. Conclusions: It is clear that merely providing a WMD to older adults does not guarantee its usage, particularly for those unfamiliar with how to utilize its health-related functions in their daily routines. This study implemented a theory-based program aimed at enhancing the ongoing use of WMDs among older adults, suggesting that continuous professional and peer support may significantly influence WMD usage. Trial Registration: ClinicalTrials.gov NCT05269303; https://clinicaltrials.gov/ct2/show/NCT05269303 %M 39556810 %R 10.2196/52435 %U https://www.jmir.org/2024/1/e52435 %U https://doi.org/10.2196/52435 %U http://www.ncbi.nlm.nih.gov/pubmed/39556810 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53768 %T Use of Random Forest to Predict Adherence in an Online Intervention for Depression Using Baseline and Early Usage Data: Model Development and Validation on Retrospective Routine Care Log Data %A Wenger,Franziska %A Allenhof,Caroline %A Schreynemackers,Simon %A Hegerl,Ulrich %A Reich,Hanna %+ Clinic for Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, Frankfurt am Main, 60528, Germany, 49 3412238744, franziska.wenger@deutsche-depressionshilfe.de %K depression %K adherence %K machine learning %K digital interventions %K random forest %K iFightDepression %K iFD %K online intervention %D 2024 %7 15.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Online interventions, such as the iFightDepression (iFD) tool, are increasingly recognized as effective alternatives to traditional face-to-face psychotherapy or pharmacotherapy for treating depression. However, particularly when used outside of study settings, low adherence rates and the resulting diminished benefits of the intervention can limit their effectiveness. Understanding the factors that predict adherence would allow for early, tailored interventions for individuals at risk of nonadherence, thereby enhancing user engagement and optimizing therapeutic outcomes. Objective: This study aims to develop and evaluate a random forest model that predicts adherence to the iFD tool to identify users at risk of noncompletion. The model was based on characteristics collected during baseline and the first week of the intervention in patients with depression. Methods: Log data from 4187 adult patients who registered for the iFD tool between October 1, 2016, and May 5, 2022, and provided informed consent were statistically analyzed. The resulting data set was divided into training (2932/4187, 70%) and test (1255/4187, 30%) sets using a randomly stratified split. The training data set was utilized to train a random forest model aimed at predicting each user’s adherence at baseline, based on the hypothesized predictors: age, self-reported gender, expectations of the intervention, current or previous depression treatments, confirmed diagnosis of depression, baseline 9-item Patient Health Questionnaire (PHQ-9) score, accompanying guide profession, and usage behavior within the first week. After training, the random forest model was evaluated on the test data set to assess its predictive performance. The importance of each variable in predicting adherence was analyzed using mean decrease accuracy, mean decrease Gini, and Shapley Additive Explanations values. Results: Of the 4187 patients evaluated, 1019 (24.34%) were classified as adherent based on our predefined definition. An initial random forest model that relied solely on sociodemographic and clinical predictors collected at baseline did not yield a statistically significant adherence prediction. However, after incorporating each patient’s usage behavior during the first week, we achieved a significant prediction of adherence (P<.001). Within this prediction, the model achieved an accuracy of 0.82 (95% CI 0.79-0.84), an F1-score of 0.53, an area under the curve of 0.83, and a specificity of 0.94 for predicting nonadherent users. The key predictors of adherence included logs, word count on the first workshop’s worksheet, and time spent on the tool, all measured during the first week. Conclusions: Our results highlight that early engagement, particularly usage behavior during the first week of the online intervention, is a far greater predictor of adherence than any sociodemographic or clinical factors. Therefore, analyzing usage behavior within the first week and identifying nonadherers through the algorithm could be beneficial for tailoring interventions aimed at improving user adherence. This could include follow-up calls or face-to-face discussions, optimizing resource utilization in the process. %M 39546342 %R 10.2196/53768 %U https://formative.jmir.org/2024/1/e53768 %U https://doi.org/10.2196/53768 %U http://www.ncbi.nlm.nih.gov/pubmed/39546342 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50963 %T Effectiveness of the Offer of the Smoke Free Smartphone App Compared With No Intervention for Smoking Cessation: Pragmatic Randomized Controlled Trial %A Jackson,Sarah %A Kale,Dimitra %A Beard,Emma %A Perski,Olga %A West,Robert %A Brown,Jamie %+ Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, United Kingdom, 44 2076795634, s.e.jackson@ucl.ac.uk %K randomized controlled trial %K smartphone app %K smoking cessation %K digital intervention %K tobacco %K mobile phone %D 2024 %7 15.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital technologies offer the potential for low-cost, scalable delivery of interventions to promote smoking cessation. Objective: We aimed to evaluate the effectiveness of the offer of Smoke Free—an evidence-informed, widely used app—for smoking cessation versus no support. Methods: In this 2-arm randomized controlled trial, 3143 motivated adult smokers were recruited online between August 2020 and April 2021 and randomized to receive an offer of the Smoke Free app plus follow-up (intervention arm) versus follow-up only (comparator arm). Both groups were shown a brief message at the end of the baseline questionnaire encouraging them to make a quit attempt. The primary outcome was self-reported 6-month continuous abstinence assessed 7 months after randomization. Secondary outcomes included quit attempts in the first month post randomization, 3-month continuous abstinence assessed at 4 months, and 6-month continuous abstinence at 7 months among those who made a quit attempt. The primary analysis was performed on an intention-to-treat (ITT) analysis basis. Sensitivity analyses included (1) restricting the intervention group to those who took up the offer of the app, (2) using complete cases, and (3) using multiple imputation. Results: The effective follow-up rate for 7 months was 41.9%. The primary analysis showed no evidence of a benefit of the intervention on rates of 6-month continuous abstinence (intervention 6.8% vs comparator 7.0%; relative risk 0.97, 95% CI 0.75-1.26). Analyses of all secondary outcomes also showed no evidence of a benefit. Similar results were observed on complete cases and using multiple imputation. When the intervention group was restricted to those who took up the offer of the app (n=395, 25.3%), participants in the intervention group were 80% more likely to report 6-month continuous abstinence (12.7% vs 7.0%; relative risk 1.80, 95% CI 1.30-2.45). Equivalent subgroup analyses produced similar results on the secondary outcomes. These differences persisted after adjustment for key baseline characteristics. Conclusions: Among motivated smokers provided with very brief advice to quit, the offer of the Smoke Free app did not have a detectable benefit for cessation compared with follow-up only. However, the app increased quit rates when smokers randomized to receive the app downloaded it. Trial Registration: ISRCTN ISRCTN85785540; https://www.isrctn.com/ISRCTN85785540 International Registered Report Identifier (IRRID): RR2-https://onlinelibrary.wiley.com/doi/full/10.1111/add.14652 %M 39546331 %R 10.2196/50963 %U https://www.jmir.org/2024/1/e50963 %U https://doi.org/10.2196/50963 %U http://www.ncbi.nlm.nih.gov/pubmed/39546331 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60787 %T Exploration of Features of Mobile Applications for Medication Adherence in Asia: Narrative Review %A Wang,Tzu %A Huang,Yen-Ming %A Chan,Hsun-Yu %+ Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, No.33, Linsen S Rd, Zhongzheng Dist, Taipei City, 100025, Taiwan, 886 33668784, yenming927@ntu.edu.tw %K Asia %K adherence %K application %K feature %K medication %K mobile %D 2024 %7 8.11.2024 %9 Review %J J Med Internet Res %G English %X Background: Medication is crucial for managing chronic diseases, yet adherence rates are often suboptimal. With advanced integration of IT and mobile internet into health care, mobile apps present a substantial opportunity for improving adherence by incorporating personalized educational, behavioral, and organizational strategies. However, determining the most effective features and functionalities for these apps within the specific health care context in Asia remains a challenge. Objective: We aimed to review the existing literature, focusing on Asian countries, to identify the optimal features of mobile apps that can effectively enhance medication adherence within the unique context of Asian societies. Methods: We conducted a narrative review with the SPIDER (sample, phenomenon of interest, design, evaluation, research type) tool. We identified studies on mobile apps for medication adherence from January 2019 to August 2024 on PubMed and Scopus. Key search terms included “Asia,” “chronic disease,” “app,” “application,” “survey,” “experiment,” “questionnaire,” “group,” “medical adherence,” “medication adherence,” “case-control,” “cohort study,” “randomized controlled trial,” “clinical trial,” “observational study,” “qualitative research,” “mixed methods,” and “analysis,” combined using logical operators “OR” and “AND.” The features of mobile apps identified in the studies were evaluated, compared, and summarized based on their disease focuses, developers, target users, features, usability, and use. Results: The study identified 14 mobile apps designed to enhance medication adherence. Of these, 11 were developed by research teams, while 3 were created by commercial companies or hospitals. All the apps incorporated multiple features to support adherence, with reminders being the most common, present in 11 apps. Patient community forums were the least common, appearing in only 1 app. In total, 6 apps provided lifestyle modification functions, offering dietary and exercise recommendations, generating individualized plans, and monitoring progress. In addition, 6 apps featured health data recording and monitoring functions, with 4 allowing users to export and share records with researchers or health care professionals. Many apps included communication features, with 10 enabling feedback from researchers or health care professionals and 7 offering web-based consultation services. Educational content was available in 8 apps, and 7 used motivation strategies to encourage adherence. Six studies showed that mobile apps improved clinical outcomes, such as blood glucose, lipid, and pressure, while reducing adverse events and boosting physical activities. Twelve studies noted positive humanistic effects, including better medication adherence, quality of life, and user satisfaction. Conclusions: This review has identified key components integrated into mobile apps to support medication adherence. However, the lack of government and corporate involvement in their development limits the generalizability of any individual app. Beyond basic reminder functions, features such as multiuser support, feedback mechanisms, web-based consultations, motivational tools, and socialization features hold significant promise for improving medication adherence. Further pragmatic research is necessary to validate the effectiveness of these selected apps in enhancing adherence. %M 39514859 %R 10.2196/60787 %U https://www.jmir.org/2024/1/e60787 %U https://doi.org/10.2196/60787 %U http://www.ncbi.nlm.nih.gov/pubmed/39514859 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e48696 %T Predictors of Engagement in Multiple Modalities of Digital Mental Health Treatments: Longitudinal Study %A Nowels,Molly Aideen %A McDarby,Meghan %A Brody,Lilla %A Kleiman,Evan %A Sagui Henson,Sara %A Castro Sweet,Cynthia %A Kozlov,Elissa %+ Division of Geriatrics and Palliative Medicine, Weill Cornell Medicine, 525 E 68th St, New York, NY, 10065, United States, 1 212 746 4888, mon2007@med.cornell.edu %K digital health %K mental health %K health care benefit %K prediction %K technology %K digital mental health %K employer-based %K teletherapy %K coaching %K utilization %K mobile phone %D 2024 %7 7.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Technology-enhanced mental health platforms may serve as a pathway to accessible and scalable mental health care; specifically, those that leverage stepped care models have the potential to address many barriers to patient care, including low mental health literacy, mental health provider shortages, perceived acceptability of care, and equitable access to evidence-based treatment. Driving meaningful engagement in care through these platforms remains a challenge. Objective: This study aimed to examine predictors of engagement in self-directed digital mental health services offered as part of an employer-based mental health benefit that uses a technology-enabled care platform. Methods: Using a prospective, longitudinal design, we examined usage data from employees who had access to an employer-sponsored mental health care benefit. Participants had access to a digital library of mental health resources, which they could use at any time, including daily exercises, interactive programs, podcasts, and mindfulness exercises. Coaching and teletherapy were also available to. The outcome was engagement with the self-directed digital mental health resources, measured by the number of interactions. Poisson regression models included sociodemographic characteristics, patient activation, mental health literacy, well-being, PHQ-9 and GAD-7 scores at baseline, primary concern for engaging in treatment, and the use of coaching or teletherapy sessions. Results: In total 950 individuals enrolled in the study, with 38% using any self-directed digital mental health resources. Approximately 44% of the sample did not use the app during the study period. Those using both self-directed digital and 1:1 modalities made up about one-quarter of the sample (235/950, 24.7%). Those using only coaching or therapy (170/950, 17.9%) and those using only self-directed digital mental health resources (126/950, 13.3%) make up the rest. At baseline, these groups statistically significantly differed on age, PHQ-9, GAD-7, MHLS, and primary concern. Receipt of coaching and teletherapy was associated with the number of self-directed digital mental health resources interactions in adjusted Poisson regression modeling. Use of any coach visit was associated with 82% (rate ratio [RR] 1.82, 95% CI 1.63-2.03) more self-directed digital mental health resource interactions while use of any teletherapy session was associated with 80% (RR 1.80, 95% CI 1.55-2.07) more digital mental health resources interactions (both P<.001). Each additional year of age was associated with increased digital mental health resources interactions (RR 1.04, 95% CI (1.03-1.05), and women had 23% more self-directed digital resources interactions than men (RR 1.23, 95% CI 1.09-1.39). Conclusions: Our key finding was that the use of coaching or teletherapy was associated with increased self-directed digital mental health resource use. Higher self-directed digital resource engagement among those receiving coaching or therapy may be a result of provider encouragement. On the other hand, when a participant engages with 1 modality in the platform, they may be more likely to begin engaging with others, becoming “super users” of all resources. %R 10.2196/48696 %U https://www.jmir.org/2024/1/e48696 %U https://doi.org/10.2196/48696 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52729 %T Understanding Users’ Engagement in a Provider-Created Mobile App for Training to Advance Hepatitis C Care: Knowledge Assessment Survey Study %A Wegener,Maximilian %A Sims,Katarzyna %A Brooks,Ralph %A Nichols,Lisa %A Sideleau,Robert %A McKay,Sharen %A Villanueva,Merceditas %+ Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, Yale University, 135 College Street, Suite 323, New Haven, CT, 06510, United States, 1 2037857026, maximilian.wegener@yale.edu %K HIV %K HCV %K hepatitis C virus %K interactive digital interventions (IDI) %K education %K mobile application %K user engagement %K training %K awareness %K treatment %K testing %D 2024 %7 1.11.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The World Health Organization and the Centers for Disease Control and Prevention have set ambitious hepatitis C virus (HCV) elimination targets for 2030. Current estimates show that the United States is not on pace to meet elimination targets due to multiple patient, clinic, institutional, and societal level barriers that contribute to HCV testing and treatment gaps. Among these barriers are unawareness of testing and treatment needs, misinformation concerning adverse treatment reactions, need for substance use sobriety, and treatment efficacy. Strategies to improve viral hepatitis education are needed. Objective: We aim to provide a high-quality HCV educational app for patients and health care workers, particularly nonprescriber staff. The app was vetted by health care providers and designed to guide users through the HCV testing and treatment stages in a self-exploratory way to promote engagement and knowledge retention. The app is comprised of five learning modules: (1) Testing for Hep C (hepatitis C), (2) Tests for Hep C Positive Patients, (3) Treatments Available to You, (4) What to Expect During Treatment, and (5) What to Expect After Treatment. Methods: An HCV knowledge assessment survey was administered to providers and patients at the Yale School of Medicine and 11 Connecticut HIV clinics as part of a grant-funded activity. The survey findings and pilot testing feedback guided the app’s design and content development. Data on app usage from November 2019 to November 2022 were analyzed, focusing on user demographics, engagement metrics, and module usage patterns. Results: There were 561 app users; 216 (38.5%) accessed the training modules of which 151 (69.9%) used the app for up to 60 minutes. Of them, 65 (30.1%) users used it for >60 minutes with a median time spent of 5 (IQR 2-8) minutes; the median time between initial accession and last use was 39 (IQR 18-60) days. Users accessed one or more modules and followed a nonsequential pattern of use: module 1: 163 (75.4%) users; module 4: 82 (38%); module 5: 67 (31%); module 3: 49 (22.7%); module 2: 41 (19%). Conclusions: This app, created in an academic setting, is one of a few available in English and Spanish that provides content-vetted HCV education for patients and health care supportive staff. It offers the convenience of on-demand education, allowing users to access crucial information about HCV management and treatment in a self-directed fashion that acknowledges and promotes variable preferences in learning approaches. While app uptake was relatively limited, we propose that future efforts should focus on combined promotion efforts with marketing strategies experts aligned with academic experts. Incorporating ongoing user feedback and integrating personalized reminders and quizzes, will further enhance engagement, supporting the broader public health HCV elimination goals. %M 39486023 %R 10.2196/52729 %U https://formative.jmir.org/2024/1/e52729 %U https://doi.org/10.2196/52729 %U http://www.ncbi.nlm.nih.gov/pubmed/39486023 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57839 %T Evaluating the Impact of a Game (Inner Dragon) on User Engagement Within a Leading Smartphone App for Smoking Cessation: Randomized Controlled Trial %A White,Justin S %A Toussaert,Séverine %A Raiff,Bethany R %A Salem,Marie K %A Chiang,Amy Yunyu %A Crane,David %A Warrender,Edward %A Lyles,Courtney R %A Abroms,Lorien C %A Westmaas,J Lee %A Thrul,Johannes %+ Department of Health Law, Policy and Management, Boston University School of Public Health, Talbot Building - 249W, 715 Albany Street, Boston, MA, 02118, United States, 1 617 358 1916, juswhite@bu.edu %K smoking cessation %K mobile app %K games for health %K gamification %K engagement %K randomized controlled trial %K mobile phone %D 2024 %7 30.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Smartphone apps are a convenient, low-cost approach to delivering smoking cessation support to large numbers of individuals. Yet, the apps are susceptible to low rates of user engagement and retention. Objective: This study aims to test the effects of a new game module (called Inner Dragon) integrated into Smoke Free (23 Limited), a leading smoking cessation app with established efficacy. The primary outcomes measured user engagement with the app. Methods: A 2-arm, parallel-group, randomized controlled trial was conducted in the United States with an 8-week follow-up. Adult individuals who smoked ≥1 cigarettes daily and planned to quit smoking within 7 days were recruited and randomized (N=500), with equal allocation. Both groups received free access to the original Smoke Free app with “core” features of its smoking cessation program (eg, a diary and craving log). The treated group received additional access to the integrated Inner Dragon game that incorporated several game mechanics designed to increase user engagement. User engagement outcomes were the number of unique app sessions, average minutes per session, days with a session, and program adherence. Self-reported and verified smoking abstinence and app satisfaction were also assessed. The main analysis estimated the intention-to-treat effect of access to Inner Dragon on each outcome. Further analyses assessed effect modification by participant characteristics and the association of intensity of game use with program adherence and abstinence. Results: Overall, user engagement was greater for treated versus control participants: they had 5.3 more sessions of Smoke Free (mean 29.6, SD 36.5 sessions vs mean 24.3, SD 37.9 sessions; P=.06), 0.8 more minutes per session (mean 6.9, SD 5.4 min vs mean 6.1, SD 5.2 min; P=.047), and 3.4 more days with a session (mean 14.3, SD 15.3 days vs mean 11.9, SD 14.3 days; P=.03). Program adherence, based on the number of times core features of the original Smoke Free app were used, was higher for treated versus control participants (mean 29.4, SD 41.3 times vs mean 22.6, SD 35.6 times; P=.03). Self-reported 7-day and 30-day point-prevalence abstinence and verified 7-day point-prevalence abstinence at 8 weeks did not significantly differ by study group. The mean repeated 1-day prevalence of quitting was higher among the treated group versus the control group (mean 17.3%, SD 25.6 vs mean 12.4%, SD 21.3; P=.01). App satisfaction and the motivation to (stay) quit did not differ by study group. Higher intensity of game use was associated with increased program adherence and self-reported abstinence. Conclusions: Findings suggest that the Inner Dragon game increased user engagement and program adherence. Additional refinements to the game design may clarify whether the game increases abstinence rates. Overall, it is feasible to deploy games and gamification to enhance user engagement in existing smoking cessation interventions. Trial Registration: ClinicalTrials.gov NCT05227027; https://clinicaltrials.gov/study/NCT05227027 %M 39475840 %R 10.2196/57839 %U https://www.jmir.org/2024/1/e57839 %U https://doi.org/10.2196/57839 %U http://www.ncbi.nlm.nih.gov/pubmed/39475840 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e51025 %T Feasibility and Engagement of a Mobile App Preparation Program (Kwit) for Smoking Cessation in an Ecological Context: Quantitative Study %A Bustamante Perez,Luz Adriana %A Romo,Lucia %A Zerhouni,Oulmann %+ Laboratoire EA 4430-Clinique Psychanalyse Developpement, Department of Psychology, University of Paris Nanterre, 200 avenue de la République, Nanterre, 92001, France, 33 783192547, adriana.bustamante93@gmail.com %K smoking cessation %K digital intervention %K behavior change techniques %K attrition rate %K mobile app %K preparation program %K motivation %K quit smoking %K ecological settings %K mobile phone %D 2024 %7 2.10.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health apps can facilitate access to effective treatment and therapeutic information services. However, the real-world effectiveness of mobile apps for smoking cessation and their potential impact in everyday settings remain unclear. Objective: In an ecological context, this study aimed to estimate the engagement rate of a mobile app–based smoking cessation preparation program and its potential impact on users’ willingness, ability, and readiness to quit smoking. Methods: A total of 2331 “organic users” (ie, users who discover and install a mobile app on their own, without any prompts) chose 1 of 2 program versions of the mobile app (Kwit): the basic version or the premium version. Both versions were identical in design, with 4 more evidence-based content items and strategies in the premium version. Outcomes were analyzed based on automated data registered in the app (engagement rate, motivation to quit, motivation type, motivation levels, and satisfaction level). Mann-Whitney and χ2 tests were used to compare the results of both groups. Results: As expected, in the ecological context, a high dropout rate was observed at different moments. A significant difference was observed between the 2 versions (n=2331; χ21=5.4; P=.02), with a proportionally higher engagement rate in the premium version (premium=4.7% vs basic=2%). Likewise, differences were also observed between the 2 groups in terms of reasons to quit (n=2331; χ24=19; P≤.001; V=0.08), motivation type (n=2331; χ27=14.7; P=.04), and motivation level. Users of the app’s premium version more frequently reported “well-being” (23.3% vs 17.9%) and “planning a pregnancy” (7.4% vs 4.4%) as their primary reasons for quitting smoking compared to those with the basic version. Moreover, they reported being more likely to be driven in the smoking cessation process by intrinsic motivation (premium=28% vs basic=20.4%), as well as feeling significantly more willing (z score=156,055; P≤.001; Cohen d=0.15), able (z score=172,905; P=.04; Cohen d=0.09), and ready (z score=166,390; P=.005; Cohen d=0.12) to stop smoking than users who had the basic version before completion of the preparation program. Among participants who finished each version of the program (premium: 9/189, 4.8%; basic: 47/2142, 2.19%), significant improvements in motivation levels were observed in both groups, although in different areas for each group (willingness levels for the premium group and ability for the basic group). Conclusions: These results suggest that even in ecological contexts where engagement rates are meager, the Kwit preparation program can address ambivalence by increasing willingness to change, self-confidence, and readiness to quit among its users, especially those who feel less able to do so. Further development and evaluations are needed to better understand determinants for regular mobile health apps. %M 39357053 %R 10.2196/51025 %U https://mhealth.jmir.org/2024/1/e51025 %U https://doi.org/10.2196/51025 %U http://www.ncbi.nlm.nih.gov/pubmed/39357053 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53819 %T A Web-Based Antiretroviral Therapy Adherence Intervention (Thrive With Me) in a Community-Recruited Sample of Sexual Minority Men Living With HIV: Results of a Randomized Controlled Study %A Horvath,Keith J %A Lammert,Sara %A Erickson,Darin %A Amico,K Rivet %A Talan,Ali J %A Shalhav,Ore %A Sun,Christina J %A Rendina,H Jonathon %+ Department of Psychology, San Diego State University, 6363 Alvarado Court, Suite 250, San Deigo, CA, 92120, United States, 1 6196943346, khorvath@sdsu.edu %K HIV %K antiretroviral therapy %K ART %K mobile health %K mHealth %K intervention %K men who have sex with men %D 2024 %7 30.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Most new HIV infections are attributed to male-to-male sexual contact in the United States. However, only two-thirds of sexual minority men living with HIV achieve an undetectable viral load (UVL). We tested a web-based antiretroviral therapy adherence intervention called Thrive with Me (TWM) with core features that included medication self-monitoring and feedback, HIV and antiretroviral therapy information, and a peer-to-peer exchange. Objective: We assessed the efficacy of TWM on HIV UVL among adult (aged ≥18 years) sexual minority men. Moreover, we assessed the impact of overall engagement and engagement with specific intervention features on HIV UVL. Methods: In total, 401 sexual minority men (mean age 39.1, SD 10.8 y; 230/384, 59.9% African American) in New York City were recruited between October 2016 and December 2019 and randomized to receive TWM (intervention) or a weekly email newsletter (control) for 5 months. Computerized assessments occurred at baseline and months 5, 11, and 17. The primary outcome was a dichotomous measure of HIV UVL (≤20 copies/μL). Generalized estimating equations with robust SEs were used to assess the effect of the TWM intervention on HIV UVL over the follow-up period in an unadjusted model and a model adjusted for baseline differences and then stratified by baseline recent drug use urinalysis. In secondary analyses, generalized linear models were used to estimate risk differences in the association of overall engagement with TWM (the sum of the number of days participants accessed ≥1 screen of the TWM intervention out of a possible 150 days) and engagement with specific TWM components on HIV UVL throughout the 17-month intervention period. Results: Participant retention was 88.5% (355/401; month 5), 81.8% (328/401; month 11), and 80.3% (322/401; month 17). No consistent differences in HIV UVL were found between those randomized to receive TWM or the control at the 5- (difference-in-differences [DD]=–7.8, 95% CI –21.1 to 5.5), 11- (DD=–13.9, 95% CI –27.7 to 0.04), or 17-month (DD=–8.2, 95% CI –22.0 to 5.7) time points, or when stratified by baseline recent drug use. However, those TWM-assigned participants with high overall levels of engagement (in the upper 25th percentile) were more likely to have an HIV UVL at the end of the 5-month active intervention period compared to those with low engagement (below the 75th percentile; risk difference=17.8, 95% CI 2.5-33.0) or no engagement (risk difference=19.4, 95% CI 3.3-35.5) in the intervention. Moreover, high engagement with the peer-to-peer exchange was associated with HIV UVL over time in unadjusted models. Conclusions: TWM did not have overall impacts on HIV UVL; however, it may assist some sexual minority men who are highly engaged with this web-based intervention in achieving HIV viral suppression. Trial Registration: ClinicalTrials.gov NCT02704208; https://clinicaltrials.gov/study/NCT02704208 %M 39348677 %R 10.2196/53819 %U https://www.jmir.org/2024/1/e53819 %U https://doi.org/10.2196/53819 %U http://www.ncbi.nlm.nih.gov/pubmed/39348677 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e62790 %T Evolutionary Trends in the Adoption, Adaptation, and Abandonment of Mobile Health Technologies: Viewpoint Based on 25 Years of Research %A Portz,Jennifer %A Moore,Susan %A Bull,Sheana %+ Division of General Internal Medicine, School of Medicine, University of Colorado, Mailstop B119, Aurora, CO, 80045, United States, 1 303 724 8856, jennifer.portz@CUAnschutz.edu %K technology adoption %K mobile health %K SMS text messaging %K mobile apps %K wearables %K social media %D 2024 %7 27.9.2024 %9 Viewpoint %J J Med Internet Res %G English %X Over the past quarter-century, mobile health (mHealth) technologies have experienced significant changes in adoption rates, adaptation strategies, and instances of abandonment. Understanding the underlying factors driving these trends is essential for optimizing the design, implementation, and sustainability of interventions using these technologies. The evolution of mHealth adoption has followed a progressive trajectory, starting with cautious exploration and later accelerating due to technological advancements, increased smartphone penetration, and growing acceptance of digital health solutions by both health care providers and patients. However, alongside widespread adoption, challenges related to usability, interoperability, privacy concerns, and socioeconomic disparities have emerged, necessitating ongoing adaptation efforts. While many mHealth initiatives have successfully adapted to address these challenges, technology abandonment remains common, often due to unsustainable business models, inadequate user engagement, and insufficient evidence of effectiveness. This paper utilizes the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework to examine the interplay between the academic and industry sectors in patterns of adoption, adaptation, and abandonment, using 3 major mHealth innovations as examples: health-related SMS text messaging, mobile apps and wearables, and social media for health communication. Health SMS text messaging has demonstrated significant potential as a tool for health promotion, disease management, and patient engagement. The proliferation of mobile apps and devices has facilitated a shift from in-person and in-clinic practices to mobile- and wearable-centric solutions, encompassing everything from simple activity trackers to advanced health monitoring devices. Social media, initially characterized by basic text-based interactions in chat rooms and online forums, underwent a paradigm shift with the emergence of platforms such as MySpace and Facebook. This transition ushered in an era of mass communication through social media. The rise of microblogging and visually focused platforms such as Twitter(now X), Instagram, Snapchat, and TikTok, along with the integration of live streaming and augmented reality features, exemplifies the ongoing innovation within the social media landscape. Over the past 25 years, there have been remarkable strides in the adoption and adaptation of mHealth technologies, driven by technological innovation and a growing recognition of their potential to revolutionize health care delivery. Each mobile technology uniquely enhances public health and health care by catering to different user needs. SMS text messaging offers wide accessibility and proven effectiveness, while mobile apps and wearables provide comprehensive functionalities for more in-depth health management. Social media platforms amplify these efforts with their vast reach and community-building potential, making it essential to select the right tool for specific health interventions to maximize impact and engagement. Nevertheless, continued efforts are needed to address persistent challenges and mitigate instances of abandonment, ensuring that mHealth interventions reach their full potential in improving health outcomes and advancing equitable access to care. %M 39331463 %R 10.2196/62790 %U https://www.jmir.org/2024/1/e62790 %U https://doi.org/10.2196/62790 %U http://www.ncbi.nlm.nih.gov/pubmed/39331463 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50508 %T User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review %A Eaton,Cyd %A Vallejo,Natalie %A McDonald,Xiomara %A Wu,Jasmine %A Rodríguez,Rosa %A Muthusamy,Nishanth %A Mathioudakis,Nestoras %A Riekert,Kristin A %+ Johns Hopkins School of Medicine, 5200 Eastern Avenue, Baltimore, MD, 21224, United States, 1 6673066201, ceaton4@jhmi.edu %K mobile health %K mHealth %K digital health %K treatment adherence %K self-management %K user engagement %K chronic health conditions %K mobile phone %D 2024 %7 24.9.2024 %9 Review %J J Med Internet Res %G English %X Background: There are numerous mobile health (mHealth) interventions for treatment adherence and self-management; yet, little is known about user engagement or interaction with these technologies. Objective: This systematic review aimed to answer the following questions: (1) How is user engagement defined and measured in studies of mHealth interventions to promote adherence to prescribed medical or health regimens or self-management among people living with a health condition? (2) To what degree are patients engaging with these mHealth interventions? (3) What is the association between user engagement with mHealth interventions and adherence or self-management outcomes? (4) How often is user engagement a research end point? Methods: Scientific database (Ovid MEDLINE, Embase, Web of Science, PsycINFO, and CINAHL) search results (2016-2021) were screened for inclusion and exclusion criteria. Data were extracted in a standardized electronic form. No risk-of-bias assessment was conducted because this review aimed to characterize user engagement measurement rather than certainty in primary study results. The results were synthesized descriptively and thematically. Results: A total of 292 studies were included for data extraction. The median number of participants per study was 77 (IQR 34-164). Most of the mHealth interventions were evaluated in nonrandomized studies (157/292, 53.8%), involved people with diabetes (51/292, 17.5%), targeted medication adherence (98/292, 33.6%), and comprised apps (220/292, 75.3%). The principal findings were as follows: (1) >60 unique terms were used to define user engagement; “use” (102/292, 34.9%) and “engagement” (94/292, 32.2%) were the most common; (2) a total of 11 distinct user engagement measurement approaches were identified; the use of objective user log-in data from an app or web portal (160/292, 54.8%) was the most common; (3) although engagement was inconsistently evaluated, most of the studies (99/195, 50.8%) reported >1 level of engagement due to the use of multiple measurement methods or analyses, decreased engagement across time (76/99, 77%), and results and conclusions suggesting that higher engagement was associated with positive adherence or self-management (60/103, 58.3%); and (4) user engagement was a research end point in only 19.2% (56/292) of the studies. Conclusions: The results revealed major limitations in the literature reviewed, including significant variability in how user engagement is defined, a tendency to rely on user log-in data over other measurements, and critical gaps in how user engagement is evaluated (infrequently evaluated over time or in relation to adherence or self-management outcomes and rarely considered a research end point). Recommendations are outlined in response to our findings with the goal of improving research rigor in this area. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022289693; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022289693 %M 39316431 %R 10.2196/50508 %U https://www.jmir.org/2024/1/e50508 %U https://doi.org/10.2196/50508 %U http://www.ncbi.nlm.nih.gov/pubmed/39316431 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e55324 %T Design and Psychometric Evaluation of Nurses’ Mobile Health Device Acceptance Scale (NMHDA-Scale): Application of the Expectation-Confirmation Theory %A Mirabootalebi,Narjes %A Meidani,Zahra %A Akbari,Hossein %A Rangraz Jeddi,Fatemeh %A Tagharrobi,Zahra %A Swoboda,Walter %A Holl,Felix %+ Trauma Nursing Research Centre, Kashan University of Medical Sciences, Isfahan Province, Kashan, 2C74+M7F, Iran, 98 9131613899, Tagharrobi_z@kaums.ac.ir %K mobile health %K acceptance %K psychometric evaluation %K nursing %K Expectation-Confirmation Theory %K smartphone %D 2024 %7 17.9.2024 %9 Original Paper %J JMIR Hum Factors %G English %X Background: The use of mobile tools in nursing care is indispensable. Given the importance of nurses’ acceptance of these tools in delivering effective care, this issue requires greater attention. Objective: This study aims to design the Mobile Health Tool Acceptance Scale for Nurses based on the Expectation-Confirmation Theory and to evaluate it psychometrically. Methods: Using a Waltz-based approach grounded in existing tools and the constructs of the Expectation-Confirmation Theory, the initial version of the scale was designed and evaluated for face and content validity. Construct validity was examined through exploratory factor analysis, concurrent validity, and known-group comparison. Reliability was assessed using measures of internal consistency and stability. Results: The initial version of the scale consisted of 33 items. During the qualitative and quantitative content validity stage, 1 item was added and 1 item was removed. Exploratory factor analysis, retaining 33 items, identified 5 factors that explained 70.53% of the variance. A significant positive correlation was found between the scores of the designed tool and nurses’ attitudes toward using mobile-based apps in nursing care (r=0.655, P<.001). The intraclass correlation coefficient, Cronbach α, and ω coefficient were 0.938, 0.953, and 0.907, respectively. Conclusions: The 33-item scale developed is a valid and reliable instrument for measuring nurses’ acceptance of mobile health tools. %M 39288375 %R 10.2196/55324 %U https://humanfactors.jmir.org/2024/1/e55324 %U https://doi.org/10.2196/55324 %U http://www.ncbi.nlm.nih.gov/pubmed/39288375 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 7 %N %P e53793 %T Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning %A Singh,Ankita %A Chakraborty,Shayok %A He,Zhe %A Pang,Yuanying %A Zhang,Shenghao %A Subedi,Ronast %A Lustria,Mia Liza %A Charness,Neil %A Boot,Walter %K domain adaptation %K adherence %K cognitive training %K deep neural networks %K early detection of cognitive decline %D 2024 %7 16.9.2024 %9 %J JMIR Aging %G English %X Background: Cognitive impairment and dementia pose a significant challenge to the aging population, impacting the well-being, quality of life, and autonomy of affected individuals. As the population ages, this will place enormous strain on health care and economic systems. While computerized cognitive training programs have demonstrated some promise in addressing cognitive decline, adherence to these interventions can be challenging. Objective: The objective of this study is to improve the accuracy of predicting adherence lapses to ultimately develop tailored adherence support systems to promote engagement with cognitive training among older adults. Methods: Data from 2 previously conducted cognitive training intervention studies were used to forecast adherence levels among older participants. Deep convolutional neural networks were used to leverage their feature learning capabilities and predict adherence patterns based on past behavior. Domain adaptation (DA) was used to address the challenge of limited training data for each participant, by using data from other participants with similar playing patterns. Time series data were converted into image format using Gramian angular fields, to facilitate clustering of participants during DA. To the best of our knowledge, this is the first effort to use DA techniques to predict older adults’ daily adherence to cognitive training programs. Results: Our results demonstrated the promise and potential of deep neural networks and DA for predicting adherence lapses. In all 3 studies, using 2 independent datasets, DA consistently produced the best accuracy values. Conclusions: Our findings highlight that deep learning and DA techniques can aid in the development of adherence support systems for computerized cognitive training, as well as for other interventions aimed at improving health, cognition, and well-being. These techniques can improve engagement and maximize the benefits of such interventions, ultimately enhancing the quality of life of individuals at risk for cognitive impairments. This research informs the development of more effective interventions, benefiting individuals and society by improving conditions associated with aging. %R 10.2196/53793 %U https://aging.jmir.org/2024/1/e53793 %U https://doi.org/10.2196/53793 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 11 %N %P e54116 %T Usage, Attitudes, Facilitators, and Barriers Toward Digital Health Technologies in Musculoskeletal Care: Survey Among Primary Care Physiotherapists in Norway %A Martinsen,Lars %A Østerås,Nina %A Moseng,Tuva %A Tveter,Anne Therese %+ Center for Treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Diakonveien 12, Oslo, 0370, Norway, 47 22451500, lars.martinsen@diakonsyk.no %K physiotherapy %K physiotherapist %K physiotherapists %K mHealth %K mobile health %K app %K apps %K application %K applications %K digital health %K smartphone %K smartphones %K ehealth %K telemedicine %K tele-medicine %K family medicine %K primary care %K primary health care %K musculoskeletal %K musculoskeletal care %K muscle %K skeleton %K musculoskeletal disorders %K MSD %K MSDs %K internet survey %K internet surveys %K online survey %K online surveys %K web-based survey %K web-based surveys %K survey %K surveys %K mobile phone %D 2024 %7 16.9.2024 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: Work burden increases for physiotherapists in the primary health care sector as the prevalence of musculoskeletal disorders (MSDs) increases. Digital health technologies (DHTs) are proposed as a viable solution to secure the sustainability of the health care system and have shown promising results in a range of conditions. However, little is known about use of DHTs among physiotherapists in the primary health care sector in Norway. Objective: This study aimed to investigate the use of and attitudes toward DHTs among physiotherapists treating patients with MSDs in primary care, and potential facilitators or barriers for adopting DHTs in clinical practice. Methods: An author-developed web-based questionnaire was distributed to physiotherapists in all Norwegian municipalities in March 2023. The questionnaire included items regarding use of technologies, attitudes, suitability, and factors influencing adoption of DHT. Suitability and agreement on statements were scored on an 11-point numeric rating scale (0=very unsuitable or strongly disagree, 10=very suitable or strongly agree). Differences across employment sites and users versus nonusers of DHT were analyzed using the χ2 test, Fisher exact test, Student t test, and Mann-Whitney U test. Results: Approximately 5000 physiotherapists were invited to participate, of which 6.8% (338) completed the questionnaire. A total of 46.2% (156/338) offered DHTs in their practice, of which 53.2% (83/156) used it on a weekly basis, mostly telephone consultations (105/156, 67.3%). A higher proportion of physiotherapists in private practice offered DHT compared with those employed by municipalities (95/170, 55.9% vs 61/168, 36.3%; P<.001). A majority (272/335, 81.2%) were positive about recommending DHTs to their patients. Suitability of DHTs in physiotherapy was rated an average of 6 (SD 2.1). Apps for smartphones or tablets were rated most suitable (mean rating 6.8, SD 2.4). The most frequently reported advantages were flexibility in how physiotherapy is offered (278/338, 82.3%) and reduced travel time for the patient (235/338, 70%). The highest rated disadvantages were limited scope for physical examination (252/338, 74.6%) and difficulty in building rapport with the patient (227/338, 67.2%). The main facilitators and barriers included a functioning (median rating 10, IQR 8-10) or lack of functioning (median rating 9, IQR 8-10) internet connection, respectively. Lack of training in DHTs was prominent regarding evaluation, diagnosing, and treatment (median rating 0, IQR 0-2), with minor, but significant, differences between nonusers and users (median rating 0, IQR 0-1 vs median rating 1, IQR 0-4); P<.001). Conclusions: Physiotherapists in Norwegian primary care treating patients with MSDs are positive about using DHTs, and almost 50% (156/338) have adopted them in clinical practice. Concerns are related to lack of a physical examination and technical aspects. Training in the use of DHTs should be addressed in implementation processes. %M 39283661 %R 10.2196/54116 %U https://rehab.jmir.org/2024/1/e54116 %U https://doi.org/10.2196/54116 %U http://www.ncbi.nlm.nih.gov/pubmed/39283661 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e59444 %T Predicting Long-Term Engagement in mHealth Apps: Comparative Study of Engagement Indices %A Tak,Yae Won %A Lee,Jong Won %A Kim,Junetae %A Lee,Yura %+ Department of Information Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea, 82 2 3010 1498, haepary@amc.seoul.kr %K treatment adherence and compliance %K patient compliance %K medication adherence %K digital therapeutics %K engagement index %K mobile phone %D 2024 %7 9.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital health care apps, including digital therapeutics, have the potential to increase accessibility and improve patient engagement by overcoming the limitations of traditional facility-based medical treatments. However, there are no established tools capable of quantitatively measuring long-term engagement at present. Objective: This study aimed to evaluate an existing engagement index (EI) in a commercial health management app for long-term use and compare it with a newly developed EI. Methods: Participants were recruited from cancer survivors enrolled in a randomized controlled trial that evaluated the impact of mobile health apps on recovery. Of these patients, 240 were included in the study and randomly assigned to the Noom app (Noom Inc). The newly developed EI was compared with the existing EI, and a long-term use analysis was conducted. Furthermore, the new EI was evaluated based on adapted measurements from the Web Matrix Visitor Index, focusing on click depth, recency, and loyalty indices. Results: The newly developed EI model outperformed the existing EI model in terms of predicting EI of a 6- to 9-month period based on the EI of a 3- to 6-month period. The existing model had a mean squared error of 0.096, a root mean squared error of 0.310, and an R2 of 0.053. Meanwhile, the newly developed EI models showed improved performance, with the best one achieving a mean squared error of 0.025, root mean squared error of 0.157, and R2 of 0.610. The existing EI exhibited significant associations: the click depth index (hazard ratio [HR] 0.49, 95% CI 0.29-0.84; P<.001) and loyalty index (HR 0.17, 95% CI 0.09-0.31; P<.001) were significantly associated with improved survival, whereas the recency index exhibited no significant association (HR 1.30, 95% CI 1.70-2.42; P=.41). Among the new EI models, the EI with a menu combination of menus available in the app’s free version yielded the most promising result. Furthermore, it exhibited significant associations with the loyalty index (HR 0.32, 95% CI 0.16-0.62; P<.001) and the recency index (HR 0.47, 95% CI 0.30-0.75; P<.001). Conclusions: The newly developed EI model outperformed the existing model in terms of the prediction of long-term user engagement and compliance in a mobile health app context. We emphasized the importance of log data and suggested avenues for future research to address the subjectivity of the EI and incorporate a broader range of indices for comprehensive evaluation. %M 39250192 %R 10.2196/59444 %U https://www.jmir.org/2024/1/e59444 %U https://doi.org/10.2196/59444 %U http://www.ncbi.nlm.nih.gov/pubmed/39250192 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57827 %T Value of Engagement in Digital Health Technology Research: Evidence Across 6 Unique Cohort Studies %A Goodday,Sarah M %A Karlin,Emma %A Brooks,Alexa %A Chapman,Carol %A Harry,Christiana %A Lugo,Nelly %A Peabody,Shannon %A Rangwala,Shazia %A Swanson,Ella %A Tempero,Jonell %A Yang,Robin %A Karlin,Daniel R %A Rabinowicz,Ron %A Malkin,David %A Travis,Simon %A Walsh,Alissa %A Hirten,Robert P %A Sands,Bruce E %A Bettegowda,Chetan %A Holdhoff,Matthias %A Wollett,Jessica %A Szajna,Kelly %A Dirmeyer,Kallan %A Dodd,Anna %A Hutchinson,Shawn %A Ramotar,Stephanie %A Grant,Robert C %A Boch,Adrien %A Wildman,Mackenzie %A Friend,Stephen H %+ 4YouandMe, 2901 3rd Ave, Seattle, WA, 98121, United States, 1 (206) 928 8243, sarah@4youandme.org %K wearables %K wearable %K mHealth %K mobile health %K app %K apps %K application %K applications %K engagement %K adherence %K retention %K participatory medicine %K participatory %K DHT %K digital health technology %K DHTs %K digital health technologies %K digital health %K mobile phone %D 2024 %7 3.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Wearable digital health technologies and mobile apps (personal digital health technologies [DHTs]) hold great promise for transforming health research and care. However, engagement in personal DHT research is poor. Objective: The objective of this paper is to describe how participant engagement techniques and different study designs affect participant adherence, retention, and overall engagement in research involving personal DHTs. Methods: Quantitative and qualitative analysis of engagement factors are reported across 6 unique personal DHT research studies that adopted aspects of a participant-centric design. Study populations included (1) frontline health care workers; (2) a conception, pregnant, and postpartum population; (3) individuals with Crohn disease; (4) individuals with pancreatic cancer; (5) individuals with central nervous system tumors; and (6) families with a Li-Fraumeni syndrome affected member. All included studies involved the use of a study smartphone app that collected both daily and intermittent passive and active tasks, as well as using multiple wearable devices including smartwatches, smart rings, and smart scales. All studies included a variety of participant-centric engagement strategies centered on working with participants as co-designers and regular check-in phone calls to provide support over study participation. Overall retention, probability of staying in the study, and median adherence to study activities are reported. Results: The median proportion of participants retained in the study across the 6 studies was 77.2% (IQR 72.6%-88%). The probability of staying in the study stayed above 80% for all studies during the first month of study participation and stayed above 50% for the entire active study period across all studies. Median adherence to study activities varied by study population. Severely ill cancer populations and postpartum mothers showed the lowest adherence to personal DHT research tasks, largely the result of physical, mental, and situational barriers. Except for the cancer and postpartum populations, median adherences for the Oura smart ring, Garmin, and Apple smartwatches were over 80% and 90%, respectively. Median adherence to the scheduled check-in calls was high across all but one cohort (50%, IQR 20%-75%: low-engagement cohort). Median adherence to study-related activities in this low-engagement cohort was lower than in all other included studies. Conclusions: Participant-centric engagement strategies aid in participant retention and maintain good adherence in some populations. Primary barriers to engagement were participant burden (task fatigue and inconvenience), physical, mental, and situational barriers (unable to complete tasks), and low perceived benefit (lack of understanding of the value of personal DHTs). More population-specific tailoring of personal DHT designs is needed so that these new tools can be perceived as personally valuable to the end user. %M 39226552 %R 10.2196/57827 %U https://www.jmir.org/2024/1/e57827 %U https://doi.org/10.2196/57827 %U http://www.ncbi.nlm.nih.gov/pubmed/39226552 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 7 %N %P e57172 %T Exploring Acceptability, Barriers, and Facilitators for Digital Health in Dermatology: Qualitative Focus Groups With Dermatologists, Nurses, and Patients %A Reinders,Patrick %A Augustin,Matthias %A Fleyder,Anastasia %A Otten,Marina %+ Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf (UKE), Martinistraße 52, Hamburg, 20246, Germany, 49 40 7410 ext 24723, m.otten@uke.de %K digitalization %K digital health interventions %K UTAUT %K unified theory of acceptance and use of technology %K barriers and facilitators %K dermatology %K qualitative research %K focus groups %K mobile phone %D 2024 %7 3.9.2024 %9 Original Paper %J JMIR Dermatol %G English %X Background: Although several digital health interventions (DHIs) have shown promise in the care of skin diseases their uptake in Germany has been limited. To fully understand the reasons for the low uptake, an in-depth analysis of patients’ and health care providers’ barriers and facilitators in dermatology is needed. Objective: The objective of this study was to explore and compare attitudes, acceptability, barriers, and facilitators of patients, dermatologists, and nurses toward DHIs in dermatology. Methods: We conducted 6 web-based focus groups each with patients (n=34), dermatologists (n=30), and nurses (n=30) using a semistructured interview guide with short descriptions of DHIs described in the literature. A content analysis was performed using deductive constructs, following the unified theory of acceptance and use of technology framework, and inductive categories. Results: Patients identified many positive performance expectancies, such as reduced travel times and improvement in follow-up appointments. Dermatologists also stated positive effects (eg, promotion of standardized care), but also negative implications of health care digitalization (eg, increased workload). All stakeholders reported that a DHI should bring additional value to all stakeholders. A lack of digital competence among patients was identified as the major barrier to adoption by all 3 groups. Nurses and dermatologists want apps that are easy to use and easy to implement into their daily routines. Trust in selected institutions, colleagues, and physicians was identified as a facilitator. Patients reported their dependence on the dermatologists’ acceptance. All groups expressed concerns about data privacy risks and dermatologists stated insecurities toward data privacy laws. Conclusions: To ensure successful digitalization in dermatology, apps should be user-friendly, adapted to users’ skill levels, and beneficial for all stakeholders. The incorporation of dermatologists’ perspectives is especially important as their acceptance may impact use among patients and nurses. DHIs should ensure and be transparent about data privacy. The found barriers and facilitators can be used for implementation strategies. %M 39226097 %R 10.2196/57172 %U https://derma.jmir.org/2024/1/e57172 %U https://doi.org/10.2196/57172 %U http://www.ncbi.nlm.nih.gov/pubmed/39226097 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58735 %T Framework Development for Reducing Attrition in Digital Dietary Interventions: Systematic Review and Thematic Synthesis %A Wang,Jian %A Mahe,Jinli %A Huo,Yujia %A Huang,Weiyuan %A Liu,Xinru %A Zhao,Yang %A Huang,Junjie %A Shi,Feng %A Li,Zhihui %A Jiang,Dou %A Li,Yilong %A Perceval,Garon %A Zhao,Lindu %A Zhang,Lin %+ Suzhou Industrial Park Monash Research Institute of Science and Technology, Monash University, Room 805, 8th Floor, Building 2, Sangtian Island Science and Technology Innovation Park, No. 1, Huayun Road, Suzhou, China, 86 13426423807, lin.zhang2@monash.edu %K thematic synthesis %K attrition rate %K dropout %K behavior change theory %K digital dietary intervention %K digital health %K mHealth %K eHealth %K mobile apps %K email %D 2024 %7 27.8.2024 %9 Review %J J Med Internet Res %G English %X Background: Dietary behaviors significantly influence health outcomes across populations. Unhealthy diets are linked to serious diseases and substantial economic burdens, contributing to approximately 11 million deaths and significant disability-adjusted life years annually. Digital dietary interventions offer accessible solutions to improve dietary behaviors. However, attrition, defined as participant dropout before intervention completion, is a major challenge, with rates as high as 75%-99%. High attrition compromises intervention validity and reliability and exacerbates health disparities, highlighting the need to understand and address its causes. Objective: This study systematically reviews the literature on attrition in digital dietary interventions to identify the underlying causes, propose potential solutions, and integrate these findings with behavior theory concepts to develop a comprehensive theoretical framework. This framework aims to elucidate the behavioral mechanisms behind attrition and guide the design and implementation of more effective digital dietary interventions, ultimately reducing attrition rates and mitigating health inequalities. Methods: We conducted a systematic review, meta-analysis, and thematic synthesis. A comprehensive search across 7 electronic databases (PubMed, MEDLINE, Embase, CENTRAL, Web of Science, CINAHL Plus, and Academic Search Complete) was performed for studies published between 2013 and 2023. Eligibility criteria included original research exploring attrition in digital dietary interventions. Data extraction focused on study characteristics, sample demographics, attrition rates, reasons for attrition, and potential solutions. We followed ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and used RStudio (Posit) for meta-analysis and NVivo for thematic synthesis. Results: Out of the 442 identified studies, 21 met the inclusion criteria. The meta-analysis showed mean attrition rates of 35% for control groups, 38% for intervention groups, and 40% for observational studies, with high heterogeneity (I²=94%-99%) indicating diverse influencing factors. Thematic synthesis identified 15 interconnected themes that align with behavior theory concepts. Based on these themes, the force-resource model was developed to explore the underlying causes of attrition and guide the design and implementation of future interventions from a behavior theory perspective. Conclusions: High attrition rates are a significant issue in digital dietary interventions. The developed framework conceptualizes attrition through the interaction between the driving force system and the supporting resource system, providing a nuanced understanding of participant attrition, summarized as insufficient motivation and inadequate or poorly matched resources. It underscores the critical necessity for digital dietary interventions to balance motivational components with available resources dynamically. Key recommendations include user-friendly design, behavior-factor activation, literacy training, force-resource matching, social support, personalized adaptation, and dynamic follow-up. Expanding these strategies to a population level can enhance digital health equity. Further empirical validation of the framework is necessary, alongside the development of behavior theory–guided guidelines for digital dietary interventions. Trial Registration: PROSPERO CRD42024512902; https://tinyurl.com/3rjt2df9 %M 39190910 %R 10.2196/58735 %U https://www.jmir.org/2024/1/e58735 %U https://doi.org/10.2196/58735 %U http://www.ncbi.nlm.nih.gov/pubmed/39190910 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e51972 %T Patients’ Expectations of Doctors’ Clinical Competencies in the Digital Health Care Era: Qualitative Semistructured Interview Study Among Patients %A Zainal,Humairah %A Hui,Xin Xiao %A Thumboo,Julian %A Fong,Warren %A Yong,Fong Kok %+ Health Services Research Unit, Singapore General Hospital, 10 Hospital Boulevard, Singapore, 168582, Singapore, 65 6908 8949, humairah.zainal@sgh.com.sg %K digital health %K clinical competence %K patient engagement %K qualitative research %K Singapore %K mobile phone %D 2024 %7 27.8.2024 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Digital technologies have impacted health care delivery globally, and are increasingly being deployed in clinical practice. However, there is limited research on patients’ expectations of doctors’ clinical competencies when using digital health care technologies (DHTs) in medical care. Understanding these expectations can reveal competency gaps, enhance patient confidence, and contribute to digital innovation initiatives. Objective: This study explores patients’ perceptions of doctors’ use of DHTs in clinical care. Using Singapore as a case study, it examines patients’ expectations regarding doctors’ communication, diagnosis, and treatment skills when using telemedicine, health apps, wearable devices, electronic health records, and artificial intelligence. Methods: Findings were drawn from individual semistructured interviews with patients from outpatient clinics. Participants were recruited using purposive sampling. Data were analyzed qualitatively using thematic analysis. Results: Twenty-five participants from different backgrounds and with various chronic conditions participated in the study. They expected doctors to be adept in handling medical data from apps and wearable devices. For telemedicine, participants expected a level of assessment of their medical conditions akin to in-person consultations. In addition, they valued doctors recognizing when a physical examination was necessary. Interestingly, eye contact was appreciated but deemed nonessential by participants across all age bands when electronic health records were used, as they valued the doctor’s efficiency more than eye contact. Nonetheless, participants emphasized the need for empathy throughout the clinical encounter regardless of DHT use. Furthermore, younger participants had a greater expectation for DHT use among doctors compared to older ones, who preferred DHTs as a complement rather than a replacement for clinical skills. The former expected doctors to be knowledgeable about the algorithms, principles, and purposes of DHTs such as artificial intelligence technologies to better assist them in diagnosis and treatment. Conclusions: By identifying patients’ expectations of doctors amid increasing health care digitalization, this study highlights that while basic clinical skills remain crucial in the digital age, the role of clinicians needs to evolve with the introduction of DHTs. It has also provided insights into how DHTs can be integrated effectively into clinical settings, aligning with patients’ expectations and preferences. Overall, the findings offer a framework for high-income countries to harness DHTs in enhancing health care delivery in the digital era. %M 39190915 %R 10.2196/51972 %U https://humanfactors.jmir.org/2024/1/e51972 %U https://doi.org/10.2196/51972 %U http://www.ncbi.nlm.nih.gov/pubmed/39190915 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e49868 %T Barriers and Facilitators to the Implementation of Digital Health Services for People With Musculoskeletal Conditions in the Primary Health Care Setting: Systematic Review %A van Tilburg,Mark Leendert %A Spin,Ivar %A Pisters,Martijn F %A Staal,J Bart %A Ostelo,Raymond WJG %A van der Velde,Miriam %A Veenhof,Cindy %A Kloek,Corelien JJ %+ Innovation of Movement Care Research Group, Research Centre for Healthy and Sustainable Living, HU University of Applied Sciences Utrecht, Heidelberglaan 7, Utrecht, 3584 CS, Netherlands, 31 618302750, Mark.vantilburg@hu.nl %K eHealth %K primary health care %K musculoskeletal problems %K implementation science %K systematic review %K mobile phone %D 2024 %7 27.8.2024 %9 Review %J J Med Internet Res %G English %X Background: In recent years, the effectiveness and cost-effectiveness of digital health services for people with musculoskeletal conditions have increasingly been studied and show potential. Despite the potential of digital health services, their use in primary care is lagging. A thorough implementation is needed, including the development of implementation strategies that potentially improve the use of digital health services in primary care. The first step in designing implementation strategies that fit the local context is to gain insight into determinants that influence implementation for patients and health care professionals. Until now, no systematic overview has existed of barriers and facilitators influencing the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Objective: This systematic literature review aims to identify barriers and facilitators to the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Methods: PubMed, Embase, and CINAHL were searched for eligible qualitative and mixed methods studies up to March 2024. Methodological quality of the qualitative component of the included studies was assessed with the Mixed Methods Appraisal Tool. A framework synthesis of barriers and facilitators to implementation was conducted using the Consolidated Framework for Implementation Research (CFIR). All identified CFIR constructs were given a reliability rating (high, medium, or low) to assess the consistency of reporting across each construct. Results: Overall, 35 studies were included in the qualitative synthesis. Methodological quality was high in 34 studies and medium in 1 study. Barriers (–) of and facilitators (+) to implementation were identified in all 5 CFIR domains: “digital health characteristics” (ie, commercial neutral [+], privacy and safety [–], specificity [+], and good usability [+]), “outer setting” (ie, acceptance by stakeholders [+], lack of health care guidelines [–], and external financial incentives [–]), “inner setting” (ie, change of treatment routines [+ and –], information incongruence (–), and support from colleagues [+]), “characteristics of the healthcare professionals” (ie, health care professionals’ acceptance [+ and –] and job satisfaction [+ and –]), and the “implementation process” (involvement [+] and justification and delegation [–]). All identified constructs and subconstructs of the CFIR had a high reliability rating. Some identified determinants that influence implementation may be facilitators in certain cases, whereas in others, they may be barriers. Conclusions: Barriers and facilitators were identified across all 5 CFIR domains, suggesting that the implementation process can be complex and requires implementation strategies across all CFIR domains. Stakeholders, including digital health intervention developers, health care professionals, health care organizations, health policy makers, health care funders, and researchers, can consider the identified barriers and facilitators to design tailored implementation strategies after prioritization has been carried out in their local context. %M 39190440 %R 10.2196/49868 %U https://www.jmir.org/2024/1/e49868 %U https://doi.org/10.2196/49868 %U http://www.ncbi.nlm.nih.gov/pubmed/39190440 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50275 %T Investigating Best Practices for Ecological Momentary Assessment: Nationwide Factorial Experiment %A Businelle,Michael S %A Hébert,Emily T %A Shi,Dingjing %A Benson,Lizbeth %A Kezbers,Krista M %A Tonkin,Sarah %A Piper,Megan E %A Qian,Tianchen %+ TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 655 Research Parkway, Suite 400, Oklahoma City, OK, 73104, United States, 1 405 271 8001 ext 50460, michael-businelle@ouhsc.edu %K ecological momentary assessment %K mobile health %K smartphone %K compliance %K ambulatory assessment %K adherence %K experience sampling %K mobile phone %K mHealth %K real-time data %K behavior %K dynamic behavioral processes %K self-report %K factorial design %D 2024 %7 12.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Ecological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants’ behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no “gold standard” for EMA study design to promote compliance. Objective: The purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs. Methods: Participants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1—number of questions per EMA survey (15 vs 25); factor 2—number of EMAs per day (2 vs 4); factor 3—EMA prompting schedule (random vs fixed times); factor 4—payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5—EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined. Results: Participants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance. Conclusions: Study results have broad implications for developing best practices guidelines for future studies that use EMA methodologies. Trial Registration: ClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228 %M 39133915 %R 10.2196/50275 %U https://www.jmir.org/2024/1/e50275 %U https://doi.org/10.2196/50275 %U http://www.ncbi.nlm.nih.gov/pubmed/39133915 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e47116 %T The Impact of a Gamified Intervention on Daily Steps in Real-Life Conditions: Retrospective Analysis of 4800 Individuals %A Mazéas,Alexandre %A Forestier,Cyril %A Harel,Guillaume %A Duclos,Martine %A Chalabaev,Aïna %+ Laboratoire Sport et Environnement Social (SENS), Université Grenoble Alpes, 1741 Rue de la Piscine, Grenoble, 38000, France, 33 476635081, alexandre.mazeas@univ-grenoble-alpes.fr %K behavior change %K daily steps %K exercise %K gamification %K intervention %K mHealth %K mobile health %K mobile phone %K physical activity %K real world data %K retrospective %K self-determination theory %K step %K steps %D 2024 %7 12.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital interventions integrating gamification features hold promise to promote daily steps. However, results regarding the effectiveness of this type of intervention are heterogeneous and not yet confirmed in real-life contexts. Objective: This study aims to examine the effectiveness of a gamified intervention and its potential moderators in a large sample using real-world data. Specifically, we tested (1) whether a gamified intervention enhanced daily steps during the intervention and follow-up periods compared to baseline, (2) whether this enhancement was higher in participants in the intervention than in nonparticipants, and (3) what participant characteristics or intervention parameters moderated the effect of the program. Methods: Data from 4819 individuals who registered for a mobile health Kiplin program between 2019 and 2022 were retrospectively analyzed. In this intervention, participants could take part in one or several games in which their daily step count was tracked, allowing individuals to play with their overall activity. Nonparticipants were people who registered for the program but did not take part in the intervention and were considered as a control group. Daily step counts were measured via accelerometers embedded in either commercial wearables or smartphones of the participants. Exposure to the intervention, the intervention content, and participants’ characteristics were included in multilevel models to test the study objectives. Results: Participants in the intervention group demonstrated a significantly greater increase in mean daily steps from baseline than nonparticipants (P<.001). However, intervention effectiveness depended on participants’ initial physical activity. The daily steps of participants with <7500 baseline daily steps significantly improved from baseline both during the Kiplin intervention (+3291 daily steps) and the follow-up period (+945 daily steps), whereas participants with a higher baseline had no improvement or significant decreases in daily steps after the intervention. Age (P<.001) and exposure (P<.001) positively moderated the intervention effect. Conclusions: In real-world settings and among a large sample, the Kiplin intervention was significantly effective in increasing the daily steps of participants from baseline during intervention and follow-up periods compared to nonparticipants. Interestingly, responses to the intervention differed based on participants’ initial steps, with the existence of a plateau effect. Drawing on the insights of self-determination theory, we can assume that the effect of gamification could depend of the initial motivation and activity of participants. %M 39133533 %R 10.2196/47116 %U https://www.jmir.org/2024/1/e47116 %U https://doi.org/10.2196/47116 %U http://www.ncbi.nlm.nih.gov/pubmed/39133533 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e53355 %T Efficacy of a Web-Based Home Blood Pressure Monitoring Program in Improving Predialysis Blood Pressure Control Among Patients Undergoing Hemodialysis: Randomized Controlled Trial %A Chen,Tingting %A Zhao,Wenbo %A Pei,Qianqian %A Chen,Yanru %A Yin,Jinmei %A Zhang,Min %A Wang,Cheng %A Zheng,Jing %K hemodialysis %K hypertension %K home blood pressure monitoring %K eHealth %K randomized controlled trial %D 2024 %7 9.8.2024 %9 %J JMIR Mhealth Uhealth %G English %X Background: Hypertension is highly prevalent among patients undergoing hemodialysis, with a significant proportion experiencing poorly controlled blood pressure (BP). Digital BP management in this population has been underused. Objective: This study aimed to explore the efficacy of a web-based home BP monitoring (HBPM) program in improving predialysis BP control and enhancing knowledge, perception, and adherence to HBPM among patients with hypertension undergoing hemodialysis. Methods: A multicenter, open-label, randomized controlled trial was conducted at 2 hemodialysis units. Patients were randomly allocated in a 1:1 ratio to either the web-based HBPM program as the intervention group or to usual care as the control group over a 6-month period. The primary outcomes were the predialysis BP control rate, defined as less than 140/90 mm Hg, and the predialysis systolic and diastolic BP, assessed from baseline to the 6-month follow-up. Secondary outcomes included patient knowledge, perception, and adherence to HBPM, evaluated using the HBPM Knowledge Questionnaire, HBPM Perception Scale, and HBPM Adherence Scale, respectively. A generalized estimating equations analysis was used to analyze the primary outcomes in the intention-to-treat analysis. Results: Of the 165 patients enrolled in the program (n=84, 50.9% in the web-based HBPM group and n=81, 49.1% in the control group), 145 (87.9%) completed the follow-up assessment. During the follow-up period, 11 instances of hypotension occurred in 9 patients in the web-based HBPM group, compared to 15 instances in 14 patients in the control group. The predialysis BP control rate increased from 30% (25/84) to 48% (40/84) in the web-based HBPM group after the 6-month intervention, whereas in the control group, it decreased from 37% (30/81) to 25% (20/81; χ22=16.82, P<.001; odds ratio 5.11, 95% CI 2.14-12.23, P<.001). The web-based HBPM group demonstrated a significant reduction after the 6-month intervention in the predialysis systolic BP (t163=2.46, P=.02; β=−6.09, 95 % CI −10.94 to −1.24, P=.01) and the predialysis diastolic BP (t163=3.20, P=.002; β=−4.93, 95% CI −7.93 to −1.93, P=.001). Scores on the HBPM Knowledge Questionnaire (t163=−9.18, P<.001), HBPM Perception Scale (t163=−10.65, P<.001), and HBPM Adherence Scale (t163=−8.04, P<.001) were significantly higher after 6 months of intervention. Conclusions: The implementation of a web-based HBPM program can enhance predialysis BP control and the knowledge, perception, and adherence to HBPM among patients undergoing hemodialysis. This web-based HBPM program should be promoted in appropriate clinical settings. Trial Registration: China Clinical Trial Registration Center ChiCTR2100051535; https://www.chictr.org.cn/showproj.html?proj=133286 %R 10.2196/53355 %U https://mhealth.jmir.org/2024/1/e53355 %U https://doi.org/10.2196/53355 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e57082 %T Application of an Adapted Health Action Process Approach Model to Predict Engagement With a Digital Mental Health Website: Cross-Sectional Study %A Rouvere,Julien %A Blanchard,Brittany E %A Johnson,Morgan %A Griffith Fillipo,Isabell %A Mosser,Brittany %A Romanelli,Meghan %A Nguyen,Theresa %A Rushton,Kevin %A Marion,John %A Althoff,Tim %A Areán,Patricia A %A Pullmann,Michael D %+ Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, 1959 NE Pacific Street, Box 356560, Seattle, WA, 98195-6560, United States, 1 206 221 5498, rouvere@uw.edu %K Health Action Process Approach (HAPA) %K digital health %K health behavior %K Mental Health America (MHA) %K digital mental health engagement %K mental health website %D 2024 %7 7.8.2024 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Digital Mental Health (DMH) tools are an effective, readily accessible, and affordable form of mental health support. However, sustained engagement with DMH is suboptimal, with limited research on DMH engagement. The Health Action Process Approach (HAPA) is an empirically supported theory of health behavior adoption and maintenance. Whether this model also explains DMH tool engagement remains unknown. Objective: This study examined whether an adapted HAPA model predicted engagement with DMH via a self-guided website. Methods: Visitors to the Mental Health America (MHA) website were invited to complete a brief survey measuring HAPA constructs. This cross-sectional study tested the adapted HAPA model with data collected using voluntary response sampling from 16,078 sessions (15,619 unique IP addresses from United States residents) on the MHA website from October 2021 through February 2022. Model fit was examined via structural equation modeling in predicting two engagement outcomes: (1) choice to engage with DMH (ie, spending 3 or more seconds on an MHA page, excluding screening pages) and (2) level of engagement (ie, time spent on MHA pages and number of pages visited, both excluding screening pages). Results: Participants chose to engage with the MHA website in 94.3% (15,161/16,078) of the sessions. Perceived need (β=.66; P<.001), outcome expectancies (β=.49; P<.001), self-efficacy (β=.44; P<.001), and perceived risk (β=.17-.18; P<.001) significantly predicted intention, and intention (β=.77; P<.001) significantly predicted planning. Planning was not significantly associated with choice to engage (β=.03; P=.18). Within participants who chose to engage, the association between planning with level of engagement was statistically significant (β=.12; P<.001). Model fit indices for both engagement outcomes were poor, with the adapted HAPA model accounting for only 0.1% and 1.4% of the variance in choice to engage and level of engagement, respectively. Conclusions: Our data suggest that the HAPA model did not predict engagement with DMH via a self-guided website. More research is needed to identify appropriate theoretical frameworks and practical strategies (eg, digital design) to optimize DMH tool engagement. %M 39110965 %R 10.2196/57082 %U https://humanfactors.jmir.org/2024/1/e57082 %U https://doi.org/10.2196/57082 %U http://www.ncbi.nlm.nih.gov/pubmed/39110965 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e49403 %T Exploring the Experiences of Community-Dwelling Older Adults on Using Wearable Monitoring Devices With Regular Support From Community Health Workers, Nurses, and Social Workers: Qualitative Descriptive Study %A Wong,Arkers Kwan Ching %A Bayuo,Jonathan %A Su,Jing Jing %A Chow,Karen Kit Sum %A Wong,Siu Man %A Wong,Bonnie Po %A Lee,Athena Yin Lam %A Wong,Frances Kam Yuet %+ School of Nursing, The Hong Kong Polytechnic University, GH 502, Hung Hom, Kowloon, China (Hong Kong), 852 34003805, arkers.wong@polyu.edu.hk %K community-dwelling older adults %K focus group %K wearable monitoring devices %K mobile phone %D 2024 %7 7.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The use of wearable monitoring devices (WMDs), such as smartwatches, is advancing support and care for community-dwelling older adults across the globe. Despite existing evidence of the importance of WMDs in preventing problems and promoting health, significant concerns remain about the decline in use after a period of time, which warrant an understanding of how older adults experience the devices. Objective: This study aims to explore and describe the experiences of community-dwelling older adults after receiving our interventional program, which included the use of a smartwatch with support from a community health workers, nurses, and social workers, including the challenges that they experienced while using the device, the perceived benefits, and strategies to promote their sustained use of the device. Methods: We used a qualitative descriptive approach in this study. Older adults who had taken part in an interventional study involving the use of smartwatches and who were receiving regular health and social support were invited to participate in focus group discussions at the end of the trial. Purposive sampling was used to recruit potential participants. Older adults who agreed to participate were assigned to focus groups based on their community. The focus group discussions were facilitated and moderated by 2 members of the research team. All discussions were recorded and transcribed verbatim. We used the constant comparison analytical approach to analyze the focus group data. Results: A total of 22 participants assigned to 6 focus groups participated in the study. The experiences of community-dwelling older adults emerged as (1) challenges associated with the use of WMDs, (2) the perceived benefits of using the WMDs, and (3) strategies to promote the use of WMDs. In addition, the findings also demonstrate a hierarchical pattern of health-seeking behaviors by older adults: seeking assistance first from older adult volunteers, then from social workers, and finally from nurses. Conclusions: Ongoing use of the WMDs is potentially possible, but it is important to ensure the availability of technical support, maintain active professional follow-ups by nurses and social workers, and include older adult volunteers to support other older adults in such programs. %M 39110493 %R 10.2196/49403 %U https://www.jmir.org/2024/1/e49403 %U https://doi.org/10.2196/49403 %U http://www.ncbi.nlm.nih.gov/pubmed/39110493 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e55123 %T The Effectiveness of Medical Adherence Mobile Health Solutions for Individuals With Epilepsy: Protocol for a Systematic Review %A Keikhosrokiani,Pantea %A Polus,Manria %A Guardado Medina,Sharon %A Isomursu,Minna %+ Faculty of Information Technology and Electrical Engineering, University of Oulu, Pentti Kaiteran katu 1, Oulu, 90570, Finland, 358 0504410809, pantea.keikhosrokiani@oulu.fi %K digital care pathway %K epilepsy %K mHealth %K mobile health %K effectiveness %K systematic review %K management %K medical adherence %K patient outcomes %K digital health %K design %K eHealth solutions %K health care professionals %D 2024 %7 6.8.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Epilepsy requires continuous management and treatment to optimize patient outcomes. The advancement of digital health has led to the development of various mobile health (mHealth) tools designed to enhance treatment adherence among individuals with epilepsy. These solutions offer crucial support through features such as reminders, educational resources, personalized feedback, assistance with managing costs, shared decision-making, and access to supportive communities. To design effective medication adherence mHealth solutions, it is essential to evaluate the effectiveness of existing mHealth tools, understand the unique circumstances of different patients, and identify the roles of health care professionals within the digital care pathway. Existing studies on epilepsy primarily focus on self-management, whereas the effectiveness and usability of medical adherence mHealth solutions often remain overlooked. Furthermore, the involvement of health care professionals in digital care pathways for epilepsy as well as the impact of adherence mHealth solutions on the patient experience have not been adequately explored. Objective: This study aims to assess the effectiveness of current mHealth solutions designed to improve medical adherence among patients with epilepsy. Furthermore, the study will examine the experiences of patients using mHealth solutions for maintaining medical adherence in epilepsy care. Finally, this review intends to determine the roles of health care professionals within mHealth systems aimed at supporting adherence to medication among patients with epilepsy. Methods: A systematic literature review has been selected as the appropriate method to address the research questions, adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The inclusion and exclusion criteria have been carefully selected, and both qualitative and quantitative analyses will be used to analyze the results. The expected results will mainly focus on the comparison, classification, and analysis of the effectiveness of current medical adherence mHealth tools. Moreover, the patient experiences using available medical adherence mHealth tools for epilepsy will be assessed. Finally, the role of health care professionals in the epilepsy digital care pathway will be explored, with emphasis on medical adherence. Results: The initial search, full-text screening, and data extraction have been carried out. Thirty-three papers were included in the final stage of the review. The study is expected to be completed by October 2024. Conclusions: To enhance the digital care pathway for epilepsy, a medical adherence mHealth solution should be personalized, manage medications, include an alarm system, track seizures, support consultations, and offer updated treatment plans. This study aims to understand how findings from the research questions can improve mHealth solutions for individuals with epilepsy. Insights from this research on the effectiveness of current mHealth adherence solutions will provide guidance for developing future mHealth systems, making them more efficient and effective in managing epilepsy. Trial Registration: PROSPERO CRD4202347400; https://tinyurl.com/48mfx22e International Registered Report Identifier (IRRID): DERR1-10.2196/55123 %M 39106484 %R 10.2196/55123 %U https://www.researchprotocols.org/2024/1/e55123 %U https://doi.org/10.2196/55123 %U http://www.ncbi.nlm.nih.gov/pubmed/39106484 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e56758 %T Acceptability and Engagement of a Smartphone-Delivered Interpretation Bias Intervention in a Sample of Black and Latinx Adults: Open Trial %A Ferguson,IreLee %A George,Grace %A Narine,Kevin O %A Turner,Amari %A McGhee,Zelda %A Bajwa,Harris %A Hart,Frances G %A Carter,Sierra %A Beard,Courtney %+ Department of Psychiatry, McLean Hospital/Harvard Medical School, 115 Mill St, Belmont, MA, 02478, United States, 1 617 855 3557, cbeard@mclean.harvard.edu %K interpretation bias %K anxiety %K depression %K Black %K Latinx %K smartphone %K mobile phone %D 2024 %7 31.7.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: Access to evidence-based interventions is urgently required, especially for individuals of minoritized identities who experience unique barriers to mental health care. Digital mental health interventions have the potential to increase accessibility. Previous pilot studies testing HabitWorks, a smartphone app providing an interpretation bias intervention, have found strong engagement and adherence for HabitWorks; however, previous trials’ samples consisted of predominantly non-Hispanic, White individuals. Objective: This study conducted an open trial of HabitWorks in a community sample of adults who identified as Black, Hispanic or Latinx, or both. This study aims to test safety, acceptability, and engagement with the HabitWorks app for Black and Latinx adults. Methods: Black, Hispanic or Latinx adults (mean age 32.83, SD 11.06 y; 22/31, 71% women) who endorsed symptoms of anxiety or depression were asked to complete interpretation modification exercises via HabitWorks 3 times per week for 1 month. Interpretation bias and anxiety and depression symptoms were assessed at baseline and posttreatment assessments. Participants completed qualitative interviews to assess overall perceptions of HabitWorks. Results: Of the 31 participants that downloaded the app, 27 (87%) used HabitWorks all 4 weeks. On average, participants completed 15.74 (SD 7.43) exercises out of the 12 prescribed, demonstrating high engagement. Acceptability ratings met all a priori benchmarks except for relevancy. Qualitative interviews also demonstrated high acceptability and few negative experiences. Significant improvements were found in interpretation style (t30=2.29; P<.001), with a large effect size (Cohen d=1.53); anxiety symptoms (t30=2.29; P=.03), with a small effect size (Cohen d=0.41); and depression symptoms (t30=3.065; P=.005), with a medium effect size (Cohen d=0.55). Conclusions: This study adds to the literature evaluating digital mental health interventions in Black and Latinx adults. Preliminary results further support a future controlled trial testing the effectiveness of HabitWorks as an intervention. %M 39083330 %R 10.2196/56758 %U https://mental.jmir.org/2024/1/e56758 %U https://doi.org/10.2196/56758 %U http://www.ncbi.nlm.nih.gov/pubmed/39083330 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e48964 %T The Acceptability, Engagement, and Feasibility of Mental Health Apps for Marginalized and Underserved Young People: Systematic Review and Qualitative Study %A Bear,Holly Alice %A Ayala Nunes,Lara %A Ramos,Giovanni %A Manchanda,Tanya %A Fernandes,Blossom %A Chabursky,Sophia %A Walper,Sabine %A Watkins,Edward %A Fazel,Mina %+ Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, United Kingdom, 44 01865 6182, holly.bear@psych.ox.ac.uk %K adolescent mental health %K marginalized groups %K smartphone apps %K engagement %K implementation science %K mobile app %K smartphone %K mobile health %K mHealth %K mental health %K challenges %K acceptability %K young %K effectiveness %K mobile phone %D 2024 %7 30.7.2024 %9 Review %J J Med Internet Res %G English %X Background: Smartphone apps may provide an opportunity to deliver mental health resources and interventions in a scalable and cost-effective manner. However, young people from marginalized and underserved groups face numerous and unique challenges to accessing, engaging with, and benefiting from these apps. Objective: This study aims to better understand the acceptability (ie, perceived usefulness and satisfaction with an app) and feasibility (ie, the extent to which an app was successfully used) of mental health apps for underserved young people. A secondary aim was to establish whether adaptations can be made to increase the accessibility and inclusivity of apps for these groups. Methods: We conducted 2 sequential studies, consisting of a systematic literature review of mental health apps for underserved populations followed by a qualitative study with underserved young male participants (n=20; age: mean 19). Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, an electronic search of 5 databases was conducted in 2021. The search yielded 18,687 results, of which 14 articles met the eligibility criteria. Results: The included studies comprised a range of groups, including those affected by homelessness, having physical health conditions, living in low- and middle-income countries, and those with sexual and gender minority identities. Establishing and maintaining user engagement was a pervasive challenge across mental health apps and populations, and dropout was a reported problem among nearly all the included studies. Positive subjective reports of usability, satisfaction, and acceptability were insufficient to determine users’ objective engagement. Conclusions: Despite the significant amount of funding directed to the development of mental health apps, juxtaposed with only limited empirical evidence to support their effectiveness, few apps have been deliberately developed or adapted to meet the heterogeneous needs of marginalized and underserved young people. Before mental health apps are scaled up, a greater understanding is needed of the types of services that more at-risk young people and those in limited-resource settings prefer (eg, standard vs digital) followed by more rigorous and consistent demonstrations of acceptability, effectiveness, and cost-effectiveness. Adopting an iterative participatory approach by involving young people in the development and evaluation process is an essential step in enhancing the adoption of any intervention, including apps, in “real-world” settings and will support future implementation and sustainability efforts to ensure that marginalized and underserved groups are reached. Trial Registration: PROSPERO CRD42021254241; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=254241 %M 39078699 %R 10.2196/48964 %U https://www.jmir.org/2024/1/e48964 %U https://doi.org/10.2196/48964 %U http://www.ncbi.nlm.nih.gov/pubmed/39078699 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55366 %T eHealth-Integrated Psychosocial and Physical Interventions for Chronic Pain in Older Adults: Scoping Review %A De Lucia,Annalisa %A Perlini,Cinzia %A Chiarotto,Alessandro %A Pachera,Sara %A Pasini,Ilenia %A Del Piccolo,Lidia %A Donisi,Valeria %+ Section of Clinical Psychology, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Piazzale Ludovico Antonio Scuro 10, Verona, 37134, Italy, 39 0458124038, cinzia.perlini@univr.it %K chronic pain %K older adults %K eHealth %K scoping review %K psychological intervention %K physical intervention %K multimodal intervention %K biopsychosocial model for chronic pain %K self-management %K mobile phone %D 2024 %7 29.7.2024 %9 Review %J J Med Internet Res %G English %X Background: Chronic noncancer pain (CNCP) is highly present among older adults, affecting their physical, psychological, and social functioning. A biopsychosocial multimodal approach to CNCP management is currently extensively suggested by international clinical practice guidelines. Recently, the growing development and application of eHealth within pain management has yielded encouraging results in terms of effectiveness and feasibility; however, its use among the older population remains underexamined. Objective: The overall aim of this scoping review was to systematically map existing literature about eHealth multimodal interventions (including both physical and psychosocial components) targeting older adults with CNCP. Methods: This review adhered to the JBI methodology, a protocol was a priori registered as a preprint on the medRxiv platform, and the results were reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Four electronic databases (PubMed, Cochrane Central Register of Controlled Trials, Web of Science, and PsycINFO) were systematically searched for relevant articles. Studies were included if they reported on multimodal interventions (including both physical and psychosocial components) delivered through any eHealth modality to an older population with any type of CNCP. Two reviewers selected the studies: first by screening titles and abstracts and second by screening full-text articles. The quality of the included studies was evaluated using the Quality Assessment Tool for Studies with Diverse Designs. The results of the studies were summarized narratively. Results: A total of 9 studies (n=6, 67% published between 2021 and 2023) with quality rated as medium to high were included, of which 7 (78%) were randomized controlled trials (n=5, 71% were pilot and feasibility studies). All the included studies evaluated self-management interventions, most of them (n=7, 78%) specifically designed for older adults. The participants were aged between 65 and 75 years on average (mean 68.5, SD 3.5 y) and had been diagnosed with different types of CNCP (eg, osteoarthritis and chronic low back pain). Most of the included studies (5/9, 56%) involved the use of multiple eHealth modalities, with a higher use of web-based programs and video consulting. Only 1 (11%) of the 9 studies involved a virtual reality–based intervention. The evaluated interventions showed signs of effectiveness in the targeted biopsychosocial outcomes, and the participants’ engagement and ratings of satisfaction were generally positive. However, several research gaps were identified and discussed. Conclusions: Overall, of late, there has been a growing interest in the potential that eHealth multimodal interventions offer in terms of improving pain, physical, and psychosocial outcomes in older adults with CNCP. However, existing literature on this topic still seems scarce and highly heterogeneous, with few proper randomized controlled trials, precluding robust conclusions. Several gaps emerged in terms of the older population considered and the lack of evaluation of comorbidities. International Registered Report Identifier (IRRID): RR2-10.1101/2023.07.27.23293235 %M 39073865 %R 10.2196/55366 %U https://www.jmir.org/2024/1/e55366 %U https://doi.org/10.2196/55366 %U http://www.ncbi.nlm.nih.gov/pubmed/39073865 %0 Journal Article %@ 2291-5222 %I %V 12 %N %P e49393 %T The Impact of User Engagement With Exposure Components on Posttraumatic Stress Symptoms in an mHealth Mobile App: Secondary Analysis of a Randomized Controlled Trial %A Davis,C Adrian %A Miller,Madeleine %A McLean,Carmen P %K posttraumatic stress disorder %K PTSD %K mHealth apps %K user engagement %K mHealth interventions %K digital interventions %K veterans %D 2024 %7 18.7.2024 %9 %J JMIR Mhealth Uhealth %G English %X Background: Mobile mental health apps are a cost-effective option for managing mental health problems, such as posttraumatic stress disorder (PTSD). The efficacy of mobile health (mHealth) apps depends on engagement with the app, but few studies have examined how users engage with different features of mHealth apps for PTSD. Objective: This study aims to examine the relationship between app engagement indices and PTSD symptom reduction using data from an unblinded pilot randomized controlled trial of “Renew” (Vertical Design), an exposure-based app for PTSD with and without coaching support. Because exposure is an effective approach for treating PTSD, we expected that engagement with exposure activities would be positively related to symptom reduction, over and above overall app usage. Methods: Participants were veterans (N=69) with clinically significant PTSD symptoms who were recruited online using Facebook advertisements and invited to use the Renew app as often as they wanted over a 6-week period. Participants completed screening and assessments online but provided informed consent, toured the app, and completed feedback interviews via telephone. We assessed users’ self-reported PTSD symptoms before and after a 6-week intervention period and collected app usage data using a research-instrumented dashboard. To examine overall app engagement, we used data on the total time spent in the app, the number of log-in days, and the number of points that the user gained in the app. To examine engagement with exposure components, we used data on total time spent completing exposure activities (both in vivo and imaginal), the number of in vivo exposure activities completed, and the number of characters written in response to imaginal exposure prompts. We used hierarchical regression analyses to test the effect of engagement indices on change in PTSD symptoms. Results: Usage varied widely. Participants spent an average of 166.09 (SD 156.52) minutes using Renew, over an average of 14.7 (SD 10.71) mean log-in days. Engagement with the exposure components of the app was positively associated with PTSD symptom reduction (F6,62=2.31; P=.04). Moreover, this relationship remained significant when controlling for overall engagement with the app (ΔF3,62=4.42; P=.007). The number of characters written during imaginal exposure (β=.37; P=.009) and the amount of time spent completing exposure activities (β=.36; P=.03) were significant contributors to the model. Conclusions: To our knowledge, this is the first study to show a relationship between symptom improvement and engagement with the active therapeutic components of an mHealth app (ie, exposure) for PTSD. This relationship held when controlling for overall app use, which suggests that it was engagement with exposure, specifically, that was associated with symptom change. Future work to identify ways of promoting greater engagement with self-guided exposure may help improve the effectiveness of mHealth apps for PTSD. Trial Registration: ClinicalTrials.gov NCT04155736; https://clinicaltrials.gov/ct2/show/NCT04155736 %R 10.2196/49393 %U https://mhealth.jmir.org/2024/1/e49393 %U https://doi.org/10.2196/49393 %0 Journal Article %@ 2562-7600 %I JMIR Publications %V 7 %N %P e54317 %T Embedding the Use of Patient Multimedia Educational Resources Into Cardiac Acute Care: Prospective Observational Study %A Hutchinson,Anastasia %A Khaw,Damien %A Malmstrom-Zinkel,Annika %A Winter,Natalie %A Dowling,Chantelle %A Botti,Mari %A McDonall,Joanne %+ Centre for Quality and Patient Safety Research—Epworth Partnership, Institute of Health Transformation, Faculty of Health, Deakin University, 185-187 Hoddle St, Richmond, Melbourne, VIC 3121, Australia, 61 0437101349, a.hutchinson@deakin.edu.au %K patient participation %K digital technology %K mHealth %K mobile health %K app %K apps %K digital health %K smartphone %K smartphones %K multimedia %K patient education %K education %K educational %K educate %K patient engagement %K nursing %K cardiac surgery %K cardiology %K cardiac %K cardio %K CCU %K cardiac care unit %K CCC %K complex cardiac care %K coronary care nursing %K nurse %K nurse %K COVID-19 %K SARS-COV-2 %K Coronavirus %K severe acute respiratory syndrome %K Coronavirus infections %K novel Coronavirus %D 2024 %7 18.7.2024 %9 Original Paper %J JMIR Nursing %G English %X Background: Multimedia interventions may play an important role in improving patient care and reducing the time constraints of patient-clinician encounters. The “MyStay Cardiac” multimedia resource is an innovative program designed to be accessed by adult patients undergoing cardiac surgery. Objective: The purpose of this study was to evaluate the uptake of the MyStay Cardiac both during and following the COVID-19 pandemic. Methods: A prospective observational study design was used that involved the evaluation of program usage data available from the digital interface of the multimedia program. Data on usage patterns were analyzed for a 30-month period between August 2020 and January 2023. Usage patterns were compared during and following the lifting of COVID-19 pandemic restrictions. Uptake of the MyStay Cardiac was measured via the type and extent of user activity data captured by the web-based information system. Results: Intensive care unit recovery information was the most accessed information, being viewed in approximately 7 of 10 usage sessions. Ward recovery (n=124/343, 36.2%), goal (n=114/343, 33.2%), and exercise (n=102/343, 29.7%) information were routinely accessed. Most sessions involved users exclusively viewing text-based information (n=210/343, 61.2%). However, in over one-third of sessions (n=132/342, 38.5%), users accessed video information. Most usage sessions occurred during the COVID-19 restriction phase of the study (August 2020-December 2021). Sessions in which video (P=.02, phi=0.124) and audio (P=.006, phi=0.161) media were accessed were significantly more likely to occur in the restriction phase compared to the postrestriction phase. Conclusions: This study found that the use of digital multimedia resources to support patient education was well received and integrated into their practice by cardiac nurses working in acute care during the COVID-19 pandemic. There was a pattern for greater usage of the MyStay Cardiac during the COVID-19 pandemic when access to the health service for nonfrontline, essential workers was limited. %M 39024556 %R 10.2196/54317 %U https://nursing.jmir.org/2024/1/e54317 %U https://doi.org/10.2196/54317 %U http://www.ncbi.nlm.nih.gov/pubmed/39024556 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e51216 %T Deconstructing Fitbit to Specify the Effective Features in Promoting Physical Activity Among Inactive Adults: Pilot Randomized Controlled Trial %A Takano,Keisuke %A Oba,Takeyuki %A Katahira,Kentaro %A Kimura,Kenta %+ Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8566, Japan, 81 298491456, keisuke.takano@aist.go.jp %K wearable activity tracker %K mHealth %K mobile health %K motivation %K physical activity %K lifestyle %K smartwatch %K wearables %K Fitbit %K exercise %K fitness %K BCT %K behavior change technique %K behavior change %K motivation %K adherence %K engagement %D 2024 %7 12.7.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Wearable activity trackers have become key players in mobile health practice as they offer various behavior change techniques (BCTs) to help improve physical activity (PA). Typically, multiple BCTs are implemented simultaneously in a device, making it difficult to identify which BCTs specifically improve PA. Objective: We investigated the effects of BCTs implemented on a smartwatch, the Fitbit, to determine how each technique promoted PA. Methods: This study was a single-blind, pilot randomized controlled trial, in which 70 adults (n=44, 63% women; mean age 40.5, SD 12.56 years; closed user group) were allocated to 1 of 3 BCT conditions: self-monitoring (feedback on participants’ own steps), goal setting (providing daily step goals), and social comparison (displaying daily steps achieved by peers). Each intervention lasted for 4 weeks (fully automated), during which participants wore a Fitbit and responded to day-to-day questionnaires regarding motivation. At pre- and postintervention time points (in-person sessions), levels and readiness for PA as well as different aspects of motivation were assessed. Results: Participants showed excellent adherence (mean valid-wear time of Fitbit=26.43/28 days, 94%), and no dropout was recorded. No significant changes were found in self-reported total PA (dz<0.28, P=.40 for the self-monitoring group, P=.58 for the goal setting group, and P=.19 for the social comparison group). Fitbit-assessed step count during the intervention period was slightly higher in the goal setting and social comparison groups than in the self-monitoring group, although the effects did not reach statistical significance (P=.052 and P=.06). However, more than half (27/46, 59%) of the participants in the precontemplation stage reported progress to a higher stage across the 3 conditions. Additionally, significant increases were detected for several aspects of motivation (ie, integrated and external regulation), and significant group differences were identified for the day-to-day changes in external regulation; that is, the self-monitoring group showed a significantly larger increase in the sense of pressure and tension (as part of external regulation) than the goal setting group (P=.04). Conclusions: Fitbit-implemented BCTs promote readiness and motivation for PA, although their effects on PA levels are marginal. The BCT-specific effects were unclear, but preliminary evidence showed that self-monitoring alone may be perceived demanding. Combining self-monitoring with another BCT (or goal setting, at least) may be important for enhancing continuous engagement in PA. Trial Registration: Open Science Framework; https://osf.io/87qnb/?view_only=f7b72d48bb5044eca4b8ce729f6b403b %M 38996332 %R 10.2196/51216 %U https://mhealth.jmir.org/2024/1/e51216 %U https://doi.org/10.2196/51216 %U http://www.ncbi.nlm.nih.gov/pubmed/38996332 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e55663 %T Effect of a Smartphone App (S-Check) on Actual and Intended Help-Seeking and Motivation to Change Methamphetamine Use Among Adult Consumers of Methamphetamine in Australia: Randomized Waitlist-Controlled Trial %A Siefried,Krista J %A Bascombe,Florence %A Clifford,Brendan %A Liu,Zhixin %A Middleton,Peter %A Kay-Lambkin,Frances %A Freestone,Jack %A Herman,Daniel %A Millard,Michael %A Steele,Maureen %A Acheson,Liam %A Moller,Carl %A Bath,Nicky %A Ezard,Nadine %+ The National Centre for Clinical Research on Emerging Drugs, University of New South Wales, UNSW Randwick Campus, 22/32 King Street, Randwick, 2031, Australia, 61 2 9065 7808, krista.siefried@svha.org.au %K methamphetamine %K smartphone app %K behavior change %K help-seeking %K motivation to change %K mHealth %K mobile health %K app %K apps %K application %K applications %K smartphone %K smartphones %K motivation %K motivational %K RCT %K randomized %K controlled trial %K controlled trials %K drug %K drugs %K substance use %K engagement %K substance abuse %K mobile phone %D 2024 %7 3.7.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Interventions are required that address delays in treatment-seeking and low treatment coverage among people consuming methamphetamine. Objective: We aim to determine whether a self-administered smartphone-based intervention, the “S-Check app” can increase help-seeking and motivation to change methamphetamine use, and determine factors associated with app engagement. Methods: This study is a randomized, 28-day waitlist-controlled trial. Consenting adults residing in Australia who reported using methamphetamine at least once in the last month were eligible to download the app for free from Android or iOS app stores. Those randomized to the intervention group had immediate access to the S-Check app, the control group was wait-listed for 28 days before gaining access, and then all had access until day 56. Actual help-seeking and intention to seek help were assessed by the modified Actual Help Seeking Questionnaire (mAHSQ), modified General Help Seeking Questionnaire, and motivation to change methamphetamine use by the modified readiness ruler. χ2 comparisons of the proportion of positive responses to the mAHSQ, modified General Help Seeking Questionnaire, and modified readiness ruler were conducted between the 2 groups. Logistic regression models compared the odds of actual help-seeking, intention to seek help, and motivation to change at day 28 between the 2 groups. Secondary outcomes were the most commonly accessed features of the app, methamphetamine use, feasibility and acceptability of the app, and associations between S-Check app engagement and participant demographic and methamphetamine use characteristics. Results: In total, 560 participants downloaded the app; 259 (46.3%) completed eConsent and baseline; and 84 (32.4%) provided data on day 28. Participants in the immediate access group were more likely to seek professional help (mAHSQ) at day 28 than those in the control group (n=15, 45.5% vs n=12, 23.5%; χ21=4.42, P=.04). There was no significant difference in the odds of actual help-seeking, intention to seek help, or motivation to change methamphetamine use between the 2 groups on the primary logistic regression analyses, while in the ancillary analyses, the imputed data set showed a significant difference in the odds of seeking professional help between participants in the immediate access group compared to the waitlist control group (adjusted odds ratio 2.64, 95% CI 1.19-5.83, P=.02). For participants not seeking help at baseline, each minute in the app increased the likelihood of seeking professional help by day 28 by 8% (ratio 1.08, 95% CI 1.02-1.22, P=.04). Among the intervention group, a 10-minute increase in app engagement time was associated with a decrease in days of methamphetamine use by 0.4 days (regression coefficient [β] –0.04, P=.02). Conclusions: The S-Check app is a feasible low-resource self-administered intervention for adults in Australia who consume methamphetamine. Study attrition was high and, while common in mobile health interventions, warrants larger studies of the S-Check app. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12619000534189; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377288&isReview=true %M 38959499 %R 10.2196/55663 %U https://mhealth.jmir.org/2024/1/e55663 %U https://doi.org/10.2196/55663 %U http://www.ncbi.nlm.nih.gov/pubmed/38959499 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e57699 %T mHealth-Based Just-in-Time Adaptive Intervention to Improve the Physical Activity Levels of Individuals With Spinal Cord Injury: Protocol for a Randomized Controlled Trial %A Carey,Rachel L %A Le,Ha %A Coffman,Donna L %A Nahum-Shani,Inbal %A Thirumalai,Mohanraj %A Hagen,Cole %A Baehr,Laura A %A Schmidt-Read,Mary %A Lamboy,Marlyn S R %A Kolakowsky-Hayner,Stephanie A %A Marino,Ralph J %A Intille,Stephen S %A Hiremath,Shivayogi V %+ Department of Health and Rehabilitation Sciences, Temple University, Pearson Hall 40, 1800 North Broad Street, Philadelphia, PA, 19121, United States, 1 215 204 0496, Shiv.Hiremath@temple.edu %K spinal cord injury %K physical activity %K just-in-time adaptive intervention %K mobile health %K randomized controlled trial %K microrandomized trial %K wearable sensors %K ecological momentary assessment %K community %K mobile phone %D 2024 %7 28.6.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: The lack of regular physical activity (PA) in individuals with spinal cord injury (SCI) in the United States is an ongoing health crisis. Regular PA and exercise-based interventions have been linked with improved outcomes and healthier lifestyles among those with SCI. Providing people with an accurate estimate of their everyday PA level can promote PA. Furthermore, PA tracking can be combined with mobile health technology such as smartphones and smartwatches to provide a just-in-time adaptive intervention (JITAI) for individuals with SCI as they go about everyday life. A JITAI can prompt an individual to set a PA goal or provide feedback about their PA levels. Objective: The primary aim of this study is to investigate whether minutes of moderate-intensity PA among individuals with SCI can be increased by integrating a JITAI with a web-based PA intervention (WI) program. The WI program is a 14-week web-based PA program widely recommended for individuals with disabilities. A secondary aim is to investigate the benefit of a JITAI on proximal PA, defined as minutes of moderate-intensity PA within 120 minutes of a PA feedback prompt. Methods: Individuals with SCI (N=196) will be randomized to a WI arm or a WI+JITAI arm. Within the WI+JITAI arm, a microrandomized trial will be used to randomize participants several times a day to different tailored feedback and PA recommendations. Participants will take part in the 24-week study from their home environment in the community. The study has three phases: (1) baseline, (2) WI program with or without JITAI, and (3) PA sustainability. Participants will provide survey-based information at the initial meeting and at the end of weeks 2, 8, 16, and 24. Participants will be asked to wear a smartwatch every day for ≥12 hours for the duration of the study. Results: Recruitment and enrollment began in May 2023. Data analysis is expected to be completed within 6 months of finishing participant data collection. Conclusions: The JITAI has the potential to achieve long-term PA performance by delivering tailored, just-in-time feedback based on the person’s actual PA behavior rather than a generic PA recommendation. New insights from this study may guide intervention designers to develop engaging PA interventions for individuals with disability. Trial Registration: ClinicalTrials.gov NCT05317832; https://clinicaltrials.gov/study/NCT05317832 International Registered Report Identifier (IRRID): DERR1-10.2196/57699 %M 38941145 %R 10.2196/57699 %U https://www.researchprotocols.org/2024/1/e57699 %U https://doi.org/10.2196/57699 %U http://www.ncbi.nlm.nih.gov/pubmed/38941145 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 16 %N %P e51662 %T Acceptability of a Digital Adherence Tool Among Patients With Tuberculosis and Tuberculosis Care Providers in Kilimanjaro Region, Tanzania: Mixed Methods Study %A Mtenga,Alan Elias %A Maro,Rehema Anenmose %A Dillip,Angel %A Msoka,Perry %A Emmanuel,Naomi %A Ngowi,Kennedy %A Sumari-de Boer,Marion %+ mHealth Department, Kilimanjaro Clinical Research Institute, KCMC/Kitandu, Longuo st, 2236, Moshi, Moshi, 25116, United Republic of Tanzania, 255 763285424, a.mtenga@kcri.ac.tz %K acceptability %K digital adherence tool %K medication reminder monitors %K patients with tuberculosis %K TB %K adherence %K TB care provider %D 2024 %7 26.6.2024 %9 Original Paper %J Online J Public Health Inform %G English %X Background: The World Health Organization has recommended digital adherence tools (DATs) as a promising intervention to improve antituberculosis drug adherence. However, the acceptability of DATs in resource-limited settings is not adequately studied. Objective: We investigated the acceptability of a DAT among patients with tuberculosis (TB) and TB care providers in Kilimanjaro, Tanzania. Methods: We conducted a convergent parallel mixed methods study among patients with TB and TB care providers participating in our 2-arm cluster randomized trial (REMIND-TB). The trial aimed to investigate whether the evriMED pillbox with reminder cues and adherence feedback effectively improves adherence to anti-TB treatment among patients with TB in Kilimanjaro, Tanzania. We conducted exit and in-depth interviews among patients as well as in-depth interviews among TB care providers in the intervention arm. We conducted a descriptive analysis of the quantitative data from exit interviews. Translated transcripts and memos were organized using NVivo software. We employed inductive and deductive thematic framework analysis, guided by Sekhon’s theoretical framework of acceptability. Results: Out of the 245 patients who completed treatment, 100 (40.8%) were interviewed during exit interviews, and 18 patients and 15 TB care providers were interviewed in-depth. Our findings showed that the DAT was highly accepted: 83% (83/100) expressed satisfaction, 98% (98/100) reported positive experiences with DAT use, 78% (78/100) understood how the intervention works, and 92% (92/100) successfully used the pillbox. Good perceived effectiveness was reported by 84% (84/100) of the participants who noticed improved adherence, and many preferred continuing receiving reminders through SMS text messages, indicating high levels of self-efficacy. Ethical concerns were minimal, as 85 (85%) participants did not worry about remote monitoring. However, some participants felt burdened using DATs; 9 (9%) faced difficulties keeping the device at home, 12 (12%) were not pleased with receiving daily reminder SMS text messages, and 30 (30%) reported challenges related to mobile network connectivity issues. TB care providers accepted the intervention due to its perceived impact on treatment outcomes and behavior change in adherence counseling, and they demonstrated high level of intervention coherence. Conclusions: DATs are highly acceptable in Tanzania. However, some barriers such as TB-related stigma and mobile network connectivity issues may limit acceptance. International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3483-4 %M 38922643 %R 10.2196/51662 %U https://ojphi.jmir.org/2024/1/e51662 %U https://doi.org/10.2196/51662 %U http://www.ncbi.nlm.nih.gov/pubmed/38922643 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52801 %T Feasibility of a 2-Part Substance Use Screener Self-Administered by Patients on Paper: Observational Study %A Kramer,Joanna %A Wilens,Timothy E %A Rao,Vinod %A Villa,Richard %A Yule,Amy M %+ Department of Psychiatry, Boston Medical Center, Crosstown Building 408, 801 Massachusetts Avenue, Boston, MA, 02118, United States, 1 6174141936, amy.yule@bmc.org %K patient reported outcome measures %K patient reported outcomes %K substance use screening %K paper and pencil screening %K screening %K tobacco %K prescription medication %K medication %K substance use %K care %K mental health %K symptoms %D 2024 %7 25.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Measurement-based care in behavioral health uses patient-reported outcome measures (PROMs) to screen for mental health symptoms and substance use and to assess symptom change over time. While PROMs are increasingly being integrated into electronic health record systems and administered electronically, paper-based PROMs continue to be used. It is unclear if it is feasible to administer a PROM on paper when the PROM was initially developed for electronic administration. Objective: This study aimed to examine the feasibility of patient self-administration of a 2-part substance use screener—the Tobacco, Alcohol, Prescription medications, and other Substances (TAPS)—on paper. This screener was originally developed for electronic administration. It begins with a limited number of questions and branches to either skip or reflex to additional questions based on an individual’s responses. In this study, the TAPS was adapted for paper use due to barriers to electronic administration within an urgent care behavioral health clinic at an urban health safety net hospital. Methods: From August 2021 to March 2022, research staff collected deidentified paper TAPS responses and tracked TAPS completion rates and adherence to questionnaire instructions. A retrospective chart review was subsequently conducted to obtain demographic information for the patients who presented to the clinic between August 2021 and March 2022. Since the initial information collected from TAPS responses was deidentified, demographic information was not linked to the individual TAPS screeners that were tracked by research staff. Results: A total of 507 new patients were seen in the clinic with a mean age of 38.7 (SD 16.6) years. In all, 258 (50.9%) patients were male. They were predominantly Black (n=212, 41.8%), White (n=152, 30%), and non-Hispanic or non-Latino (n=403, 79.5%). Most of the patients were publicly insured (n=411, 81.1%). Among these 507 patients, 313 (61.7%) completed the TAPS screener. Of these 313 patients, 76 (24.3%) adhered to the instructions and 237 (75.7%) did not follow the instructions correctly. Of the 237 respondents who did not follow the instructions correctly, 166 (70%) answered more questions and 71 (30%) answered fewer questions than required in TAPS part 2. Among the 237 patients who did not adhere to questionnaire instructions, 44 (18.6%) responded in a way that contradicted their response in part 1 of the screener and ultimately affected their overall TAPS score. Conclusions: It was challenging for patients to adhere to questionnaire instructions when completing a substance use screener on paper that was originally developed for electronic use. When selecting PROMs for measurement-based care, it is important to consider the structure of the questionnaire and how the PROM will be administered to determine if additional support for PROM self-administration needs to be implemented. %M 38916950 %R 10.2196/52801 %U https://formative.jmir.org/2024/1/e52801 %U https://doi.org/10.2196/52801 %U http://www.ncbi.nlm.nih.gov/pubmed/38916950 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e54029 %T Development of an Artificial Intelligence–Based Tailored Mobile Intervention for Nurse Burnout: Single-Arm Trial %A Cho,Aram %A Cha,Chiyoung %A Baek,Gumhee %+ College of Nursing & Graduate Program in System Health Science and Engineering, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, Hellen #202, Seoul, 03760, Republic of Korea, 82 0232772883, chiyoung@ewha.ac.kr %K artificial intelligence %K burnout %K mobile app %K nurses %K nurse %K mHealth %K mobile health %K app %K apps %K applications %K usability %K satisfaction %K effectiveness %K tailored %K mind-body %K meditation %K mindfulness %K ACT %K algorithm %K algorithms %K occupational health %K digital health %K recommender %K optimization %K acceptance and commitment therapy %K job %K worker %K workers %K stress %K employee %K employees %D 2024 %7 21.6.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Nurse burnout leads to an increase in turnover, which is a serious problem in the health care system. Although there is ample evidence of nurse burnout, interventions developed in previous studies were general and did not consider specific burnout dimensions and individual characteristics. Objective: The objectives of this study were to develop and optimize the first tailored mobile intervention for nurse burnout, which recommends programs based on artificial intelligence (AI) algorithms, and to test its usability, effectiveness, and satisfaction. Methods: In this study, an AI-based mobile intervention, Nurse Healing Space, was developed to provide tailored programs for nurse burnout. The 4-week program included mindfulness meditation, laughter therapy, storytelling, reflective writing, and acceptance and commitment therapy. The AI algorithm recommended one of these programs to participants by calculating similarity through a pretest consisting of participants’ demographics, research variables, and burnout dimension scores measured with the Copenhagen Burnout Inventory. After completing a 4-week program, burnout, job stress, stress response using the Stress Response Inventory Modified Form, the usability of the app, coping strategy by the coping strategy indicator, and program satisfaction (1: very dissatisfied; 5: very satisfied) were measured. The AI recognized the recommended program as effective if the user’s burnout score reduced after the 2-week program and updated the algorithm accordingly. After a pilot test (n=10), AI optimization was performed (n=300). A paired 2-tailed t test, ANOVA, and the Spearman correlation were used to test the effect of the intervention and algorithm optimization. Results: Nurse Healing Space was implemented as a mobile app equipped with a system that recommended 1 program out of 4 based on similarity between users through AI. The AI algorithm worked well in matching the program recommended to participants who were most similar using valid data. Users were satisfied with the convenience and visual quality but were dissatisfied with the absence of notifications and inability to customize the program. The overall usability score of the app was 3.4 out of 5 points. Nurses’ burnout scores decreased significantly after the completion of the first 2-week program (t=7.012; P<.001) and reduced further after the second 2-week program (t=2.811; P=.01). After completing the Nurse Healing Space program, job stress (t=6.765; P<.001) and stress responses (t=5.864; P<.001) decreased significantly. During the second 2-week program, the burnout level reduced in the order of participation (r=–0.138; P=.04). User satisfaction increased for both the first (F=3.493; P=.03) and second programs (F=3.911; P=.02). Conclusions: This program effectively reduced burnout, job stress, and stress responses. Nurse managers were able to prevent nurses from resigning and maintain the quality of medical services using this AI-based program to provide tailored interventions for nurse burnout. Thus, this app could improve qualitative health care, increase employee satisfaction, reduce costs, and ultimately improve the efficiency of the health care system. %M 38905631 %R 10.2196/54029 %U https://www.jmir.org/2024/1/e54029 %U https://doi.org/10.2196/54029 %U http://www.ncbi.nlm.nih.gov/pubmed/38905631 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 11 %N %P e48129 %T The Value of a Virtual Assistant to Improve Engagement in Computerized Cognitive Training at Home: Exploratory Study %A Zsoldos,Isabella %A Trân,Eléonore %A Fournier,Hippolyte %A Tarpin-Bernard,Franck %A Fruitet,Joan %A Fouillen,Mélodie %A Bailly,Gérard %A Elisei,Frédéric %A Bouchot,Béatrice %A Constant,Patrick %A Ringeval,Fabien %A Koenig,Olivier %A Chainay,Hanna %+ Laboratoire d’Étude des Mécanismes Cognitifs, Université Lumière Lyon 2, 5 Avenue Pierre Mendès France, Lyon, 69500, France, 33 478774335, isabella.zsoldos@hotmail.fr %K cognitive training %K cognitive decline %K cognitive disorders %K mild cognitive impairment %K Alzheimer disease %K digital therapies %K virtual health assistant %K conversational agent %K artificial intelligence %K social interaction %K THERADIA %D 2024 %7 20.6.2024 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: Impaired cognitive function is observed in many pathologies, including neurodegenerative diseases such as Alzheimer disease. At present, the pharmaceutical treatments available to counter cognitive decline have only modest effects, with significant side effects. A nonpharmacological treatment that has received considerable attention is computerized cognitive training (CCT), which aims to maintain or improve cognitive functioning through repeated practice in standardized exercises. CCT allows for more regular and thorough training of cognitive functions directly at home, which represents a significant opportunity to prevent and fight cognitive decline. However, the presence of assistance during training seems to be an important parameter to improve patients’ motivation and adherence to treatment. To compensate for the absence of a therapist during at-home CCT, a relevant option could be to include a virtual assistant to accompany patients throughout their training. Objective: The objective of this exploratory study was to evaluate the interest of including a virtual assistant to accompany patients during CCT. We investigated the relationship between various individual factors (eg, age, psycho-affective functioning, personality, personal motivations, and cognitive skills) and the appreciation and usefulness of a virtual assistant during CCT. This study is part of the THERADIA (Thérapies Digitales Augmentées par l’Intelligence Artificielle) project, which aims to develop an empathetic virtual assistant. Methods: A total of 104 participants were recruited, including 52 (50%) young adults (mean age 21.2, range 18 to 27, SD 2.9 years) and 52 (50%) older adults (mean age 67.9, range 60 to 79, SD 5.1 years). All participants were invited to the laboratory to answer several questionnaires and perform 1 CCT session, which consisted of 4 cognitive exercises supervised by a virtual assistant animated by a human pilot via the Wizard of Oz method. The participants evaluated the virtual assistant and CCT at the end of the session. Results: Analyses were performed using the Bayesian framework. The results suggest that the virtual assistant was appreciated and perceived as useful during CCT in both age groups. However, older adults rated the assistant and CCT more positively overall than young adults. Certain characteristics of users, especially their current affective state (ie, arousal, intrinsic relevance, goal conduciveness, and anxiety state), appeared to be related to their evaluation of the session. Conclusions: This study provides, for the first time, insight into how young and older adults perceive a virtual assistant during CCT. The results suggest that such an assistant could have a beneficial influence on users’ motivation, provided that it can handle different situations, particularly their emotional state. The next step of our project will be to evaluate our device with patients experiencing mild cognitive impairment and to test its effectiveness in long-term cognitive training. %M 38901017 %R 10.2196/48129 %U https://rehab.jmir.org/2024/1/e48129 %U https://doi.org/10.2196/48129 %U http://www.ncbi.nlm.nih.gov/pubmed/38901017 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53607 %T Effects of Peer- or Professional-Led Support in Enhancing Adherence to Wearable Monitoring Devices Among Community-Dwelling Older Adults: Systematic Review of Randomized Controlled Trials %A Chan,Colette Sze Wing %A Kan,Mandy Ming Pui %A Wong,Arkers Kwan Ching %+ School of Nursing, The Hong Kong Polytechnic University, GH 502, The Hong Kong Polytechnic University, Hung Hom, 00000, China (Hong Kong), 852 34003805, arkers.wong@polyu.edu.hk %K wearable monitoring device %K older adults %K adherence %K systematic review %K healthy aging %K peer support %K professional help %K support %K peers %K peer %K professionals %K wearable %K monitoring devices %K monitoring device %K community-dwelling %K older adults %K older adult %K aging %K aging %K elderly %D 2024 %7 20.6.2024 %9 Review %J J Med Internet Res %G English %X Background: Despite the well-documented health benefits associated with wearable monitoring devices (WMDs), adherence among community-dwelling older adults remains low. By providing guidance on the purpose and benefits of using WMDs, facilitating goal-setting aligned with the device’s features, promoting comprehension of the health data captured by the device, and assisting in overcoming technological challenges, peers and health care professionals can potentially enhance older adults’ adherence to WMDs. However, the effectiveness of such support mechanisms in promoting adherence to WMDs among older adults remains poorly understood. Objective: The aims of this systematic review were to examine the effects of peer- or professional-led intervention programs designed to improve adherence to WMDs among community-dwelling older adults and to identify the intervention components that may positively influence the effects of the intervention. Methods: We conducted a comprehensive search across 7 electronic databases (Cochrane Central Register of Controlled Trials [CENTRAL], PubMed, EMBASE, PsycINFO, British Nursing Index, Web of Science, and CINAHL) to identify articles published between January 1, 2010, and June 26, 2023. We specifically targeted randomized controlled trials that examined the impact of peer- or professional-led interventions on enhancing adherence to WMDs among individuals aged 60 years and older residing in the community. Two independent reviewers extracted data from the included studies and assessed the potential risk of bias in accordance with the Cochrane Risk of Bias tool for randomized trials, version 2. Results: A total of 10,511 studies were identified through the database search. Eventually, we included 3 randomized controlled trials involving 154 community-dwelling older adults. The participants had a mean age of 65 years. Our review revealed that increasing awareness of being monitored and implementing the SystemCHANGE approach, a habit change tool focusing on personal goals and feedback, were effective strategies for enhancing adherence to WMDs among older adults. All of the included studies exhibited a low risk of bias. Conclusions: By collaboratively designing specific goals related to WMDs with health care professionals, including nurses and physicians, older adults exhibited a higher likelihood of adhering to the prescribed use of WMDs. These goal-setting tools provided a framework for structure and motivation, facilitating the seamless integration of WMDs into their daily routines. Researchers should prioritize interventions that target awareness and goal-setting as effective approaches to enhance adherence to WMDs among older adults, thereby maximizing the realization of associated health benefits. %M 38900546 %R 10.2196/53607 %U https://www.jmir.org/2024/1/e53607 %U https://doi.org/10.2196/53607 %U http://www.ncbi.nlm.nih.gov/pubmed/38900546 %0 Journal Article %@ 2291-5222 %I %V 12 %N %P e54946 %T Engagement in mHealth-Prompted Self-Measured Blood Pressure Monitoring Among Participants Recruited From a Safety-Net Emergency Department: Secondary Analysis of the Reach Out Trial %A Skolarus,Lesli E %A Lin,Chun Chieh %A Mishra,Sonali %A Meurer,William %A Dinh,Mackenzie %A Whitfield,Candace %A Bi,Ran %A Brown,Devin %A Oteng,Rockefeller %A Buis,Lorraine R %A Kidwell,Kelley %K hypertension %K self-measured blood pressure %K mobile health %K blood pressure %K emergency %K blood pressure monitoring %K risk factor %K cardiovascular %K cardiovascular disease %K utilization %K feedback %K care %K systolic blood pressure %K emergency department %K mHealth %K health disparities %K engagement %D 2024 %7 12.6.2024 %9 %J JMIR Mhealth Uhealth %G English %X Background: Hypertension, a key modifiable risk factor for cardiovascular disease, is more prevalent among Black and low-income individuals. To address this health disparity, leveraging safety-net emergency departments for scalable mobile health (mHealth) interventions, specifically using text messaging for self-measured blood pressure (SMBP) monitoring, presents a promising strategy. This study investigates patterns of engagement, associated factors, and the impact of engagement on lowering blood pressure (BP) in an underserved population. Objective: We aimed to identify patterns of engagement with prompted SMBP monitoring with feedback, factors associated with engagement, and the association of engagement with lowered BP. Methods: This is a secondary analysis of data from Reach Out, an mHealth, factorial trial among 488 hypertensive patients recruited from a safety-net emergency department in Flint, Michigan. Reach Out participants were randomized to weekly or daily text message prompts to measure their BP and text in their responses. Engagement was defined as a BP response to the prompt. The k-means clustering algorithm and visualization were used to determine the pattern of SMBP engagement by SMBP prompt frequency—weekly or daily. BP was remotely measured at 12 months. For each prompt frequency group, logistic regression models were used to assess the univariate association of demographics, access to care, and comorbidities with high engagement. We then used linear mixed-effects models to explore the association between engagement and systolic BP at 12 months, estimated using average marginal effects. Results: For both SMBP prompt groups, the optimal number of engagement clusters was 2, which we defined as high and low engagement. Of the 241 weekly participants, 189 (78.4%) were low (response rate: mean 20%, SD 23.4) engagers, and 52 (21.6%) were high (response rate: mean 86%, SD 14.7) engagers. Of the 247 daily participants, 221 (89.5%) were low engagers (response rate: mean 9%, SD 12.2), and 26 (10.5%) were high (response rate: mean 67%, SD 8.7) engagers. Among weekly participants, those who were older (>65 years of age), attended some college (vs no college), married or lived with someone, had Medicare (vs Medicaid), were under the care of a primary care doctor, and took antihypertensive medication in the last 6 months had higher odds of high engagement. Participants who lacked transportation to appointments had lower odds of high engagement. In both prompt frequency groups, participants who were high engagers had a greater decline in BP compared to low engagers. Conclusions: Participants randomized to weekly SMBP monitoring prompts responded more frequently overall and were more likely to be classed as high engagers compared to participants who received daily prompts. High engagement was associated with a larger decrease in BP. New strategies to encourage engagement are needed for participants with lower access to care. Trial Registration: ClinicalTrials.gov NCT03422718; https://clinicaltrials.gov/study/NCT03422718 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-020-04340-z %R 10.2196/54946 %U https://mhealth.jmir.org/2024/1/e54946 %U https://doi.org/10.2196/54946 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e45469 %T App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data %A Lehmann,Marco %A Jones,Lucy %A Schirmann,Felix %+ Oviva AG, Dortustraße 48, Potsdam, 14467, Germany, 49 3055572034, marco.lehmann@oviva.com %K obesity %K weight loss %K blended-care %K digital health %K real-world data %K app engagement %K mHealth %K mobile health %K technology engagement %K weight management %K mobile phone %D 2024 %7 7.6.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Early weight loss is an established predictor for treatment outcomes in weight management interventions for people with obesity. However, there is a paucity of additional, reliable, and clinically actionable early predictors in weight management interventions. Novel blended-care weight management interventions combine coach and app support and afford new means of structured, continuous data collection, informing research on treatment adherence and outcome prediction. Objective: Against this backdrop, this study analyzes app engagement as a predictor for weight loss in large-scale, real-world, blended-care interventions. We hypothesize that patients who engage more frequently in app usage in blended-care treatment (eg, higher logging activity) lose more weight than patients who engage comparably less frequently at 3 and 6 months of intervention. Methods: Real-world data from 19,211 patients in obesity treatment were analyzed retrospectively. Patients were treated with 3 different blended-care weight management interventions, offered in Switzerland, the United Kingdom, and Germany by a digital behavior change provider. The principal component analysis identified an overarching metric for app engagement based on app usage. A median split informed a distinction in higher and lower engagers among the patients. Both groups were matched through optimal propensity score matching for relevant characteristics (eg, gender, age, and start weight). A linear regression model, combining patient characteristics and app-derived data, was applied to identify predictors for weight loss outcomes. Results: For the entire sample (N=19,211), mean weight loss was –3.24% (SD 4.58%) at 3 months and –5.22% (SD 6.29%) at 6 months. Across countries, higher app engagement yielded more weight loss than lower engagement after 3 but not after 6 months of intervention (P3 months<.001 and P6 months=.59). Early app engagement within the first 3 months predicted percentage weight loss in Switzerland and Germany, but not in the United Kingdom (PSwitzerland<.001, PUnited Kingdom=.12, and PGermany=.005). Higher age was associated with stronger weight loss in the 3-month period (PSwitzerland=.001, PUnited Kingdom=.002, and PGermany<.001) and, for Germany, also in the 6-month period (PSwitzerland=.09, PUnited Kingdom=.46, and PGermany=.03). In Switzerland, higher numbers of patients’ messages to coaches were associated with higher weight loss (P3 months<.001 and P6 months<.001). Messages from coaches were not significantly associated with weight loss (all P>.05). Conclusions: Early app engagement is a predictor of weight loss, with higher engagement yielding more weight loss than lower engagement in this analysis. This new predictor lends itself to automated monitoring and as a digital indicator for needed or adapted clinical action. Further research needs to establish the reliability of early app engagement as a predictor for treatment adherence and outcomes. In general, the obtained results testify to the potential of app-derived data to inform clinical monitoring practices and intervention design. %M 38848556 %R 10.2196/45469 %U https://www.jmir.org/2024/1/e45469 %U https://doi.org/10.2196/45469 %U http://www.ncbi.nlm.nih.gov/pubmed/38848556 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e56003 %T Smartphone-Based Survey and Message Compliance in Adults Initially Unready to Quit Smoking: Secondary Analysis of a Randomized Controlled Trial %A Ulm,Clayton %A Chen,Sixia %A Fleshman,Brianna %A Benson,Lizbeth %A Kendzor,Darla E %A Frank-Pearce,Summer %A Neil,Jordan M %A Vidrine,Damon %A De La Torre,Irene %A Businelle,Michael S %+ TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 655 Research Parkway, Suite 400, Oklahoma City, OK, 73104, United States, 1 405 271 8001, michael-businelle@ouhsc.edu %K just-in-time adaptive intervention %K tailored messaging %K smoking cessation %K mobile health %K survey compliance %K phase-based model %K smoking %K smoker %K survey %K smokers %K messaging %K smartphone %K efficacy %K pilot randomized controlled trial %K adult smokers %K linear regression %K age %K intervention engagement %K engagement %D 2024 %7 7.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Efficacy of smartphone-based interventions depends on intervention content quality and level of exposure to that content. Smartphone-based survey completion rates tend to decline over time; however, few studies have identified variables that predict this decline over longer-term interventions (eg, 26 weeks). Objective: This study aims to identify predictors of survey completion and message viewing over time within a 26-week smoking cessation trial. Methods: This study examined data from a 3-group pilot randomized controlled trial of adults who smoke (N=152) and were not ready to quit smoking within the next 30 days. For 182 days, two intervention groups received smartphone-based morning and evening messages based on current readiness to quit smoking. The control group received 2 daily messages unrelated to smoking. All participants were prompted to complete 26 weekly smartphone-based surveys that assessed smoking behavior, quit attempts, and readiness to quit. Compliance was operationalized as percentages of weekly surveys completed and daily messages viewed. Linear regression and mixed-effects models were used to identify predictors (eg, intervention group, age, and sex) of weekly survey completion and daily message viewing and decline in compliance over time. Results: The sample (mean age 50, SD 12.5, range 19-75 years; mean years of education 13.3, SD 1.6, range 10-20 years) was 67.8% (n=103) female, 74.3% (n=113) White, 77% (n=117) urban, and 52.6% (n=80) unemployed, and 61.2% (n=93) had mental health diagnoses. On average, participants completed 18.3 (71.8%) out of 25.5 prompted weekly surveys and viewed 207.3 (60.6%) out of 345.1 presented messages (31,503/52,460 total). Age was positively associated with overall weekly survey completion (P=.003) and daily message viewing (P=.02). Mixed-effects models indicated a decline in survey completion from 77% (114/148) in the first week of the intervention to 56% (84/150) in the last week of the intervention (P<.001), which was significantly moderated by age, sex, ethnicity, municipality (ie, rural/urban), and employment status. Similarly, message viewing declined from 72.3% (1533/2120) in the first week of the intervention to 44.6% (868/1946) in the last week of the intervention (P<.001). This decline in message viewing was significantly moderated by age, sex, municipality, employment status, and education. Conclusions: This study demonstrated the feasibility of a 26-week smartphone-based smoking cessation intervention. Study results identified subgroups that displayed accelerated rates in the decline of survey completion and message viewing. Future research should identify ways to maintain high levels of interaction with mobile health interventions that span long intervention periods, especially among subgroups that have demonstrated declining rates of intervention engagement over time. Trial Registration: ClinicalTrials.gov NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129 %M 38848557 %R 10.2196/56003 %U https://formative.jmir.org/2024/1/e56003 %U https://doi.org/10.2196/56003 %U http://www.ncbi.nlm.nih.gov/pubmed/38848557 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e51708 %T Six-Month Outcomes of a Theory- and Technology-Enhanced Physical Activity Intervention for Latina Women (Pasos Hacia La Salud II): Randomized Controlled Trial %A Connell Bohlen,Lauren %A Dunsiger,Shira I %A von Ash,Tayla %A Larsen,Britta A %A Pekmezi,Dori %A Marquez,Becky %A Benitez,Tanya J %A Mendoza-Vasconez,Andrea %A Hartman,Sheri J %A Williams,David M %A Marcus,Bess H %+ Center for Health Promotion and Health Equity, Department of Behavioral and Social Sciences, Brown University School of Public Health, 121 South Main Street, Box G-S121-8, Providence, RI, 02912, United States, 1 4018636559, lauren_bohlen@brown.edu %K digital health %K web-based intervention %K exercise %K social support %K behavior change intervention %K support %K Latina women %K women %K Latina %K physical activity %K barrier %K aerobic %K remote intervention %K text message %K behavior change %K behavior %D 2024 %7 6.6.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: More than half (55%) of Latina women do not meet aerobic physical activity (PA) guidelines, and frequently cite time, childcare, and transportation as barriers to PA. In addition to linguistic adaptations for this population, successful PA interventions for Latina women addressed these barriers through remote intervention delivery approaches (eg, mail, phone, or web delivery). Objective: We aimed to evaluate 6-month outcomes of a randomized trial comparing a Spanish-language, individually tailored, web-delivered PA intervention (original) to an enhanced version with text messages and additional features (enhanced). Further, we evaluated if increases in PA at 6 months were moderated by baseline activity status. Methods: In total, 195 Latina women aged 18-65 years participated in a trial comparing the efficacy of the enhanced versus original interventions at initiating PA behavior change. We examined minutes per week of accelerometer-measured PA in the enhanced versus original arms, and the proportion of each arm meeting aerobic PA guidelines (150 min/wk at 6 mo). For moderator analyses, participants were classified as inactive (0 min/wk) or low active (1-90 min/wk) at baseline, measured via the 7 Day Physical Activity Recall interview. Results: PA increased from 19.7 (SD 47.9) minutes per week at baseline to 46.9 (SD 66.2) minutes per week at 6 months in the enhanced arm versus 20.6 (SD 42.7) minutes per week to 42.9 (SD 78.2) minutes per week in the original arm (P=.78). Overall, 30% (31/103) of the enhanced group met aerobic PA guidelines at 6 months, compared to 21% (19/92) of the original group (odds ratio [OR] 1.75, 95% CI 0.87-3.55). Baseline PA (inactive vs low active) moderated treatment effects on PA. For inactive participants, there were no group differences at 6 months (b=7.1; SE 22.8; P=.75), while low-active participants increased more in enhanced than original (b=72.5; SE 27.9; P=.01). For low-active participants, 45% (46/103) of the enhanced group met PA guidelines at 6 months, versus 20% (18/92) of the original arm (OR 3.29, 95% CI 1.05-11.31). For inactive participants, there were no group differences (25/103, 24% vs n=19/92, 21% for enhanced vs original, respectively; OR 1.28, 95% CI 0.54-3.06). Conclusions: Intervention effects were conditional on baseline PA. For low-active Latina women, the enhanced intervention was more effective at increasing PA. Additional tailored intervention enhancements may be necessary to increase PA for inactive Latina women. Trial Registration: ClinicalTrials.gov NCT03491592; https://www.clinicaltrials.gov/study/NCT03491592 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-022-06575-4 %M 38842930 %R 10.2196/51708 %U https://www.jmir.org/2024/1/e51708 %U https://doi.org/10.2196/51708 %U http://www.ncbi.nlm.nih.gov/pubmed/38842930 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e50650 %T Detecting and Understanding Social Influence During Drinking Situations: Protocol for a Bluetooth-Based Sensor Feasibility and Acceptability Study %A Jackson,Kristina %A Meisel,Matthew %A Sokolovsky,Alexander %A Chen,Katie %A Barnett,Nancy %+ Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University, Box G-S121-4, Providence, RI, 02912, United States, 1 (401) 863 6617, kristina_jackson@brown.edu %K Bluetooth technology %K passive sensing %K social influence %K alcohol use %K ecological momentary assessment %K social network %K feasibility %K acceptability %K mobile phone %D 2024 %7 6.6.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: High-risk alcohol consumption among young adults frequently occurs in the presence of peers who are also drinking. A high-risk drinking situation may consist of particular social network members who have a primary association with drinking. Fine-grained approaches such as ecological momentary assessment (EMA) are growing in popularity for studying real-time social influence, but studies using these approaches exclusively rely on participant self-report. Passive indicators of peer presence using Bluetooth-based technology to detect real-time interactions have the potential to assist in the development of just-in-time interventions. Objective: This study seeks to examine the feasibility and acceptability of using a Bluetooth-based sensor and smartphone app to measure social contact in real-world drinking situations. Methods: Young adults (N=20) who drink heavily and report social drinking will be recruited from the community to participate in a 3-week EMA study. Using a social network interview, index participants will identify and recruit 3 of their friends to carry a Bluetooth beacon. Participants will complete a series of EMA reports on their own personal Android devices including random reports; morning reports; first-drink reports; and signal-contingent reports, which are triggered following the detection of a beacon carried by a peer participant. EMA will assess alcohol use and characteristics of the social environment, including who is nearby and who is drinking. For items about peer proximity and peer drinking, a customized peer list will be presented to participants. Feedback about the study protocol will be ascertained through weekly contact with both index and peer participants, followed by a qualitative interview at the end of the study. We will examine the feasibility and acceptability of recruitment, enrollment of participants and peers, and retention. Feasibility will be determined using indexes of eligibility, enrollment, and recruitment. Acceptability will be determined through participant enrollment and retention, protocol compliance, and participant-reported measures of acceptability. Feasibility and acceptability for peer participants will be informed by enrollment rates, latency to enrollment, compliance with carrying the beacon, and self-reported reasons for compliance or noncompliance with beacon procedures. Finally, EMA data about peer proximity and peer drinking will support the validity of the peer selection process. Results: Participant recruitment began in February 2023, and enrollment was completed in December 2023. Results will be reported in 2025. Conclusions: The protocol allows us to examine the feasibility and acceptability of a Bluetooth-based sensor for the detection of social contact between index participants and their friends, including social interactions during real-world drinking situations. Data from this study will inform just-in-time adaptive interventions seeking to address drinking in the natural environment by providing personalized feedback about a high-risk social context and alerting an individual that they are in a potentially unsafe situation. International Registered Report Identifier (IRRID): DERR1-10.2196/50650 %M 38842927 %R 10.2196/50650 %U https://www.researchprotocols.org/2024/1/e50650 %U https://doi.org/10.2196/50650 %U http://www.ncbi.nlm.nih.gov/pubmed/38842927 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 10 %N %P e52386 %T Engagement With a Relaxation and Mindfulness Mobile App Among People With Cancer: Exploratory Analysis of Use Data and Self-Reports From a Randomized Controlled Trial %A Schläpfer,Sonja %A Schneider,Fabian %A Santhanam,Prabhakaran %A Eicher,Manuela %A Kowatsch,Tobias %A Witt,Claudia M %A Barth,Jürgen %+ Institute for Complementary and Integrative Medicine, University Hospital Zurich and University of Zurich, Sonneggstrasse 6, Zurich, 8091, Switzerland, 41 44 255 94 51, sonja.schlaepfer@usz.ch %K mobile health %K mHealth %K digital health %K eHealth %K smartphone %K mobile phone %K implementation %K adherence %K self-guided %K unguided %K fully automated %K conversational agent %K chatbot %K behavior change %K tailoring %K self-care %K cancer %K app development %D 2024 %7 31.5.2024 %9 Original Paper %J JMIR Cancer %G English %X Background: Mobile health (mHealth) apps offer unique opportunities to support self-care and behavior change, but poor user engagement limits their effectiveness. This is particularly true for fully automated mHealth apps without any human support. Human support in mHealth apps is associated with better engagement but at the cost of reduced scalability. Objective: This work aimed to (1) describe the theory-informed development of a fully automated relaxation and mindfulness app to reduce distress in people with cancer (CanRelax app 2.0), (2) describe engagement with the app on multiple levels within a fully automated randomized controlled trial over 10 weeks, and (3) examine whether engagement was related to user characteristics. Methods: The CanRelax app 2.0 was developed in iterative processes involving input from people with cancer and relevant experts. The app includes evidence-based relaxation exercises, personalized weekly coaching sessions with a rule-based conversational agent, 39 self-enactable behavior change techniques, a self-monitoring dashboard with gamification elements, highly tailored reminder notifications, an educational video clip, and personalized in-app letters. For the larger study, German-speaking adults diagnosed with cancer within the last 5 years were recruited via the web in Switzerland, Austria, and Germany. Engagement was analyzed in a sample of 100 study participants with multiple measures on a micro level (completed coaching sessions, relaxation exercises practiced with the app, and feedback on the app) and a macro level (relaxation exercises practiced without the app and self-efficacy toward self-set weekly relaxation goals). Results: In week 10, a total of 62% (62/100) of the participants were actively using the CanRelax app 2.0. No associations were identified between engagement and level of distress at baseline, sex assigned at birth, educational attainment, or age. At the micro level, 71.88% (3520/4897) of all relaxation exercises and 714 coaching sessions were completed in the app, and all participants who provided feedback (52/100, 52%) expressed positive app experiences. At the macro level, 28.12% (1377/4897) of relaxation exercises were completed without the app, and participants’ self-efficacy remained stable at a high level. At the same time, participants raised their weekly relaxation goals, which indicates a potential relative increase in self-efficacy. Conclusions: The CanRelax app 2.0 achieved promising engagement even though it provided no human support. Fully automated social components might have compensated for the lack of human involvement and should be investigated further. More than one-quarter (1377/4897, 28.12%) of all relaxation exercises were practiced without the app, highlighting the importance of assessing engagement on multiple levels. %M 38819907 %R 10.2196/52386 %U https://cancer.jmir.org/2024/1/e52386 %U https://doi.org/10.2196/52386 %U http://www.ncbi.nlm.nih.gov/pubmed/38819907 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e50446 %T Evaluating a New Digital App–Based Program for Heart Health: Feasibility and Acceptability Pilot Study %A Lockwood,Kimberly G %A Kulkarni,Priya R %A Paruthi,Jason %A Buch,Lauren S %A Chaffard,Mathieu %A Schitter,Eva C %A Branch,OraLee H %A Graham,Sarah A %+ Lark Health, 809 Cuesta Dr, Suite B #1033, Mountain View, CA, 94040, United States, 1 5033801340, kimberly.lockwood@lark.com %K digital health %K cardiovascular disease %K artificial intelligence %K AI %K acceptability and feasibility %K pilot study %K lifestyle coaching %K mobile phone %D 2024 %7 24.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Cardiovascular disease (CVD) is the leading cause of death in the United States, affecting a significant proportion of adults. Digital health lifestyle change programs have emerged as a promising method of CVD prevention, offering benefits such as on-demand support, lower cost, and increased scalability. Prior research has shown the effectiveness of digital health interventions in reducing negative CVD outcomes. This pilot study focuses on the Lark Heart Health program, a fully digital artificial intelligence (AI)–powered smartphone app, providing synchronous CVD risk counseling, educational content, and personalized coaching. Objective: This pilot study evaluated the feasibility and acceptability of a fully digital AI-powered lifestyle change program called Lark Heart Health. Primary analyses assessed (1) participant satisfaction, (2) engagement with the program, and (3) the submission of health screeners. Secondary analyses were conducted to evaluate weight loss outcomes, given that a major focus of the Heart Health program is weight management. Methods: This study enrolled 509 participants in the 90-day real-world single-arm pilot study of the Heart Health app. Participants engaged with the app by participating in coaching conversations, logging meals, tracking weight, and completing educational lessons. The study outcomes included participant satisfaction, app engagement, the completion of screeners, and weight loss. Results: On average, Heart Health study participants were aged 60.9 (SD 10.3; range 40-75) years, with average BMI indicating class I obesity. Of the 509 participants, 489 (96.1%) stayed enrolled until the end of the study (dropout rate: 3.9%). Study retention, based on providing a weight measurement during month 3, was 80% (407/509; 95% CI 76.2%-83.4%). Participant satisfaction scores indicated high satisfaction with the overall app experience, with an average score of ≥4 out of 5 for all satisfaction indicators. Participants also showed high engagement with the app, with 83.4% (408/489; 95% CI 80.1%-86.7%) of the sample engaging in ≥5 coaching conversations in month 3. The results indicated that participants were successfully able to submit health screeners within the app, with 90% (440/489; 95% CI 87%-92.5%) submitting all 3 screeners measured in the study. Finally, secondary analyses showed that participants lost weight during the program, with analyses showing an average weight nadir of 3.8% (SD 2.9%; 95% CI 3.5%-4.1%). Conclusions: The study results indicate that participants in this study were satisfied with their experience using the Heart Health app, highly engaged with the app features, and willing and able to complete health screening surveys in the app. These acceptability and feasibility results provide a key first step in the process of evidence generation for a new AI-powered digital program for heart health. Future work can expand these results to test outcomes with a commercial version of the Heart Health app in a diverse real-world sample. %M 38787598 %R 10.2196/50446 %U https://formative.jmir.org/2024/1/e50446 %U https://doi.org/10.2196/50446 %U http://www.ncbi.nlm.nih.gov/pubmed/38787598 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e40796 %T Attrition Rates in HIV Viral Load Monitoring and Factors Associated With Overdue Testing Among Children Within South Africa’s Antiretroviral Treatment Program: Retrospective Descriptive Analysis %A Haeri Mazanderani,Ahmad %A Radebe,Lebohang %A Sherman,Gayle G %+ Centre for HIV & STIs, National Institute for Communicable Diseases, National Health Laboratory Service, 1 Modderfontein Road, Sandringham, Johannesburg, 2031, South Africa, 27 826428609, ahmadh@nicd.ac.za %K HIV %K monitoring %K viral load %K suppression %K overdue %K retention %K VL test %K attrition %K child %K youth %K pediatric %K paediatric %K sexually transmitted %K sexual transmission %K virological failure %K South Africa %K infant %K adolescent %K big data %K descriptive analysis %K laboratory data %D 2024 %7 14.5.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Numerous studies in South Africa have reported low HIV viral load (VL) suppression and high attrition rates within the pediatric HIV treatment program. Objective: Using routine laboratory data, we evaluated HIV VL monitoring, including mobility and overdue VL (OVL) testing, within 5 priority districts in South Africa. Methods: We performed a retrospective descriptive analysis of National Health Laboratory Service (NHLS) data for children and adolescents aged 1-15 years having undergone HIV VL testing between May 1, 2019, and April 30, 2020, from 152 facilities within the City of Johannesburg, City of Tshwane, eThekwini, uMgungundlovu, and Zululand. HIV VL test–level data were deduplicated to patient-level data using the NHLS CDW (Corporate Data Warehouse) probabilistic record-linking algorithm and then further manually deduplicated. An OVL was defined as no subsequent VL determined within 18 months of the last test. Variables associated with the last VL test, including age, sex, VL findings, district type, and facility type, are described. A multivariate logistic regression analysis was performed to identify variables associated with an OVL test. Results: Among 21,338 children and adolescents aged 1-15 years who had an HIV VL test, 72.70% (n=15,512) had a follow-up VL test within 18 months. Furthermore, 13.33% (n=2194) of them were followed up at a different facility, of whom 3.79% (n=624) were in a different district and 1.71% (n=281) were in a different province. Among patients with a VL of ≥1000 RNA copies/mL of plasma, the median time to subsequent testing was 6 (IQR 4-10) months. The younger the age of the patient, the greater the proportion with an OVL, ranging from a peak of 52% among 1-year-olds to a trough of 21% among 14-year-olds. On multivariate analysis, 2 consecutive HIV VL findings of ≥1000 RNA copies/mL of plasma were associated with an increased adjusted odds ratio (AOR) of having an OVL (AOR 2.07, 95% CI 1.71-2.51). Conversely, patients examined at a hospital (AOR 0.86, 95% CI 0.77-0.96), those with ≥2 previous tests (AOR 0.78, 95% CI 0.70-0.86), those examined in a rural district (AOR 0.63, 95% CI 0.54-0.73), and older age groups of 5-9 years (AOR 0.56, 95% CI 0.47-0.65) and 10-14 years (AOR 0.51, 95% CI 0.44-0.59) compared to 1-4 years were associated with a significantly decreased odds of having an OVL test. Conclusions: Considerable attrition occurs within South Africa’s pediatric HIV treatment program, with over one-fourth of children having an OVL test 18 months subsequent to their previous test. In particular, younger children and those with virological failure were found to be at increased risk of having an OVL test. Improved HIV VL monitoring is essential for improving outcomes within South Africa’s pediatric antiretroviral treatment program. %M 38743934 %R 10.2196/40796 %U https://publichealth.jmir.org/2024/1/e40796 %U https://doi.org/10.2196/40796 %U http://www.ncbi.nlm.nih.gov/pubmed/38743934 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e50851 %T Understanding Patient Perspectives on the Use of Gamification and Incentives in mHealth Apps to Improve Medication Adherence: Qualitative Study %A Tran,Steven %A Smith,Lorraine %A Carter,Stephen %+ School of Pharmacy, Faculty of Medicine and Health, University of Sydney, A15, Science Rd, Camperdown, 2050, Australia, 61 93512222, steventran@hotmail.com.au %K qualitative %K patient %K perspectives %K gamification %K incentives %K mobile app %K mobile health %K mHealth %K medication adherence %K mobile phone %D 2024 %7 14.5.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Medication nonadherence remains a significant health and economic burden in many high-income countries. Emerging smartphone interventions have started to use features such as gamification and financial incentives with varying degrees of effectiveness on medication adherence and health outcomes. A more consistent approach to applying these features, informed by patient perspectives, may result in more predictable and beneficial results from this type of intervention. Objective: This qualitative study aims to identify patient perspectives on the use of gamification and financial incentives in mobile health (mHealth) apps for medication adherence in Australian patients taking medication for chronic conditions. Methods: A total of 19 participants were included in iterative semistructured web-based focus groups conducted between May and December 2022. The facilitator used exploratory prompts relating to mHealth apps, gamification, and financial incentives, along with concepts raised from previous focus groups. Transcriptions were independently coded to develop a set of themes. Results: Three themes were identified: purpose-driven design, trust-based standards, and personal choice. All participants acknowledged gamification and financial incentives as potentially effective features in mHealth apps for medication adherence. However, they also indicated that the effectiveness heavily depended on implementation and execution. Major concerns relating to gamification and financial incentives were perceived trivialization and potential for medication abuse, respectively. Conclusions: The study’s findings provide a foundation for developers seeking to apply these novel features in an app intervention for a general cohort of patients. However, the study highlights the need for standards for mHealth apps for medication adherence, with particular attention to the use of gamification and financial incentives. Future research with patients and stakeholders across the mHealth app ecosystem should be explored to formalize and validate a set of standards or framework. %M 38743461 %R 10.2196/50851 %U https://mhealth.jmir.org/2024/1/e50851 %U https://doi.org/10.2196/50851 %U http://www.ncbi.nlm.nih.gov/pubmed/38743461 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e53756 %T Self-Selected Versus Assigned Target to Reduce Smartphone Use and Improve Mental Health: Protocol for a Randomized Controlled Trial %A Sharma,Kamal Kant %A Somasundaram,Jeeva %A Sachdeva,Ashish %+ Max Institute of Healthcare Management, Indian School of Business, Knowledge City, Sector 81, Sahibzada Ajit Singh Nagar, Punjab, 140306, India, 91 01724591831, ashish_sachdeva@isb.edu %K screen time %K monetary incentives %K target selection %K mental health %K mobile phone %D 2024 %7 6.5.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Smartphones have become integral to people’s lives, with a noticeable increase in the average screen time, both on a global scale and, notably, in India. Existing research links mobile consumption to sleep problems, poor physical and mental health, and lower subjective well-being. The comparative effectiveness of monetary incentives given for self-selected versus assigned targets on reducing screen time and thereby improving mental health remains unanswered. Objective: This study aims to assess the impact of monetary incentives and target selection on mobile screen time reduction and mental health. Methods: We designed a 3-armed randomized controlled trial conducted with employees and students at an educational institution in India. The study is conducted digitally over 12 weeks, including baseline (2 weeks), randomization (1 week), intervention (5 weeks), and postintervention (4 week) periods. We emailed the employees and students to inquire about their interest in participation. Those who expressed interest received detailed study information and consent forms. After securing consent, participants were asked to complete the initial survey and provide their mobile screen time during the baseline period. At the beginning of the intervention period, the participants were randomly allocated into 1 of 3 study groups in a 2:2:1 ratio (self-selected vs assigned vs control). Participants in the self-selected group were presented with 3 target options: 10%, 20%, and 30%, and they were asked to self-select a target to reduce their mobile screen time from their baseline average mobile screen time. Participants in the assigned group were given a target to reduce their mobile screen time from their baseline average mobile screen time. The assigned target was set as the average of the targets selected by participants in the self-selected group. During the intervention period, participants in the self-selected and assigned group were eligible to receive a monetary incentive of INR (Indian Rupee) 50 (US $0.61) per day for successfully attaining their target. Participants in the control group neither received nor selected a target for reducing their mobile screen time and did not receive any monetary incentives during the intervention period. All participants received information regarding the advantages of reducing mobile screen time. As an incentive, all participants would receive INR 500 (US $6.06) upon completion of the study and a chance to win 1 of 2 lotteries valued at INR 5000 (US $60.55) for consistently sharing their mobile screen time data. Results: Currently, the study intervention is being rolled out. Enrollment occurred between August 21, 2023, and September 2, 2023; data collection concluded in November 2023. We expect that results will be available by early 2024. Conclusions: The monetary incentives and self-selected versus assigned targets might be effective interventions in reducing mobile screen time among working professionals and students. Trial Registration: AsPredicted 142497; https://aspredicted.org/hr3nn.pdf International Registered Report Identifier (IRRID): DERR1-10.2196/53756 %M 38709546 %R 10.2196/53756 %U https://www.researchprotocols.org/2024/1/e53756 %U https://doi.org/10.2196/53756 %U http://www.ncbi.nlm.nih.gov/pubmed/38709546 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e46420 %T Regulatory Issues in Electronic Health Records for Adolescent HIV Research: Strategies and Lessons Learned %A Green,Sara Shaw %A Lee,Sung-Jae %A Chahin,Samantha %A Pooler-Burgess,Meardith %A Green-Jones,Monique %A Gurung,Sitaji %A Outlaw,Angulique Y %A Naar,Sylvie %+ Center for Translational Behavioral Science, Department of Behavioral Sciences and Social Medicine, Florida State University, 2010 Levy Ave, Building B, Suite B0266, Tallahassee, FL, 32310, United States, 1 8506442334, sara.green@med.fsu.edu %K electronic health record %K HIV %K pragmatic trial %K regulatory %K EHR %K pre-exposure prophylaxis %K retention %K attrition %K dropout %K legal %K regulation %K adherence %K ethic %K review board %K implementation %K data use %K privacy %D 2024 %7 2.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Electronic health records (EHRs) are a cost-effective approach to provide the necessary foundations for clinical trial research. The ability to use EHRs in real-world clinical settings allows for pragmatic approaches to intervention studies with the emerging adult HIV population within these settings; however, the regulatory components related to the use of EHR data in multisite clinical trials poses unique challenges that researchers may find themselves unprepared to address, which may result in delays in study implementation and adversely impact study timelines, and risk noncompliance with established guidance. Objective: As part of the larger Adolescent Trials Network (ATN) for HIV/AIDS Interventions Protocol 162b (ATN 162b) study that evaluated clinical-level outcomes of an intervention including HIV treatment and pre-exposure prophylaxis services to improve retention within the emerging adult HIV population, the objective of this study is to highlight the regulatory process and challenges in the implementation of a multisite pragmatic trial using EHRs to assist future researchers conducting similar studies in navigating the often time-consuming regulatory process and ensure compliance with adherence to study timelines and compliance with institutional and sponsor guidelines. Methods: Eight sites were engaged in research activities, with 4 sites selected from participant recruitment venues as part of the ATN, who participated in the intervention and data extraction activities, and an additional 4 sites were engaged in data management and analysis. The ATN 162b protocol team worked with site personnel to establish the necessary regulatory infrastructure to collect EHR data to evaluate retention in care and viral suppression, as well as para-data on the intervention component to assess the feasibility and acceptability of the mobile health intervention. Methods to develop this infrastructure included site-specific training activities and the development of both institutional reliance and data use agreements. Results: Due to variations in site-specific activities, and the associated regulatory implications, the study team used a phased approach with the data extraction sites as phase 1 and intervention sites as phase 2. This phased approach was intended to address the unique regulatory needs of all participating sites to ensure that all sites were properly onboarded and all regulatory components were in place. Across all sites, the regulatory process spanned 6 months for the 4 data extraction and intervention sites, and up to 10 months for the data management and analysis sites. Conclusions: The process for engaging in multisite clinical trial studies using EHR data is a multistep, collaborative effort that requires proper advanced planning from the proposal stage to adequately implement the necessary training and infrastructure. Planning, training, and understanding the various regulatory aspects, including the necessity of data use agreements, reliance agreements, external institutional review board review, and engagement with clinical sites, are foremost considerations to ensure successful implementation and adherence to pragmatic trial timelines and outcomes. %M 38696775 %R 10.2196/46420 %U https://formative.jmir.org/2024/1/e46420 %U https://doi.org/10.2196/46420 %U http://www.ncbi.nlm.nih.gov/pubmed/38696775 %0 Journal Article %@ 2291-5222 %I %V 12 %N %P e44463 %T Effects of a Planned Web-Based Educational Intervention Based on the Health Belief Model for Patients With Ischemic Stroke in Promoting Secondary Prevention During the COVID-19 Lockdown in China: Quasi-Experimental Study %A Liu,Zhuo %A Sun,Xin %A Guo,Zhen-Ni %A Sun,Ye %A Yang,Yi %A Yan,Xiuli %K health belief model %K health education %K secondary prevention %K stroke %K medication adherence %K patient education %K web-based education %K digital intervention %K promotion %K stroke patients %K ischemic %K prevention %K quasi-experimental study %K education %K control group %K health management %K management %K systolic blood pressure %K blood pressure %K effectiveness %K medication adherence %D 2024 %7 24.4.2024 %9 %J JMIR Mhealth Uhealth %G English %X Background: Some common modified vascular risk factors remain poorly controlled among stroke survivors, and educational programs may help improve these conditions. Objective: This study aimed to evaluate the effect of a planned web-based educational intervention based on the health belief model (HBM) in promoting secondary prevention among patients with ischemic stroke. Methods: An evaluation-blinded quasi-experimental trial with a historical control group was conducted. Patients admitted from March to June 2020 were assigned to the historical control group, and patients admitted from July to October 2020 were assigned to the intervention group. The control group received routine health management. The intervention group received 6 additional sessions based on the HBM via Tencent Meeting, an audio and video conferencing application, within 3 months after discharge. Sessions were held every 2 weeks, with each session lasting approximately 40 minutes. These sessions were conducted in small groups, with about 8 to 10 people in each group. The primary outcomes were changes in blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c (HbA1c), and the proportion of patients achieving the treatment target. The secondary outcomes were medication adherence, assessed with the Morisky Medicine Adherence Scale (MMAS), and disability, assessed with the modified Rankin scale. Results: In total, 315 patients experiencing their first-ever stroke were analyzed. More patients in the intervention group had controlled BP (41.9% vs 28.4%; adjusted odds ratio [aOR] 1.93; P=.01), LDL-C (83.1% vs 67.7%; aOR 2.66; P=.001), and HbA1c (91.9% vs 83.9%; aOR: 3.37; P=.04) levels as well as a significant postintervention decrease in the systolic BP (adjusted β −3.94; P=.02), LDL-C (adjusted β −0.21; P=.008), and HbA1c (adjusted β −0.27; P<.001), compared with control groups. Significant between-group differences were observed in medication adherence (79.4% vs 63.2%; aOR 2.31; P=.002) but not in favorable functional outcomes. Conclusions: A web-based education program based on the HBM may be more effective than current methods used to educate patients having strokes on optimal vascular risk factors and medication adherence. Trial Registration: Chinese Clinical Trial Registry ChiCTR2000040804; https://www.chictr.org.cn/showproj.html?proj=62431 %R 10.2196/44463 %U https://mhealth.jmir.org/2024/1/e44463 %U https://doi.org/10.2196/44463 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e49512 %T Momentary Factors and Study Characteristics Associated With Participant Burden and Protocol Adherence: Ecological Momentary Assessment %A Tate,Allan D %A Fertig,Angela R %A de Brito,Junia N %A Ellis,Émilie M %A Carr,Christopher Patrick %A Trofholz,Amanda %A Berge,Jerica M %+ Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, 202 Miller Hall, 101 Buck Rd, Health Sciences Campus, Athens, GA, 30602, United States, 1 706 542 6317, allan.tate@uga.edu %K adherence %K burden %K data quality %K ecological momentary assessment %K mental health %K mHealth %K mobile health %K participant adherence %K public health %K stress %K study design %K survey burden %K survey %D 2024 %7 24.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Ecological momentary assessment (EMA) has become a popular mobile health study design to understand the lived experiences of dynamic environments. The numerous study design choices available to EMA researchers, however, may quickly increase participant burden and could affect overall adherence, which could limit the usability of the collected data. Objective: This study quantifies what study design, participant attributes, and momentary factors may affect self-reported burden and adherence. Methods: The EMA from the Phase 1 Family Matters Study (n=150 adult Black, Hmong, Latino or Latina, Native American, Somali, and White caregivers; n=1392 observation days) was examined to understand how participant self-reported survey burden was related to both design and momentary antecedents of adherence. The daily burden was measured by the question “Overall, how difficult was it for you to fill out the surveys today?” on a 5-item Likert scale (0=not at all and 4=extremely). Daily protocol adherence was defined as completing at least 2 signal-contingent surveys, 1 event-contingent survey, and 1 end-of-day survey each. Stress and mood were measured earlier in the day, sociodemographic and psychosocial characteristics were reported using a comprehensive cross-sectional survey, and EMA timestamps for weekends and weekdays were used to parameterize time-series models to evaluate prospective correlates of end-of-day study burden. Results: The burden was low at 1.2 (SD 1.14) indicating “a little” burden on average. Participants with elevated previous 30-day chronic stress levels (mean burden difference: 0.8; P=.04), 1 in 5 more immigrant households (P=.02), and the language primarily spoken in the home (P=.04; 3 in 20 more non-English–speaking households) were found to be population attributes of elevated moderate-high burden. Current and 1-day lagged nonadherence were correlated with elevated 0.39 and 0.36 burdens, respectively (P=.001), and the association decayed by the second day (β=0.08; P=.47). Unit increases in momentary antecedents, including daily depressed mood (P=.002) and across-day change in stress (P=.008), were positively associated with 0.15 and 0.07 higher end-of-day burdens after controlling for current-day adherence. Conclusions: The 8-day EMA implementation appeared to capture momentary sources of stress and depressed mood without substantial burden to a racially or ethnically diverse and immigrant or refugee sample of parents. Attention to sociodemographic attributes (eg, EMA in the primary language of the caregiver) was important for minimizing participant burden and improving data quality. Momentary stress and depressed mood were strong determinants of participant-experienced EMA burden and may affect adherence to mobile health study protocols. There were no strong indicators of EMA design attributes that created a persistent burden for caregivers. EMA stands to be an important observational design to address dynamic public health challenges related to human-environment interactions when the design is carefully tailored to the study population and to study research objectives. %M 38656787 %R 10.2196/49512 %U https://formative.jmir.org/2024/1/e49512 %U https://doi.org/10.2196/49512 %U http://www.ncbi.nlm.nih.gov/pubmed/38656787 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e48173 %T Remote Symptom Monitoring Using Patient-Reported Outcomes in Patients With Chronic Kidney Disease: Process Evaluation of a Randomized Controlled Trial %A Grove,Birgith Engelst %A de Thurah,Annette %A Ivarsen,Per %A Kvisgaard,Ann Katrine %A Hjollund,Niels Henrik %A Grytnes,Regine %A Schougaard,Liv Marit Valen %+ AmbuFlex, Centre for Patient-Reported Outcomes, Gødstrup Hospital, Møllegade 16, Herning, 7400, Denmark, 45 28904835, bigcri@rm.dk %K chronic kidney disease %K pragmatic randomized controlled trial %K process evaluation %K patient-reported outcome measures %K remote monitoring %K monitoring %K patient-reported outcome %K chronic kidney %K intervention %D 2024 %7 24.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: In Denmark, outpatient follow-up for patients with chronic kidney disease (CKD) is changing from in-hospital visits toward more remote health care delivery. The nonuse of remote patient-reported outcomes (PROs) is a well-known challenge, and it can be difficult to explain which mechanisms of interventions influence the outcome. Process evaluation may, therefore, be used to answer important questions on how and why interventions work, aiming to enhance the implications for clinical practice. Objective: This study aimed to provide insight into the intervention process by evaluating (1) the representativity of the study population, (2) patient and physician use patterns, (3) patient adherence to the intervention, and (4) clinical engagement. Methods: A process evaluation determining the reach, dose, fidelity, and clinical engagement was carried out, alongside a multicenter randomized controlled trial (RCT). We developed and implemented an intervention using PRO measures to monitor outpatients remotely. Data were collected for the PRO intervention arms in the RCT from 4 sources: (1) PRO data from the participants to determine personal factors, (2) the web-based PRO system to identify key usage intervention patterns, (3) medical records to identify clinical factors relating to the use of the intervention, and (4) semistructured interviews conducted with involved physicians. Results: Of the 320 patients invited, 152 (47.5%) accepted to participate. The study population reflected the target population. The mean adherence rate to the PRO intervention arms was 82% (95% CI 76-87). The questionnaire response rate was 539/544 (99.1%). A minority of 13 (12.9%) of 101 patients needed assistance to complete study procedures. Physicians assessed 477/539 (88.5%) of the questionnaires. Contact was established in 417/539 (77.4%) of the cases, and 122/539 (22.6%) of the patients did not have contact. Physicians initiated 288/417 (69.1%) and patients requested 129/417 (30.9%) of all the contacts. The primary causes of contact were clinical data (242/417, 58%), PRO data (92/417, 22.1%), and medication concerns and precautionary reasons (83/417, 19.9%). Physicians found the use of PRO measures in remote follow-up beneficial for assessing the patient’s health. The inclusion of self-reported clinical data in the questionnaire motivated physicians to assess patient responses. However, some barriers were emphasized, such as loss of a personal relationship with the patient and the risk of missing important symptoms in the absence of a face-to-face assessment. Conclusions: This study demonstrates the importance and practical use of remote monitoring among patients with CKD. Overall, the intervention was implemented as intended. We observed high patient adherence rates, and the physicians managed most questionnaires. Some physicians worried that distance from the patients made it unfeasible to use their “clinical glance,” posing a potential risk of overlooking crucial patients‘ symptoms. These findings underscore key considerations for the implementation of remote follow-up. Introducing a hybrid approach combining remote and face-to-face consultations may address these concerns. Trial Registration: ClinicalTrials.gov NCT03847766; https://clinicaltrials.gov/study/NCT03847766 %M 38656781 %R 10.2196/48173 %U https://formative.jmir.org/2024/1/e48173 %U https://doi.org/10.2196/48173 %U http://www.ncbi.nlm.nih.gov/pubmed/38656781 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e45545 %T Service Quality and Residents’ Preferences for Facilitated Self-Service Fundus Disease Screening: Cross-Sectional Study %A Lin,Senlin %A Ma,Yingyan %A Jiang,Yanwei %A Li,Wenwen %A Peng,Yajun %A Yu,Tao %A Xu,Yi %A Zhu,Jianfeng %A Lu,Lina %A Zou,Haidong %+ Shanghai Eye Diseases Prevention &Treatment Center/ Shanghai Eye Hospital, School of Medicine, Tongji University, No 1440, Hongqqiao Road, Shanghai, 200336, China, 86 02162539696, zouhaidong@sjtu.edu.cn %K digital technology %K screening %K self-service %K eye disease %K health economics evaluation %K health technology assessment %K disease screening %K artificial intelligence %K AI %K eye %K community %K effectiveness %K screening efficiency %K safety %D 2024 %7 17.4.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents’ preference for this new pattern are unclear. Objective: This study aimed to compare the service quality and residents’ preferences between facilitated self-service eye screening and traditional manual screening and to explore the relationships between the screening service’s quality and residents’ preferences. Methods: We conducted a cross-sectional study in Shanghai, China. Residents who underwent facilitated self-service fundus disease screening at one of the screening sites were assigned to the exposure group; those who were screened with a traditional fundus camera operated by an optometrist at an adjacent site comprised the control group. The primary outcome was the screening service quality, including effectiveness (image quality and screening efficiency), physiological discomfort, safety, convenience, and trustworthiness. The secondary outcome was the participants’ preferences. Differences in service quality and the participants’ preferences between the 2 groups were compared using chi-square tests separately. Subgroup analyses for exploring the relationships between the screening service’s quality and residents’ preference were conducted using generalized logit models. Results: A total of 358 residents enrolled; among them, 176 (49.16%) were included in the exposure group and the remaining 182 (50.84%) in the control group. Residents’ basic characteristics were balanced between the 2 groups. There was no significant difference in service quality between the 2 groups (image quality pass rate: P=.79; average screening time: P=.57; no physiological discomfort rate: P=.92; safety rate: P=.78; convenience rate: P=.95; trustworthiness rate: P=.20). However, the proportion of participants who were willing to use the same technology for their next screening was significantly lower in the exposure group than in the control group (P<.001). Subgroup analyses suggest that distrust in the facilitated self-service eye screening might increase the probability of refusal to undergo screening (P=.02). Conclusions: This study confirms that the facilitated self-service fundus disease screening pattern could achieve good service quality. However, it was difficult to reverse residents’ preferences for manual screening in a short period, especially when the original manual service was already excellent. Therefore, the digital transformation of health care must be cautious. We suggest that attention be paid to the residents’ individual needs. More efficient man-machine collaboration and personalized health management solutions based on large language models are both needed. %M 38630535 %R 10.2196/45545 %U https://www.jmir.org/2024/1/e45545 %U https://doi.org/10.2196/45545 %U http://www.ncbi.nlm.nih.gov/pubmed/38630535 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53000 %T Clinical Decision Support System for Guidelines-Based Treatment of Gonococcal Infections, Screening for HIV, and Prescription of Pre-Exposure Prophylaxis: Design and Implementation Study %A Karki,Saugat %A Shaw,Sarah %A Lieberman,Michael %A Pérez,Alejandro %A Pincus,Jonathan %A Jakhmola,Priya %A Tailor,Amrita %A Ogunrinde,Oyinkansola Bukky %A Sill,Danielle %A Morgan,Shane %A Alvarez,Miguel %A Todd,Jonathan %A Smith,Dawn %A Mishra,Ninad %+ Division of STD Prevention, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA, 30333, United States, 1 4047187483, skarki@cdc.gov %K clinical decision support systems %K CDS %K gonorrhea %K pre-exposure prophylaxis %K PrEP %K HIV %K sexually transmitted infections %K electronic health records %K guideline adherence %D 2024 %7 15.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: The syndemic nature of gonococcal infections and HIV provides an opportunity to develop a synergistic intervention tool that could address the need for adequate treatment for gonorrhea, screen for HIV infections, and offer pre-exposure prophylaxis (PrEP) for persons who meet the criteria. By leveraging information available on electronic health records, a clinical decision support (CDS) system tool could fulfill this need and improve adherence to Centers for Disease Control and Prevention (CDC) treatment and screening guidelines for gonorrhea, HIV, and PrEP. Objective: The goal of this study was to translate portions of CDC treatment guidelines for gonorrhea and relevant portions of HIV screening and prescribing PrEP that stem from a diagnosis of gonorrhea as an electronic health record–based CDS intervention. We also assessed whether this CDS solution worked in real-world clinic. Methods: We developed 4 tools for this CDS intervention: a form for capturing sexual history information (SmartForm), rule-based alerts (best practice advisory), an enhanced sexually transmitted infection (STI) order set (SmartSet), and a documentation template (SmartText). A mixed methods pre-post design was used to measure the feasibility, use, and usability of the CDS solution. The study period was 12 weeks with a baseline patient sample of 12 weeks immediately prior to the intervention period for comparison. While the entire clinic had access to the CDS solution, we focused on a subset of clinicians who frequently engage in the screening and treatment of STIs within the clinical site under the name “X-Clinic.” We measured the use of the CDS solution within the population of patients who had either a confirmed gonococcal infection or an STI-related chief complaint. We conducted 4 midpoint surveys and 3 key informant interviews to quantify perception and impact of the CDS solution and solicit suggestions for potential future enhancements. The findings from qualitative data were determined using a combination of explorative and comparative analysis. Statistical analysis was conducted to compare the differences between patient populations in the baseline and intervention periods. Results: Within the X-Clinic, the CDS alerted clinicians (as a best practice advisory) in one-tenth (348/3451, 10.08%) of clinical encounters. These 348 encounters represented 300 patients; SmartForms were opened for half of these patients (157/300, 52.33%) and was completed for most for them (147/300, 89.81%). STI test orders (SmartSet) were initiated by clinical providers in half of those patients (162/300, 54%). HIV screening was performed during about half of those patient encounters (191/348, 54.89%). Conclusions: We successfully built and implemented multiple CDC treatment and screening guidelines into a single cohesive CDS solution. The CDS solution was integrated into the clinical workflow and had a high rate of use. %M 38621237 %R 10.2196/53000 %U https://formative.jmir.org/2024/1/e53000 %U https://doi.org/10.2196/53000 %U http://www.ncbi.nlm.nih.gov/pubmed/38621237 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54912 %T Behavioral Activation Mobile App to Motivate Smokers to Quit: Feasibility and Pilot Randomized Controlled Trial %A Borrelli,Belinda %A Bartlett,Y Kiera %A Fulford,Daniel %A Frasco,Greg %A Armitage,Christopher J %A Wearden,Alison %+ Center for Behavioral Science Research, Henry M. Goldman School of Dental Medicine, Boston University, Floor 3, 560 Harrison Ave, Boston, MA, 02118, United States, 1 617 358 3358, belindab@bu.edu %K smoking cessation %K mobile app %K motivation %K depressed mood %K depression %K behavioral activation %K negative affect %K positive affect %K quit smoking %K health behavior change %D 2024 %7 4.4.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Behavioral activation (BA) is an evidence-based treatment for depression that fosters engagement in values-based activities to increase access to positive reinforcement. Depressed mood has been shown to hinder smoking cessation. Objective: This study determined the feasibility and preliminary efficacy of a mobile app to motivate smokers to quit by using BA and integrating motivational messages to quit smoking. Methods: Adult smokers (N=56; mean age 34.5, SD 9.52 years) who were not ready to quit smoking within 30 days were recruited from advertisements and randomized to either 8 weeks of the BA app (set 2 values-based activities per week+motivational messages+feedback on changes in smoking, mood, and values-based activities) or the control group (no app; received resources for quitting smoking). All participants completed the baseline and end-of-treatment web-based questionnaires. Controls also completed weekly web-based assessments, and BA app participants completed assessments through the app. Results: There were no dropouts and only 2 participants in each condition did not complete the end-of-treatment questionnaire. The results demonstrated that it is feasible to recruit smokers who are unmotivated to quit into a smoking cessation induction trial: 86% (57/66) of eligible participants were randomized (BA app: n=27; control: n=29). Participants reported high levels of satisfaction: 80% (20/25) of participants said they would recommend the BA app, there were moderate-to-high scores on the Mobile App Rating Scale, and 88% (22/25) of participants rated the app 3 stars or higher (out of 5). There were high levels of BA app engagement: 96% (26/27) of participants planned activities, and 67% (18/27) of participants planned 7 or more activities. High engagement was found even among those who were at the highest risk for continued smoking (low motivation to quit, low confidence to quit, and high negative affect). The results provided support for the hypothesized relationships between BA constructs: greater pleasant activity completion was associated with greater positive affect (b=0.37, SE 0.21; 95% CI –0.05 to 0.79; P=.08), and greater positive affect tended to predict fewer cigarettes smoked the next day (b=–0.19, SE 0.10; 95% CI –0.39 to 0.01; P=.06). Additionally, a greater number of activities planned was associated with lower negative affect (b=–0.26, SE 0.15; 95% CI –0.55 to 0.04; P=.09). Overall, 16% (4/25) of BA app participants set a quit date versus 4% (1/27) among controls, and there were promising (but not significant) trends for motivation and confidence to quit. Conclusions: The findings suggest that a mobile app intervention can be made appealing to smokers who are unmotivated to quit by focusing on aspects most important to them, such as mood management. This theory-based intervention has shown some initial support for the underlying theoretical constructs, and further efficacy testing is warranted in a fully powered trial. %M 38573739 %R 10.2196/54912 %U https://formative.jmir.org/2024/1/e54912 %U https://doi.org/10.2196/54912 %U http://www.ncbi.nlm.nih.gov/pubmed/38573739 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e46287 %T Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial %A Sheng,Yiyang %A Bond,Raymond %A Jaiswal,Rajesh %A Dinsmore,John %A Doyle,Julie %+ NetwellCASALA, Dundalk Institution of Technology, Dublin Road, PJ Carrolls Building, Dundalk Institute of Technology, Co.Louth, Ireland, Dundalk, A91 K584, Ireland, 353 894308214, shengexz@gmail.com %K aging %K digital health %K multimorbidity %K chronic disease %K engagement %K k-means clustering %D 2024 %7 28.3.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Multiple chronic conditions (multimorbidity) are becoming more prevalent among aging populations. Digital health technologies have the potential to assist in the self-management of multimorbidity, improving the awareness and monitoring of health and well-being, supporting a better understanding of the disease, and encouraging behavior change. Objective: The aim of this study was to analyze how 60 older adults (mean age 74, SD 6.4; range 65-92 years) with multimorbidity engaged with digital symptom and well-being monitoring when using a digital health platform over a period of approximately 12 months. Methods: Principal component analysis and clustering analysis were used to group participants based on their levels of engagement, and the data analysis focused on characteristics (eg, age, sex, and chronic health conditions), engagement outcomes, and symptom outcomes of the different clusters that were discovered. Results: Three clusters were identified: the typical user group, the least engaged user group, and the highly engaged user group. Our findings show that age, sex, and the types of chronic health conditions do not influence engagement. The 3 primary factors influencing engagement were whether the same device was used to submit different health and well-being parameters, the number of manual operations required to take a reading, and the daily routine of the participants. The findings also indicate that higher levels of engagement may improve the participants’ outcomes (eg, reduce symptom exacerbation and increase physical activity). Conclusions: The findings indicate potential factors that influence older adult engagement with digital health technologies for home-based multimorbidity self-management. The least engaged user groups showed decreased health and well-being outcomes related to multimorbidity self-management. Addressing the factors highlighted in this study in the design and implementation of home-based digital health technologies may improve symptom management and physical activity outcomes for older adults self-managing multimorbidity. %M 38546724 %R 10.2196/46287 %U https://www.jmir.org/2024/1/e46287 %U https://doi.org/10.2196/46287 %U http://www.ncbi.nlm.nih.gov/pubmed/38546724 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 13 %N %P e51974 %T Designing mHealth Apps to Incorporate Evidence-Based Techniques for Prolonging User Engagement %A Monachelli,Rebecca %A Davis,Sharon Watkins %A Barnard,Allison %A Longmire,Michelle %A Docherty,John P %A Oakley-Girvan,Ingrid %+ Medable Inc, 525 University Ave, Palo Alto, CA, 94301, United States, 1 8778206259, oakley@stanford.edu %K adherence %K app design %K attrition %K mHealth %K user engagement %K user experience %K proof-of-concept %D 2024 %7 26.3.2024 %9 Viewpoint %J Interact J Med Res %G English %X Maintaining user engagement with mobile health (mHealth) apps can be a challenge. Previously, we developed a conceptual model to optimize patient engagement in mHealth apps by incorporating multiple evidence-based methods, including increasing health literacy, enhancing technical competence, and improving feelings about participation in clinical trials. This viewpoint aims to report on a series of exploratory mini-experiments demonstrating the feasibility of testing our previously published engagement conceptual model. We collected data from 6 participants using an app that showed a series of educational videos and obtained additional data via questionnaires to illustrate and pilot the approach. The videos addressed 3 elements shown to relate to engagement in health care app use: increasing health literacy, enhancing technical competence, and improving positive feelings about participation in clinical trials. We measured changes in participants’ knowledge and feelings, collected feedback on the videos and content, made revisions based on this feedback, and conducted participant reassessments. The findings support the feasibility of an iterative approach to creating and refining engagement enhancements in mHealth apps. Systematically identifying the key evidence-based elements intended to be included in an app’s design and then systematically testing the implantation of each element separately until a satisfactory level of positive impact is achieved is feasible and should be incorporated into standard app design. While mHealth apps have shown promise, participants are more likely to drop out than to be retained. This viewpoint highlights the potential for mHealth researchers to test and refine mHealth apps using approaches to better engage users. %M 38416858 %R 10.2196/51974 %U https://www.i-jmr.org/2024/1/e51974 %U https://doi.org/10.2196/51974 %U http://www.ncbi.nlm.nih.gov/pubmed/38416858 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53294 %T Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial %A Li,Shiyu %A Du,Yan %A Miao,Hongyu %A Sharma,Kumar %A Li,Chengdong %A Yin,Zenong %A Brimhall,Bradley %A Wang,Jing %+ College of Nursing, Florida State University, Vivian M Duxbury Hall, 98 Varsity Way, Tallahassee, FL, 31306, United States, 1 850 644 3299, jingwang@nursing.fsu.edu %K self-monitoring %K adherence %K weight loss %K digital technology %K behavior change %K group-based trajectory modeling %K precision health %K mobile phone %D 2024 %7 20.3.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase. Objective: This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective. Methods: This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models. Results: Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: −6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: −0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09). Conclusions: The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders. Trial Registration: ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287 International Registered Report Identifier (IRRID): RR2-10.1016/j.cct.2022.106845 %M 38506903 %R 10.2196/53294 %U https://www.jmir.org/2024/1/e53294 %U https://doi.org/10.2196/53294 %U http://www.ncbi.nlm.nih.gov/pubmed/38506903 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e51236 %T Patient Engagement With and Perspectives on a Mobile Health Home Spirometry Intervention: Mixed Methods Study %A Liu,Andrew W %A Brown, III,William %A Madu,Ndubuisi E %A Maiorano,Ali R %A Bigazzi,Olivia %A Medina,Eli %A Sorric,Christopher %A Hays,Steven R %A Odisho,Anobel Y %+ Center for Digital Health Innovation, University of California, 1700 Owens St 541, San Francisco, CA, 94158, United States, 1 415 353 7171, anobel.odisho@ucsf.edu %K mobile health %K mHealth %K remote patient monitoring %K interview %K interviews %K dropout %K attrition %K eHealth %K methods %K telemedicine %K statistics %K numerical data %K patient-centered care %K spirometry %K lung transplant %K lung %K transplant %K transplants %K transplantation %K organ %K organs %K engagement %K monitor %K monitoring %K pulmonary %K respiratory %K lungs %K experience %K experiences %K device %K devices %K complication %K complications %D 2024 %7 20.3.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Patient engagement attrition in mobile health (mHealth) remote patient monitoring (RPM) programs decreases program benefits. Systemic disparities lead to inequities in RPM adoption and use. There is an urgent need to understand patients’ experiences with RPM in the real world, especially for patients who have stopped using the programs, as addressing issues faced by patients can increase the value of mHealth for patients and subsequently decrease attrition. Objective: This study sought to understand patient engagement and experiences in an RPM mHealth intervention in lung transplant recipients. Methods: Between May 4, 2020, and November 1, 2022, a total of 601 lung transplant recipients were enrolled in an mHealth RPM intervention to monitor lung function. The predictors of patient engagement were evaluated using multivariable logistic and linear regression. Semistructured interviews were conducted with 6 of 39 patients who had engaged in the first month but stopped using the program, and common themes were identified. Results: Patients who underwent transplant more than 1 year before enrollment in the program had 84% lower odds of engaging (odds ratio [OR] 0.16, 95% CI 0.07-0.35), 82% lower odds of submitting pulmonary function measurements (OR 0.18, 95% CI 0.09-0.33), and 78% lower odds of completing symptom checklists (OR 0.22, 95% CI 0.10-0.43). Patients whose primary language was not English had 78% lower odds of engaging compared to English speakers (OR 0.22, 95% CI 0.07-0.67). Interviews revealed 4 prominent themes: challenges with devices, communication breakdowns, a desire for more personal interactions and specific feedback with the care team about their results, understanding the purpose of the chat, and understanding how their data are used. Conclusions: Care delivery and patient experiences with RPM in lung transplant mHealth can be improved and made more equitable by tailoring outreach and enhancements toward non-English speakers and patients with a longer time between transplant and enrollment. Attention to designing programs to provide personalization through supplementary provider contact, education, and information transparency may decrease attrition rates. %M 38506896 %R 10.2196/51236 %U https://mhealth.jmir.org/2024/1/e51236 %U https://doi.org/10.2196/51236 %U http://www.ncbi.nlm.nih.gov/pubmed/38506896 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e49857 %T An Ecological Mobile Momentary Intervention to Support Dynamic Goal Pursuit: Feasibility and Acceptability Study %A O'Driscoll,Ciarán %A Singh,Aneesha %A Chichua,Iya %A Clodic,Joachim %A Desai,Anjali %A Nikolova,Dara %A Yap,Alex Jie %A Zhou,Irene %A Pilling,Stephen %+ CORE Data Lab, Centre for Outcomes Research and Effectiveness, University College London, Gower Street, London, WC1E 6BT, United Kingdom, 44 207679 1897, c.odriscoll@ucl.ac.uk %K goal pursuit %K ecological momentary intervention %K ecological momentary assessment %K mood %K dynamics %K network analysis %K MCII %K COM-B %K support %K pilot study %K training %K feasibility %K acceptability %K self-monitoring %K implementation %K psychological %K effectiveness %D 2024 %7 20.3.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Individuals can experience difficulties pursuing their goals amid multiple competing priorities in their environment. Effective goal dynamics require flexible and generalizable pursuit skills. Supporting successful goal pursuit requires a perpetually adapting intervention responsive to internal states. Objective: The purpose of this study was to (1) develop a flexible intervention that can adapt to an individual’s changing short to medium-term goals and be applied to their daily life and (2) examine the feasibility and acceptability of the just-in-time adaptive intervention for goal pursuit. Methods: This study involved 3 iterations to test and systematically enhance all aspects of the intervention. During the pilot phase, 73 participants engaged in an ecological momentary assessment (EMA) over 1 month. After week 1, they attended an intervention training session and received just-in-time intervention prompts during the following 3 weeks. The training employed the Capability, Opportunity, Motivation, and Behavior (COM-B) framework for goal setting, along with mental contrasting with implementation intentions (MCII). Subsequent prompts, triggered by variability in goal pursuit, guided the participants to engage in MCII in relation to their current goal. We evaluated feasibility and acceptability, efficacy, and individual change processes by combining intensive (single-case experimental design) and extensive methods. Results: The results suggest that the digital intervention was feasible and acceptable to participants. Compliance with the intervention was high (n=63, 86%). The participants endorsed high acceptability ratings relating to both the study procedures and the intervention. All participants (N=73, 100%) demonstrated significant improvements in goal pursuit with an average difference of 0.495 units in the outcome (P<.001). The results of the dynamic network modeling suggest that self-monitoring behavior (EMA) and implementing the MCII strategy may aid in goal reprioritization, where goal pursuit itself is a driver of further goal pursuit. Conclusions: This pilot study demonstrated the feasibility and acceptability of a just-in-time adaptive intervention among a nonclinical adult sample. This intervention used self-monitoring of behavior, the COM-B framework, and MCII strategies to improve dynamic goal pursuit. It was delivered via an Ecological Momentary Intervention (EMI) procedure. Future research should consider the utility of this approach as an additional intervention element within psychological interventions to improve goal pursuit. Sustaining goal pursuit throughout interventions is central to their effectiveness and warrants further evaluation. %M 38506904 %R 10.2196/49857 %U https://formative.jmir.org/2024/1/e49857 %U https://doi.org/10.2196/49857 %U http://www.ncbi.nlm.nih.gov/pubmed/38506904 %0 Journal Article %@ 2152-7202 %I JMIR Publications %V 16 %N %P e50242 %T Patients’ Perspectives on Plans Generated During Primary Care Visits and Self-Reported Adherence at 3 Months: Data From a Randomized Trial %A Stults,Cheryl D %A Mazor,Kathleen M %A Cheung,Michael %A Ruo,Bernice %A Li,Martina %A Walker,Amanda %A Saphirak,Cassandra %A Vaida,Florin %A Singh,Sonal %A Fisher,Kimberly A %A Rosen,Rebecca %A Yood,Robert %A Garber,Lawrence %A Longhurst,Christopher %A Kallenberg,Gene %A Yu,Edward %A Chan,Albert %A Millen,Marlene %A Tai-Seale,Ming %+ Palo Alto Medical Foundation Research Institute, Center for Health Systems Research, Sutter Health, 795 El Camino Real, Ames Building, Palo Alto, CA, 94301, United States, 1 650 853 2346, cheryl.stults@sutterhealth.org %K primary care %K survey %K patient adherence %K adherence %K self-reported %K surveys %K content analysis %K RCT %K randomized %K controlled trial %K controlled trials %K plan %K plans %K willingness %K experience %K experiences %K attitude %K attitudes %K opinion %K opinion %K perception %K perceptions %K perspective %K perspectives %D 2024 %7 14.3.2024 %9 Original Paper %J J Particip Med %G English %X Background: Effective primary care necessitates follow-up actions by the patient beyond the visit. Prior research suggests room for improvement in patient adherence. Objective: This study sought to understand patients’ views on their primary care visits, the plans generated therein, and their self-reported adherence after 3 months. Methods: As part of a large multisite cluster randomized pragmatic trial in 3 health care organizations, patients completed 2 surveys—the first within 7 days after the index primary care visit and another 3 months later. For this analysis of secondary outcomes, we combined the results across all study participants to understand patient adherence to care plans. We recorded patient characteristics and survey responses. Cross-tabulation and chi-square statistics were used to examine bivariate associations, adjusting for multiple comparisons when appropriate. We used multivariable logistic regression to assess how patients’ intention to follow, agreement, and understanding of their plans impacted their plan adherence, allowing for differences in individual characteristics. Qualitative content analysis was conducted to characterize the patient’s self-reported plans and reasons for adhering (or not) to the plan 3 months later. Results: Of 2555 patients, most selected the top box option (9=definitely agree) that they felt they had a clear plan (n=2011, 78%), agreed with the plan (n=2049, 80%), and intended to follow the plan (n=2108, 83%) discussed with their provider at the primary care visit. The most common elements of the plans reported included reference to exercise (n=359, 14.1%), testing (laboratory, imaging, etc; n=328, 12.8%), diet (n=296, 11.6%), and initiation or adjustment of medications; (n=284, 11.1%). Patients who strongly agreed that they had a clear plan, agreed with the plan, and intended to follow the plan were all more likely to report plan completion 3 months later (P<.001) than those providing less positive ratings. Patients who reported plans related to following up with the primary care provider (P=.008) to initiate or adjust medications (P≤.001) and to have a specialist visit were more likely to report that they had completely followed the plan (P=.003). Adjusting for demographic variables, patients who indicated intent to follow their plan were more likely to follow-through 3 months later (P<.001). Patients’ reasons for completely following the plan were mainly that the plan was clear (n=1114, 69.5%), consistent with what mattered (n=1060, 66.1%), and they were determined to carry through with the plan (n=887, 53.3%). The most common reasons for not following the plan were lack of time (n=217, 22.8%), having decided to try a different approach (n=105, 11%), and the COVID-19 pandemic impacted the plan (n=105, 11%). Conclusions: Patients’ initial assessment of their plan as clear, their agreement with the plan, and their initial willingness to follow the plan were all strongly related to their self-reported completion of the plan 3 months later. Patients whose plans involved lifestyle changes were less likely to report that they had “completely” followed their plan. Trial Registration: ClinicalTrials.gov NCT03385512; https://clinicaltrials.gov/study/NCT03385512 International Registered Report Identifier (IRRID): RR2-10.2196/30431 %M 38483458 %R 10.2196/50242 %U https://jopm.jmir.org/2024/1/e50242 %U https://doi.org/10.2196/50242 %U http://www.ncbi.nlm.nih.gov/pubmed/38483458 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e50528 %T A Mobile Applet for Assessing Medication Adherence and Managing Adverse Drug Reactions Among Patients With Cancer: Usability and Utility Study %A Ni,Chenxu %A Wang,Yi-fu %A Zhang,Yun-ting %A Yuan,Min %A Xu,Qing %A Shen,Fu-ming %A Li,Dong-Jie %A Huang,Fang %+ Shanghai Tenth People’s Hospital, 301 Middle Yanchang Road, Shanghai, 200072, China, 86 66302570, hazel_huang@126.com %K WeChat applet %K usability testing %K utility testing %K cancer patients %K patients %K cancer %K qualitative study %D 2024 %7 29.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Medication adherence and the management of adverse drug reactions (ADRs) are crucial to the efficacy of antitumor drugs. A WeChat applet, also known as a “Mini Program,” is similar to the app but has marked advantages. The development and use of a WeChat applet makes follow-up convenient for patients with cancer. Objective: This study aimed to assess the usability and utility of a newly developed WeChat applet, “DolphinCare,” among patients with cancer in Shanghai. Methods: A qualitative methodology was used to obtain an in-depth understanding of the experiences of patients with cancer when using DolphinCare from the usability and utility aspects. The development phase consisted of 2 parts: alpha and beta testing. Alpha testing combined the theory of the Fogg Behavior Model and the usability model. Alpha testing also involved testing the design of DolphinCare using a conceptual framework, which included factors that could affect medication adherence and ADRs. Beta testing was conducted using in-depth interviews. In-depth interviews allowed us to assist the patients in using DolphinCare and understand whether they liked or disliked DolphinCare and found it useful. Results: We included participants who had an eHealth Literacy Scale (eHEALS) score of ≥50%, and a total of 20 participants were interviewed consecutively. The key positive motivators described by interviewers were to be reminded to take their medications and to alleviate their ADRs. The majority of the patients were able to activate and use DolphinCare by themselves. Most patients indicated that their trigger to follow-up DolphinCare was the recommendation of their known and trusted health care professionals. All participants found that labels containing the generic names of their medication and the medication reminders were useful, including timed pop-up push notifications and text alerts. The applet presented the corresponding information collection forms of ADRs to the patient to fill out. The web-based consultation system enables patients to consult pharmacists or physicians in time when they have doubts about medications or have ADRs. The applet had usabilities and utilities that could improve medication adherence and the management of ADRs among patients with cancer. Conclusions: This study provides preliminary evidence regarding the usability and utility of this type of WeChat applet among patients with cancer, which is expected to be promoted for managing follow-up among other patients with other chronic disease. %M 38421700 %R 10.2196/50528 %U https://formative.jmir.org/2024/1/e50528 %U https://doi.org/10.2196/50528 %U http://www.ncbi.nlm.nih.gov/pubmed/38421700 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e48168 %T Attrition in Conversational Agent–Delivered Mental Health Interventions: Systematic Review and Meta-Analysis %A Jabir,Ahmad Ishqi %A Lin,Xiaowen %A Martinengo,Laura %A Sharp,Gemma %A Theng,Yin-Leng %A Tudor Car,Lorainne %+ Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, 11 Mandalay Road, Level 18, Singapore, 308232, Singapore, 65 69041258, lorainne.tudor.car@ntu.edu.sg %K conversational agent %K chatbot %K mental health %K mHealth %K attrition %K dropout %K mobile phone %K artificial intelligence %K AI %K systematic review %K meta-analysis %K digital health interventions %D 2024 %7 27.2.2024 %9 Review %J J Med Internet Res %G English %X Background: Conversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials. Objective: This review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition. Methods: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings. Results: The systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition. Conclusions: Our results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415 %M 38412023 %R 10.2196/48168 %U https://www.jmir.org/2024/1/e48168 %U https://doi.org/10.2196/48168 %U http://www.ncbi.nlm.nih.gov/pubmed/38412023 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 8 %N %P e52576 %T User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study %A Björnsdottir,Sigridur %A Ulfsdottir,Hildigunnur %A Gudmundsson,Elias Freyr %A Sveinsdottir,Kolbrun %A Isberg,Ari Pall %A Dobies,Bartosz %A Akerlie Magnusdottir,Gudlaug Erla %A Gunnarsdottir,Thrudur %A Karlsdottir,Tekla %A Bjornsdottir,Gudlaug %A Sigurdsson,Sigurdur %A Oddsson,Saemundur %A Gudnason,Vilmundur %+ Department of Endocrinology, Metabolism and Diabetes, Karolinska Institutet, Solnavägen 1, Stockholm, 171 77, Sweden, 46 8 524 800 00, sigridur.bjornsdottir@ki.se %K digital health program %K nonalcoholic fatty liver disease %K NAFLD %K cardiometabolic health %K digital therapeutics %K liver %K chronic %K hepatic %K cardiometabolic %K cardiovascular %K cardiology %K weight %K acceptability %K digital health %K metabolic syndrome %K diabetic %K diabetes %K diabetics %K type 2 %K BMI %K lifestyle %K exercise %K physical activity %K coaching %K diet %K dietary %K nutrition %K nutritional %K patient education %K coach %K feasibility %K fat %K body composition %D 2024 %7 15.2.2024 %9 Original Paper %J JMIR Cardio %G English %X Background: Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the world. Common comorbidities are central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome. Cardiovascular disease is the most common cause of death among people with NAFLD, and lifestyle changes can improve health outcomes. Objective: This study aims to explore the acceptability of a digital health program in terms of engagement, retention, and user satisfaction in addition to exploring changes in clinical outcomes, such as weight, cardiometabolic risk factors, and health-related quality of life. Methods: We conducted a prospective, open-label, single-arm, 12-week study including 38 individuals with either a BMI >30, metabolic syndrome, or type 2 diabetes mellitus and NAFLD screened by FibroScan. An NAFLD-specific digital health program focused on disease education, lowering carbohydrates in the diet, food logging, increasing activity level, reducing stress, and healthy lifestyle coaching was offered to participants. The coach provided weekly feedback on food logs and other in-app activities and opportunities for participants to ask questions. The coaching was active throughout the 12-week intervention period. The primary outcome was feasibility and acceptability of the 12-week program, assessed through patient engagement, retention, and satisfaction with the program. Secondary outcomes included changes in weight, liver fat, body composition, and other cardiometabolic clinical parameters at baseline and 12 weeks. Results: In total, 38 individuals were included in the study (median age 59.5, IQR 46.3-68.8 years; n=23, 61% female). Overall, 34 (89%) participants completed the program and 29 (76%) were active during the 12-week program period. The median satisfaction score was 6.3 (IQR 5.8-6.7) of 7. Mean weight loss was 3.5 (SD 3.7) kg (P<.001) or 3.2% (SD 3.4%), with a 2.2 (SD 2.7) kg reduction in fat mass (P<.001). Relative liver fat reduction was 19.4% (SD 23.9%). Systolic blood pressure was reduced by 6.0 (SD 13.5) mmHg (P=.009). The median reduction was 0.14 (IQR 0-0.47) mmol/L for triglyceride levels (P=.003), 3.2 (IQR 0.0-5.4) µU/ml for serum insulin (s-insulin) levels (P=.003), and 0.5 (IQR –0.7 to 3.8) mmol/mol for hemoglobin A1c (HbA1c) levels (P=.03). Participants who were highly engaged (ie, who used the app at least 5 days per week) had greater weight loss and liver fat reduction. Conclusions: The 12-week-long digital health program was feasible for individuals with NAFLD, receiving high user engagement, retention, and satisfaction. Improved liver-specific and cardiometabolic health was observed, and more engaged participants showed greater improvements. This digital health program could provide a new tool to improve health outcomes in people with NAFLD. Trial Registration: Clinicaltrials.gov NCT05426382; https://clinicaltrials.gov/study/NCT05426382 %M 38152892 %R 10.2196/52576 %U https://cardio.jmir.org/2024/1/e52576 %U https://doi.org/10.2196/52576 %U http://www.ncbi.nlm.nih.gov/pubmed/38152892 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e45942 %T Mobile App Intervention of a Randomized Controlled Trial for Patients With Obesity and Those Who Are Overweight in General Practice: User Engagement Analysis Quantitative Study %A Buss,Vera Helen %A Barr,Margo %A Parker,Sharon M %A Kabir,Alamgir %A Lau,Annie Y S %A Liaw,Siaw-Teng %A Stocks,Nigel %A Harris,Mark F %+ Centre for Primary Health Care and Equity, University of New South Wales, AGSM Building, High Street, Kensington Campus, Sydney, 2052, Australia, 61 290656041, Margo.barr@unsw.edu.au %K health literacy %K primary health care %K mobile application %K overweight %K vulnerable populations %K health behavior %K mHealth %K obesity %K weight loss %K mysnapp app %K mobile phone %D 2024 %7 9.2.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The Health eLiteracy for Prevention in General Practice trial is a primary health care–based behavior change intervention for weight loss in Australians who are overweight and those with obesity from lower socioeconomic areas. Individuals from these areas are known to have low levels of health literacy and are particularly at risk for chronic conditions, including diabetes and cardiovascular disease. The intervention comprised health check visits with a practice nurse, a purpose-built patient-facing mobile app (mysnapp), and a referral to telephone coaching. Objective: This study aimed to assess mysnapp app use, its user profiles, the duration and frequency of use within the Health eLiteracy for Prevention in General Practice trial, its association with other intervention components, and its association with study outcomes (health literacy and diet) to determine whether they have significantly improved at 6 months. Methods: In 2018, a total of 22 general practices from 2 Australian states were recruited and randomized by cluster to the intervention or usual care. Patients who met the main eligibility criteria (ie, BMI>28 in the previous 12 months and aged 40-74 years) were identified through the clinical software. The practice staff then provided the patients with details about this study. The intervention consisted of a health check with a practice nurse and a lifestyle app, a telephone coaching program, or both depending on the participants’ choice. Data were collected directly through the app and combined with data from the 6-week health check with the practice nurses, the telephone coaching, and the participants’ questionnaires at baseline and 6-month follow-up. The analyses comprised descriptive and inferential statistics. Results: Of the 120 participants who received the intervention, 62 (52%) chose to use the app. The app and nonapp user groups did not differ significantly in demographics or prior recent hospital admissions. The median time between first and last app use was 52 (IQR 4-95) days, with a median of 5 (IQR 2-10) active days. App users were significantly more likely to attend the 6-week health check (2-sided Fisher exact test; P<.001) and participate in the telephone coaching (2-sided Fisher exact test; P=.007) than nonapp users. There was no association between app use and study outcomes shown to have significantly improved (health literacy and diet) at 6 months. Conclusions: Recruitment and engagement were difficult for this study in disadvantaged populations with low health literacy. However, app users were more likely to attend the 6-week health check and participate in telephone coaching, suggesting that participants who opted for several intervention components felt more committed to this study. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12617001508369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373505 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-023239 %M 38335014 %R 10.2196/45942 %U https://mhealth.jmir.org/2024/1/e45942 %U https://doi.org/10.2196/45942 %U http://www.ncbi.nlm.nih.gov/pubmed/38335014 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e51225 %T The Impact of Intervention Design on User Engagement in Digital Therapeutics Research: Factorial Experiment With a Mixed Methods Study %A Lee,Hyerim %A Choi,Eung Ho %A Shin,Jung U %A Kim,Tae-Gyun %A Oh,Jooyoung %A Shin,Bokyoung %A Sim,Jung Yeon %A Shin,Jaeyong %A Kim,Meelim %+ Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, Atkinson Hall, 9500 Gilman Dr, La Jolla, San Diego, CA, 92121, United States, 1 323 776 5171, mek007@health.ucsd.edu %K atopic %K dermatitis %K experimental design %K mobile health %K patient engagement %K research methodology %D 2024 %7 9.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: User engagement is crucial for digital therapeutics (DTx) effectiveness; due to variations in the conceptualization of engagement and intervention design, assessment and retention of engagement remain challenging. Objective: We investigated the influence of the perceived acceptability of experimental intervention components and satisfaction with core intervention components in DTx on user engagement, while also identifying potential barriers and facilitators to user engagement. Methods: We conducted a mixed methods study with a 2 × 2 factorial design, involving 12 outpatients with atopic dermatitis. Participants were randomized into 4 experimental groups based on push notification (“basic” or “advanced”) and human coach (“on” or “off”) experimental intervention components. All participants engaged in self-monitoring and learning courses as core intervention components within an app-based intervention over 8 weeks. Data were collected through in-app behavioral data, physician- and self-reported questionnaires, and semistructured interviews assessed at baseline, 4 weeks, and 8 weeks. Descriptive statistics and thematic analysis were used to evaluate user engagement, perceived acceptability of experimental intervention components (ie, push notification and human coach), satisfaction with core intervention components (ie, self-monitoring and learning courses), and intervention effectiveness through clinical outcomes. Results: The primary outcome indicated that group 4, provided with “advanced-level push notifications” and a “human coach,” showed higher completion rates for self-monitoring forms and learning courses compared to the predetermined threshold of clinical significance. Qualitative data analysis revealed three key themes: (1) perceived acceptability of the experimental intervention components, (2) satisfaction with the core intervention components, and (3) suggestions for improvement in the overall intervention program. Regarding clinical outcomes, the Perceived Stress Scale and Dermatology Life Quality Index scores presented the highest improvement in group 4. Conclusions: These findings will help refine the intervention and inform the design of a subsequent randomized trial to test its effectiveness. Furthermore, this design may serve as a model for broadly examining and optimizing overall engagement in DTx and for future investigation into the complex relationship between engagement and clinical outcomes. Trial Registration: Clinical Research Information Service KCT0007675; http://tinyurl.com/2m8rjrmv %M 38335015 %R 10.2196/51225 %U https://formative.jmir.org/2024/1/e51225 %U https://doi.org/10.2196/51225 %U http://www.ncbi.nlm.nih.gov/pubmed/38335015 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e48880 %T Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study %A Schröder,Sonja %A Buntrock,Claudia %A Neumann,Louisa %A Müller,Jürgen L %A Fromberger,Peter %+ Clinic for Psychiatry and Psychotherapy – Forensic Psychiatry, University Medical Center Göttingen, Rosdorfer Weg 70, Göttingen, 37081, Germany, 49 5514022114, sonja.schroeder@med.uni-goettingen.de %K mHealth %K web-based intervention %K acceptance %K Unified Theory of Acceptance and Use of Technology %K UTAUT %K sexual offenses against children %K child abuse %K child pornography %K children %K sexual offense %K cross-sectional study %K community %K anxiety %K psychiatry %D 2024 %7 26.1.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Individuals who have committed sexual offenses against children often have difficulties finding treatment, despite its potential effectiveness. Although the development of web-based interventions could enhance therapeutic supply, up to now the acceptance thereof among this target group is unknown. Objective: For the first time, this study assesses the acceptance of a web-based intervention among individuals who committed sexual offenses against children and analyzes variables that predict acceptance. Following the Unified Theory of Acceptance and Use of Technology (UTAUT), it is assumed that acceptance of web-based interventions in individuals who have committed sexual offenses against children follows the same mechanisms as for individuals in general psychiatry. Methods: This cross-sectional study is based on the data from an ongoing clinical trial (@myTabu) evaluating the effectiveness of a web-based intervention in individuals who committed sexual offenses against children (N=113). Acceptance level was measured using a questionnaire based on the UTAUT and modified for the target group. Furthermore, predictors of acceptance from the UTAUT (performance expectancy, effort expectancy, and social influence [SI]), attitudes toward web-based interventions, and internet anxiety were assessed at baseline. Results: Most participants (61.1%, 69/113), reported high acceptance, while 36.3% (41/113) of them indicated moderate acceptance, and 2.7% (3/113) of them expressed low acceptance. In a linear regression model, the predictors explained 41.2% of the variance (F11,101=9.055; P=.01). Attitudes toward web-based interventions (B=0.398, 95% CI 0.16-0.64; P=.001) and SI (B=0.183, 95% CI 0.03-0.38; P=.04) significantly predicted acceptance. Post hoc explorative analysis showed that the participants’ belief that people close to them would recommend the use of a web-based intervention is a predictor of acceptance. In contrast, the belief that their community supervisor would recommend the use thereof was not predictive in this respect. Conclusions: For the participants of this study, we identified high acceptance of web-based interventions for the majority of participants. SI and the participants’ attitudes toward web-based interventions were important in predicting acceptance. Trial Registration: German Clinical Trial Registration (DRKS, Deutsches Register Klinischer Studien) DRKS 00021256; https://drks.de/search/de/trial/DRKS00021256 %M 38277200 %R 10.2196/48880 %U https://formative.jmir.org/2024/1/e48880 %U https://doi.org/10.2196/48880 %U http://www.ncbi.nlm.nih.gov/pubmed/38277200 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e44214 %T Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial %A White,Katie M %A Carr,Ewan %A Leightley,Daniel %A Matcham,Faith %A Conde,Pauline %A Ranjan,Yatharth %A Simblett,Sara %A Dawe-Lane,Erin %A Williams,Laura %A Henderson,Claire %A Hotopf,Matthew %+ Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom, 44 020 7848 0002, katie.white@kcl.ac.uk %K remote measurement %K technology %K engagement %K app %K depression %K smartphones %K wearable devices %K engagement %K symptom tracking %K self-awareness %K community %K mobile phone %D 2024 %7 19.1.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Multiparametric remote measurement technologies (RMTs), which comprise smartphones and wearable devices, have the potential to revolutionize understanding of the etiology and trajectory of major depressive disorder (MDD). Engagement with RMTs in MDD research is of the utmost importance for the validity of predictive analytical methods and long-term use and can be conceptualized as both objective engagement (data availability) and subjective engagement (system usability and experiential factors). Positioning the design of user interfaces within the theoretical framework of the Behavior Change Wheel can help maximize effectiveness. In-app components containing information from credible sources, visual feedback, and access to support provide an opportunity to promote engagement with RMTs while minimizing team resources. Randomized controlled trials are the gold standard in quantifying the effects of in-app components on engagement with RMTs in patients with MDD. Objective: This study aims to evaluate whether a multiparametric RMT system with theoretically informed notifications, visual progress tracking, and access to research team contact details could promote engagement with remote symptom tracking over and above the system as usual. We hypothesized that participants using the adapted app (intervention group) would have higher engagement in symptom monitoring, as measured by objective and subjective engagement. Methods: A 2-arm, parallel-group randomized controlled trial (participant-blinded) with 1:1 randomization was conducted with 100 participants with MDD over 12 weeks. Participants in both arms used the RADAR-base system, comprising a smartphone app for weekly symptom assessments and a wearable Fitbit device for continuous passive tracking. Participants in the intervention arm (n=50, 50%) also had access to additional in-app components. The primary outcome was objective engagement, measured as the percentage of weekly questionnaires completed during follow-up. The secondary outcomes measured subjective engagement (system engagement, system usability, and emotional self-awareness). Results: The levels of completion of the Patient Health Questionnaire-8 (PHQ-8) were similar between the control (67/97, 69%) and intervention (66/97, 68%) arms (P value for the difference between the arms=.83, 95% CI −9.32 to 11.65). The intervention group participants reported slightly higher user engagement (1.93, 95% CI −1.91 to 5.78), emotional self-awareness (1.13, 95% CI −2.93 to 5.19), and system usability (2.29, 95% CI −5.93 to 10.52) scores than the control group participants at follow-up; however, all CIs were wide and included 0. Process evaluation suggested that participants saw the in-app components as helpful in increasing task completion. Conclusions: The adapted system did not increase objective or subjective engagement in remote symptom tracking in our research cohort. This study provides an important foundation for understanding engagement with RMTs for research and the methodologies by which this work can be replicated in both community and clinical settings. Trial Registration: ClinicalTrials.gov NCT04972474; https://clinicaltrials.gov/ct2/show/NCT04972474 International Registered Report Identifier (IRRID): RR2-10.2196/32653 %M 38241070 %R 10.2196/44214 %U https://mhealth.jmir.org/2024/1/e44214 %U https://doi.org/10.2196/44214 %U http://www.ncbi.nlm.nih.gov/pubmed/38241070 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e52197 %T Predictors of Use and Drop Out From a Web-Based Cognitive Behavioral Therapy Program and Health Community for Depression and Anxiety in Primary Care Patients: Secondary Analysis of a Randomized Controlled Trial %A Rotondi,Armando J %A Belnap,Bea Herbeck %A Rothenberger,Scott %A Feldman,Robert %A Hanusa,Barbara %A Rollman,Bruce L %+ Mental Illness Research Education and Clinical Center, VA Pittsburgh Healthcare System, Veterans Administration, Research Office Building (151R-U), University Drive C, Pittsburgh, PA, 15240, United States, 1 412 360 2494, armandorotondi1@gmail.com %K e-mental health %K user engagement %K initiation %K discontinue %K depression %K anxiety %K cognitive behavioral therapy %K computerized CBT %K online health community %K collaborative care %K internet support group %D 2024 %7 17.1.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: A previously reported study examined the treatment of primary care patients with at least moderate severity depressive or anxiety symptoms via an evidence-based computerized cognitive behavioral therapy (CCBT) program (Beating the Blues) and an online health community (OHC) that included a moderated internet support group. The 2 treatment arms proved to be equally successful at 6-month follow-up. Objective: Although highly promising, e-mental health treatment programs have encountered high rates of noninitiation, poor adherence, and discontinuation. Identifying ways to counter these tendencies is critical for their success. To further explore these issues, this study identified the primary care patient characteristics that increased the chances patients would not initiate the use of an intervention, (ie, not try it even once), initiate use, and go on to discontinue or continue to use an intervention. Methods: The study had 3 arms: one received access to CCBT (n=301); another received CCBT plus OHC (n=302), which included a moderated internet support group; and the third received usual care (n=101). Participants in the 2 active intervention arms of the study were grouped together for analyses of CCBT use (n=603) because both arms had access to CCBT, and there were no differences in outcomes between the 2 arms. Analyses of OHC use were based on 302 participants who were randomized to that arm. Results: Several baseline patient characteristics were associated with failure to initiate the use of CCBT, including having worse physical health (measured by the Short Form Health Survey Physical Components Score, P=.01), more interference from pain (by the Patient-Reported Outcomes Measurement Information System Pain Interference score, P=.048), less formal education (P=.02), and being African American or another US minority group (P=.006). Characteristics associated with failure to initiate use of the OHC were better mental health (by the Short Form Health Survey Mental Components Score, P=.04), lower use of the internet (P=.005), and less formal education (P=.001). Those who initiated the use of the CCBT program but went on to complete less of the program had less formal education (P=.01) and lower severity of anxiety symptoms (P=.03). Conclusions: This study found that several patient characteristics predicted whether a patient was likely to not initiate use or discontinue the use of CCBT or OHC. These findings have clear implications for actionable areas that can be targeted during initial and ongoing engagement activities designed to increase patient buy-in, as well as increase subsequent use and the resulting success of eHealth programs. Trial Registration: ClinicalTrials.gov NCT01482806; https://clinicaltrials.gov/study/NCT01482806 %M 38231552 %R 10.2196/52197 %U https://mental.jmir.org/2024/1/e52197 %U https://doi.org/10.2196/52197 %U http://www.ncbi.nlm.nih.gov/pubmed/38231552 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 7 %N %P e44199 %T The Report of Access and Engagement With Digital Health Interventions Among Children and Young People: Systematic Review %A Whitehead,Lisa %A Robinson,Suzanne %A Arabiat,Diana %A Jenkins,Mark %A Morelius,Evalotte %+ School of Nursing and Midwifery, Edith Cowan University, 270 Joondalup Drive, Joondalup, 6027, Australia, 61 438145638, l.whitehead@ecu.edu.au %K access %K engagement %K digital health technology %K mobile phone %K children %D 2024 %7 17.1.2024 %9 Review %J JMIR Pediatr Parent %G English %X Background: Digital health interventions are increasingly used to deliver health-related interventions for children and young people to change health behaviors and improve health outcomes. Digital health interventions have the potential to enhance access to and engagement with children and young people; however, they may also increase the divide between those who can access technology and are supported to engage and those who are not. This review included studies that reported on the access to or engagement with digital health interventions among children and young people. Objective: This review aims to identify and report on access and engagement in studies involving digital health interventions among children and young people. Methods: A systematic review following the Joanna Briggs Institute methods for conducting systematic reviews was conducted. An electronic literature search was conducted for all studies published between January 1, 2010, and August 2022, across sources, including MEDLINE, CINAHL, and PsycINFO. Studies were included if they examined any aspect of access or engagement in relation to interventions among children and young people. The quality of the included papers was assessed, and data were extracted. Data were considered for meta-analysis, where possible. Results: A total of 3292 references were identified using search terms. Following the exclusion of duplicates and review by inclusion criteria, 40 studies were independently appraised for their methodological quality. A total of 16 studies were excluded owing to their low assessed quality and flawed critical elements in the study design. The studies focused on a variety of health conditions; type 1 diabetes, weight management and obesity, mental health issues, and sexual health were the predominant conditions. Most studies were conducted in developed countries, with most of them being conducted in the United States. Two studies reported data related to access and considered ethnicity and social determinants. No studies used strategies to enhance or increase access. All studies included in the review reported on at least 1 aspect of engagement. Engagement with interventions was measured in relation to frequency of engagement, with no reference to the concept of effective engagement. Conclusions: Most digital health interventions do not consider the factors that can affect access and engagement. Of those studies that measured either access or engagement or both, few sought to implement strategies to improve access or engagement to address potential disparities between groups. Although the literature to date provides some insight into access and engagement and how these are addressed in digital health interventions, there are major limitations in understanding how both can be enhanced to promote equity. Consideration of both access and engagement is vital to ensure that children and young people have the ability to participate in studies. Trial Registration: PROSPERO CRD42020170874; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=170874 %M 38231560 %R 10.2196/44199 %U https://pediatrics.jmir.org/2024/1/e44199 %U https://doi.org/10.2196/44199 %U http://www.ncbi.nlm.nih.gov/pubmed/38231560 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e43683 %T Mapping the Cardiometabolic Patient Experience and Self-Care Behaviors to Inform Design, Implementation, and Persistent Use of Digital Health Care Solutions: Mixed Methods Study %A Liska,Jan %A Mical,Marie %A Maillard,Christophe %A Dessapt,Cécile %A Bendig,Europa %A Mai,Daniel %A Piette,John D %A De Geest,Sabina %A Fontaine,Guillaume %+ Sanofi, 46-48 Avenue de la Grande Armée, Paris, 75017, France, 33 141247000, Jan.Liska@sanofi.com %K self-care %K adherence %K digital health %K design %K implementation %K coronary %K type 2 diabetes %K care %K patient engagement %K behavior %K interview %K treatment %K tool %K digital tool %K support %D 2024 %7 12.1.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Cardiometabolic conditions including acute coronary syndrome (ACS) and type 2 diabetes (T2D) require comprehensive care and patient engagement in self-care behaviors, and the drivers of those behaviors at the individual and health system level are still poorly understood. Objective: We aim to gain insights into self-care behaviors of individuals with cardiometabolic conditions. Methods: A convenience sample of 98 adult patients with ACS and T2D was recruited in the United States, Germany, and Taiwan to participate in a mixed methods study using ethnographic methods. All participants completed 7-day web-based diaries tracking their level of engagement, and 48 completed 90-minute web-based semistructured interviews between February 4, 2021, and March 27, 2021, focusing on themes including moments of engagement. Qualitative analysis identified factors influencing self-care practices and a Patient Mind States Model prototype. Results: Patient reports indicate that many patients feel social pressure to adhere to treatment. Patients’ experience can be understood within 5 categories defined in terms of their degree of engagement and adherence (“ignoring,” “struggling,” “juggling,” “controlling,” and “reframing”). Conclusions: For people living with ACS and T2D, the self-care journey is defined by patterns of patient experiences, which can identify areas that tailored digital health care interventions may play a meaningful role. %M 38214969 %R 10.2196/43683 %U https://formative.jmir.org/2024/1/e43683 %U https://doi.org/10.2196/43683 %U http://www.ncbi.nlm.nih.gov/pubmed/38214969 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e47321 %T Use and Engagement With Low-Intensity Cognitive Behavioral Therapy Techniques Used Within an App to Support Worry Management: Content Analysis of Log Data %A Farrand,Paul %A Raue,Patrick J %A Ward,Earlise %A Repper,Dean %A Areán,Patricia %+ Clinical Education, Development and Research, Faculty of Health and Life Sciences, University of Exeter, Sir Henry Wellcome Building for Mood Disorders Reserach, Perry Road, Exeter, EX4 4QG, United Kingdom, 44 01392725793, p.a.farrand@exeter.ac.uk %K cognitive behavioral therapy %K low-intensity %K mCBT %K app %K log data %K worry management %K CBT %K management %K application %K therapy %K implementation %K treatment %K symptoms %K anxiety %K worry %K engagement %D 2024 %7 10.1.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Low-intensity cognitive behavioral therapy (LICBT) has been implemented by the Improving Access to Psychological Therapies services across England to manage excessive worry associated with generalized anxiety disorder and support emotional well-being. However, barriers to access limit scalability. A solution has been to incorporate LICBT techniques derived from an evidence-based protocol within the Iona Mind Well-being app for Worry management (IMWW) with support provided through an algorithmically driven conversational agent. Objective: This study aims to examine engagement with a mobile phone app to support worry management with specific attention directed toward interaction with specific LICBT techniques and examine the potential to reduce symptoms of anxiety. Methods: Log data were examined with respect to a sample of “engaged” users who had completed at least 1 lesson related to the Worry Time and Problem Solving in-app modules that represented the “minimum dose.” Paired sample 2-tailed t tests were undertaken to examine the potential for IMWW to reduce worry and anxiety, with multivariate linear regressions examining the extent to which completion of each of the techniques led to reductions in worry and anxiety. Results: There was good engagement with the range of specific LICBT techniques included within IMWW. The vast majority of engaged users were able to interact with the cognitive behavioral therapy model and successfully record types of worry. When working through Problem Solving, the conversational agent was successfully used to support the user with lower levels of engagement. Several users engaged with Worry Time outside of the app. Forgetting to use the app was the most common reason for lack of engagement, with features of the app such as completion of routine outcome measures and weekly reflections having lower levels of engagement. Despite difficulties in the collection of end point data, there was a significant reduction in severity for both anxiety (t53=5.5; P<.001; 95% CI 2.4-5.2) and low mood (t53=2.3; P=.03; 95% CI 0.2-3.3). A statistically significant linear model was also fitted to the Generalized Anxiety Disorder–7 (F2,51=6.73; P<.001), while the model predicting changes in the Patient Health Questionnaire–8 did not reach significance (F2,51=2.33; P=.11). This indicates that the reduction in these measures was affected by in-app engagement with Worry Time and Problem Solving. Conclusions: Engaged users were able to successfully interact with the LICBT-specific techniques informed by an evidence-based protocol although there were lower completion rates of routine outcome measures and weekly reflections. Successful interaction with the specific techniques potentially contributes to promising data, indicating that IMWW may be effective in the management of excessive worry. A relationship between dose and improvement justifies the use of log data to inform future developments. However, attention needs to be directed toward enhancing interaction with wider features of the app given that larger improvements were associated with greater engagement. %M 38029300 %R 10.2196/47321 %U https://mhealth.jmir.org/2024/1/e47321 %U https://doi.org/10.2196/47321 %U http://www.ncbi.nlm.nih.gov/pubmed/38029300 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 10 %N %P e43882 %T Feasibility, Adherence, and Effectiveness of Blended Psychotherapy for Severe Mental Illnesses: Scoping Review %A Ehrt-Schäfer,Yamina %A Rusmir,Milan %A Vetter,Johannes %A Seifritz,Erich %A Müller,Mario %A Kleim,Birgit %+ Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland, 41 +41583842817, yamina.ehrt@pukzh.ch %K blended psychotherapy %K severe mental illnesses %K digital health intervention %K e-mental health %K scoping review %D 2023 %7 26.12.2023 %9 Review %J JMIR Ment Health %G English %X Background: Blended psychotherapy (bPT) combines face-to-face psychotherapy with digital interventions to enhance the effectiveness of mental health treatment. The feasibility and effectiveness of bPT have been demonstrated for various mental health issues, although primarily for patients with higher levels of functioning. Objective: This scoping review aims to investigate the feasibility, adherence, and effectiveness of bPT for the treatment of patients with severe mental illnesses (SMIs). Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, we conducted searches in PubMed, MEDLINE, Embase, PsycINFO, and PsycArticles for studies published until March 23, 2023. Results: Out of 587 screened papers, we incorporated 25 studies encompassing 23 bPT interventions, involving a total of 2554 patients with SMI. The intervention formats and research designs exhibited significant variation. Our findings offer preliminary evidence supporting the feasibility of bPT for SMI, although there is limited research on adherence. Nevertheless, the summarized studies indicated promising attrition rates, spanning from 0% to 37%, implying a potential beneficial impact of bPT on adherence to SMI treatment. The quantity of evidence on the effects of bPT for SMI was limited and challenging to generalize. Among the 15 controlled trials, 4 concluded that bPT interventions were effective compared with controls. However, it is noteworthy that 2 of these studies used the same study population, and the control groups exhibited significant variations. Conclusions: Overall, our review suggests that while bPT appears promising as a treatment method, further research is necessary to establish its effectiveness for SMI. We discuss considerations for clinical implementation, directions, and future research. %M 38147373 %R 10.2196/43882 %U https://mental.jmir.org/2023/1/e43882 %U https://doi.org/10.2196/43882 %U http://www.ncbi.nlm.nih.gov/pubmed/38147373 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e49354 %T Exploring Different Incentive Structures Among US Adults Who Use e-Cigarettes to Optimize Retention in Longitudinal Web-Based Surveys: Case Study %A Crespi,Elizabeth %A Heller,Johanna %A Hardesty,Jeffrey J %A Nian,Qinghua %A Sinamo,Joshua K %A Welding,Kevin %A Kennedy,Ryan David %A Cohen,Joanna E %+ Institute for Global Tobacco Control, Department of Health, Behavior & Society, Johns Hopkins Bloomberg School of Public Health, 2213 McElderry Street, Baltimore, MD, 21205, United States, 1 410 614 5378, ecrespi2@jhu.edu %K incentive %K conditional incentive %K web-based survey %K longitudinal study %K follow-up %K nicotine %K e-cigarettes %K tobacco %K survey %K retention %K demographics %K case study %K optimization %K adults %D 2023 %7 13.12.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Longitudinal cohort studies are critical for understanding the evolution of health-influencing behaviors, such as e-cigarette use, over time. Optimizing follow-up rates in longitudinal studies is necessary for ensuring high-quality data with sufficient power for analyses. However, achieving high rates of follow-up in web-based longitudinal studies can be challenging, even when monetary incentives are provided. Objective: This study compares participant progress through a survey and demographics for 2 incentive structures (conditional and hybrid unconditional-conditional) among US adults using e-cigarettes to understand the optimal incentive structure. Methods: The data used in this study are from a web-based longitudinal cohort study (wave 4; July to September 2022) of US adults (aged 21 years or older) who use e-cigarettes ≥5 days per week. Participants (N=1804) invited to the follow-up survey (median completion time=16 minutes) were randomly assigned into 1 of 2 incentive structure groups (n=902 each): (1) conditional (US $30 gift code upon survey completion) and (2) hybrid unconditional-conditional (US $15 gift code prior to survey completion and US $15 gift code upon survey completion). Chi-square tests assessed group differences in participant progress through 5 sequential stages of the survey (started survey, completed screener, deemed eligible, completed survey, and deemed valid) and demographics. Results: Of the 902 participants invited to the follow-up survey in each group, a higher proportion of those in the conditional (662/902, 73.4%) than the hybrid (565/902, 62.6%) group started the survey (P<.001). Of those who started the survey, 643 (97.1%) participants in the conditional group and 548 (97%) participants in the hybrid group completed the screener (P=.89), which was used each wave to ensure participants remained eligible. Of those who completed the screener, 555 (86.3%) participants in the conditional group and 446 (81.4%) participants in the hybrid group were deemed eligible for the survey (P=.02). Of those eligible, 514 (92.6%) participants from the conditional group and 401 (89.9%) participants from the hybrid group completed the survey and were deemed valid after data review (P=.14). Overall, more valid completions were yielded from the conditional (514/902, 57%) than the hybrid group (401/902, 44.5%; P<.001). Among those who validly completed the survey, no significant differences were found by group for gender, income, race, ethnicity, region, e-cigarette use frequency, past 30-day cigarette use, or number of waves previously completed. Conclusions: Providing a US $30 gift code upon survey completion yielded higher rates of survey starts and completions than providing a US $15 gift code both before and after survey completion. These 2 methods yielded participants with similar demographics, suggesting that one approach is not superior in obtaining a balanced sample. Based on this case study, future web-based surveys examining US adults using e-cigarettes could consider providing the full incentive upon completion of the survey. International Registered Report Identifier (IRRID): RR2-10.2196/38732 %M 38090793 %R 10.2196/49354 %U https://www.jmir.org/2023/1/e49354 %U https://doi.org/10.2196/49354 %U http://www.ncbi.nlm.nih.gov/pubmed/38090793 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e50729 %T Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals %A Lu,Ziyuan %A Signer,Tabea %A Sylvester,Ramona %A Gonzenbach,Roman %A von Wyl,Viktor %A Haag,Christina %+ Institute for Implementation Science in Health Care, University of Zurich, Universitätstrasse 84, Zurich, 8006, Switzerland, 41 446346380, viktor.vonwyl@uzh.ch %K physical activity %K activity sensor %K normalization process theory %K rehabilitation %K chronic disease %K chronic %K aftercare %K sensor %K sensors %K exercise %K neurology %K neuroscience %K neurorehabilitation %K adherence %K need %K needs %K experience %K experiences %K questionnaire %K questionnaires %K mobile phone %D 2023 %7 8.12.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Physical activity is central to maintaining the quality of life for patients with complex chronic conditions and is thus at the core of neurorehabilitation. However, maintaining activity improvements in daily life is challenging. The novel Stay With It program aims to promote physical activity after neurorehabilitation by cultivating self-monitoring skills and habits. Objective: We examined the implementation of the Stay With It program at the Valens Rehabilitation Centre in Switzerland using the normalization process theory framework, focusing on 3 research aims. We aimed to examine the challenges and facilitators of program implementation from the perspectives of patients and health care professionals. We aimed to evaluate the potential of activity sensors to support program implementation and patient acceptance. Finally, we aimed to evaluate patients’ engagement in physical activity after rehabilitation, patients’ self-reported achievement of home activity goals, and factors influencing physical activity. Methods: Patients were enrolled if they had a disease that was either chronic or at risk for chronicity and participated in the Stay With It program. Patients were assessed at baseline, the end of rehabilitation, and a 3-month follow-up. The health care professionals designated to deliver the program were surveyed before and after program implementation. We used a mixed methods approach combining standardized questionnaires, activity-sensing data (patients only), and free-text questions. Results: This study included 23 patients and 13 health care professionals. The diverse needs of patients and organizational hurdles were major challenges to program implementation. Patients’ intrinsic motivation and health care professionals’ commitment to refining the program emerged as key facilitators. Both groups recognized the value of activity sensors in supporting program implementation and sustainability. Although patients appreciated the sensor’s ability to monitor, motivate, and quantify activity, health care professionals saw the sensor as a motivational tool but expressed concerns about technical difficulties and potential inaccuracies. Physical activity levels after patients returned home varied considerably, both within and between individuals. The self-reported achievement of activity goals at home also varied, in part because of vague definitions. Common barriers to maintaining activity at home were declining health and fatigue often resulting from heat and pain. At the 3-month follow-up, 35% (8/23) of the patients withdrew from the study, with most citing deteriorating physical health as the reason and that monitoring and discussing their low activity would negatively affect their mental health. Conclusions: Integrating aftercare programs like Stay With It into routine care is vital for maintaining physical activity postrehabilitation. Although activity trackers show promise in promoting motivation through monitoring, they may lead to frustration during health declines. Their acceptability may also be influenced by an individual’s health status, habits, and technical skills. Our study highlights the importance of considering health care professionals’ perspectives when integrating new interventions into routine care. %M 38064263 %R 10.2196/50729 %U https://mhealth.jmir.org/2023/1/e50729 %U https://doi.org/10.2196/50729 %U http://www.ncbi.nlm.nih.gov/pubmed/38064263 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43584 %T Predictors of Dropout Among Psychosomatic Rehabilitation Patients During the COVID-19 Pandemic: Secondary Analysis of a Longitudinal Study of Digital Training %A Gao,Lingling %A Keller,Franziska Maria %A Becker,Petra %A Dahmen,Alina %A Lippke,Sonia %+ Health Psychology and Behavioural Medicine, Constructor University Bremen, Campus Ring 1, Bremen, 28759, Germany, 49 4212004730, slippke@constructor.university %K dropout %K web-based study %K digital therapy %K medical rehabilitation %K digital training %K mental disorder %K psychosomatic rehabilitation %K COVID-19 %D 2023 %7 27.11.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: High dropout rates are a common problem reported in web-based studies. Understanding which risk factors interrelate with dropping out from the studies provides the option to prevent dropout by tailoring effective strategies. Objective: This study aims to contribute an understanding of the predictors of web-based study dropout among psychosomatic rehabilitation patients. We investigated whether sociodemographics, voluntary interventions, physical and mental health, digital use for health and rehabilitation, and COVID-19 pandemic–related variables determine study dropout. Methods: Patients (N=2155) recruited from 4 psychosomatic rehabilitation clinics in Germany filled in a web-based questionnaire at T1, which was before their rehabilitation stay. Approximately half of the patients (1082/2155, 50.21%) dropped out at T2, which was after the rehabilitation stay, before and during which 3 voluntary digital trainings were provided to them. According to the number of trainings that the patients participated in, they were categorized into a comparison group or 1 of 3 intervention groups. Chi-square tests were performed to examine the differences between dropout patients and retained patients in terms of sociodemographic variables and to compare the dropout rate differences between the comparison and intervention groups. Logistic regression analyses were used to assess what factors were related to study dropout. Results: The comparison group had the highest dropout rate of 68.4% (173/253) compared with the intervention groups’ dropout rates of 47.98% (749/1561), 50% (96/192), and 42.9% (64/149). Patients with a diagnosis of combined anxiety and depressive disorder had the highest dropout rate of 64% (47/74). Younger patients (those aged <50 y) and patients who were less educated were more likely to drop out of the study. Patients who used health-related apps and the internet less were more likely to drop out of the study. Patients who remained in their jobs and patients who were infected by COVID-19 were more likely to drop out of the study. Conclusions: This study investigated the predictors of dropout in web-based studies. Different factors such as patient sociodemographics, physical and mental health, digital use, COVID-19 pandemic correlates, and study design can correlate with the dropout rate. For web-based studies with a focus on mental health, it is suggested to consider these possible dropout predictors and take appropriate steps to help patients with a high risk of dropping out overcome difficulties in completing the study. %M 37903289 %R 10.2196/43584 %U https://www.jmir.org/2023/1/e43584 %U https://doi.org/10.2196/43584 %U http://www.ncbi.nlm.nih.gov/pubmed/37903289 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e46237 %T Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review %A Grayek,Emily %A Krishnamurti,Tamar %A Hu,Lydia %A Babich,Olivia %A Warren,Katherine %A Fischhoff,Baruch %+ Department of Engineering and Public Policy, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States, 1 (412) 268 2000, egrayek@andrew.cmu.edu %K mobile health %K mHealth %K adherence %K evaluation %K usability %K efficacy %K systematic review %K application %K compliance %K safety %K effectiveness %K engagement %K risk %K medical device %K clinical trials %D 2023 %7 15.11.2023 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: The rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app’s effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses. Objective: This systematic review aims to address 2 critical questions regarding clinical trials of software as a medical device (SaMD) apps: How well do researchers report adherence and engagement metrics for studies of effectiveness and efficacy? and What efficacy analyses do researchers use to account for nonadherence and how appropriate are their methods? Methods: We searched the Food and Drug Administration’s registration database for registrations of repeated-use, patient-facing SaMD therapeutics. For each such registration, we searched ClinicalTrials.gov, company websites, and MEDLINE for the corresponding clinical trial and study articles through March 2022. Adherence and engagement data were summarized for each of the 24 identified articles, corresponding to 10 SaMD therapeutics. Each article was analyzed with a framework developed using the Cochrane risk-of-bias questions to estimate the potential effects of imperfect adherence on SaMD effectiveness. This review, funded by the Richard King Mellon Foundation, is registered on the Open Science Framework. Results: We found that although most articles (23/24, 96%) reported collecting information about SaMD therapeutic engagement, of the 20 articles for apps with prescribed use, only 9 (45%) reported adherence information across all aspects of prescribed use: 15 (75%) reported metrics for the initiation of therapeutic use, 16 (80%) reported metrics reporting adherence between the initiation and discontinuation of the therapeutic (implementation), and 4 (20%) reported the discontinuation of the therapeutic (persistence). The articles varied in the reported metrics. For trials that reported adherence or engagement, there were 4 definitions of initiation, 8 definitions of implementation, and 4 definitions of persistence. All articles studying a therapeutic with a prescribed use reported effectiveness estimates that might have been affected by nonadherence; only a few (2/20, 10%) used methods appropriate to evaluate efficacy. Conclusions: This review identifies 5 areas for improving future SaMD trials and studies: use consistent metrics for reporting adherence, use reliable adherence metrics, preregister analyses for observational studies, use less biased efficacy analysis methods, and fully report statistical methods and assumptions. %M 37966871 %R 10.2196/46237 %U https://mhealth.jmir.org/2023/1/e46237 %U https://doi.org/10.2196/46237 %U http://www.ncbi.nlm.nih.gov/pubmed/37966871 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e48435 %T The Efficacy of an mHealth App in Facilitating Weight Loss Among Japanese Fitness Center Members: Regression Analysis Study %A Eguchi,Akifumi %A Kawamura,Yumi %A Kawashima,Takayuki %A Ghaznavi,Cyrus %A Ishimura,Keiko %A Kohsaka,Shun %A Matsuo,Satoru %A Mizuno,Shinichiro %A Sasaki,Yuki %A Takahashi,Arata %A Tanoue,Yuta %A Yoneoka,Daisuke %A Miyata,Hiroaki %A Nomura,Shuhei %+ Department of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan, 81 3 5363 3774, s-nomura@keio.jp %K digital health %K gym attendance %K Japan %K real-world data %K smartphone application %K weight loss %D 2023 %7 8.11.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Self-tracking smartphone apps have emerged as promising tools to encourage healthy behaviors. In this longitudinal study, we used gym use data from members of a major fitness club that operates gyms throughout Japan from January 2014 to December 2019. Objective: Our objective was to assess the extent to which a health and fitness self-tracking mobile app introduced to gym members on January 1, 2018, contributed to their weight loss. The app allows users to input information regarding diet, sleep, weight, and gym exercise so that they can receive personalized feedback from an artificial intelligence chatbot to improve their health behaviors. Methods: We used linear regression to quantify the association between app use and weight loss. The primary outcome of the study was the weight loss achieved by each gym user, which was calculated as the difference between their initial and final weights in kilograms, as recorded in the app. Individuals who did not attend the gym or failed to use the mobile app at least twice during the study period were excluded from the analysis. The model accounted for age, gender, distance between the gym and the member’s residence, average weekly number of times a member used the gym, user’s gym membership length in weeks, average weekly number of times a member input information into the app, and the number of weeks that the app was used at least once. Results: Data from 26,589 participants were analyzed. Statistically significant associations were detected between weight loss and 2 metrics related to app use: the average weekly frequency of use and the total number of weeks in which the app was used at least once. One input per week was found to be associated with a loss of 62.1 (95% CI 53.8-70.5) g, and 1 week of app use was associated with 21.7 (95% CI 20.5-22.9) g of weight loss from the day of the first input to that of the final input to the app. Furthermore, the average number of times that a member used the gym weekly was also shown to be statistically significantly associated with weight loss: 1 use per week was associated with 255.5 (95% CI 228.5-282.6) g of weight loss. Conclusions: This empirical study demonstrated a significant association between weight loss among gym members and not only the frequency of weekly gym use but also the use of a health and fitness self-tracking app. However, further work is needed to examine the mechanisms through which mobile apps affect health behaviors and to identify the specific app features that are most effective in promoting weight loss. %M 37938885 %R 10.2196/48435 %U https://formative.jmir.org/2023/1/e48435 %U https://doi.org/10.2196/48435 %U http://www.ncbi.nlm.nih.gov/pubmed/37938885 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e46640 %T Improving Knowledge, Engagement, and Self-Efficacy in the Creation of Healthy Home Environments for Mothers Using a Facebook Intervention (Design for Wellness): Randomized Controlled Trial %A Aperman-Itzhak,Tal %A Prilleltensky,Isaac %A Rosen,Laura %+ Department of Health Promotion, School of Public Health, Faculty of Medicine, Tel Aviv University, PO Box 39040, Ramat Aviv, Tel Aviv, 6997801, Israel, 972 508342585, talap1@gmail.com %K environmental home design %K wellness %K Facebook intervention %K nudging %K healthy living %K social media %K Israel %D 2023 %7 7.11.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Designing the home environment can promote well-being. Social networks provide learning opportunities to improve health. Objective: This study aimed to develop and evaluate a Facebook intervention called Design for Wellness (DWELL). The program was created to improve knowledge, engagement, and self-efficacy in the creation of healthy home environments. Methods: A randomized controlled trial was conducted to assess the effects of the intervention program DWELL. Content was uploaded to the Facebook group and gave the participants practical solutions for how to design their home environment for wellness. The intervention addressed multiple components of health behaviors, such as healthy eating, physical activity, tobacco-free environment, hygiene, family conversations regarding wellness issues, and stress reduction. The main outcome was the participants’ overall score on the DWELL index, which we developed to assess the elements of our intervention: knowledge, awareness, engagement, and self-efficacy regarding home design for wellness. The intervention was conducted in Israel and lasted 6 weeks during the third wave of the COVID-19 pandemic. The primary analysis included a multivariable model to assess the DWELL score at the end of the study while controlling for baseline characteristics. The waitlist control group did not receive an intervention between the 2 administrations of the questionnaire. Results: In total, 643 participants began the program: 322 (50.1%) in the intervention group and 321 (49.9%) in the control group. Of the 643 participants, 476 (74%) completed the study. At the end of the study, there was a statistically significant benefit of the intervention as assessed using a one-way analysis of covariance: there was a mean difference of 8.631 (SD 1.408) points in the DWELL score in favor of the intervention group (intervention: mean 61.92, SD 14.30; control: mean 53.29, SD 16.374; P<.001). Qualitative feedback from participants in the intervention group strengthened the positive results as most of them found the group beneficial. The Facebook group was very active. Being more engaged in the group correlated with having a higher DWELL score, but this relationship was weak (r=0.37; P<.001). The mean significant difference of 26.281 (SD 19.24) points between the overall DWELL score and the overall engagement score indicated that participants who were not active in the group still followed the posts and benefited. We found no improvements in the secondary outcome regarding participants’ well-being. The COVID-19 lockdown may have prevented this. Conclusions: DWELL was found to be a beneficial intervention for improving perceptions of the design of home environments to foster wellness. Facebook was an effective platform to deliver this intervention. DWELL may become a prototype for other health promotion interventions. Trial Registration: ClinicalTrials.gov NCT03736525; https://clinicaltrials.gov/study/NCT03736525?term=DWELL&rank=1 %M 37934566 %R 10.2196/46640 %U https://www.jmir.org/2023/1/e46640 %U https://doi.org/10.2196/46640 %U http://www.ncbi.nlm.nih.gov/pubmed/37934566 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 10 %N %P e44034 %T Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study %A Nowell,William B %A Curtis,Jeffrey R %A Zhao,Hong %A Xie,Fenglong %A Stradford,Laura %A Curtis,David %A Gavigan,Kelly %A Boles,Jessica %A Clinton,Cassie %A Lipkovich,Ilya %A Venkatachalam,Shilpa %A Calvin,Amy %A Hayes,Virginia S %+ Global Healthy Living Foundation, 515 N Midland Ave, Upper Nyack, NY, 10960, United States, 1 9163963097, lstradford@ghlf.org %K real-world evidence %K real-world data %K patients %K rheumatoid arthritis %K patient-reported outcomes %K patient-generated health data %K mobile technology %K wearable digital technology %K mobile phone %D 2023 %7 7.11.2023 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Digital health studies using electronic patient-reported outcomes (ePROs) and wearables bring new challenges, including the need for participants to consistently provide trial data. Objective: This study aims to characterize the engagement, protocol adherence, and data completeness among participants with rheumatoid arthritis enrolled in the Digital Tracking of Arthritis Longitudinally (DIGITAL) study. Methods: Participants were invited to participate in this app-based study, which included a 14-day run-in and an 84-day main study. In the run-in period, data were collected via the ArthritisPower mobile app to increase app familiarity and identify the individuals who were motivated to participate. Successful completers of the run-in period were mailed a wearable smartwatch, and automated and manual prompts were sent to participants, reminding them to complete app input or regularly wear and synchronize devices, respectively, during the main study. Study coordinators monitored participant data and contacted participants via email, SMS text messaging, and phone to resolve adherence issues per a priori rules, in which consecutive spans of missing data triggered participant contact. Adherence to data collection during the main study period was defined as providing requested data for >70% of 84 days (daily ePRO, ≥80% daily smartwatch data) or at least 9 of 12 weeks (weekly ePRO). Results: Of the 470 participants expressing initial interest, 278 (59.1%) completed the run-in period and qualified for the main study. Over the 12-week main study period, 87.4% (243/278) of participants met the definition of adherence to protocol-specified data collection for weekly ePRO, and 57.2% (159/278) did so for daily ePRO. For smartwatch data, 81.7% (227/278) of the participants adhered to the protocol-specified data collection. In total, 52.9% (147/278) of the participants met composite adherence. Conclusions: Compared with other digital health rheumatoid arthritis studies, a short run-in period appears useful for identifying participants likely to engage in a study that collects data via a mobile app and wearables and gives participants time to acclimate to study requirements. Automated or manual prompts (ie, “It’s time to sync your smartwatch”) may be necessary to optimize adherence. Adherence varies by data collection type (eg, ePRO vs smartwatch data). International Registered Report Identifier (IRRID): RR2-10.2196/14665 %M 37934559 %R 10.2196/44034 %U https://humanfactors.jmir.org/2023/1/e44034 %U https://doi.org/10.2196/44034 %U http://www.ncbi.nlm.nih.gov/pubmed/37934559 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e47813 %T Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners %A Yan,Xinghui %A Newman,Mark W %A Park,Sun Young %A Sander,Angelle %A Choi,Sung Won %A Miner,Jennifer %A Wu,Zhenke %A Carlozzi,Noelle %+ Department of Physical Medicine and Rehabilitation, University of Michigan, North Campus Research Complex 2800 Plymouth Rd., Building NCRC B14, Ann Arbor, MI, 48108, United States, 1 734 764 0644, carlozzi@umich.edu %K mHealth intervention %K mobile health %K behavior change %K qualitative study %K user adherence %K behavioral messages %K general well-being %D 2023 %7 24.10.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Mobile health (mHealth) interventions can deliver personalized behavioral support to users in daily contexts. These interventions have been increasingly adopted to support individuals who require low-cost and low-burden support. Prior research has demonstrated the feasibility and acceptability of an mHealth intervention app (CareQOL) designed for use with informal care partners. To further optimize the intervention delivery, we need to investigate how care partners, many of whom lack the time for self-care, react and act in response to different behavioral messages. Objective: The goal of this study was to understand the factors that impact care partners’ decision-making and actions in response to different behavioral messages. Insights from this study will help optimize future tailored and personalized behavioral interventions. Methods: We conducted semistructured interviews with participants who had recently completed a 3-month randomized controlled feasibility trial of the CareQOL mHealth intervention app. Of the 36 participants from the treatment group of the randomized controlled trial, 23 (64%) participated in these interviews. To prepare for each interview, the team first selected representative behavioral messages (eg, targeting different health dimensions) and presented them to participants during the interview to probe their influence on participants’ thoughts and actions. The time of delivery, self-reported perceptions of the day, and user ratings of a message were presented to the participants during the interviews to assist with recall. Results: The interview data showed that after receiving a message, participants took various actions in response to different messages. Participants performed suggested behaviors or adjusted them either immediately or in a delayed manner (eg, sometimes up to a month later). We identified 4 factors that shape the variations in user actions in response to different behavioral messages: uncertainties about the workload required to perform suggested behaviors, concerns about one’s ability to routinize suggested behaviors, in-the-moment willingness and ability to plan for suggested behaviors, and overall capability to engage with the intervention. Conclusions: Our study showed that care partners use mHealth behavioral messages differently regarding the immediacy of actions and the adaptation to suggested behaviors. Multiple factors influence people’s perceptions and decisions regarding when and how to take actions. Future systems should consider these factors to tailor behavioral support for individuals and design system features to support the delay or adaptation of the suggested behaviors. The findings also suggest extending the assessment of user adherence by considering the variations in user actions on behavioral support (ie, performing suggested or adjusted behaviors immediately or in a delayed manner). International Registered Report Identifier (IRRID): RR2-10.2196/32842 %M 37874621 %R 10.2196/47813 %U https://formative.jmir.org/2023/1/e47813 %U https://doi.org/10.2196/47813 %U http://www.ncbi.nlm.nih.gov/pubmed/37874621 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e49407 %T mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach %A Kgasi,Mmamolefe %A Chimbo,Bester %A Motsi,Lovemore %+ Faculty of ICT, Tshwane University of Technology, Department of End User Computing, Pretoria, South Africa, 27 715633727, kgasimr@tut.ac.za %K diabetes %K mobile health %K mHealth %K self-monitoring %K self-management %K chronic diseases %K health care provision %D 2023 %7 23.10.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has led to serious challenges and emphasized the importance of using technology for health care operational transformation. Consequently, the need for technological innovations has increased, thus empowering patients with chronic conditions to tighten their adherence to medical prescriptions. Objective: This study aimed to develop a model for a mobile health (mHealth) self-monitoring system for patients with diabetes in rural communities within resource-limited countries. The developed model could be based on the implementation of a system for the self-monitoring of patients with diabetes to increase medical adherence. Methods: This study followed a quantitative approach, in which data were collected from health care providers using a questionnaire with close-ended questions. Data were collected from district hospitals in 3 South African provinces that were selected based on the prevalence rates of diabetes and the number of patients with diabetes treated. The collected data were analyzed using smart partial least squares to validate the model and test the suggested hypotheses. Results: Using variance-based structural equation modeling that leverages smart partial least squares, the analysis indicated that environmental factors significantly influence all the independent constructs that inform patients’ change of behavior toward the use of mHealth for self-monitoring of medication adherence. Technology characteristics such as effort expectancy, self-efficacy, and performance expectancy were equally significant; hence, their hypotheses were accepted. In contrast, the contributions of culture and social aspects were found to be insignificant, and their hypotheses were rejected. In addition, an analysis was conducted to determine the interaction effects of the moderating variables on the independent constructs. The results indicated that with the exception of cultural and social influences, there were significant interacting effects on other independent constructs influencing mHealth use for self-monitoring. Conclusions: On the basis of the findings of this study, we conclude that behavioral changes are essential for the self-monitoring of chronic diseases. Therefore, it is important to enhance those effects that stimulate the behavior to change toward the use of mHealth for self-monitoring. Motivational aspects were also found to be highly significant as they triggered changes in behavior. The developed model can be used to extend the research on the self-monitoring of patients with chronic conditions. Moreover, the model will be used as a basic architecture for the implementation of fully fledged systems for self-monitoring of patients with diabetes. %M 37870902 %R 10.2196/49407 %U https://formative.jmir.org/2023/1/e49407 %U https://doi.org/10.2196/49407 %U http://www.ncbi.nlm.nih.gov/pubmed/37870902 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45173 %T A Digital Gaming Intervention to Strengthen the Social Networks of Older Dutch Adults: Mixed Methods Process Evaluation of a Digitally Conducted Randomized Controlled Trial %A Janssen,Jeroen %A Châtel,Bas %A Den Heijer,Nora %A Tieben,Rob %A Deen,Menno %A Corten,Rense %A Peeters,Geeske %A Olde Rikkert,Marcel %+ Department of Geriatric Medicine, Radboud University Medical Center, Postbus 9101, Nijmegen, 6500 HB, Netherlands, 31 243616772, jeroen.janssen@radboudumc.nl %K eHealth %K gerontology %K loneliness %K mixed methods %K mobile games %K qualitative research %K serious games %D 2023 %7 20.10.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Digital loneliness interventions for older adults are promising, yet conclusive evidence is lacking due to a lack of randomized controlled trials (RCTs) and difficulties with recruitment. Process evaluation of performed RCTs is essential to inform future interventions. Still, it is rarely carried out, resulting in an overly optimistic view of the impact of eHealth interventions on loneliness in older adults and options to conduct such research entirely remotely. Objective: We describe a mixed methods process evaluation of a digitally conducted RCT assessing the effectiveness of a mobile social gaming app to facilitate meaningful social interactions in older adults. Methods: We analyzed the questionnaire and game data of the RCT participants to evaluate recruitment and onboarding, intervention adherence, and intervention acceptability. The RCT participants were allocated either to the main group of older adults (aged 65 years or older) or the side group (aged between 18 and 64 years). The side group used networking to play with the older adults. We also conducted 6 post-RCT evaluation interviews and 1 focus group with a total of 4 RCT participants and 5 welfare organization representatives that aided in RCT recruitment. Results: In total, 371 people aged 18 years or older signed up for the RCT, of which 64% (238/371) were aged 65 years or older. Of the total sample, 20% (76/371) installed the app and signed informed consent, showing a large dropout during onboarding. The high number of questions was a relevant barrier for participants. Both questionnaire and gameplay adherence were low. Participants indicated that the games elicited contact and a feeling of togetherness and proposed challenging and competitive games with increasing difficulty levels. They suggested focusing on enjoying the games rather than administering questionnaires. Conclusions: Conducting a remote digital trial of a social gaming intervention for older adults is a great challenge. Remote recruitment and informed consent acquisition may often not result in sufficient participation. Personal engagement with fellow participants and researchers might be essential for adherence and enjoyment. Future digital gaming interventions should start with small-scale studies with in-person contact, repeated instructions, and fewer questionnaires. %M 37862093 %R 10.2196/45173 %U https://formative.jmir.org/2023/1/e45173 %U https://doi.org/10.2196/45173 %U http://www.ncbi.nlm.nih.gov/pubmed/37862093 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e46852 %T Perinatal Women’s Perspectives of, and Engagement in, Digital Emotional Well-Being Training: Mixed Methods Study %A Davis,Jacqueline A %A Ohan,Jeneva L %A Gregory,Sonia %A Kottampally,Keerthi %A Silva,Desiree %A Prescott,Susan L %A Finlay-Jones,Amy L %+ Telethon Kids Institute, 15 Hospital Avenue, Nedlands, 6009, Australia, 61 478173989, jackie.davis@telethonkids.org.au %K perinatal %K digital mental health interventions %K well-being %K mindfulness %K self-compassion %K engagement %K ORIGINS %D 2023 %7 17.10.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Psychological distress in the early postpartum period can have long-lasting deleterious effects on a mother’s well-being and negatively affect her infant’s development. Intervention approaches based in contemplative practices such as mindfulness and loving-kindness and compassion are intended to alleviate distress and cultivate well-being and can be delivered effectively as digital mental health interventions (DMHIs). Objective: To understand the feasibility of engaging perinatal women in digital interventions, this study aimed to document participants’ experiences in the Mums Minds Matter (MMM) study, a pilot randomized controlled trial comparing mindfulness, loving-kindness and compassion, and progressive muscle relaxation training delivered in a digital format and undertaken during pregnancy. To assess the different stages of engagement during and after the intervention, we adapted the connect, attend, participate, enact (CAPE) framework that is based on the idea that individuals go through different stages of engagement before they are able to enact change. Methods: The MMM study was nested within a longitudinal birth cohort, The ORIGINS Project. We aimed to recruit 25 participants per randomization arm. Data were collected sequentially during the intervention through regular web-based surveys over 8 weeks, with opportunities to provide regular feedback. In the postintervention phase, qualitative data were collected through purposive sampling. Results: Of 310 eligible women, 84 (27.1% [connect rate]) enrolled to participate in MMM. Of the remaining 226 women who did not proceed to randomization, 223 (98.7%) failed to complete the baseline surveys and timed out of eligibility (after 30 weeks’ gestation), and 3 (1.3%) displayed high psychological distress scores. Across all program groups, 17 (20% [attend rate]) of the 84 participants actively opted out, although more may have disengaged from the intervention but did not withdraw. The main reasons for withdrawal were busy life and other priorities. In this study, we assessed active engagement and ongoing skills use (participate and enact) through postintervention interviews. We undertook 15 participant interviews, conducted 1 month to 3 months after the intervention. Our results provide insights into participant barriers and enablers as well as app changes, such as the ability to choose topics, daily reminders, case studies, and diversity in sounds. Implementing a DMHI that is brief, includes frequent prompts or nudges, and is easily accessible is a key strategy to target perinatal women. Conclusions: Our research will enable future app designs that are sufficiently nuanced to maximize the uptake, engagement, and application of mental health skills and contemplative practices in the perinatal period. Providing convenient access to engaging and effective prevention programs is critical and should be part of prenatal self-care. Our research underscores the appeal and feasibility of digital intervention approaches based in contemplative practices for perinatal women. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) 12620000672954p; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000672954p International Registered Report Identifier (IRRID): RR2-10.2196/19803 %M 37847537 %R 10.2196/46852 %U https://www.jmir.org/2023/1/e46852 %U https://doi.org/10.2196/46852 %U http://www.ncbi.nlm.nih.gov/pubmed/37847537 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e47198 %T User Engagement Clusters of an 8-Week Digital Mental Health Intervention Guided by a Relational Agent (Woebot): Exploratory Study %A Hoffman,Valerie %A Flom,Megan %A Mariano,Timothy Y %A Chiauzzi,Emil %A Williams,Andre %A Kirvin-Quamme,Andrew %A Pajarito,Sarah %A Durden,Emily %A Perski,Olga %+ Woebot Health, Inc., 535 Mission St, San Francisco, CA, 94107, United States, 1 4152739742, valerie_hoffman@woebothealth.com %K anxiety %K clustering %K depression %K digital health %K digital mental health intervention %K mental health %K relational agents %K user engagement %D 2023 %7 13.10.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: With the proliferation of digital mental health interventions (DMHIs) guided by relational agents, little is known about the behavioral, cognitive, and affective engagement components associated with symptom improvement over time. Obtaining a better understanding could lend clues about recommended use for particular subgroups of the population, the potency of different intervention components, and the mechanisms underlying the intervention’s success. Objective: This exploratory study applied clustering techniques to a range of engagement indicators, which were mapped to the intervention’s active components and the connect, attend, participate, and enact (CAPE) model, to examine the prevalence and characterization of each identified cluster among users of a relational agent-guided DMHI. Methods: We invited adults aged 18 years or older who were interested in using digital support to help with mood management or stress reduction through social media to participate in an 8-week DMHI guided by a natural language processing–supported relational agent, Woebot. Users completed assessments of affective and cognitive engagement, working alliance as measured by goal and task working alliance subscale scores, and enactment (ie, application of therapeutic recommendations in real-world settings). The app passively collected data on behavioral engagement (ie, utilization). We applied agglomerative hierarchical clustering analysis to the engagement indicators to identify the number of clusters that provided the best fit to the data collected, characterized the clusters, and then examined associations with baseline demographic and clinical characteristics as well as mental health outcomes at week 8. Results: Exploratory analyses (n=202) supported 3 clusters: (1) “typical utilizers” (n=81, 40%), who had intermediate levels of behavioral engagement; (2) “early utilizers” (n=58, 29%), who had the nominally highest levels of behavioral engagement in week 1; and (3) “efficient engagers” (n=63, 31%), who had significantly higher levels of affective and cognitive engagement but the lowest level of behavioral engagement. With respect to mental health baseline and outcome measures, efficient engagers had significantly higher levels of baseline resilience (P<.001) and greater declines in depressive symptoms (P=.01) and stress (P=.01) from baseline to week 8 compared to typical utilizers. Significant differences across clusters were found by age, gender identity, race and ethnicity, sexual orientation, education, and insurance coverage. The main analytic findings remained robust in sensitivity analyses. Conclusions: There were 3 distinct engagement clusters found, each with distinct baseline demographic and clinical traits and mental health outcomes. Additional research is needed to inform fine-grained recommendations regarding optimal engagement and to determine the best sequence of particular intervention components with known potency. The findings represent an important first step in disentangling the complex interplay between different affective, cognitive, and behavioral engagement indicators and outcomes associated with use of a DMHI incorporating a natural language processing–supported relational agent. Trial Registration: ClinicalTrials.gov NCT05672745; https://classic.clinicaltrials.gov/ct2/show/NCT05672745 %M 37831490 %R 10.2196/47198 %U https://www.jmir.org/2023/1/e47198 %U https://doi.org/10.2196/47198 %U http://www.ncbi.nlm.nih.gov/pubmed/37831490 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 10 %N %P e48843 %T Patient Experience of Digitalized Follow-up of Antidepressant Treatment in Psychiatric Outpatient Care: Qualitative Analysis %A Hamlin,Matilda %A Holmén,Joacim %A Wentz,Elisabet %A Aiff,Harald %A Ali,Lilas %A Steingrimsson,Steinn %+ Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Universitetsplatsen 1, Gothenburg, 405 30, Sweden, 46 31786 00 00, steinn.steingrimsson@vgregion.se %K major depressive disorder %K digital psychiatry %K mobile app %K adherence %K antidepressant %K antidepressants %K depressive %K depression %K mHealth %K mobile health %K app %K apps %K application %K applications %K experience %K interview %K interviews %K medication %K prescribe %K prescription %K dose %D 2023 %7 11.10.2023 %9 Original Paper %J JMIR Ment Health %G English %X Background: Nonadherence to pharmaceutical antidepressant treatment is common among patients with depression. Digitalized follow-up (ie, self-monitoring systems through mobile apps) has been suggested as an effective adjunct to conventional antidepressant treatment to increase medical adherence, improve symptoms of depression, and reduce health care resource use. Objective: The aim of this study was to determine patients’ experience of digitalized follow-up using a mobile app as an adjunct to treatment concurrent with a new prescription, a change of antidepressant, or a dose increase. Methods: This was a qualitative, descriptive study. Patients at 2 psychiatric outpatient clinics were recruited at the time of changing antidepressant medication. After using a mobile app (either a commercial app or a public app) for 4-6 weeks with daily registrations of active data, such as medical intake and questions concerning general mental health status, individual semistructured interviews were conducted. Recorded data were transcribed and then analyzed using content analysis. Results: In total, 13 patients completed the study. The mean age was 35 (range 20-67) years, 8 (61.5%) were female, and all reported high digital literacy. Overall, the emerging themes indicated that the patients found the digital app to be a valuable adjunct to antidepressant treatment but with potential for improvement. Both user adherence and medical adherence were positively affected by a daily reminder and the app’s ease of use. User adherence was negatively affected by the severity of depression. The positive experience of visually presented data as graphs was a key finding, which was beneficial for self-awareness, the patient-physician relationship, and user adherence. Finally, the patients had mixed reactions to the app’s content and requested tailored content. Conclusions: The patients identified several factors addressing both medical adherence and user adherence to a digital app when using it for digitalized follow-up concurrent with the critical time related to changes in antidepressant medication. The findings highlight the need for rigorous evidence-based empirical studies to generate sustainable research results. %M 37819697 %R 10.2196/48843 %U https://mental.jmir.org/2023/1/e48843 %U https://doi.org/10.2196/48843 %U http://www.ncbi.nlm.nih.gov/pubmed/37819697 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43358 %T The Effects of Dose, Practice Habits, and Objects of Focus on Digital Meditation Effectiveness and Adherence: Longitudinal Study of 280,000 Digital Meditation Sessions Across 103 Countries %A Cearns,Micah %A Clark,Scott R %+ Insight Timer Research, Insight Timer, 64 York Street, Sydney, 2000, Australia, 61 8313 8163, micah@insight.co %K mindfulness %K meditation %K digital meditation %K mindfulness dose-response %K meditation dose-response %K dose-response %K meditation adherence %K mindfulness adherence %K longitudinal meditation research %K outcome %K ecological memory assessment %K mental well-being %K healthy lifestyle %K digital health intervention %D 2023 %7 19.9.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The efficacy of digital meditation is well established. However, the extent to which the benefits remain after 12 weeks in real-world settings remains unknown. Additionally, findings related to dosage and practice habits have been mixed, and the studies were conducted on small and homogeneous samples and used a limited range of analytical procedures and meditation techniques. Findings related to the predictors of adherence are also lacking and may help inform future meditators and meditation programs on how to best structure healthy sustainable practices. Objective: This study aimed to measure outcome change across a large and globally diverse population of meditators and meditations in their naturalistic practice environments, assess the dose-response relationships between practice habits and outcome change, and identify predictors of adherence. Methods: We used ecological momentary assessment to assess participants’ well-being over a 14-month period. We engineered outcomes related to the variability of change over time (equanimity) and recovery following a drop in mood (resilience) and established the convergent and divergent validity of these outcomes using a validated scale. Using linear mixed-effects and generalized additive mixed-effects models, we modeled outcome changes and patterns of dose-response across outcomes. We then used logistic regression to study the practice habits of participants in their first 30 sessions to derive odds ratios of long-term adherence. Results: Significant improvements were observed in all outcomes (P<.001). Generalized additive mixed models revealed rapid improvements over the first 50-100 sessions, with further improvements observed until the end of the study period. Outcome change corresponded to 1 extra day of improved mood for every 5 days meditated and half-a-day-faster mood recovery compared with baseline. Overall, consistency of practice was associated with the largest outcome change (4-7 d/wk). No significant differences were observed across session lengths in linear models (mood: P=.19; equanimity: P=.10; resilience: P=.29); however, generalized additive models revealed significant differences over time (P<.001). Longer sessions (21-30 min) were associated with the largest magnitude of change in mood from the 20th session onward and fewer sessions to recovery (increased resilience); midlength sessions (11-20 min) were associated with the largest decreases in recovery; and mood stability was similar across session lengths (equanimity). Completing a greater variety of practice types was associated with significantly greater improvements across all outcomes. Adhering to a long-term practice was best predicted by practice consistency (4-7 d/wk), a morning routine, and maintaining an equal balance between interoceptive and exteroceptive meditations. Conclusions: Long-term real-world digital meditation practice is effective and associated with improvements in mood, equanimity, and resilience. Practice consistency and variety rather than length best predict improvement. Long-term sustainable practices are best predicted by consistency, a morning routine, and a practice balanced across objects of focus that are internal and external to the body. %M 37725801 %R 10.2196/43358 %U https://www.jmir.org/2023/1/e43358 %U https://doi.org/10.2196/43358 %U http://www.ncbi.nlm.nih.gov/pubmed/37725801 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 9 %N %P e44320 %T Effects of Web-Based and Mobile Self-Care Support in Addition to Standard Care in Patients After Radical Prostatectomy: Randomized Controlled Trial %A Wennerberg,Camilla %A Hellström,Amanda %A Schildmeijer,Kristina %A Ekstedt,Mirjam %+ Department of Health and Caring Sciences, Linnaeus University, Hus Vita, Kalmar, SE-391 82, Sweden, 46 737822601, camilla.wennerberg@lnu.se %K eHealth %K linear mixed model %K prostatic neoplasms %K radical prostatectomy %K randomized controlled trial %K self-care %K telemedicine %K mobile health %K mHealth %K prostate cancer %K sexual dysfunction %K urinary incontinence %K web-based %K pelvic exercise %K physical activity %D 2023 %7 6.9.2023 %9 Original Paper %J JMIR Cancer %G English %X Background: Prostate cancer is a common form of cancer that is often treated with radical prostatectomy, which can leave patients with urinary incontinence and sexual dysfunction. Self-care (pelvic floor muscle exercises and physical activity) is recommended to reduce the side effects. As more and more men are living in the aftermath of treatment, effective rehabilitation support is warranted. Digital self-care support has the potential to improve patient outcomes, but it has rarely been evaluated longitudinally in randomized controlled trials. Therefore, we developed and evaluated the effects of digital self-care support (electronic Patient Activation in Treatment at Home [ePATH]) on prostate-specific symptoms. Objective: This study aimed to investigate the effects of web-based and mobile self-care support on urinary continence, sexual function, and self-care, compared with standard care, at 1, 3, 6, and 12 months after radical prostatectomy. Methods: A multicenter randomized controlled trial with 2 study arms was conducted, with the longitudinal effects of additional digital self-care support (ePATH) compared with those of standard care alone. ePATH was designed based on the self-determination theory to strengthen patients’ activation in self-care through nurse-assisted individualized modules. Men planned for radical prostatectomy at 3 county hospitals in southern Sweden were included offline and randomly assigned to the intervention or control group. The effects of ePATH were evaluated for 1 year after surgery using self-assessed questionnaires. Linear mixed models and ordinal regression analyses were performed. Results: This study included 170 men (85 in each group) from January 2018 to December 2019. The participants in the intervention and control groups did not differ in their demographic characteristics. In the intervention group, 64% (53/83) of the participants used ePATH, but the use declined over time. The linear mixed model showed no substantial differences between the groups in urinary continence (β=−5.60; P=.09; 95% CI −12.15 to −0.96) or sexual function (β=−.12; P=.97; 95% CI −7.05 to −6.81). Participants in the intervention and control groups did not differ in physical activity (odds ratio 1.16, 95% CI 0.71-1.89; P=.57) or pelvic floor muscle exercises (odds ratio 1.51, 95% CI 0.86-2.66; P=.15). Conclusions: ePATH did not affect postoperative side effects or self-care but reflected how this support may work in typical clinical conditions. To complement standard rehabilitation, digital self-care support must be adapted to the context and individual preferences for use and effect. Trial Registration: ISRCTN Registry ISRCTN18055968; https://www.isrctn.com/ISRCTN18055968 International Registered Report Identifier (IRRID): RR2-10.2196/11625 %M 37672332 %R 10.2196/44320 %U https://cancer.jmir.org/2023/1/e44320 %U https://doi.org/10.2196/44320 %U http://www.ncbi.nlm.nih.gov/pubmed/37672332 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 12 %N %P e41502 %T Just-In-Time Adaptive Intervention to Sit Less and Move More in People With Type 2 Diabetes: Protocol for a Microrandomized Trial %A Daryabeygi-Khotbehsara,Reza %A Dunstan,David W %A Islam,Sheikh Mohammed Shariful %A Zhang,Yuxin %A Abdelrazek,Mohamed %A Maddison,Ralph %+ Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221 Burwood Hw, Geelong, 3125, Australia, 61 3 924 459362, reza.d@deakin.edu.au %K diabetes %K just-in-time adaptive intervention %K JITAI %K micro-randomized trial %K MRT %K physical activity %K sedentary behavior %D 2023 %7 6.9.2023 %9 Protocol %J JMIR Res Protoc %G English %X Background: Reducing sedentary behavior and increasing physical activity in people with type 2 diabetes (T2D) are associated with various positive health benefits. Just-in-time adaptive interventions offer the potential to target both of these behaviors through more contextually aware, tailored, and personalized support. We have developed a just-in-time adaptive intervention to promote sitting less and moving more in people with T2D. Objective: This paper presents the study protocol for a microrandomized trial to investigate whether motivational messages are effective in reducing time spent sitting in people with T2D and to determine what behavior change techniques are effective and in which context (eg, location, etc). Methods: We will use a 6-week microrandomized trial design. A total of 22 adults with T2D will be recruited. The intervention aims to reduce sitting time and increase time spent standing and walking and comprises a mobile app (iMove), a bespoke activity sensor called Sedentary Behavior Detector (SORD), a messaging system, and a secured database. Depending on the randomization sequence, participants will potentially receive motivational messages 5 times a day. Results: Recruitment was initiated in October 2022. As of now, 6 participants (2 female and 4 male) have consented and enrolled in the study. Their baseline measurements have been completed, and they have started using iMove. The mean age of 6 participants is 56.8 years, and they were diagnosed with T2D for 9.4 years on average. Conclusions: This study will inform the optimization of digital behavior change interventions to support people with T2D Sit Less and Move More to increase daily physical activity. This study will generate new evidence about the immediate effectiveness of sedentary behavior interventions, their active ingredients, and associated factors. Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12622000426785; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383664 International Registered Report Identifier (IRRID): DERR1-10.2196/41502 %M 37672323 %R 10.2196/41502 %U https://www.researchprotocols.org/2023/1/e41502 %U https://doi.org/10.2196/41502 %U http://www.ncbi.nlm.nih.gov/pubmed/37672323 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e47183 %T Acceptability and Utility of a Smartphone App to Support Adolescent Mental Health (BeMe): Program Evaluation Study %A Prochaska,Judith J %A Wang,Yixin %A Bowdring,Molly A %A Chieng,Amy %A Chaudhary,Neha P %A Ramo,Danielle E %+ Stanford Prevention Research Center, Department of Medicine, Stanford University, 3180 Porter Drive Room A105, Palo Alto, CA, 94304-1212, United States, 1 650 724 3608, jpro@stanford.edu %K adolescents %K mobile app %K depression %K anxiety %K resilience %K digital intervention %K digital mental health %K mobile phone %D 2023 %7 28.8.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Adolescents face unprecedented mental health challenges, and technology has the opportunity to facilitate access and support digitally connected generations. The combination of digital tools and live human connection may hold particular promise for resonating with and flexibly supporting young people’s mental health. Objective: This study aimed to describe the BeMe app-based platform to support adolescents’ mental health and well-being and to examine app engagement, usability, and satisfaction. Methods: Adolescents in the United States, aged 13 to 20 years, were recruited via the web and enrolled between September 1 and October 31, 2022. App engagement, feature use, clinical functioning, and satisfaction with BeMe were examined for 30 days. BeMe provides content based on cognitive behavioral therapy, dialectical behavior therapy, motivational interviewing, and positive psychology; interactive activities; live text-based coaching; links to clinical services; and crisis support tools (digital and live). Results: The average age of the sample (N=13,421) was 15.04 (SD 1.7) years, and 56.72% (7612/13,421) identified with she/her pronouns. For the subsample that completed the in-app assessments, the mean scores indicated concern for depression (8-item Patient Health Questionnaire mean 15.68/20, SD 5.9; n=239), anxiety (7-item Generalized Anxiety Disorder Questionnaire mean 13.37/17, SD 5.0; n=791), and poor well-being (World Health Organization–Five Well-being Index mean 30.15/100, SD 16.1; n=1923). Overall, the adolescents engaged with BeMe for an average of 2.38 (SD 2.7) days in 7.94 (SD 24.1) sessions and completed 11.26 (SD 19.8) activities. Most adolescents engaged with BeMe’s content (12,270/13,421, 91.42%), mood ratings (13,094/13,421, 97.56%), and interactive skills (10,098/13,421, 75.24%), and almost one-fifth of the adolescents engaged with coaching (2539/13,421, 18.92%), clinical resources (2411/13,421, 17.96%), and crisis support resources (2499/13,421, 18.62%). Overall app engagement (total activities) was highest among female and gender-neutral adolescents compared with male adolescents (all P<.001) and was highest among younger adolescents (aged 13-14 years) compared with all other ages (all P<.001). Satisfaction ratings were generally high for content (eg, 158/176, 89.8% rated as helpful and 1044/1139, 91.66% improved coping self-efficacy), activities (5362/8468, 63.32% helpful and 4408/6072, 72.6% useful in coping with big feelings), and coaching (747/894, 83.6% helpful and 747/894, 83.6% improved coping self-efficacy). Engagement (total activities completed) predicted the likelihood of app satisfaction (P<.001). Conclusions: Many adolescents downloaded the BeMe app and completed multiple sessions and activities. Engagement with BeMe was higher among female and younger adolescents. Ratings of BeMe’s content, activities, and coaching were very positive for cognitive precursors aimed at reducing depression and anxiety and improving well-being. The findings will inform future app development to promote more sustained engagement, and future evaluations will assess the effects of BeMe on changes in mental health outcomes. %M 37639293 %R 10.2196/47183 %U https://mhealth.jmir.org/2023/1/e47183 %U https://doi.org/10.2196/47183 %U http://www.ncbi.nlm.nih.gov/pubmed/37639293 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e43676 %T Acceptability of the LetSync App Wireframes for an mHealth Intervention to Improve HIV Care Engagement and Treatment Among Black Partnered Sexual Minority Men: Findings from In-Depth Qualitative Interviews %A Becker,Nozipho %A Kim,Hyunjin C %A Bright,Darius J %A Williams III,Robert %A Anguera,Joaquin A %A Arnold,Emily A %A Saberi,Parya %A Neilands,Torsten B %A Pollack,Lance M %A Tan,Judy Y %+ Center for AIDS Prevention Studies, Division of Prevention Science, Department of Medicine, University of California San Francisco, 550 16th Street, 3rd Floor, San Francisco, CA, 94158, United States, 1 415 502 1000 ext 17163, judy.tan@ucsf.edu %K digital health %K mobile health %K mHealth %K mobile app %K app %K Black sexual minority men %K couples %K HIV care engagement %K HIV treatment %K United States %K mobile phone %D 2023 %7 25.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: HIV disparities continue to be a significant challenge affecting Black sexual minority men in the United States. Inadequate engagement and retention of patients in HIV care has been associated with poor health outcomes. Interventions to improve sustained commitment to HIV care are needed. Mobile health interventions can help facilitate access to and use of HIV health services, particularly among individuals at risk for disengaging with care. Objective: We designed the LetSync app wireframes for a mobile health intervention using a couple-centered design approach to improve HIV engagement and treatment among Black sexual minority men and their partners. The objective of this study was to gauge future app user interest and elicit feedback to improve the design, development, and usability of the LetSync app. Methods: We conducted in-depth interviews with 24 Black sexual minority men to assess the acceptability of the LetSync app wireframes between May 2020 and January 2021. Participants reviewed the LetSync app wireframes and provided feedback regarding perceived usefulness and interest in future app use and suggestions for improvement. Results: Participants indicated interest in the future LetSync app and noted that the wireframes’ features were acceptable and usable. In our study, the future LetSync app was frequently referred to as a potential resource that could help facilitate users’ engagement in HIV care through the following mechanisms: enable scheduling of appointments and timely reminders for clinic visits; help improve HIV medication adherence; encourage and motivate participants to ask questions to their health care provider and stay engaged in conversations during clinic visits; facilitate effective communication by assisting couples with planning, coordination, and management of daily routines; help participants understand their partner’s health needs, including access to and use of health care services; and facilitate participants’ ability to improve their relationship skills, partner support, and self-efficacy in managing conflict. In addition to near-universal interest in potential daily app use, study participants indicted that they would recommend the LetSync app to other family members, friends, and people in their social networks who are living with HIV. Conclusions: Our findings revealed considerable interest in future app use for HIV care management, which could possibly increase the chance of the LetSync app being successfully adopted by Black sexual minority men in couples. Owing to its interactive and couple-centered approach, the LetSync app could help improve communication between Black sexual minority men and their partners and health providers. In addition, the LetSync app could provide an acceptable modality for these men to receive support in accessing HIV care services. %M 37624634 %R 10.2196/43676 %U https://formative.jmir.org/2023/1/e43676 %U https://doi.org/10.2196/43676 %U http://www.ncbi.nlm.nih.gov/pubmed/37624634 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44924 %T Understanding Attrition in Text-Based Health Promotion for Fathers: Survival Analysis %A Fletcher,Richard %A Regan,Casey %A Dizon,Jason %A Leigh,Lucy %+ School of Health Sciences, College of Health, Medicine, and Wellbeing, The University of Newcastle, University Drive, Callaghan, 2308, Australia, 61 429 152 405, richard.fletcher@newcastle.edu.au %K attrition %K dropout %K text-based program %K parenting %K fathers %D 2023 %7 18.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Web-based interventions targeting parents with health and parenting support frequently report high rates of attrition. The SMS4dads text messaging program, developed in Australia, has delivered texts to over 10,000 fathers. The brief text messages, which are sent 3 times per week from 16 weeks of gestation to 48 weeks after birth, include regular reminders that participants can leave the program by texting back “STOP” to any message. Although acceptance of the program is high, almost 1 in 5 ask it to be removed. Analyzing the factors influencing attrition from digital parenting programs such as SMS4dads may assist in developing more effective interventions. Objective: This study aimed to examine factors associated with attrition in a text-based intervention targeting fathers. Methods: Demographic characteristics, requests to complete a psychological scale, individual message content, participant feedback, and automatically collected data registering clicks on links embedded in the texts were examined to identify attrition factors among 3261 participants enrolled in SMS4dads from 4 local health districts in New South Wales, Australia, between September 2020 and December 2021. Results: Participants who were smokers, recorded risky alcohol consumption, had a lower education level, or signed up prenatally had 30% to 47% higher hazard of dropout from the program, whereas participant age, Aboriginal or Torres Strait Islander status, rurality, and psychological distress score (as Kessler Psychological Distress Scale [K10] category) were not associated with dropout. Primary reasons for dropping out reported by 202 of 605 respondents included “other reasons” (83/202, 41.1%), followed by “not helpful” (47/202, 23.3%) and “too busy” (44/202, 21.8%). Program features such as repeated requests to complete a psychological scale (K10) and the content of individual messages were not linked to increased dropout rates. Analysis of a sample (216/2612) of inactive participants who had not engaged (clicked on any embedded links) for at least 10 weeks but who had not opted out identified a further 1.5% of participants who would opt to leave the program if asked. Conclusions: Identifying which features of the participant population and of the program are linked to dropout rates can provide guidance for improving program adherence. However, with limited information from feedback surveys of those exiting early, knowing which features to target does not, by itself, suggest ways to increase engagement. Planning ahead to include robust measures of attrition, including more detailed feedback from participants, could provide more effective guidance. A novel element in this study was seeking feedback from inactive participants to estimate dropout from this group and thereby provide an overall dropout rate of 20%. The retention rate of 80%, relatively high compared with other web-based parenting programs for fathers, suggests that tailoring the content to specifically address fathers’ role may be an important consideration in reducing fathers’ disengagement. %M 37594788 %R 10.2196/44924 %U https://formative.jmir.org/2023/1/e44924 %U https://doi.org/10.2196/44924 %U http://www.ncbi.nlm.nih.gov/pubmed/37594788 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e47436 %T Design and Early Use of the Nationally Implemented Healthier You National Health Service Digital Diabetes Prevention Programme: Mixed Methods Study %A Ross,Jamie %A Hawkes,Rhiannon E %A Miles,Lisa M %A Cotterill,Sarah %A Bower,Peter %A Murray,Elizabeth %+ Centre for Primary Care, Wolfson Institute of Population Health Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB, United Kingdom, 44 02080168037, jamie.ross@qmul.ac.uk %K digital health %K engagement %K diabetes prevention %K mobile phone %D 2023 %7 17.8.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The Healthier You National Health Service Digital Diabetes Prevention Programme (NHS-digital-DPP) is a 9-month digital behavior change intervention delivered by 4 independent providers that is implemented nationally across England. No studies have explored the design features included by service providers of digital diabetes prevention programs to promote engagement, and little is known about how participants of nationally implemented digital diabetes prevention programs such as this one make use of them. Objective: This study aimed to understand engagement with the NHS-digital-DPP. The specific objectives were to describe how engagement with the NHS-digital-DPP is promoted via design features and strategies and describe participants’ early engagement with the NHS-digital-DPP apps. Methods: Mixed methods were used. The qualitative study was a secondary analysis of documents detailing the NHS-digital-DPP intervention design and interviews with program developers (n=6). Data were deductively coded according to an established framework of engagement with digital health interventions. For the quantitative study, anonymous use data collected over 9 months for each provider representing participants’ first 30 days of use of the apps were obtained for participants enrolled in the NHS-digital-DPP. Use data fields were categorized into 4 intervention features (Track, Learn, Coach Interactions, and Peer Support). The amount of engagement with the intervention features was calculated for the entire cohort, and the differences between providers were explored statistically. Results: Data were available for 12,857 participants who enrolled in the NHS-digital-DPP during the data collection phase. Overall, 94.37% (12,133/12,857) of those enrolled engaged with the apps in the first 30 days. The median (IQR) number of days of use was 11 (2-25). Track features were engaged with the most (number of tracking events: median 46, IQR 3-22), and Peer Support features were the least engaged with, a median value of 0 (IQR 0-0). Differences in engagement with features were observed across providers. Qualitative findings offer explanations for the variations, including suggesting the importance of health coaches, reminders, and regular content updates to facilitate early engagement. Conclusions: Almost all participants in the NHS-digital-DPP started using the apps. Differences across providers identified by the mixed methods analysis provide the opportunity to identify features that are important for engagement with digital health interventions and could inform the design of other digital behavior change interventions. %M 37590056 %R 10.2196/47436 %U https://www.jmir.org/2023/1/e47436 %U https://doi.org/10.2196/47436 %U http://www.ncbi.nlm.nih.gov/pubmed/37590056 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43727 %T Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review %A Forbes,Ainslie %A Keleher,Madeline Rose %A Venditto,Michael %A DiBiasi,Faith %+ Otsuka Pharmaceutical Development & Commercialization, Inc, 508 Carnegie Center Dr, Princeton, NJ, 08540, United States, 1 301 956 2702, ainslie.forbes@otsuka-us.com %K digital therapeutics %K digital interventions %K digital health %K mobile health %K mobile phone %K depression %K major depressive disorder %K engagement %K adherence %K systematic literature review %D 2023 %7 11.8.2023 %9 Review %J J Med Internet Res %G English %X Background: New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness. Objective: This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy. Methods: We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study. Results: This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability. Conclusions: Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations. %M 37566447 %R 10.2196/43727 %U https://www.jmir.org/2023/1/e43727 %U https://doi.org/10.2196/43727 %U http://www.ncbi.nlm.nih.gov/pubmed/37566447 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 8 %N %P e44943 %T User Retention and Engagement in the Digital-Based Diabetes Education and Self-Management for Ongoing and Newly Diagnosed (myDESMOND) Program: Descriptive Longitudinal Study %A Barker,Mary M %A Chauhan,Radhika %A Davies,Melanie J %A Brough,Christopher %A Northern,Alison %A Stribling,Bernie %A Schreder,Sally %A Khunti,Kamlesh %A Hadjiconstantinou,Michelle %+ Diabetes Research Centre, University of Leicester, NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, LE4 5PW, United Kingdom, 44 116 2584320, mh333@le.ac.uk %K retention %K engagement %K digital self-management %K type 2 diabetes %K mobile phone %D 2023 %7 21.7.2023 %9 Original Paper %J JMIR Diabetes %G English %X Background: Digital health interventions have the potential to improve the physical and psychosocial health of people living with type 2 diabetes. However, research investigating the long-term (≥1 year) retention and engagement of users within these programs is limited. Objective: The aim of this study was to evaluate long-term user retention and engagement in the digital-based Diabetes Education and Self-Management for Ongoing and Newly Diagnosed (myDESMOND) program, using real-world data. Methods: Anonymized data from all myDESMOND users who registered with the program on or before November 16, 2020, were included in the analyses. User retention was defined as the period between the day a user registered with the myDESMOND program and their last day of access. The primary engagement outcome was defined as the total number of log-ins to the program per user. The associations between retention, engagement, and sociodemographic factors (age, sex, and ethnicity) were tested using Cox regression models and Wilcoxon rank sum tests. Results: A total of 9522 myDESMOND users were included in this analysis. Of the 9522 users, 5360 (56.29%) remained on the program for at least a month, whereas 1676 (17.6%) remained on the program for at least 1 year. Retention was significantly higher among older users; the adjusted hazard ratio (representing the risk of users leaving the program within the first year) among users aged ≥50 years, compared with those aged <50 years, was 0.79 (95% CI 0.75-0.84; P<.001). The median number of myDESMOND log-ins per user was 8 (IQR 4-8); however, this was significantly lower among users aged <50 years (P<.001). Engagement metrics also differed according to sociodemographic characteristics; the estimated time spent per log-in was 5.35 (IQR 2.22-11.80) minutes among all users; however, this was significantly higher among female users (P<.001), users aged ≥50 years (P<.001), and users of White ethnicity (P=.02). Conclusions: Although retention and engagement of users within myDESMOND were found to be high, these findings highlight the need for age- and culture-specific implementation strategies and content adaptations to improve retention and engagement among all users of self-management programs. %M 37477963 %R 10.2196/44943 %U https://diabetes.jmir.org/2023/1/e44943 %U https://doi.org/10.2196/44943 %U http://www.ncbi.nlm.nih.gov/pubmed/37477963 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e47121 %T Behavioral Economic Strategies to Improve Enrollment Rates in Clinical Research: Embedded Recruitment Pilot Trial %A Greene,Brittney %A Bernardo,Leah %A Thompson,Morgan %A Loughead,James %A Ashare,Rebecca %+ State University of New York at Buffalo, 334 Diefendorf Hall, Buffalo, NY, 14214, United States, 1 7168296273, rlashare@buffalo.edu %K behavior change %K behavioral economics %K clinical trials %K contingency management %K evidence based %K information provision %K recruitment %K retention %K SMS text messaging %K study within a trial %K SWAT %D 2023 %7 21.7.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Nearly 1 in 3 clinical trials end prematurely due to underenrollment. Strategies to enhance recruitment are often implemented without scientific rigor to evaluate efficacy. Evidence-based, cost-effective behavioral economic strategies designed to influence decision-making may be useful to promote clinical trial enrollment. Objective: This study evaluated 2 behavioral economic strategies to improve enrollment and retention rates across 4 clinical trials: information provision (IP) and contingency management (CM; ie, lottery). IP targets descriptive and injunctive norms about participating in research and CM provides participants incentives to reinforce a target behavior. Methods: A sample of 212 participants was enrolled across 4 clinical trials focused on tobacco use: 2 focused on HIV and 2 focused on neuroimaging. The CM condition included a lottery: for each study visit completed, participants received 5 “draws” from a bowl containing 500 “chips” valued at US $0, US $1, US $5, or US $100. In the IP condition, text messages that targeted injunctive norms about research (eg, “Many find it a rewarding way to advance science and be part of a community”) were sent through the Way to Health platform before all study visits. Participants were randomized to 1 of 4 conditions: IP, CM, IP+CM, or standard recruitment (SR). We performed logistic regression, controlling for sex and study, with condition as a between-subject predictor. Outcomes were the percentage of participants who attended a final eligibility visit (primary), met intent-to-treat (ITT) criteria (secondary), and completed the study (secondary). Recruitment was evaluated by the percentage of participants who attended a final eligibility visit, enrollment by ITT status, and retention by the percentage of participants who completed the study. Results: Rates of attending the eligibility visit and meeting ITT status were 58.9% (33/56) and 33.9% (19/56) for IP+CM; 45.5% (25/55) and 18.2% (10/55) for IP only; 41.5% (22/53) and 18.9% (10/53) for CM only; and 37.5% (18/48) and 12.5% (6/48) for SR, respectively. In the logistic regression, females were more likely to meet ITT status than males (odds ratio [OR] 2.7, 95% CI 1.2-5.7; P=.01). The IP+CM group was twice as likely to attend the final eligibility visit than the SR group (OR 2.4, 95% CI 1.1-5.2; P=.04). The IP+CM group was also significantly more likely to reach ITT status than the SR condition (OR 3.9, 95% CI 1.3-11.1; P=.01). Those who received any active intervention (IP, CM, or IP+CM) had a higher study completion rate (33/53, 63.5%) compared to those who received SR (5/12, 41.7%), but this difference was not significant (P=.26). Conclusions: Combining IP and CM strategies may motivate participants to participate in research and improve recruitment and retention rates. Evidence from this study provides preliminary support for the utility of behavioral economics strategies to improve enrollment and reduce attrition in clinical trials. %M 37477975 %R 10.2196/47121 %U https://formative.jmir.org/2023/1/e47121 %U https://doi.org/10.2196/47121 %U http://www.ncbi.nlm.nih.gov/pubmed/37477975 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e42093 %T Comparing Adherence to the Experience Sampling Method Among Patients With Schizophrenia Spectrum Disorder and Unaffected Individuals: Observational Study From the Multicentric DiAPAson Project %A Zarbo,Cristina %A Zamparini,Manuel %A Nielssen,Olav %A Casiraghi,Letizia %A Rocchetti,Matteo %A Starace,Fabrizio %A de Girolamo,Giovanni %A , %+ Unit of Epidemiological and Evaluation Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Via Pilastroni 4, Brescia, 25125, Italy, 39 3896875449, cristinazarbo@gmail.com %K ecological momentary assessment %K multicenter study %K mobile application %K mobile app %K compliance %K psychosis %D 2023 %7 18.7.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The Experience Sampling Method (ESM) is a valid method of remotely recording activities and mood, but the predictors of adherence to ESM in patients with Schizophrenia Spectrum Disorder (SSD) are not known. Studies on adherence are significant as they highlight the strengths and weaknesses of ESM-based study designs and allow the development of recommendations and practical guidelines for implementing future studies or treatment plans. Objective: The aim of this study was to compare the adherence to ESM in patients with SSD and unaffected control individuals, investigate their patterns, and report the predictors of adherence. Methods: In total, 131 patients with SSD (74 in residential facilities and 57 outpatients) and 115 unaffected control individuals were recruited at 10 different centers in Italy as part of the DiAPAson project. Demographic information, symptom severity, disability level, and level of function were recorded for the clinical sample. Participants were evaluated for daily time use and mood through a smartphone-based ESM 8 times a day for 7 consecutive days. Adherence was measured by the response rate to ESM notifications. Results were analyzed using the chi-square test, ANOVA, Kruskal-Wallis test, and Friedman test, and a logistic regression model. Results: The overall adherence rate in this study was 50% for residents, 59% for outpatients, and 78% for unaffected control individuals. Indeed, patients with SSD had a lower rate of adherence to ESM than the unaffected control group (P≤.001), independent of time slot, day of monitoring, or day of the week. No differences in adherence rates between weekdays and weekends were found among the 3 groups. The adherence rate was the lowest in the late evening time slot (8 PM to 12 AM) and days 6-7 of the study for both patients with SSD and unaffected control individuals. The adherence rate among patients with SSD was not predicted by sociodemographic characteristics, cognitive function, or other clinical features. A higher adherence rate (ie, ≥70%) among patients with SSD was predicted by higher collaboration skills (odds ratio [OR] 2.952; P=.046) and self-esteem (OR 3.394; P=.03), and lower positive symptom severity (OR 0.835; P=.04). Conclusions: Adherence to ESM prompts for both patients with SSD and unaffected control individuals decreased during late evening and after 6 days of monitoring. Higher self-esteem and collaboration skills predicted higher adherence to ESM among patients with SSD, while higher positive symptom scores predicted lower adherence rates. This study provides important information to guide protocols for future studies using ESM. Future clinical or research studies should set ESM monitoring to waking hours, limit the number of days of monitoring, select patients with more collaborative skills and avoid those with marked positive symptoms, provide intensive training sessions, and improve participants’ self-confidence with technologies. International Registered Report Identifier (IRRID): RR2-10.1186/s12888-020-02588-y %M 37463030 %R 10.2196/42093 %U https://www.jmir.org/2023/1/e42093 %U https://doi.org/10.2196/42093 %U http://www.ncbi.nlm.nih.gov/pubmed/37463030 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e45057 %T Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study %A Crane,Nicole %A Hagerman,Charlotte %A Horgan,Olivia %A Butryn,Meghan %+ Center for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, 3141 Chestnut Street, Stratton Hall, Philadelphia, PA, 19104, United States, 1 724 740 8648, nvt24@drexel.edu %K weight loss %K digital technology %K diet %K exercise %K behavior change %K mobile phone %D 2023 %7 18.7.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Long-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence. Objective: This study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3). Methods: Participants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling. Results: During WLM, consistently high rates of SM (≥50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had ≥1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03). Conclusions: Participants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement. %M 37463017 %R 10.2196/45057 %U https://mhealth.jmir.org/2023/1/e45057 %U https://doi.org/10.2196/45057 %U http://www.ncbi.nlm.nih.gov/pubmed/37463017 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 12 %N %P e47930 %T Leveraging Electronic Health Record Technology and Team Care to Address Medication Adherence: Protocol for a Cluster Randomized Controlled Trial %A Blecker,Saul %A Schoenthaler,Antoinette %A Martinez,Tiffany Rose %A Belli,Hayley M %A Zhao,Yunan %A Wong,Christina %A Fitchett,Cassidy %A Bearnot,Harris R %A Mann,Devin %+ Department of Population Health, NYU Grossman School of Medicine, 227 E 30th Street, 6th Floor, New York, NY, 10016, United States, 1 6465012513, saul.blecker@nyulangone.org %K medication adherence %K hypertension %K clinical decision support %K proportion of days covered %K EHR %K electronic health record %K technology %K adherence %K primary care %D 2023 %7 7.7.2023 %9 Protocol %J JMIR Res Protoc %G English %X Background: Low medication adherence is a common cause of high blood pressure but is often unrecognized in clinical practice. Electronic data linkages between electronic health records (EHRs) and pharmacies offer the opportunity to identify low medication adherence, which can be used for interventions at the point of care. We developed a multicomponent intervention that uses linked EHR and pharmacy data to automatically identify patients with elevated blood pressure and low medication adherence. The intervention then combines team-based care with EHR-based workflows to address medication nonadherence. Objective: This study aims to describe the design of the Leveraging EHR Technology and Team Care to Address Medication Adherence (TEAMLET) trial, which tests the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence among patients with hypertension. Methods: TEAMLET is a pragmatic, cluster randomized controlled trial in which 10 primary care practices will be randomized 1:1 to the multicomponent intervention or usual care. We will include all patients with hypertension and low medication adherence who are seen at enrolled practices. The primary outcome is medication adherence, as measured by the proportion of days covered, and the secondary outcome is clinic systolic blood pressure. We will also assess intervention implementation, including adoption, acceptability, fidelity, cost, and sustainability. Results: As of May 2023, we have randomized 10 primary care practices into the study, with 5 practices assigned to each arm of the trial. The enrollment for the study commenced on October 5, 2022, and the trial is currently ongoing. We anticipate patient recruitment to go through the fall of 2023 and the primary outcomes to be assessed in the fall of 2024. Conclusions: The TEAMLET trial will evaluate the effectiveness of a multicomponent intervention that leverages EHR-based data and team-based care on medication adherence. If successful, the intervention could offer a scalable approach to address inadequate blood pressure control among millions of patients with hypertension. Trial Registration: ClinicalTrials.gov NCT05349422; https://clinicaltrials.gov/ct2/show/NCT05349422 International Registered Report Identifier (IRRID): DERR1-10.2196/47930 %M 37418304 %R 10.2196/47930 %U https://www.researchprotocols.org/2023/1/e47930 %U https://doi.org/10.2196/47930 %U http://www.ncbi.nlm.nih.gov/pubmed/37418304 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44126 %T Barriers to and Facilitators of Using Remote Measurement Technology in the Long-Term Monitoring of Individuals With ADHD: Interview Study %A Denyer,Hayley %A Deng,Qigang %A Adanijo,Abimbola %A Asherson,Philip %A Bilbow,Andrea %A Folarin,Amos %A Groom,Madeleine J %A Hollis,Chris %A Wykes,Til %A Dobson,Richard JB %A Kuntsi,Jonna %A Simblett,Sara %+ Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom, 44 20 7848 5308, hayley.denyer@kcl.ac.uk %K attention-deficit/hyperactivity disorder %K ADHD %K remote measurement technology %K engagement %K barriers and facilitators %K qualitative analysis %K mobile phone %D 2023 %7 30.6.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Remote measurement technology (RMT) has the potential to address current research and clinical challenges of attention-deficit/hyperactivity disorder (ADHD) symptoms and its co-occurring mental health problems. Despite research using RMT already being successfully applied to other populations, adherence and attrition are potential obstacles when applying RMT to a disorder such as ADHD. Hypothetical views and attitudes toward using RMT in a population with ADHD have previously been explored; however, to our knowledge, there is no previous research that has used qualitative methods to understand the barriers to and facilitators of using RMT in individuals with ADHD following participation in a remote monitoring period. Objective: We aimed to evaluate the barriers to and facilitators of using RMT in individuals with ADHD compared with a group of people who did not have a diagnosis of ADHD. We also aimed to explore participants’ views on using RMT for 1 or 2 years in future studies. Methods: In total, 20 individuals with ADHD and 20 individuals without ADHD were followed up for 10 weeks using RMT that involved active (questionnaires and cognitive tasks) and passive (smartphone sensors and wearable devices) monitoring; 10 adolescents and adults with ADHD and 12 individuals in a comparison group completed semistructured qualitative interviews at the end of the study period. The interviews focused on potential barriers to and facilitators of using RMT in adults with ADHD. A framework methodology was used to explore the data qualitatively. Results: Barriers to and facilitators of using RMT were categorized as health-related, user-related, and technology-related factors across both participant groups. When comparing themes that emerged across the participant groups, both individuals with and without ADHD experienced similar barriers and facilitators in using RMT. The participants agreed that RMT can provide useful objective data. However, slight differences between the participant groups were identified as barriers to RMT across all major themes. Individuals with ADHD described the impact that their ADHD symptoms had on participating (health-related theme), commented on the perceived cost of completing the cognitive tasks (user-related theme), and described more technical challenges (technology-related theme) than individuals without ADHD. Hypothetical views on future studies using RMT in individuals with ADHD for 1 or 2 years were positive. Conclusions: Individuals with ADHD agreed that RMT, which uses repeated measurements with ongoing active and passive monitoring, can provide useful objective data. Although themes overlapped with previous research on barriers to and facilitators of engagement with RMT (eg, depression and epilepsy) and with a comparison group, there are unique considerations for people with ADHD, for example, understanding the impact that ADHD symptoms may have on engaging with RMT. Researchers need to continue working with people with ADHD to develop future RMT studies for longer periods. %M 37389932 %R 10.2196/44126 %U https://formative.jmir.org/2023/1/e44126 %U https://doi.org/10.2196/44126 %U http://www.ncbi.nlm.nih.gov/pubmed/37389932 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43633 %T Predicting Disengagement to Better Support Outcomes in a Web-Based Weight Loss Program Using Machine Learning Models: Cross-Sectional Study %A Brankovic,Aida %A Hendrie,Gilly A %A Baird,Danielle L %A Khanna,Sankalp %+ The Australian e-Health Research Centre, Health & Biosecurity, Commonwealth Scientific Industrial Research Organisation, STARS building Level 7, Herston, Brisbane, 4029, Australia, 61 732533629, aida.brankovic@csiro.au %K web-based weight loss program %K predicting engagement %K machine learning–driven intervention %K machine learning %K artificial intelligence %D 2023 %7 26.6.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Engagement is key to interventions that achieve successful behavior change and improvements in health. There is limited literature on the application of predictive machine learning (ML) models to data from commercially available weight loss programs to predict disengagement. Such data could help participants achieve their goals. Objective: This study aimed to use explainable ML to predict the risk of member disengagement week by week over 12 weeks on a commercially available web-based weight loss program. Methods: Data were available from 59,686 adults who participated in the weight loss program between October 2014 and September 2019. Data included year of birth, sex, height, weight, motivation to join the program, use statistics (eg, weight entries, entries into the food diary, views of the menu, and program content), program type, and weight loss. Random forest, extreme gradient boosting, and logistic regression with L1 regularization models were developed and validated using a 10-fold cross-validation approach. In addition, temporal validation was performed on a test cohort of 16,947 members who participated in the program between April 2018 and September 2019, and the remaining data were used for model development. Shapley values were used to identify globally relevant features and explain individual predictions. Results: The average age of the participants was 49.60 (SD 12.54) years, the average starting BMI was 32.43 (SD 6.19), and 81.46% (39,594/48,604) of the participants were female. The class distributions (active and inactive members) changed from 39,369 and 9235 in week 2 to 31,602 and 17,002 in week 12, respectively. With 10-fold-cross-validation, extreme gradient boosting models had the best predictive performance, which ranged from 0.85 (95% CI 0.84-0.85) to 0.93 (95% CI 0.93-0.93) for area under the receiver operating characteristic curve and from 0.57 (95% CI 0.56-0.58) to 0.95 (95% CI 0.95-0.96) for area under the precision-recall curve (across 12 weeks of the program). They also presented a good calibration. Results obtained with temporal validation ranged from 0.51 to 0.95 for area under a precision-recall curve and 0.84 to 0.93 for area under the receiver operating characteristic curve across the 12 weeks. There was a considerable improvement in area under a precision-recall curve of 20% in week 3 of the program. On the basis of the computed Shapley values, the most important features for predicting disengagement in the following week were those related to the total activity on the platform and entering a weight in the previous weeks. Conclusions: This study showed the potential of applying ML predictive algorithms to help predict and understand participants’ disengagement with a web-based weight loss program. Given the association between engagement and health outcomes, these findings can prove valuable in providing better support to individuals to enhance their engagement and potentially achieve greater weight loss. %M 37358890 %R 10.2196/43633 %U https://www.jmir.org/2023/1/e43633 %U https://doi.org/10.2196/43633 %U http://www.ncbi.nlm.nih.gov/pubmed/37358890 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e45414 %T Usage and Daily Attrition of a Smartphone-Based Health Behavior Intervention: Randomized Controlled Trial %A Egilsson,Erlendur %A Bjarnason,Ragnar %A Njardvik,Urdur %+ Department of Psychology, University of Iceland, Saemundargata 12, Reykjavik, 102, Iceland, 354 5254240, erlendu@hi.is %K mHealth intervention %K mobile health %K adolescent %K attrition %K mental health %K physical activity %D 2023 %7 26.6.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Although most adolescents have access to smartphones, few of them use mobile health (mHealth) apps for health improvement, highlighting the apparent lack of interest in mHealth apps among adolescents. Adolescent mHealth interventions have been burdened with high attrition rates. Research on these interventions among adolescents has frequently lacked detailed time-related attrition data alongside analysis of attrition reasons through usage. Objective: The objective was to obtain daily attrition rates among adolescents in an mHealth intervention to gain a deeper understanding of attrition patterns, including the role of motivational support, such as altruistic rewards, through analysis of app usage data. Methods: A randomized controlled trial was conducted with 304 adolescent participants (152 boys and 152 girls) aged 13-15 years. Based on 3 participating schools, participants were randomly assigned to control, treatment as usual (TAU), and intervention groups. Measures were obtained at baseline, continuously throughout the 42-day trial period (research groups), and at the trial end. The mHealth app is called SidekickHealth and is a social health game with the following 3 main categories: nutrition, mental health, and physical health. Primary measures were attrition based on time from launch, and the type, frequency, and time of health behavior exercise usage. Outcome differences were obtained through comparison tests, while regression models and survival analyses were used for attrition measures. Results: Attrition differed significantly between the intervention and TAU groups (44.4% vs 94.3%; χ21=61.220; P<.001). The mean usage duration was 6.286 days in the TAU group and 24.975 days in the intervention group. In the intervention group, male participants were active significantly longer than female participants (29.155 vs 20.433 days; χ21=6.574; P<.001). Participants in the intervention group completed a larger number of health exercises in all trial weeks, and a significant decrease in usage was observed from the first to second week in the TAU group (t105=9.208; P<.001) but not in the intervention group. There was a significant increase in health exercises in the intervention group from the fifth to sixth week (t105=3.446; P<.001). Such a significant increase in usage was not evident in the TAU group. The research group was significantly related to attrition time (hazard ratio 0.308, 95% CI 0.222-0.420), as well as the numbers of mental health exercises (P<.001) and nutrition exercises (P<.001). Conclusions: Differences in attrition rates and usage between groups of adolescents were identified. Motivational support is a significant factor for lowering attrition in adolescent mHealth interventions. The results point to sensitivity periods in the completion of diverse health tasks, and emphasis on time-specific attrition, along with the type, frequency, and time of health behavior exercise usage, is likely a fruitful avenue for further research on mHealth interventions for adolescent populations, in which attrition rates remain excessive. Trial Registration: ClinicalTrials.gov NCT05912439; https://clinicaltrials.gov/study/NCT05912439 %M 37358888 %R 10.2196/45414 %U https://mhealth.jmir.org/2023/1/e45414 %U https://doi.org/10.2196/45414 %U http://www.ncbi.nlm.nih.gov/pubmed/37358888 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e38342 %T How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial %A Bell,Lauren %A Garnett,Claire %A Bao,Yihan %A Cheng,Zhaoxi %A Qian,Tianchen %A Perski,Olga %A Potts,Henry W W %A Williamson,Elizabeth %+ Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, United Kingdom, 44 02035495303, h.potts@ucl.ac.uk %K mobile health %K mHealth %K digital health %K behavior change %K behavior change %K digital behavior change %K engagement %K micro-randomized trial %K randomized trial %K randomization %K just-in-time adaptive intervention %K adaptive intervention %K push notification %K notification %K excessive alcohol consumption %K smartphone app %K alcohol %K drinking %K drinker %K mobile phone %D 2023 %7 9.6.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Drink Less is a behavior change app to help higher-risk drinkers in the United Kingdom reduce their alcohol consumption. The app includes a daily notification asking users to “Please complete your drinks and mood diary,” yet we did not understand the causal effect of the notification on engagement nor how to improve this component of Drink Less. We developed a new bank of 30 new messages to increase users’ reflective motivation to engage with Drink Less. This study aimed to determine how standard and new notifications affect engagement. Objective: Our objective was to estimate the causal effect of the notification on near-term engagement, to explore whether this effect changed over time, and to create an evidence base to further inform the optimization of the notification policy. Methods: We conducted a micro-randomized trial (MRT) with 2 additional parallel arms. Inclusion criteria were Drink Less users who consented to participate in the trial, self-reported a baseline Alcohol Use Disorders Identification Test score of ≥8, resided in the United Kingdom, were aged ≥18 years, and reported interest in drinking less alcohol. Our MRT randomized 350 new users to test whether receiving a notification, compared with receiving no notification, increased the probability of opening the app in the subsequent hour, over the first 30 days since downloading Drink Less. Each day at 8 PM, users were randomized with a 30% probability of receiving the standard message, a 30% probability of receiving a new message, or a 40% probability of receiving no message. We additionally explored time to disengagement, with the allocation of 60% of eligible users randomized to the MRT (n=350) and 40% of eligible users randomized in equal number to the 2 parallel arms, either receiving the no notification policy (n=98) or the standard notification policy (n=121). Ancillary analyses explored effect moderation by recent states of habituation and engagement. Results: Receiving a notification, compared with not receiving a notification, increased the probability of opening the app in the next hour by 3.5-fold (95% CI 2.91-4.25). Both types of messages were similarly effective. The effect of the notification did not change significantly over time. A user being in a state of already engaged lowered the new notification effect by 0.80 (95% CI 0.55-1.16), although not significantly. Across the 3 arms, time to disengagement was not significantly different. Conclusions: We found a strong near-term effect of engagement on the notification, but no overall difference in time to disengagement between users receiving the standard fixed notification, no notification at all, or the random sequence of notifications within the MRT. The strong near-term effect of the notification presents an opportunity to target notifications to increase “in-the-moment” engagement. Further optimization is required to improve the long-term engagement. International Registered Report Identifier (IRRID): RR2-10.2196/18690 %M 37294612 %R 10.2196/38342 %U https://mhealth.jmir.org/2023/1/e38342 %U https://doi.org/10.2196/38342 %U http://www.ncbi.nlm.nih.gov/pubmed/37294612 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45234 %T Promoting Engagement With Smartphone Apps for Suicidal Ideation in Young People: Development of an Adjunctive Strategy Using a Lived Experience Participatory Design Approach %A Gan,Daniel Z Q %A McGillivray,Lauren %A Larsen,Mark Erik %A Bloomfield,Taylor %A Torok,Michelle %+ Black Dog Institute, University of New South Wales, Hospital Road, Sydney, NSW 2031, Australia, 61 423828945, danielzqgan@gmail.com %K eHealth %K digital mental health %K smartphone app %K engagement %K youth suicide prevention %K qualitative methods %K suicide %K development %K youth %K mental health %K support %K user-centered %K design %K survey %K interview %K prototype %K prevention %K participatory design %K mobile phone %D 2023 %7 6.6.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Suicide among young people is a worrying public health concern. Despite this, there is a lack of suitable interventions aligned with the needs of this priority population. Emerging evidence supports the effectiveness of digital interventions in alleviating the severity of suicidal thoughts. However, their efficacy may be undermined by poor engagement. Technology-supported strategies (eg, electronic prompts and reminders) have been deployed alongside digital interventions to increase engagement with the latter. However, evidence of their efficacy is inconclusive. User-centered design approaches may be key to developing feasible and effective engagement strategies. Currently, no study has been published on how such an approach might be expressly applied toward developing strategies for promoting engagement with digital interventions. Objective: This study aimed to detail the processes and activities involved in developing an adjunctive strategy for promoting engagement with LifeBuoy—a smartphone app that helps young people manage suicidal thoughts. Methods: Development of the engagement strategy took place in 2 phases. The discovery phase aimed to create an initial prototype by synthesizing earlier findings—from 2 systematic reviews and a cross-sectional survey of the broader mental health app user population—with qualitative insights from LifeBuoy users. A total of 16 web-based interviews were conducted with young people who participated in the LifeBuoy trial. Following the discovery phase, 3 interviewees were invited by the research team to take part in the workshops in the design phase, which sought to create a final prototype by making iterative improvements to the initial prototype. These improvements were conducted over 2 workshops. Thematic analysis was used to analyze the qualitative data obtained from the interviews and workshops. Results: Main themes from the interviews centered around the characteristics of the strategy, timing of notifications, and suitability of social media platforms. Subsequently, themes that emerged from the design workshops emphasized having a wider variety of content, greater visual consistency with LifeBuoy, and a component with more detailed information to cater to users with greater informational needs. Thus, refinements to the prototype were focused on (1) improving the succinctness, variety, and practical value of Instagram content, (2) creating a blog containing articles contributed by mental health professionals and young people with lived experience of suicide, and (3) standardizing the use of marine-themed color palettes across the Instagram and blog components. Conclusions: This is the first study to describe the development of a technology-supported adjunctive strategy for promoting engagement with a digital intervention. It was developed by integrating perspectives from end users with lived experience of suicide with evidence from the existing literature. The development process documented in this study may be useful for guiding similar projects aimed at supporting the use of digital interventions for suicide prevention or mental health. %M 37279058 %R 10.2196/45234 %U https://formative.jmir.org/2023/1/e45234 %U https://doi.org/10.2196/45234 %U http://www.ncbi.nlm.nih.gov/pubmed/37279058 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e47575 %T Supporting Adolescents With HIV in South Africa Through an Adherence-Supporting App: Mixed Methods Beta-Testing Study %A Mulawa,Marta I %A Mtukushe,Bulelwa %A Knippler,Elizabeth T %A Matiwane,Mluleki %A Al-Mujtaba,Maryam %A Muessig,Kathryn E %A Hoare,Jacqueline %A Hightow-Weidman,Lisa B %+ School of Nursing, Duke University, DUMC 3322, Durham, NC, 27710, United States, 1 919 684 9555, marta.mulawa@duke.edu %K adolescents %K HIV %K adherence %K mHealth %K mobile health %K technology %K smartphone app %K health app %K beta testing %K implementation %K digital health intervention %K usability %K HIV treatment %D 2023 %7 1.6.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Novel smartphone app–delivered interventions have the potential to improve HIV treatment adherence among adolescents with HIV, although such interventions are limited. Our team has developed Masakhane Siphucule Impilo Yethu (MASI; Xhosa for “Let's empower each other and improve our health”), a smartphone app–delivered intervention to improve treatment adherence among adolescents with HIV in South Africa. MASI was adapted to the South African cultural context using the HealthMpowerment platform, an evidence-based digital health intervention developed for and with youth in the United States. Objective: We conducted this beta-testing study to (1) explore the initial usability of MASI, (2) examine engagement and experiences using MASI features, and (3) inform refinements to the app and intervention implementation plan prior to a subsequent pilot randomized controlled trial (RCT). Methods: This study was conducted from August 2021 to December 2021 in Cape Town, South Africa. Beta-testing participants received access to MASI for 3 weeks. A mixed methods approach was used, with brief questionnaires and semistructured in-depth interviews conducted prior to app installation and after 1 week to 2 weeks of app testing. Engagement with MASI was measured through analysis of back-end app paradata, and follow-up in-depth interview guides were tailored to each participant based on their app use. Results: Participants in the beta-testing study (6 male participants, 6 female participants; ages 16-19 years) collectively spent 4.3 hours in MASI, averaging 21.4 minutes per participant over the 3-week period (range 1-51.8 minutes). Participants logged into MASI an average of 24.1 (range 10-75) times during the study period. The mean System Usability Scale score was 69.5 (SD 18), which is considered slightly above average for digital health apps. Thematic analysis of qualitative results revealed generally positive experiences across MASI features, although opportunities to refine the app and intervention delivery were identified. Conclusions: Initial usability of MASI was high, and participants described having a generally positive experience across MASI features. Systematically analyzing paradata and using the interview findings to explore participant experiences allowed us to gain richer insights into patterns of participant engagement, enabling our team to further enhance MASI. The results from this study led to a few technological refinements to improve the user experience. Enhancements were also made to the intervention implementation plan in preparation for a pilot RCT. Lessons learned from the conduct of this beta-testing study may inform the development, implementation, and evaluation of similar app-delivered interventions in the future. %M 37261883 %R 10.2196/47575 %U https://formative.jmir.org/2023/1/e47575 %U https://doi.org/10.2196/47575 %U http://www.ncbi.nlm.nih.gov/pubmed/37261883 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 10 %N %P e41256 %T Implementation of a Digital Health Tool for Patients Awaiting Input From a Specialist Weight Management Team: Observational Study %A Hanson,Petra %A Summers,Charlotte %A Panesar,Arjun %A Liarakos,Alexandros Leonidas %A Oduro-Donkor,Dominic %A Whyte Oshodi,Danniella %A Hailston,Luke %A Randeva,Harpal %A Menon,Vinod %A de la Fosse,Michaela %A Kaura,Amit %A Shuttlewood,Emma %A Loveder,Mark %A Poole,Donna %A Barber,Thomas M %+ National Heart & Lung Institute, Imperial College London, 9th Floor, Building E - Sir Michael Uren, White City Campus, London, W12 7ED, United Kingdom, 44 (0)20 7594 5735, a.kaura@imperial.ac.uk %K weight management %K precision health %K digital health, hospital %K secondary care %K tier 3 weight management %K National Health Service %K weight %K obese %K obesity %K focus group %K perspective %K opinion %K attitude %K behavior change %K behavior change %K mHealth %K mobile health %K health app %D 2023 %7 31.5.2023 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Digital tools are increasingly used on a population level as a weight loss strategy for people living with overweight and obesity. Evidence supports the feasibility of digital tools for the management of obesity in a community setting, but there is only emerging evidence for the feasibility of such tools in specialist weight management services. No study has assessed the uptake of digital tools among patients awaiting their first appointment with a specialist weight management service. Objective: The objective of this study was to understand interest, acceptance, and engagement with a digital behavioral change platform to support specialist weight management. Methods: This was an observational study registered as a service innovation. All patients on the waiting list for a first appointment in the tier 3 weight management service at University Hospitals Coventry and Warwickshire National Health Service (NHS) Trust were eligible to access the NHS-approved digital tool. Data on interest and engagement with the digital tool were collected. Routine clinical data were used to describe patient demographics. Focus groups were held to explore patients’ views on the use of digital tools as part of a specialist weight management service. Results: A total of 199 patients on the waiting list were informed about the available digital tool. Just over a half (n=102, 51.3%) of patients were interested in using the app, with over one-third (n=68, 34%) of all patients engaging with the app. Overall, a third of patients on the waiting list (n=63, 32%) did not respond to the invite and 34 (17%) of patients expressed no interest in the app. Emotional eating and higher BMI was associated with interest in the Gro Health app. Male gender was associated with reduced engagement with the app. There were no differences in interest in the Gro Health app according to age, ethnicity, metabolic measures of glycemia, and lipid profile. Conclusions: It is feasible to offer digital tools such as Gro Health to patients awaiting their first appointment with specialist weight management services. Future research should explore barriers and facilitators of engagement with digital tools. Additionally, there is a need to further evaluate the effectiveness of such tools in specialist weight management services. %M 37256653 %R 10.2196/41256 %U https://humanfactors.jmir.org/2023/1/e41256 %U https://doi.org/10.2196/41256 %U http://www.ncbi.nlm.nih.gov/pubmed/37256653 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e44685 %T Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review %A Leong,Utek %A Chakraborty,Bibhas %+ Centre for Quantitative Medicine and Program in Health Services and Systems Research, Duke-NUS Medical School, National University of Singapore, 8 College Road, #06-31, Singapore, 169857, Singapore, 65 66016502, bibhas.chakraborty@duke-nus.edu.sg %K microrandomized trials %K engagement %K adherence %K mobile health %K mHealth interventions %K mobile phone %D 2023 %7 22.5.2023 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Microrandomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multicomponent, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions. Objective: In this scoping review, we aimed to quantify the proportion of existing or planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. In addition, for the trials that have explicitly assessed (or have planned to assess) engagement, we aimed to investigate how engagement has been operationalized and to identify the factors that have been studied as determinants of engagement in MRTs of mHealth interventions. Methods: We conducted a broad search for MRTs of mHealth interventions in 5 databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized these data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs. Results: Our database and manual search yielded 22 eligible evidence sources. Most of these studies (14/22, 64%) were designed to evaluate the effects of intervention components. The median sample size of the included MRTs was 110.5. At least 1 explicit measure of engagement was included in 91% (20/22) of the included MRTs. We found that objective measures such as system usage data (16/20, 80%) and sensor data (7/20, 35%) are the most common methods of measuring engagement. All studies included at least 1 measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by 1 study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 (30%) of the 20 studies that measured engagement assessed the determinants of engagement in MRTs of mHealth interventions; notification-related variables were the most common determinants of engagement assessed (4/6, 67% studies). Of the 6 studies, 3 (50%) examined the moderators of participant engagement—2 studies investigated time-related moderators exclusively, and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators. Conclusions: Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials. %M 37213178 %R 10.2196/44685 %U https://mhealth.jmir.org/2023/1/e44685 %U https://doi.org/10.2196/44685 %U http://www.ncbi.nlm.nih.gov/pubmed/37213178 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e43033 %T The Effect of Periodic Email Prompts on Participant Engagement With a Behavior Change mHealth App: Longitudinal Study %A Agachi,Elena %A Bijmolt,Tammo H A %A van Ittersum,Koert %A Mierau,Jochen O %+ Department of Marketing, Faculty of Economics and Business, University of Groningen, Nettelbosje 2, Groningen, 9747 AE, Netherlands, 31 50 363 3686, e.agachi@rug.nl %K mobile health %K behavior change %K mobile app %K digital health %K engagement %K retention %K email %K hidden Markov model %D 2023 %7 11.5.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Following the need for the prevention of noncommunicable diseases, mobile health (mHealth) apps are increasingly used for promoting lifestyle behavior changes. Although mHealth apps have the potential to reach all population segments, providing accessible and personalized services, their effectiveness is often limited by low participant engagement and high attrition rates. Objective: This study concerns a large-scale, open-access mHealth app, based in the Netherlands, focused on improving the lifestyle behaviors of its participants. The study examines whether periodic email prompts increased participant engagement with the mHealth app and how this effect evolved over time. Points gained from the activities in the app were used as an objective measure of participant engagement with the program. The activities considered were physical workouts tracked through the mHealth app and interactions with the web-based coach. Methods: The data analyzed covered 22,797 unique participants over a period of 78 weeks. A hidden Markov model (HMM) was used for disentangling the overtime effects of periodic email prompts on participant engagement with the mHealth app. The HMM accounted for transitions between latent activity states, which generated the observed measure of points received in a week. Results: The HMM indicated that, on average, 70% (15,958/22,797) of the participants were in the inactivity state, gaining 0 points in total per week; 18% (4103/22,797) of the participants were in the average activity state, gaining 27 points per week; and 12% (2736/22,797) of the participants were in the high activity state, gaining 182 points per week. Receiving and opening a generic email was associated with a 3 percentage point increase in the likelihood of becoming active in that week, compared with the weeks when no email was received. Examining detailed email categories revealed that the participants were more likely to increase their activity level following emails that were in line with the program’s goal, such as emails regarding health campaigns, while being resistant to emails that deviated from the program’s goal, such as emails regarding special deals. Conclusions: Participant engagement with a behavior change mHealth app can be positively influenced by email prompts, albeit to a limited extent. Given the relatively low costs associated with emails and the high population reach that mHealth apps can achieve, such instruments can be a cost-effective means of increasing participant engagement in the stride toward improving program effectiveness. %M 37166974 %R 10.2196/43033 %U https://mhealth.jmir.org/2023/1/e43033 %U https://doi.org/10.2196/43033 %U http://www.ncbi.nlm.nih.gov/pubmed/37166974 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e36837 %T An App-Based Intervention for Pediatric Weight Management: Pre-Post Acceptability and Feasibility Trial %A Cox,Jennifer S %A Hinton,Elanor C %A Hamilton Shield,Julian %A Lawrence,Natalia S %+ NIHR Bristol Biomedical Research Centre Nutrition Theme, 3rd Floor, Education & Research Centre, Upper Maudlin Street, Bristol, BS2 8AE, United Kingdom, 44 07718905807, jennifer.cox@bristol.ac.uk %K obesity %K pediatric %K intervention %K eHealth %K weight management %D 2023 %7 24.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: A multidisciplinary approach to weight management is offered at tier 3 pediatric weight management services in the United Kingdom. Encouraging dietary change is a major aim, with patients meeting with dieticians, endocrinologists, psychologists, nurse specialists, and social workers on average every other month. Objective: This research sought to trial an inhibitory control training smartphone app—FoodT—with the clinic population of a pediatric weight management service. FoodT has shown positive impacts on food choice in adult users, with resulting weight loss. It was hoped that when delivered as an adjunctive treatment alongside the extensive social, medical, psychological, and dietetic interventions already offered at the clinic, the introduction of inhibitory control training may offer patients another tool that supports eating choice. In this feasibility trial, recruitment, retention, and app use were the primary outcomes. An extensive battery of measures was included to test the feasibility and acceptability of these measures for future powered trials. Methods: FoodT was offered to pediatric patients and their parents during a routine clinic appointment, and patients were asked to use the app at home every day for the first week and once per week for the rest of the month. Feasibility and acceptability were measured in terms of recruitment, engagement with the app, and retention to the trial. A battery of psychometric tests was given before and after app use to assess the acceptability of collecting data on changes to food choices and experiences that would inform future trial work. Results: A total of 12 children and 10 parents consented (22/62, 35% of those approached). Further, 1 child and no parents achieved the recommended training schedule. No participants completed the posttrial measures. The reasons for not wanting to be recruited to the trial included participants not considering their weight to be connected to eating choices and not feeling that the app suited their needs. No reasons are known for noncompletion. Conclusions: It is unclear whether the intervention itself or the research processes, including the battery of measures, prevented completion. It is therefore difficult to make any decisions as to the value that the app has within this setting. Important lessons have been learned from this research that have potential broad relevance, including the importance of co-designing interventions with service users and avoiding deterring people from early-stage participation in extensive data collection. %M 37093633 %R 10.2196/36837 %U https://formative.jmir.org/2023/1/e36837 %U https://doi.org/10.2196/36837 %U http://www.ncbi.nlm.nih.gov/pubmed/37093633 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 10 %N %P e43164 %T Mobile Acceptance and Commitment Therapy in Bipolar Disorder: Microrandomized Trial %A Cochran,Amy %A Maronge,Jacob M %A Victory,Amanda %A Hoel,Sydney %A McInnis,Melvin G %A Thomas,Emily BK %+ Department of Population Health Sciences, University of Wisconsin Madison, 610 Walnut Street, Madison, WI, 53726, United States, 1 608 262 0772, cochran4@wisc.edu %K acceptance and commitment therapy %K bipolar disorder %K mobile applications %K randomized controlled trials %K micro-randomized trial %K precision medicine %K mindfulness %D 2023 %7 20.4.2023 %9 Original Paper %J JMIR Ment Health %G English %X Background: Mobile interventions promise to fill in gaps in care with their broad reach and flexible delivery. Objective: Our goal was to investigate delivery of a mobile version of acceptance and commitment therapy (ACT) for individuals with bipolar disorder (BP). Methods: Individuals with BP (n=30) participated in a 6-week microrandomized trial. Twice daily, participants logged symptoms in the app and were repeatedly randomized (or not) to receive an ACT intervention. Self-reported behavior and mood were measured as the energy devoted to moving toward valued domains or away from difficult emotions and with depressive d and manic m scores from the digital survey of mood in BP survey (digiBP). Results: Participants completed an average of 66% of in-app assessments. Interventions did not significantly impact the average toward energy or away energy but did significantly increase the average manic score m (P=.008) and depressive score d (P=.02). This was driven by increased fidgeting and irritability and interventions focused on increasing awareness of internal experiences. Conclusions: The findings of the study do not support a larger study on the mobile ACT in BP but have significant implications for future studies seeking mobile therapy for individuals with BP. Trial Registration: ClinicalTrials.gov NCT04098497; https://clinicaltrials.gov/ct2/show/NCT04098497 %M 37079363 %R 10.2196/43164 %U https://mental.jmir.org/2023/1/e43164 %U https://doi.org/10.2196/43164 %U http://www.ncbi.nlm.nih.gov/pubmed/37079363 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45305 %T The Impact of Family Therapy Participation on Youths and Young Adult Engagement and Retention in a Telehealth Intensive Outpatient Program: Quality Improvement Analysis %A Berry,Katie R %A Gliske,Kate %A Schmidt,Clare %A Ballard,Jaime %A Killian,Michael %A Fenkel,Caroline %+ Charlie Health, Inc, 233 E Main St Suite 401, Bozeman, MT, 59715, United States, 1 9545527671, krberry@fsu.edu %K adolescents %K family therapy %K intensive outpatient %K mental health %K treatment engagement %K young adults %D 2023 %7 20.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background:  Early treatment dropout among youths and young adults (28%-75%) puts them at risk for poorer outcomes. Family engagement in treatment is linked to lower dropout and better attendance in outpatient, in-person treatment. However, this has not been studied in intensive or telehealth settings. Objective:  We aimed to examine whether family members’ participation in telehealth intensive outpatient (IOP) therapy for mental health disorders in youths and young adults is associated with patient’s treatment engagement. A secondary aim was to assess demographic factors associated with family engagement in treatment. Methods:  Data were collected from intake surveys, discharge outcome surveys, and administrative data for patients who attended a remote IOP for youths and young adults, nationwide. Data included 1487 patients who completed both intake and discharge surveys and either completed or disengaged from treatment between December 2020 and September 2022. Descriptive statistics were used to characterize the sample’s baseline differences in demographics, engagement, and participation in family therapy. Mann-Whitney U and chi-square tests were used to explore differences in engagement and treatment completion between patients with and those without family therapy. Binomial regression was used to explore significant demographic predictors of family therapy participation and treatment completion. Results:  Patients with family therapy had significantly better engagement and treatment completion outcomes than clients with no family therapy. Youths and young adults with ≥1 family therapy session were significantly more likely to stay in treatment an average of 2 weeks longer (median 11 weeks vs 9 weeks) and to attend a higher percentage of IOP sessions (median 84.38% vs 75.00%). Patients with family therapy were more likely to complete treatment than clients with no family therapy (608/731, 83.2% vs 445/752, 59.2%; P<.001). Different demographic variables were associated with an increased likelihood of participating in family therapy, including younger age (odds ratio 1.3) and identifying as heterosexual (odds ratio 1.4). After controlling for demographic factors, family therapy remained a significant predictor of treatment completion, such that each family therapy session attended was associated with a 1.4-fold increase in the odds of completing treatment (95% CI 1.3-1.4). Conclusions:  Youths and young adults whose families participate in any family therapy have lower dropout, greater length of stay, and higher treatment completion than those whose families do not participate in services in a remote IOP program. The findings of this quality improvement analysis are the first to establish a relationship between participation in family therapy and an increased engagement and retention in remote treatment for youths and young patients in IOP programing. Given the established importance of obtaining an adequate dosage of treatment, bolstering family therapy offerings is another tool that could contribute to the provision of care that better meets the needs of youths, young adults, and their families. %M 37079372 %R 10.2196/45305 %U https://formative.jmir.org/2023/1/e45305 %U https://doi.org/10.2196/45305 %U http://www.ncbi.nlm.nih.gov/pubmed/37079372 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e41275 %T The Relationship Between How Participants Articulate Their Goals and Accomplishments and Weight Loss Outcomes: Secondary Analysis of a Pilot of a Web-Based Weight Loss Intervention %A Jake-Schoffman,Danielle E %A Waring,Molly E %A DiVito,Joseph %A Goetz,Jared M %A Pan,Cindy %A Pagoto,Sherry L %+ Department of Health Education and Behavior, College of Health and Human Performance, University of Florida, PO Box 118210, Gainesville, FL, 32611, United States, 1 352 294 1046, djakeschoffman@ufl.edu %K weight loss %K social media %K goal setting %K web-based program %K behavior change %K habit formation %K diabetes %K Facebook %K lifestyle %D 2023 %7 16.3.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In behavioral weight loss interventions, participants are asked to set weekly goals to support long-term habits that lead to weight loss. Although participants are asked to set and accomplish weekly goals, we do not know how often they do this and whether doing so is associated with weight loss. Web-based weight loss interventions allow for the analysis of participant engagement data, including how participants articulate their goals and accomplishments. Objective: Using engagement data from a web-based weight loss intervention, we examined whether participants articulating their goals and accomplishments in measurable and repeating terms were associated with greater weight loss. Methods: Adults with overweight or obesity received a 12-week Facebook-delivered weight loss intervention based on the Diabetes Prevention Program Lifestyle Intervention. Participants replied to conversation threads that queried about their goals and accomplishments. Two independent coders classified participants’ posts that articulated goals or accomplishments as measurable or repeating. Crude and age-adjusted linear regression models were used to examine the relationship between the frequency of post type and percent weight loss. Results: Participants (N=53; n=48, 91% female; n=48, 91% non-Hispanic White) were on average 46.2 (SD 10.5) years old with a mean BMI of 32.4 (SD 4.8) kg/m2. Over 12 weeks, participants shared a median of 4 (IQR 1-8) posts that reported goals and 10 (IQR 4-24) posts that reported accomplishments. Most participants shared ≥1 post with a goal (n=43, 81%) and ≥1 post with an accomplishment (n=47, 89%). Each post reporting a goal was associated with 0.2% greater weight loss (95% CI −0.3% to 0.0%). Sharing ≥1 post with a repeating goal was associated with an average of 2.2% greater weight loss (95% CI −3.9% to −0.4%). Each post with a repeating goal was associated with an average of 0.5% greater weight loss (95% CI −1.0% to 0.0%). Sharing ≥1 post with measurable and repeating goals was associated with an average of 1.9% greater weight loss (95% CI −3.7% to −0.2%). Sharing each post with an accomplishment was associated with an average of 0.1% greater weight loss (95% CI −0.1% to 0.0%). Every post with an accomplishment that was repeating was associated with an average of 0.2% greater weight loss (95% CI −0.3% to 0.0%). Sharing other types of goals and accomplishments was not associated with weight loss. Conclusions: In a web-based weight loss intervention, stating goals in repeating or both measurable and repeating terms was associated with greater weight loss, but simply stating them in measurable terms was not. For accomplishments, only those articulated in repeating terms were associated with greater weight loss. Posts about one-time goals and accomplishments represent an opportunity to encourage planning for future behaviors. Future research should examine if stating goals and accomplishments in repeating terms signals habit formation. %M 36927569 %R 10.2196/41275 %U https://mhealth.jmir.org/2023/1/e41275 %U https://doi.org/10.2196/41275 %U http://www.ncbi.nlm.nih.gov/pubmed/36927569 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 6 %N %P e42399 %T Mediating Role of Treatment Perceptions in the Relationship Between Individual Characteristics and Engagement With a Digital Psychological Intervention for Pediatric Chronic Pain: Secondary Data Analysis %A de la Vega,Rocio %A Palermo,Tonya M %+ Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, M/S CURE-3, PO Box 5371, Seattle, WA, 98145-5005, United States, 1 206 884 4208, tonya.palermo@seattlechildrens.org %K treatment adherence %K treatment perceptions %K mediators %K pediatric pain %K psychological intervention %K digital health %K treatment %K intervention %K engagement %K self-management %K psychological %D 2023 %7 6.3.2023 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: Engagement predicts benefits from self-managed treatments. However, engagement is an important concern in digital interventions, with over 50% of patients being nonadherent to interventions in chronic conditions such as chronic pain. Little is known about the individual characteristics that contribute to engagement with a digital self-management treatment. Objective: This study tested the mediating role of treatment perceptions (difficulty and helpfulness) in the association between individual baseline characteristics (treatment expectancies and readiness to change) and treatment engagement (online and offline) with a digital psychological intervention for adolescents with chronic pain. Methods: A secondary data analysis of a single-arm trial of Web-based Management of Adolescent Pain, a self-guided internet intervention developed for the management of chronic pain in adolescents, was conducted. Survey data were collected at baseline (T1), midtreatment (ie, 4 weeks after the treatment started; T2), and post treatment (T3). Online engagement was assessed using back-end information on the number of days adolescents accessed the treatment website, while the offline engagement was assessed with the reported frequency of use of skills (ie, pain management strategies) learned at the end of the treatment. Four parallel multiple mediator linear regression models, using ordinary least square regression incorporating the variables were tested. Results: In total, 85 adolescents with chronic pain (12-17 years old, 77% female) participated. Several mediation models were significant in predicting online engagement. A significant indirect effect was found for the path expectancies–helpfulness–online engagement (effect 0.125; SE 0.098; 95% CI 0.013-0.389) and for the path precontemplation–helpfulness–online engagement (effect −1.027; SE 0.650; 95% CI −2.518 to −0.054). Fourteen percent of the variance of online engagement was explained by the model including expectancies as a predictor (F3=3.521; P<.05), whereas 15% was explained by the model where readiness to change was the predictor (F3=3.934; P<.05). Offline engagement was partially explained in the model including readiness to change as the predictor but with marginal significance (F3=2.719; R2=0.111; P=.05). Conclusions: Treatment perception, specifically, perceived helpfulness, was a mediator of the pathway between both treatment expectancies and readiness to change and online engagement with a digital psychological intervention for chronic pain. Assessing these variables at baseline and midtreatment may help to determine the risk of nonadherence. Further work is needed to confirm these mediation pathways in larger samples. Trial Registration: ClinicalTrials.gov NCT04043962; https://clinicaltrials.gov/ct2/show/NCT04043962 %M 36877543 %R 10.2196/42399 %U https://pediatrics.jmir.org/2023/1/e42399 %U https://doi.org/10.2196/42399 %U http://www.ncbi.nlm.nih.gov/pubmed/36877543 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e40961 %T Influences on Patient Uptake of and Engagement With the National Health Service Digital Diabetes Prevention Programme: Qualitative Interview Study %A Ross,Jamie %A Cotterill,Sarah %A Bower,Peter %A Murray,Elizabeth %+ Centre for Primary Care, Wolfson Institute of Population Health Science, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB, United Kingdom, 44 20 8016 80, Jamie.ross@qmul.ac.uk %K diabetes prevention %K digital health interventions %K engagement %K qualitative research %K mobile phone %D 2023 %7 28.2.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital diabetes prevention programs (digital-DPPs) are being implemented as population-based approaches to type 2 diabetes mellitus prevention in several countries to address problems with the uptake of traditional face-to-face diabetes prevention programs. However, assessments of digital-DPPs have largely focused on clinical outcomes and usability among those who have taken them up, whereas crucial information on decision-making about uptake (eg, whether a user downloads and registers on an app) and engagement (eg, the extent of use of an app or its components over time) is limited. Greater understanding of factors that influence uptake and engagement decisions may support large-scale deployments of digital-DPPs in real-world settings. Objective: This study aimed to explore the key influences on uptake and engagement decisions of individuals who were offered the National Health Service Healthier You: Digital Diabetes Prevention Programme (NHS-digital-DPP). Methods: A qualitative interview study was conducted using semistructured interviews. Participants were adults, aged ≥18 years, diagnosed with nondiabetic hyperglycemia, and those who had been offered the NHS-digital-DPP. Recruitment was conducted via 4 providers of the NHS-digital-DPP and 3 primary care practices in England. Interviews were conducted remotely and were guided by a theoretically informed topic guide. Analysis of interviews was conducted using an inductive thematic analysis approach. Results: Interviews were conducted with 32 participants who had either accepted or declined the NHS-digital-DPP. In total, 7 overarching themes were identified as important factors in both decisions to take up and to engage with the NHS-digital-DPP. These were knowledge and understanding, referral process, self-efficacy, self-identity, motivation and support, advantages of digital service, and reflexive monitoring. Perceptions of accessibility and convenience of the NHS-digital-DPP were particularly important for uptake, and barriers in terms of the referral process and health care professionals’ engagement were reported. Specific digital features including health coaches and monitoring tools were important for engagement. Conclusions: This study adds to the literature on factors that influence the uptake of and engagement with digital-DPPs and suggests that digital-DPPs can overcome many barriers to the uptake of face-to-face diabetes prevention programs in supporting lifestyle changes aimed at diabetes prevention. %M 36853751 %R 10.2196/40961 %U https://www.jmir.org/2023/1/e40961 %U https://doi.org/10.2196/40961 %U http://www.ncbi.nlm.nih.gov/pubmed/36853751 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e40207 %T Perceptions of Using Instant Messaging Apps for Alcohol Reduction Intervention Among University Student Drinkers: Semistructured Interview Study With Chinese University Students in Hong Kong %A Chau,Siu Long %A Wong,Yiu Cheong %A Zeng,Ying Pei %A Lee,Jung Jae %A Wang,Man Ping %+ School of Nursing, The University of Hong Kong, 5/F, Academic Building, 3 Sassoon Road, Pokfulam, Hong Kong, Hong Kong, 852 3917 6636, mpwang@hku.hk %K instant messaging apps %K mobile phone %K WhatsApp %K alcohol reduction intervention %K alcohol use %K university students %K young adults %K instant messaging %K alcohol reduction %K adverse lifestyle %K intervention %K health promotion %K text messages %K health behaviours %K health behaviors %K apps %D 2023 %7 27.2.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Mobile instant messaging (IM) apps (eg, WhatsApp and WeChat) have been widely used by the general population and are more interactive than text-based programs (SMS text messaging) to modify unhealthy lifestyles. Little is known about IM app use for health promotion, including alcohol reduction for university students. Objective: This study aims to explore university student drinkers' perceptions of using IM apps for alcohol reduction as they had high alcohol exposure (eg, drinking invitations from peers and alcohol promotion on campus) and the proportion of IM app use in Hong Kong. Methods: A qualitative study was conducted with 20 Hong Kong Chinese university students (current drinkers) with Alcohol Use Disorder Identification test scores of ≥8 recruited using purposive sampling. Semistructured individual interviews were conducted from September to October 2019. Interview questions focused on drinking behaviors, quitting history, opinions toward IM app use as an intervention tool, perceived usefulness of IM apps for alcohol reduction, and opinions on the content and design of IM apps for alcohol reduction. Each interview lasted approximately 1 hour. All interviews were audio-taped and transcribed verbatim. Two researchers independently analyzed the transcripts using thematic analysis with an additional investigator to verify the consistency of the coding. Results: Participants considered IM apps a feasible and acceptable platform for alcohol reduction intervention. They preferred to receive IMs based on personalized problem-solving and drinking consequences with credible sources. Other perceived important components of instant messages included providing psychosocial support in time and setting goals with participants to reduce drinking. They further provided suggestions on the designs of IM interventions, in which they preferred simple and concise messages, chat styles based on participants' preferences (eg, adding personalized emojis and stickers in the chat), and peers as counselors. Conclusions: Qualitative interviews with Chinese university student drinkers showed high acceptability, engagement, and perceived utility of IM apps for alcohol reduction intervention. IM intervention can be an alternative for alcohol reduction intervention apart from traditional text-based programs. The study has implications for developing the IM intervention for other unhealthy behaviors and highlights important topics that warrant future research, including substance use and physical inactivity. Trial Registration: ClinicalTrials.gov NCT04025151; https://clinicaltrials.gov/ct2/show/NCT04025151?term=NCT04025151 %M 36848207 %R 10.2196/40207 %U https://formative.jmir.org/2023/1/e40207 %U https://doi.org/10.2196/40207 %U http://www.ncbi.nlm.nih.gov/pubmed/36848207 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e39258 %T Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model %A Currey,Danielle %A Torous,John %+ Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Ave, Boston, MA, 02446, United States, 1 6176676700, jtorous@gmail.com %K mHealth %K mental health %K smartphones %K phenotype %K symptom %K college %K students %K young adults %K responsive %K personalized %K app %K application %K intervention %K effectiveness %K protocol %K model %K digital %K engagement %K algorithm %K usage %D 2023 %7 9.2.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Mental health apps offer a transformative means to increase access to scalable evidence-based care for college students. Yet low rates of engagement currently preclude the effectiveness of these apps. One promising solution is to make these apps more responsive and personalized through digital phenotyping methods able to predict symptoms and offer tailored interventions. Objective: Following our protocol and using the exact model shared in that paper, our primary aim in this study is to assess the prospective validity of mental health symptom prediction using the mindLAMP app through a replication study. We also explored secondary aims around app intervention personalization and correlations of engagement with the Technology Acceptance Model (TAM) and Digital Working Alliance Inventory scale in the context of automating the study. Methods: The study was 28 days in duration and followed the published protocol, with participants collecting digital phenotyping data and being offered optional scheduled and algorithm-recommended app interventions. Study compensation was tied to the completion of weekly surveys and was not otherwise tied to engagement or use of the app. Results: The data from 67 participants were used in this analysis. The area under the curve values for the symptom prediction model ranged from 0.58 for the UCLA Loneliness Scale to 0.71 for the Patient Health Questionnaire-9. Engagement with the scheduled app interventions was high, with a study mean of 73%, but few participants engaged with the optional recommended interventions. The perceived utility of the app in the TAM was higher (P=.01) among those completing at least one recommended intervention. Conclusions: Our results suggest how digital phenotyping methods can be used to create generalizable models that may help create more personalized and engaging mental health apps. Automating studies is feasible, and our results suggest targets to increase engagement in future studies. International Registered Report Identifier (IRRID): RR2-10.2196/37954 %M 36757759 %R 10.2196/39258 %U https://www.jmir.org/2023/1/e39258 %U https://doi.org/10.2196/39258 %U http://www.ncbi.nlm.nih.gov/pubmed/36757759 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e44059 %T Direct and Indirect Predictors of Medication Adherence With Bipolar Disorder: Path Analysis %A Cohen,Bar %A Sixsmith,Andrew %A Pollock Star,Ariel %A Haglili,Ophir %A O'Rourke,Norm %+ Department of Epidemiology, Biostatistics and Community Health Sciences, Ben-Gurion University of the Negev, Building M6, Room #308, P.O. Box 653, Be'er Sheva, 8421637, Israel, 972 8 6477301, ORourke@bgu.ac.il %K alcohol misuse %K bipolar disorder %K cognitive loss %K depression %K hypo/mania %K mania %K medication adherence %K mental health %K path analysis %K perceived cognitive failures %K polypharmacy %K psychiatric disorder %K psychosocial %D 2023 %7 7.2.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Despite the efficacy of treatment and severity of symptoms, medication adherence by many with bipolar disorder (BD) is variable at best. This poses a significant challenge for BD care management. Objective: For this study, we set out to identify psychosocial and psychiatric predictors of medication adherence with BD. Methods: Using microtargeted social media advertising, we recruited an international sample of young and older adults with BD living in North America (Canada and the United States), Western Europe (eg, United Kingdom and Ireland), Australia and New Zealand (N=92). On average, participants were 55.35 (SD 9.65; range 22-73) years of age, had been diagnosed with BD 14.25 (SD 11.14; range 1-46) years ago, and were currently prescribed 2.40 (SD 1.28; range 0-6) psychotropic medications. Participants completed questionnaires online including the Morisky Medication Adherence Scale. Results: Medication adherence did not significantly differ across BD subtypes, country of residence, or prescription of lithium versus other mood stabilizers (eg, anticonvulsants). Path analyses indicate that alcohol misuse and subjective or perceived cognitive failures are direct predictors of medication adherence. BD symptoms, psychological well-being, and the number of comorbid psychiatric conditions emerged as indirect predictors of medication adherence via perceived cognitive failures. Conclusions: Alcohol misuse did not predict perceived cognitive failures. Nor did age predict medication adherence or cognitive failures. This is noteworthy given the 51-year age range of participants. That is, persons in their 20s with BD reported similar levels of medication adherence and perceived cognitive failures as those in their 60s. This suggests that perceived cognitive loss is a facet of adult life with BD, in contrast to the assumption that accelerated cognitive aging with BD begins in midlife. %M 36749623 %R 10.2196/44059 %U https://formative.jmir.org/2023/1/e44059 %U https://doi.org/10.2196/44059 %U http://www.ncbi.nlm.nih.gov/pubmed/36749623 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 10 %N %P e42566 %T Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial %A Ditton,Elizabeth %A Knott,Brendon %A Hodyl,Nicolette %A Horton,Graeme %A Oldmeadow,Christopher %A Walker,Frederick Rohan %A Nilsson,Michael %+ Centre for Rehab Innovations, University of Newcastle, University Drive, Callaghan, 2308, Australia, 61 2 404 ext 20738, elizabeth.ditton@uon.edu.au %K burnout %K psychological %K burnout interventions %K well-being %K medicine %K medical student %K digital intervention %K app-delivered intervention %K individualized intervention %K randomized controlled trial %K RCT %K randomized %K Acceptance and Commitment Training %K stress %K mobile health %K mHealth %K mobile phone %D 2023 %7 6.2.2023 %9 Original Paper %J JMIR Ment Health %G English %X Background: Physician burnout is a common problem, with onset frequently occurring during undergraduate education. Early intervention strategies that train medical students in psychological flexibility skills could support well-being and mitigate burnout risks associated with unmodifiable career stressors. There is a need for randomized controlled trials to assess effectiveness. As psychological flexibility varies contextually and among individuals, tailoring interventions may improve outcomes. Smartphone apps can facilitate individualization and accessibility, and the evaluation of this approach is an identified research priority. Objective: This study aimed to evaluate the effectiveness of a stand-alone app–delivered Acceptance and Commitment Training intervention for improving medical students’ self-reported burnout, well-being, psychological flexibility, and psychological distress outcomes. We aimed to explore whether an individualized app would demonstrate benefits over a nonindividualized version. Methods: This parallel randomized controlled trial was conducted with a sample of medical students from 2 Australian universities (N=143). Participants were randomly allocated to 1 of 3 intervention arms (individualized, nonindividualized, and waitlist) using a 1:1:1 allocation ratio. Individualized and nonindividualized participants were blinded to group allocation. The 5-week intervention included an introductory module (stage 1) and on-demand access to short skill training activities (stage 2), which students accessed at their own pace. Stage 2 was either nonindividualized or individualized to meet students’ identified psychological flexibility training needs. Results: The mean differences in change from baseline between the intervention groups and the waitlist group were not statistically significant for burnout outcomes: exhaustion (primary; individualized: −0.52, 95% CI −3.70 to 2.65, P=.75; nonindividualized: 1.60, 95% CI −1.84 to 5.03, P=.37), cynicism (individualized: −1.26, 95% CI −4.46 to 1.94, P=.44; nonindividualized: 1.00, 95% CI −2.45 to 4.46, P=.57), and academic efficacy (individualized: 0.94, 95% CI −0.90 to 2.79, P=.32; nonindividualized: 2.02, 95% CI 0.02-4.03, P=.05). Following the intervention, the individualized group demonstrated improved psychological flexibility (0.50, 95% CI 0.12-0.89; P=.01), reduced inflexibility (0.48, 95% CI −0.92 to −0.04; P=.04), and reduced stress (−6.89, 95% CI −12.01 to 5.99; P=.01), and the nonindividualized group demonstrated improved well-being (6.46, 95% CI 0.49-12.42; P=.04) and stress (−6.36, 95% CI −11.90 to −0.83; P=.03) compared with waitlist participants. Between-group differences for the individualized and nonindividualized arms were not statistically significant. High attrition (75/143, 52.4%) was observed. Conclusions: This trial provides early support for the potential benefits of Acceptance and Commitment Training for medical student well-being and psychological outcomes and demonstrates that psychological flexibility and inflexibility can be trained using a smartphone app. Although postintervention burnout outcomes were not statistically significant, improvements in secondary outcomes could indicate early risk mitigation. Replication studies with larger samples and longer-term follow-up are required, and future research should focus on improving implementation frameworks to increase engagement and optimize individualization methods. Trial Registration: Australian New Zealand Clinical Trials Registry 12621000911897; https://tinyurl.com/2p92cwrw International Registered Report Identifier (IRRID): RR2-10.2196/32992 %M 36745486 %R 10.2196/42566 %U https://mental.jmir.org/2023/1/e42566 %U https://doi.org/10.2196/42566 %U http://www.ncbi.nlm.nih.gov/pubmed/36745486 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e40934 %T Engagement With and Acceptability of Digital Media Platforms for Use in Improving Health Behaviors Among Vulnerable Families: Systematic Review %A Eppes,Elisabet V %A Augustyn,Marycatherine %A Gross,Susan M %A Vernon,Paris %A Caulfield,Laura E %A Paige,David M %+ Department of Population, Family, and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD, 21205, United States, 1 484 467 3121, elisabet.eppes@gmail.com %K text messaging %K social media %K mobile app %K low-income %K engagement %K health promotion %K community %K nutrition and physical activity %K pregnancy %K breastfeeding %K maternal and child health %K mobile phone %D 2023 %7 3.2.2023 %9 Review %J J Med Internet Res %G English %X Background: The use of digital communication platforms to improve health behaviors has increased dramatically over the last decade. Public health practitioners have adopted digital communication technologies such as text messages, mobile apps, and social media to reach diverse populations. However, the effectiveness of digital communication platforms used by community-serving agencies remains unclear, and patterns of engagement and acceptability of different platforms have not been studied. Objective: This review aimed to identify the types of digital communication strategies used by community-serving organizations to promote healthy behaviors, assess the strength of evidence for health behavioral change, and describe the degree of consumer engagement with and acceptability of these strategies. The study population included low-income pregnant women, parents of young children, and adolescents. Methods: A systematic review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using PubMed, Scopus, Web of Science, CINAHL, and APA PsycInfo, covering research conducted from 2009 to 2022. Studies were included if they examined the use of digital communication (ie, texting, mobile apps, or social media) to promote healthy behaviors in the target population. Risk of bias and strength of evidence were assessed using the Effective Public Health Practice Project Risk of Bias tool and criteria from Agency for Healthcare Research and Quality, respectively. Results: Twenty-three peer-reviewed research studies published between 2012 and 2022, conducted in the United States, the United Kingdom, and Australia, were included in the review. The sample comprised studies exploring the use of texting (n=12), apps (n=6), social media (n=3), and multiple platforms (n=2; eg, texting and mobile apps). Targeted health behaviors included healthy diet, physical activity, obesity prevention, healthy pregnancy, breastfeeding, vaccine use, smoking cessation, and nutrition benefit redemption. The sample included 8 randomized controlled trials, 6 pretest-posttest design, 3 mixed methods studies, 2 pilot studies, 1 feasibility study, 1 prospective cohort study, 1 descriptive study, and 1 cross-sectional study. The median sample size was 77.5. There was no strong evidence to suggest the effectiveness of digital media campaigns in improving health behaviors; however, there were moderate to high levels of engagement and high levels of acceptability across digital platforms. Conclusions: Low-income pregnant women, parents of young children, and adolescents demonstrated moderate levels of engagement with and high levels of acceptability of digital media health campaigns conducted by community-serving agencies. The effectiveness of these strategies in improving health behaviors was inconclusive. Additional rigorous studies with larger sample sizes are required. In addition, more research is required to consistently measure and report participants’ engagement with each platform. Digital communication platforms are critical tools for public health practitioners, and future investigations of the effectiveness of these platforms in engaging clients and improving health behaviors will maximize client services. %M 36735286 %R 10.2196/40934 %U https://www.jmir.org/2023/1/e40934 %U https://doi.org/10.2196/40934 %U http://www.ncbi.nlm.nih.gov/pubmed/36735286 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e40865 %T The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination %A Auster-Gussman,Lisa A %A Rikhy,Mohit %A Lockwood,Kimberly G %A Branch,OraLee H %A Graham,Sarah A %+ Lark Health, 2570 El Camino Real, Mountain View, CA, 94040, United States, 1 650 300 1755, sarah.graham@lark.com %K engagement %K retention %K scales %K self-monitoring %K mobile app %K digital health %K AI %K smartphone %K platform %K app %K application %K health program %K program %D 2023 %7 3.2.2023 %9 Research Letter %J JMIR Mhealth Uhealth %G English %X %M 36735288 %R 10.2196/40865 %U https://mhealth.jmir.org/2023/1/e40865 %U https://doi.org/10.2196/40865 %U http://www.ncbi.nlm.nih.gov/pubmed/36735288 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e41663 %T Factors Influencing Community Participation in Internet Interventions Compared With Research Trials: Observational Study in a Nationally Representative Adult Cohort %A Batterham,Philip %A Gulliver,Amelia %A Sunderland,Matthew %A Farrer,Louise %A Kay-Lambkin,Frances %A Trias,Angelica %A Calear,Alison %+ Centre for Mental Health Research, College of Health and Medicine, The Australian National University, 63 Eggleston Road, Acton ACT, 2601, Australia, 61 2 61251031, philip.batterham@anu.edu.au %K mental health %K uptake %K engagement %K internet %K research participation %K implementation %D 2023 %7 2.2.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital mental health (DMH) programs can be effective in treating and preventing mental health problems. However, community engagement with these programs can be poor. Understanding the barriers and enablers of DMH program use may assist in identifying ways to increase the uptake of these programs, which have the potential to provide broad-scale prevention and treatment in the community. Objective: In this study, we aimed to identify and compare factors that may influence participation in DMH programs in practice and research trials, identify any respondent characteristics that are associated with these factors, and assess the relationship between intentions to use DMH programs and actual uptake. Methods: Australian adults aged ≥18 years were recruited from market research panels to participate in the study. The sample was representative of the Australian adult population based on age, gender, and location. Participants completed a cross-sectional web-based survey assessing demographic characteristics, mental health symptom measures, attitudes and use of DMH programs in practice and in research studies, and the factors influencing their use in both settings. Results: Across both research and practice, trust in the organization delivering the service or trial was the top-ranked factor influencing participation, followed by anonymity or privacy and adequate information. There was little variation in rankings across demographic groups, including intentions to use DMH programs or mental health status. Intentions to use DMH programs were a strong predictor of both current (odds ratio 2.50, 99% CI 1.41-4.43; P<.001) and past (odds ratio 2.98, 99% CI 1.71-5.19; P<.001) use behaviors. Conclusions: Efforts to increase the uptake of DMH programs or participation in research trials should focus on clearly communicating the following to users: the legitimacy of the organization delivering the program, security and use of participant data, and effectiveness of DMH programs. %M 36729613 %R 10.2196/41663 %U https://www.jmir.org/2023/1/e41663 %U https://doi.org/10.2196/41663 %U http://www.ncbi.nlm.nih.gov/pubmed/36729613 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 11 %N %P e39975 %T Engagement With Gamification Elements in a Smoking Cessation App and Short-term Smoking Abstinence: Quantitative Assessment %A Rajani,Nikita B %A Bustamante,Luz %A Weth,Dominik %A Romo,Lucia %A Mastellos,Nikolaos %A Filippidis,Filippos T %+ Department of Primary Care and Public Health, Imperial College London, St Dunstan's Road, London, W6 8RP, United Kingdom, 44 7427615928, nikita.rajani14@imperial.ac.uk %K gamification %K smoking cessation %K smoking abstinence %K mHealth %K mobile apps %K mobile phone %K smartphone %K digital health %K user engagement %K cognitive outcome %K self-support %K in-app metrics %D 2023 %7 1.2.2023 %9 Original Paper %J JMIR Serious Games %G English %X Background: Gamification in smoking cessation apps has been found to improve cognitive outcomes associated with higher odds of quitting. Although some research has shown that gamification can also positively impact behavioral outcomes such as smoking cessation, studies have largely focused on physical activity and mental health. Only a few studies have explored the effects of gamification on smoking cessation outcomes, of which the majority have adopted qualitative methodologies and/or assessed engagement with apps using self-report. Objective: This study aimed to explore levels of user engagement with gamification features in a smoking cessation app via in-app metrics. Specifically, the objective of this paper was to investigate whether higher engagement with gamification features is associated with the likelihood of quitting in the short term. Methods: Data from a larger online study that recruited smokers seeking to quit were analyzed to address the objectives presented in this paper. The study took place between June 2019 and July 2020, and participants were primarily recruited via social media posts. Participants who met the eligibility criteria used 1 of 2 mobile apps for smoking cessation. In-app metrics shared by the developer of one of the smoking cessation apps, called Kwit, were used to assess engagement with gamification features. Out of 58 participants who used the Kwit app, 14 were excluded due to missing data or low engagement with the app (ie, not opening the app once a week). For the remaining 44 participants, mean (SD) values were calculated for engagement with the app using in-app metrics. A logistic regression model was used to investigate the association between engagement with gamification and 7-day smoking abstinence. Results: In total, data from 44 participants who used the Kwit app were analyzed. The majority of participants were male, married, and employed. Almost 30% (n=13) of participants self-reported successful 7-day abstinence at the end of the study. On average, the Kwit app was opened almost 31 (SD 39) times during the 4-week study period, with the diary feature used the most often (mean 22.8, SD 49.3). Moreover, it was found that each additional level unlocked was associated with approximately 22% higher odds of achieving 7-day abstinence after controlling for other factors such as age and gender (odds ratio 1.22, 95% CI 1.01-1.47). Conclusions: This study highlights the likely positive effects of certain gamification elements such as levels and achievements on short-term smoking abstinence. Although more robust research with a larger sample size is needed, this research highlights the important role that gamification features integrated into mobile apps can play in facilitating and supporting health behavior change. %M 36724003 %R 10.2196/39975 %U https://games.jmir.org/2023/1/e39975 %U https://doi.org/10.2196/39975 %U http://www.ncbi.nlm.nih.gov/pubmed/36724003 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e42266 %T User Engagement and Weight Loss Facilitated by a Mobile App: Retrospective Review of Medical Records %A Valinskas,Sarunas %A Nakrys,Marius %A Aleknavičius,Kasparas %A Jonusas,Justinas %A Lileikienė,Angelė %+ Lithuania Business University of Applied Sciences, Turgaus st 21, Klaipėda, 91249, Lithuania, 370 26311099, justinas.jonusas@kilo.health %K intermittent fasting %K fasting %K weight %K weight loss %K mobile application %K body composition %K mHealth %K mobile health %K diet %K dietary intervention %K weight loss outcome %K adherence %K engagement %K mobile app %K motivation %K intervention outcome %K fasting apps %K dietary interventions %K obesity %K regression analysis %D 2023 %7 24.1.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Intermittent fasting (IF) has gained popularity in recent years for its effect on weight loss and supposed additional health benefits, such as a positive effect on body composition and metabolic markers. Mobile apps can act as platforms that help deliver dietary interventions by improving adherence and motivation. Although the effect of IF on weight loss has been demonstrated in earlier trials, there is not much research about the engagement and weight loss results with IF apps. Objective: Our main objective was to compare how a nudging platform (including smart scales) influences engagement (the extent to which users interact with the app measured by the number of active days) with the app among users who had obesity at the beginning of use. The secondary objectives were to evaluate the body weight changes among active and nonactive users and, finally, to evaluate the body composition changes of users possessing smart scales during app usage. Through this study, we hope to provide (1) more insight into how nudging (using smart scales as a nudging platform) is associated with engagement with the mobile app, (2) how engagement with the mobile app is associated with weight loss, and (3) how IF is associated with body composition. Methods: We performed a retrospective analysis of data from 665 users with obesity (BMI≥30) who started using the IF app DoFasting. Of them, 244 used body composition scales that estimated body fat and body muscle values. Users were stratified into engagement groups in accordance with their activity ratio (number of active days divided by the total time of use). Baseline and final users' weight (in kg), body fat (in %), and body muscle (in %) were compared. Results: Our findings suggest an association between the nudging platform (smart scales) and better engagement with the app. Smart scale users had a significantly higher activity ratio than regular users. Additionally, active DoFasting users lost significantly more weight. Further, body composition analysis showed that app usage might be related to body fat loss and an increase in muscle mass. Conclusions: We found a possible association between the nudging and gamified elements and higher app engagement. Additionally, increased app engagement is associated with increased weight loss. Thus, nudging and gamified elements of mobile health apps, such as interactive tools, goals, challenges, and progress tracking, are suggested to affect engagement positively and should be investigated further in future research. Finally, the IF regime delivered through the DoFasting app might be related to the body muscle mass gain and reduced fat mass. %M 36692936 %R 10.2196/42266 %U https://formative.jmir.org/2023/1/e42266 %U https://doi.org/10.2196/42266 %U http://www.ncbi.nlm.nih.gov/pubmed/36692936 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43629 %T Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials %A Bricker,Jonathan %A Miao,Zhen %A Mull,Kristin %A Santiago-Torres,Margarita %A Vock,David M %+ Division of Public Health Sciences, Fred Hutch Cancer Center, 1100 Fairview Avenue North, M3-B232, Seattle, WA, 98109, United States, 1 2066675000, jbricker@fredhutch.org %K acceptance and commitment therapy %K ACT %K attrition %K digital interventions %K dropout %K eHealth %K engagement %K iCanQuit %K mobile health %K mHealth %K QuitGuide %K smartphone apps %K smoking %K tobacco %K trajectories %K mobile phone %D 2023 %7 20.1.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods. Objective: This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529). Methods: Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction. Results: The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold). Conclusions: Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes. %M 36662550 %R 10.2196/43629 %U https://www.jmir.org/2023/1/e43629 %U https://doi.org/10.2196/43629 %U http://www.ncbi.nlm.nih.gov/pubmed/36662550 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e40784 %T Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial %A Trinquart,Ludovic %A Liu,Chunyu %A McManus,David D %A Nowak,Christopher %A Lin,Honghuang %A Spartano,Nicole L %A Borrelli,Belinda %A Benjamin,Emelia J %A Murabito,Joanne M %+ Section of General Internal Medicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston Medical Center, 73 Mount Wayte Ave, Framingham, MA, 01702, United States, 1 5089353400, murabito@bu.edu %K smartphone notifications %K digital device use %K randomized trial %K smartphone %K apps %K mobile health %K mHealth %K devices %K cardiovascular %K data %K intervention %K blood pressure %K heart rate %K digital %K tool %K notification %K messaging %K prompt %K nudge %K behavior change %K self-monitoring %K self care %K cardiology %D 2023 %7 20.1.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited. Objective: This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data. Methods: We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant’s name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary). Results: Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening. Conclusions: Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research. Trial Registration: ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019 %M 36662544 %R 10.2196/40784 %U https://www.jmir.org/2023/1/e40784 %U https://doi.org/10.2196/40784 %U http://www.ncbi.nlm.nih.gov/pubmed/36662544 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 6 %N %P e36807 %T Factors Influencing Continued Wearable Device Use in Older Adult Populations: Quantitative Study %A Muñoz Esquivel,Karla %A Gillespie,James %A Kelly,Daniel %A Condell,Joan %A Davies,Richard %A McHugh,Catherine %A Duffy,William %A Nevala,Elina %A Alamäki,Antti %A Jalovaara,Juha %A Tedesco,Salvatore %A Barton,John %A Timmons,Suzanne %A Nordström,Anna %+ Department of Computer Science, Atlantic Technological University, Port Road, Letterkenny, F92 FC93, Ireland, 353 74 918 6000, karla.munozesquivel@atu.ie %K usability %K older adults %K remote sensing %K sensor systems %K wearable device %K mobile phone %D 2023 %7 19.1.2023 %9 Original Paper %J JMIR Aging %G English %X Background: The increased use of wearable sensor technology has highlighted the potential for remote telehealth services such as rehabilitation. Telehealth services incorporating wearable sensors are most likely to appeal to the older adult population in remote and rural areas, who may struggle with long commutes to clinics. However, the usability of such systems often discourages patients from adopting these services. Objective: This study aimed to understand the usability factors that most influence whether an older adult will decide to continue using a wearable device. Methods: Older adults across 4 different regions (Northern Ireland, Ireland, Sweden, and Finland) wore an activity tracker for 7 days under a free-living environment protocol. In total, 4 surveys were administered, and biometrics were measured by the researchers before the trial began. At the end of the trial period, the researchers administered 2 further surveys to gain insights into the perceived usability of the wearable device. These were the standardized System Usability Scale (SUS) and a custom usability questionnaire designed by the research team. Statistical analyses were performed to identify the key factors that affect participants’ intention to continue using the wearable device in the future. Machine learning classifiers were used to provide an early prediction of the intention to continue using the wearable device. Results: The study was conducted with older adult volunteers (N=65; mean age 70.52, SD 5.65 years) wearing a Xiaomi Mi Band 3 activity tracker for 7 days in a free-living environment. The results from the SUS survey showed no notable difference in perceived system usability regardless of region, sex, or age, eliminating the notion that usability perception differs based on geographical location, sex, or deviation in participants’ age. There was also no statistically significant difference in SUS score between participants who had previously owned a wearable device and those who wore 1 or 2 devices during the trial. The bespoke usability questionnaire determined that the 2 most important factors that influenced an intention to continue device use in an older adult cohort were device comfort (τ=0.34) and whether the device was fit for purpose (τ=0.34). A computational model providing an early identifier of intention to continue device use was developed using these 2 features. Random forest classifiers were shown to provide the highest predictive performance (80% accuracy). After including the top 8 ranked questions from the bespoke questionnaire as features of our model, the accuracy increased to 88%. Conclusions: This study concludes that comfort and accuracy are the 2 main influencing factors in sustaining wearable device use. This study suggests that the reported factors influencing usability are transferable to other wearable sensor systems. Future work will aim to test this hypothesis using the same methodology on a cohort using other wearable technologies. %M 36656636 %R 10.2196/36807 %U https://aging.jmir.org/2023/1/e36807 %U https://doi.org/10.2196/36807 %U http://www.ncbi.nlm.nih.gov/pubmed/36656636 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 12 %P e42397 %T Dropout Rate in Digital Health Interventions for the Prevention of Skin Cancer: Systematic Review, Meta-analysis, and Metaregression %A Hernández-Rodríguez,Juan-Carlos %A García-Muñoz,Cristina %A Ortiz-Álvarez,Juan %A Saigí-Rubió,Francesc %A Conejo-Mir,Julián %A Pereyra-Rodriguez,Jose-Juan %+ Department of Nursing and Physical Therapy, University of Cadiz, Avda. Ana de Viya 52, Cadiz, 11009, Spain, 34 956 01 90 00, ccriss.g@gmail.com %K skin cancer %K digital health %K dropout %K prevention %K systematic review %K meta-analysis %K meta analyses %K review methodology %K cancer %K skin %K dermatology %K attrition %K digital intervention %K digital treatment %K eHealth %K randomized controlled trial %K RCT %D 2022 %7 9.12.2022 %9 Review %J J Med Internet Res %G English %X Background: Digital strategies are innovative approaches to the prevention of skin cancer, but the attrition following this kind of intervention needs to be analyzed. Objective: The aim of this paper is to assess the dropouts from studies focused on digital strategies for the prevention of skin cancer. Methods: We conducted this systematic review with meta-analyses and metaregression according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statements. Search terms for skin cancer, digital strategies, and prevention were combined to search PubMed, Scopus, Web of Science, CINAHL, and Cochrane Library from inception until July 2022. Randomized clinical trials that reported dropouts of participants and compared digital strategies with other interventions to prevent skin cancer in healthy or disease-free participants were included. Two independent reviewers extracted data for analysis. The Revised Cochrane Collaboration Bias tool was employed. We calculated the pooled dropout rate of participants through a meta-analysis of proportions and examined whether dropout was more or less frequent in digital interventions against comparators via an odds ratio (OR) meta-analysis. Data were pooled using a random-effects model. Subgroup meta-analyses were conducted in a meta-analysis of proportions and OR meta-analysis to assess the dropout events when data were sorted by digital interventions or control comparator. A univariate metaregression based on a random-effects model assessed possible moderators of dropout. Participants’ dropout rates as pooled proportions were calculated for all groups combined, and the digital and comparator groups separately. OR>1 indicated higher dropouts for digital-based interventions. Metaregressions were performed for age, sex, length of intervention, and sample size. Results: A total of 17 studies were included. The overall pooled dropout rate was 9.5% (95% CI 5.0-17.5). The subgroup meta-analysis of proportions revealed a dropout rate of 11.6% for digital strategies (95% CI 6.8-19.0) and 10.0% for comparators (95% CI 5.5-17.7). A trend of higher dropout rates for digital strategies was observed in the overall (OR 1.16, 95% CI 0.98-1.36) and subgroup OR meta-analysis, but no significant differences were found between the groups. None of the covariates moderated the effect size in the univariate metaregression. Conclusions: Digital strategies had a higher dropout rate compared to other prevention interventions, but the difference was not significant. Standardization is needed regarding reporting the number of and reasons for dropouts. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42022329669; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329669 %M 36485027 %R 10.2196/42397 %U https://www.jmir.org/2022/12/e42397 %U https://doi.org/10.2196/42397 %U http://www.ncbi.nlm.nih.gov/pubmed/36485027 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 11 %P e30285 %T Identifying Personality Characteristics and Indicators of Psychological Well-Being Associated With Attrition in the Motivation Makes the Move! Physical Activity Intervention: Randomized Technology-Supported Trial %A Kaseva,Kaisa %A Tervaniemi,Mari %A Heikura,Enni %A Kostilainen,Kaisamari %A Pöyhönen-Alho,Maritta %A Shoemaker,J Kevin %A Petrella,Robert J %A Peltonen,Juha E %+ Department of Sport and Exercise Medicine, Clinicum, Faculty of Medicine, University of Helsinki, Alppikatu 2, Helsinki, 00530, Finland, 358 443077737, kaisa.kaseva@helsinki.fi %K randomized trial %K physical activity %K lifestyles %K personality %K psychological well-being %K study attrition %K mental health %K lifestyle interventions %D 2022 %7 25.11.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Data attrition has been a common problem in longitudinal lifestyle interventions. The contributors to attrition in technology-supported physical activity interventions have not been thoroughly studied. Objective: The present study examined the roles of personality characteristics and indicators of psychological well-being in data attrition within a technology-supported, longitudinal intervention study with overweight adults. Methods: Participants (N=89) were adults from the Motivation Makes the Move! intervention study. Data attrition was studied after a 3-month follow-up. Participants’ personality characteristics were studied using the Short Five self-report questionnaire. Psychological well-being indicators were assessed with the RAND 36-item health survey, Positive and Negative Affect Schedule, and Beck Depression Inventory. Logistic regression analyses were conducted to assess the risk of discontinuing the study. The analyses were adjusted for sex, age, study group, and educational status. Results: At the 3-month follow-up, 65 of 89 participants (73% of the initial sample) had continued in the study. Participants’ personality characteristics and indicators of psychological well-being were not associated with the risk of dropping out of the study (all P values >.05). The results remained the same after covariate controls. Conclusions: Participant attrition was not attributable to personality characteristics or psychological well-being in the Motivation Makes the Move! study conducted with overweight adults. As attrition remains a challenge within longitudinal, technology-supported lifestyle interventions, attention should be paid to the potentially dynamic natures of personality and psychological well-being, as well as other elements beyond these. Trial Registration: ClinicalTrials.gov NCT02686502; https://clinicaltrials.gov/ct2/show/NCT02686502 %M 36427239 %R 10.2196/30285 %U https://formative.jmir.org/2022/11/e30285 %U https://doi.org/10.2196/30285 %U http://www.ncbi.nlm.nih.gov/pubmed/36427239 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 11 %P e38255 %T Usage of a Web-Based eHealth Intervention for Women With Stress Urinary Incontinence: Mixed Methods Study %A Firet,Lotte %A Teunissen,Theodora Alberta Maria %A Kool,Rudolf Bertijn %A Notten,Kim Josephina Bernadette %A Lagro-Janssen,Antoinette Leonarda Maria %A van der Vaart,Huub %A Assendelft,Willem Jan Jozef %+ Department of Primary and Community Care, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein 21, Nijmegen, Postbox 9101, Netherlands, 31 243618181, lotte.firet@radboudumc.nl %K eHealth %K urinary incontinence %K women %K usage %K nonattrition %K adherence %K implementation science %K pelvic floor muscle training %K mixed methods design %D 2022 %7 17.11.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Stress urinary incontinence (SUI) is highly prevalent among women and has an impact on physical and mental well-being. eHealth with pelvic floor muscle training (PFMT) has shown to be effective in reducing complaints. The usage and nonusage attrition of eHealth for SUI is unknown, but knowledge about users and their usage patterns is crucial for implementation purposes. Objective: This study aimed to evaluate how an eHealth intervention for SUI was used and by whom, explore reasons for nonusage attrition, and determine what factors are associated with usage. Methods: In this observational, mixed methods study, women with SUI independently registered to a web-based eHealth intervention, Baas over je blaas, a translation of the Swedish internet program Tät-treatment of stress urinary incontinence. Log-in data were collected during 3-month access to the website, and surveys were sent at baseline. Participants were divided into three user groups (low, intermediate, and high) and were compared based on sociodemographic and incontinence-related characteristics. Nominal logistic regression analysis was used to study factors associated with eHealth usage. Qualitative content analysis was used for open-ended questions about nonusage attrition and about facilitators of and barriers to eHealth usage. Results: Participants (n=561) had a mean age of 50.3 (SD 12.1) years, and most of them (340/553, 61.5%) had never visited a health care professional for SUI before. Most users were low users (295/515, 57.3%), followed by intermediate users (133/515, 25.8%) and high users (87/515, 16.9%). User groups differed significantly in age (48.3, SD 12 years; 52.1, SD 11.6 years; and 55.3, SD 10.9 years; P<.001) and in their expected ability to train the pelvic floor muscles (7.5, SD 1.4; 7.7, SD 1.4; and 8.1, SD 1.5 for low, intermediate, and high users, respectively; P=.006). Nonusage attrition was mainly caused by problems in integrating PFMT into everyday life. High age (>50 years), previous PFMT, and high expected ability to train the pelvic floor muscles are associated with high usage. Facilitators for eHealth usage were the clear explanation of exercises and the possibility of self-management. Barriers were its noncommittal character and the absence of personal contact. Conclusions: eHealth fulfills a need for women with SUI who have never received treatment. Those who discontinued prematurely did so mainly because it was difficult to integrate the training schedule into their everyday lives. High eHealth usage was more likely for women aged >50 years, with previous PFMT, and with high expectations about their ability to train the pelvic floor muscles. Knowledge of these user characteristics can guide clinicians and correct their misunderstandings about the suitable target population for this intervention. Furthermore, strategies for reinforcing expectations and self-efficacy are important to upscale eHealth usage, together with paying attention to people’s need for personal contact. International Registered Report Identifier (IRRID): RR2-10.2196/13164 %M 36394923 %R 10.2196/38255 %U https://www.jmir.org/2022/11/e38255 %U https://doi.org/10.2196/38255 %U http://www.ncbi.nlm.nih.gov/pubmed/36394923 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 11 %P e41463 %T Omnichannel Communication to Boost Patient Engagement and Behavioral Change With Digital Health Interventions %A Blasiak,Agata %A Sapanel,Yoann %A Leitman,Dana %A Ng,Wei Ying %A De Nicola,Raffaele %A Lee,V Vien %A Todorov,Atanas %A Ho,Dean %+ The Institute for Digital Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, #05-COR Centre for Life Sciences, Singapore, 117456, Singapore, 65 6601 7766, agata.blasiak@nus.edu.sg %K digital health intervention %K omnichannel engagement %K behavioral change %K communication channels %K personalized engagement %K health care %K patient care %K health care outcome %K patient engagement %K digital twin %K DHI %K digital health %K eHealth %K framework %K development %D 2022 %7 16.11.2022 %9 Viewpoint %J J Med Internet Res %G English %X Digital health interventions are being increasingly incorporated into health care workflows to improve the efficiency of patient care. In turn, sustained patient engagement with digital health interventions can maximize their benefits toward health care outcomes. In this viewpoint, we outline a dynamic patient engagement by using various communication channels and the potential use of omnichannel engagement to integrate these channels. We conceptualize a novel patient care journey where multiple web-based and offline communication channels are integrated through a “digital twin.” The principles of implementing omnichannel engagement for digital health interventions and digital twins are also broadly covered. Omnichannel engagement in digital health interventions implies a flexibility for personalization, which can enhance and sustain patient engagement with digital health interventions, and ultimately, patient quality of care and outcomes. We believe that the novel concept of omnichannel engagement in health care can be greatly beneficial to patients and the system once it is successfully realized to its full potential. %M 36383427 %R 10.2196/41463 %U https://www.jmir.org/2022/11/e41463 %U https://doi.org/10.2196/41463 %U http://www.ncbi.nlm.nih.gov/pubmed/36383427 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 11 %N 2 %P e38886 %T A New Approach to Enhancing Engagement in eHealth Apps %A Oakley-Girvan,Ingrid %A Docherty,John P %+ Research, Value and Strategy, Medable Inc, 525 University Ave, Suite A70, Palo Alto, CA, 94301, United States, 1 877 820 6259, Ingrid@medable.com %K user engagement %K eHealth %K attrition %K adherence %K apps %K app design %K user experience %D 2022 %7 9.11.2022 %9 Viewpoint %J Interact J Med Res %G English %X This viewpoint presents a 3-phase conceptual model of the process of user engagement with eHealth apps. We also describe how knowledge gleaned from psychosocial, behavioral, and cognitive science can be incorporated into this model to enhance user engagement with an eHealth app in each phase of the engagement process. %M 36279587 %R 10.2196/38886 %U https://www.i-jmr.org/2022/2/e38886 %U https://doi.org/10.2196/38886 %U http://www.ncbi.nlm.nih.gov/pubmed/36279587 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 5 %N 3 %P e37090 %T Validation of a Remote and Fully Automated Story Recall Task to Assess for Early Cognitive Impairment in Older Adults: Longitudinal Case-Control Observational Study %A Skirrow,Caroline %A Meszaros,Marton %A Meepegama,Udeepa %A Lenain,Raphael %A Papp,Kathryn V %A Weston,Jack %A Fristed,Emil %+ Novoic Ltd, Wenlock Studios, Office G.05, 50-52 Wharf Road, Islington, London, N1 7EU, United Kingdom, 44 7759 093006, caroline@novoic.com %K neurology %K memory %K episodic %K speech %K psychometrics %K reliability %K validity %K aging %K elder %K older adult %K Alzheimer disease %K mild cognitive impairment %K mobile apps %K mobile health %K mHealth %K smartphone %K cognition %K cognitive decline %K cognitive impairment %K development %K validation %K recall %K memory %K story %K stories %K observational study %K acceptability %K usability %K semantic %K cognitive test %K speech %K linguistic %K mobile phone %D 2022 %7 30.9.2022 %9 Original Paper %J JMIR Aging %G English %X Background: Story recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring. Objective: This study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD. Methods: The “Amyloid Prediction in Early Stage Alzheimer’s disease” (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants’ personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer’s Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire. Results: Of the 200 participants recruited in the AMYPRED studies, 151 (75.5%)—78 cognitively unimpaired (CU) and 73 MCI or mild AD—engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests. Conclusions: The unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring. %M 36178715 %R 10.2196/37090 %U https://aging.jmir.org/2022/3/e37090 %U https://doi.org/10.2196/37090 %U http://www.ncbi.nlm.nih.gov/pubmed/36178715 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 9 %P e40249 %T Medical Staff and Resident Preferences for Using Deep Learning in Eye Disease Screening: Discrete Choice Experiment %A Lin,Senlin %A Li,Liping %A Zou,Haidong %A Xu,Yi %A Lu,Lina %+ Shanghai Eye Disease Prevention and Treatment Center, Shanghai Eye Hospital, No. 1440, Hongqiao Road, Shanghai, 200336, China, 86 02162539696, lulina781019@qq.com %K discrete choice experiment %K preference %K artificial intelligence %K AI %K vision health %K screening %D 2022 %7 20.9.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Deep learning–assisted eye disease diagnosis technology is increasingly applied in eye disease screening. However, no research has suggested the prerequisites for health care service providers and residents willing to use it. Objective: The aim of this paper is to reveal the preferences of health care service providers and residents for using artificial intelligence (AI) in community-based eye disease screening, particularly their preference for accuracy. Methods: Discrete choice experiments for health care providers and residents were conducted in Shanghai, China. In total, 34 medical institutions with adequate AI-assisted screening experience participated. A total of 39 medical staff and 318 residents were asked to answer the questionnaire and make a trade-off among alternative screening strategies with different attributes, including missed diagnosis rate, overdiagnosis rate, screening result feedback efficiency, level of ophthalmologist involvement, organizational form, cost, and screening result feedback form. Conditional logit models with the stepwise selection method were used to estimate the preferences. Results: Medical staff preferred high accuracy: The specificity of deep learning models should be more than 90% (odds ratio [OR]=0.61 for 10% overdiagnosis; P<.001), which was much higher than the Food and Drug Administration standards. However, accuracy was not the residents’ preference. Rather, they preferred to have the doctors involved in the screening process. In addition, when compared with a fully manual diagnosis, AI technology was more favored by the medical staff (OR=2.08 for semiautomated AI model and OR=2.39 for fully automated AI model; P<.001), while the residents were in disfavor of the AI technology without doctors’ supervision (OR=0.24; P<.001). Conclusions: Deep learning model under doctors’ supervision is strongly recommended, and the specificity of the model should be more than 90%. In addition, digital transformation should help medical staff move away from heavy and repetitive work and spend more time on communicating with residents. %M 36125854 %R 10.2196/40249 %U https://www.jmir.org/2022/9/e40249 %U https://doi.org/10.2196/40249 %U http://www.ncbi.nlm.nih.gov/pubmed/36125854 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 3 %P e35486 %T Participants’ and Nurses’ Experiences With a Digital Intervention for Patients With Depressive Symptoms and Comorbid Hypertension or Diabetes in Peru: Qualitative Post–Randomized Controlled Trial Study %A Toyama,Mauricio %A Cavero,Victoria %A Araya,Ricardo %A Menezes,Paulo Rossi %A Mohr,David C %A Miranda,J Jaime %A Diez-Canseco,Francisco %+ CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Av. Armendariz 445, Miraflores, Lima, 15074, Peru, 51 958549065, m.toyama.g@gmail.com %K mobile intervention %K depression %K diabetes %K hypertension %K comorbidity %K qualitative research %K mobile phone %D 2022 %7 15.9.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Depression is one of the most prevalent mental disorders and a leading cause of disability, disproportionately affecting specific groups, such as patients with noncommunicable diseases. Over the past decade, digital interventions have been developed to provide treatment for these patients. CONEMO (Emotional Control in Spanish) is an 18-session psychoeducational digital intervention delivered through a smartphone app and minimally supported by a nurse. CONEMO demonstrated effectiveness in reducing depressive symptoms through a randomized controlled trial (RCT) among patients with diabetes, hypertension, or both, in Lima, Peru. However, in addition to clinical outcomes, it is important to explore users’ experiences, satisfaction, and perceptions of usability and acceptability, which can affect their engagement with the intervention. Objective: This study aimed to explore the RCT participants’ experiences with CONEMO in Peru, complemented with information provided by the nurses who monitored them. Methods: In 2018, semistructured interviews were conducted with a sample of 29 (13.4%) patients from the 217 patients who participated in the CONEMO intervention in Peru and the 3 hired nurses who supported its delivery. Interviewees were selected at random based on their adherence to the digital intervention (0-5, 10-14, and 15-18 sessions completed), to include different points of view. Content analysis was conducted to analyze the interviews. Results: Participants’ mean age was 64.4 (SD 8.5) years, and 79% (23/29) of them were women. Most of the interviewed participants (21/29, 72%) stated that CONEMO fulfilled their expectations and identified positive changes in their physical and mental health after using it. Some of these improvements were related to their thoughts and feelings (eg, think differently, be more optimistic, and feel calmer), whereas others were related to their routines (eg, go out more and improve health-related habits). Most participants (19/29, 66%) reported not having previous experience with using smartphones, and despite experiencing some initial difficulties, they managed to use CONEMO. The most valued features of the app were the videos and activities proposed for the participant to perform. Most participants (27/29, 93%) had a good opinion about the study nurses and reported feeling supported by them. A few participants provided suggestions to improve the intervention, which included adding more videos, making the sessions’ text simple, extending the length of the intervention, and improving the training session with long explanations. Conclusions: The findings of this qualitative study provide further support and contextualize the positive results found in the CONEMO RCT, including insights into the key features that made the intervention effective and engaging. The participants’ experience with the smartphone and CONEMO app reveal that it is feasible to be used by people with little knowledge of technology. In addition, the study identified suggestions to improve the CONEMO intervention for its future scale-up. Trial Registration: ClinicalTrials.gov NCT03026426; https://clinicaltrials.gov/ct2/show/NCT03026426 %M 36107482 %R 10.2196/35486 %U https://humanfactors.jmir.org/2022/3/e35486 %U https://doi.org/10.2196/35486 %U http://www.ncbi.nlm.nih.gov/pubmed/36107482 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 8 %P e40096 %T Characterizing User Engagement With a Digital Intervention for Pain Self-management Among Youth With Sickle Cell Disease and Their Caregivers: Subanalysis of a Randomized Controlled Trial %A Lalloo,Chitra %A Nishat,Fareha %A Zempsky,William %A Bakshi,Nitya %A Badawy,Sherif %A Ko,Yeon Joo %A Dampier,Carlton %A Stinson,Jennifer %A Palermo,Tonya M %+ Department of Child Health Evaluative Sciences, The Hospital for Sick Children, 686 Bay Street, Toronto, ON, M5G 0A4, Canada, 1 416 813 2332 ext 302332, chitra.lalloo@sickkids.ca %K engagement %K adolescents %K caregivers %K sickle cell %K pain %K mHealth %K self-management %K digital health analytics %K mixed methods %K youth %K management %K disease %K acute pain %K chronic pain %K coping %K North America %K intervention %K child %K digital health %K program %D 2022 %7 30.8.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Sickle cell disease (SCD) is characterized by severe acute pain episodes as well as risk for chronic pain. Digital delivery of SCD pain self-management support may enhance pain self-management skills and accessibility for youth. However, little is known about how youth with SCD and their caregivers engage with digital health programs. iCanCope with pain is a digital pain self-management platform adapted for youth with SCD and caregivers through a user-centered design approach. The program was delivered via a website (separate versions for youth and caregiver) and mobile app (youth only). Objective: We aimed to characterize patterns of user engagement with the iCanCope with SCD program among youth with SCD and their caregivers. Methods: A randomized controlled trial was completed across multiple North American SCD clinics. Eligible youth were aged 12-18 years, diagnosed with SCD, English-speaking, and experiencing moderate-to-severe pain interference. Eligible caregivers were English-speaking with a child enrolled in the study. Dyads were randomized to receive the iCanCope intervention or attention-control education for 8-12 weeks. This report focused on engagement among dyads who received the intervention. User-level analytics were captured. Individual interviews were conducted with 20% of dyads. Descriptive statistics characterized quantitative engagement. Content analysis summarized qualitative interview data. Exploratory analysis tested the hypothesis that caregiver engagement would be positively associated with child engagement. Results: The cohort included primarily female (60% [34/57] of youth; 91% [49/56] of caregivers) and Black (>90% of youth [53/57] and caregivers [50/56]) participants. Among 56 dyads given program access, differential usage patterns were observed: both the youth and caregiver engaged (16/56, 29%), only the youth engaged (24/56, 43%), only the caregiver engaged (1/56, 2%), and neither individual engaged (16/56, 29%). While most youth engaged with the program (40/57, 70%), most caregivers did not (39/56, 70%). Youth were more likely to engage with the app than the website (85% [34/57] versus 68% [23/57]), and the most popular content categories were goal setting, program introduction, and symptom history. Among caregivers, program introduction, behavioral plans, and goal setting were the most popular content areas. As hypothesized, there was a moderate positive association between caregiver and child engagement (χ21=6.6; P=.01; ϕ=0.34). Interviews revealed that most dyads would continue to use the program (11/12, 92%) and recommend it to others (10/12, 83%). The reasons for app versus website preference among youth were ease of use, acceptable time commitment, and interactivity. Barriers to caregiver engagement included high time burden and limited perceived relevance of content. Conclusions: This is one of the first studies to apply digital health analytics to characterize patterns of engagement with SCD self-management among youth and caregivers. The findings will be used to optimize the iCanCope with SCD program prior to release. Trial Registration: ClinicalTrials.gov NCT03201874; https://clinicaltrials.gov/ct2/show/NCT03201874 %M 36040789 %R 10.2196/40096 %U https://www.jmir.org/2022/8/e40096 %U https://doi.org/10.2196/40096 %U http://www.ncbi.nlm.nih.gov/pubmed/36040789 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 8 %P e38261 %T Predictors of Dropout in a Digital Intervention for the Prevention and Treatment of Depression in Patients With Chronic Back Pain: Secondary Analysis of Two Randomized Controlled Trials %A Moshe,Isaac %A Terhorst,Yannik %A Paganini,Sarah %A Schlicker,Sandra %A Pulkki-Råback,Laura %A Baumeister,Harald %A Sander,Lasse B %A Ebert,David Daniel %+ Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, P.O. Box 63, Helsinki, 00014, Finland, 358 406324442, isaac.moshe@helsinki.fi %K adherence %K dropout %K law of attrition %K attrition %K digital health %K internet intervention %K depression %K back pain %K comorbidity %K mental health %K eHealth %K mobile phone %D 2022 %7 30.8.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Depression is a common comorbid condition in individuals with chronic back pain (CBP), leading to poorer treatment outcomes and increased medical complications. Digital interventions have demonstrated efficacy in the prevention and treatment of depression; however, high dropout rates are a major challenge, particularly in clinical settings. Objective: This study aims to identify the predictors of dropout in a digital intervention for the treatment and prevention of depression in patients with comorbid CBP. We assessed which participant characteristics may be associated with dropout and whether intervention usage data could help improve the identification of individuals at risk of dropout early on in treatment. Methods: Data were collected from 2 large-scale randomized controlled trials in which 253 patients with a diagnosis of CBP and major depressive disorder or subclinical depressive symptoms received a digital intervention for depression. In the first analysis, participants’ baseline characteristics were examined as potential predictors of dropout. In the second analysis, we assessed the extent to which dropout could be predicted from a combination of participants’ baseline characteristics and intervention usage variables following the completion of the first module. Dropout was defined as completing <6 modules. Analyses were conducted using logistic regression. Results: From participants’ baseline characteristics, lower level of education (odds ratio [OR] 3.33, 95% CI 1.51-7.32) and both lower and higher age (a quadratic effect; age: OR 0.62, 95% CI 0.47-0.82, and age2: OR 1.55, 95% CI 1.18-2.04) were significantly associated with a higher risk of dropout. In the analysis that aimed to predict dropout following completion of the first module, lower and higher age (age: OR 0.60, 95% CI 0.42-0.85; age2: OR 1.59, 95% CI 1.13-2.23), medium versus high social support (OR 3.03, 95% CI 1.25-7.33), and a higher number of days to module completion (OR 1.05, 95% CI 1.02-1.08) predicted a higher risk of dropout, whereas a self-reported negative event in the previous week was associated with a lower risk of dropout (OR 0.24, 95% CI 0.08-0.69). A model that combined baseline characteristics and intervention usage data generated the most accurate predictions (area under the receiver operating curve [AUC]=0.72) and was significantly more accurate than models based on baseline characteristics only (AUC=0.70) or intervention usage data only (AUC=0.61). We found no significant influence of pain, disability, or depression severity on dropout. Conclusions: Dropout can be predicted by participant baseline variables, and the inclusion of intervention usage variables may improve the prediction of dropout early on in treatment. Being able to identify individuals at high risk of dropout from digital health interventions could provide intervention developers and supporting clinicians with the ability to intervene early and prevent dropout from occurring. %M 36040780 %R 10.2196/38261 %U https://www.jmir.org/2022/8/e38261 %U https://doi.org/10.2196/38261 %U http://www.ncbi.nlm.nih.gov/pubmed/36040780 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 8 %P e33772 %T Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study %A Van Baelen,Freek %A De Regge,Melissa %A Larivière,Bart %A Verleye,Katrien %A Schelfout,Sam %A Eeckloo,Kristof %+ Strategic Policy Cell, Ghent University Hospital, 10, Corneel Heymanslaan, Ghent, 9000, Belgium, 32 92643493, melissa.deregge@uzgent.be %K mHealth app %K engagement %K social influence %K app integration %K well-being %K Belgium %K mHealth %K behavioral %K behavioral engagement %K mobile health %K mobile health apps %K mobile phone %D 2022 %7 26.8.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The last decade has seen a considerable increase in the number of mobile health (mHealth) apps in everyday life. These mHealth apps have the potential to significantly improve the well-being of chronically ill patients. However, behavioral engagement with mHealth apps remains low. Objective: The aim of this study was to describe the behavioral engagement of chronically ill patients with mHealth apps by investigating (1) how it is affected by social factors (ie, physician recommendation) and app-related factors (ie, app integration) and (2) how it affects patient well-being. This study also considers the moderating effect of attachment to traditional health care and the mobile app experience among patients. Methods: We carried out a scenario-based survey study of chronically ill patients (N=521). A Bayesian structural equation modeling with mediation and moderation analysis was conducted in MPlus. Results: Both physician recommendations for mHealth app use and app integration have positive effects on the behavioral engagement of chronically ill patients with mHealth apps. Higher behavioral engagement positively affects the hedonic well-being (extent of pleasure) and the eudaemonic well-being (extent of self-efficacy) of chronically ill patients. Mobile app experience, however, positively moderates the relationship between app integration and behavioral engagement, whereas patient attachment to traditional care does not moderate the relationship between physician recommendation and behavioral engagement. Taken together, the proportion of variance explained (R²) equals 21% for behavioral engagement and 52.8% and 62.2% for hedonic and eudaemonic well-being, respectively, thereby providing support for the strong influence of app integration and physician recommendation via the mediation of the patients’ behavioral engagement on both patients’ hedonic and eudaemonic well-being. Conclusions: Physician recommendation and app integration enable behavioral engagement and promote well-being among chronically ill patients. It is thus important to take social and app-related factors into consideration during and after the development of mHealth apps. %M 36018618 %R 10.2196/33772 %U https://mhealth.jmir.org/2022/8/e33772 %U https://doi.org/10.2196/33772 %U http://www.ncbi.nlm.nih.gov/pubmed/36018618 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 8 %P e35657 %T Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review %A Madujibeya,Ifeanyi %A Lennie,Terry %A Aroh,Adaeze %A Chung,Misook L %A Moser,Debra %+ College of Nursing, University of Kentucky, 751 Rose Street, Lexington, KY, 40536, United States, 1 859 334 0561, ima232@uky.edu %K heart failure %K mobile health interventions %K mHealth interventions %K patient engagement %K system usage data %K heart failure outcomes %K mobile phone %D 2022 %7 22.8.2022 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Despite the potential of mobile health (mHealth) interventions to facilitate the early detection of signs of heart failure (HF) decompensation and provide personalized management of symptoms, the outcomes of such interventions in patients with HF have been inconsistent. As engagement with mHealth is required for interventions to be effective, poor patient engagement with mHealth interventions may be associated with mixed evidence. It is crucial to understand how engagement with mHealth interventions is measured in patients with HF, and the effects of engagement on HF outcomes. Objective: In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes. Methods: We conducted a systematic literature search in 7 databases for relevant studies published in the English language from 2009 to September 2021 and reported the descriptive characteristics of the studies. We used content analysis to identify themes that described patient engagement with mHealth interventions in the qualitative studies included in the review. Results: We synthesized 32 studies that operationalized engagement with mHealth interventions in 4771 patients with HF (3239/4771, 67.88%, male), ranging from a sample of 7 to 1571 (median 53.3) patients, followed for a median duration of 90 (IQR 45-180) days. Patient engagement with mHealth interventions was measured only quantitatively based on system usage data in 72% (23/32) of the studies, only qualitatively based on data from semistructured interviews and focus groups in 6% (2/32) of studies, and by a combination of both quantitative and qualitative data in 22% (7/32) of studies. System usage data were evaluated using 6 metrics of engagement: number of physiological parameters transmitted (19/30, 63% studies), number of HF questionnaires completed (2/30, 7% studies), number of log-ins (4/30, 13% studies), number of SMS text message responses (1/30, 3% studies), time spent (5/30, 17% studies), and the number of features accessed and screen viewed (4/30, 13% studies). There was a lack of consistency in how the system usage metrics were reported across studies. In total, 80% of the studies reported only descriptive characteristics of system usage data. The emotional, cognitive, and behavioral domains of patient engagement were identified through qualitative studies. Patient engagement levels ranged from 45% to 100% and decreased over time. The effects of engagement on HF knowledge, self-care, exercise adherence, and HF hospitalization were inconclusive. Conclusions: The measures of patient engagement with mHealth interventions in patients with HF are underreported and lack consistency. The application of inferential analytical methods to engagement data is extremely limited. There is a need for a working group on mHealth that may consolidate the previous operational definitions of patient engagement into an optimal and standardized measure. %M 35994345 %R 10.2196/35657 %U https://mhealth.jmir.org/2022/8/e35657 %U https://doi.org/10.2196/35657 %U http://www.ncbi.nlm.nih.gov/pubmed/35994345 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 8 %P e37640 %T Appropriate Use and Operationalization of Adherence to Digital Cognitive Behavioral Therapy for Depression and Anxiety in Youth: Systematic Review %A Li,Sophie H %A Achilles,Melinda R %A Werner-Seidler,Aliza %A Beames,Joanne R %A Subotic-Kerry,Mirjana %A O'Dea,Bridianne %+ Black Dog Institute and School of Psychology, The University of New South Wales, Hospital Road, Randwick, 2031, Australia, 61 411116615, s.h.li@blackdog.org.au %K adherence %K youth %K digital %K cognitive behavioral therapy %K review %K mobile phone %D 2022 %7 17.8.2022 %9 Review %J JMIR Ment Health %G English %X Background: Digital, self-guided cognitive behavioral therapy (CBT) interventions circumvent many barriers to in-person therapy for young people (aged 12-24 years), although adherence to these interventions is low. The absence or insufficient disclosure of recommendations or instructions for appropriate use may account for this. As such, many young people may not self-administer these interventions appropriately or receive the optimal degree of treatment. Objective: This systematic review aims to synthesize the literature on digital CBT for depression and anxiety in young people to describe how appropriate use has been defined and communicated to users as instructions for use, to describe how adherence has been measured, and to determine the associations between adherence and treatment outcomes. Methods: A systematic review was conducted with 2 reviewers (SHL and MRA) extracting data independently. Overall, 4 electronic databases (Embase, MEDLINE, PsycINFO, and Cochrane Library) were searched in April 2021 for studies that met the following inclusion criteria: participants aged between 12 and 24 years, evaluated a digital CBT intervention targeting depression or anxiety, and reported instructions or recommendations for use or measures of adherence. Studies that evaluated non-CBT interventions or cognitive- or behavioral-only interventions were excluded. Methodological quality was assessed using the Cochrane Risk of Bias Tool and the Integrated Quality Criteria for the Review of Multiple Study Designs. Results: There were 32 manuscripts that met the inclusion criteria, of which 28 (88%) were unique studies (N=16,578 youths). Definitions of appropriate use varied among the different interventions in terms of intended recipients, duration and frequency of use, and the features used to support engagement and adherence to appropriate use definitions. Reporting of appropriate use definitions in studies was inconsistent, with no study systematically describing components of appropriate use or providing information on how recommendations for use were relayed to users. Most often, definitions of appropriate use were derived from the study protocol and descriptions of intervention features. Adherence was mostly operationalized as the degree of intervention completion; however, reporting of adherence data was heterogeneous. There was little evidence of an association between degree of use and outcomes in the 9 studies that examined this. Conclusions: Definitions of appropriate use are unique to each digital CBT intervention. However, statements of appropriate use are not systematically reported in the literature. Furthermore, the extent to which recommendations for use are communicated to users is not routinely reported. Despite unique definitions of appropriate use, adherence was most often generically operationalized as the degree of intervention completion and was not consistently associated with outcomes. We proposed a framework to promote systematic reporting of definitions of appropriate use for digital interventions to provide guidance to users and to assist the development of appropriate and nuanced measures of adherence. Trial Registration: PROSPERO CRD42020208668; https://tinyurl.com/4bu2yram %M 35976180 %R 10.2196/37640 %U https://mental.jmir.org/2022/8/e37640 %U https://doi.org/10.2196/37640 %U http://www.ncbi.nlm.nih.gov/pubmed/35976180 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 8 %P e33545 %T Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series %A Ramadurai,Ramya %A Beckham,Erin %A McHugh,R Kathryn %A Björgvinsson,Thröstur %A Beard,Courtney %+ Department of Psychology, American University, 4400 Massachusetts Avenue NW, Washington, DC, 20016, United States, 1 202 885 8000, rr4748a@student.american.edu %K engagement %K mental health apps %K cognitive bias modification %K human support %K mobile health %K mHealth %K mobile phone %D 2022 %7 17.8.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy. Objective: This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring. Methods: We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser. Results: We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct. Conclusions: Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps. %M 35976196 %R 10.2196/33545 %U https://mental.jmir.org/2022/8/e33545 %U https://doi.org/10.2196/33545 %U http://www.ncbi.nlm.nih.gov/pubmed/35976196 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 10 %N 3 %P e39186 %T Breathing as an Input Modality in a Gameful Breathing Training App (Breeze 2): Development and Evaluation Study %A Lukic,Yanick Xavier %A Teepe,Gisbert Wilhelm %A Fleisch,Elgar %A Kowatsch,Tobias %+ Centre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/58, Zurich, , Switzerland, 41 446328638, ylukic@ethz.ch %K breathing training %K serious game %K biofeedback %K digital health %K mobile health %K mHealth %K mobile phone %K machine learning %K deep learning %K transfer learning %K neural networks %D 2022 %7 16.8.2022 %9 Original Paper %J JMIR Serious Games %G English %X Background: Slow-paced breathing training can have positive effects on physiological and psychological well-being. Unfortunately, use statistics indicate that adherence to breathing training apps is low. Recent work suggests that gameful breathing training may help overcome this challenge. Objective: This study aimed to introduce and evaluate the gameful breathing training app Breeze 2 and its novel real-time breathing detection algorithm that enables the interactive components of the app. Methods: We developed the breathing detection algorithm by using deep transfer learning to detect inhalation, exhalation, and nonbreathing sounds (including silence). An additional heuristic prolongs detected exhalations to stabilize the algorithm’s predictions. We evaluated Breeze 2 with 30 participants (women: n=14, 47%; age: mean 29.77, SD 7.33 years). Participants performed breathing training with Breeze 2 in 2 sessions with and without headphones. They answered questions regarding user engagement (User Engagement Scale Short Form [UES-SF]), perceived effectiveness (PE), perceived relaxation effectiveness, and perceived breathing detection accuracy. We used Wilcoxon signed-rank tests to compare the UES-SF, PE, and perceived relaxation effectiveness scores with neutral scores. Furthermore, we correlated perceived breathing detection accuracy with actual multi-class balanced accuracy to determine whether participants could perceive the actual breathing detection performance. We also conducted a repeated-measure ANOVA to investigate breathing detection differences in balanced accuracy with and without the heuristic and when classifying data captured from headphones and smartphone microphones. The analysis controlled for potential between-subject effects of the participants’ sex. Results: Our results show scores that were significantly higher than neutral scores for the UES-SF (W=459; P<.001), PE (W=465; P<.001), and perceived relaxation effectiveness (W=358; P<.001). Perceived breathing detection accuracy correlated significantly with the actual multi-class balanced accuracy (r=0.51; P<.001). Furthermore, we found that the heuristic significantly improved the breathing detection balanced accuracy (F1,25=6.23; P=.02) and that detection performed better on data captured from smartphone microphones than than on data from headphones (F1,25=17.61; P<.001). We did not observe any significant between-subject effects of sex. Breathing detection without the heuristic reached a multi-class balanced accuracy of 74% on the collected audio recordings. Conclusions: Most participants (28/30, 93%) perceived Breeze 2 as engaging and effective. Furthermore, breathing detection worked well for most participants, as indicated by the perceived detection accuracy and actual detection accuracy. In future work, we aim to use the collected breathing sounds to improve breathing detection with regard to its stability and performance. We also plan to use Breeze 2 as an intervention tool in various studies targeting the prevention and management of noncommunicable diseases. %M 35972793 %R 10.2196/39186 %U https://games.jmir.org/2022/3/e39186 %U https://doi.org/10.2196/39186 %U http://www.ncbi.nlm.nih.gov/pubmed/35972793 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 8 %P e33696 %T Analyzing the Impact of Mobile App Engagement on Mental Health Outcomes: Secondary Analysis of the Unwinding Anxiety Program %A Nardi,William %A Roy,Alexandra %A Dunsiger,Shira %A Brewer,Judson %+ Department of Behavioral and Social Sciences, Brown University, 121 South Main Street, Providence, RI, 02903, United States, 1 8609649144, william_nardi@brown.edu %K anxiety %K worry %K engagement %K mobile app %K mental health %K mobile phone %D 2022 %7 15.8.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: App-based interventions provide a promising avenue for mitigating the burden on mental health services by complimenting therapist-led treatments for anxiety. However, it remains unclear how specific systems’ use of app features may be associated with changes in mental health outcomes (eg, anxiety and worry). Objective: This study was a secondary analysis of engagement data from a stage 1 randomized controlled trial testing the impact of the Unwinding Anxiety mobile app among adults with generalized anxiety disorder. The aims of this study were 2-fold: to investigate whether higher microengagement with the primary intervention feature (ie, educational modules) is associated with positive changes in mental health outcomes at 2 months (ie, anxiety, worry, interoceptive awareness, and emotional reactivity) and to investigate whether the use of adjunctive app features is also associated with changes in mental health outcomes. Methods: We analyzed the intervention group during the stage 1 trial of the Unwinding Anxiety mobile app. The total use of specific mobile app features and the use specific to each feature were calculated. We used multivariate linear models with a priori significance of α=.05 to investigate the impact of cumulative app use on anxiety, worry, interoceptive awareness, and emotional regulation at 2 months, controlling for baseline scores, age, and education level in all models. Significant relationships between system use metrics and baseline participant characteristics were assessed for differences in use groupings using between-group testing (ie, 2-tailed t tests for continuous data and chi-square analyses for categorical data). Results: The sample was primarily female (25/27, 93%), and the average age was 42.9 (SD 15.6) years. Educational module completion, the central intervention component, averaged 20.2 (SD 11.4) modules out of 32 for the total sample. Multivariate models revealed that completing >75% of the program was associated with an average 22.6-point increase in interoceptive awareness (b=22.6; SE 8.32; P=.01; 95% CI 5.3-39.8) and an 11.6-point decrease in worry (b=−11.6; SE 4.12; P=.01; 95% CI −20.2 to −3.1). In addition, a single log unit change in the total number of meditations was associated with a 0.62-point reduction in the Generalized Anxiety Disorder-7 scale scores (b=0.62; SE 0.27; P=.005; 95% CI −1.2 to −0.6), whereas a single log unit use of the stress meter was associated with an average of a 0.5-point increase in emotional regulation scores (Five Facet Mindfulness Questionnaire; b=0.5; SE 0.21; P=.03; 95% CI 0.1-0.9). Conclusions: This study offers a clearer understanding of the impact of engagement with app features on broader engagement with the health outcomes of interest. This study highlights the importance of comprehensive investigations of engagement during the development of evidence-based mobile apps. %M 35969440 %R 10.2196/33696 %U https://www.jmir.org/2022/8/e33696 %U https://doi.org/10.2196/33696 %U http://www.ncbi.nlm.nih.gov/pubmed/35969440 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 8 %P e36620 %T Understanding Engagement in Digital Mental Health and Well-being Programs for Women in the Perinatal Period: Systematic Review Without Meta-analysis %A Davis,Jacqueline A %A Ohan,Jeneva L %A Gibson,Lisa Y %A Prescott,Susan L %A Finlay-Jones,Amy L %+ Telethon Kids Institute, 15 Hospital Avenue, Nedlands, 6009, Australia, 61 478173989, jackie.davis@telethonkids.org.au %K digital interventions %K perinatal %K mental health %K well-being %K logic model %K systematic review %K mobile phone %D 2022 %7 9.8.2022 %9 Review %J J Med Internet Res %G English %X Background: Pregnancy and the postnatal period can be a time of increased psychological distress, which can be detrimental to both the mother and the developing child. Digital interventions are cost-effective and accessible tools to support positive mental health in women during the perinatal period. Although studies report efficacy, a key concern regarding web-based interventions is the lack of engagement leading to drop out, lack of participation, or reduced potential intervention benefits. Objective: This systematic review aimed to understand the reporting and levels of engagement in studies of digital psychological mental health or well-being interventions administered during the perinatal period. Specific objectives were to understand how studies report engagement across 4 domains specified in the Connect, Attend, Participate, and Enact (CAPE) model, make recommendations on best practices to report engagement in digital mental health interventions (DMHIs), and understand levels of engagement in intervention studies in this area. To maximize the utility of this systematic review, we intended to develop practical tools for public health use: to develop a logic model to reference the theory of change, evaluate the studies using the CAPE framework, and develop a guide for future data collection to enable consistent reporting in digital interventions. Methods: This systematic review used the Cochrane Synthesis Without Meta-analysis reporting guidelines. This study aimed to identify studies reporting DMHIs delivered during the perinatal period in women with subclinical mood symptoms. A systematic database search was used to identify relevant papers using the Ovid Platform for MEDLINE, PsycINFO, EMBASE, Scopus, Web of Science, and Medical Subject Headings on Demand for all English-language articles published in the past 10 years. Results: Searches generated a database of 3473 potentially eligible studies, with a final selection of 16 (0.46%) studies grouped by study design. Participant engagement was evaluated using the CAPE framework and comparable variables were described. All studies reported at least one engagement metric. However, the measures used were inconsistent, which may have contributed to the wide-ranging results. There was insufficient reporting for enactment (ie, participants’ real-world use of intervention skills), with only 38% (6/16) of studies clearly recording longer-term practice through postintervention interviews. The logic model proposes ways of conceptualizing and reporting engagement details in DMHIs more consistently in the future. Conclusions: The perinatal period is the optimal time to intervene with strength-based digital tools to build positive mental health. Despite the growing number of studies on digital interventions, few robustly explore engagement, and there is limited evidence of long-term skill use beyond the intervention period. Our results indicate variability in the reporting of both short- and long-term participant engagement behaviors, and we recommend the adoption of standardized reporting metrics in future digital interventions. Trial Registration: PROSPERO CRD42020162283; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=162283 %M 35943773 %R 10.2196/36620 %U https://www.jmir.org/2022/8/e36620 %U https://doi.org/10.2196/36620 %U http://www.ncbi.nlm.nih.gov/pubmed/35943773 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 8 %P e37952 %T Digital Patient Experience: Umbrella Systematic Review %A Wang,Tingting %A Giunti,Guido %A Melles,Marijke %A Goossens,Richard %+ Industrial Design Engineering, Delft University of Technology, Gebouw 32, Landbergstraat 15, Delft, 2628 CE, Netherlands, 31 623018218, t.wang-8@tudelft.nl %K digital health %K eHealth %K telemedicine %K telehealth %K mobile health %K mHealth %K patient experience %K user experience %K influencing factors %K user-centered design %K human-computer interaction %D 2022 %7 4.8.2022 %9 Review %J J Med Internet Res %G English %X Background: The adoption and use of technology have significantly changed health care delivery. Patient experience has become a significant factor in the entire spectrum of patient-centered health care delivery. Digital health facilitates further improvement and empowerment of patient experiences. Therefore, the design of digital health is served by insights into the barriers to and facilitators of digital patient experience (PEx). Objective: This study aimed to systematically review the influencing factors and design considerations of PEx in digital health from the literature and generate design guidelines for further improvement of PEx in digital health. Methods: We performed an umbrella systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched Scopus, PubMed, and Web of Science databases. Two rounds of small random sampling (20%) were independently reviewed by 2 reviewers who evaluated the eligibility of the articles against the selection criteria. Two-round interrater reliability was assessed using the Fleiss-Cohen coefficient (k1=0.88 and k2=0.80). Thematic analysis was applied to analyze the extracted data based on a small set of a priori categories. Results: The search yielded 173 records, of which 45 (26%) were selected for data analysis. Findings and conclusions showed a great diversity; most studies presented a set of themes (19/45, 42%) or descriptive information only (16/45, 36%). The digital PEx–related influencing factors were classified into 9 categories: patient capability, patient opportunity, patient motivation, intervention technology, intervention functionality, intervention interaction design, organizational environment, physical environment, and social environment. These can have three types of impacts: positive, negative, or double edged. We captured 4 design constructs (personalization, information, navigation, and visualization) and 3 design methods (human-centered or user-centered design, co-design or participatory design, and inclusive design) as design considerations. Conclusions: We propose the following definition for digital PEx: “Digital patient experience is the sum of all interactions affected by a patient’s behavioral determinants, framed by digital technologies, and shaped by organizational culture, that influence patient perceptions across the continuum of care channeling digital health.” In this study, we constructed a design and evaluation framework that contains 4 phases—define design, define evaluation, design ideation, and design evaluation—and 9 design guidelines to help digital health designers and developers address digital PEx throughout the entire design process. Finally, our review suggests 6 directions for future digital PEx–related research. %M 35925651 %R 10.2196/37952 %U https://www.jmir.org/2022/8/e37952 %U https://doi.org/10.2196/37952 %U http://www.ncbi.nlm.nih.gov/pubmed/35925651 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 8 %P e35268 %T Just-in-Time Prompts for Running, Walking, and Performing Strength Exercises in the Built Environment: 4-Week Randomized Feasibility Study %A Sporrel,Karlijn %A Wang,Shihan %A Ettema,Dick D F %A Nibbeling,Nicky %A Krose,Ben J A %A Deutekom,Marije %A de Boer,Rémi D D %A Simons,Monique %+ Human Geography and Spatial Planning, Utrecht University, Princetonlaan 8a, Utrecht, 3584 CB, Netherlands, 31 642514287, k.sporrel@uu.nl %K just-in-time interventions %K context-based %K prompts %K reminders %K physical activity %K mobile health %K mHealth %K exercise application %K Fogg Behavior Model %K user experience %K engagement %K feasibility study %K mobile phone %D 2022 %7 1.8.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: App-based mobile health exercise interventions can motivate individuals to engage in more physical activity (PA). According to the Fogg Behavior Model, it is important that the individual receive prompts at the right time to be successfully persuaded into PA. These are referred to as just-in-time (JIT) interventions. The Playful Active Urban Living (PAUL) app is among the first to include 2 types of JIT prompts: JIT adaptive reminder messages to initiate a run or walk and JIT strength exercise prompts during a walk or run (containing location-based instruction videos). This paper reports on the feasibility of the PAUL app and its JIT prompts. Objective: The main objective of this study was to examine user experience, app engagement, and users’ perceptions and opinions regarding the PAUL app and its JIT prompts and to explore changes in the PA behavior, intrinsic motivation, and the perceived capability of the PA behavior of the participants. Methods: In total, 2 versions of the closed-beta version of the PAUL app were evaluated: a basic version (Basic PAUL) and a JIT adaptive version (Smart PAUL). Both apps send JIT exercise prompts, but the versions differ in that the Smart PAUL app sends JIT adaptive reminder messages to initiate running or walking behavior, whereas the Basic PAUL app sends reminder messages at randomized times. A total of 23 participants were randomized into 1 of the 2 intervention arms. PA behavior (accelerometer-measured), intrinsic motivation, and the perceived capability of PA behavior were measured before and after the intervention. After the intervention, participants were also asked to complete a questionnaire on user experience, and they were invited for an exit interview to assess user perceptions and opinions of the app in depth. Results: No differences in PA behavior were observed (Z=−1.433; P=.08), but intrinsic motivation for running and walking and for performing strength exercises significantly increased (Z=−3.342; P<.001 and Z=−1.821; P=.04, respectively). Furthermore, participants increased their perceived capability to perform strength exercises (Z=2.231; P=.01) but not to walk or run (Z=−1.221; P=.12). The interviews indicated that the participants were enthusiastic about the strength exercise prompts. These were perceived as personal, fun, and relevant to their health. The reminders were perceived as important initiators for PA, but participants from both app groups explained that the reminder messages were often not sent at times they could exercise. Although the participants were enthusiastic about the functionalities of the app, technical issues resulted in a low user experience. Conclusions: The preliminary findings suggest that the PAUL apps are promising and innovative interventions for promoting PA. Users perceived the strength exercise prompts as a valuable addition to exercise apps. However, to be a feasible intervention, the app must be more stable. %M 35916693 %R 10.2196/35268 %U https://formative.jmir.org/2022/8/e35268 %U https://doi.org/10.2196/35268 %U http://www.ncbi.nlm.nih.gov/pubmed/35916693 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 3 %P e38704 %T Digital Graphic Follow-up Tool (Rehabkompassen) for Identifying Rehabilitation Needs Among People After Stroke: Randomized Clinical Feasibility Study %A Hu,Xiaolei %A Jonzén,Karolina %A Lindahl,Olof A %A Karlsson,Marcus %A Norström,Fredrik %A Lundström,Erik %A Sunnerhagen,Katharina Stibrant %+ Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden, 46 705956708, xiaolei.hu@umu.se %K stroke %K rehabilitation %K needs assessment %K outcome assessment %K structured follow-up: follow-up %K digital tool %K digital health %K eHealth %K feasibility %K randomized controlled trial %K RCT %K adherence %K acceptability %K clinical setting %K Rankin scale %K outpatient %D 2022 %7 29.7.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Stroke is a leading cause of disability among adults, with heavy social and economic burden worldwide. A cost-effective solution is urgently needed to facilitate the identification of individual rehabilitation needs and thereby provide tailored rehabilitations to reduce disability among people who have had a stroke. A novel digital graphic follow-up tool Rehabkompassen has recently been developed to facilitate capturing the multidimensional rehabilitation needs of people who have had a stroke. Objective: The aim of this study was to evaluate the feasibility and acceptability of conducting a definitive trial to evaluate Rehabkompassen as a digital follow-up tool among people who have had a stroke in outpatient clinical settings. Methods: This pilot study of Rehabkompassen was a parallel, open-label, 2-arm prospective, proof-of-concept randomized controlled trial (RCT) with an allocation ratio of 1:1 in a single outpatient clinic. Patients who have had a stroke within the 3 previous months, aged ≥18 years, and living in the community were included. The trial compared usual outpatient visits with Rehabkompassen (intervention group) and without Rehabkompassen (control group) at the 3-month follow-up as well as usual outpatient visit with Rehabkompassen at the 12-month follow-up. Information on the recruitment rate, delivery, and uptake of Rehabkompassen; assessment and outcome measures completion rates; the frequency of withdrawals; the loss of follow-up; and satisfaction scores were obtained. The key outcomes were evaluated in both groups. Results: In total, 28 patients (14 control, 14 Rehabkompassen) participated in this study, with 100 patients screened. The overall recruitment rate was 28% (28/100). Retention in the trial was 86% (24/28) at the 12-month follow-up. All participants used the tool as planned during their follow-ups, which provided a 100% (24/24) task completion rate of using Rehabkompassen and suggested excellent feasibility. Both patient- and physician-participants reported satisfaction with the instrument (19/24, 79% and 2/2, 100%, respectively). In all, 2 (N=2, 100%) physicians and 18 (N=24, 75%) patients were willing to use the tool in the future. Furthermore, modified Rankin Scale as the primary outcome and various stroke impacts as secondary outcomes were both successfully collected and compared in this study. Conclusions: This study demonstrated the high feasibility and adherence of the study protocol as well as the high acceptability of Rehabkompassen among patients who have had a stroke and physicians in an outpatient setting in comparison to the predefined criterion. The information collected in this feasibility study combined with the amendments of the study protocol may improve the future definitive RCT. The results of this trial support the feasibility and acceptability of conducting a large definitive RCT. Trial Registration: ClinicalTrials.gov NCT04915027; https://clinicaltrials.gov/ct2/show/NCT04915027 %M 35904867 %R 10.2196/38704 %U https://humanfactors.jmir.org/2022/3/e38704 %U https://doi.org/10.2196/38704 %U http://www.ncbi.nlm.nih.gov/pubmed/35904867 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 7 %P e37169 %T Changes in Resilience Following Engagement With a Virtual Mental Health System: Real-world Observational Study %A Graziani,Grant %A Aylward,Brandon S %A Kunkle,Sarah %A Shih,Emily %+ Ginger, 116 New Montgomery St. Suite 500, San Francisco, CA, 94105, United States, 1 855 446 4374, ggraziani@ginger.io %K behavioral coaching %K psychological resilience %K mental health %K telehealth %D 2022 %7 29.7.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Digital health services can serve as scalable solutions to address the growing demand for mental health care. However, more research is needed to better understand the association between engagement with care and improvements in subclinical outcomes. Objective: This study aims to fill this research gap by examining the relationship between members’ engagement with the Ginger platform and changes in their psychological resilience. Methods: We conducted a retrospective observational study of 3272 members who accessed Ginger, an on-demand mental health service, between January 2021 and November 2021. Each member completed the 10-item Connor-Davidson Resilience Scale questionnaire, a measure of psychological resilience, at baseline and again during a 6- to 16-week follow-up window. Depression and anxiety symptoms (9-item Patient Health Questionnaire and 7-item Generalized Anxiety Disorder) were also measured. Linear regression was used to identify the association between engagement with Ginger’s multiple care modalities and changes in resilience. Moderator analysis was conducted to test whether clinical depression or anxiety at baseline moderated the relationship between engagement level and changes in resilience. Results: Of the 3272 members, 2683 (82%) reported low resilience at baseline. The mean change in resilience was 0.77 (SD 5.50) points. Linear regression models showed that age and census region did not predict changes in resilience; however, male members showed larger improvements (coefficient=0.58; P=.04). Baseline mental health outcomes, including resilience and depression and anxiety symptoms, were strong predictors of changes in resilience. Every point decrease in baseline resilience is associated with a 0.28-point increase in change in resilience (P<.001), and members with no or mild depression and anxiety at baseline saw changes in resilience that were 1.44 points (P<.001) larger than their clinical counterparts. Engagement with the Ginger system predicted changes in resilience. Members who engaged with Ginger coaching, clinical services, or both improved their resilience by 1.82, 1.55, and 1.40 points, respectively (P<.001), more than those who only engaged with Ginger content. Screening negative for moderate to severe depression and anxiety at baseline was associated with larger improvements in resilience (coefficient=1.30; P<.001); however, subclinical status was not shown to be a moderator for the association between level of engagement and changes in resilience. Conclusions: Engagement with Ginger services was associated with improvements in resilience. Members who engaged in coaching or clinical care had significantly larger improvements compared with those who only engaged in self-guided content, regardless of whether a member screened positive for clinical depression or anxiety at baseline. %M 35904875 %R 10.2196/37169 %U https://formative.jmir.org/2022/7/e37169 %U https://doi.org/10.2196/37169 %U http://www.ncbi.nlm.nih.gov/pubmed/35904875 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 7 %P e38068 %T Predicting Participant Engagement in a Social Media–Delivered Lifestyle Intervention Using Microlevel Conversational Data: Secondary Analysis of Data From a Pilot Randomized Controlled Trial %A Xu,Ran %A Divito,Joseph %A Bannor,Richard %A Schroeder,Matthew %A Pagoto,Sherry %+ Department of Allied Health Sciences, Institute for Collaboration in Health, Interventions, and Policy, University of Connecticut, Koons Hall, Room 326, Storrs, CT, 06269, United States, 1 860 486 2945, ran.2.xu@uconn.edu %K weight loss %K social media intervention %K engagement %K data science %K natural language processing %K NLP %K social media %K lifestyle %K machine learning %K mobile phone %D 2022 %7 28.7.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Social media–delivered lifestyle interventions have shown promising outcomes, often generating modest but significant weight loss. Participant engagement appears to be an important predictor of weight loss outcomes; however, engagement generally declines over time and is highly variable both within and across studies. Research on factors that influence participant engagement remains scant in the context of social media–delivered lifestyle interventions. Objective: This study aimed to identify predictors of participant engagement from the content generated during a social media–delivered lifestyle intervention, including characteristics of the posts, the conversation that followed the post, and participants’ previous engagement patterns. Methods: We performed secondary analyses using data from a pilot randomized trial that delivered 2 lifestyle interventions via Facebook. We analyzed 80 participants’ engagement data over a 16-week intervention period and linked them to predictors, including characteristics of the posts, conversations that followed the post, and participants’ previous engagement, using a mixed-effects model. We also performed machine learning–based classification to confirm the importance of the significant predictors previously identified and explore how well these measures can predict whether participants will engage with a specific post. Results: The probability of participants’ engagement with each post decreased by 0.28% each week (P<.001; 95% CI 0.16%-0.4%). The probability of participants engaging with posts generated by interventionists was 6.3% (P<.001; 95% CI 5.1%-7.5%) higher than posts generated by other participants. Participants also had a 6.5% (P<.001; 95% CI 4.9%-8.1%) and 6.1% (P<.001; 95% CI 4.1%-8.1%) higher probability of engaging with posts that directly mentioned weight and goals, respectively, than other types of posts. Participants were 44.8% (P<.001; 95% CI 42.8%-46.9%) and 46% (P<.001; 95% CI 44.1%-48.0%) more likely to engage with a post when they were replied to by other participants and by interventionists, respectively. A 1 SD decrease in the sentiment of the conversation on a specific post was associated with a 5.4% (P<.001; 95% CI 4.9%-5.9%) increase in the probability of participants’ subsequent engagement with the post. Participants’ engagement in previous posts was also a predictor of engagement in subsequent posts (P<.001; 95% CI 0.74%-0.79%). Moreover, using a machine learning approach, we confirmed the importance of the predictors previously identified and achieved an accuracy of 90.9% in terms of predicting participants’ engagement using a balanced testing sample with 1600 observations. Conclusions: Findings revealed several predictors of engagement derived from the content generated by interventionists and other participants. Results have implications for increasing engagement in asynchronous, remotely delivered lifestyle interventions, which could improve outcomes. Our results also point to the potential of data science and natural language processing to analyze microlevel conversational data and identify factors influencing participant engagement. Future studies should validate these results in larger trials. Trial Registration: ClinicalTrials.gov NCT02656680; https://clinicaltrials.gov/ct2/show/NCT02656680 %M 35900824 %R 10.2196/38068 %U https://formative.jmir.org/2022/7/e38068 %U https://doi.org/10.2196/38068 %U http://www.ncbi.nlm.nih.gov/pubmed/35900824 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 5 %N 3 %P e36770 %T Dose-Response Relationship of a Blended In-Person and Online Family-Based Childhood Obesity Management Program: Secondary Analysis of a Behavior Intervention %A Liu,Sam %A Smith,Nicholas %A Nuss,Kayla %A Perdew,Megan %A Adiputranto,Dimas %A Naylor,Patti-Jean %+ School of Exercise Science, Physical and Health Education, University of Victoria, PO Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada, 1 2507218392, samliu@uvic.ca %K engagement %K dose response %K childhood obesity %K web-based intervention %K child %K obesity %K weight %K web based %K intervention %K family %K families %K lifestyle %K parent %K parental support %K healthy eating %K family support %K physical activity %K diet %K exercise %K fitness %K online portal %D 2022 %7 5.7.2022 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: The Early Intervention Program (EIP) was a 10-week, blended, in-person and online lifestyle intervention for families with children who were off the healthy weight trajectory. The engagement pattern and the dose response of EIP have not been examined. Objective: The aims of this paper are to examine families’ engagement patterns with the EIP and to evaluate the dose-response relationship between EIP engagement patterns and physical activity and healthy eating–related outcomes at 10 weeks. Methods: Families with children (8-12 years old) who are off the healthy weight trajectory (child BMI ≥85th percentile for age and sex) were recruited. Pre- and postintervention questionnaires assessed child lifestyle behaviors, parental support behaviors, family lifestyle habits, as well as parental physical activity and healthy-eating identity. Hierarchical cluster analysis of both in-person and online components was used to classify engagement patterns. Regression analysis assessed differences in outcomes by engagement groups. Results: Two distinct clusters of engagement groups were identified (N=66), which were in-person (IP; n=40, 61%) and in-person + online (IP+; n=26, 39%) engagement. Relative to the IP group at week 10, IP+ showed a greater child moderate-to-vigorous physical activity level (1.53, SD 0.56; P=.008), child physical activity confidence (1.04, SD 0.37; P=.007), parental support for child physical activity (5.54, SD 2.57; P=.04) and healthy eating (2.43, SD 1.16; P=.04), family habits for physical activity (3.02, SD 1.50; P=.049) and healthy eating (3.95, SD 1.84; P=.04), and parental identity for physical activity (2.82, SD 1.19; P=.02). Conclusions: The online EIP portal complemented the in-person sessions. Additional engagement with the portal was associated with greater improvements in child physical activity and parental support behaviors, habits, and identity for physical activity. %M 35787514 %R 10.2196/36770 %U https://pediatrics.jmir.org/2022/3/e36770 %U https://doi.org/10.2196/36770 %U http://www.ncbi.nlm.nih.gov/pubmed/35787514 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 3 %P e29725 %T Bridging the Digital Divide in Psychological Therapies: Observational Study of Engagement With the SlowMo Mobile App for Paranoia in Psychosis %A Hardy,Amy %A Ward,Thomas %A Emsley,Richard %A Greenwood,Kathryn %A Freeman,Daniel %A Fowler,David %A Kuipers,Elizabeth %A Bebbington,Paul %A Garety,Philippa %+ Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Henry Wellcome Building, London, SE5 8AF, United Kingdom, 44 2078485178, amy.hardy@kcl.ac.uk %K paranoia %K psychosis %K digital health %K apps %K human-centered design %K user experience %K adherence %K engagement %K therapy %D 2022 %7 1.7.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Marginalized groups are more likely to experience problems with technology-related access, motivation, and skills. This is known as the “digital divide.” Technology-related exclusion is a potential barrier to the equitable implementation of digital health. SlowMo therapy was developed with an inclusive, human-centered design to optimize accessibility and bridge the “digital divide.” SlowMo is an effective, blended digital psychological therapy for paranoia in psychosis. Objective: This study explores the “digital divide” and mobile app engagement in the SlowMo randomized controlled trial. Methods: Digital literacy was assessed at baseline, and a multidimensional assessment of engagement (ie, adherence [via system analytics and self-report] and self-reported user experience) was conducted at 12 weeks after therapy. Engagement was investigated in relation to demographics (ie, gender, age, ethnicity, and paranoia severity). Results: Digital literacy data demonstrated that technology use and confidence were lower in Black people and older people (n=168). The engagement findings indicated that 80.7% (96/119) of therapy completers met the a priori analytics adherence criteria. However, analytics adherence did not differ by demographics. High rates of user experience were reported overall (overall score: mean 75%, SD 17.1%; n=82). No differences in user experience were found for ethnicity, age, or paranoia severity, although self-reported app use, enjoyment, and usefulness were higher in women than in men. Conclusions: This study identified technology-related inequalities related to age and ethnicity, which did not influence engagement with SlowMo, suggesting that the therapy design bridged the “digital divide.” Intervention design may moderate the influence of individual differences on engagement. We recommend the adoption of inclusive, human-centered design to reduce the impact of the “digital divide” on therapy outcomes. Trial Registration: ISRCTN Registry ISRCTN32448671; https://www.isrctn.com/ISRCTN32448671 %M 35776506 %R 10.2196/29725 %U https://humanfactors.jmir.org/2022/3/e29725 %U https://doi.org/10.2196/29725 %U http://www.ncbi.nlm.nih.gov/pubmed/35776506 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 3 %P e34925 %T The Influencing Contexts and Potential Mechanisms Behind the Use of Web-Based Self-management Support Interventions: Realistic Evaluation %A Engelen,Marscha %A van Gaal,Betsie %A Vermeulen,Hester %A Zuidema,Rixt %A Bredie,Sebastian %A van Dulmen,Sandra %+ IQ Healthcare, Radboud Institute for Health Sciences, Radboud university medical center, P O Box 9101, Nijmegen, 6500 HB, Netherlands, 31 630261845, marscha.engelen@radboudumc.nl %K self-management %K telemedicine %K chronic disease %K cardiovascular diseases %K rheumatoid arthritis %K patient dropouts %K realistic evaluation %K program use %D 2022 %7 1.7.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Self-management can increase self-efficacy and quality of life and improve disease outcomes. Effective self-management may also help reduce the pressure on health care systems. However, patients need support in dealing with their disease and in developing skills to manage the consequences and changes associated with their condition. Web-based self-management support programs have helped patients with cardiovascular disease (CVD) and rheumatoid arthritis (RA), but program use has been low. Objective: This study aimed to identify the patient, disease, and program characteristics that determine whether patients use web-based self-management support programs or not. Methods: A realistic evaluation methodology was used to provide a comprehensive overview of context (patient and disease characteristics), mechanism (program characteristics), and outcome (program use). Secondary data of adult patients with CVD (n=101) and those with RA (n=77) were included in the study. The relationship between context (sex, age, education, employment status, living situation, self-management [measured using Patient Activation Measure-13], quality of life [measured using RAND 36-item health survey], interaction efficacy [measured using the 5-item perceived efficacy in patient-physician interactions], diagnosis, physical comorbidity, and time since diagnosis) and outcome (program use) was analyzed using logistic regression analyses. The relationship between mechanism (program design, implementation strategies, and behavior change techniques [BCTs]) and outcome was analyzed through a qualitative interview study. Results: This study included 68 nonusers and 111 users of web-based self-management support programs, of which 56.4% (101/179) were diagnosed with CVD and 43.6% (78/179) with RA. Younger age and a lower level of education were associated with program use. An interaction effect was found between program use and diagnosis and 4 quality of life subscales (social functioning, physical role limitations, vitality, and bodily pain). Patients with CVD with higher self-management and quality of life scores were less likely to use the program, whereas patients with RA with higher self-management and quality of life scores were more likely to use the program. Interviews with 10 nonusers, 10 low users, and 18 high users were analyzed to provide insight into the relationship between mechanisms and outcome. Program use was encouraged by an easy-to-use, clear, and transparent design and by recommendations from professionals and email reminders. A total of 5 BCTs were identified as potential mechanisms to promote program use: tailored information, self-reporting behavior, delayed feedback, providing information on peer behavior, and modeling. Conclusions: This realistic evaluation showed that certain patient, disease, and program characteristics (age, education, diagnosis, program design, type of reminder, and BCTs) are associated with the use of web-based self-management support programs. These results represent the first step in improving the tailoring of web-based self-management support programs. Future research on the interaction between patient and program characteristics should be conducted to improve the tailoring of participants to program components. %M 35776437 %R 10.2196/34925 %U https://humanfactors.jmir.org/2022/3/e34925 %U https://doi.org/10.2196/34925 %U http://www.ncbi.nlm.nih.gov/pubmed/35776437 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 8 %N 6 %P e33867 %T Correlates of Engagement Within an Online HIV Prevention Intervention for Single Young Men Who Have Sex With Men: Randomized Controlled Trial %A Choi,Seul Ki %A Golinkoff,Jesse %A Michna,Mark %A Connochie,Daniel %A Bauermeister,José %+ Department of Family and Community Health, School of Nursing, University of Pennsylvania, 418 Curie Blvd, Philadelphia, PA, 19104, United States, 1 2155734734, skchoi@nursing.upenn.edu %K paradata %K mobile health %K mHealth %K digital health intervention %K risk reduction %K HIV prevention %K public health %K digital health %K sexual health %K sexual risks %D 2022 %7 27.6.2022 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Digital HIV interventions (DHI) have been efficacious in reducing sexual risk behaviors among sexual minority populations, yet challenges in promoting and sustaining users’ engagement in DHI persist. Understanding the correlates of DHI engagement and their impact on HIV-related outcomes remains a priority. This study used data from a DHI (myDEx) designed to promote HIV prevention behaviors among single young men who have sex with men (YMSM; ages 18-24 years) seeking partners online. Objective: The goal of this study is to conduct a secondary analysis of the myDex project data to examine whether YMSM’s online behaviors (eg, online partner-seeking behaviors and motivations) are linked to participants’ engagement (ie, the number of log-ins and the number of sessions viewed). Methods: We recruited 180 YMSM who were randomized into either myDEx arm or attention-control arm using a stratified 2:1 block randomization. In the myDEx arm, we had 120 YMSM who had access to the 6-session intervention content over a 3-month period. We used Poisson regressions to assess the association between YMSM’s baseline characteristics on their DHI engagement. We then examined the association between the participants’ engagement and their self-reported changes in HIV-related outcomes at the 3-month follow-up. Results: The mean number of log-ins was 5.44 (range 2-14), and the number of sessions viewed was 6.93 (range 0-22) across the 3-month trial period. In multivariable models, the number of log-ins was positively associated with high education attainment (estimated Poisson regression coefficient [β]=.22; P=.045). The number of sessions viewed was associated with several baseline characteristics, including the greater number of sessions viewed among non-Hispanic YMSM (β=.27; P=.002), higher education attainment (β=.22; P=.003), higher perceived usefulness of online dating for hookups (β=.13; P=.002) and perceived loneliness (β=.06; P=.004), as well as lower experienced online discrimination (β=–.01; P=.007) and limerence (β=–.02; P=.004). The number of sessions viewed was negatively associated with changes in internalized homophobia (β=–.06; P<.001) and with changes in perceived usefulness of online dating for hookups (β=–.20; P<.001). There were no significant associations between the number of log-ins and changes in the participants’ behaviors at the 90-day follow-up. Conclusions: DHI engagement is linked to participants’ sociodemographic and online behaviors. Given the importance of intervention engagement in the intervention’s effectiveness, DHIs with personalized intervention components that consider the individuals’ differences could increase the overall engagement and efficacy of DHIs. Trial Registration: ClinicalTrials.gov NCT02842060; https://clinicaltrials.gov/ct2/show/NCT02842060. %M 35759333 %R 10.2196/33867 %U https://publichealth.jmir.org/2022/6/e33867 %U https://doi.org/10.2196/33867 %U http://www.ncbi.nlm.nih.gov/pubmed/35759333 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 6 %P e35285 %T The Aim2Be mHealth Intervention for Children With Overweight or Obesity and Their Parents: Person-Centered Analyses to Uncover Digital Phenotypes %A De-Jongh González,Olivia %A Tugault-Lafleur,Claire N %A Buckler,E Jean %A Hamilton,Jill %A Ho,Josephine %A Buchholz,Annick %A Morrison,Katherine M %A Ball,Geoff DC %A Mâsse,Louise C %+ School of Population and Public Health, University of British Columbia, BC Children's Hospital Research Institute, 4480 Oak St., Vancouver, BC, V6H 3V4, Canada, 1 6048752000 ext 5563, lmasse@bcchr.ubc.ca %K mobile health %K mHealth %K childhood obesity %K digital phenotypes %K latent class analysis %D 2022 %7 22.6.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite the growing number of mobile health (mHealth) interventions targeting childhood obesity, few studies have characterized user typologies derived from individuals’ patterns of interactions with specific app features (digital phenotypes). Objective: This study aims to identify digital phenotypes among 214 parent-child dyads who used the Aim2Be mHealth app as part of a randomized controlled trial conducted between 2019 and 2020, and explores whether participants’ characteristics and health outcomes differed across phenotypes. Methods: Latent class analysis was used to identify distinct parent and child phenotypes based on their use of the app’s behavioral, gamified, and social features over 3 months. Multinomial logistic regression models were used to assess whether the phenotypes differed by demographic characteristics. Covariate-adjusted mixed-effect models evaluated changes in BMI z scores (zBMI), diet, physical activity, and screen time across phenotypes. Results: Among parents, 5 digital phenotypes were identified: socially engaged (35/214, 16.3%), independently engaged (18/214, 8.4%) (socially and independently engaged parents are those who used mainly the social or the behavioral features of the app, respectively), fully engaged (26/214, 12.1%), partially engaged (32/214, 15%), and unengaged (103/214, 48.1%) users. Married parents were more likely to be fully engaged than independently engaged (P=.02) or unengaged (P=.01) users. Socially engaged parents were older than fully engaged (P=.02) and unengaged (P=.01) parents. The latent class analysis revealed 4 phenotypes among children: fully engaged (32/214, 15%), partially engaged (61/214, 28.5%), dabblers (42/214, 19.6%), and unengaged (79/214, 36.9%) users. Fully engaged children were younger than dabblers (P=.04) and unengaged (P=.003) children. Dabblers lived in higher-income households than fully and partially engaged children (P=.03 and P=.047, respectively). Fully engaged children were more likely to have fully engaged (P<.001) and partially engaged (P<.001) parents than unengaged children. Compared with unengaged children, fully and partially engaged children had decreased total sugar (P=.006 and P=.004, respectively) and energy intake (P=.03 and P=.04, respectively) after 3 months of app use. Partially engaged children also had decreased sugary beverage intake compared with unengaged children (P=.03). Similarly, children with fully engaged parents had decreased zBMI, whereas children with unengaged parents had increased zBMI over time (P=.005). Finally, children with independently engaged parents had decreased caloric intake, whereas children with unengaged parents had increased caloric intake over time (P=.02). Conclusions: Full parent-child engagement is critical for the success of mHealth interventions. Further research is needed to understand program design elements that can affect participants’ engagement in supporting behavior change. Trial Registration: ClinicalTrials.gov NCT03651284; https://clinicaltrials.gov/ct2/show/NCT03651284 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-020-4080-2 %M 35731547 %R 10.2196/35285 %U https://www.jmir.org/2022/6/e35285 %U https://doi.org/10.2196/35285 %U http://www.ncbi.nlm.nih.gov/pubmed/35731547 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e35342 %T Developing mHealth to the Context and Valuation of Injured Patients and Professionals in Hospital Trauma Care: Qualitative and Quantitative Formative Evaluations %A Houwen,Thymen %A Vugts,Miel A P %A Lansink,Koen W W %A Theeuwes,Hilco P %A Neequaye,Nicky %A Beerekamp,M Susan H %A Joosen,Margot C W %A de Jongh,Mariska A C %+ Network Emergency Care Brabant, Elisabeth-TweeSteden Ziekenhuis, Hilvarenbeekseweg 60, Tilburg, 5022 GC, Netherlands, 31 132212103, t.houwen@etz.nl %K wounds and injuries %K telemedicine %K recovery of function %K rehabilitation %K patient care management %K qualitative research %K evaluation study %K holistic health %D 2022 %7 20.6.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Trauma care faces challenges to innovating their services, such as with mobile health (mHealth) app, to improve the quality of care and patients’ health experience. Systematic needs inquiries and collaborations with professional and patient end users are highly recommended to develop and prepare future implementations of such innovations. Objective: This study aimed to develop a trauma mHealth app for patient information and support in accordance with the Center for eHealth Research and Disease Management road map and describe experiences of unmet information and support needs among injured patients with trauma, barriers to and facilitators of the provision of information and support among trauma care professionals, and drivers of value of an mHealth app in patients with trauma and trauma care professionals. Methods: Formative evaluations were conducted using quantitative and qualitative methods. Ten semistructured interviews with patients with trauma and a focus group with 4 trauma care professionals were conducted for contextual inquiry and value specification. User requirements and value drivers were applied in prototyping. Furthermore, a complementary quantitative discrete choice experiment (DCE) was conducted with 109 Dutch trauma surgeons, which enabled triangulation on value specification results. In the DCE, preferences were stated for hypothetical mHealth products with various attributes. Panel data from the DCE were analyzed using conditional and mixed logit models. Results: Patients disclosed a need for more psychosocial support and easy access to more extensive information on their injury, its consequences, and future prospects. Health care professionals designated workload as an essential issue; a digital solution should not require additional time. The conditional logit model of DCE results suggested that access to patient app data through electronic medical record integration (odds ratio [OR] 3.3, 95% CI 2.55-4.34; P<.001) or a web viewer (OR 2.3, 95% CI 1.64-3.31; P<.001) was considered the most important for an mHealth solution by surgeons, followed by the inclusion of periodic self-measurements (OR 2, 95% CI 1.64-2.46; P<.001), the local adjustment of patient information (OR 1.8, 95% CI 1.42-2.33; P<.001), local hospital identification (OR 1.7, 95% CI 1.31-2.10; P<.001), complication detection (OR 1.5, 95% CI 1.21-1.84; P<.001), and the personalization of rehabilitation through artificial intelligence (OR 1.4, 95% CI 1.13-1.62; P=.001). Conclusions: In the context of trauma care, end users have many requirements for an mHealth solution that addresses psychosocial functioning; dependable information; and, possibly, a prediction of how a patient’s recovery trajectory is evolving. A structured development approach provided insights into value drivers and facilitated mHealth prototype enhancement. The findings imply that iterative development should move on from simple and easily implementable mHealth solutions to those that are suitable for broader innovations of care pathways that most—but plausibly not yet all—end users in trauma care will value. This study could inspire the trauma care community. %M 35723928 %R 10.2196/35342 %U https://humanfactors.jmir.org/2022/2/e35342 %U https://doi.org/10.2196/35342 %U http://www.ncbi.nlm.nih.gov/pubmed/35723928 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e33972 %T Features and Components Preferred by Adolescents in Smartphone Apps for the Promotion of Physical Activity: Focus Group Study %A Domin,Alex %A Ouzzahra,Yacine %A Vögele,Claus %+ Research Group for Self-Regulation and Health, Department of Behavioural and Cognitive Sciences, University of Luxembourg, Maison des Sciences Humaines, 11, Porte des Sciences, Esch-sur-Alzette, L-4366, Luxembourg, 352 46 66 44 9389, alex.domin@uni.lu %K mHealth %K physical activity %K mobile phone %K health %K qualitative research %K focus groups %K smartphone apps %K behavior change %K mobile health %K adolescents %D 2022 %7 9.6.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: There is solid evidence that lack of physical activity (PA) is a risk factor for chronic diseases. Sufficient levels of PA in childhood and adolescence are particularly important, as they can set the standards for PA levels in adulthood. The latest reports show that only a small percentage of adolescents reach the recommended levels of PA in European Union countries at the age of 15 years. In view of the scale of the problem, it is crucial to develop interventions that promote and support PA in adolescents. Considering their low implementation costs and ubiquitous presence, smartphone apps could be advantageous as a part of PA interventions. Objective: This study aimed at investigating the attitudes and preferences of adolescents aged 16-18 years toward various PA app features and components that could (1) make the app more attractive for them and consequently (2) increase their interest and engagement with the app. Methods: Two separate focus group discussions were conducted in 2 groups of adolescents (n=4 each) aged 16-18 years. Focus groups were carried out online via video conference. The discussions were conducted using a semistructured interview. Participants (n=8; 4 males and 4 females) had a mean age of 17.25 years (SD 0.82 years). Transcripts were analyzed following the approach by Krueger and Casey, that is, categorizing participants’ answers and comments according to the questions and themes from the focus group schedule. Results: Features, such as “goal setting and planning,” “coaching and training programs,” “activity tracking,” “feedback,” and “location tracking” were appraised as attractive, motivating, and interesting. An “automatic activity recognition” feature was perceived as useful only under the condition that its precision was high. The “reminders” component was also deemed as useful only if a range of conditions was fulfilled (timeliness, opportunity for customization, etc). The features “mood and sleep tracking,” “sharing workout results via social networks,” “digital avatar and coach,” and “rewards” were generally perceived negatively and considered as useless and not motivating. In general, participants preferred features with an easy-to-navigate interface and a clear, simplistic, and straightforward layout with a modern design. Customization and personalization qualities were highly appreciated throughout an app, together with data precision. Conclusions: This study contributes to the understanding of the features and components preferred by adolescents in apps promoting PA. Such apps should provide users with precise data, and have a simplistic modern design and a straightforward easy-to-use interface. Apps should be personalized and customizable. Desired features to be included in an app are goal setting and planning, feedback, coaching and training programs, and activity tracking. The features should involve high levels of data precision and timely delivery while taking into consideration the real-life context. %M 35679113 %R 10.2196/33972 %U https://humanfactors.jmir.org/2022/2/e33972 %U https://doi.org/10.2196/33972 %U http://www.ncbi.nlm.nih.gov/pubmed/35679113 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 7 %N 2 %P e23641 %T Technological Proficiencies, Engagement, and Practical Considerations for mHealth Programs at an Urban Safety-Net Hospital Emergency Departments: Data Analysis %A Treacy-Abarca,Sean %A Mercado,Janisse %A Serrano,Jorge %A Gonzalez,Jennifer %A Menchine,Michael %A Arora,Sanjay %A Wu,Shinyi %A Burner,Elizabeth %+ David Geffen School of Medicine, University of California Los Angeles, 10833 Le Conte Ave, Los Angeles, CA, 90095, United States, 1 3108256373, sean.e.treacy@gmail.com %K mHealth %K engagement %K practical considerations %K safety-net hospital %K emergency department %K minority health %K low income %D 2022 %7 6.6.2022 %9 Original Paper %J JMIR Diabetes %G English %X Background: Safety-net emergency departments often serve as the primary entry point for medical care for low income predominantly minority patient populations. Herein, we sought to provide insight into the feasibility, technological proficiencies, engagement characteristics, and practical considerations for a mHealth intervention at a safety-net emergency department. Objective: We aimed to analyze patient technological proficiency to understand the feasibility of and draw practical considerations for mobile phone technology (mHealth) solutions for patients with chronic disease served by safety-net emergency departments. Methods: We analyzed data from a previous diabetes randomized clinical mHealth trial for a diabetes social support intervention. Patients from a safety-net emergency department with preexisting diabetes who used SMS text messages, owned a mobile phone, and with hemoglobin A1c levels >8.5% were enrolled. A text message–based mHealth program to improve disease self-management was provided to all patients. Supporters of patients were randomized to receive a mailed copy or mHealth-based curriculum designed to improve diabetes support. Among enrolled patients, we surveyed mobile technological capacity and frequency of use. We performed latent class analysis to identify classes of patients by level of technological proficiency and compared demographic characteristics between the latent classes to identify demographic subgroups that may require more training or tailoring of the mHealth approach. Study engagement between classes was assessed by comparing the mean number of text messages exchanged, loss to follow-up, and early termination. Results: Of 1876 patients who were approached, 44.2% (n=829) of patients had a stable mobile phone and were able to use text messages. Among them 166 met the trial inclusion and enrolled, 90% (149/166) of the cohort were ethnically diverse. Significant variance was found in technology capacity and frequency of use. Our latent class analysis classified 75% (124/166) of patients as highly technologically proficient and 25% (42/166) patients as minimally technologically proficient. Age (P<.001) and level of education (P<.001) were associated with class membership. Highly technologically proficient patients were younger and had higher levels of education (45.74 years old; high school or more: 90%) than minimally technologically proficient patients (53.64 years old; high school or more: 18%). Highly technologically proficient participants exchanged a mean of 40 text messages with the system coordinators compared to a mean of 10 text messages by minimally technologically proficient patients (P<.001). Conclusions: This study found that nearly half of the patients screened at the safety-net emergency department were equipped for an SMS text message–based mHealth intervention. In the small sample of patients who were enrolled, the majority were classified as highly technologically proficient. These highly proficient patients had greater study engagement. mHealth use in emergency departments may be an opportunity to improve health of ethnically diverse populations by pairing sophisticated chronic disease self-management program with SMS text message–based and traditional in-person interventions to reach patients through the method that is most familiar and comfortable. International Registered Report Identifier (IRRID): RR2-10.1016/j.cct.2019.03.003 %M 35666555 %R 10.2196/23641 %U https://diabetes.jmir.org/2022/2/e23641 %U https://doi.org/10.2196/23641 %U http://www.ncbi.nlm.nih.gov/pubmed/35666555 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 6 %P e30712 %T Understanding the Relationship Between Mood Symptoms and Mobile App Engagement Among Patients With Breast Cancer Using Machine Learning: Case Study %A Baglione,Anna N %A Cai,Lihua %A Bahrini,Aram %A Posey,Isabella %A Boukhechba,Mehdi %A Chow,Philip I %+ Department of Engineering Systems and Environment, University of Virginia, Olsson Hall, 151 Engineer's Way, Charlottesville, VA, 22904, United States, 1 434 264 7484, ab5bt@virginia.edu %K breast cancer %K digital intervention %K mobile intervention %K mobile health %K mHealth %K app engagement %K user engagement %K mental health %K depression %K anxiety %D 2022 %7 2.6.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Health interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success; however, the relationship between mood and engagement among patients with cancer remains poorly understood. A reason for this is the lack of a data-driven process for analyzing mood and app engagement data for patients with cancer. Objective: This study aimed to provide a step-by-step process for using app engagement metrics to predict continuously assessed mood outcomes in patients with breast cancer. Methods: We described the steps involved in data preprocessing, feature extraction, and data modeling and prediction. We applied this process as a case study to data collected from patients with breast cancer who engaged with a mobile mental health app intervention (IntelliCare) over 7 weeks. We compared engagement patterns over time (eg, frequency and days of use) between participants with high and low anxiety and between participants with high and low depression. We then used a linear mixed model to identify significant effects and evaluate the performance of the random forest and XGBoost classifiers in predicting weekly mood from baseline affect and engagement features. Results: We observed differences in engagement patterns between the participants with high and low levels of anxiety and depression. The linear mixed model results varied by the feature set; these results revealed weak effects for several features of engagement, including duration-based metrics and frequency. The accuracy of predicting depressed mood varied according to the feature set and classifier. The feature set containing survey features and overall app engagement features achieved the best performance (accuracy: 84.6%; precision: 82.5%; recall: 64.4%; F1 score: 67.8%) when used with a random forest classifier. Conclusions: The results from the case study support the feasibility and potential of our analytic process for understanding the relationship between app engagement and mood outcomes in patients with breast cancer. The ability to leverage both self-report and engagement features to analyze and predict mood during an intervention could be used to enhance decision-making for researchers and clinicians and assist in developing more personalized interventions for patients with breast cancer. %M 35653183 %R 10.2196/30712 %U https://medinform.jmir.org/2022/6/e30712 %U https://doi.org/10.2196/30712 %U http://www.ncbi.nlm.nih.gov/pubmed/35653183 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 5 %P e35371 %T Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review %A Jakob,Robert %A Harperink,Samira %A Rudolf,Aaron Maria %A Fleisch,Elgar %A Haug,Severin %A Mair,Jacqueline Louise %A Salamanca-Sanabria,Alicia %A Kowatsch,Tobias %+ Centre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zurich, Professur Informationsmanagement, WEV G 217, Weinbergstr. 56/58, Zurich, 8092, Switzerland, 41 44 632 53 57, rjakob@ethz.ch %K intended use %K adherence %K engagement %K attrition %K retention %K mHealth %K eHealth %K digital health intervention %K noncommunicable disease %K NCD %K mobile phone %D 2022 %7 25.5.2022 %9 Review %J J Med Internet Res %G English %X Background: Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions. Objective: This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks. Methods: A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings. Results: The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%). Conclusions: This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data. %M 35612886 %R 10.2196/35371 %U https://www.jmir.org/2022/5/e35371 %U https://doi.org/10.2196/35371 %U http://www.ncbi.nlm.nih.gov/pubmed/35612886 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 5 %P e37302 %T Adherence and Engagement With a Cognitive Behavioral Therapy–Based Conversational Agent (Wysa for Chronic Pain) Among Adults With Chronic Pain: Survival Analysis %A Sinha,Chaitali %A Cheng,Abby L %A Kadaba,Madhura %+ Wysa, 131 Dartmouth St, Boston, MA, 02116, United States, 1 7819219969, chaitali@wysa.io %K retention %K engagement %K Wysa %K chronic pain %K digital health %K digital application %K app %K mental health %K digital intervention %K health intervention %K symptom management %K user engagement %K conversational agent %D 2022 %7 23.5.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Digital applications are commonly used to support mental health and well-being. However, successfully retaining and engaging users to complete digital interventions is challenging, and comorbidities such as chronic pain further reduce user engagement. Digital conversational agents (CAs) may improve user engagement by applying engagement principles that have been implemented within in-person care settings. Objective: To evaluate user retention and engagement with an artificial intelligence–led digital mental health app (Wysa for Chronic Pain) that is customized for individuals managing mental health symptoms and coexisting chronic pain. Methods: In this ancillary survival analysis of a clinical trial, participants included 51 adults who presented to a tertiary care center for chronic musculoskeletal pain, who endorsed coexisting symptoms of depression or anxiety (Patient-Reported Outcomes Measurement Information System score of ≥55 for depression or anxiety), and initiated onboarding to an 8-week subscription of Wysa for Chronic Pain. The study outcomes were user retention, defined as revisiting the app each week and on the last day of engagement, and user engagement, defined by the number of sessions the user completed. Results: Users engaged in a cumulative mean of 33.3 sessions during the 8-week study period. The survival analysis depicted a median user retention period (i.e., time to complete disengagement) of 51 days, with the usage of a morning check-in feature having a significant relationship with a longer retention period (P=.001). Conclusions: Our findings suggest that user retention and engagement with a CBT-based CA built for users with chronic pain is higher than standard industry metrics. These results have clear implications for addressing issues of suboptimal engagement of digital health interventions and improving access to care for chronic pain. Future work should use these findings to inform the design of evidence-based interventions for individuals with chronic pain and to enhance user retention and engagement of digital health interventions more broadly. Trial Registration: ClinicalTrials.gov NCT04640090; https://clinicaltrials.gov/ct2/show/NCT04640090 %M 35526201 %R 10.2196/37302 %U https://formative.jmir.org/2022/5/e37302 %U https://doi.org/10.2196/37302 %U http://www.ncbi.nlm.nih.gov/pubmed/35526201 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e36959 %T A Nurse-Led Multimedia Intervention to Increase Patient Participation in Recovery After Knee Arthroplasty: Hybrid Type II Implementation Study %A McDonall,Jo %A Redley,Bernice %A Livingston,Patricia %A Hutchinson,Ana %A de Steiger,Richard %A Botti,Mari %+ School of Nursing and Midwifery, Faculty of Health, Deakin University, 1 Gheringhap St., Geelong, 3220, Australia, 61 92446630, jo.mcdonall@deakin.edu.au %K patient participation %K multimedia %K nurse-facilitated %K knee arthroplasty %K orthopedic surgery %K acute care %K nurse %K participatory medicine %K digital technology %D 2022 %7 19.5.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Advances in digital technology and the use of multimedia platforms to deliver information provide clinicians with a unique opportunity to develop innovative ways to consistently provide high-quality, accessible, and evidence-based information to support patient participation. Introducing new technologies into everyday acute care clinical practice can be difficult. Objective: The aim of this paper was to provide a description of an implementation strategy and the subsequent evaluation undertaken to examine the contextual factors important to the successful adoption of new technology by nurses in the context of acute postoperative care. Methods: Implementation of the intervention and process evaluation was undertaken in 3 phases: phase 1, preimplementation stakeholder engagement and identification of barriers and enablers to implementation; phase 2, supported implementation of the intervention; and phase 3, evaluation of uptake, usability, and acceptability of the intervention in clinical practice. Results: The outcomes of the implementation of the multimedia intervention in the context of acute postoperative care were positive. Of the 104 patients in the intervention group, 103 (99%) received the intervention. All 103 patients completed the 8-item intervention questionnaire and 93.3% (97/103) were interviewed on day 3 to evaluate usability, uptake, and acceptability. Of these 97 patients, almost all (n=94, 91%) found the program easy to use and most (n=64, 62%) could view the MyStay Total Knee Replacement program as often as they wanted. The findings also suggest that the time to implement the program was minimal (5-10 minutes). Collaboration with nurses and patients before and during implementation to identify potential barriers to successful implementation of the intervention was essential to develop timely strategies to overcome these barriers. To ensure end-user engagement, careful consideration was given to nurses’ views on who was responsible for facilitating this intervention. Conclusions: The findings provide evidence that the structured implementation of the multimedia intervention was robust and successful in terms of patient participant recruitment and application; however, it was difficult to assess the level of engagement by nurse clinicians with the program. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12614000340639; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12614000340639 %M 35588363 %R 10.2196/36959 %U https://humanfactors.jmir.org/2022/2/e36959 %U https://doi.org/10.2196/36959 %U http://www.ncbi.nlm.nih.gov/pubmed/35588363 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 5 %P e36114 %T Multimodal Chronic Pain Therapy for Adults via Smartphone: Randomized Controlled Clinical Trial %A Morcillo-Muñoz,Yolanda %A Sánchez-Guarnido,Antonio José %A Calzón-Fernández,Silvia %A Baena-Parejo,Isabel %+ Primary Care, Andalusian Health Service, Plaza de la Mujer s/n, District Campo de Gibraltar, Algeciras, 11207, Spain, 34 670946860, ymmcadiz1969@gmail.com %K chronic pain %K eHealth %K multimodal intervention %K catastrophizing %K self-management %K mHealth %K mobile phone %K randomized controlled trials %D 2022 %7 11.5.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Combination therapies delivered remotely via the internet or mobile devices are increasingly being used to improve and promote the self-management of chronic conditions. However, little is known regarding the long-term effects of these interventions. Objective: The aim of this study is to evaluate the effectiveness of a multimodal intervention program that measures associated variables such as catastrophizing, pain acceptance, and quality of life using a mobile device in people with chronic pain in an outpatient setting. Methods: A randomized controlled clinical trial was performed using parallel treatment groups. A total of 209 patients with chronic musculoskeletal pain were randomly assigned to one of the two study arms. The intervention group received a standard web-based psychosocial therapy-type program of activities through a smartphone for 6 weeks. The control group only had access to the Find out more section of the app, which contained audiovisual material for pain management based on a self-help approach. The primary outcome was catastrophizing measured using the Pain Catastrophizing Scale (PCS). Secondary outcomes were pain acceptance measured using the Chronic Pain Acceptance Questionnaire and health-related quality of life measured using the EuroQol Visual Analogue Scale. Assessments were conducted at baseline (T1), after treatment (T2), and at the 3-month follow-up (T3). The variations between the different phases were assessed using the percentage change rescaled with log base 2. The Cohen d was calculated based on the results of the linear mixed model. The investigators of the study who evaluated the results were not involved in patient recruitment and were blinded to the group assignment. Results: Positive effects were found in the intervention group (T2–T1) in catastrophizing between the baseline and posttreatment phases (P<.001) and in helplessness (−0.72 vs 0.1; P=.002), rumination (−1.59 vs −0.53; P<.001), acceptance (0.38 vs 0.05; P=.001), and quality of life (0.43 vs −0.01; P=.002), although no significant changes were found for magnification (0.2 vs 0.77; P=.14) and satisfaction with health (0.25 vs −0.27; P=.13). Three months after treatment, significant differences were observed in the intervention group for the outcome variable of catastrophizing (PCS; −0.59 vs 0.2; P=.006) and the PCS subscales of helplessness (−0.65 vs 0.01; P=.07), rumination (1.23 vs −0.59; P=.04), and magnification (0.1 vs 0.86; P=.02). Conclusions: The results of our study suggest that app-based mobile multidimensional treatments for adults with chronic pain improve catastrophizing, quality of life, and psychological flexibility immediately after treatment and that the effects are maintained for the primary outcome of catastrophizing for at least 3 months following treatment. Moreover, they promote self-management and can be used to complement face-to-face pain treatments. Trial Registration: ClinicalTrials.gov NCT04509154; https://clinicaltrials.gov/ct2/show/NCT04509154 %M 35373 %R 10.2196/36114 %U https://www.jmir.org/2022/5/e36114 %U https://doi.org/10.2196/36114 %U http://www.ncbi.nlm.nih.gov/pubmed/35373 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 5 %P e36404 %T Nonusage Attrition of Adolescents in an mHealth Promotion Intervention and the Role of Socioeconomic Status: Secondary Analysis of a 2-Arm Cluster-Controlled Trial %A Maenhout,Laura %A Peuters,Carmen %A Cardon,Greet %A Crombez,Geert %A DeSmet,Ann %A Compernolle,Sofie %+ Department of Movement and Sports Sciences, Ghent University, Watersportlaan 2, Ghent, 9000, Belgium, 32 92646363, laura.maenhout@ugent.be %K mHealth %K nonusage attrition %K adolescents %K socioeconomic status %K mobile phone %D 2022 %7 10.5.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health (mHealth) interventions may help adolescents adopt healthy lifestyles. However, attrition in these interventions is high. Overall, there is a lack of research on nonusage attrition in adolescents, particularly regarding the role of socioeconomic status (SES). Objective: The aim of this study was to focus on the role of SES in the following three research questions (RQs): When do adolescents stop using an mHealth intervention (RQ1)? Why do they report nonusage attrition (RQ2)? Which intervention components (ie, self-regulation component, narrative, and chatbot) prevent nonusage attrition among adolescents (RQ3)? Methods: A total of 186 Flemish adolescents (aged 12-15 years) participated in a 12-week mHealth program. Log data were monitored to measure nonusage attrition and usage duration for the 3 intervention components. A web-based questionnaire was administered to assess reasons for attrition. A survival analysis was conducted to estimate the time to attrition and determine whether this differed according to SES (RQ1). Descriptive statistics were performed to map the attrition reasons, and Fisher exact tests were used to determine if these reasons differed depending on the educational track (RQ2). Mixed effects Cox proportional hazard regression models were used to estimate the associations between the use duration of the 3 components during the first week and attrition. An interaction term was added to the regression models to determine whether associations differed by the educational track (RQ3). Results: After 12 weeks, 95.7% (178/186) of the participants stopped using the app. 30.1% (56/186) of the adolescents only opened the app on the installation day, and 44.1% (82/186) stopped using the app in the first week. Attrition at any given time during the intervention period was higher for adolescents from the nonacademic educational track compared with those from the academic track. The other SES indicators (family affluence and perceived financial situation) did not explain attrition. The most common reasons for nonusage attrition among participants were perceiving that the app did not lead to behavior change, not liking the app, thinking that they already had a sufficiently healthy lifestyle, using other apps, and not being motivated by the environment. Attrition reasons did not differ depending on the educational track. More time spent in the self-regulation and narrative components during the first week was associated with lower attrition, whereas chatbot use duration was not associated with attrition rates. No moderating effects of SES were observed in the latter association. Conclusions: Nonusage attrition was high, especially among adolescents in the nonacademic educational track. The reported reasons for attrition were diverse, with no statistical differences according to the educational level. The duration of the use of the self-regulation and narrative components during the first week may prevent attrition for both educational tracks. Trial Registration: ClinicalTrials.gov NCT04719858; http://clinicaltrials.gov/ct2/show/NCT04719858 %M 35536640 %R 10.2196/36404 %U https://mhealth.jmir.org/2022/5/e36404 %U https://doi.org/10.2196/36404 %U http://www.ncbi.nlm.nih.gov/pubmed/35536640 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 5 %P e37946 %T Asthma and Technology in Emerging African American Adults (The ATHENA Project): Protocol for a Trial Using the Multiphase Optimization Strategy Framework %A Baptist,Alan %A Gibson-Scipio,Wanda %A Carcone,April Idalski %A Ghosh,Samiran %A Jacques-Tiura,Angela J %A Hall,Amy %A MacDonell,Karen Kolmodin %+ Department of Family Medicine and Public Health Sciences, School of Medicine, Wayne State University, iBio 6135 Woodward Ave, Detroit, MI, 48202, United States, 1 3135776996, karen.macdonell@wayne.edu %K African American emerging adults %K asthma management %K mHealth %K mobile health %K motivational interviewing %K asthma control %K physical activity %D 2022 %7 10.5.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Asthma causes substantial morbidity and mortality in the United States, particularly among African American emerging adults (AAEAs; aged 18-30 years), but very few asthma programs have targeted this population. Interventions that provide education and address underlying motivation for managing asthma may be the most effective. However, intensive face-to-face interventions are often difficult to implement in this population. Objective: The purpose of this study is to develop an effective mobile asthma management intervention to improve control among AAEAs. Methods: We will assess the ability of multiple technologic components to assist and improve traditional asthma education. The first component is the Motivational Enhancement System for asthma management. It is a mobile 4-session intervention using supported self-regulation and motivational interviewing. Personalized content is based on each participant’s activity level, daily experiences, and goals. The second component is supportive accountability. It is administered by asthma nurses using targeted mobile support (Skype/voice calls) to provide education, promote self-efficacy, and overcome barriers through a motivational interviewing–based framework. The third component is SMS text messaging. It provides reminders for asthma education, medication adherence, and physical activity. The fourth component is physical activity tracking. It uses wearable technology to help meet user-defined physical activity goals. Using a multiphase optimization strategy (MOST) framework, we will test intervention components and combinations of components to identify the most effective mobile intervention. The MOST framework is an innovative, and cost- and time-effective framework that uses engineering principles to produce effective behavioral interventions. We will conduct a component selection experiment using a factorial research design to build an intervention that has been optimized for maximum efficacy, using a clinically significant improvement in asthma. Participants (N=180) will be randomized to 1 of 6 intervention arms. Participants will be recruited from multiple sites of the American Lung Association-Airway Clinical Research Centers network and ambulatory care clinics at the Detroit Medical Center. Data collections will occur at baseline, and 3, 6, and 12 months. Results: At study completion, we will have an empirically supported optimized mobile asthma management intervention to improve asthma control for AAEAs. We hypothesize that postintervention (3, 6, and 12 months), participants with uncontrolled asthma will show a clinically significant improvement in asthma control. We also hypothesize that improvements in asthma management behaviors (including physical activity), quality of life, symptoms, adherence, and exacerbation (secondary outcomes) will be observed. Conclusions: AAEAs are disproportionately impacted by asthma, but have been underrepresented in research. Mobile asthma management interventions may help improve asthma control and allow people to live healthier lives. During this project, we will use an innovative strategy to develop an optimized mobile asthma management intervention using the most effective combination of nurse-delivered asthma education, a smartphone app, and text messaging. International Registered Report Identifier (IRRID): PRR1-10.2196/37946 %M 35536642 %R 10.2196/37946 %U https://www.researchprotocols.org/2022/5/e37946 %U https://doi.org/10.2196/37946 %U http://www.ncbi.nlm.nih.gov/pubmed/35536642 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 5 %P e32006 %T Factors Predicting Engagement of Older Adults With a Coach-Supported eHealth Intervention Promoting Lifestyle Change and Associations Between Engagement and Changes in Cardiovascular and Dementia Risk: Secondary Analysis of an 18-Month Multinational Randomized Controlled Trial %A Coley,Nicola %A Andre,Laurine %A Hoevenaar-Blom,Marieke P %A Ngandu,Tiia %A Beishuizen,Cathrien %A Barbera,Mariagnese %A van Wanrooij,Lennard %A Kivipelto,Miia %A Soininen,Hilkka %A van Gool,Willem %A Brayne,Carol %A Moll van Charante,Eric %A Richard,Edo %A Andrieu,Sandrine %A , %A , %+ Center for Epidemiology and Research in Population health (CERPOP), University of Toulouse III Paul Sabatier (UPS), National Institute of Health and Medical Research (INSERM) mixed research unit (UMR) 1295, 37 allées Jules Guesde, Toulouse, 31000, France, 33 561145680, nicola.coley@inserm.fr %K aging %K eHealth %K disparities %K engagement %K prevention %K cardiovascular %K lifestyle %K risk factors %D 2022 %7 9.5.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital health interventions could help to prevent age-related diseases, but little is known about how older adults engage with such interventions, especially in the long term, or whether engagement is associated with changes in clinical, behavioral, or biological outcomes in this population. Disparities in engagement levels with digital health interventions may exist among older people and be associated with health inequalities. Objective: This study aimed to describe older adults’ engagement with an eHealth intervention, identify factors associated with engagement, and examine associations between engagement and changes in cardiovascular and dementia risk factors (blood pressure, cholesterol, BMI, physical activity, diet, and cardiovascular and dementia risk scores). Methods: This was a secondary analysis of the 18-month randomized controlled Healthy Ageing Through Internet Counselling in the Elderly trial of a tailored internet-based intervention encouraging behavior changes, with remote support from a lifestyle coach, to reduce cardiovascular and cognitive decline risk in 2724 individuals aged ≥65 years, recruited offline in the Netherlands, Finland, and France. Engagement was assessed via log-in frequency, number of lifestyle goals set, measurements entered and messages sent to coaches, and percentage of education materials read. Clinical and biological data were collected during in-person visits at baseline and 18 months. Lifestyle data were self-reported on a web-based platform. Results: Of the 1389 intervention group participants, 1194 (85.96%) sent at least one message. They logged in a median of 29 times, and set a median of 1 goal. Higher engagement was associated with significantly greater improvement in biological and behavioral risk factors, with evidence of a dose-response effect. Compared with the control group, the adjusted mean difference (95% CI) in 18-month change in the primary outcome, a composite z-score comprising blood pressure, BMI, and cholesterol, was −0.08 (−0.12 to −0.03), −0.04 (−0.08 to 0.00), and 0.00 (−0.08 to 0.08) in the high, moderate, and low engagement groups, respectively. Low engagers showed no improvement in any outcome measures compared with the control group. Participants not using a computer regularly before the study engaged much less with the intervention than those using a computer up to 7 (adjusted odds ratio 5.39, 95% CI 2.66-10.95) or ≥7 hours per week (adjusted odds ratio 6.58, 95% CI 3.21-13.49). Those already working on or with short-term plans for lifestyle improvement at baseline, and with better cognition, engaged more. Conclusions: Greater engagement with an eHealth lifestyle intervention was associated with greater improvement in risk factors in older adults. However, those with limited computer experience, who tended to have a lower level of education, or who had poorer cognition engaged less. Additional support or forms of intervention delivery for such individuals could help minimize potential health inequalities associated with the use of digital health interventions in older people. %M 35385395 %R 10.2196/32006 %U https://www.jmir.org/2022/5/e32006 %U https://doi.org/10.2196/32006 %U http://www.ncbi.nlm.nih.gov/pubmed/35385395 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 5 %P e37292 %T A Group-Facilitated, Internet-Based Intervention to Promote Mental Health and Well-Being in a Vulnerable Population of University Students: Randomized Controlled Trial of the Be Well Plan Program %A Fassnacht,Daniel B %A Ali,Kathina %A van Agteren,Joep %A Iasiello,Matthew %A Mavrangelos,Teri %A Furber,Gareth %A Kyrios,Michael %+ College of Education, Psychology and Social Work, Flinders University, Sturt Road, Bedford Park, Adelaide, 5042, Australia, 61 8 8201 2621, dan.fassnacht@flinders.edu.au %K COVID-19 %K mental health %K well-being %K depression %K anxiety %K online %K digital %K intervention %K Be Well Plan %K health outcome %K online health %K digital health %K health intervention %K primary outcome %K cognition %K randomized control trial %K resilience %K participant satisfaction %K student %D 2022 %7 5.5.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: A growing literature supports the use of internet-based interventions to improve mental health outcomes. However, most programs target specific symptoms or participant groups and are not tailored to facilitate improvements in mental health and well-being or do not allow for needs and preferences of individual participants. The Be Well Plan, a 5-week group-facilitated, internet-based mental health and well-being group intervention addresses these gaps, allowing participants to select a range of activities that they can tailor to their specific characteristics, needs, and preferences. Objective: This study aims to test whether the Be Well Plan program was effective in improving primary outcomes of mental well-being, resilience, anxiety, and depression compared to a waitlist control group during the COVID-19 pandemic; secondary outcomes included self-efficacy, a sense of control, and cognitive flexibility. The study further seeks to examine participants’ engagement and satisfaction with the program. Methods: A randomized controlled trial (RCT) was conducted with 2 parallel arms, an intervention and a waitlist control group. The intervention involved 5 weekly 2-hour sessions, which were facilitated in group format using Zoom videoconferencing software. University students were recruited via social media posts, lectures, emails, flyers, and posters. Results: Using an intentional randomization 2:1 allocation strategy, we recruited 215 participants to the trial (n=126, 58.6%, intervention group; n=89, 41.4%, waitlist control group). Of the 126 participants assigned to the intervention group, 75 (59.5%) commenced the program and were included in modified intention-to-treat (mITT) analyses. mITT intervention participants attended, on average, 3.41 sessions (SD 1.56, median 4); 55 (73.3%) attended at least 4 sessions, and 25 (33.3%) attended all 5 sessions. Of the 49 intervention group participants who completed the postintervention assessment, 47 (95.9%) were either very satisfied (n=31, 66%) or satisfied (n=16, 34%). The mITT analysis for well-being (F1,162=9.65, P=.002, Cohen d=0.48) and resilience (F1,162=7.85, P=.006, Cohen d=0.44) showed significant time × group interaction effects, suggesting that both groups improved over time, but the Be Well Plan (intervention) group showed significantly greater improvement compared to the waitlist control group. A similar pattern of results was observed for depression and anxiety (Cohen d=0.32 and 0.37, respectively), as well as the secondary outcomes (self-efficacy, Cohen d=0.50; sense of control, Cohen d=0.42; cognitive flexibility, Cohen d=0.65). Larger effect sizes were observed in the completer analyses. Reliable change analysis showed that the majority of mITT participants (58/75, 77.3%) demonstrated a significant reliable improvement in at least 1 of the primary outcomes. Conclusions: The Be Well Plan program was effective in improving mental health and well-being, including mental well-being, resilience, depression, and anxiety. Participant satisfaction scores and attendance indicated a high degree of engagement and satisfaction with the program. Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12621000180819; https://tinyurl.com/2p8da5sk %M 35471196 %R 10.2196/37292 %U https://mental.jmir.org/2022/5/e37292 %U https://doi.org/10.2196/37292 %U http://www.ncbi.nlm.nih.gov/pubmed/35471196 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 5 %P e27277 %T A Multifaceted Intervention to Improve Medication Adherence in Kidney Transplant Recipients: An Exploratory Analysis of the Fidelity of the TAKE IT Trial %A Yoon,Esther S %A Hur,Scott %A Curtis,Laura M %A Wynia,Aiden H %A Zheng,Pauline %A Nair,Sumi S %A Bailey,Stacy C %A Serper,Marina %A Reese,Peter P %A Ladner,Daniela P %A Wolf,Michael S %+ Center for Applied Health Research on Aging, Feinberg School of Medicine, Northwestern University, 750 N. Lake Shore Drive, Chicago, IL, 60611, United States, 1 3125034948, esther.yoon@northwestern.edu %K kidney transplantation %K medication adherence %K fidelity %K digital health %K patient portal %D 2022 %7 5.5.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Inadequate adherence to prescribed immunosuppressive medication regimens among kidney transplant recipients is common, yet interventions are needed to support patients in sustaining adequate adherence to prescribed regimens and achieving optimal transplant outcomes. Objective: We examined the preliminary fidelity of a transplant center-based, multifaceted adherence monitoring strategy known as TAKE IT. Methods: The TAKE IT strategy includes: (1) routine, online, monthly patient self-report adherence assessments; (2) care alerts directed to nurses; (3) quarterly reports monitoring tacrolimus values and adherence trends; (4) support tools tailored to specific adherence concerns. A 2-arm, patient-randomized trial is underway at two large transplant centers (N=449). To evaluate the initial fidelity of TAKE IT, we investigated patient uptake of monthly adherence assessments during the course of a 3-month period, whether any disparities emerged, and the nature of any reported adherence concerns. Results: Among 202 patients randomized and exposed to TAKE IT for 3-months or more, 81% (164/202) completed an adherence assessment, 73% (148/202) completed at least two, and 57% (116/202) completed all monthly assessments. Overall, 50% (82/164) of kidney transplant recipients reported at least one adherence concern over the 3-month assessment period. The most common barriers were classified as regimen-related (eg, regimen complexity), cognitive (eg, forgetfulness), and medical (eg, side effects). Higher-income participants were more likely to complete all surveys compared to lower-income participants (P=.01). Conclusions: TAKE IT demonstrated 81% (164/202) completion of an adherence assessment, 73% (148/202) completion of at least two, and 57% (116/202) completion of all monthly assessments during this brief, initial observation period. Among those that did respond to the online assessments, the majority demonstrated sustained engagement. Additional monitoring modalities could also be offered to meet patient preferences to ensure all patients’ medication use can be properly monitored. Trial Registration: ClinicalTrials.gov NCT03104868; https://clinicaltrials.gov/ct2/show/NCT03104868 %M 35511225 %R 10.2196/27277 %U https://formative.jmir.org/2022/5/e27277 %U https://doi.org/10.2196/27277 %U http://www.ncbi.nlm.nih.gov/pubmed/35511225 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 5 %P e35471 %T Assessing Engagement With Patient-Generated Health Data Recording and Its Impact on Health Behavior Changes in Multicomponent Interventions: Supplementary Analysis %A Kinouchi,Kaori %A Ohashi,Kazutomo %+ Department of Children and Women's Health, Area of integrated Health and Nursing Science, Osaka University Graduate School of Medicine, 1-7-B411, Yamadaoka, Suita, Osaka, 5650871, Japan, 81 668792537, kinouchi@sahs.med.osaka-u.ac.jp %K patient-generated health data %K engagement %K health behavior change %K postpartum women %K health data %K health informatics %K pelvic health %D 2022 %7 3.5.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The use and sharing of patient-generated health data (PGHD) by clinicians or researchers is expected to enhance the remote monitoring of specific behaviors that affect patient health. In addition, PGHD use could support patients’ decision-making on preventive care management, resulting in reduced medical expenses. However, sufficient evidence on the use and sharing of PGHD is lacking, and the impact of PGHD recording on patients’ health behavior changes remains unclear. Objective: This study aimed to assess patients’ engagement with PGHD recording and to examine the impact of PGHD recording on their health behavior changes. Methods: This supplementary analysis used the data of 47 postpartum women who had been assigned to the intervention group of our previous study for managing urinary incontinence. To assess the patients’ engagement with PGHD recording during the intervention period (8 weeks), the fluctuation in the number of patients who record their PGHD (ie, PGHD recorders) was evaluated by an approximate curve. In addition, to assess adherence to the pelvic floor muscle training (PFMT), the weekly mean number of pelvic floor muscle contractions performed per day among 17 PGHD recorders was examined by latent class growth modeling (LCGM). Results: The fluctuation in the number of PGHD recorders was evaluated using the sigmoid curve formula (R2=0.91). During the first week of the intervention, the percentage of PGHD recorders was around 64% (30/47) and then decreased rapidly from the second to the third week. After the fourth week, the percentage of PGHD recorders was 36% (17/47), which remained constant until the end of the intervention. When analyzing the data of these 17 PGHD recorders, PFMT adherence was categorized into 3 classes by LCGM: high (7/17, 41%), moderate (3/17, 18%), and low (7/17, 41%). Conclusions: The number of PGHD recorders declined over time in a sigmoid curve. A small number of users recorded PGHD continuously; therefore, patients’ engagement with PGHD recording was low. In addition, more than half of the PGHD recorders (moderate- and low-level classes combined: 10/17, 59%) had poor PFMT adherence. These results suggest that PGHD recording does not always promote health behavior changes. %M 35503411 %R 10.2196/35471 %U https://formative.jmir.org/2022/5/e35471 %U https://doi.org/10.2196/35471 %U http://www.ncbi.nlm.nih.gov/pubmed/35503411 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 5 %P e35048 %T Engagement, Predictors, and Outcomes of a Trauma Recovery Digital Mental Health Intervention: Longitudinal Study %A Yeager,Carolyn M %A Benight,Charles C %+ Lyda Hill Institute for Human Resilience, University of Colorado Colorado Springs, Fourth Floor, 4863 North Nevada Avenue, Colorado Springs, CO, 80918, United States, 1 (719) 413 8075, cyeager@uccs.edu %K engagement %K digital health %K digital mental health intervention %K social cognitive theory %K SCT %K self-efficacy %K outcome expectations %K trauma %K posttraumatic stress disorder %K PTSD %D 2022 %7 2.5.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: Worldwide, exposure to potentially traumatic events is extremely common, and many individuals develop posttraumatic stress disorder (PTSD) along with other disorders. Unfortunately, considerable barriers to treatment exist. A promising approach to overcoming treatment barriers is a digital mental health intervention (DMHI). However, engagement with DMHIs is a concern, and theoretically based research in this area is sparse and often inconclusive. Objective: The focus of this study is on the complex issue of DMHI engagement. On the basis of the social cognitive theory framework, the conceptualization of engagement and a theoretically based model of predictors and outcomes were investigated using a DMHI for trauma recovery. Methods: A 6-week longitudinal study with a national sample of survivors of trauma was conducted to measure engagement, predictors of engagement, and mediational pathways to symptom reduction while using a trauma recovery DMHI (time 1: N=915; time 2: N=350; time 3: N=168; and time 4: N=101). Results: Confirmatory factor analysis of the engagement latent constructs of duration, frequency, interest, attention, and affect produced an acceptable model fit (χ22=8.3; P=.02; comparative fit index 0.973; root mean square error of approximation 0.059; 90% CI 0.022-0.103). Using the latent construct, the longitudinal theoretical model demonstrated adequate model fit (comparative fit index 0.929; root mean square error of approximation 0.052; 90% CI 0.040-0.064), indicating that engagement self-efficacy (β=.35; P<.001) and outcome expectations (β=.37; P<.001) were significant predictors of engagement (R2=39%). The overall indirect effect between engagement and PTSD symptom reduction was significant (β=–.065; P<.001; 90% CI –0.071 to –0.058). This relationship was serially mediated by both skill activation self-efficacy (β=.80; P<.001) and trauma coping self-efficacy (β=.40; P<.001), which predicted a reduction in PTSD symptoms (β=−.20; P=.02). Conclusions: The results of this study may provide a solid foundation for formalizing the nascent science of engagement. Engagement conceptualization comprised general measures of attention, interest, affect, and use that could be applied to other applications. The longitudinal research model supported 2 theoretically based predictors of engagement: engagement self-efficacy and outcome expectancies. A total of 2 task-specific self-efficacies—skill activation and trauma coping—proved to be significant mediators between engagement and symptom reduction. Taken together, this model can be applied to other DMHIs to understand engagement, as well as predictors and mechanisms of action. Ultimately, this could help improve the design and development of engaging and effective trauma recovery DMHIs. %M 35499857 %R 10.2196/35048 %U https://mental.jmir.org/2022/5/e35048 %U https://doi.org/10.2196/35048 %U http://www.ncbi.nlm.nih.gov/pubmed/35499857 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 4 %P e30898 %T Social Networking Service, Patient-Generated Health Data, and Population Health Informatics: National Cross-sectional Study of Patterns and Implications of Leveraging Digital Technologies to Support Mental Health and Well-being %A Ye,Jiancheng %A Wang,Zidan %A Hai,Jiarui %+ Feinberg School of Medicine, Northwestern University, 633 N. Saint Clair St, Chicago, IL, 60611, United States, 1 312 503 3690, jiancheng.ye@u.northwestern.edu %K patient-generated health data %K social network %K population health informatics %K mental health %K social determinants of health %K health data sharing %K technology acceptability %K mobile phone %K mobile health %D 2022 %7 29.4.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: The emerging health technologies and digital services provide effective ways of collecting health information and gathering patient-generated health data (PGHD), which provide a more holistic view of a patient’s health and quality of life over time, increase visibility into a patient’s adherence to a treatment plan or study protocol, and enable timely intervention before a costly care episode. Objective: Through a national cross-sectional survey in the United States, we aimed to describe and compare the characteristics of populations with and without mental health issues (depression or anxiety disorders), including physical health, sleep, and alcohol use. We also examined the patterns of social networking service use, PGHD, and attitudes toward health information sharing and activities among the participants, which provided nationally representative estimates. Methods: We drew data from the 2019 Health Information National Trends Survey of the National Cancer Institute. The participants were divided into 2 groups according to mental health status. Then, we described and compared the characteristics of the social determinants of health, health status, sleeping and drinking behaviors, and patterns of social networking service use and health information data sharing between the 2 groups. Multivariable logistic regression models were applied to assess the predictors of mental health. All the analyses were weighted to provide nationally representative estimates. Results: Participants with mental health issues were significantly more likely to be younger, White, female, and lower-income; have a history of chronic diseases; and be less capable of taking care of their own health. Regarding behavioral health, they slept <6 hours on average, had worse sleep quality, and consumed more alcohol. In addition, they were more likely to visit and share health information on social networking sites, write online diary blogs, participate in online forums or support groups, and watch health-related videos. Conclusions: This study illustrates that individuals with mental health issues have inequitable social determinants of health, poor physical health, and poor behavioral health. However, they are more likely to use social networking platforms and services, share their health information, and actively engage with PGHD. Leveraging these digital technologies and services could be beneficial for developing tailored and effective strategies for self-monitoring and self-management. %M 35486428 %R 10.2196/30898 %U https://www.jmir.org/2022/4/e30898 %U https://doi.org/10.2196/30898 %U http://www.ncbi.nlm.nih.gov/pubmed/35486428 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 4 %P e35120 %T Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review %A Amagai,Saki %A Pila,Sarah %A Kaat,Aaron J %A Nowinski,Cindy J %A Gershon,Richard C %+ Northwestern University Feinberg School of Medicine, 625 North Michigan Avenue, 2700 suite, Chicago, IL, 60613, United States, 1 312 503 1725, saki.amagai@northwestern.edu %K mobile phone %K mHealth %K retention %K engagement %D 2022 %7 26.4.2022 %9 Review %J J Med Internet Res %G English %X Background: Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps. Objective: This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention. Methods: We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention. Results: Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained. Conclusions: Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention. %M 35471414 %R 10.2196/35120 %U https://www.jmir.org/2022/4/e35120 %U https://doi.org/10.2196/35120 %U http://www.ncbi.nlm.nih.gov/pubmed/35471414 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 4 %P e36354 %T Adapting Child Health Knowledge Translation Tools for Somali Parents: Qualitative Study Exploring Process Considerations and Stakeholder Engagement %A Elliott,Sarah A %A Wright,Kelsey S %A Scott,Shannon D %A Mohamed,Muna %A Farah,Asha %A Hartling,Lisa %+ Alberta Research Centre for Health Evidence, Department of Pediatrics, University of Alberta, 4-472 Edmonton Clinic Health Academy, Edmonton, AB, ​T6G 1C9, Canada, 1 (780) 492 6124, hartling@ualberta.ca %K knowledge translation %K cultural adaptation %K trust %K linguistics %K parents %K child health %D 2022 %7 4.4.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: We have developed a series of knowledge translation (KT) tools that integrate parental experiences to communicate evidence-based information about acute childhood health conditions to parents and caregivers. While we created these tools with parent input, it is unclear if they are useful for diverse parent groups, including specific immigrant and refugee groups in Canada. Objective: This study aims to explore the usefulness of our preexisting KT tools within our local Somali community, and understand what cultural and linguistic adaptations could improve their usability. Methods: After viewing 4 KT tools (differing in design and format) about various acute child health conditions, health care providers (HCPs) and knowledge brokers (KBs) who work with Somali families were interviewed about the usability of these tools and discussed considerations for adapting KT tools for use within the Somali community. Results: A total of 13 HCPs and KBs participated and indicated that the Somali community values accessibility, representation, and the role of trusted others in delivering effective KT products. Understanding accessibility barriers, the power of adequate representation, and engaging meaningfully with prominent community leaders were key suggestions for ensuring relevance of KT products and uptake by community members. Conclusions: This study represents an essential piece of understanding processes for adapting or developing KT products for culturally and linguistically diverse communities. %M 35377330 %R 10.2196/36354 %U https://formative.jmir.org/2022/4/e36354 %U https://doi.org/10.2196/36354 %U http://www.ncbi.nlm.nih.gov/pubmed/35377330 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 3 %P e28801 %T Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial %A Nuijten,Raoul %A Van Gorp,Pieter %A Khanshan,Alireza %A Le Blanc,Pascale %A van den Berg,Pauline %A Kemperman,Astrid %A Simons,Monique %+ Department of Industrial Engineering, Eindhoven University of Technology, Groene Loper 3, Eindhoven, 5612 AE, Netherlands, 31 040 247 2290, r.c.y.nuijten@tue.nl %K mHealth %K health promotion %K physical activity %K personalization %K adaptive goal setting %K gamification %K office workers %D 2022 %7 31.3.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Promising results have been obtained by using gamification techniques as behavior change strategies, especially when they were tailored toward an individual’s preferences and goals; yet, it remains unclear how goals could be personalized to effectively promote health behaviors. Objective: In this study, we aim to evaluate the impact of personalized goal setting in the context of gamified mHealth interventions. We hypothesize that interventions suggesting health goals that are tailored based on end users’ (self-reported) current and desired capabilities will be more engaging than interventions with generic goals. Methods: The study was designed as a 2-arm randomized intervention trial. Participants were recruited among staff members of 7 governmental organizations. They participated in an 8-week digital health promotion campaign that was especially designed to promote walks, bike rides, and sports sessions. Using an mHealth app, participants could track their performance on two social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per organizational department. The mHealth app also provided a news feed that showed when other participants had scored points. Points could be collected by performing any of the 6 assigned tasks (eg, walk for at least 2000 m). The level of complexity of 3 of these 6 tasks was updated every 2 weeks by changing either the suggested task intensity or the suggested frequency of the task. The 2 intervention arms—with participants randomly assigned—consisted of a personalized treatment that tailored the complexity parameters based on participants’ self-reported capabilities and goals and a control treatment where the complexity parameters were set generically based on national guidelines. Measures were collected from the mHealth app as well as from intake and posttest surveys and analyzed using hierarchical linear models. Results: The results indicated that engagement with the program inevitably dropped over time. However, engagement was higher for participants who had set themselves a goal in the intake survey. The impact of personalization was especially observed for frequency parameters because the personalization of sports session frequency did foster higher engagement levels, especially when participants set a goal to improve their capabilities. In addition, the personalization of suggested ride duration had a positive effect on self-perceived biking performance. Conclusions: Personalization seems particularly promising for promoting the frequency of physical activity (eg, promoting the number of suggested sports sessions per week), as opposed to the intensity of the physical activity (eg, distance or duration). Replications and variations of our study setup are critical for consolidating and explaining (or refuting) these effects. Trial Registration: ClinicalTrials.gov NCT05264155; https://clinicaltrials.gov/ct2/show/NCT05264155 %M 35357323 %R 10.2196/28801 %U https://mhealth.jmir.org/2022/3/e28801 %U https://doi.org/10.2196/28801 %U http://www.ncbi.nlm.nih.gov/pubmed/35357323 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e27158 %T Understanding Engagement and the Potential Impact of an Electronic Drug Repository: Multi-Methods Study %A Soobiah,Charlene %A Phung,Michelle %A Tadrous,Mina %A Jamieson,Trevor %A Bhatia,R Sacha %A Desveaux,Laura %+ Institute for Health System Solutions and Virtual Care, Women's College Hospital, 76 Grenville St, Toronto, ON, M5S 1B2, Canada, 1 (416) 323 6400, laura.desveaux@thp.ca %K centralized drug repository %K mixed methods %K electronic survey %D 2022 %7 30.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Centralized drug repositories can reduce adverse events and inappropriate prescriptions by enabling access to dispensed medication data at the point of care; however, how they achieve this goal is largely unknown. Objective: This study aims to understand the perceived clinical value; the barriers to and enablers of adoption; and the clinician groups for which a provincial, centralized drug repository may provide the most benefit. Methods: A mixed methods approach, including a web-based survey and semistructured interviews, was used. Participants were clinicians (eg, nurses, physicians, and pharmacists) in Ontario who were eligible to use the digital health drug repository (DHDR), irrespective of actual use. Survey data were ranked on a 7-point adjectival scale and analyzed using descriptive statistics, and interviews were analyzed using qualitative descriptions. Results: Of the 161 survey respondents, only 40 (24.8%) actively used the DHDR. Perceptions of the utility of the DHDR were neutral (mean scores ranged from 4.11 to 4.76). Of the 75.2% (121/161) who did not use the DHDR, 97.5% (118/121) rated access to medication information (eg, dose, strength, and frequency) as important. Reasons for not using the DHDR included the cumbersome access process and the perception that available data were incomplete or inaccurate. Of the 33 interviews completed, 26 (79%) were active DHDR users. The DHDR was a satisfactory source of secondary information; however, the absence of medication instructions and prescribed medications (which were not dispensed) limited its ability to provide a comprehensive profile to meaningfully support clinical decision-making. Conclusions: Digital drug repositories must be adjusted to align with the clinician’s needs to provide value. Ensuring integration with point-of-care systems, comprehensive clinical data, and streamlined onboarding processes would optimize clinically meaningful use. The electronic provision of accessible drug information to providers across health care settings has the potential to improve efficiency and reduce medication errors. %M 35353042 %R 10.2196/27158 %U https://formative.jmir.org/2022/3/e27158 %U https://doi.org/10.2196/27158 %U http://www.ncbi.nlm.nih.gov/pubmed/35353042 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 3 %P e35172 %T Associations Between Behavior Change Techniques and Engagement With Mobile Health Apps: Protocol for a Systematic Review %A Milne-Ives,Madison %A Homer,Sophie %A Andrade,Jackie %A Meinert,Edward %+ Centre for Health Technology, University of Plymouth, 6 Kirkby Place, Room 2, Plymouth, PL4 6DN, United Kingdom, 44 1752600600, madison.milne-ives@plymouth.ac.uk %K engagement %K behavior change techniques %K telemedicine %K mobile apps %D 2022 %7 29.3.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Digitally enabled care along with an emphasis on self-management of health is steadily growing. Mobile health apps provide a promising means of supporting health behavior change; however, engagement with them is often poor and evidence of their impact on health outcomes is lacking. As engagement is a key prerequisite to health behavior change, it is essential to understand how engagement with mobile health apps and their target health behaviors can be better supported. Although the importance of engagement is emphasized strongly in the literature, the understanding of how different components of engagement are associated with specific techniques that aim to change behaviors is lacking. Objective: The purpose of this systematic review protocol is to provide a synthesis of the associations between various behavior change techniques (BCTs) and the different components and measures of engagement with mobile health apps. Methods: The review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the PICOS (Population, Intervention, Comparator, Outcome, and Study type) frameworks. The following seven databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, APA PsycInfo, ScienceDirect, Cochrane Library, and Web of Science. Title and abstract screening, full-text review, and data extraction will be conducted by 2 independent reviewers. Data will be extracted into a predetermined form, any disagreements in screening or data extraction will be discussed, and a third reviewer will be consulted if consensus cannot be reached. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 and the Risk Of Bias In Non-Randomized Studies - of Interventions (ROBINS-I) tools; descriptive and thematic analyses will be conducted to summarize the relationships between BCTs and the different components of engagement. Results: The systematic review has not yet started. It is expected to be completed and submitted for publication by May 2022. Conclusions: This systematic review will summarize the associations between different BCTs and various components and measures of engagement with mobile health apps. This will help identify areas where further research is needed to examine BCTs that could potentially support effective engagement and help inform the design and evaluation of future mobile health apps. Trial Registration: PROSPERO CRD42022312596; https://tinyurl.com/nhzp8223 International Registered Report Identifier (IRRID): PRR1-10.2196/35172 %M 35348460 %R 10.2196/35172 %U https://www.researchprotocols.org/2022/3/e35172 %U https://doi.org/10.2196/35172 %U http://www.ncbi.nlm.nih.gov/pubmed/35348460 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 3 %P e30754 %T Measuring Adherence Within a Self-Guided Online Intervention for Depression and Anxiety: Secondary Analyses of a Randomized Controlled Trial %A Hanano,Maria %A Rith-Najarian,Leslie %A Boyd,Meredith %A Chavira,Denise %+ Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095, United States, 1 9493501523, mariahanano@g.ucla.edu %K self-guided %K adherence %K depression %K anxiety %K online intervention %D 2022 %7 28.3.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: Self-guided online interventions offer users the ability to participate in an intervention at their own pace and address some traditional service barriers (eg, attending in-person appointments, cost). However, these interventions suffer from high dropout rates, and current literature provides little guidance for defining and measuring online intervention adherence as it relates to clinical outcomes. Objective: This study aims to develop and test multiple measures of adherence to a specific self-guided online intervention, as guided by best practices from the literature. Methods: We conducted secondary analyses on data from a randomized controlled trial of an 8-week online cognitive behavioral program that targets depression and anxiety in college students. We defined multiple behavioral and attitudinal adherence measures at varying levels of effort (ie, low, moderate, and high). Linear regressions were run with adherence terms predicting improvement in the primary outcome measure, the 21-item Depression, Anxiety, and Stress Scale (DASS-21). Results: Of the 947 participants, 747 initiated any activity and 449 provided posttest data. Results from the intent-to-treat sample indicated that high level of effort for behavioral adherence significantly predicted symptom change (F4,746=17.18, P<.001; and β=–.26, P=.04). Moderate level of effort for attitudinal adherence also significantly predicted symptom change (F4,746=17.25, P<.001; and β=–.36, P=.03). Results differed in the initiators-only sample, such that none of the adherence measures significantly predicted symptom change (P=.09-.27). Conclusions: Our findings highlight the differential results of dose-response models testing adherence measures in predicting clinical outcomes. We summarize recommendations that might provide helpful guidance to future researchers and intervention developers aiming to investigate online intervention adherence. Trial Registration: ClinicalTrials.gov NCT04361045; https://clinicaltrials.gov/ct2/show/NCT04361045 %M 35343901 %R 10.2196/30754 %U https://mental.jmir.org/2022/3/e30754 %U https://doi.org/10.2196/30754 %U http://www.ncbi.nlm.nih.gov/pubmed/35343901 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e32537 %T A Novel Experience Sampling Method Tool Integrating Momentary Assessments of Cognitive Biases: Two Compliance, Usability, and Measurement Reactivity Studies %A Boemo,Teresa %A Socastro,Angela %A Blanco,Ivan %A Martin-Garcia,Oscar %A Pacheco-Romero,Ana Mar %A Rodríguez-Carvajal,Raquel %A Sanchez-Lopez,Alvaro %+ Complutense University of Madrid, Campus de Somosaguas, s/n, Madrid, 28223, Spain, 34 674107873, mboemo@ucm.es %K experience sampling method %K compliance %K usability %K measurement reactivity %K emotion %K cognitive biases %D 2022 %7 28.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Experience sampling methods (ESMs) are increasingly being used to study ecological emotion dynamics in daily functioning through repeated assessments taken over several days. However, most of these ESM approaches are only based on self-report assessments, and therefore, studies on the ecological trajectories of their underlying mechanisms are scarce (ie, cognitive biases) and require evaluation through experimental tasks. We developed a novel ESM tool that integrates self-report measures of emotion and emotion regulation with a previously validated app-based cognitive task that allows for the assessment of underlying mechanisms during daily functioning. Objective: The objective of the study is to test this new tool and study its usability and the possible factors related to compliance with it in terms of latency and missing responses. Among the compliance predictors, we considered psychological and time-related variables, as well as usability, measurement reactivity, and participants’ satisfaction with the tool. Methods: We conducted 2 extensive ESM studies—study 1 (N=84; a total of 3 assessments per day for 5 days) and study 2 (N=135; a total of 3 assessments per day for 10 days). Results: In both studies, participants found the tool highly usable (average usability score >81). By using mixed regression models, we found both common and specific results for the compliance predictors. In both study 1 and study 2, latency was significantly predicted by the day (P<.001 and P=.003, respectively). Participants showed slower responses to the notification as the days of the study progressed. In study 2 but not in study 1, latency was further predicted by individual differences in overload with the use of the app, and missing responses were accounted for by individual differences in stress reactivity to notifications (P=.04). Thus, by using a more extensive design, participants who experienced higher overload during the study were characterized by slower responses to notifications (P=.01), whereas those who experienced higher stress reactivity to the notification system were characterized by higher missing responses. Conclusions: The new tool had high levels of usability. Furthermore, the study of compliance is of enormous importance when implementing novel ESM methods, including app-based cognitive tasks. The main predictors of latency and missing responses found across studies, specifically when using extensive ESM protocols (study 2), are methodology-related variables. Future research that integrates cognitive tasks in ESM designs should take these results into consideration by performing accurate estimations of participants’ response rates to facilitate the optimal quality of novel eHealth approaches, as in this study. %M 35343900 %R 10.2196/32537 %U https://formative.jmir.org/2022/3/e32537 %U https://doi.org/10.2196/32537 %U http://www.ncbi.nlm.nih.gov/pubmed/35343900 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e27588 %T Effectiveness, Cost-effectiveness, and Cost-Utility of a Digital Smoking Cessation Intervention for Cancer Survivors: Health Economic Evaluation and Outcomes of a Pragmatic Randomized Controlled Trial %A Mujcic,Ajla %A Blankers,Matthijs %A Boon,Brigitte %A Verdonck-de Leeuw,Irma M %A Smit,Filip %A van Laar,Margriet %A Engels,Rutger %+ Erasmus School of Social and Behavioural Sciences, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, 3062PA, Netherlands, 31 30 29 59 256, amujcic@trimbos.nl %K smoking cessation %K cancer survivors %K effectiveness %K cost-effectiveness %K eHealth %D 2022 %7 17.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Smoking cessation (SC) interventions may contribute to better treatment outcomes and the general well-being of cancer survivors. Objective: This study aims to evaluate the effectiveness, cost-effectiveness, and cost-utility of a digital interactive SC intervention compared with a noninteractive web-based information brochure for cancer survivors. Methods: A health economic evaluation alongside a pragmatic 2-arm parallel-group randomized controlled trial was conducted with follow-ups at 3, 6, and 12 months. The study was conducted in the Netherlands over the internet from November 2016 to September 2019. The participants were Dutch adult smoking cancer survivors with the intention to quit smoking. In total, 165 participants were included and analyzed: 83 (50.3%) in the MyCourse group and 82 (49.7%) in the control group. In the intervention group, participants had access to a newly developed, digital, minimally guided SC intervention (MyCourse-Quit Smoking). Control group participants received a noninteractive web-based information brochure on SC. Both groups received unrestricted access to usual care. The primary outcome was self-reported 7-day smoking abstinence at the 6-month follow-up. Secondary outcomes were quality-adjusted life years gained, number of cigarettes smoked, nicotine dependence, and treatment satisfaction. For the health economic evaluation, intervention costs, health care costs, and costs stemming from productivity losses were assessed over a 12-month horizon. Results: At the 6-month follow-up, the quit rates were 28% (23/83) and 26% (21/82) in the MyCourse and control groups, respectively (odds ratio 0.47, 95% CI 0.03-7.86; P=.60). In both groups, nicotine dependence scores were reduced at 12 months, and the number of smoked cigarettes was reduced by approximately half. The number of cigarettes decreased more over time, and the MyCourse group demonstrated a significantly greater reduction at the 12-month follow-up (incidence rate ratio 0.87; 95% CI 0.76-1.00; P=.04). Intervention costs were estimated at US $193 per participant for the MyCourse group and US $74 for the control group. The mean per-participant societal costs were US $25,329 (SD US $29,137) and US $21,836 (SD US $25,792), respectively. In the cost-utility analysis, MyCourse was not preferred over the control group from a societal perspective. With smoking behavior as the outcome, the MyCourse group led to marginally better results per reduced pack-year against higher societal costs, with a mean incremental cost-effectiveness ratio of US $52,067 (95% CI US $32,515-US $81,346). Conclusions: At 6 months, there was no evidence of a differential effect on cessation rates; in both groups, approximately a quarter of the cancer survivors quit smoking and their number of cigarettes smoked was reduced by half. At 12 months, the MyCourse intervention led to a greater reduction in the number of smoked cigarettes, albeit at higher costs than for the control group. No evidence was found for a differential effect on quality-adjusted life years. Trial Registration: The Netherlands Trial Register NTR6011; https://www.trialregister.nl/trial/5434 International Registered Report Identifier (IRRID): RR2-10.1186/s12885-018-4206-z %M 35297777 %R 10.2196/27588 %U https://www.jmir.org/2022/3/e27588 %U https://doi.org/10.2196/27588 %U http://www.ncbi.nlm.nih.gov/pubmed/35297777 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e27202 %T An mHealth Intervention to Improve Medication Adherence and Health Outcomes Among Patients With Coronary Heart Disease: Randomized Controlled Trial %A Ni,Zhao %A Wu,Bei %A Yang,Qing %A Yan,Lijing L %A Liu,Changqing %A Shaw,Ryan J %+ School of Medicine, Yale University, 135 College Street, New Haven, CT, 06510, United States, 1 646 617 2232, zhao.ni@yale.edu %K mHealth %K medication adherence %K coronary disease %K blood pressure %K China %K randomized controlled trial %D 2022 %7 9.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: The treatment of many chronic illnesses involves long-term pharmaceutical therapy, but it is an ongoing challenge to find effective ways to improve medication adherence to promote good health outcomes. Cardioprotective medications can prevent the enlargement of harmful clots, cardiovascular symptoms, and poor therapeutic outcomes, such as uncontrolled high blood pressure and hyperlipidemia, for patients with coronary heart disease. Poor adherence to cardioprotective medications, however, has been reported as a global health concern among patients with coronary heart disease, and it is particularly a concern in China. Objective: This study aimed to evaluate the efficacy of a mobile health (mHealth) intervention using 2 mobile apps to improve medication adherence and health outcomes. Methods: A randomized, placebo-controlled, 2-arm parallel study was conducted in a major university-affiliated medical center located in Chengdu, China. Participants were recruited by flyers and health care provider referrals. Each participant was observed for 90 days, including a 60-day period of mHealth intervention and a 30-day period of nonintervention follow-up. The study coordinator used WeChat and Message Express to send educational materials and reminders to take medication, respectively. Participants used WeChat to receive both the educational materials and reminders. Participants in the control group only received educational materials. This study received ethics approval from the Duke Health Institutional Review Board (Pro00073395) on May 5, 2018, and was approved by West China Hospital (20170331180037). Recruitment began on May 20, 2018. The pilot phase of this study was registered on June 8, 2016, and the current, larger-scale study was retrospectively registered on January 11, 2021 (ClinicalTrials.gov). Results: We recruited 230 patients with coronary heart disease. Of these patients, 196 completed the baseline survey and received the intervention. The majority of participants were married (181/196, 92.4%), male (157/196, 80.1%), and lived in urban China (161/196, 82.1%). Participants’ average age was 61 years, and half were retired (103/191, 53.9%). More than half the participants (121/196, 61.7%) were prescribed at least 5 medications. The mean decrease in medication nonadherence score was statistically significant at both 60 days (t179=2.04, P=.04) and 90 days (t155=3.48, P<.001). Systolic blood pressure and diastolic blood pressure decreased in the experimental group but increased in the control group. The mean decrease in diastolic blood pressure was statistically significant at both 60 days (t160=2.07, P=.04) and 90 days (t164=2.21, P=.03). The mean decrease in systolic blood pressure was significantly different in the groups at 90 days (t165=3.12, P=.002). Conclusions: The proposed mHealth intervention can improve medication adherence and health outcomes, including systolic blood pressure and diastolic blood pressure. Trial Registration: ClinicalTrials.gov NCT02793830; https://clinicaltrials.gov/ct2/show/NCT02793830 and ClinicalTrials.gov NCT04703439; https://clinicaltrials.gov/ct2/show/NCT04703439 %M 35262490 %R 10.2196/27202 %U https://www.jmir.org/2022/3/e27202 %U https://doi.org/10.2196/27202 %U http://www.ncbi.nlm.nih.gov/pubmed/35262490 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e33701 %T Digital Life Coaching During Stem Cell Transplantation: Development and Usability Study %A Banerjee,Rahul %A Huang,Chiung-Yu %A Dunn,Lisa %A Knoche,Jennifer %A Ryan,Chloe %A Brassil,Kelly %A Jackson,Lindsey %A Patel,Dhiren %A Lo,Mimi %A Arora,Shagun %A Wong,Sandy W %A Wolf,Jeffrey %A Martin III,Thomas %A Dhruva,Anand %A Shah,Nina %+ Division of Hematology/Oncology, Department of Medicine, University of California San Francisco, 400 Parnassus Avenue, San Francisco, CA, 94158, United States, 1 415 353 8000, rahul.banerjee.md@gmail.com %K digital health %K life coaching %K multiple myeloma %K stem cell transplantation %K stem cell therapy %K cancer %K high-dose chemotherapy %K patient engagement %K feasibility %K digital life coaching %K mobile phone %D 2022 %7 4.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: For patients with multiple myeloma receiving high-dose chemotherapy followed by autologous stem cell transplantation (SCT), acute life disruptions and symptom burden may lead to worsened quality of life (QOL) and increased emotional distress. Digital life coaching (DLC), whereby trained coaches deliver personalized well-being–related support via phone calls and SMS text messaging, has been shown to improve QOL among SCT survivors. However, DLC has not been investigated during the acute peri-SCT period, which is generally characterized by symptomatic exacerbations and 2-week hospitalizations. Objective: We launched a single-arm pilot study to investigate the feasibility of patient engagement with DLC during this intensive period. Methods: We approached English-speaking adult patients with multiple myeloma undergoing autologous SCT at our center. Enrolled patients received 16 weeks of virtual access to a life coach beginning on day −5 before SCT. Coaches used structured frameworks to help patients identify and overcome personal barriers to well-being. Patients chose the coaching topics and preferred communication styles. Our primary endpoint was ongoing DLC engagement, defined as bidirectional conversations occurring at least once every 4 weeks during the study period. Secondary endpoints were electronic patient-reported outcome assessments of QOL, distress, and sleep disturbances. Results: Of the 20 patients who were screened, 17 (85%) chose to enroll and 15 (75%) underwent SCT as planned. Of these 15 patients (median age 65 years, range 50-81 years), 11 (73%) demonstrated ongoing DLC engagement. The median frequency of bidirectional conversations during the 3-month study period was once every 6.2 days (range 3.9-28 days). During index hospitalizations with median lengths of stay of 16 days (range 14-31 days), the median frequency of conversations was once every 5.3 days (range 2.7-15 days). Electronic patient-reported outcome assessments (94% adherence) demonstrated an expected QOL nadir during the second week after SCT. The prevalence of elevated distress was highest immediately before and after SCT, with 69% of patients exhibiting elevated distress on day −5 and on day +2. Conclusions: DLC may be feasible for older patients during intensive hospital-based cancer treatments such as autologous SCT for multiple myeloma. The limitations of our study include small sample size, selection bias among enrolled patients, and heterogeneity in DLC use. Based on the positive results of this pilot study, a larger phase 2 randomized study of DLC during SCT is underway to investigate the efficacy of DLC with regard to patient well-being. Trial Registration: ClinicalTrials.gov NCT04432818; https://clinicaltrials.gov/ct2/show/NCT04432818. %M 35039279 %R 10.2196/33701 %U https://formative.jmir.org/2022/3/e33701 %U https://doi.org/10.2196/33701 %U http://www.ncbi.nlm.nih.gov/pubmed/35039279 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 3 %P e29415 %T mHealth Interventions for Self-management of Hypertension: Framework and Systematic Review on Engagement, Interactivity, and Tailoring %A Cao,Weidan %A Milks,M Wesley %A Liu,Xiaofu %A Gregory,Megan E %A Addison,Daniel %A Zhang,Ping %A Li,Lang %+ Department of Biomedical Informatics, The Ohio State University, 250 Lincoln Tower, 1800 Cannon Drive, Columbus, OH, 43210, United States, 1 614 292 4778, lang.li@osumc.edu %K mHealth %K mobile app %K digital behavior change %K interventions %K systematic review %K hypertension %K engagement %K interactivity %K tailoring %K mobile phone %D 2022 %7 2.3.2022 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Engagement is essential for the effectiveness of digital behavior change interventions. Existing systematic reviews examining hypertension self-management interventions via mobile apps have primarily focused on intervention efficacy and app usability. Engagement in the prevention or management of hypertension is largely unknown. Objective: This systematic review explores the definition and role of engagement in hypertension-focused mobile health (mHealth) interventions, as well as how determinants of engagement (ie, tailoring and interactivity) have been implemented. Methods: A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013 to 2020, was conducted. A total of 21 studies were included in this systematic review. Results: The engagement was defined or operationalized as a microlevel concept, operationalized as interaction with the interventions (ie, frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all 3 studies that tested the relationship, increased engagement was associated with better biomedical outcomes (eg, blood pressure change). Interactivity was limited in digital behavior change interventions, as only 7 studies provided 2-way communication between users and a health care professional, and 9 studies provided 1-way communication in possible critical conditions; that is, when abnormal blood pressure values were recorded, users or health care professionals were notified. The tailoring of interventions varied at different aspects, from the tailoring of intervention content (including goals, patient education, advice and feedback from health professionals, reminders, and motivational messages) to the tailoring of intervention dose and communication mode. Tailoring was carried out in a number of ways, considering patient characteristics such as goals, preferences, disease characteristics (eg, hypertension stage and medication list), disease self-management experience levels, medication adherence rate, and values and beliefs. Conclusions: Available studies support the importance of engagement in intervention effectiveness as well as the essential roles of patient factors in tailoring, interactivity, and engagement. A patient-centered engagement framework for hypertension self-management using mHealth technology is proposed here, with the intent of facilitating intervention design and disease self-management using mHealth technology. %M 35234655 %R 10.2196/29415 %U https://mhealth.jmir.org/2022/3/e29415 %U https://doi.org/10.2196/29415 %U http://www.ncbi.nlm.nih.gov/pubmed/35234655 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e32130 %T Increasing the Effectiveness of a Physical Activity Smartphone Intervention With Positive Suggestions: Randomized Controlled Trial %A Skvortsova,Aleksandrina %A Cohen Rodrigues,Talia %A de Buisonjé,David %A Kowatsch,Tobias %A Santhanam,Prabhakaran %A Veldhuijzen,Dieuwke S %A van Middendorp,Henriët %A Evers,Andrea %+ Department of Psychology, McGill University, 1205 avenue du Docteur-Penfield, Montreal, QC, H3A 1B1, Canada, 1 4386303664, a.skvortsova@fsw.leidenuniv.nl %K eHealth %K mobile health %K physical activity %K walking %K positive suggestions %K outcome expectations %K mobile phone %D 2022 %7 1.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: eHealth interventions have the potential to increase the physical activity of users. However, their effectiveness varies, and they often have only short-term effects. A possible way of enhancing their effectiveness is to increase the positive outcome expectations of users by giving them positive suggestions regarding the effectiveness of the intervention. It has been shown that when individuals have positive expectations regarding various types of interventions, they tend to benefit from these interventions more. Objective: The main objective of this web-based study is to investigate whether positive suggestions can change the expectations of participants regarding the effectiveness of a smartphone physical activity intervention and subsequently enhance the number of steps the participants take during the intervention. In addition, we study whether suggestions affect perceived app effectiveness, engagement with the app, self-reported vitality, and fatigue of the participants. Methods: This study involved a 21-day fully automated physical activity intervention aimed at helping participants to walk more steps. The intervention was delivered via a smartphone-based app that delivered specific tasks to participants (eg, setting activity goals or looking for social support) and recorded their daily step count. Participants were randomized to either a positive suggestions group (69/133, 51.9%) or a control group (64/133, 48.1%). Positive suggestions emphasizing the effectiveness of the intervention were implemented in a web-based flyer sent to the participants before the intervention. Suggestions were repeated on days 8 and 15 of the intervention via the app. Results: Participants significantly increased their daily step count from baseline compared with 21 days of the intervention (t107=−8.62; P<.001) regardless of the suggestions. Participants in the positive suggestions group had more positive expectations regarding the app (B=−1.61, SE 0.47; P<.001) and higher expected engagement with the app (B=3.80, SE 0.63; P<.001) than the participants in the control group. No effects of suggestions on the step count (B=−22.05, SE 334.90; P=.95), perceived effectiveness of the app (B=0.78, SE 0.69; P=.26), engagement with the app (B=0.78, SE 0.75; P=.29), and vitality (B=0.01, SE 0.11; P=.95) were found. Positive suggestions decreased the fatigue of the participants during the 3 weeks of the intervention (B=0.11, SE 0.02; P<.001). Conclusions: Although the suggestions did not affect the number of daily steps, they increased the positive expectations of the participants and decreased their fatigue. These results indicate that adding positive suggestions to eHealth physical activity interventions might be a promising way of influencing subjective but not objective outcomes of interventions. Future research should focus on finding ways of strengthening the suggestions, as they have the potential to boost the effectiveness of eHealth interventions. Trial Registration: Open Science Framework 10.17605/OSF.IO/CWJES; https://osf.io/cwjes %M 35230245 %R 10.2196/32130 %U https://www.jmir.org/2022/3/e32130 %U https://doi.org/10.2196/32130 %U http://www.ncbi.nlm.nih.gov/pubmed/35230245 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 2 %P e32138 %T Text Messaging Intervention for Mental Wellness in American Indian and Alaska Native Teens and Young Adults (BRAVE Study): Analysis of User Engagement Patterns %A Wrobel,Julia %A Silvasstar,Joshva %A Peterson,Roger %A Sumbundu,Kanku %A Kelley,Allyson %A Stephens,David %A Craig Rushing,Stephanie %A Bull,Sheana %+ Colorado School of Public Health, University of Colorado, 13001 East 17th Place, Mail Stop B119, Aurora, CO, 80045, United States, 1 307 724 4585, JULIA.WROBEL@cuanschutz.edu %K American Indian %K Alaska Native %K adolescent %K mental health %K help-seeking skills, text messaging %K mHealth, behavioral intervention %K user engagement %K feasibility %K engagement %K low-touch %K intervention %D 2022 %7 25.2.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Many American Indian and Alaska Native (AI/AN or Native) communities express concern about high rates of suicide and poor mental health. Technology-based health interventions that nurture resilience, coping skills, connectedness, and help-seeking skills may be an effective strategy for promoting health and wellbeing among AI/AN youth. The Northwest Portland Area Indian Health Board designed the BRAVE intervention for AI/AN youth. BRAVE is delivered via SMS text messaging and includes role model videos, mental wellness strategies, links to culturally relevant resources, and social support from family and friends. Objective: The aim of this study is to explore system data from the BRAVE intervention to determine patterns of user engagement and differences in psychosocial outcomes based on the number of clicks on BRAVE content. Methods: The BRAVE study included 1030 AI/AN teens and young adults nationwide (15 to 24 years old). The message series in the BRAVE and STEM study arms included 3 to 5 SMS text messages per week, featuring 1 role model video and 1 image per week. Messages were sent out via Mobile Commons (Upland Software Inc), a mobile messaging provider that supports text, picture, and video SMS. Results: Of the 509 participants in the original BRAVE analysis, 270 had sufficient data to analyze user engagement, with at least 1 trackable click on a study SMS text message. Of the 270, 184 (68.1%) were female, 50 (18.5%) were male, and 36 (13.3%) selected another gender category. The average participant was 20.6 years old, with a minimum and maximum age of 15 and 26 years. Most participants had relatively low engagement measured by the number of clicks (median 2; mean 3.4), although others clicked message content as many as 49 times. Users engaged most frequently with the YouTube-based content (viewing 1 of 7 role model videos), with 64.8% (175/270) of total clicks coming from the role model videos, and earlier episodes receiving the highest number of clicks. Most baseline psychosocial measures were not significantly associated with the number of links clicked. However, help-seeking behavior was highly significant (P<.001), with a rate ratio of 0.82 (0.73, 0.92), indicating that each 1-unit increase in help-seeking score at baseline was associated with an 18% decrease in the expected number of study content clicks. Conclusions: This is the first study to set initial standards for assessing user engagement in an mHealth intervention. Our work underscores the feasibility of exploring the impact of engagement on intended outcomes, allowing for more precise exploration of the dose-response relationship that may be realized through these low-touch interventions that offer promising potential for reaching high numbers of program participants. Trial Registration: ClinicalTrials.gov NCT04979481; https://clinicaltrials.gov/ct2/show/NCT04979481 %M 35212633 %R 10.2196/32138 %U https://formative.jmir.org/2022/2/e32138 %U https://doi.org/10.2196/32138 %U http://www.ncbi.nlm.nih.gov/pubmed/35212633 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 5 %N 1 %P e32274 %T Changes in Use of a Leisure Activity Mobile App for Children With Disabilities During the COVID-19 Pandemic: Retrospective Study %A Yoo,Paul Yejong %A Movahed,Mehrnoosh %A Rue,Ishana %A Santos,Carlos Denner Dos %A Majnemer,Annette %A Shikako,Keiko %+ Faculty of Medicine and Health Sciences, McGill University, 3654 prom Sir-William-Osler, Montreal, QC, H3G 1Y5, Canada, 1 514 398 4400 ext 0802, keiko.thomas@mcgill.ca %K COVID-19 %K participation %K childhood disability %K online leisure %K app engagement %K mHealth %K children %K parents %K mobile apps %K mobile health %K digital health %K pandemic %K online leisure activities %K user engagement %K app usability %D 2022 %7 25.2.2022 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: Participation in leisure activities is essential for child development and a human right as per the United Nations Convention on the Rights of the Child. Children with disabilities face several restrictions when participating in leisure activities as compared to same age peers without disabilities. Access to information about accessible, inclusive leisure activities is one of the barriers limiting participation, and one potential health promotion strategy is to provide access to information to increase participation. The Jooay App is a mobile app listing such activities in Canada and Australia. With the COVID-19 global pandemic and subsequent public health measures, most community-based facilities providing the activities listed on Jooay were closed. The app therefore started listing online activities offered with the expectation of continuing to provide information for families and understanding the extent to which users relied on the mobile app as a tool to identify new safe leisure opportunities. Objective: This study aims to describe the engagement of the Jooay app before and during COVID-19, and to estimate the extent to which the listing of online activities was related to the engagement of the Jooay app. Methods: We conducted a retrospective study comparing Jooay app use between March 2020 and February 2021 to the engagement between March 2019 and February 2020 by Jooay users. Spearman rank correlations were carried out to identify associations between the activities listed and the users’ engagement from May 2020 to February 2021. Results: Active engagement with the Jooay app from March 2020 to February 2021 dropped by an average of 135 engagements (64.2%) compared to engagements in 2019-2020. The largest monthly drop in engagement was observed in May 2020 by 239 engagements (88.8%). There was a strong positive correlation between the number of active users and the number of online activities listed on the app (rs=0.900). Conclusions: The engagement with the Jooay App presented an expected decrease during the first wave of the COVID-19 pandemic. The addition of online adapted leisure activities to the app’s listings during the pandemic increased app use. Access to information about inclusive activities is a barrier for children with disabilities to engage in leisure. Mobile health solutions can be responsive to contextual factors and consider the social determinants of health such as socioeconomic and public health emergency issues that can impact the participation of vulnerable populations such as children with disabilities and help eliminate barriers to participation. The provision of online leisure opportunities during the pandemic could facilitate participation in these activities during the pandemic and beyond, which is essential and beneficial for the physical and mental well-being of children with disabilities and their families. %M 35100129 %R 10.2196/32274 %U https://pediatrics.jmir.org/2022/1/e32274 %U https://doi.org/10.2196/32274 %U http://www.ncbi.nlm.nih.gov/pubmed/35100129 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 10 %N 1 %P e31570 %T A Serious Puzzle Game to Enhance Adherence to Antirheumatic Drugs in Patients With Rheumatoid Arthritis: Systematic Development Using Intervention Mapping %A Pouls,Bart PH %A Bekker,Charlotte L %A van Dulmen,Sandra %A Vriezekolk,Johanna E %A van den Bemt,Bart JF %+ Department of Rheumatology Research, Sint Maartenskliniek, Hengstdal 3, Nijmegen, 6574NA, Netherlands, 31 612502678, b.pouls@maartenskliniek.nl %K medication adherence %K serious game %K eHealth %K rheumatoid arthritis %K intervention mapping %K intervention development %D 2022 %7 18.2.2022 %9 Original Paper %J JMIR Serious Games %G English %X Background: Patients’ implicit attitudes toward medication need and concerns may influence their adherence. Targeting these implicit attitudes by combining game-entertainment with medication-related triggers might improve medication adherence in patients with rheumatoid arthritis (RA). Objective: The aim of this study was to describe the systematic development of a serious game to enhance adherence to antirheumatic drugs by using intervention mapping. Methods: A serious game was developed using the intervention mapping framework guided by a multidisciplinary expert group, which proceeded along 6 steps: (1) exploring the problem by assessing the relationship between medication adherence and implicit attitudes, (2) defining change objectives, (3) selecting evidence-based behavior change techniques that focused on adjusting implicit attitudes, (4) designing the intervention, (5) guaranteeing implementation by focusing on intrinsic motivation, and (6) planning a scientific evaluation. Results: Based on the problem assessment and guided by the Dual-Attitude Model, implicit negative and illness-related attitudes of patients with RA were defined as the main target for the intervention. Consequently, the change objective was “after the intervention, participants have a more positive attitude toward antirheumatic drugs.” Attention bias modification, evaluative conditioning, and goal priming were the techniques chosen to implicitly target medication needs. These techniques were redesigned into medication-related triggers and built in the serious puzzle game. Thirty-seven patients with RA tested the game at several stages. Intrinsic motivation was led by the self-determination theory and addressed the 3 needs, that is, competence, autonomy, and relatedness. The intervention will be evaluated in a randomized clinical trial that assesses the effect of playing the serious game on antirheumatic drug adherence. Conclusions: We systematically developed a serious game app to enhance adherence to antirheumatic drugs among patients with RA by using the intervention mapping framework. This paper could serve as a guideline for other health care providers when developing similar interventions. %M 35179510 %R 10.2196/31570 %U https://games.jmir.org/2022/1/e31570 %U https://doi.org/10.2196/31570 %U http://www.ncbi.nlm.nih.gov/pubmed/35179510 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 2 %P e25948 %T Positive Coping as a Mediator of Mobile Health Intervention Effects on Quality of Life Among People Living With HIV: Secondary Analysis of the Randomized Controlled Trial Run4Love %A Zeng,Yu %A Guo,Yan %A Ho,Rainbow Tin Hung %A Zhu,Mengting %A Zeng,Chengbo %A Monroe-Wise,Aliza %A Li,Yiran %A Qiao,Jiaying %A Zhang,Hanxi %A Cai,Weiping %A Li,Linghua %A Liu,Cong %+ Department of Medical Statistic, School of Public Health, Sun Yat-sen University, Guangzhou, China, 86 020 87334202, Yan.Guo1@umassmed.edu %K mediation effect %K mobile health %K quality of life %K positive coping %K HIV %K randomized controlled trial %D 2022 %7 17.2.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: The effectiveness of psychosocial interventions on quality of life (QOL) among people living with HIV has been validated, including mobile health (mHealth) interventions. However, it is unclear which components of such interventions account for these effects. Objective: This study aims to examine positive coping as a potential mediator of the effects of an mHealth intervention on QOL among people living with HIV. Methods: For this secondary analysis, we used data from an mHealth-based randomized controlled trial, Run4Love, which was conducted to improve QOL and mental health outcomes of people living with HIV. A total of 300 participants were randomly assigned to the intervention group to receive the adapted cognitive-behavioral stress management courses and regular physical activity promotion or the waitlist control group in a 1:1 ratio. Our analysis focused on positive coping and QOL, which were repeatedly measured at baseline and at 3-, 6-, and 9-month follow-ups. Latent growth curve models were constructed to explore the mediating role of positive coping in the effects of the mHealth intervention on QOL. Results: Positive coping served as a mediator in the effect of the mHealth intervention on QOL for up to 9 months. The mHealth intervention had a significant and positive indirect effect on the slope of QOL via the slope of positive coping (b=2.592×1.620=4.198, 95% CI 1.189-7.207, P=.006). The direct effect of the intervention was not significant (b=0.552, 95% CI −2.154 to 3.258, P=.69) when controlling for the mediator. Conclusions: The longitudinal findings suggest that positive coping could be a crucial mediator of the mHealth intervention in enhancing QOL among people living with HIV. These findings underscore the importance of improving positive coping skills in mHealth interventions to improve QOL among people living with HIV. %M 35175209 %R 10.2196/25948 %U https://www.jmir.org/2022/2/e25948 %U https://doi.org/10.2196/25948 %U http://www.ncbi.nlm.nih.gov/pubmed/35175209 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 2 %P e27735 %T Attrition Within Digital Health Interventions for People With Multiple Sclerosis: Systematic Review and Meta-analysis %A Bevens,William %A Weiland,Tracey %A Gray,Kathleen %A Jelinek,George %A Neate,Sandra %A Simpson-Yap,Steve %+ Centre for Epidemiology and Biostatistics, The University of Melbourne, 207 Bouverie Street, Carlton, 3053, Australia, 61 0498337231, william.bevens@unimelb.edu.au %K digital health %K meta-analysis %K self-management %K eHealth %K attrition %K digital health interventions %K DHI %K multiple sclerosis %K MS %K randomized controlled trials %D 2022 %7 9.2.2022 %9 Review %J J Med Internet Res %G English %X Background: Digital health interventions have revolutionized multiple sclerosis (MS) care by supporting people with MS to better self-manage their disease. It is now understood that the technological elements that comprise this category of digital health interventions can influence participant engagement in self-management programs, and people with MS can experience significant barriers, influenced by these elements, to remaining engaged during a period of learning. It is essential to explore the influence of technological elements in mitigating attrition. Objective: This study aimed to examine the study design and technological elements of documented digital health interventions targeted at people with MS—digital health interventions that were intended to support a program of engagement over a defined period—and to explore how these correlated with attrition among participants of randomized controlled trials (RCTs). Methods: We conducted a systematic review and meta-analysis of RCTs (n=32) describing digital health self-management interventions for people with MS. We analyzed attrition in included studies, using a random-effects model and meta-regression to measure the association between potential moderators. Results: There were no measured differences in attrition between the intervention and control arms; however, some of the heterogeneity observed was explained by the composite technological element score. The pooled attrition rates for the intervention and control arms were 14.7% and 15.6%, respectively. Conclusions: This paper provides insight into the technological composition of digital health interventions designed for people with MS and describes the degree of attrition in both study arms. This paper will aid in the design of future studies in this area, particularly for digital health interventions of this type. %M 35138262 %R 10.2196/27735 %U https://www.jmir.org/2022/2/e27735 %U https://doi.org/10.2196/27735 %U http://www.ncbi.nlm.nih.gov/pubmed/35138262 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 2 %P e31877 %T Using Smartphones to Reduce Research Burden in a Neurodegenerative Population and Assessing Participant Adherence: A Randomized Clinical Trial and Two Observational Studies %A Beukenhorst,Anna L %A Burke,Katherine M %A Scheier,Zoe %A Miller,Timothy M %A Paganoni,Sabrina %A Keegan,Mackenzie %A Collins,Ella %A Connaghan,Kathryn P %A Tay,Anna %A Chan,James %A Berry,James D %A Onnela,Jukka-Pekka %+ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 4th Floor, 677 Huntington Avenue, Boston, MA, MA 02115, United States, 1 (617) 4951000, beuk@hsph.harvard.edu %K digital phenotyping %K mobile health %K trial %K smartphones %K attrition %K mobile phone %D 2022 %7 4.2.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Smartphone studies provide an opportunity to collect frequent data at a low burden on participants. Therefore, smartphones may enable data collection from people with progressive neurodegenerative diseases such as amyotrophic lateral sclerosis at high frequencies for a long duration. However, the progressive decline in patients’ cognitive and functional abilities could also hamper the feasibility of collecting patient-reported outcomes, audio recordings, and location data in the long term. Objective: The aim of this study is to investigate the completeness of survey data, audio recordings, and passively collected location data from 3 smartphone-based studies of people with amyotrophic lateral sclerosis. Methods: We analyzed data completeness in three studies: 2 observational cohort studies (study 1: N=22; duration=12 weeks and study 2: N=49; duration=52 weeks) and 1 clinical trial (study 3: N=49; duration=20 weeks). In these studies, participants were asked to complete weekly surveys; weekly audio recordings; and in the background, the app collected sensor data, including location data. For each of the three studies and each of the three data streams, we estimated time-to-discontinuation using the Kaplan–Meier method. We identified predictors of app discontinuation using Cox proportional hazards regression analysis. We quantified data completeness for both early dropouts and participants who remained engaged for longer. Results: Time-to-discontinuation was shortest in the year-long observational study and longest in the clinical trial. After 3 months in the study, most participants still completed surveys and audio recordings: 77% (17/22) in study 1, 59% (29/49) in study 2, and 96% (22/23) in study 3. After 3 months, passively collected location data were collected for 95% (21/22), 86% (42/49), and 100% (23/23) of the participants. The Cox regression did not provide evidence that demographic characteristics or disease severity at baseline were associated with attrition, although it was somewhat underpowered. The mean data completeness was the highest for passively collected location data. For most participants, data completeness declined over time; mean data completeness was typically lower in the month before participants dropped out. Moreover, data completeness was lower for people who dropped out in the first study month (very few data points) compared with participants who adhered long term (data completeness fluctuating around 75%). Conclusions: These three studies successfully collected smartphone data longitudinally from a neurodegenerative population. Despite patients’ progressive physical and cognitive decline, time-to-discontinuation was higher than in typical smartphone studies. Our study provides an important benchmark for participant engagement in a neurodegenerative population. To increase data completeness, collecting passive data (such as location data) and identifying participants who are likely to adhere during the initial phase of a study can be useful. Trial Registration: ClinicalTrials.gov NCT03168711; https://clinicaltrials.gov/ct2/show/NCT03168711 %M 35119373 %R 10.2196/31877 %U https://mhealth.jmir.org/2022/2/e31877 %U https://doi.org/10.2196/31877 %U http://www.ncbi.nlm.nih.gov/pubmed/35119373 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 2 %P e33189 %T Exploring and Characterizing Patient Multibehavior Engagement Trails and Patient Behavior Preference Patterns in Pathway-Based mHealth Hypertension Self-Management: Analysis of Use Data %A Wu,Dan %A Huyan,Xiaoyuan %A She,Yutong %A Hu,Junbin %A Duan,Huilong %A Deng,Ning %+ College of Biomedical Engineering and Instrument Science, Ministry of Education Key Laboratory of Biomedical Engineering, Zhejiang University, 38 Zheda Rd, Zhouyiqing Bldg 512, Yuquan Campus, Hangzhou, 310000, China, 86 571 2295 2693, zju.dengning@gmail.com %K hypertension %K mobile health %K patient behavior %K engagement %K data analysis %D 2022 %7 3.2.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Hypertension is a long-term medical condition. Mobile health (mHealth) services can help out-of-hospital patients to self-manage. However, not all management is effective, possibly because the behavior mechanism and behavior preferences of patients with various characteristics in hypertension management were unclear. Objective: The purpose of this study was to (1) explore patient multibehavior engagement trails in the pathway-based hypertension self-management, (2) discover patient behavior preference patterns, and (3) identify the characteristics of patients with different behavior preferences. Methods: This study included 863 hypertensive patients who generated 295,855 use records in the mHealth app from December 28, 2016, to July 2, 2020. Markov chain was used to infer the patient multibehavior engagement trails, which contained the type, quantity, time spent, sequence, and transition probability value (TP value) of patient behavior. K-means algorithm was used to group patients by the normalized behavior preference features: the number of behavioral states that a patient performed in each trail. The pages in the app represented the behavior states. Chi-square tests, Z-test, analyses of variance, and Bonferroni multiple comparisons were conducted to characterize the patient behavior preference patterns. Results: Markov chain analysis revealed 3 types of behavior transition (1-way transition, cycle transition, and self-transition) and 4 trails of patient multibehavior engagement. In perform task trail (PT-T), patients preferred to start self-management from the states of task blood pressure (BP), task drug, and task weight (TP value 0.29, 0.18, and 0.20, respectively), and spent more time on the task food state (35.87 s). Some patients entered the states of task BP and task drug (TP value 0.20, 0.25) from the reminder item state. In the result-oriented trail (RO-T), patients spent more energy on the ranking state (19.66 s) compared to the health report state (13.25 s). In the knowledge learning trail (KL-T), there was a high probability of cycle transition (TP value 0.47, 0.31) between the states of knowledge list and knowledge content. In the support acquisition trail (SA-T), there was a high probability of self-transition in the questionnaire (TP value 0.29) state. Cluster analysis discovered 3 patient behavior preference patterns: PT-T cluster, PT-T and KL-T cluster, and PT-T and SA-T cluster. There were statistically significant associations between the behavior preference pattern and gender, education level, and BP. Conclusions: This study identified the dynamic, longitudinal, and multidimensional characteristics of patient behavior. Patients preferred to focus on BP, medications, and weight conditions and paid attention to BP and medications using reminders. The diet management and questionnaires were complicated and difficult to implement and record. Competitive methods such as ranking were more likely to attract patients to pay attention to their own self-management states. Female patients with lower education level and poorly controlled BP were more likely to be highly involved in hypertension health education. %M 35113032 %R 10.2196/33189 %U https://mhealth.jmir.org/2022/2/e33189 %U https://doi.org/10.2196/33189 %U http://www.ncbi.nlm.nih.gov/pubmed/35113032 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 2 %P e31565 %T Real-world Implementation of a Smartphone-Based Psychoeducation Program for Bipolar Disorder: Observational Ecological Study %A García-Estela,Aitana %A Cantillo,Jordi %A Angarita-Osorio,Natalia %A Mur-Milà,Estanislao %A Anmella,Gerard %A Pérez,Víctor %A Vieta,Eduard %A Hidalgo-Mazzei,Diego %A Colom,Francesc %+ Mental Health Research Group, Hospital del Mar Medical Research Institute (IMIM), Office 202, PRBB Building, Doctor Aiguader, 88, Barcelona, 08003, Spain, 34 933160400 ext 1493, fcolom@imim.es %K bipolar disorder %K psychoeducation %K smartphone %K app %K SIMPLe %K Intervention %K mobile phone %D 2022 %7 2.2.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: SIMPLe is an internet‐delivered self‐management mobile app for bipolar disorder (BD) designed to combine technology with evidence-based interventions and facilitate access to psychoeducational content. The SIMPLe app was launched to the real world to make it available worldwide within the context of BD treatment. Objective: The main aims of this study are as follows: to describe app use, engagement, and retention rates based on server data; to identify patterns of user retention over the first 6-month follow-up of use; and to explore potential factors contributing to discontinuation of app use. Methods: This was an observational ecological study in which we pooled available data from a real-world implementation of the SIMPLe app. Participation was open on the project website, and the data-collection sources were a web-based questionnaire on clinical data and treatment history administered at inclusion and at 6 months, subjective data gathered through continuous app use, and the use patterns captured by the app server. Characteristics and engagement of regular users, occasional users, and no users were compared using 2-tailed t tests or analysis of variance or their nonparametric equivalent. Survival analysis and risk functions were applied to regular users’ data to examine and compare use and user retention. In addition, a user evaluation analysis was performed based on satisfaction, perceived usefulness, and reasons to discontinue app use. Results: We included 503 participants with data collected between 2016 and 2018, of whom 77.5% (n=390) used the app. Among the app users, 44.4% (173/390) completed the follow-up assessment, and data from these participants were used in our analyses. Engagement declined gradually over the first 6 months of use. The probability of retention of the regular users after 1 month of app use was 67.4% (263/390; 95% CI 62.7%-72.4%). Age (P=.002), time passed since illness onset (P<.001), and years since diagnosis of BD (P=.048) correlate with retention duration. In addition, participants who had been diagnosed with BD for longer used the app on more days (mean 97.73, SD 69.15 days; P=.002) than those who had had a more recent onset (mean 66.49, SD 66.18 days; P=.002) or those who had been diagnosed more recently (mean 73.45, SD 66 days; P=.01). Conclusions: The user retention rate of the app decreased rapidly after each month until reaching only one-third of the users at 6 months. There exists a strong association between age and app engagement of individuals with BD. Other variables such as years lived with BD, diagnosis of an anxiety disorder, and taking antipsychotics seem relevant as well. Understanding these associations can help in the definition of the most suitable user profiles for predicting trends of engagement, optimization of app prescription, and management. %M 35107440 %R 10.2196/31565 %U https://www.jmir.org/2022/2/e31565 %U https://doi.org/10.2196/31565 %U http://www.ncbi.nlm.nih.gov/pubmed/35107440 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 9 %N 1 %P e31349 %T The Effect of Mobile Care Delivery on Clinically Meaningful Outcomes, Satisfaction, and Engagement Among Physical Therapy Patients: Observational Retrospective Study %A Beresford,Lauren %A Norwood,Todd %+ Omada Health Inc, 500 Sansome Street, Suite 200, San Francisco, CA, 94111, United States, 1 6197642287, lauren.beresford@omadahealth.com %K physical therapy %K mobile apps %K engagement %K health care delivery %D 2022 %7 2.2.2022 %9 Original Paper %J JMIR Rehabil Assist Technol %G English %X Background: Musculoskeletal care is now delivered via mobile apps as a health care benefit. Although preliminary evidence shows that the clinical outcomes of mobile musculoskeletal care are comparable with those of in-person care, no research has examined the features of app-based care that secure these outcomes. Objective: Drawing on the literature around in-person physical therapy, this study examines how patient-provider relationships and program engagement in app-based physical therapy affect clinically meaningful improvements in pain, function, and patient satisfaction. It then evaluates the effects of patient-provider relationships forged through in-app messages or video visits and timely, direct access to care on patients’ engagement in their recovery. Methods: We conducted an observational, retrospective study of 814 pre- and postsurveyed participants enrolled in a mobile app physical therapy program where physical therapists prescribed workouts, education, and therapeutic activities after a video evaluation from February 2019 to December 2020. We estimated generalized linear models with logit functions to evaluate the effect of program engagement on clinical outcomes, minimal clinically important differences (MCIDs) in pain (ΔVisual Analogue Scale ≤−1.5) and function (ΔPatient Specific Functional Scale ≥1.3), and the effects of patient-provider relationships and clinical outcomes on patient satisfaction—participant reported likelihood to recommend the program (Net Promoter Scores of 9-10). We estimated Poisson generalized linear models to evaluate the effects of stronger patient-provider relationships and timely access to physical therapy within 24 hours on engagement including the number of weekly workouts and weeks in the program. Results: The odds that participants (N=814) had a pain MCID increased by 13% (odds ratio [OR] 1.13, 95% CI 1.04-1.23; P=.003) with each weekly workout and the odds of a function MCID by 4% (OR 1.04, 95% CI 1.00-1.08; P=.03) with each week in the program. Participants with MCIDs in function and large changes in pain (Δ Visual Analogue Scale ≤−3.5) were 1.85 (95% CI 1.17-2.93; P=.01) and 2.84 times (95% CI 1.68-4.78; P<.001) more satisfied, respectively. Those with video follow-up visits were 2 to 3 times (P=.01) more satisfied. Each physical therapist’s message increased weekly workouts by 11% (OR 1.11, 95% CI 1.07-1.16; P<.001). Video follow-up visits increased weekly workouts by at least 16% (OR 1.16, 95% CI 1.04-1.29; P=.01) and weeks in the program at least 8% (OR 1.08, 95% CI 1.01-1.14; P=.02). Access was associated with a 14% increase (OR 1.14, 95% CI 1.05-1.24; P=.003) in weekly workouts. Conclusions: Similar to in-person care, program engagement positively affects clinical outcomes, and strong patient-provider relationships positively affect satisfaction. In app-based physical therapy, clinical outcomes positively affect patient satisfaction. Timely access to care and strong patient-provider relationships, particularly those forged through video visits, affect engagement. %M 35107436 %R 10.2196/31349 %U https://rehab.jmir.org/2022/1/e31349 %U https://doi.org/10.2196/31349 %U http://www.ncbi.nlm.nih.gov/pubmed/35107436 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 1 %P e30583 %T Investigating When, Which, and Why Users Stop Using a Digital Health Intervention to Promote an Active Lifestyle: Secondary Analysis With A Focus on Health Action Process Approach–Based Psychological Determinants %A Schroé,Helene %A Crombez,Geert %A De Bourdeaudhuij,Ilse %A Van Dyck,Delfien %+ Department of Movement and Sports Sciences, Faculty of Medicine and Health, Ghent University, Watersportlaan 2, Ghent, 9000, Belgium, 32 9264 63 63, helene.schroe@ugent.be %K digital health %K psychosocial determinants %K health action process approach %K physical activity %K sedentary behavior %K attrition %K dropout %K mobile health %K healthy life style %K health behaviors %D 2022 %7 31.1.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Digital health interventions have gained momentum to change health behaviors such as physical activity (PA) and sedentary behavior (SB). Although these interventions show promising results in terms of behavior change, they still suffer from high attrition rates, resulting in a lower potential and accessibility. To reduce attrition rates in the future, there is a need to investigate the reasons why individuals stop using the interventions. Certain demographic variables have already been related to attrition; however, the role of psychological determinants of behavior change as predictors of attrition has not yet been fully explored. Objective: The aim of this study was to examine when, which, and why users stopped using a digital health intervention. In particular, we aimed to investigate whether psychological determinants of behavior change were predictors for attrition. Methods: The sample consisted of 473 healthy adults who participated in the intervention MyPlan 2.0 to promote PA or reduce SB. The intervention was developed using the health action process approach (HAPA) model, which describes psychological determinants that guide individuals in changing their behavior. If participants stopped with the intervention, a questionnaire with 8 question concerning attrition was sent by email. To analyze when users stopped using the intervention, descriptive statistics were used per part of the intervention (including pre- and posttest measurements and the 5 website sessions). To analyze which users stopped using the intervention, demographic variables, behavioral status, and HAPA-based psychological determinants at pretest measurement were investigated as potential predictors of attrition using logistic regression models. To analyze why users stopped using the intervention, descriptive statistics of scores to the attrition-related questionnaire were used. Results: The study demonstrated that 47.9% (227/473) of participants stopped using the intervention, and drop out occurred mainly in the beginning of the intervention. The results seem to indicate that gender and participant scores on the psychological determinants action planning, coping planning, and self-monitoring were predictors of first session, third session, or whole intervention completion. The most endorsed reasons to stop using the intervention were the time-consuming nature of questionnaires (55%), not having time (50%), dissatisfaction with the content of the intervention (41%), technical problems (39%), already meeting the guidelines for PA/SB (31%), and, to a lesser extent, the experience of medical/emotional problems (16%). Conclusions: This study provides some directions for future studies. To decrease attrition, it will be important to personalize interventions on different levels, questionnaires (either for research purposes or tailoring) should be kept to a minimum especially in the beginning of interventions by, for example, using objective monitoring devices, and technical aspects of digital health interventions should be thoroughly tested in advance. Trial Registration: ClinicalTrials.gov NCT03274271; https://clinicaltrials.gov/ct2/show/NCT03274271 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3456-7 %M 35099400 %R 10.2196/30583 %U https://mhealth.jmir.org/2022/1/e30583 %U https://doi.org/10.2196/30583 %U http://www.ncbi.nlm.nih.gov/pubmed/35099400 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 1 %P e32404 %T Exploring Children’s Engagement in Monitoring Indoor Air Quality: Longitudinal Study %A Kim,Sunyoung %A Sohanchyk,Gregory %+ School of Communication and Information, Rutgers University, 4 Huntington Street, New Brunswick, NJ, 08901, United States, 1 8489327585, sunyoung.kim@rutgers.edu %K children %K indoor air quality %K mobile app %K awareness %K longitudinal deployment %D 2022 %7 21.1.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Indoor air pollution is harmful to everyone, but children are of particular concern, as they are more vulnerable to its adverse health effects from air pollutants. Although mobile technology is increasingly being designed to support monitoring and improving air quality indoors, little attention has been paid to its use by and for children. Previously, we created inAirKids, a child-friendly device to promote children’s engagement with monitoring indoor air quality through a participatory design process. The next step is to evaluate its usability in the real world. Objective: The aim of this study is to investigate how inAirKids affects children’s understanding of and engagement with indoor air quality through a longitudinal field deployment study. Methods: We deployed inAirKids in the homes of 9 children aged between 6 and 7 years, and investigated their use for up to 16 weeks by conducting semistructured, biweekly interviews. Results: The results show that participants promptly engaged with inAirKids but quickly lost interest in it owing to the lack of engaging factors to sustain engagement. In addition, we identified 2 design considerations that can foster sustained engagement of children with monitoring indoor air quality: design interactivity for engaging in continuity and corporate hands-on activities as part of indoor air quality monitoring for experiential learning. Conclusions: Our findings shed light on the potential to promote the engagement of children in indoor air quality as well as considerations for designing a child-friendly digital device. To the best of our knowledge, this is the first longitudinal field deployment to investigate how to engage children in monitoring indoor air quality. %M 35060916 %R 10.2196/32404 %U https://formative.jmir.org/2022/1/e32404 %U https://doi.org/10.2196/32404 %U http://www.ncbi.nlm.nih.gov/pubmed/35060916 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 1 %P e24239 %T A Digital Intervention for Respiratory Tract Infections (Internet Dr): Process Evaluation to Understand How to Support Self-care for Minor Ailments %A Miller,Sascha %A Yardley,Lucy %A Smith,Peter %A Weal,Mark %A Anderson,Alexander %A Stuart,Beth %A Little,Paul %A Morrison,Leanne %+ Center for Clinical and Community Applications of Health Psychology, Department of Psychology, University of Southampton, Building 44, Highfield Campus, Southampton, SO17 1BJ, United Kingdom, 44 02380595000, S.Miller@soton.ac.uk %K illness behavior %K self-care %K internet %K evaluation studies %K respiratory tract infection %K mobile phone %D 2022 %7 19.1.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Approximately 57 million physician appointments annually in the United Kingdom are for minor ailments. These illnesses could be self-cared for, which would potentially lower patients’ anxiety, increase their confidence, and be more convenient. In a randomized controlled trial of the Internet Dr digital intervention, patients with access to the intervention had fewer consultations for respiratory tract infections (RTIs). Having established intervention efficacy, further examination of trial data is required to understand how the intervention works. Objective: This paper reports a process evaluation of Internet Dr usage by the intervention group. The evaluation aims to demonstrate how meaningful usage metrics (ie, interactions that are specific and relevant to the intervention) can be derived from the theoretical principles underlying the intervention, then applied to examine whether these interactions are effective in supporting self-care for RTIs, for whom, and at what time. Methods: The Internet Dr trial recorded patients’ characteristics and usage data over 24 weeks. At follow-up, users reported whether their levels of enablement to cope with their illness changed over the trial period. The Medical Research Council process evaluation guidance and checklists from the framework for Analyzing and Measuring Usage and Engagement Data were applied to structure research questions examining associations between usage and enablement. Results: Viewing pages containing advice on caring for RTIs were identified as a meaningful metric for measuring intervention usage. Almost half of the users (616/1491, 42.31%) viewed at least one advice page, with most people (478/616, 77.6%) accessing them when they initially enrolled in the study. Users who viewed an advice page reported increased enablement to cope with their illness as a result of having participated in the study compared with users who did not (mean 2.12, SD 2.92 vs mean 1.65, SD 3.10; mean difference 0.469, 95% CI 0.082-0.856). The target population was users who had visited their general practitioners for an RTI in the year before the trial, and analyses revealed that this group was more likely to access advice pages (odds ratio 1.35, 95% CI 1.159-1.571; P<.001). Conclusions: The process evaluation identifies viewing advice pages as associated with increased enablement to self-care, even when accessed in the absence of a RTI, meaning that dissemination activities need not be restricted to targeting users who are ill. The intervention was effective at reaching the target population of users who had previously consulted their general practitioners. However, attrition before reaching advice pages was high, highlighting the necessity of prioritizing access during the design phase. These findings provide guidance on how the intervention may be improved and disseminated and have wider implications for minor ailment interventions. %M 35044317 %R 10.2196/24239 %U https://formative.jmir.org/2022/1/e24239 %U https://doi.org/10.2196/24239 %U http://www.ncbi.nlm.nih.gov/pubmed/35044317 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 1 %P e30026 %T Engagement Strategies to Improve Adherence and Retention in Web-Based Mindfulness Programs: Systematic Review %A Winter,Natalie %A Russell,Lahiru %A Ugalde,Anna %A White,Victoria %A Livingston,Patricia %+ Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, 1 Gheringhap Street, Geelong, 3220, Australia, 61 3 5227 1100, n.heynsbergh@deakin.edu.au %K chronic disease %K chronic illness %K digital health %K digital technology %K internet mindfulness %K mindfulness based stress reduction %K patient dropouts %K mobile phone %D 2022 %7 12.1.2022 %9 Review %J J Med Internet Res %G English %X Background: Web-based mindfulness programs may be beneficial in improving the well-being outcomes of those living with chronic illnesses. Adherence to programs is a key indicator in improving outcomes; however, with the digitization of programs, it is necessary to enhance engagement and encourage people to return to digital health platforms. More information is needed on how engagement strategies have been used in web-based mindfulness programs to encourage adherence. Objective: The aim of this study is to develop a list of engagement strategies for web-based mindfulness programs and evaluate the impact of engagement strategies on adherence. Methods: A narrative systematic review was conducted across the MEDLINE Complete, CINAHL Complete, APA PsycINFO, and Embase databases and followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Articles were screened using the population, intervention, comparator, and outcome framework. Adults aged >18 years with chronic health conditions were included in the study. Mindfulness interventions, including those in combination with mindfulness-based cognitive therapy, delivered on the web through the internet or smartphone technology were included. Interventions lasted at least 2 weeks. Studies with a randomized controlled trial design or a pilot randomized controlled trial design were included. Engagement strategies, including web-based program features and facilitator-led strategies, adherence, and retention, were included. Results: A total of 1265 articles were screened, of which 19 were relevant and were included in the review. On average, 70.98% (2258/3181) of the study participants were women with a mean age of 46 (SD 13) years. Most commonly, mindfulness programs were delivered to people living with mental health conditions (8/19, 42%). Of the 19 studies, 8 (42%) used only program features to encourage adherence, 5 (26%) used facilitator-led strategies, and 6 (32%) used a combination of the two. Encouraging program adherence was the most common engagement strategy used, which was used in 77% (10/13) of the facilitator-led studies and 57% (8/14) of the program feature studies. Nearly two-thirds (63%) of the studies provided a definition of adherence, which varied between 50% and 100% completion across studies. The overall mean participant compliance to the mindfulness programs was 56% (SD 15%). Most studies (10/19, 53%) had a long-term follow-up, with the most common follow-up period being 12 weeks after intervention (3/10, 30%). After the intervention, the mean retention was 78% (SD 15%). Conclusions: Engagement strategies in web-based mindfulness programs comprise reminders to use the program. Other features may be suitable for encouraging adherence to interventions, and a facilitator-led component may result in higher retention. There is variance in the way adherence is measured, and intervention lengths and follow-up periods are inconsistent. More thorough reporting and a standardized framework for measuring adherence are needed to more accurately assess adherence and engagement strategies. %M 35019851 %R 10.2196/30026 %U https://www.jmir.org/2022/1/e30026 %U https://doi.org/10.2196/30026 %U http://www.ncbi.nlm.nih.gov/pubmed/35019851 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 1 %P e31381 %T Educators' Perspectives on Integrating Technology Into Sexual Health Education: Implementation Study %A Decker,Martha J %A Harrison,Salish %A Price,Melisa %A Gutmann-Gonzalez,Abigail %A Yarger,Jennifer %A Tenney,Rachel %+ Department of Epidemiology and Biostatistics, Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, 550 16th Street, Second Floor, San Francisco, CA, 94158, United States, 1 (415) 476 3095, Mara.Decker@ucsf.edu %K adolescent %K sex education %K technology %K mobile app %K implementation %K California %K health educator %D 2022 %7 12.1.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: In the last decade, the use of technology-based sexual health education has increased. Multiple studies have shown the feasibility of technology-based interventions, while a subset has also shown efficacy in improving youths’ sexual health outcomes such as increased condom use and knowledge. However, little is known about health educators’ experiences in integrating technology to augment sexual health curricula. Objective: The purpose of this study was to assess the perceptions and experiences of health educators regarding the incorporation of technology into a sexual health education program designed for underserved youth in Fresno County, California, and to identify facilitators and challenges to incorporating technology into the in-person curriculum. Methods: This implementation study used data collected as part of a cluster randomized controlled trial to evaluate In the Know (ITK), an in-person sexual health education curriculum that includes technology-based content, such as a resource locator, videos, and games, which can be accessed through a mobile app or website. Data from implementation logs from each cohort (n=51) and annual interviews (n=8) with health educators were analyzed to assess the health educators’ experiences using the technology and adaptations made during the implementation. Results: The health educators reported that technological issues affected implementation to some degree: 87% of the time in the first year, which decreased to 47% in the third year as health educators’ familiarity with the app increased and functionality improved. Technology issues were also more common in non–school settings. Successes and challenges in 3 domains emerged: managing technology, usability of the ITK app, and youth engagement. The health educators generally had positive comments about the app and youth engagement with the technology-based content and activities; however, they also noted certain barriers to adolescents’ use of the mobile app including limited data storage and battery life on mobile phones. Conclusions: Health educators require training and support to optimize technology as a resource for engaging with youth and providing sensitive information. Although technology is often presented as a solution to reach underserved populations, educational programs should consider the technological needs and limitations of the participants, educators, and settings. International Registered Report Identifier (IRRID): RR2-10.2196/18060 %M 35019842 %R 10.2196/31381 %U https://humanfactors.jmir.org/2022/1/e31381 %U https://doi.org/10.2196/31381 %U http://www.ncbi.nlm.nih.gov/pubmed/35019842 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 1 %P e29302 %T Users’ Experiences With the NoHoW Web-Based Toolkit With Weight and Activity Tracking in Weight Loss Maintenance: Long-term Randomized Controlled Trial %A Mattila,Elina %A Hansen,Susanne %A Bundgaard,Lise %A Ramsey,Lauren %A Dunning,Alice %A Silva,Marlene N %A Harjumaa,Marja %A Ermes,Miikka %A Marques,Marta M %A Matos,Marcela %A Larsen,Sofus C %A Encantado,Jorge %A Santos,Inês %A Horgan,Graham %A O'Driscoll,Ruairi %A Turicchi,Jake %A Duarte,Cristiana %A Palmeira,António L %A Stubbs,R James %A Heitmann,Berit Lilienthal %A Lähteenmäki,Liisa %+ VTT Technical Research Centre of Finland Ltd, Tekniikantie 21, Espoo, 02150, Finland, 358 407162230, elina.m.mattila@vtt.fi %K digital behavior change intervention %K user experience %K technology acceptance %K weight-loss maintenance %K focus groups %K mixed methods %K mobile phone %D 2022 %7 10.1.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital behavior change interventions (DBCIs) offer a promising channel for providing health promotion services. However, user experience largely determines whether they are used, which is a precondition for effectiveness. Objective: The primary aim of this study is to evaluate user experiences with the NoHoW Toolkit (TK)—a DBCI that targets weight loss maintenance—over a 12-month period by using a mixed methods approach and to identify the main strengths and weaknesses of the TK and the external factors affecting its adoption. The secondary aim is to objectively describe the measured use of the TK and its association with user experience. Methods: An 18-month, 2×2 factorial randomized controlled trial was conducted. The trial included 3 intervention arms receiving an 18-week active intervention and a control arm. The user experience of the TK was assessed quantitatively through electronic questionnaires after 1, 3, 6, and 12 months of use. The questionnaires also included open-ended items that were thematically analyzed. Focus group interviews were conducted after 6 months of use and thematically analyzed to gain deeper insight into the user experience. Log files of the TK were used to evaluate the number of visits to the TK, the total duration of time spent in the TK, and information on intervention completion. Results: The usability level of the TK was rated as satisfactory. User acceptance was rated as modest; this declined during the trial in all the arms, as did the objectively measured use of the TK. The most appreciated features were weekly emails, graphs, goal setting, and interactive exercises. The following 4 themes were identified in the qualitative data: engagement with features, decline in use, external factors affecting user experience, and suggestions for improvements. Conclusions: The long-term user experience of the TK highlighted the need to optimize the technical functioning, appearance, and content of the DBCI before and during the trial, similar to how a commercial app would be optimized. In a trial setting, the users should be made aware of how to use the intervention and what its requirements are, especially when there is more intensive intervention content. Trial Registration: ISRCTN Registry ISRCTN88405328; https://www.isrctn.com/ISRCTN88405328 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-029425 %M 35006081 %R 10.2196/29302 %U https://www.jmir.org/2022/1/e29302 %U https://doi.org/10.2196/29302 %U http://www.ncbi.nlm.nih.gov/pubmed/35006081 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 1 %P e30807 %T A Smartphone App to Improve Oral Anticoagulation Adherence in Patients With Atrial Fibrillation: Prospective Observational Study %A Senoo,Keitaro %A Miki,Tomonori %A Ohkura,Takashi %A Iwakoshi,Hibiki %A Nishimura,Tetsuro %A Shiraishi,Hirokazu %A Teramukai,Satoshi %A Matoba,Satoaki %+ Department of Cardiac Arrhythmia Research and Innovation, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto-shi, Kamigyo-ku Kajii-cho 465, Kawaramachi-Hirokoji, Kyoto, 602-8566, Japan, 81 8031117168, swcqg251@yahoo.co.jp %K atrial fibrillation %K smartphone app %K anticoagulants %K drug adherence %K education %K patient involvement %D 2022 %7 7.1.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Poor adherence to oral anticoagulation in elderly patients with atrial fibrillation (AF) has been shown to negatively impact health care costs, morbidity, and mortality. Although various methods such as automated reminders, counseling, telephone support, and patient education have been effective in improving medication adherence, the burden on health care providers has been considerable. Recently, an attempt has been made to improve medication adherence without burdening health care providers by using smartphone apps; however, the use of the app for elderly patients with AF is still limited. Objective: The purpose of this study was to determine whether the newly developed smartphone app for patients with AF (the Smart AF), which integrates education, automatic reminder, and patient engagement strategies with a simple user interface, can improve medication adherence in elderly patients with AF. Methods: Patient enrollment was carried out by obtaining informed consent from patients with AF attending Kyoto Prefectural University of Medicine hospital between May 2019 and September 2020. Follow-up was planned at 1, 3, and 6 months after enrollment, and questionnaire reminders were automatically sent to patient apps at designated follow-up time points. A questionnaire-based survey of medication adherence was performed electronically using the self-reported 8-item Morisky Medication Adherence Scale (MMAS-8) as the survey tool. Results: A total of 136 patients with AF were enrolled in this study. During the follow-up period, 112 (82%) patients underwent follow-up at 1 month, 107 (79%) at 3 months, and 96 (71%) at 6 months. The mean age of the enrolled patients was 64.3 years (SD 9.6), and male participants accounted for 79.4% (108/136) of the study population. The mean CHADS2 (congestive heart failure, hypertension, age, diabetes, previous stroke, or transient ischemic attack) score was 1.2, with hypertension being the most common comorbidity. At the time of enrollment, 126 (93%) and 10 (7%) patients were taking direct oral anticoagulants and warfarin, respectively. For medication adherence as measured according to the MMAS-8, MMAS scores at 1 month, 3 months, and 6 months were significantly improved compared with baseline MMAS scores (all P values less than .01). The overall improvement in medication adherence achieved by the 6-month intervention was as follows: 77.8% (14/18) of the patients in the high adherence group (score=8) at baseline remained in the same state, 45.3% (24/53) of the patients in the medium adherence group (score=6 to <8) at baseline moved to the high adherence group, and 72% (18/25) of the patients in the low adherence group (score <6) moved to either the medium or high adherence group. Conclusions: The Smart AF app improved medication adherence among elderly patients with AF. In the realm of medication management, an approach using a mobile health technology that emphasizes education, automatic reminder, and patient engagement may be helpful. %M 34894626 %R 10.2196/30807 %U https://mhealth.jmir.org/2022/1/e30807 %U https://doi.org/10.2196/30807 %U http://www.ncbi.nlm.nih.gov/pubmed/34894626 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 10 %N 1 %P e25586 %T Dose–Response Effects of Patient Engagement on Health Outcomes in an mHealth Intervention: Secondary Analysis of a Randomized Controlled Trial %A Li,Yiran %A Guo,Yan %A Hong,Y Alicia %A Zeng,Yu %A Monroe-Wise,Aliza %A Zeng,Chengbo %A Zhu,Mengting %A Zhang,Hanxi %A Qiao,Jiaying %A Xu,Zhimeng %A Cai,Weiping %A Li,Linghua %A Liu,Cong %+ Department of Medical Statistics, School of Public Health, 74 Zhongshan 2nd Road, Guangzhou, 510080, China, 86 020 87333239, Yan.Guo1@umassmed.edu %K mHealth %K patient engagement %K dose–response relationship %K long-term effect %K generalized linear mixed effects model %D 2022 %7 4.1.2022 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The dose–response relationship between patient engagement and long-term intervention effects in mobile health (mHealth) interventions are understudied. Studies exploring long-term and potentially changing relationships between patient engagement and health outcomes in mHealth interventions are needed. Objective: This study aims to examine dose–response relationships between patient engagement and 3 psychosocial outcomes in an mHealth intervention, Run4Love, using repeated measurements of outcomes at baseline and 3, 6, and 9 months. Methods: This study is a secondary analysis using longitudinal data from the Run4Love trial, a randomized controlled trial with 300 people living with HIV and elevated depressive symptoms to examine the effects of a 3-month mHealth intervention on reducing depressive symptoms and improving quality of life (QOL). We examined the relationships between patient engagement and depressive symptoms, QOL, and perceived stress in the intervention group (N=150) using 4–time-point outcome measurements. Patient engagement was assessed using the completion rate of course assignments and frequency of items completed. Cluster analysis was used to categorize patients into high- and low-engagement groups. Generalized linear mixed effects models were conducted to investigate the dose–response relationships between patient engagement and outcomes. Results: The cluster analysis identified 2 clusters that were distinctively different from each other. The first cluster comprised 72 participants with good compliance to the intervention, completing an average of 74% (53/72) of intervention items (IQR 0.22). The second cluster comprised 78 participants with low compliance to the intervention, completing an average of 15% (11/72) of intervention items (IQR 0.23). Results of the generalized linear mixed effects models showed that, compared with the low-engagement group, the high-engagement group had a significant reduction in more depressive symptoms (β=−1.93; P=.008) and perceived stress (β=−1.72; P<.001) and an improved QOL (β=2.41; P=.01) over 9 months. From baseline to 3, 6, and 9 months, the differences in depressive symptoms between the 2 engagement groups were 0.8, 1.6, 2.3, and 3.7 points, respectively, indicating widening between-group differences over time. Similarly, between-group differences in QOL and perceived stress increased over time (group differences in QOL: 0.9, 1.9, 4.7, and 5.1 points, respectively; group differences in the Perceived Stress Scale: 0.9, 1.4, 2.3, and 3.0 points, respectively). Conclusions: This study revealed a positive long-term dose–response relationship between patient engagement and 3 psychosocial outcomes among people living with HIV and elevated depressive symptoms in an mHealth intervention over 9 months using 4 time-point repeat measurement data. The high- and low-engagement groups showed significant and widening differences in depressive symptoms, QOL, and perceived stress at the 3-, 6-, and 9-month follow-ups. Future mHealth interventions should improve patient engagement to achieve long-term and sustained intervention effects. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://www.chictr.org.cn/showproj.aspx?proj=21019 %M 34982724 %R 10.2196/25586 %U https://mhealth.jmir.org/2022/1/e25586 %U https://doi.org/10.2196/25586 %U http://www.ncbi.nlm.nih.gov/pubmed/34982724 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 12 %P e31367 %T Centering Lived Experience in Developing Digital Interventions for Suicide and Self-injurious Behaviors: User-Centered Design Approach %A Kruzan,Kaylee Payne %A Meyerhoff,Jonah %A Biernesser,Candice %A Goldstein,Tina %A Reddy,Madhu %A Mohr,David C %+ Center for Behavioral Intervention Technologies, Feinberg School of Medicine, Northwestern University, 750 N Lake Shore Dr, Chicago, IL, 60611, United States, 1 3125036585, kaylee.kruzan@northwestern.edu %K user-centered design %K intervention %K suicide %K nonsuicidal self-injury %K lived experience %K technology-enabled services %K digital intervention %K engagement %K mobile phone %D 2021 %7 24.12.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: The prevalence of self-injurious thoughts and behaviors (SITB) signals a growing public health crisis. Despite a recognized need for improved and scalable interventions, the field of SITB intervention faces several challenges: existing interventions are often time and resource intensive, most individuals with SITB do not seek formal mental health care, and efficacious treatments are characterized by small effects. Combined, these challenges indicate a need for improved SITB interventions for individuals in formal treatment and those who are not treatment engaged but are at high risk of worsening mental health and future suicide attempts. Objective: We present a methodological approach and set of techniques that may address these challenges by centering the lived experience of individuals with SITB in the process of developing needed services: user-centered design (UCD). Methods: We highlight the value of UCD in the context of digital interventions for SITB by describing the UCD approach and explicating how it can be leveraged to include lived experience throughout the development and evaluation process. We provide a detailed case example highlighting 3 phases of the early development process that can be used to design an intervention that is engaging and meets end-user needs. In addition, we point to novel applications of UCD to complement new directions in SITB research. Results: In this paper, we offer a 2-pronged approach to meet these challenges. First, in terms of addressing access to effective interventions, digital interventions hold promise to extend the reach of evidence-based treatments outside of brick-and-mortar health care settings. Second, to address challenges related to treatment targets and engagement, we propose involving individuals with lived experience in the design and research process. Conclusions: UCD offers a well-developed and systematic process to center the unique needs, preferences, and perceived barriers of individuals with lived SITB experience in the development and evaluation of digital interventions. %M 34951602 %R 10.2196/31367 %U https://mental.jmir.org/2021/12/e31367 %U https://doi.org/10.2196/31367 %U http://www.ncbi.nlm.nih.gov/pubmed/34951602 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e25330 %T Active Usage of Mobile Health Applications: Cross-sectional Study %A Wang,Yang %A Wu,Tailai %A Chen,Zhuo %+ School of Medicine and Health Management, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Wuhan, 430030, China, 86 13477072665, lncle2012@yahoo.com %K active usage %K mobile health %K 3-factor theory %K consumer satisfaction %K consumer dissatisfaction %K medical informatics %D 2021 %7 22.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health applications are being increasingly used for people’s health management. The different uses of mobile health applications lead to different health outcomes. Although active usage of mobile health applications is shown to be linked to the effectiveness of mobile health services, the factors that influence people’s active usage of mobile health applications are not well studied. Objective: This paper aims to examine the antecedents of active usage of mobile health applications. Methods: Grounded on the 3-factor theory, we proposed 10 attributes of mobile health applications that influence the active usage of mobile health applications through consumers’ satisfaction and dissatisfaction. We classified these 10 attributes into 3 categories (ie, excitement attributes, performance attributes, and basic attributes). Using the survey method, 494 valid responses were collected and analyzed using structural equation modeling. Results: Our analysis results revealed that both consumer satisfaction (β=0.351, t=6.299, P<.001) and dissatisfaction (β=–0.251, t=5.119, P<.001) significantly influenced active usage. With regard to the effect of attributes, excitement attributes (β=0.525, t=12.861, P<.001) and performance attributes (β=0.297, t=6.508, P<.001) positively influenced consumer satisfaction, while performance attributes (β=–0.231, t=3.729, P<.001) and basic attributes (β=–0.412, t=7.132, P<.001) negatively influenced consumer dissatisfaction. The results of the analysis confirmed our proposed hypotheses. Conclusions: Our study provides a novel perspective to study the active usage of mobile health applications. By categorizing the attributes of mobile health applications into 3 categories, the differential effects of different attributes can be tested. Meanwhile, consumer satisfaction and dissatisfaction are confirmed to be independent from each other. %M 34941545 %R 10.2196/25330 %U https://www.jmir.org/2021/12/e25330 %U https://doi.org/10.2196/25330 %U http://www.ncbi.nlm.nih.gov/pubmed/34941545 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e32653 %T Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial %A White,Katie M %A Matcham,Faith %A Leightley,Daniel %A Carr,Ewan %A Conde,Pauline %A Dawe-Lane,Erin %A Ranjan,Yatharth %A Simblett,Sara %A Henderson,Claire %A Hotopf,Matthew %+ Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 de Crespigny Park, London, SE5 8AF, United Kingdom, 44 7850684847, katie.white@kcl.ac.uk %K app %K engagement %K major depressive disorder %K remote measurement technologies %K research %K mobile phone %D 2021 %7 21.12.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Multi-parametric remote measurement technologies (RMTs) comprise smartphone apps and wearable devices for both active and passive symptom tracking. They hold potential for understanding current depression status and predicting future depression status. However, the promise of using RMTs for relapse prediction is heavily dependent on user engagement, which is defined as both a behavioral and experiential construct. A better understanding of how to promote engagement in RMT research through various in-app components will aid in providing scalable solutions for future remote research, higher quality results, and applications for implementation in clinical practice. Objective: The aim of this study is to provide the rationale and protocol for a 2-armed randomized controlled trial to investigate the effect of insightful notifications, progress visualization, and researcher contact details on behavioral and experiential engagement with a multi-parametric mobile health data collection platform, Remote Assessment of Disease and Relapse (RADAR)–base. Methods: We aim to recruit 140 participants upon completion of their participation in the RADAR Major Depressive Disorder study in the London site. Data will be collected using 3 weekly tasks through an active smartphone app, a passive (background) data collection app, and a Fitbit device. Participants will be randomly allocated at a 1:1 ratio to receive either an adapted version of the active app that incorporates insightful notifications, progress visualization, and access to researcher contact details or the active app as usual. Statistical tests will be used to assess the hypotheses that participants using the adapted app will complete a higher percentage of weekly tasks (behavioral engagement: primary outcome) and score higher on self-awareness measures (experiential engagement). Results: Recruitment commenced in April 2021. Data collection was completed in September 2021. The results of this study will be communicated via publication in 2022. Conclusions: This study aims to understand how best to promote engagement with RMTs in depression research. The findings will help determine the most effective techniques for implementation in both future rounds of the RADAR Major Depressive Disorder study and, in the long term, clinical practice. Trial Registration: ClinicalTrials.gov NCT04972474; http://clinicaltrials.gov/ct2/show/NCT04972474 International Registered Report Identifier (IRRID): DERR1-10.2196/32653 %M 34932005 %R 10.2196/32653 %U https://www.researchprotocols.org/2021/12/e32653 %U https://doi.org/10.2196/32653 %U http://www.ncbi.nlm.nih.gov/pubmed/34932005 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 12 %P e30000 %T Understanding Engagement Strategies in Digital Interventions for Mental Health Promotion: Scoping Review %A Saleem,Maham %A Kühne,Lisa %A De Santis,Karina Karolina %A Christianson,Lara %A Brand,Tilman %A Busse,Heide %+ Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Achterstraße 30, Bremen, 28359, Germany, 49 42121856 ext 923, saleem@leibniz-bips.de %K digital interventions %K mental health promotion %K engagement %K scoping review %K mobile phone %D 2021 %7 20.12.2021 %9 Review %J JMIR Ment Health %G English %X Background: Digital interventions offer a solution to address the high demand for mental health promotion, especially when facing physical contact restrictions or lacking accessibility. Engagement with digital interventions is critical for their effectiveness; however, retaining users’ engagement throughout the intervention is challenging. It remains unclear what strategies facilitate engagement with digital interventions that target mental health promotion. Objective: Our aim is to conduct a scoping review to investigate user engagement strategies and methods to evaluate engagement with digital interventions that target mental health promotion in adults. Methods: This scoping review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews. The search was conducted in 7 electronic databases from inception to April 2020. The inclusion criteria for studies were as follows: adult (aged ≥18 years) users of digital interventions for mental health promotion from the general population; any digital intervention for mental health promotion; and user engagement strategies described in the intervention design. We extracted the following data items: study characteristics, digital intervention (type and engagement strategy), evaluation of engagement strategy (method and result specifying whether the strategy was effective at facilitating engagement), and features of engagement (extent of use and subjective experience of users). Results: A total of 2766 studies were identified, of which 16 (0.58%) met the inclusion criteria. The 16 studies included randomized controlled trials (6/16, 37%), studies analyzing process data (5/16, 31%), observational studies (3/16, 19%), and qualitative studies (2/16, 13%). The digital interventions for mental health promotion were either web based (12/16, 75%) or mobile app based (4/16, 25%). The engagement strategies included personalized feedback about intervention content or users’ mental health status; guidance regarding content and progress through e-coaching; social forums, and interactivity with peers; content gamification; reminders; and flexibility and ease of use. These engagement strategies were deemed effective based on qualitative user feedback or responses on questionnaires or tools (4/16, 25%), usability data (5/16, 31%), or both (7/16, 44%). Most studies identified personalized support in the form of e-coaching, peer support through a social platform, personalized feedback, or joint videoconference sessions as an engaging feature. Conclusions: Personalized support during the intervention, access to social support, and personalized feedback seem to promote engagement with digital interventions for mental health promotion. These findings need to be interpreted with caution because the included studies were heterogeneous, had small sample sizes, and typically did not address engagement as the primary outcome. Despite the importance of user engagement for the effectiveness of digital interventions, this field has not yet received much attention. Further research is needed on the effectiveness of different strategies required to facilitate user engagement in digital interventions for mental health promotion. %M 34931995 %R 10.2196/30000 %U https://mental.jmir.org/2021/12/e30000 %U https://doi.org/10.2196/30000 %U http://www.ncbi.nlm.nih.gov/pubmed/34931995 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 12 %P e29098 %T Perceptions of Factors Influencing Engagement With Health and Well-being Apps in the United Kingdom: Qualitative Interview Study %A Szinay,Dorothy %A Perski,Olga %A Jones,Andy %A Chadborn,Tim %A Brown,Jamie %A Naughton,Felix %+ School of Health Sciences, University of East Anglia, Norwich Research Park, Earlham Road, Norwich, NR4 7TJ, United Kingdom, 44 1603593064, d.szinay@uea.ac.uk %K behavior change %K health apps %K mHealth %K smartphone app %K framework analysis %K COM-B %K TDF %K user engagement %K motivation %K usability %K engagement %K mobile phone %D 2021 %7 16.12.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Digital health devices, such as health and well-being smartphone apps, could offer an accessible and cost-effective way to deliver health and well-being interventions. A key component of the effectiveness of health and well-being apps is user engagement. However, engagement with health and well-being apps is typically poor. Previous studies have identified a list of factors that could influence engagement; however, most of these studies were conducted on a particular population or for an app targeting a particular behavior. An understanding of the factors that influence engagement with a wide range of health and well-being apps can inform the design and the development of more engaging apps in general. Objective: The aim of this study is to explore user experiences of and reasons for engaging and not engaging with a wide range of health and well-being apps. Methods: A sample of adults in the United Kingdom (N=17) interested in using a health or well-being app participated in a semistructured interview to explore experiences of engaging and not engaging with these apps. Participants were recruited via social media platforms. Data were analyzed with the framework approach, informed by the Capability, Opportunity, Motivation–Behaviour (COM-B) model and the Theoretical Domains Framework, which are 2 widely used frameworks that incorporate a comprehensive set of behavioral influences. Results: Factors that influence the capability of participants included available user guidance, statistical and health information, reduced cognitive load, well-designed reminders, self-monitoring features, features that help establish a routine, features that offer a safety net, and stepping-stone app characteristics. Tailoring, peer support, and embedded professional support were identified as important factors that enhance user opportunities for engagement with health and well-being apps. Feedback, rewards, encouragement, goal setting, action planning, self-confidence, and commitment were judged to be the motivation factors that affect engagement with health and well-being apps. Conclusions: Multiple factors were identified across all components of the COM-B model that may be valuable for the development of more engaging health and well-being apps. Engagement appears to be influenced primarily by features that provide user guidance, promote minimal cognitive load, support self-monitoring (capability), provide embedded social support (opportunity), and provide goal setting with action planning (motivation). This research provides recommendations for policy makers, industry, health care providers, and app developers for increasing effective engagement. %M 34927597 %R 10.2196/29098 %U https://mhealth.jmir.org/2021/12/e29098 %U https://doi.org/10.2196/29098 %U http://www.ncbi.nlm.nih.gov/pubmed/34927597 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 12 %P e31353 %T A Personalized Approach Bias Modification Smartphone App (“SWiPE”) to Reduce Alcohol Use: Open-Label Feasibility, Acceptability, and Preliminary Effectiveness Study %A Manning,Victoria %A Piercy,Hugh %A Garfield,Joshua Benjamin Bernard %A Clark,Stuart Gregory %A Andrabi,Mah Noor %A Lubman,Dan Ian %+ Turning Point, Eastern Health, 110 Church St, Richmond, Melbourne, 3121, Australia, 61 0428337961, victoria.manning@monash.edu %K alcohol %K hazardous alcohol use %K alcohol use disorder %K approach bias modification %K cognitive bias modification %K smartphone app %K ehealth %K mobile phone app %K mhealth %K digital health %D 2021 %7 10.12.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Approach bias modification (ApBM), a computerized cognitive intervention that trains people to “avoid” alcohol-related images and “approach” nonalcohol images, reduces the likelihood of relapse when administered during residential alcohol treatment. However, most individuals experiencing alcohol problems do not require, do not seek, or have difficulty accessing residential treatment. Smartphone-delivered ApBM could offer an easily accessible intervention to reduce alcohol consumption that can be personalized (eg, allowing selection of personally relevant alcohol and positive nonalcohol training images) and gamified to optimize engagement. Objective: We examined the feasibility, acceptability, and preliminary effectiveness of “SWiPE,” a gamified, personalized alcohol ApBM smartphone app, and explored alcohol consumption and craving outcomes in people drinking at hazardous levels or above (Alcohol Use Disorders Identification Test [AUDIT] score ≥8) who wanted to reduce their alcohol use. Methods: In this open-label trial, frequency and quantity of alcohol consumption, alcohol dependence severity, and craving were measured prior to participants downloading SWiPE. Participants (n=1309) were instructed to complete at least 2 sessions per week for 4 weeks. Recruitment and completion rates were indicators of feasibility. Functionality, aesthetics, and quality ratings were indicators of acceptability. Participants were prompted to report frequency and quantity of alcohol consumption weekly during training and 1 month after training. They completed measures of craving and dependence after 4 weeks of training. Results: We recruited 1309 participants (mean age 47.0, SD 10.0 years; 758/1309, 57.9% female; mean AUDIT score 21.8, SD 6.5) over 6 months. Participants completed a median of 5 sessions (IQR 2-9); 31.2% (409/1309) completed ≥8 sessions; and 34.8% (455/1309) completed the posttraining survey. Mean Mobile Application Rating Scale scores indicated good acceptability for functionality and aesthetics and fair acceptability for subjective quality. Among those who completed the posttraining assessment, mean past-week drinking days reduced from 5.1 (SD 2.0) pre-training to 4.2 (SD 2.3) in week 4 (t454=7.87; P<.001), and mean past-week standard drinks reduced from 32.8 (SD 22.1) to 24.7 (SD 20.1; t454=8.58; P<.001). Mean Craving Experience Questionnaire frequency scores reduced from 4.5 (SD 2.0) to 2.8 (SD 1.8; t435=19.39; P<.001). Severity of Dependence scores reduced from 7.7 (SD 3.0) to 6.0 (SD 3.2; t435=12.44; P<.001). For the 19.4% (254/1309) of participants who completed a 1-month follow-up, mean past-week drinking days and standard drinks were 3.9 (SD 2.5) and 23.9 (SD 20.7), respectively, both significantly lower than at baseline (P<.001). Conclusions: The findings suggest SWiPE is feasible and acceptable and may be effective at reducing alcohol consumption and craving in a predominantly nontreatment-seeking sample of adult Australians drinking at hazardous levels. SWiPE’s efficacy, relative to a control condition, now needs establishing in a randomized controlled trial. Smartphone-delivered personalized ApBM could be a highly scalable, widely accessible support tool for reducing alcohol use. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12620000638932; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000638932p International Registered Report Identifier (IRRID): RR2-10.2196/21278 %M 34890355 %R 10.2196/31353 %U https://mhealth.jmir.org/2021/12/e31353 %U https://doi.org/10.2196/31353 %U http://www.ncbi.nlm.nih.gov/pubmed/34890355 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e22557 %T Comparing the Effects of Gamification and Teach-Back Training Methods on Adherence to a Therapeutic Regimen in Patients After Coronary Artery Bypass Graft Surgery: Randomized Clinical Trial %A Ghorbani,Banafsheh %A Jackson,Alun C %A Noorchenarboo,Mohammad %A Mandegar,Mohammad H %A Sharifi,Farshad %A Mirmoghtadaie,Zohrehsadat %A Bahramnezhad,Fatemeh %+ School of Nursing & Midwifery, Nursing and Midwifery Care Research Center, Spiritual Health Group, Research Center of Quran, Hadith and Medicine, Tehran University of Medical Sciences, Nosrat St., Tohid Sq., Tehran, 141973317, Iran, 98 2166914368, bahramnezhad@sina.tums.ac.ir %K teach back %K gamification %K treatment regimen %K coronary artery bypass graft %K patient training %D 2021 %7 10.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients undergoing coronary artery bypass graft surgery (CABGS) may fail to adhere to their treatment regimen for many reasons. Among these, one of the most important reasons for nonadherence is the inadequate training of such patients or training using inappropriate methods. Objective: This study aimed to compare the effect of gamification and teach-back training methods on adherence to a therapeutic regimen in patients after CABGS. Methods: This randomized clinical trial was conducted on 123 patients undergoing CABGS in Tehran, Iran, in 2019. Training was provided to the teach-back group individually. In the gamification group, an app developed for the purpose was installed on each patient’s smartphone, with training given via this device. The control group received usual care, or routine training. Adherence to the therapeutic regimen was assessed using a questionnaire on adherence to a therapeutic regimen (physical activity and dietary regimen) and an adherence scale as a pretest and a 1-month posttest. Results: One-way analysis of variance (ANOVA) for comparing the mean scores of teach-back and gamification training methods showed that the mean normalized scores for the dietary regimen (P<.001, F=71.80), movement regimen (P<.001, F=124.53), and medication regimen (P<.001, F=9.66) before and after intervention were significantly different between the teach-back, gamification, and control groups. In addition, the results of the Dunnett test showed that the teach-back and gamification groups were significantly different from the control group in all three treatment regimen methods. There was no statistically significant difference in adherence to the therapeutic regimen between the teach-back and control groups. Conclusions: Based on the results of this study, the use of teach-back and gamification training approaches may be suggested for patients after CABGS to facilitate adherence to the therapeutic regimen. Trial Registration: Iranian Registry of Clinical Trials IRCT20111203008286N8; https://en.irct.ir/trial/41507 %M 34890346 %R 10.2196/22557 %U https://www.jmir.org/2021/12/e22557 %U https://doi.org/10.2196/22557 %U http://www.ncbi.nlm.nih.gov/pubmed/34890346 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 12 %P e32165 %T An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study %A Goodday,Sarah M %A Karlin,Emma %A Alfarano,Alexandria %A Brooks,Alexa %A Chapman,Carol %A Desille,Rachelle %A Rangwala,Shazia %A Karlin,Daniel R %A Emami,Hoora %A Woods,Nancy Fugate %A Boch,Adrien %A Foschini,Luca %A Wildman,Mackenzie %A Cormack,Francesca %A Taptiklis,Nick %A Pratap,Abhishek %A Ghassemi,Marzyeh %A Goldenberg,Anna %A Nagaraj,Sujay %A Walsh,Elaine %A , %A Friend,Stephen %+ 4YouandMe, 2901 Third Ave Suite 330, Seattle, WA, 98121, United States, 1 2069288254, sarah@4youandme.org %K stress %K wearable %K digital health %K frontline %K COVID-19 %K health care worker %K alternative %K design %K app %K assessment %K sensor %K engagement %K support %K knowledge %D 2021 %7 10.12.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Several app-based studies share similar characteristics of a light touch approach that recruit, enroll, and onboard via a smartphone app and attempt to minimize burden through low-friction active study tasks while emphasizing the collection of passive data with minimal human contact. However, engagement is a common challenge across these studies, reporting low retention and adherence. Objective: This study aims to describe an alternative to a light touch digital health study that involved a participant-centric design including high friction app-based assessments, semicontinuous passive data from wearable sensors, and a digital engagement strategy centered on providing knowledge and support to participants. Methods: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study included US frontline health care workers followed between May and November 2020. The study comprised 3 main components: (1) active and passive assessments of stress and symptoms from a smartphone app, (2) objective measured assessments of acute stress from wearable sensors, and (3) a participant codriven engagement strategy that centered on providing knowledge and support to participants. The daily participant time commitment was an average of 10 to 15 minutes. Retention and adherence are described both quantitatively and qualitatively. Results: A total of 365 participants enrolled and started the study, and 81.0% (n=297) of them completed the study for a total study duration of 4 months. Average wearable sensor use was 90.6% days of total study duration. App-based daily, weekly, and every other week surveys were completed on average 69.18%, 68.37%, and 72.86% of the time, respectively. Conclusions: This study found evidence for the feasibility and acceptability of a participant-centric digital health study approach that involved building trust with participants and providing support through regular phone check-ins. In addition to high retention and adherence, the collection of large volumes of objective measured data alongside contextual self-reported subjective data was able to be collected, which is often missing from light touch digital health studies. Trial Registration: ClinicalTrials.gov NCT04713111; https://clinicaltrials.gov/ct2/show/NCT04713111 %M 34726607 %R 10.2196/32165 %U https://formative.jmir.org/2021/12/e32165 %U https://doi.org/10.2196/32165 %U http://www.ncbi.nlm.nih.gov/pubmed/34726607 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e30092 %T Assessing Patient Engagement in Health Care: Proposal for a Modeling and Simulation Framework for Behavioral Analysis %A Alwasel,Athary %A Stergioulas,Lampros %A Fakhimi,Masoud %A Garn,Wolfgang %+ Surrey Business School, University of Surrey, Stag Hill, Guildford, GU2 7XH, United Kingdom, 44 1483 683048, a.alwasel@surrey.ac.uk %K modeling and simulation %K behavioral analysis %K patient engagement %K behavioral factors, health care %K human factors %K outcomes %K patient health %K health policy %K chronic diseases %K behavioral model %D 2021 %7 8.12.2021 %9 Proposal %J JMIR Res Protoc %G English %X Human behavior plays a vital role in health care effectiveness and system performance. Therefore, it is necessary to look carefully at the interactions within a system and how a system is affected by the behavioral responses and activities of its various components, particularly human components and actions. Modeling patients’ engagement behaviors can be valuable in many ways; for example, models can evaluate the effects of therapeutic interventions on health improvement, health care effectiveness, and desired outcomes of changing health lifestyles. Modeling and simulation (M&S) help us to understand the interactions within a whole system under defined conditions. M&S in patient behavior analysis involve models that attempt to identify certain human behaviors that most likely have an impact on health care operations and services. Our study’s overall aims are (1) to investigate the impacts of patients’ engagement and various human behavior patterns on health care effectiveness and the achievement of desired outcomes and (2) to construct and validate a framework for modeling patient engagement and implementing and supporting patient management best practices, health policy-making processes, and innovative interventions in health care. We intend to extract routinely collected data of different parameters from general patients diagnosed with chronic diseases, such as diabetes. Our plan is to design data sets and extract health data from a pool of >4 million patient records from different general practices in England. We will focus on the primary electronic medical records of patients with at least 1 chronic disease (>200,000 records). Simulation techniques will be used to study patient engagement and its impact on health care effectiveness and outcome measures. The study will integrate available approaches to develop a framework for modeling how patients’ behaviors affect health care activities and outcomes and to underline the characteristics and salient factors that operational management needs to be aware of when developing a behavioral model for assessing patient engagement. The M&S framework, which is under development, will consider patient behavior in context and the underlying factors of human behavior with the help of simulation techniques. The proposed framework will be validated and evaluated through a health care case study. We expect to identify leading factors that influence and affect patient engagement and associated behavioral activities and to illustrate the challenges and complexities of developing simulation models for conducting behavioral analyses within health care settings. Additionally, we will assess patients’ engagement behaviors in terms of achieving health care effectiveness and desired outcomes, and we will specifically evaluate the impacts of patient engagement activities on health care services, patient management styles, and the effectiveness of health interventions in terms of achieving the intended outcomes—improved health and patient satisfaction.International Registered Report Identifier (IRRID): PRR1-10.2196/30092 %M 34889774 %R 10.2196/30092 %U https://www.researchprotocols.org/2021/12/e30092 %U https://doi.org/10.2196/30092 %U http://www.ncbi.nlm.nih.gov/pubmed/34889774 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 12 %P e32007 %T Examining the Theoretical Framework of Behavioral Activation for Major Depressive Disorder: Smartphone-Based Ecological Momentary Assessment Study %A van Genugten,Claire Rosalie %A Schuurmans,Josien %A Hoogendoorn,Adriaan W %A Araya,Ricardo %A Andersson,Gerhard %A Baños,Rosa %A Botella,Cristina %A Cerga Pashoja,Arlinda %A Cieslak,Roman %A Ebert,David Daniel %A García-Palacios,Azucena %A Hazo,Jean-Baptiste %A Herrero,Rocío %A Holtzmann,Jérôme %A Kemmeren,Lise %A Kleiboer,Annet %A Krieger,Tobias %A Smoktunowicz,Ewelina %A Titzler,Ingrid %A Topooco,Naira %A Urech,Antoine %A Smit,Johannes H %A Riper,Heleen %+ Department of Research and Innovation, GGZ inGeest, Specialized Mental Health Care, Oldenaller 1, Amsterdam, 1081HJ, Netherlands, 31 0207884666, c.genugten@ggzingeest.nl %K depression %K behavioral activation %K theoretical framework %K ecological momentary assessment %K random-intercept cross-lagged panel model %K behavior %K framework %K EMA %K smartphone %K mental health %K treatment %K engagement %K mood %D 2021 %7 6.12.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Behavioral activation (BA), either as a stand-alone treatment or as part of cognitive behavioral therapy, has been shown to be effective for treating depression. The theoretical underpinnings of BA derive from Lewinsohn et al’s theory of depression. The central premise of BA is that having patients engage in more pleasant activities leads to them experiencing more pleasure and elevates their mood, which, in turn, leads to further (behavioral) activation. However, there is a dearth of empirical evidence about the theoretical framework of BA. Objective: This study aims to examine the assumed (temporal) associations of the 3 constructs in the theoretical framework of BA. Methods: Data were collected as part of the “European Comparative Effectiveness Research on Internet-based Depression Treatment versus treatment-as-usual” trial among patients who were randomly assigned to receive blended cognitive behavioral therapy (bCBT). As part of bCBT, patients completed weekly assessments of their level of engagement in pleasant activities, the pleasure they experienced as a result of these activities, and their mood over the course of the treatment using a smartphone-based ecological momentary assessment (EMA) application. Longitudinal cross-lagged and cross-sectional associations of 240 patients were examined using random intercept cross-lagged panel models. Results: The analyses did not reveal any statistically significant cross-lagged coefficients (all P>.05). Statistically significant cross-sectional positive associations between activities, pleasure, and mood levels were identified. Moreover, the levels of engagement in activities, pleasure, and mood slightly increased over the duration of the treatment. In addition, mood seemed to carry over, over time, while both levels of engagement in activities and pleasurable experiences did not. Conclusions: The results were partially in accordance with the theoretical framework of BA, insofar as the analyses revealed cross-sectional relationships between levels of engagement in activities, pleasurable experiences deriving from these activities, and enhanced mood. However, given that no statistically significant temporal relationships were revealed, no conclusions could be drawn about potential causality. A shorter measurement interval (eg, daily rather than weekly EMA reports) might be more attuned to detecting potential underlying temporal pathways. Future research should use an EMA methodology to further investigate temporal associations, based on theory and how treatments are presented to patients. Trial Registration: ClinicalTrials.gov, NCT02542891, https://clinicaltrials.gov/ct2/show/NCT02542891; German Clinical Trials Register, DRKS00006866, https://tinyurl.com/ybja3xz7; Netherlands Trials Register, NTR4962, https://www.trialregister.nl/trial/4838; ClinicalTrials.Gov, NCT02389660, https://clinicaltrials.gov/ct2/show/NCT02389660; ClinicalTrials.gov, NCT02361684, https://clinicaltrials.gov/ct2/show/NCT02361684; ClinicalTrials.gov, NCT02449447, https://clinicaltrials.gov/ct2/show/NCT02449447; ClinicalTrials.gov, NCT02410616, https://clinicaltrials.gov/ct2/show/NCT02410616; ISRCTN registry, ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725 %M 34874888 %R 10.2196/32007 %U https://mental.jmir.org/2021/12/e32007 %U https://doi.org/10.2196/32007 %U http://www.ncbi.nlm.nih.gov/pubmed/34874888 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e33568 %T Optimizing a Just-in-Time Adaptive Intervention to Improve Dietary Adherence in Behavioral Obesity Treatment: Protocol for a Microrandomized Trial %A Goldstein,Stephanie P %A Zhang,Fengqing %A Klasnja,Predrag %A Hoover,Adam %A Wing,Rena R %A Thomas,John Graham %+ Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI, 02903, United States, 1 4017939727, stephanie_goldstein@brown.edu %K obesity %K weight loss %K dietary adherence %K just-in-time adaptive intervention %K microrandomized trial %K mobile phone %D 2021 %7 6.12.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Behavioral obesity treatment (BOT) is a gold standard approach to weight loss and reduces the risk of cardiovascular disease. However, frequent lapses from the recommended diet stymie weight loss and prevent individuals from actualizing the health benefits of BOT. There is a need for innovative treatment solutions to improve adherence to the prescribed diet in BOT. Objective: The aim of this study is to optimize a smartphone-based just-in-time adaptive intervention (JITAI) that uses daily surveys to assess triggers for dietary lapses and deliver interventions when the risk of lapse is high. A microrandomized trial design will evaluate the efficacy of any interventions (ie, theory-driven or a generic alert to risk) on the proximal outcome of lapses during BOT, compare the effects of theory-driven interventions with generic risk alerts on the proximal outcome of lapse, and examine contextual moderators of interventions. Methods: Adults with overweight or obesity and cardiovascular disease risk (n=159) will participate in a 6-month web-based BOT while using the JITAI to prevent dietary lapses. Each time the JITAI detects elevated lapse risk, the participant will be randomized to no intervention, a generic risk alert, or 1 of 4 theory-driven interventions (ie, enhanced education, building self-efficacy, fostering motivation, and improving self-regulation). The primary outcome will be the occurrence of lapse in the 2.5 hours following randomization. Contextual moderators of intervention efficacy will also be explored (eg, location and time of day). The data will inform an optimized JITAI that selects the theory-driven approach most likely to prevent lapses in a given moment. Results: The recruitment for the microrandomized trial began on April 19, 2021, and is ongoing. Conclusions: This study will optimize a JITAI for dietary lapses so that it empirically tailors the provision of evidence-based intervention to the individual and context. The finalized JITAI will be evaluated for efficacy in a future randomized controlled trial of distal health outcomes (eg, weight loss). Trial Registration: ClinicalTrials.gov NCT04784585; http://clinicaltrials.gov/ct2/show/NCT04784585 International Registered Report Identifier (IRRID): DERR1-10.2196/33568 %M 34874892 %R 10.2196/33568 %U https://www.researchprotocols.org/2021/12/e33568 %U https://doi.org/10.2196/33568 %U http://www.ncbi.nlm.nih.gov/pubmed/34874892 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 11 %P e29666 %T Effects of Internet-Based Cognitive Behavioral Therapy for Harmful Alcohol Use and Alcohol Dependence as Self-help or With Therapist Guidance: Three-Armed Randomized Trial %A Johansson,Magnus %A Berman,Anne H %A Sinadinovic,Kristina %A Lindner,Philip %A Hermansson,Ulric %A Andréasson,Sven %+ Department of Global Public Health, Karolinska Institutet, Solnavägen 1E, Stockholm, 11365, Sweden, 46 727249971, magnus.johansson.1@ki.se %K alcohol dependence %K alcohol use disorders %K internet-based interventions %K internet-based cognitive behavioral therapy %K ICBT %K cognitive behavioral therapy %K CBT %K eHealth %K alcohol use %K substance abuse %K outcomes %K help-seeking behavior %K internet-based interventions %K alcohol dependence %K mobile phone %D 2021 %7 24.11.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Alcohol use is a major contributor to health loss. Many persons with harmful use or alcohol dependence do not obtain treatment because of limited availability or stigma. They may use internet-based interventions as an alternative way of obtaining support. Internet-based interventions have previously been shown to be effective in reducing alcohol consumption in studies that included hazardous use; however, few studies have been conducted with a specific focus on harmful use or alcohol dependence. The importance of therapist guidance in internet-based cognitive behavioral therapy (ICBT) programs is still unclear. Objective: This trial aims to investigate the effects of a web-based alcohol program with or without therapist guidance among anonymous adult help-seekers. Methods: A three-armed randomized controlled trial was conducted to compare therapist-guided ICBT and self-help ICBT with an information-only control condition. Swedish-speaking adult internet users with alcohol dependence (3 or more International Classification of Diseases, Tenth Revision criteria) or harmful alcohol use (alcohol use disorder identification test>15) were included in the study. Participants in the therapist-guided ICBT and self-help ICBT groups had 12-week access to a program consisting of 5 main modules, as well as a drinking calendar with automatic feedback. Guidance was given by experienced therapists trained in motivational interviewing. The primary outcome measure was weekly alcohol consumption in standard drinks (12 g of ethanol). Secondary outcomes were alcohol-related problems measured using the total alcohol use disorder identification test-score, diagnostic criteria for alcohol dependence and alcohol use disorder, depression, anxiety, health, readiness to change, and access to other treatments or support. Follow-up was conducted 3 (posttreatment) and 6 months after recruitment. Results: During the recruitment period, from March 2015 to March 2017, 1169 participants were included. Participants had a mean age of 45 (SD 13) years, and 56.72% (663/1169) were women. At the 3-month follow-up, the therapist-guided ICBT and control groups differed significantly in weekly alcohol consumption (−3.84, 95% Cl −6.53 to −1.16; t417=2.81; P=.005; Cohen d=0.27). No significant differences were found in weekly alcohol consumption between the self-help ICBT group and the therapist-guided ICBT at 3 months, between the self-help ICBT and the control group at 3 months, or between any of the groups at the 6-month follow-up. A limitation of the study was the large number of participants who were completely lost to follow-up (477/1169, 40.8%). Conclusions: In this study, a therapist-guided ICBT program was not found to be more effective than the same program in a self-help ICBT version for reducing alcohol consumption or other alcohol-related outcomes. In the short run, therapist-guided ICBT was more effective than information. Only some internet help-seekers may need a multisession program and therapist guidance to change their drinking when they use internet-based interventions. Trial Registration: ClinicalTrials.gov NCT02377726; https://clinicaltrials.gov/ct2/show/NCT02377726 %M 34821563 %R 10.2196/29666 %U https://www.jmir.org/2021/11/e29666 %U https://doi.org/10.2196/29666 %U http://www.ncbi.nlm.nih.gov/pubmed/34821563 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 11 %P e32306 %T A Smartphone-Based Self-Management Intervention for Individuals with Bipolar Disorder (LiveWell): Qualitative Study on User Experiences of the Behavior Change Process %A Jonathan,Geneva K %A Dopke,Cynthia A %A Michaels,Tania %A Martin,Clair R %A Ryan,Chloe %A McBride,Alyssa %A Babington,Pamela %A Goulding,Evan H %+ Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Dr Suite 1520, Chicago, IL, 60660, United States, 1 312 503 1189, e-goulding@fsm.northwestern.edu %K behavioral intervention technology %K mHealth %K bipolar disorder %K depression %K illness management %K smartphone %K behavior change %K early warning signs %K self-management %K qualitative %K behavior %K intervention %K management %K user experience %K perception %K utilization %D 2021 %7 22.11.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Bipolar disorder is a severe mental illness characterized by recurrent episodes of depressed, elevated, and mixed mood states. The addition of psychotherapy to pharmacological management can decrease symptoms, lower relapse rates, and improve quality of life; however, access to psychotherapy is limited. Mental health technologies such as smartphone apps are being studied as a means to increase access to and enhance the effectiveness of adjunctive psychotherapies for bipolar disorder. Individuals with bipolar disorder find this intervention format acceptable, but our understanding of how people utilize and integrate these tools into their behavior change and maintenance processes remains limited. Objective: The objective of this study was to explore how individuals with bipolar disorder perceive and utilize a smartphone intervention for health behavior change and maintenance. Methods: Individuals with bipolar disorder were recruited via flyers placed at university-affiliated and private outpatient mental health practices to participate in a pilot study of LiveWell, a smartphone-based self-management intervention. At the end of the study, all participants completed in-depth qualitative exit interviews. The behavior change framework developed to organize the intervention design was used to deductively code behavioral targets and determinants involved in target engagement. Inductive coding was used to identify themes not captured by this framework. Results: In terms of behavioral targets, participants emphasized the importance of managing mood episode–related signs and symptoms. They also discussed the importance of maintaining regular routines, sleep duration, and medication adherence. Participants emphasized that receiving support from a coach as well as seeking and receiving assistance from family, friends, and providers were important for managing behavioral targets and staying well. In terms of determinants, participants stressed the important role of monitoring for their behavior change and maintenance efforts. Monitoring facilitated self-awareness and reflection, which was considered valuable for staying well. Some participants also felt that the intervention facilitated learning information necessary for managing bipolar disorder but others felt that the information provided was too basic. Conclusions: In addition to addressing acceptability, satisfaction, and engagement, a person-based design of mental health technologies can be used to understand how people experience the impact of these technologies on their behavior change and maintenance efforts. This understanding may then be used to guide ongoing intervention development. The participants’ perceptions aligned with the intervention’s primary behavioral targets and use of a monitoring tool as a core intervention feature. Participant feedback further indicates that developing additional content and tools to address building and engaging social support may be an important avenue for improving LiveWell. A comprehensive behavior change framework to understand participant perceptions of their behavior change and maintenance efforts may help facilitate ongoing intervention development. %M 34813488 %R 10.2196/32306 %U https://mental.jmir.org/2021/11/e32306 %U https://doi.org/10.2196/32306 %U http://www.ncbi.nlm.nih.gov/pubmed/34813488 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 11 %P e32521 %T Smartband-Based Automatic Smoking Detection and Real-time Mindfulness Intervention: Protocol for a Feasibility Trial %A Horvath,Mark %A Grutman,Aurora %A O'Malley,Stephanie S %A Gueorguieva,Ralitza %A Khan,Nashmia %A Brewer,Judson A %A Garrison,Kathleen A %+ Department of Psychiatry, Yale School of Medicine, 1 Church Street #730, New Haven, CT, 06510, United States, 1 4152608618, kathleen.garrison@yale.edu %K smartband %K smartphone %K smoking %K mindfulness %K craving %K mHealth %D 2021 %7 16.11.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Smoking is the leading cause of preventable death in the United States. Smoking cessation interventions delivered by smartphone apps are a promising tool for helping smokers quit. However, currently available smartphone apps for smoking cessation have not exploited their unique potential advantages to aid quitting. Notably, few to no available apps use wearable technologies, most apps require users to self-report their smoking, and few to no apps deliver treatment automatically contingent upon smoking. Objective: This pilot trial tests the feasibility of using a smartband and smartphone to monitor and detect smoking and deliver brief mindfulness interventions in real time to reduce smoking. Methods: Daily smokers (N=100, ≥5 cigarettes per day) wear a smartband for 60 days to monitor and detect smoking, notify them about their smoking events in real time, and deliver real-time brief mindfulness exercises triggered by detected smoking events or targeted at predicted smoking events. Smokers set a quit date at 30 days. A three-step intervention to reduce smoking is tested. First, participants wear a smartband to monitor and detect smoking, and notify them of smoking events in real time to bring awareness to smoking and triggers for 21 days. Next, a “mindful smoking” exercise is triggered by detected smoking events to bring a clear recognition of the actual effects of smoking for 7 days. Finally, after their quit date, a “RAIN” (recognize, allow, investigate, nonidentification) exercise is delivered to predicted smoking events (based on the initial 3 weeks of tracking smoking data) to help smokers learn to work mindfully with cravings rather than smoke for 30 days. The primary outcomes are feasibility measures of treatment fidelity, adherence, and acceptability. The secondary outcomes are smoking rates at end of treatment. Results: Recruitment for this trial started in May 2021 and will continue until November 2021 or until enrollment is completed. Data monitoring and management are ongoing for enrolled participants. The final 60-day end of treatment data is anticipated in January 2022. We expect that all trial results will be available in April 2022. Conclusions: Findings will provide data and information on the feasibility of using a smartband and smartphone to monitor and detect smoking and deliver real-time brief mindfulness interventions, and whether the intervention warrants additional testing for smoking cessation. Trial Registration: ClinicalTrials.gov NCT03995225; https://clinicaltrials.gov/ct2/show/NCT03995225 International Registered Report Identifier (IRRID): DERR1-10.2196/32521 %M 34783663 %R 10.2196/32521 %U https://www.researchprotocols.org/2021/11/e32521 %U https://doi.org/10.2196/32521 %U http://www.ncbi.nlm.nih.gov/pubmed/34783663 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 11 %P e30332 %T Experiences of Wearable Technology by Persons with Knee Osteoarthritis Participating in a Physical Activity Counseling Intervention: Qualitative Study Using a Relational Ethics Lens %A Leese,Jenny %A MacDonald,Graham %A Backman,Catherine L %A Townsend,Anne %A Nimmon,Laura %A Li,Linda C %+ Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada, 1 604 207 4020, lli@arthritisresearch.ca %K relational ethics %K physical activity %K wearable %K arthritis %K qualitative %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Current evidence indicates physical activity wearables could support persons with knee osteoarthritis (OA) to be more physically active. However, recent evidence also identifies some persons with arthritis experience guilt or worry while using a wearable if they are not as active as they feel they should be. Questions remain around how persons with knee OA experience benefits or downsides using a wearable in their everyday lives. Better understanding is needed if wearables are to be incorporated in arthritis self-management in ethically aware ways. Objective: Using an ethics lens, we aimed to describe a range of experiences from persons with knee OA who used a wearable during a physical activity counseling intervention study. Methods: This is a secondary analysis of qualitative interviews nested within a randomized controlled trial. Guided by phenomenography, we explored the experiences of persons with knee OA following participation in a physical activity counseling intervention that involved using a Fitbit Flex and biweekly phone calls with a study physiotherapist (PT) in an 8-week period. Benefits or downsides experienced in participants’ relationships with themselves or the study PT when using the wearable were identified using a relational ethics lens. Results: Interviews with 21 participants (12 females and 9 males) aged 40 to 82 years were analyzed. Education levels ranged from high school graduates (4/21, 19%) to bachelor’s degrees or above (11/21, 52%). We identified 3 categories of description: (1) participants experienced their wearable as a motivating or nagging influence to be more active, depending on how freely they were able to make autonomous choices about physical activity in their everyday lives; (2) some participants felt a sense of accomplishment from seeing progress in their wearable data, which fueled their motivation; (3) for some participants, sharing wearable data helped to build mutual trust in their relationship with the study PT. However, they also expressed there was potential for sharing wearable data to undermine this trust, particularly if this data was inaccurate. Conclusions: Findings provide an early glimpse into positive and negative emotional impacts of using a wearable that can be experienced by participants with knee OA when participating in a randomized controlled trial to support physical activity. To our knowledge, this is the first qualitative study that uses a relational ethics lens to explore how persons with arthritis experienced changes in their relationship with a health professional when using a wearable during research participation. %M 34766912 %R 10.2196/30332 %U https://mhealth.jmir.org/2021/11/e30332 %U https://doi.org/10.2196/30332 %U http://www.ncbi.nlm.nih.gov/pubmed/34766912 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 11 %P e22218 %T Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study %A Martinez,Gonzalo J %A Mattingly,Stephen M %A Robles-Granda,Pablo %A Saha,Koustuv %A Sirigiri,Anusha %A Young,Jessica %A Chawla,Nitesh %A De Choudhury,Munmun %A D'Mello,Sidney %A Mark,Gloria %A Striegel,Aaron %+ Computer Science and Engineering, University of Notre Dame, 400 Main Building, Notre Dame, IN, 46556, United States, 1 574 631 5000, gmarti11@nd.edu %K adherence %K compliance %K wearables %K smartphones %K research design %K ecological momentary assessment %K mobile sensing %K mobile phone %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Studies that use ecological momentary assessments (EMAs) or wearable sensors to track numerous attributes, such as physical activity, sleep, and heart rate, can benefit from reductions in missing data. Maximizing compliance is one method of reducing missing data to increase the return on the heavy investment of time and money into large-scale studies. Objective: This paper aims to identify the extent to which compliance can be prospectively predicted from individual attributes and initial compliance. Methods: We instrumented 757 information workers with fitness trackers for 1 year and conducted EMAs in the first 56 days of study participation as part of an observational study. Their compliance with the EMA and fitness tracker wearing protocols was analyzed. Overall, 31 individual characteristics (eg, demographics and personalities) and behavioral variables (eg, early compliance and study portal use) were considered, and 14 variables were selected to create beta regression models for predicting compliance with EMAs 56 days out and wearable compliance 1 year out. We surveyed study participation and correlated the results with compliance. Results: Our modeling indicates that 16% and 25% of the variance in EMA compliance and wearable compliance, respectively, could be explained through a survey of demographics and personality in a held-out sample. The likelihood of higher EMA and wearable compliance was associated with being older (EMA: odds ratio [OR] 1.02, 95% CI 1.00-1.03; wearable: OR 1.02, 95% CI 1.01-1.04), speaking English as a first language (EMA: OR 1.38, 95% CI 1.05-1.80; wearable: OR 1.39, 95% CI 1.05-1.85), having had a wearable before joining the study (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.50, 95% CI 1.23-1.83), and exhibiting conscientiousness (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.34, 95% CI 1.14-1.58). Compliance was negatively associated with exhibiting extraversion (EMA: OR 0.74, 95% CI 0.64-0.85; wearable: OR 0.67, 95% CI 0.57-0.78) and having a supervisory role (EMA: OR 0.65, 95% CI 0.54-0.79; wearable: OR 0.66, 95% CI 0.54-0.81). Furthermore, higher wearable compliance was negatively associated with agreeableness (OR 0.68, 95% CI 0.56-0.83) and neuroticism (OR 0.85, 95% CI 0.73-0.98). Compliance in the second week of the study could help explain more variance; 62% and 66% of the variance in EMA compliance and wearable compliance, respectively, was explained. Finally, compliance correlated with participants’ self-reflection on the ease of participation, usefulness of our compliance portal, timely resolution of issues, and compensation adequacy, suggesting that these are avenues for improving compliance. Conclusions: We recommend conducting an initial 2-week pilot to measure trait-like compliance and identify participants at risk of long-term noncompliance, performing oversampling based on participants’ individual characteristics to avoid introducing bias in the sample when excluding data based on noncompliance, using an issue tracking portal, and providing special care in troubleshooting to help participants maintain compliance. %M 34766911 %R 10.2196/22218 %U https://mhealth.jmir.org/2021/11/e22218 %U https://doi.org/10.2196/22218 %U http://www.ncbi.nlm.nih.gov/pubmed/34766911 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e26221 %T Dropout From an Internet-Delivered Cognitive Behavioral Therapy Intervention for Adults With Depression and Anxiety: Qualitative Study %A Lawler,Kate %A Earley,Caroline %A Timulak,Ladislav %A Enrique,Angel %A Richards,Derek %+ E-Mental Health Research Group, School of Psychology, Trinity College Dublin, College Green, Dublin, Ireland, 353 851510008, lawlerka@tcd.ie %K depression %K anxiety %K iCBT %K dropout %K internet interventions %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Treatment dropout continues to be reported from internet-delivered cognitive behavioral therapy (iCBT) interventions, and lower completion rates are generally associated with lower treatment effect sizes. However, evidence is emerging to suggest that completion of a predefined number of modules is not always necessary for clinical benefit or consideration of the needs of each individual patient. Objective: The aim of this study is to perform a qualitative analysis of patients’ experiences with an iCBT intervention in a routine care setting to achieve a deeper insight into the phenomenon of dropout. Methods: A total of 15 purposively sampled participants (female: 8/15, 53%) from a larger parent randomized controlled trial were interviewed via telephone using a semistructured interview schedule that was developed based on the existing literature and research on dropout in iCBT. Data were analyzed using a descriptive-interpretive approach. Results: The experience of treatment leading to dropout can be understood in terms of 10 domains: relationship to technology, motivation to start, background knowledge and attitudes toward iCBT, perceived change in motivation, usage of the program, changes due to the intervention, engagement with content, experience interacting with the supporter, experience of web-based communication, and termination of the supported period. Conclusions: Patients who drop out of treatment can be distinguished in terms of their change in motivation: those who felt ready to leave treatment early and those who had negative reasons for dropping out. These 2 groups of participants have different treatment experiences, revealing the potential attributes and nonattributes of dropout. The reported between-group differences should be examined further to consider those attributes that are strongly descriptive of the experience and regarded less important than those that have become loosely affiliated. %M 34766909 %R 10.2196/26221 %U https://formative.jmir.org/2021/11/e26221 %U https://doi.org/10.2196/26221 %U http://www.ncbi.nlm.nih.gov/pubmed/34766909 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 11 %P e29866 %T The Influence of Gender and Age on the Outcomes of and Adherence to a Digital Interdisciplinary Mental Health Promotion Intervention in an Australasian Nonclinical Setting: Cohort Study %A Przybylko,Geraldine %A Morton,Darren %A Morton,Jason %A Renfrew,Melanie %+ Lifestyle Medicine and Health Research Centre, Avondale University, 582 Freemans Drive, Cooranbong, 2265, Australia, 61 418574001, geraldineprzybylko@eliawellness.com %K age %K gender %K adherence %K digital health %K interdisciplinary %K mental health %K promotion %K intervention %K lifestyle medicine %K positive psychology %K multicomponent %K lifestyle %K outcome %K cohort study %D 2021 %7 11.11.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: The global prevalence of mental health disorders is at a crisis point, particularly in the wake of COVID-19, prompting calls for the development of digital interdisciplinary mental health promotion interventions (MHPIs) for nonclinical cohorts. However, the influence of gender and age on the outcomes of and adherence to MHPIs is not well understood. Objective: The aim of this study was to determine the influence of gender and age on the outcomes of and adherence to a 10-week digital interdisciplinary MHPI that integrates strategies from positive psychology and lifestyle medicine and utilizes persuasive systems design (PSD) principles in a nonclinical setting. Methods: This study involved 488 participants who completed the digital interdisciplinary MHPI. Participants completed a pre and postintervention questionnaire that used: (1) the “mental health” and “vitality” subscales from the Short Form 36 (SF-36) Health Survey; (2) the Depression, Anxiety and Stress Scale (DASS-21); and (3) Satisfaction With Life Scale (SWL). Adherence to the digital interdisciplinary MHPI was measured by the number of educational videos the participants viewed and the extent to which they engaged in experiential challenge activities offered as part of the program. Results: On average, the participants (N=488; mean age 47.1 years, SD 14.1; 77.5% women) demonstrated statistically significant improvements in all mental health and well-being outcome measures, and a significant gender and age interaction was observed. Women tended to experience greater improvements than men in the mental health and well-being measures, and older men experienced greater improvements than younger men in the mental health and vitality subscales. Multiple analysis of variance results of the adherence measures indicated a significant difference for age but not gender. No statistically significant interaction between gender and age was observed for adherence measures. Conclusions: Digital interdisciplinary MHPIs that utilize PSD principles can improve the mental health and well-being of nonclinical cohorts, regardless of gender or age. Hence, there may be a benefit in utilizing PSD principles to develop universal MHPIs such as that employed in this study, which can be used across gender and age groups. Future research should examine which PSD principles optimize universal digital interdisciplinary MHPIs. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12619000993190; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377889 and Australian New Zealand Clinical Trials Registry ACTRN12619001009101; http://www.anzctr.org.au/ACTRN12619001009101.aspx %M 34762058 %R 10.2196/29866 %U https://mental.jmir.org/2021/11/e29866 %U https://doi.org/10.2196/29866 %U http://www.ncbi.nlm.nih.gov/pubmed/34762058 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 11 %P e32847 %T Mechanisms of Smartphone Apps for Cigarette Smoking Cessation: Results of a Serial Mediation Model From the iCanQuit Randomized Trial %A Bricker,Jonathan B %A Levin,Michael %A Lappalainen,Raimo %A Mull,Kristin %A Sullivan,Brianna %A Santiago-Torres,Margarita %+ Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M3-B232, Seattle, WA, 98109, United States, 1 2066675074, jbricker@fredhutch.org %K mediation %K engagement %K digital %K mHealth: smartphone %K acceptance %K smoking %K cessation %K app %K randomized controlled trial %K model %K intervention %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Engagement with digital interventions is a well-known predictor of treatment outcomes, but this knowledge has had limited actionable value. Instead, learning why engagement with digital interventions impact treatment outcomes can lead to targeted improvements in their efficacy. Objective: This study aimed to test a serial mediation model of an Acceptance and Commitment Therapy (ACT) smartphone intervention for smoking cessation. Methods: In this randomized controlled trial, participants (N=2415) from 50 US states were assigned to the ACT-based smartphone intervention (iCanQuit) or comparison smartphone intervention (QuitGuide). Their engagement with the apps (primary measure: number of logins) was measured during the first 3 months, ACT processes were measured at baseline and 3 months (acceptance of internal cues to smoke, valued living), and smoking cessation was measured at 12 months with 87% follow-up retention. Results: There was a significant serial mediation effect of iCanQuit on smoking cessation through multiple indicators of intervention engagement (ie, total number of logins, total number of minutes used, and total number of unique days of use) and in turn through increases in mean acceptance of internal cues to smoke from baseline to 3 months. Analyses of the acceptance subscales showed that the mediation was through acceptance of physical sensations and emotions, but not acceptance of thoughts. There was no evidence that the effect of the iCanQuit intervention was mediated through changes in valued living. Conclusions: In this first study of serial mediators underlying the efficacy of smartphone apps for smoking cessation, our results suggest the effect of the iCanQuit ACT-based smartphone app on smoking cessation was mediated through multiple indicators of engagement and in turn through increases in the acceptance of physical sensations and emotions that cue smoking. Trial Registration: Clinical Trials.gov NCT02724462; https://clinicaltrials.gov/ct2/show/NCT02724462 %M 34751662 %R 10.2196/32847 %U https://mhealth.jmir.org/2021/11/e32847 %U https://doi.org/10.2196/32847 %U http://www.ncbi.nlm.nih.gov/pubmed/34751662 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 11 %P e30622 %T The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis %A Carey,Alissa %A Yang,Qiuchen %A DeLuca,Laura %A Toro-Ramos,Tatiana %A Kim,Youngin %A Michaelides,Andreas %+ Academic Research, Noom Inc, Fl 9, 229 W 28th St, New York, NY, 10001, United States, 1 631 938 1248, andreas@noom.com %K engagement %K mHealth %K obesity %K weight management %K Noom %K application %K app %K behavioral change %K digital behavior change interventions %D 2021 %7 8.11.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: There is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss. Objective: This retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks. Methods: Engagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks. Results: At 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group. Conclusions: Our results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs. %M 34747706 %R 10.2196/30622 %U https://mhealth.jmir.org/2021/11/e30622 %U https://doi.org/10.2196/30622 %U http://www.ncbi.nlm.nih.gov/pubmed/34747706 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 11 %P e27282 %T Identifying App-Based Meditation Habits and the Associated Mental Health Benefits: Longitudinal Observational Study %A Stecher,Chad %A Berardi,Vincent %A Fowers,Rylan %A Christ,Jaclyn %A Chung,Yunro %A Huberty,Jennifer %+ College of Health Solutions, Arizona State University, 500 N 3rd Street, Phoenix, AZ, 85003, United States, 1 6024960957, chad.stecher@asu.edu %K behavioral habits %K habit formation %K mindfulness meditation %K mental health %K mHealth %K mobile health %K dynamic time warping %K mobile phone %D 2021 %7 4.11.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Behavioral habits are often initiated by contextual cues that occur at approximately the same time each day; so, it may be possible to identify a reflexive habit based on the temporal similarity of repeated daily behavior. Mobile health tools provide the detailed, longitudinal data necessary for constructing such an indicator of reflexive habits, which can improve our understanding of habit formation and help design more effective mobile health interventions for promoting healthier habits. Objective: This study aims to use behavioral data from a commercial mindfulness meditation mobile phone app to construct an indicator of reflexive meditation habits based on temporal similarity and estimate the association between temporal similarity and meditation app users’ perceived health benefits. Methods: App-use data from June 2019 to June 2020 were analyzed for 2771 paying subscribers of a meditation mobile phone app, of whom 86.06% (2359/2771) were female, 72.61% (2012/2771) were college educated, 86.29% (2391/2771) were White, and 60.71% (1664/2771) were employed full-time. Participants volunteered to complete a survey assessing their perceived changes in physical and mental health from using the app. Receiver operating characteristic curve analysis was used to evaluate the ability of the temporal similarity measure to predict future behavior, and variable importance statistics from random forest models were used to corroborate these findings. Logistic regression was used to estimate the association between temporal similarity and self-reported physical and mental health benefits. Results: The temporal similarity of users’ daily app use before completing the survey, as measured by the dynamic time warping (DTW) distance between app use on consecutive days, significantly predicted app use at 28 days and at 6 months after the survey, even after controlling for users’ demographic and socioeconomic characteristics, total app sessions, duration of app use, and number of days with any app use. In addition, the temporal similarity measure significantly increased in the area under the receiver operating characteristic curve (AUC) for models predicting any future app use in 28 days (AUC=0.868 with DTW and 0.850 without DTW; P<.001) and for models predicting any app use in 6 months (AUC=0.821 with DTW and 0.802 without DTW; P<.001). Finally, a 1% increase in the temporal similarity of users’ daily meditation practice with the app over 6 weeks before the survey was associated with increased odds of reporting mental health improvements, with an odds ratio of 2.94 (95% CI 1.832-6.369). Conclusions: The temporal similarity of the meditation app use was a significant predictor of future behavior, which suggests that this measure can identify reflexive meditation habits. In addition, temporal similarity was associated with greater perceived mental health benefits, which demonstrates that additional mental health benefits may be derived from forming reflexive meditation habits. %M 34734826 %R 10.2196/27282 %U https://www.jmir.org/2021/11/e27282 %U https://doi.org/10.2196/27282 %U http://www.ncbi.nlm.nih.gov/pubmed/34734826 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 11 %P e31483 %T Benefits, Problems, and Potential Improvements in a Nationwide Patient Portal: Cross-sectional Survey of Pharmacy Customers’ Experiences %A Sääskilahti,Maria %A Ojanen,Anna %A Ahonen,Riitta %A Timonen,Johanna %+ School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, PO Box 1627, Kuopio, 70211, Finland, 358 403552505, maria.saaskilahti@uef.fi %K benefit %K problem %K improvement need %K patient portal %K patient engagement %K experience %K survey %D 2021 %7 3.11.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient engagement is a worldwide trend in health care. Patient portals have the potential to increase patients’ knowledge about their health and care and therefore enhance patient engagement. Portal users’ experiences are needed to determine if these portals work appropriately and if there are barriers to achieving the aims that were set before their implementation. Objective: The aim of this study is to analyze pharmacy customers’ experiences of the Finnish nationwide patient portal My Kanta in terms of benefits, problems, and potential improvements. Methods: A questionnaire survey was conducted among pharmacy customers in the spring of 2019. The questionnaires (N=2866) were distributed from 18 community pharmacies across mainland Finland to customers aged ≥18 years who were purchasing prescription medicines for themselves or their children aged <18 years. Using open-ended questions, customers were asked about their experiences of the benefits and problems of My Kanta and what improvements could be made. Their responses were encoded and categorized using inductive content analysis, stored in SPSS Statistics for Windows, and analyzed using frequencies. Results: Of the 2866 questionnaires, a total of 994 (34.68%) questionnaires were included in the analysis. Most respondents were My Kanta users (820/994, 82.5%); of these 820 users, 667 (81.3%) reported at least one benefit, 311 (37.9%) reported at least one problem, and 327 (39.9%) reported at least one potential improvement when using My Kanta. The most commonly mentioned benefits were opportunities to view health data (290/667, 43.5%) and prescriptions (247/667, 37%) and to renew prescriptions (220/667, 33%). The most extensively reported problems with My Kanta were that the portal lacks health data (71/311, 22.8%), navigating the service and searching for information is difficult (68/311, 21.9%), and the delay before health data are incorporated into the service (41/311, 13.2%). The most frequently suggested potential improvements were that My Kanta needs more comprehensive health data (89/327, 27.2%); the service should be easier to navigate and information easier to access (71/327, 21.7%); the service should have more functions (51/327, 15.6%); and health data should be entered into the portal more promptly (47/327, 14.4%). Conclusions: Pharmacy customers reported more benefits than problems or potential improvements regarding the use of My Kanta. The service is useful for viewing health data and prescriptions and for renewing prescriptions. However, portal users would like to see more data and functions available in the portal and data searches to be made easier. These improvements could make the data and functions provided by the portal easier to view and use and hence promote patient engagement. %M 34730542 %R 10.2196/31483 %U https://www.jmir.org/2021/11/e31483 %U https://doi.org/10.2196/31483 %U http://www.ncbi.nlm.nih.gov/pubmed/34730542 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 11 %P e31274 %T Adherence With Online Therapy vs Face-to-Face Therapy and With Online Therapy vs Care as Usual: Secondary Analysis of Two Randomized Controlled Trials %A Lippke,Sonia %A Gao,Lingling %A Keller,Franziska Maria %A Becker,Petra %A Dahmen,Alina %+ Department of Psychology and Methods, Jacobs University Bremen, Campus Ring 1, Bremen, 28759, Germany, 49 421200 ext 4730, s.lippke@jacobs-university.de %K psychotherapeutic aftercare %K medical rehabilitation %K online therapy %K face-to-face therapy %K care as usual %K retention %K dropout %D 2021 %7 3.11.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Adherence to internet-delivered interventions targeting mental health such as online psychotherapeutic aftercare is important for the intervention’s impact. High dropout rates limit the impact and generalizability of findings. Baseline differences may be putting patients at risk for dropping out, making comparisons between online with face-to-face (F2F) therapy and care as usual (CAU) necessary to examine. Objective: This study investigated adherence to online, F2F, and CAU interventions as well as study dropout among these groups and the subjective evaluation of the therapeutic relationship. Sociodemographic, social-cognitive, and health-related variables were considered. Methods: In a randomized controlled trial, 6023 patients were recruited, and 300 completed the baseline measures (T1), 144 completed T2 (retention 44%-52%), and 95 completed T3 (retention 24%-36%). Sociodemographic variables (eg, age, gender, marital status, educational level), social-cognitive determinants (eg, self-efficacy, social support), health-related variables (eg, depressiveness), and expectation towards the treatment for patients assigned to online or F2F were measured at T1. Results: There were no significant differences between the groups regarding dropout rates (χ21=0.02-1.06, P≥.30). Regarding adherence to the treatment condition, the online group outperformed the F2F and CAU conditions (P≤.01), indicating that patients randomized into the F2F and CAU control groups were much more likely to show nonadherent behavior in comparison with the online therapy groups. Within study groups, gender differences were significant only in the CAU group at T2, with women being more likely to drop out. At T3, age and marital status were also only significant in the CAU group. Patients in the online therapy group were significantly more satisfied with their treatment than patients in the F2F group (P=.02; Eta²=.09). Relationship satisfaction and success satisfaction were equally high (P>.30; Eta²=.02). Combining all study groups, patients who reported lower depressiveness scores at T1 (T2: odds ratio [OR] 0.55, 95% CI 0.35-0.87; T3: OR 0.56, 95% CI 0.37-0.92) were more likely to be retained, and patients who had higher self-efficacy (T2: OR 0.57, 95% CI 0.37-0.89; T3: OR 0.52, 95% CI 0.32-0.85) were more likely to drop out at T2 and T3. Additionally, at T3, the lower social support that patients reported was related to a higher likelihood of remaining in the study (OR 0.68, 95% CI 0.48-0.96). Comparing the 3 intervention groups, positive expectation was significantly related with questionnaire completion at T2 and T3 after controlling for other variables (T2: OR 1.64, 95% CI 1.08-2.50; T3: OR 1.59, 95% CI 1.01-2.51). Conclusions: While online interventions have many advantages over F2F variants such as saving time and effort to commute to F2F therapy, they also create difficulties for therapists and hinder their ability to adequately react to patients’ challenges. Accordingly, patient characteristics that might put them at risk for dropping out or not adhering to the treatment plan should be considered in future research and practice. Online aftercare, as described in this research, should be provided more often to medical rehabilitation patients. Trial Registration: ClinicalTrials.gov NCT04989842; https://clinicaltrials.gov/ct2/show/NCT04989842 %M 34730541 %R 10.2196/31274 %U https://www.jmir.org/2021/11/e31274 %U https://doi.org/10.2196/31274 %U http://www.ncbi.nlm.nih.gov/pubmed/34730541 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e25749 %T A Mobile App to Enhance Behavioral Activation Treatment for Substance Use Disorder: App Design, Use, and Integration Into Treatment in the Context of a Randomized Controlled Trial %A Paquette,Catherine E %A Rubalcava,Dillon T %A Chen,Yun %A Anand,Deepika %A Daughters,Stacey B %+ Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, 235 E. Cameron Avenue, Chapel Hill, NC, 27599-3270, United States, 1 919 962 9924, daughter@unc.edu %K substance use disorder %K smartphone app %K mHealth %K behavioral activation %K mobile phone %D 2021 %7 3.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Group-based formats typically used in low-resource substance use disorder (SUD) treatment settings result in little individual attention to help reinforce and guide skill use, which may contribute to poor posttreatment outcomes. Smartphone apps offer a convenient, user-friendly, and cost-effective tool that can extend the reach of effective SUD treatments. A smartphone app was developed and integrated into a group-based, brief behavioral activation (BA) treatment for SUD to increase engagement in treatment skills outside clinician-administered sessions. Objective: This study aims to describe the features of the app and its use and integration into treatment, report the participants’ self-reported feasibility and acceptability of the app, and discuss challenges and provide recommendations for future smartphone app integration into behavioral treatments for SUD. Methods: A total of 56 individuals recruited from intensive outpatient SUD treatment received a smartphone-enhanced BA treatment, the Life Enhancement Treatment for Substance Use. Self-reported weekly app use and reasons for nonuse were assessed at posttreatment and at 1- and 3-month follow-ups. In addition, 2-tailed t tests and chi-square tests compared the self-reported use of each app component and overall app use over time. Results: Participant feedback suggested that the integration of the smartphone app into the Life Enhancement Treatment for Substance Use was feasible and well accepted, and participants found the app useful for planning value-based activities outside of sessions. Self-reported app engagement decreased over the follow-up period: 72% (39/54) of participants reported using the app at posttreatment, decreasing to 69% (37/54) at the 1-month follow-up and 37% (20/54) at the 3-month follow-up. Participants reported forgetting to use the app as a primary reason for nonuse. Conclusions: This study provides support for the feasibility and acceptability of smartphone-enhanced BA treatment, offering promise for future research testing the integration of technology into SUD treatment. Design decisions may help streamline smartphone integration into treatment, for example, allowing participants to download the treatment app on their own phones or use a low-cost study smartphone (or offering both options). Long-term app engagement may be increased via built-in reminders, alerts, and in-app messages. Trial Registration: ClinicalTrials.gov NCT02707887; https://clinicaltrials.gov/ct2/show/study/NCT02707887 %M 34730535 %R 10.2196/25749 %U https://formative.jmir.org/2021/11/e25749 %U https://doi.org/10.2196/25749 %U http://www.ncbi.nlm.nih.gov/pubmed/34730535 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e26136 %T Conducting Health Literacy Research With Hard-to-Reach Regional Culturally and Linguistically Diverse Populations: Evaluation Study of Recruitment and Retention Methods Before and During COVID-19 %A Perrins,Genevieve %A Ferdous,Tabassum %A Hay,Dawn %A Harreveld,Bobby %A Reid-Searl,Kerry %+ Central Queensland Multicultural Association, CQUniversity Rockhampton North, Room 31, Building 41 Buzacott Circle, 554-700 Yaamba Road, Norman Gardens, Rockhampton, 4701, Australia, 61 423853809, evie.perrins@cqma.org.au %K health literacy %K cultural and linguistic diversity %K COVID-19 %K health care barriers %K hard-to-reach research participants %K regional Australia %K health literacy profiles %K literacy %D 2021 %7 2.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: In health research, culturally and linguistically diverse (CALD) health care consumers are cited as hidden or hard to reach. This paper evaluates the approach used by researchers to attract and retain hard-to-reach CALD research participants for a study investigating health communication barriers between CALD health care users and health care professionals in regional Australia. As the study was taking place during the COVID-19 pandemic, subsequent restrictions emerged. Thus, recruitment and retention methods were adapted. This evaluation considered the effectiveness of recruitment and retention used throughout the pre-COVID and during-COVID periods. Objective: This evaluation sought to determine the effectiveness of recruitment and retention efforts of researchers during a study that targeted regional hard-to-reach CALD participants. Methods: Recruitment and retention methods were categorized into the following 5 phases: recruitment, preintervention data collection, intervention, postintervention data collection, and interviews. To compare the methods used by researchers, recruitment and retention rates were divided into pre-COVID and during-COVID periods. Thereafter, in-depth reflections of the methods employed within this study were made. Results: This paper provides results relating to participant recruitment and retainment over the course of 5 research phases that occurred before and during COVID. During the pre-COVID recruitment phase, 22 participants were recruited. Of these participants, 15 (68%) transitioned to the next phase and completed the initial data collection phase. By contrast, 18 participants completed the during-COVID recruitment phase, with 13 (72%) continuing to the next phase. The success rate of the intervention phase in the pre-COVID period was 93% (14/15), compared with 84.6% (11/13) in the during-COVID period. Lastly, 93% (13/14) of participants completed the postintervention data collection in the pre-COVID period, compared with 91% (10/11) in the during-COVID period. In total, 40 participants took part in the initial data collection phase, with 23 (58%) completing the 5 research phases. Owing to the small sample size, it was not determined if there was any statistical significance between the groups (pre- and during-COVID periods). Conclusions: The success of this program in recruiting and maintaining regional hard-to-reach CALD populations was preserved over the pre- and during-COVID periods. The pandemic required researchers to adjust study methods, thereby inadvertently contributing to the recruitment and retention success of the project. The maintenance of participants during this period was due to flexibility offered by researchers through adaptive methods, such as the use of cultural gatekeepers, increased visibility of CALD researchers, and use of digital platforms. The major findings of this evaluation are 2-fold. First, increased diversity in the research sample required a high level of flexibility from researchers, meaning that such projects may be more resource intensive. Second, community organizations presented a valuable opportunity to connect with potential hard-to-reach research participants. %M 34581673 %R 10.2196/26136 %U https://formative.jmir.org/2021/11/e26136 %U https://doi.org/10.2196/26136 %U http://www.ncbi.nlm.nih.gov/pubmed/34581673 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e31064 %T Acceptability, Engagement, and Exploratory Outcomes of an Emotional Well-being App: Mixed Methods Preliminary Evaluation and Descriptive Analysis %A Eisenstadt,Amelia %A Liverpool,Shaun %A Metaxa,Athina-Marina %A Ciuvat,Roberta Maria %A Carlsson,Courtney %+ Evidence Based Practice Unit, University College London and Anna Freud National Centre for Children and Families, The Kantor Centre of Excellence, 4-8 Rodney Street, London, N1 9JH, United Kingdom, 44 20 7794 2313, mia.eisenstadt@annafreud.org %K smartphone %K app %K well-being %K awareness %K mental health %K formative %K mobile phone %D 2021 %7 1.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: There is growing evidence suggesting that the emotional well-being of the public has been negatively affected in the past year. Consequently, demand for well-being support has increased. Although there is substantial empirical support for mental health apps that target diagnosed conditions, there is less research on emotional well-being apps. Among existing well-being apps, few studies have been conducted on apps that are based on lived experience and those that seek to enhance users’ understanding of their emotional patterns. Thus, the acceptability of these novel apps requires further evaluation before upscaling. Objective: This evaluation aims to describe the acceptability, engagement, and preliminary outcomes of using an app (Paradym) designed to promote emotional well-being and positive mental health. Methods: This is a pre-post, mixed-methods, single-arm evaluation that is aggregated with digital analytics data. We anonymously collected real-world data on the demographics and well-being of the participants as well as the usability and acceptance of the app using validated questionnaires and open-ended questions. Participants tested the app for a minimum of 2 weeks before completing the follow-up measures. Google Analytics was used to record the level of app engagement. Chi-square and 2-tailed t tests were conducted to analyze quantitative data, and a thematic analysis approach was adopted for qualitative data. Results: A total of 115 participants completed baseline questionnaires, of which 79.1% (91/115) users downloaded the app. The sample was diverse in terms of ethnicity, including 43.4% (50/115) people who self-identified as belonging to minority ethnic groups. Most of the participants were female (78/115, 67.8%) and between the ages of 18 and 25 years (39/115, 33.9%). A total of 34 app users who completed questionnaires at baseline and follow-up provided valuable feedback to inform the future directions of Paradym. Favorable themes emerged describing the app’s content, functionality, and underlying principles. Although usability feedback varied across items, a considerable number of participants (22/34, 64%) found that the app was easy to use. Google Analytics revealed that at least 79% (27/34) of people used the app daily. On the basis of preliminary observations, app users experience increased mental well-being. Post hoc analyses indicated that the reduction in depression scores (t33=−2.16) and the increase in the well-being measures (t33=2.87) were statistically significant. No adverse events were reported during the follow-up period. Conclusions: The findings of this evaluation are encouraging and document positive preliminary evidence for the Paradym app. %M 34569466 %R 10.2196/31064 %U https://formative.jmir.org/2021/11/e31064 %U https://doi.org/10.2196/31064 %U http://www.ncbi.nlm.nih.gov/pubmed/34569466 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e26886 %T Identifying Opportunities, and Motivation to Enhance Capabilities, Influencing the Development of a Personalized Digital Health Hub Model of Care for Hip Fractures: Mixed Methods Exploratory Study %A Yadav,Lalit %A Gill,Tiffany K %A Taylor,Anita %A De Young,Jennifer %A Chehade,Mellick J %+ NHMRC Centre for Research Excellence in Frailty and Healthy Ageing, Adelaide Medical School, University of Adelaide, Level 5G 581, Royal Adelaide Hospital, Adelaide, 5000, Australia, 61 870742006, Lalit.yadav@adelaide.edu.au %K digital health %K mixed-methods %K hip fractures %K behavior change %K patient education %K model of care %K mobile phone %K patient networked units %D 2021 %7 28.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Most older people after a hip fracture injury never return to their prefracture status, and some are admitted to residential aged care facilities. Advancement of digital technology has helped in optimizing health care including self-management and telerehabilitation. Objective: This study aims to understand the perspectives of older patients with hip fracture and their family members and residential aged caregivers on the feasibility of developing a model of care using a personalized digital health hub. Methods: We conducted a mixed methods study in South Australia involving patients aged 50 years and older, their family members, and residential aged caregivers. Quantitative data analysis included basic demographic characteristics, and access to digital devices was analyzed using descriptive statistics. Spearman rank-order correlation was used to examine correlations between the perceived role of a personalized digital health hub in improving health and the likelihood of subsequent use. Findings from qualitative analysis were interpreted using constructs of capability, opportunity, and motivation to help understand the factors influencing the likelihood of potential personalized digital health hub use. Results: This study recruited 100 participants—55 patients, 13 family members, and 32 residential aged caregivers. The mean age of the patients was 76.4 (SD 8.4, range 54-88) years, and 60% (33/55) of the patients were female. Approximately 50% (34/68) of the patients and their family members had access to digital devices, despite less than one-third using computers as part of their occupation. Approximately 72% (72/100) of the respondents thought that personalized digital health hub could improve health outcomes in patients. However, a moderate negative correlation existed with increasing age and likelihood of personalized digital health hub use (Spearman ρ=–0.50; P<.001), and the perceived role of the personalized digital health hub in improving health had a strong positive correlation with the likelihood of personalized digital health hub use by self (Spearman ρ=0.71; P<.001) and by society, including friends and family members (Spearman ρ=0.75; P<.001). Most patients (54/55, 98%) believed they had a family member, friend, or caregiver who would be able to help them use a personalized digital health hub. Qualitative analysis explored capability by understanding aspects of existing knowledge, including willingness to advance digital navigation skills. Access could be improved through supporting opportunities, and factors influencing intrinsic motivation were considered crucial for designing a personalized digital health hub–enabled model of care. Conclusions: This study emphasized the complex relationship between capabilities, motivation, and opportunities for patients, their family members, and formal caregivers as a patient networked unit. The next stage of research will continue to involve a cocreation approach followed by iterative processes and understand the factors influencing the development and successful integration of complex digital health care interventions in real-world scenarios. %M 34709183 %R 10.2196/26886 %U https://www.jmir.org/2021/10/e26886 %U https://doi.org/10.2196/26886 %U http://www.ncbi.nlm.nih.gov/pubmed/34709183 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 10 %P e29397 %T Predictors of Booster Engagement Following a Web-Based Brief Intervention for Alcohol Misuse Among National Guard Members: Secondary Analysis of a Randomized Controlled Trial %A Coughlin,Lara N %A Blow,Frederic C %A Walton,Maureen %A Ignacio,Rosalinda V %A Walters,Heather %A Massey,Lynn %A Barry,Kristen L %A McCormick,Richard %+ Addiction Center, Department of Psychiatry, University of Michigan, 2800 Plymouth Rd, Ann Arbor, MI, 48109, United States, 1 734 615 4774, laraco@med.umich.edu %K alcohol use %K National Guard %K brief intervention %K boosters %K engagement %D 2021 %7 26.10.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Alcohol misuse is a major health concern among military members. Reserve component members face unique barriers as they live off base with limited access to behavioral health services. Web and app-based brief interventions are a promising means to improve access to treatment for those who misuse alcohol, with the use of booster sessions to enhance effectiveness, solidify gains, and reinforce changes. However, little is known about who will engage in booster sessions. Objective: This study aims to evaluate booster engagement across booster delivery modalities (Web and Peer) and identify participant-specific factors associated with booster session engagement. Methods: Following a brief web-based alcohol misuse intervention in National Guard members (N=739), we examined engagement in a series of three booster sessions. Using unadjusted and adjusted models, demographic and clinical characteristics that may serve as predictors of booster session engagement were examined across the 2 arms of the trial with different types of booster sessions: peer-delivered (N=245) and web-delivered (N=246). Results: Booster session completion was greater for Peer than Web Booster sessions, with 142 (58%) service members in the Peer Booster arm completing all three boosters compared with only 108 (44%) of participants in the Web Booster arm (χ23=10.3; P=.006). In a model in which the 2 groups were combined, socioeconomic factors predicted booster engagement. In separate models, the demographic and clinical predictors of booster engagement varied between the 2 delivery modalities. Conclusions: The use of peer-delivered boosters, especially among subsets of reserve members at risk of lack of engagement, may foster greater uptake and improve treatment outcomes. Trial Registration: ClinicalTrials.gov NCT02181283; https://clinicaltrials.gov/ct2/show/NCT02181283 %M 34698652 %R 10.2196/29397 %U https://mental.jmir.org/2021/10/e29397 %U https://doi.org/10.2196/29397 %U http://www.ncbi.nlm.nih.gov/pubmed/34698652 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 10 %P e29913 %T Six-Month Outcomes from the NEXit Junior Trial of a Text Messaging Smoking Cessation Intervention for High School Students: Randomized Controlled Trial With Bayesian Analysis %A Bendtsen,Marcus %A Bendtsen,Preben %A Müssener,Ulrika %+ Department of Health, Medicine and Caring Sciences, Linköping University, Building 511, Linköping, 58183, Sweden, 46 13286975, marcus.bendtsen@liu.se %K smoking %K cessation %K text messaging %K high school %K randomized controlled trial %K intervention %K student %K young adult %K teenager %K outcome %K Bayesian %K Sweden %K prevalence %K lifestyle %K behavior %D 2021 %7 21.10.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The prevalence of daily or occasional smoking among high school students in Sweden was approximately 20% in 2019, which is problematic since lifestyle behaviors are established in adolescence and track into adulthood. The Nicotine Exit (NEXit) Junior trial was conducted in response to a lack of evidence for the effects of text message smoking cessation interventions among high school students in Sweden. Objective: The aim of this study was to estimate the 3- and 6-month effects of a text messaging intervention among high school students in Sweden on smoking cessation outcomes. Methods: A 2-arm, single-blind randomized controlled trial was employed to estimate the effects of the intervention on smoking cessation in comparison to treatment as usual. Participants were recruited from high schools in Sweden using advertising and promotion by school staff from January 10, 2018, to January 10, 2019. Weekly or daily smokers who were willing to make a quit attempt were eligible for inclusion. Prolonged abstinence and point prevalence of smoking cessation were measured at 3 and 6 months after randomization. Results: Complete case analysis was possible on 57.9% (310/535) of the participants at 6 months, with no observed statistically significant effect on 5-month prolonged abstinence (odds ratio [OR] 1.27, 95% CI 0.73-2.20; P=.39) or 4-week smoking cessation (OR 1.42; 95% CI 0.83-2.46; P=.20). Sensitivity analyses using imputation yielded similar findings. Unplanned Bayesian analyses showed that the effects of the intervention were in the anticipated direction. The findings were limited by the risk of bias induced by high attrition (42.1%). The trial recruited high school students in a pragmatic setting and included both weekly and daily smokers; thus, generalization to the target population is more direct compared with findings obtained under more strict study procedures. Conclusions: Higher than expected attrition rates to follow-up 6 months after randomization led to null hypothesis tests being underpowered; however, unplanned Bayesian analyses found that the effects of the intervention were in the anticipated direction. Future trials of smoking cessation interventions targeting high school students should aim to prepare strategies for increasing retention to mid- and long-term follow-up. Trial Registration: IRCTN Registry ISRCTN15396225; https://www.isrctn.com/ISRCTN15396225 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-018-3028-2 %M 34673532 %R 10.2196/29913 %U https://mhealth.jmir.org/2021/10/e29913 %U https://doi.org/10.2196/29913 %U http://www.ncbi.nlm.nih.gov/pubmed/34673532 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 10 %P e22199 %T Acceptance and Use of Telepsychology From the Clients’ Perspective: Questionnaire Study to Document Perceived Advantages and Barriers %A Sora,Beatriz %A Nieto,Rubén %A Montesano del Campo,Adrian %A Armayones,Manuel %+ Department of Psychology, Rovira i Virgili University, Campus Sescelades. Carretera Valls, s/n, Tarragona, 43007, Spain, 34 977558097 ext 8097, beatriz.sora@urv.cat %K telepsychology %K telepsychology advantages %K telepsychology barriers %K telepsychology use %K telepsychology usefulness %K intention to use telepsychology %D 2021 %7 15.10.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Telepsychology is increasingly being incorporated in clinical practice, being offered in many psychotherapy centers, especially after the impact of the pandemic. However, there seems to be a remarkable discrepancy between the offer, or interest in, and real-world uptake of e-mental health interventions among the population. A critical precondition is clients’ willingness to accept and use telepsychology, although this issue has thus far been overlooked in research. Objective: The aim of this study was to examine people’s acceptance and use of telepsychology by adopting an extended model of the unified theory of acceptance and use of technology (UTAUT) that integrates perceived telepsychology advantages and barriers, usefulness perceptions, behavioral intention, and telepsychology use. Methods: An online survey was conducted with a convenience sample of 514 participants. Structural equation models were computed to test a mediation model. Results: Results supported the UTAUT model to explain participants’ acceptance and use of telepsychology. They showed a causal chain in which perceived telepsychology advantages and barriers were related to telepsychology use through the perceived usefulness of and intention to use telepsychology. Conclusions: Telepsychology use may be explained according to the UTAUT model when coupled with participants’ perceptions of telepsychology advantages and barriers. Mental health stakeholders could consider these factors in order to increase the acceptance and use of telepsychology. %M 34652276 %R 10.2196/22199 %U https://mental.jmir.org/2021/10/e22199 %U https://doi.org/10.2196/22199 %U http://www.ncbi.nlm.nih.gov/pubmed/34652276 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e32271 %T Acceptability, Engagement, and Effects of a Mobile Digital Intervention to Support Mental Health for Young Adults Transitioning to College: Pilot Randomized Controlled Trial %A Suffoletto,Brian %A Goldstein,Tina %A Gotkiewicz,Dawn %A Gotkiewicz,Emily %A George,Brandie %A Brent,David %+ Department of Emergency Medicine, Stanford University, 900 Welch Road, Suite 350, Palo Alto, CA, 94304, United States, 1 412 901 6892, suffbp@stanford.edu %K college %K mental health %K self-management %K digital intervention %K mHealth %D 2021 %7 14.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The transition from high school to college can exacerbate mental health problems in young adults yet barriers prevent seamless mental health care. Existing digital support tools show promise but are not yet designed to optimize engagement or implementation. Objective: The goal of the research was to test acceptability and effects of an automated digital Mobile Support Tool for Mental Health (MoST-MH) for young adults transitioning to college. Methods: Youths aged 18 years and older with a current mental health diagnosis preparing to transition to college (n=52; 85% female [45/52], 91% White [48/52]) were recruited from a primary care (n=31) and a mental health clinic (n=21). Participants were randomized 2:1 to either receive MoST-MH (n=34) or enhanced Usual Care (eUC; n=18). MoST-MH included periodic text message and web-based check-ins of emotional health, stressors, negative impacts, and self-efficacy that informed tailored self-care support messages. Both eUC and MoST-MH participants received links to a library of psychoeducational videos and were asked to complete web-based versions of the Mental Health Self-Efficacy Scale (MHSES), College Counseling Center Assessment of Psychological Symptoms (CCAPS), and Client Service Receipt Inventory for Mental Health (C-SRI) monthly for 3 months and the Post-Study System Usability Scale (PSSUQ) at 3-months. Results: MoST-MH participants were sent a median of 5 (range 3 to 10) text message check-in prompts over the 3-month study period and 100% were completed; participants were sent a median of 2 (range 1 to 8) web-based check-in prompts among which 78% (43/55) were completed. PSSUQ scores indicate high usability (mean score 2.0). Results from the completer analysis demonstrated reductions in mental health symptoms over time and significant between-group effects of MoST-MH compared to eUC on depressive symptom severity (d=0.36, 95% CI 0.08 to 0.64). No significant differences in mental health self-efficacy or mental health health care use were observed. Conclusions: In this pilot trial, we found preliminary evidence that MoST-MH was engaged with at high rates and found to be highly usable and reduced depression symptoms relative to eUC among youth with mental health disorders transitioning to college. Findings were measured during the COVID-19 pandemic, and the study was not powered to detect differences in outcomes between groups; therefore, further testing is needed. Trial Registration: ClinicalTrials.gov NCT04560075; https://clinicaltrials.gov/ct2/show/NCT04560075 %M 34647893 %R 10.2196/32271 %U https://formative.jmir.org/2021/10/e32271 %U https://doi.org/10.2196/32271 %U http://www.ncbi.nlm.nih.gov/pubmed/34647893 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e23968 %T Need for Cognition Among Users of Self-Monitoring Systems for Physical Activity: Survey Study %A Halttu,Kirsi %A Oinas-Kukkonen,Harri %+ Oulu Advanced Research on Service and Information Systems Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, P.O. Box 3000, Oulu, FI-90014, Finland, 358 458601190, kirsi.halttu@oulu.fi %K self-monitoring %K wearables %K physical activity tracking %K mHealth %K need for cognition %K persuasive design %K tailoring %K user research %K mobile phone %D 2021 %7 14.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Need for cognition (NFC) is among the most studied personality traits in psychology. Despite its apparent relevance for engaging with technology and the use of information, it has not been studied in the context of self-monitoring systems and wearables for health. This study is the first to explore the relationship between NFC and commercial self-monitoring systems among healthy users. Objective: This study aims to explore the effect of NFC levels on the selection of self-monitoring systems and evaluation of system features of self-monitoring and feedback, as well as perceived credibility and perceived persuasiveness. We also assessed perceived behavior change in the form of self-reported activity after adopting the system. Methods: Survey data were collected in October 2019 among university students and personnel. The invitation to respond to the questionnaire was addressed to those who had used a digital system to monitor their physical activity for at least two months. The web-based questionnaire comprised the following 3 parts: details of system use, partially randomly ordered theoretical measurement items, and user demographics. The data were analyzed using structural equation modeling. The effect of NFC was assessed both as 3 groups (low, moderate, and high) and as a continuous moderator variable. Results: In all, 238 valid responses to the questionnaire were obtained. Individuals with high NFC reported all tested system features with statistically significantly higher scores. The NFC also had some effect on system selection. Hypothesized relationships with perceived credibility gained support in a different way for individuals with low and high NFC; for those with low NFC, credibility increased the persuasiveness of the system, but this effect was absent among individuals with high NFC. For users with high NFC, credibility was related to feedback and self-monitoring and perhaps continuously evaluated during prolonged use instead of being a static system property. Furthermore, the relationship between perceived persuasiveness and self-reported activity after adopting the system had a large effect size (Cohen f2=0.355) for individuals with high NFC, a small effect size for individuals with moderate NFC (Cohen f2=0.107), and a nonsignificant path (P=.16) for those with low NFC. We also detected a moderating effect of NFC in two paths on perceived persuasiveness but only among women. Our research model explained 59.2%, 63.9%, and 47.3% of the variance in perceived persuasiveness of the system among individuals with low, moderate, and high NFC, respectively. Conclusions: The system choices of individuals seem to reflect their intrinsic motivations to engage with rich data, and commercial systems might themselves be a tailoring strategy. Important characteristics of the system, such as perceived credibility, have different roles depending on the NFC levels. Our data demonstrate that NFC as a trait that differentiates information processing has several implications for the selection, design, and tailoring of self-monitoring systems. %M 34647894 %R 10.2196/23968 %U https://formative.jmir.org/2021/10/e23968 %U https://doi.org/10.2196/23968 %U http://www.ncbi.nlm.nih.gov/pubmed/34647894 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e25772 %T The Use of Task Shifting to Improve Treatment Engagement in an Internet-Based Mindfulness Intervention Among Chinese University Students: Randomized Controlled Trial %A Rodriguez,Marcus %A Eisenlohr-Moul,Tory A %A Weisman,Jared %A Rosenthal,M Zachary %+ Pitzer College, 1050 N Mills Ave, BN 205, Claremont, CA, 91711, United States, 1 9784605088, jweisman@pitzer.edu %K mindfulness %K mental health %K social support %K internet-based intervention %K treatment outcome %K university students %K smartphone %K mobile phone %D 2021 %7 13.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Traditional in-person psychotherapies are incapable of addressing global mental health needs. Use of computer-based interventions is one promising solution for closing the gap between the amount of global mental health treatment needed and received. Objective: Although many meta-analyses have provided evidence supporting the efficacy of self-guided, computer-based interventions, most report low rates of treatment engagement (eg, high attrition and low adherence). The aim of this study is to investigate the efficacy of an adjunctive treatment component that uses task shifting, wherein mental health care is provided by nonspecialist peer counselors to enhance engagement in an internet-based, self-directed, evidence-based mindfulness intervention among Chinese university students. Methods: From 3 universities across China, 54 students who reported at least mild stress, anxiety, or depression were randomly assigned to a 4-week internet-based mindfulness intervention (MIND) or to the intervention plus peer counselor support (MIND+), respectively. Be Mindful delivers all the elements of mindfulness-based cognitive therapy in an internet-based, 4-week course. Participants completed daily monitoring of mindfulness practice and mood, as well as baseline and posttreatment self-reported levels of depression, anxiety, stress, and trait mindfulness. We screened 56 volunteer peer counselor candidates who had no former training in the delivery of mental health services. Of these, 10 were invited to participate in a day-long training, and 4 were selected. Peer counselors were instructed to provide 6 brief (15-20 minute) sessions each week, to help encouraging participants to complete the internet-based intervention. Peer counselors received weekly web-based group supervision. Results: For both conditions, participation in the internet-based intervention was associated with significant improvements in mindfulness and mental health outcomes. The pre-post effect sizes (Cohen d) for mindfulness, depression, anxiety, and stress were 0.55, 0.95, 0.89, and 1.13, respectively. Participants assigned to the MIND+ (vs MIND) condition demonstrated significantly less attrition and more adherence, as indicated by a greater likelihood of completing posttreatment assessments (16/27, 59% vs 7/27, 26%; χ21=6.1; P=.01) and a higher percentage of course completion (72.6/100, 72.6% vs 50.7/100, 50.7%; t52=2.10; P=.04), respectively. No significant between-group differences in daily frequency and duration of mindfulness practice were observed. Multilevel logistic growth models showed that MIND+ participants reported significantly greater pre-post improvements in daily stress ratings (interaction estimate 0.39, SE 0.18; t317=2.29; P=.02) and depression (interaction estimate 0.38, SE 0.16; t330=2.37; P=.02) than those in the MIND condition. Conclusions: This study provides new insights into effective ways of leveraging technology and task shifting to implement large-scale mental health initiatives that are financially feasible, easily transportable, and quickly scalable in low-resource settings. The findings suggest that volunteer peer counselors receiving low-cost, low-intensity training and supervision may significantly improve participants’ indices of treatment engagement and mental health outcomes in an internet-based mindfulness intervention among Chinese university students. %M 34643532 %R 10.2196/25772 %U https://formative.jmir.org/2021/10/e25772 %U https://doi.org/10.2196/25772 %U http://www.ncbi.nlm.nih.gov/pubmed/34643532 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e32365 %T Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design %A Szinay,Dorothy %A Cameron,Rory %A Naughton,Felix %A Whitty,Jennifer A %A Brown,Jamie %A Jones,Andy %+ Behavioural and Implementation Science Group, School of Health Sciences, University of East Anglia, Norwich Research Park Earlham Road, Norwich, NR4 7TJ, United Kingdom, 44 1603593064, d.szinay@uea.ac.uk %K discrete choice experiment %K stated preference methods %K mHealth %K digital health %K quantitative methodology %K uptake %K engagement %K methodology %K preference %K Bayesian %K design %K tutorial %K qualitative %K user preference %D 2021 %7 11.10.2021 %9 Tutorial %J J Med Internet Res %G English %X Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method—a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or a service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations in which revealed preferences are difficult to collect but is much less used in the field of digital health. This paper outlines the stages involved in developing a DCE. As a case study, it uses the application of a DCE to reveal preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of 2 or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique. %M 34633290 %R 10.2196/32365 %U https://www.jmir.org/2021/10/e32365 %U https://doi.org/10.2196/32365 %U http://www.ncbi.nlm.nih.gov/pubmed/34633290 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e26125 %T Perceptions and Attitudes Toward the Use of a Mobile Health App for Remote Monitoring of Gingivitis and Willingness to Pay for Mobile Health Apps (Part 3): Mixed Methods Study %A Tobias,Guy %A Sgan-Cohen,Harold %A Spanier,Assaf B %A Mann,Jonathan %+ Department of Community Dentistry, Faculty of Dental Medicine, The Hebrew University-Hadassah School of Dental Medicine, Ein Kerem, Jerusalem, 91120, Israel, 972 52 705 2333, guy.tobias@mail.huji.ac.il %K mHealth %K public health %K oral health promotion %K gum health %K willingness to pay %K willingness to use %K willingness %K perception %K attitude %K mouth %K oral health %K dentist %K app %K monitoring %K mixed method %D 2021 %7 5.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Gum infection, known as gingivitis, is a global issue. Gingivitis does not cause pain; however, if left untreated, it can worsen, leading to bad breath, bleeding gums, and even tooth loss, as the problem spreads to the underlying structures anchoring the teeth in the jaws. The asymptomatic nature of gingivitis leads people to postpone dental appointments until clinical signs are obvious or pain is evident. The COVID-19 pandemic has necessitated social distancing, which has caused many people to postpone dental visits and neglect gingival health. iGAM is a dental mobile health (mHealth) app that remotely monitors gum health, and an observational study demonstrated the ability of iGAM to reduce gingivitis. We found that a weekly dental selfie using the iGAM app reduced the signs of gingivitis and promoted oral health in a home-based setting. Objective: The aim of this mixed methods study is to assess perceptions, attitudes, willingness to pay, and willingness to use an mHealth app. Methods: The first qualitative phase of the study included eight semistructured interviews, and the second quantitative phase included data collected from responses to 121 questionnaires. Results: There was a consensus among all interviewees that apps dealing with health-related issues (mHealth apps) can improve health. Three themes emerged from the interviews: the iGAM app is capable of improving health, the lack of use of medical apps, and a contradiction between the objective state of health and the self-definition of being healthy. Participants were grouped according to how they responded to the question about whether they believed that mHealth apps could improve their health. Participants who believed that mHealth apps can enhance health (mean 1.96, SD 1.01) had a higher willingness to pay for the service (depending on price) than those who did not believe in app efficacy (mean 1.31, SD 0.87; t119=−2417; P=.02). A significant positive correlation was found between the amount a participant was willing to pay and the benefits offered by the app (rs=0.185; P=.04). Conclusions: Potential mHealth users will be willing to pay for app use depending on their perception of the app’s ability to help them personally, provided they define themselves as currently unhealthy. %M 34609320 %R 10.2196/26125 %U https://formative.jmir.org/2021/10/e26125 %U https://doi.org/10.2196/26125 %U http://www.ncbi.nlm.nih.gov/pubmed/34609320 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e26418 %T Psychoeducational Messaging to Reduce Alcohol Use for College Students With Type 1 Diabetes: Internet-Delivered Pilot Trial %A Wisk,Lauren E %A Magane,Kara M %A Nelson,Eliza B %A Tsevat,Rebecca K %A Levy,Sharon %A Weitzman,Elissa R %+ Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California Los Angeles, 1100 Glendon Ave, Suite 850, Los Angeles, CA, 90024, United States, 1 3102675308, lwisk@mednet.ucla.edu %K adolescent %K young adult %K diabetes mellitus %K type 1 %K binge drinking %K alcohol drinking %K self care %K risk-taking %K universities %K students %K attitude %K mobile phone %D 2021 %7 30.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: College environments promote high-volume or binge alcohol consumption among youth, which may be especially harmful to those with type 1 diabetes (T1D). Little is known about the acceptability and effectiveness of interventions targeting reduced alcohol use by college students with T1D, and it is unclear whether intervention framing (specifically, the narrator of intervention messages) matters with respect to affecting behavior change. Interventions promoted by peer educators may be highly relatable and socially persuasive, whereas those delivered by clinical providers may be highly credible and motivating. Objective: The aim of this study is to determine the acceptability and impacts of an alcohol use psychoeducational intervention delivered asynchronously through web-based channels to college students with T1D. The secondary aim is to compare the impacts of two competing versions of the intervention that differed by narrator (peer vs clinician). Methods: We recruited 138 college students (aged 17-25 years) with T1D through web-based channels and delivered a brief intervention to participants randomly assigned to 1 of 2 versions that differed only with respect to the audiovisually recorded narrator. We assessed the impacts of the exposure to the intervention overall and by group, comparing the levels of alcohol- and diabetes-related knowledge, perceptions, and use among baseline, immediately after the intervention, and 2 weeks after intervention delivery. Results: Of the 138 enrolled participants, 122 (88.4%) completed all follow-up assessments; the participants were predominantly women (98/122, 80.3%), were White non-Hispanic (102/122, 83.6%), and had consumed alcohol in the past year (101/122, 82.8%). Both arms saw significant postintervention gains in the knowledge of alcohol’s impacts on diabetes-related factors, health-protecting attitudes toward drinking, and concerns about drinking. All participants reported significant decreases in binge drinking 2 weeks after the intervention (21.3%; odds ratio 0.48, 95% CI 0.31-0.75) compared with the 2 weeks before the intervention (43/122, 35.2%). Changes in binge drinking after the intervention were affected by changes in concerns about alcohol use and T1D. Those who viewed the provider narrator were significantly more likely to rate their narrator as knowledgeable and trustworthy; there were no other significant differences in intervention effects by the narrator. Conclusions: The intervention model was highly acceptable and effective at reducing self-reported binge drinking at follow-up, offering the potential for broad dissemination and reach given the web-based format and contactless, on-demand content. Both intervention narrators increased knowledge, improved health-protecting attitudes, and increased concerns regarding alcohol use. The participants’ perceptions of expertise and credibility differed by narrator. Trial Registration: ClinicalTrials.gov NCT02883829; https://clinicaltrials.gov/ct2/show/NCT02883829 International Registered Report Identifier (IRRID): RR2-10.1177/1932296819839503 %M 34591022 %R 10.2196/26418 %U https://www.jmir.org/2021/9/e26418 %U https://doi.org/10.2196/26418 %U http://www.ncbi.nlm.nih.gov/pubmed/34591022 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 9 %P e29990 %T Trends in Health Information Technology Use Among the US Population With and Without Cardiovascular Risk Factors, 2012-2018: Evidence From the National Health Interview Survey %A Gandrakota,Nikhila %A Ali,Mohammed K %A Shah,Megha K %+ Department of Family & Preventive Medicine, Emory University School of Medicine, 4500 N Shallowford Rd, Atlanta, GA, 30338, United States, 1 4047786920, nikhila.gandrakota@emory.edu %K telemedicine %K cardiovascular risk factors %K health information technology %K telehealth %K digital health %K public health %K surveillance %D 2021 %7 30.9.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic has required clinicians to pivot to offering services via telehealth; however, it is unclear which patients (users of care) are equipped to use digital health. This is especially pertinent for adults managing chronic diseases, such as obesity, hypertension, and diabetes, which require regular follow-up, medication management, and self-monitoring. Objective: The aim of this study is to measure the trends and assess factors affecting health information technology (HIT) use among members of the US population with and without cardiovascular risk factors. Methods: We used serial cross-sectional data from the National Health Interview Survey for the years 2012-2018 to assess trends in HIT use among adults, stratified by age and cardiovascular risk factor status. We developed multivariate logistic regression models adjusted for age, sex, race, insurance status, marital status, geographic region, and perceived health status to assess the likelihood of HIT use among patients with and without cardiovascular disease risk factors. Results: A total of 14,304 (44.6%) and 14,644 (58.7%) participants reported using HIT in 2012 and 2018, respectively. When comparing the rates of HIT use for the years 2012 and 2018, among participants without cardiovascular risk factors, the HIT use proportion increased from 51.1% to 65.8%; among those with one risk factor, it increased from 43.9% to 59%; and among those with more than one risk factor, it increased from 41.3% to 54.7%. Increasing trends in HIT use were highest among adults aged >65 years (annual percentage change [APC] 8.3%), who had more than one cardiovascular risk factor (APC 5%) and among those who did not graduate from high school (APC 8.8%). Likelihood of HIT use was significantly higher in individuals who were younger, female, and non-Hispanic White; had higher education and income; were married; and reported very good or excellent health status. In 2018, college graduates were 7.18 (95% CI 5.86-8.79), 6.25 (95% CI 5.02-7.78), or 7.80 (95% CI 5.87-10.36) times more likely to use HIT compared to adults without high school education among people with multiple cardiovascular risk factors, one cardiovascular risk factor, or no cardiovascular risk factors, respectively. Conclusions: Over 2012-2018, HIT use increased nationally, with greater use noted among younger and higher educated US adults. Targeted strategies are needed to engage wider age, racial, education, and socioeconomic groups by lowering barriers to HIT access and use. %M 34591026 %R 10.2196/29990 %U https://publichealth.jmir.org/2021/9/e29990 %U https://doi.org/10.2196/29990 %U http://www.ncbi.nlm.nih.gov/pubmed/34591026 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e28037 %T Acceptability Evaluation of the Use of Virtual Reality Games in Smoking-Prevention Education for High School Students: Prospective Observational Study %A Guo,Jong-Long %A Hsu,Hsiao-Pei %A Lai,Tzu-Ming %A Lin,Mei-Ling %A Chung,Chih-Ming %A Huang,Chiu-Mieh %+ Institute of Clinical Nursing, College of Nursing, National Yang Ming Chiao Tung University, No.155, Sec.2, Linong Street, Taipei, 112, Taiwan, 886 2 28267362, cmhuang2021@nycu.edu.tw %K behavioral intention %K ARCS motivation model %K persuasiveness %K smoking prevention %K educational games %D 2021 %7 28.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Alternative forms of cigarettes, such as electronic cigarettes (e-cigarettes), are becoming increasingly common among adolescents. Many high schools now provide smoking-prevention education in an attempt to minimize the potential negative health effects and illness burdens e-cigarettes may induce in adolescents. However, it is often difficult to motivate young students to engage with traditional education regarding the harmful effects of tobacco; thus, the development of alternative approaches may be required. Objective: In this study, we aimed to conduct an acceptability evaluation of educational virtual reality games designed to support smoking-prevention measures. We based the acceptability evaluation on the following two experience types: game-playing and content-learning experiences. The paths by which these experience types affect the intention to abstain from smoking were also examined. Methods: We applied a prospective observational study design. We developed educational games based on three-dimensional virtual reality technology, in which participants operated joysticks to complete challenge tasks. To increase the possibility of the games fostering motivation to abstain from smoking, the ARCS motivational model (comprising attention, relevance, confidence, and satisfaction) was used as a framework during the games’ design. We measured the participants’ game-playing experiences by inquiring about the strength of the ARCS elements; content-learning experiences were measured using overall knowledge improvement and the perceived persuasiveness of the content. A total of 130 students participated in the program. Study hypotheses for this evaluation were derived from a literature review. We used partial least squares structural equation modeling to examine the proposed hypotheses. Results: Based on the responses of the students to questionnaire items concerning attention, relevance, confidence, and satisfaction in the context of the games, most students agreed or strongly agreed that the educational games were motivational, and that their game-playing experiences were positive. Regarding content-learning experiences, there was a significant improvement in knowledge (t129=25.67, P<.001), and most students perceived themselves as being persuaded to abstain from smoking. Attention, relevance, and satisfaction significantly influenced perceived persuasiveness (t=3.19, P<.001; t=4.28, P<.001; and t=3.49, P<.001, respectively); however, confidence did not (t=0.42, P=.67). Perceived persuasiveness, relevance, and satisfaction significantly influenced the intention to abstain from smoking (t=3.57, P<.001). In addition to directly affecting the intention to abstain from smoking, indirect effects were observed from both relevance and satisfaction to intention via perceived persuasiveness (t=2.87, P=.004 and t=2.11, P=.04, respectively). However, intention was not significantly influenced by knowledge improvement. Conclusions: Our findings revealed that the educational games were positively accepted by the participating students. This indicates that the integration of the ARCS framework and persuasive strategies is applicable for smoking-prevention education. We recommend that the games be included as teaching materials for smoking-prevention education. %M 34581679 %R 10.2196/28037 %U https://www.jmir.org/2021/9/e28037 %U https://doi.org/10.2196/28037 %U http://www.ncbi.nlm.nih.gov/pubmed/34581679 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e25630 %T Patterns for Patient Engagement with the Hypertension Management and Effects of Electronic Health Care Provider Follow-up on These Patterns: Cluster Analysis %A Wu,Dan %A An,Jiye %A Yu,Ping %A Lin,Hui %A Ma,Li %A Duan,Huilong %A Deng,Ning %+ College of Biomedical Engineering and Instrument Science, Ministry of Education Key Laboratory of Biomedical Engineering, Zhejiang University, Zhouyiqing Bldg 512, Yuquan Campus, 38 Zheda Rd, Hangzhou, 310027, China, 86 571 2295 269, zju.dengning@gmail.com %K hypertension %K health care services %K mHealth %K patient engagement %K electronic follow-up %K cluster analysis %D 2021 %7 28.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Hypertension is a long-term medical condition. Electronic and mobile health care services can help patients to self-manage this condition. However, not all management is effective, possibly due to different levels of patient engagement (PE) with health care services. Health care provider follow-up is an intervention to promote PE and blood pressure (BP) control. Objective: This study aimed to discover and characterize patterns of PE with a hypertension self-management app, investigate the effects of health care provider follow-up on PE, and identify the follow-up effects on BP in each PE pattern. Methods: PE was represented as the number of days that a patient recorded self-measured BP per week. The study period was the first 4 weeks for a patient to engage in the hypertension management service. K-means algorithm was used to group patients by PE. There was compliance follow-up, regular follow-up, and abnormal follow-up in management. The follow-up effect was calculated by the change in PE (CPE) and the change in systolic blood pressure (CSBP, SBP) before and after each follow-up. Chi-square tests and z scores were used to ascertain the distribution of gender, age, education level, SBP, and the number of follow-ups in each cluster. The follow-up effect was identified by analysis of variances. Once a significant effect was detected, Bonferroni multiple comparisons were further conducted to identify the difference between 2 clusters. Results: Patients were grouped into 4 clusters according to PE: (1) PE started low and dropped even lower (PELL), (2) PE started high and remained high (PEHH), (3) PE started high and dropped to low (PEHL), and (4) PE started low and rose to high (PELH). Significantly more patients over 60 years old were found in the PEHH cluster (P≤.05). Abnormal follow-up was significantly less frequent (P≤.05) in the PELL cluster. Compliance follow-up and regular follow-up can improve PE. In the clusters of PEHH and PELH, the improvement in PE in the first 3 weeks and the decrease in SBP in all 4 weeks were significant after follow-up. The SBP of the clusters of PELL and PELH decreased more (–6.1 mmHg and –8.4 mmHg) after follow-up in the first week. Conclusions: Four distinct PE patterns were identified for patients engaging in the hypertension self-management app. Patients aged over 60 years had higher PE in terms of recording self-measured BP using the app. Once SBP reduced, patients with low PE tended to stop using the app, and a continued decline in PE occurred simultaneously with the increase in SBP. The duration and depth of the effect of health care provider follow-up were more significant in patients with high or increased engagement after follow-up. %M 34581680 %R 10.2196/25630 %U https://www.jmir.org/2021/9/e25630 %U https://doi.org/10.2196/25630 %U http://www.ncbi.nlm.nih.gov/pubmed/34581680 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 9 %P e31421 %T Patterns of Missing Data With Ecological Momentary Assessment Among People Who Use Drugs: Feasibility Study Using Pilot Study Data %A Markowski,Kelly L %A Smith,Jeffrey A %A Gauthier,G Robin %A Harcey,Sela R %+ Rural Drug Addiction Research Center, University of Nebraska-Lincoln, 660 N 12th St, Lincoln, NE, 68508, United States, 1 8153536605, kmarkowski2@unl.edu %K EMA %K ecological momentary assessment %K PWUD %K people who use drugs %K noncompliance %K missing data %K mobile phone %D 2021 %7 24.9.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Ecological momentary assessment (EMA) is a set of research methods that capture events, feelings, and behaviors as they unfold in their real-world setting. Capturing data in the moment reduces important sources of measurement error but also generates challenges for noncompliance (ie, missing data). To date, EMA research has only examined the overall rates of noncompliance. Objective: In this study, we identify four types of noncompliance among people who use drugs and aim to examine the factors associated with the most common types. Methods: Data were obtained from a recent pilot study of 28 Nebraskan people who use drugs who answered EMA questions for 2 weeks. We examined questions that were not answered because they were skipped, they expired, the phone was switched off, or the phone died after receiving them. Results: We found that the phone being switched off and questions expiring comprised 93.34% (1739/1863 missing question-instances) of our missing data. Generalized structural equation model results show that participant-level factors, including age (relative risk ratio [RRR]=0.93; P=.005), gender (RRR=0.08; P=.006), homelessness (RRR=3.80; P=.04), personal device ownership (RRR=0.14; P=.008), and network size (RRR=0.57; P=.001), are important for predicting off missingness, whereas only question-level factors, including time of day (ie, morning compared with afternoon, RRR=0.55; P<.001) and day of week (ie, Tuesday-Saturday compared with Sunday, RRR=0.70, P=.02; RRR=0.64, P=.005; RRR=0.58, P=.001; RRR=0.55, P<.001; and RRR=0.66, P=.008, respectively) are important for predicting expired missingness. The week of study is important for both (ie, week 2 compared with week 1, RRR=1.21, P=.03, for off missingness and RRR=1.98, P<.001, for expired missingness). Conclusions: We suggest a three-pronged strategy to preempt missing EMA data with high-risk populations: first, provide additional resources for participants likely to experience phone charging problems (eg, people experiencing homelessness); second, ask questions when participants are not likely to experience competing demands (eg, morning); and third, incentivize continued compliance as the study progresses. Attending to these issues can help researchers ensure maximal data quality. %M 34464327 %R 10.2196/31421 %U https://formative.jmir.org/2021/9/e31421 %U https://doi.org/10.2196/31421 %U http://www.ncbi.nlm.nih.gov/pubmed/34464327 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e19896 %T Factors Affecting Engagement in Web-Based Health Care Patient Information: Narrative Review of the Literature %A Oktay,Liam Alperen %A Abuelgasim,Eyad %A Abdelwahed,Aida %A Houbby,Nour %A Lampridou,Smaragda %A Normahani,Pasha %A Peters,Nicholas %A Jaffer,Usman %+ Imperial College NHS Trust, Praed Street, London, W2 0NE, United Kingdom, 44 7968872992, usman.jaffer@nhs.net %K patient education %K web-based health information %K internet %K patient engagement %K mobile phone %D 2021 %7 23.9.2021 %9 Review %J J Med Internet Res %G English %X Background: Web-based content is rapidly becoming the primary source of health care information. There is a pressing need for web-based health care content to not only be accurate but also be engaging. Improved engagement of people with web-based health care content has the potential to inform as well as influence behavioral change to enable people to make better health care choices. The factors associated with better engagement with web-based health care content have previously not been considered. Objective: The aims of this study are to identify the factors that affect engagement with web-based health care content and develop a framework to be considered when creating such content. Methods: A comprehensive search of the PubMed and MEDLINE database was performed from January 1, 1946, to January 5, 2020. The reference lists of all included studies were also searched. The Medical Subject Headings database was used to derive the following keywords: “patient information,” “online,” “internet,” “web,” and “content.” All studies in English pertaining to the factors affecting engagement in web-based health care patient information were included. No restrictions were set on the study type. Analysis of the themes arising from the results was performed using inductive content analysis. Results: The search yielded 814 articles, of which 56 (6.9%) met our inclusion criteria. The studies ranged from observational and noncontrolled studies to quasi-experimental studies. Overall, there was significant heterogeneity in the types of interventions and outcome assessments, which made quantitative assessment difficult. Consensus among all authors of this study resulted in six categories that formed the basis of a framework to assess the factors affecting engagement in web-based health care content: easy to understand, support, adaptability, accessibility, visuals and content, and credibility and completeness. Conclusions: There is a paucity of high-quality data relating to the factors that improve the quality of engagement with web-based health care content. Our framework summarizes the reported studies, which may be useful to health care content creators. An evaluation of the utility of web-based content to engage users is of significant importance and may be accessible through tools such as the Net Promoter score. Web 3.0 technology and development of the field of psychographics for health care offer further potential for development. Future work may also involve improvement of the framework through a co-design process. %M 34554104 %R 10.2196/19896 %U https://www.jmir.org/2021/9/e19896 %U https://doi.org/10.2196/19896 %U http://www.ncbi.nlm.nih.gov/pubmed/34554104 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e25922 %T Facilitator Contact, Discussion Boards, and Virtual Badges as Adherence Enhancements to a Web-Based, Self-guided, Positive Psychological Intervention for Depression: Randomized Controlled Trial %A Moskowitz,Judith Tedlie %A Addington,Elizabeth L %A Shiu,Eva %A Bassett,Sarah M %A Schuette,Stephanie %A Kwok,Ian %A Freedman,Melanie E %A Leykin,Yan %A Saslow,Laura R %A Cohn,Michael A %A Cheung,Elaine O %+ Department of Medical Social Sciences, Osher Center for Integrative Medicine, Northwestern University Feinberg School of Medicine, 625 N Michigan Ave, Suite 2700, Chicago, IL, 60611, United States, 1 3125037712, judith.moskowitz@northwestern.edu %K mHealth %K adherence %K depression %K discussion board %K gamification %K positive psychological intervention %K mobile phone %D 2021 %7 22.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Adherence to self-guided interventions tends to be very low, especially in people with depression. Prior studies have demonstrated that enhancements may increase adherence, but little is known about the efficacy of various enhancements in comparison to, or in combination with, one another. Objective: The aim of our study is to test whether 3 enhancements—facilitator contact (FC), an online discussion board, and virtual badges (VB)—alone, or in combination, improve adherence to a self-guided, web-based intervention for depression. We also examined whether age, gender, race, ethnicity, comfort with technology, or baseline depression predicted adherence or moderated the effects that each enhancement had on adherence. Methods: Participants were recruited through web-based sources and, after completing at least 4 out of 7 daily emotion reports, were sequentially assigned to 1 of 9 conditions—the intervention alone; the intervention plus 1, 2, or all 3 enhancements; or an emotion reporting control condition. The intervention was a positive psychological program consisting of 8 skills that specifically targeted positive emotions, and it was delivered over 5 weeks in a self-guided, web-based format. We operationalized adherence as the number of skills accessed. Results: A total of 602 participants were enrolled in this study. Participants accessed, on average, 5.61 (SD 2.76) of 8 skills. The total number of enhancements participants received (0-3) did not predict the number of skills accessed. Participants who were assigned to the VB+FC condition accessed significantly more skills than those in the intervention only conditions. Furthermore, participants in arms that received the combination of both the VB and FC enhancements (VB+FC and VB+FC+online discussion board) accessed a greater number of skills relative to the number of skills accessed by participants who received either VB or FC without the other. Moderation analyses revealed that the receipt of VB (vs no VB) predicted higher adherence among participants with moderately severe depression at baseline. Conclusions: The results suggested that the VB+FC combination significantly increased the number of skills accessed in a self-guided, web-based intervention for elevated depression. We have provided suggestions for refinements to these enhancements, which may further improve adherence. Trial Registration: ClinicalTrials.gov NCT02861755; http://clinicaltrials.gov/ct2/show/NCT02861755 %M 34550076 %R 10.2196/25922 %U https://www.jmir.org/2021/9/e25922 %U https://doi.org/10.2196/25922 %U http://www.ncbi.nlm.nih.gov/pubmed/34550076 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 9 %P e25878 %T Barriers and Facilitators Associated With App-Based Treatment for Female Urinary Incontinence: Mixed Methods Evaluation %A Wessels,Nienke J %A Loohuis,Anne M M %A van der Worp,Henk %A Abbenhuis,Linde %A Dekker,Janny %A Berger,Marjolein Y %A van Gemert-Pijnen,Julia E W C %A Blanker,Marco H %+ Department of General Practice and Elderly Care Medicine, University Medical Centre Groningen, University of Groningen, FA21, PO Box 196, Groningen, , Netherlands, 31 05 03616746, n.j.wessels@umcg.nl %K mHealth %K female %K mixed methods %K primary health care %K urinary incontinence %D 2021 %7 17.9.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: App-based treatment for urinary incontinence is a proven effective and cost-effective alternative to care as usual, but successful implementation requires that we identify and address the barriers and facilitators associated with app use. Objective: The goal of the research was to explore the factors influencing app-based treatment for urinary incontinence and identify which barriers or facilitators are associated with treatment success or failure. Methods: We used a sequential explanatory mixed methods design to connect the results of a randomized controlled trial with data from semistructured interviews. This previous RCT had shown the noninferiority of app-based treatment compared with care as usual for urinary incontinence over 4 months. Participants who reported success or failure with app-based treatment, as measured by the change in International Consultation on Incontinence Modular Questionnaire Urinary Incontinence Short Form symptom score, were selected for telephone interview by purposive sampling (n=17). This study reports mainly on the qualitative component of our mixed methods study. Qualitative analyses were conducted in two ways. First, we analyzed the qualitative data of all interviewed participants and discussed the relationships between the main themes. Second, the experiences between the success (n=9) and failure group (n=8) were compared and contrasted to explore factors that were positively or negatively associated with the quantitative effect of app-based treatment. These factors were then interpreted as barriers to and facilitators of successful app-based treatment. Results: Four interrelated themes were identified as affecting the app based treatment effect: adherence, personal factors, app factors, and awareness. Qualitative analyses of the relationships between the themes showed that adherence-related factors directly influenced treatment effect in both a positive and negative matter. In turn, adherence was also positively and negatively influenced by the other 3 themes. Additionally, awareness was positively influenced by the treatment effect. Within these themes, several factors were identified that acted as barriers (eg, unrealistic expectation of time investment and interfering personal circumstances), facilitators (eg, strict integration of exercises and prior pelvic floor muscle therapy), or both (eg, personality traits and increased awareness of symptoms). Conclusions: This study shows that the effect of app-based treatment for urinary incontinence is mainly influenced by adherence, which in turn is affected by personal factors, app-based factors, and awareness. The identified factors could function as both facilitators and barriers depending on the user and interaction with other themes. Insight into these facilitators and barriers could lead to improved implementation and increased treatment effectiveness by targeting women most likely to benefit and through further development of the app. International Registered Report Identifier (IRRID): RR2-10.1002/nau.23507 %M 34533466 %R 10.2196/25878 %U https://mhealth.jmir.org/2021/9/e25878 %U https://doi.org/10.2196/25878 %U http://www.ncbi.nlm.nih.gov/pubmed/34533466 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 4 %N 3 %P e27999 %T Digital Technologies for Monitoring and Improving Treatment Adherence in Children and Adolescents With Asthma: Scoping Review of Randomized Controlled Trials %A Milne-Ives,Madison %A Lam,Ching %A Meinert,Edward %+ Centre for Health Technology, University of Plymouth, 6 Kirkby Place, Room 2, Plymouth, PL4 6DT, United Kingdom, 44 1752600600, edward.meinert@plymouth.ac.uk %K asthma %K disease management %K child %K adolescent %K telemedicine %D 2021 %7 17.9.2021 %9 Review %J JMIR Pediatr Parent %G English %X Background: Inadequate pediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to monitor and support treatment adherence in children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research on these technologies and how they are being integrated into existing health care services and care pathways. Objective: This study aims to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma. Methods: This study was structured according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) and Population, Intervention, Comparator, Outcome, and Study frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials, Web of Science, Embase, and PsycINFO) were systematically searched for studies published in English from 2014 onward. Two reviewers independently screened the references and selected studies for inclusion based on the eligibility criteria. Data were systematically extracted per research question, which were synthesized in a descriptive analysis. Results: A wide variety of study characteristics, including the number and age of participants, study duration, and type of digital intervention, were identified. There was mixed evidence for the effectiveness of the interventions. Of the 10 studies that evaluated treatment adherence, 7 (70%) found improvements, but the evidence was inconsistent for asthma control (6/9, 67% of studies reported improvement or maintenance, but only 1 was significantly different between groups) and health outcome variables (5/9, 56% of studies found no evidence of effectiveness). The 6 studies that examined patient perceptions and assessments of acceptability and usability generally had positive findings. Conclusions: A wide range of digital interventions are being developed and evaluated to support the monitoring and treatment adherence of children and adolescents with asthma. Meta-analyses are inhibited by the use of samples with a variety of overlapping age ranges; a theoretical framework for evaluating specific age groups would aid comparison between studies. Most studies found significant evidence for improved adherence to treatment or medications, but there was mixed evidence of the impact of the digital interventions on asthma control and other health outcomes. There are gaps in the literature relating to cost-effectiveness and integration with existing clinical care pathways. This study will be necessary to determine which digital interventions for children and young people with asthma are worth supporting and adopting in the clinical care pathways. %M 34533463 %R 10.2196/27999 %U https://pediatrics.jmir.org/2021/3/e27999 %U https://doi.org/10.2196/27999 %U http://www.ncbi.nlm.nih.gov/pubmed/34533463 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e26869 %T Identifying Enablers of Participant Engagement in Clinical Trials of Consumer Health Technologies: Qualitative Study of Influenza Home Testing %A Dharanikota,Spurthy %A LeRouge,Cynthia M %A Lyon,Victoria %A Durneva,Polina %A Thompson,Matthew %+ Department of Information Systems and Business Analytics, Florida International University, 11200 SW 8th Street, Miami, FL, 33199, United States, 1 3057812536, sdhar006@fiu.edu %K consumer health care technologies %K CHTs %K smartphone-supported home tests %K Smart-HT %K premarket clinical trials %K trial engagement %K at-home diagnostic testing %K mobile phone %D 2021 %7 14.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: A rise in the recent trend of self-managing health using consumer health technologies highlights the importance of efficient and successful consumer health technology trials. Trials are particularly essential to support large-scale implementations of consumer health technologies, such as smartphone-supported home tests. However, trials are generally fraught with challenges, such as inadequate enrollment, lack of fidelity to interventions, and high dropout rates. Understanding the reasons underlying individuals’ participation in trials can inform the design and execution of future trials of smartphone-supported home tests. Objective: This study aims to identify the enablers of potential participants’ trial engagement for clinical trials of smartphone-supported home tests. We use influenza home testing as our instantiation of a consumer health technology subject to trial to investigate the dispositional and situational enablers that influenced trial engagement. Methods: We conducted semistructured interviews with 31 trial participants using purposive sampling to facilitate demographic diversity. The interviews included a discussion of participants’ personal characteristics and external factors that enabled their trial engagement with a smartphone-supported home test for influenza. We performed both deductive and inductive thematic analyses to analyze the interview transcripts and identify enabler themes. Results: Our thematic analyses revealed a structure of dispositional and situational enablers that enhanced trial engagement. Situationally, clinical affiliation, personal advice, promotional recruitment strategies, financial incentives, and insurance status influenced trial engagement. In addition, digital health literacy, motivation to advance medical research, personal innovativeness, altruism, curiosity, positive attitude, and potential to minimize doctors’ visits were identified as the dispositional enablers for trial engagement in our study. Conclusions: We organized the identified themes for dispositional and situational enablers of trial engagement with a smartphone-supported home test into a research framework that can guide future research as well as the trial design and execution of smartphone-supported home tests. We suggest several trial design and engagement strategies to enhance the financial and scientific viability of these trials that pave the way for advancements in patient care. Furthermore, our study also offers practical strategies to trial organizers to enhance participants’ enrollment and engagement in clinical trials of these home tests. %M 34519664 %R 10.2196/26869 %U https://www.jmir.org/2021/9/e26869 %U https://doi.org/10.2196/26869 %U http://www.ncbi.nlm.nih.gov/pubmed/34519664 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e14908 %T Association Between eHealth Literacy in Online Health Communities and Patient Adherence: Cross-sectional Questionnaire Study %A Lu,Xinyi %A Zhang,Runtong %+ School of Management and E-business, Zhejiang Gongshang University, 18 Xuezheng Street, Qiantang District, Hangzhou, 310018, China, 86 18801329327, xinyilu@bjtu.edu.cn %K online health communities %K OHCs %K eHealth literacy %K patient adherence %K health information %K physician-patient communication %D 2021 %7 13.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: eHealth literacy is significantly associated with patients’ online information behavior, physician-patient relationship, patient adherence, and health outcomes. As an important product of the internet, online health communities (OHCs) can help redistribute idle medical resources, increase medical resource utilization, and improve patient adherence. However, studies on eHealth literacy in OHCs are limited. Therefore, this study examined patients’ eHealth literacy regarding health information–seeking behavior and physician-patient communication in OHCs. Objective: This study aimed to investigate the association between eHealth literacy in OHCs and patient adherence by employing social cognitive theory. Methods: This was an empirical study, in which a research model consisting of 1 independent variable (patients’ eHealth literacy), 3 mediators (physician-patient communication in OHCs, patient health information–seeking behavior in OHCs, and patients’ perceived quality of health information in OHCs), 1 dependent variable (patient adherence), and 4 control variables (age, gender, living area, and education level) was established to examine the associations. Multi-item scales were used to measure variables. An anonymous online survey involving 560 participants was conducted through Chinese OHCs in July 2018 to collect data. Partial least squares and structural equation modeling were adopted to analyze data and test hypotheses. Results: The survey response rate was 79.6% (446/560). The reliability, convergent validity, and discriminant validity were acceptable. Age, gender, living area, and education level were positively associated with patient adherence, and gender was positively associated with physician-patient communication and patients’ perceived quality of internet health information in OHCs. Patients’ eHealth literacy was positively associated with patient adherence through the mediations of physician-patient communication, internet health information–seeking behavior, and perceived quality of internet health information in OHCs. Conclusions: Results indicate that physician-patient communication, internet health information–seeking behavior, and the perceived quality of internet health information are significantly associated with improving patient adherence via a guiding of eHealth literacy in OHCs. These findings suggest that physicians can understand and guide their patients’ eHealth literacy to improve treatment efficiency; OHCs’ operators should this strengthen the management of information quality, develop user-friendly features, and minimize the gap between the actual and perceived information quality. %M 34515638 %R 10.2196/14908 %U https://www.jmir.org/2021/9/e14908 %U https://doi.org/10.2196/14908 %U http://www.ncbi.nlm.nih.gov/pubmed/34515638 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 9 %P e25168 %T Combined Use of Web-Based and In-Person Education on Ill Health Self-management Skills in Adults With Bipolar Disorder: Protocol for a Mixed Methods Study %A Hatzioannou,Anna %A Chatzittofis,Andreas %A Koutroubas,Virginia Sunday %A Papastavrou,Evridiki %A Karanikola,Maria %+ Nursing Department, School of Health Sciences, Cyprus University of Technology, 15 Vragadinou Street, Limassol, 3041, Cyprus, 357 99786069, maria.karanikola@cut.ac.cy %K education %K empowerment %K bipolar disorders %K self-management %K bipolar %K mental health %D 2021 %7 8.9.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Addressing the enhancement of ill health self-management skills in adults diagnosed with bipolar disorder may be considered an important intervention for health care systems worldwide. Objective: This protocol describes the study “Management of my Bipolarity” (MoB), which aims to develop an educational intervention for adults with bipolar disorder and assess its effectiveness. The objectives include (a) a literature review on bipolar disorder educational interventions; (b) a qualitative exploration of the educational needs of people with bipolar disorder; (c) development of an educational intervention based on objectives (a) and (b) (ie, the MoB educational intervention); and (d) exploration of the effectiveness of the intervention regarding participants’ knowledge of their mental health condition and enhancement of their ill health self-management skills. The MoB educational intervention will consist of an in-person and a web-based intervention in the form of a digital platform. Methods: The proposed interventional study is a combination of a qualitative and a quantitative design (mixed methods study). A focus group and content analysis will be implemented for the qualitative assessment of the educational needs of adults with bipolar disorder. The intervention will be developed based on the qualitative data of the study and relevant literature. The effectiveness of the acquired knowledge and self-management skills will be assessed according to (a) substance use behavior, (b) health locus of control, (c) impulse control, (d) adherence to pharmacotherapy, (e) relapse prevention, (f) improvement of quality of life, and (g) bipolar disorder knowledge level via structured instruments in the quantitative part of the study using descriptive and inferential statistics (SPSS version 24.0). Results: A total of 13 patients with bipolar disorder have been interviewed (8 women, 5 men) to identify educational needs to be covered through the intervention. Moreover, a literature review on bipolar disorder educational interventions has been completed. These data have been incorporated in the design of the MoB in-person intervention and the digital platform. The digital platform is live, and the development of the MoB in-person intervention was completed at the end of 2020. The recruitment of the participants for the intervention (40 patients) and the control group (40 patients) began during the first semester of 2021. Moreover, by tracking the platform for 1.5 years, we have recorded that 2180 users have visited the platform with an average session duration of almost 2 minutes. Mobile and tablet devices are being used by 70% of the visitors. Conclusions: Since new parameters regarding educational interventions will be explored, these findings are expected to provide evidence that participation in structured educational interventions offers patients the opportunity to improve adherence to pharmacotherapy and increase their quality of life. Trial Registration: ClinicalTrials.gov NCT04643210; https://clinicaltrials.gov/ct2/show/NCT04643210 International Registered Report Identifier (IRRID): DERR1-10.2196/25168 %M 34494969 %R 10.2196/25168 %U https://www.researchprotocols.org/2021/9/e25168 %U https://doi.org/10.2196/25168 %U http://www.ncbi.nlm.nih.gov/pubmed/34494969 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e29018 %T Adherence to Telemonitoring Therapy for Medicaid Patients With Hypertension: Case Study %A Park,Sulki %A Kum,Hye-Chung %A Morrisey,Michael A %A Zheng,Qi %A Lawley,Mark A %+ Department of Health Policy and Management, Texas A&M University, 212 Adriance Lab Rd, College Station, TX, 77843, United States, 1 979 436 9439, kum@tamu.edu %K telemedicine %K hypertension %K Medicaid %K blood pressure %K pulse %K telemonitoring %K mobile phone %D 2021 %7 6.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Almost 50% of the adults in the United States have hypertension. Although clinical trials indicate that home blood pressure monitoring can be effective in managing hypertension, the reported results might not materialize in practice because of patient adherence problems. Objective: The aims of this study are to characterize the adherence of Medicaid patients with hypertension to daily telemonitoring, identify the impacts of adherence reminder calls, and investigate associations with blood pressure control. Methods: This study targeted Medicaid patients with hypertension from the state of Texas. A total of 180 days of blood pressure and pulse data in 2016-2018 from a telemonitoring company were analyzed for mean transmission rate and mean blood pressure change. The first 30 days of data were excluded because of startup effects. The protocols required the patients to transmit readings by a specified time daily. Patients not transmitting their readings received an adherence reminder call to troubleshoot problems and encourage transmission. The patients were classified into adherent and nonadherent cohorts; adherent patients were those who transmitted data on at least 80% of the days. Results: The mean patient age was 73.2 (SD 11.7) years. Of the 823 patients, 536 (65.1%) were women, and 660 (80.2%) were urban residents. The adherent cohort (475/823, 57.7%) had mean transmission rates of 74.9% before the adherence reminder call and 91.3% after the call, whereas the nonadherent cohort (348/823, 42.3%) had mean transmission rates of 39% and 58% before and after the call, respectively. From month 1 to month 5, the transmission rates dropped by 1.9% and 10.2% for the adherent and nonadherent cohorts, respectively. The systolic and diastolic blood pressure values improved by an average of 2.2 and 0.7 mm Hg (P<.001 and P=.004), respectively, for the adherent cohort during the study period, whereas only the systolic blood pressure value improved by an average of 1.6 mm Hg (P=.02) for the nonadherent cohort. Conclusions: Although we found that patients can achieve high levels of adherence, many experience adherence problems. Although adherence reminder calls help, they may not be sufficient. Telemonitoring lowered blood pressure, as has been observed in clinical trials. Furthermore, blood pressure control was positively associated with adherence. %M 34486977 %R 10.2196/29018 %U https://www.jmir.org/2021/9/e29018 %U https://doi.org/10.2196/29018 %U http://www.ncbi.nlm.nih.gov/pubmed/34486977 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 8 %P e26861 %T A Mobile Health App (WYZ) for Engagement in Care and Antiretroviral Therapy Adherence Among Youth and Young Adults Living With HIV: Single-Arm Pilot Intervention Study %A Saberi,Parya %A Lisha,Nadra E %A Erguera,Xavier A %A Hudes,Estie Sid %A Johnson,Mallory O %A Ruel,Theodore %A Neilands,Torsten B %+ Department of Medicine, University of California, San Francisco, 550 16th street, San Francisco, CA, 94143, United States, 1 415 502 1000 ext 17171, Parya.Saberi@ucsf.edu %K youth living with HIV %K mobile health %K mobile app %K engagement in care %K antiretroviral therapy adherence %K pilot %D 2021 %7 31.8.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Youth are globally recognized as being vulnerable to HIV. Younger age has been correlated with worse health outcomes. Mobile health (mHealth) interventions have the potential to interact with youth where they are, using a device they already access. Objective: Using predefined benchmarks, we sought to evaluate the feasibility and acceptability of WYZ, an mHealth app, for improved engagement in care and antiretroviral therapy (ART) adherence among youth and young adults living with HIV. WYZ was designed and developed with input from youth and young adults living with HIV using a human-centered design approach and was based on the information, motivation, and behavioral skills framework to address common barriers to care and ART adherence among youth and young adults living with HIV. Methods: We recruited youth and young adults living with HIV (18-29 years old) from the San Francisco Bay Area to take part in a 6-month pilot trial. Their participation included completing baseline and exit surveys, and participating in seven phone check-ins about their use of WYZ. Results: Youth and young adults living with HIV (N=79) reported high levels of feasibility and acceptability with WYZ use. We met predefined benchmarks for recruitment (79/84, 94%), mean logins per week (5.3), tracking ART adherence (5442/9393, 57.9%), posting chat topics per week (4.8), and app crashes reported per week (0.24). The ease of app download, install, and setup, and comfort with security, privacy, and anonymity were highly rated (all over 91%). Additionally, participants reported high satisfaction for a research project that was remotely conducted. Participants used the app for shorter timeframes compared to the predefined benchmark. Conclusions: We noted high feasibility and acceptability with WYZ. Further research to examine the efficacy of WYZ will enable youth and young adults living with HIV and their providers to make informed decisions when using, recommending, and prescribing the app for improved engagement in HIV care and ART adherence. Trial Registration: ClinicalTrials.gov NCT03587857; https://clinicaltrials.gov/ct2/show/NCT03587857 %M 34463622 %R 10.2196/26861 %U https://formative.jmir.org/2021/8/e26861 %U https://doi.org/10.2196/26861 %U http://www.ncbi.nlm.nih.gov/pubmed/34463622 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 8 %P e27977 %T Factors to Effective Telemedicine Visits During the COVID-19 Pandemic: Cohort Study %A Gmunder,Kristin Nicole %A Ruiz,Jose W %A Franceschi,Dido %A Suarez,Maritza M %+ University of Miami Miller School of Medicine, 1600 NW 10th Ave #1140, Miami, FL, 33136, United States, 1 908 635 9107, kgmunder@med.miami.edu %K telemedicine %K COVID-19 %K patient portals %K delivery of health care %K telehealth %K pandemic %K digital health %D 2021 %7 27.8.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: With COVID-19 there was a rapid and abrupt rise in telemedicine implementation often without sufficient time for providers or patients to adapt. As telemedicine visits are likely to continue to play an important role in health care, it is crucial to strive for a better understanding of how to ensure completed telemedicine visits in our health system. Awareness of these barriers to effective telemedicine visits is necessary for a proactive approach to addressing issues. Objective: The objective of this study was to identify variables that may affect telemedicine visit completion in order to determine actions that can be enacted across the entire health system to benefit all patients. Methods: Data were collected from scheduled telemedicine visits (n=362,764) at the University of Miami Health System (UHealth) between March 1, 2020 and October 31, 2020. Descriptive statistics, mixed effects logistic regression, and random forest modeling were used to identify the most important patient-agnostic predictors of telemedicine completion. Results: Using descriptive statistics, struggling telemedicine specialties, providers, and clinic locations were identified. Through mixed effects logistic regression (adjusting for clustering at the clinic site level), the most important predictors of completion included previsit phone call/SMS text message reminder status (confirmed vs not answered) (odds ratio [OR] 6.599, 95% CI 6.483-6.717), MyUHealthChart patient portal status (not activated vs activated) (OR 0.315, 95% CI 0.305-0.325), provider’s specialty (primary care vs medical specialty) (OR 1.514, 95% CI 1.472-1.558), new to the UHealth system (yes vs no) (OR 1.285, 95% CI 1.201-1.374), and new to provider (yes vs no) (OR 0.875, 95% CI 0.859-0.891). Random forest modeling results mirrored those from logistic regression. Conclusions: The highest association with a completed telemedicine visit was the previsit appointment confirmation by the patient via phone call/SMS text message. An active patient portal account was the second strongest variable associated with completion, which underscored the importance of patients having set up their portal account before the telemedicine visit. Provider’s specialty was the third strongest patient-agnostic characteristic associated with telemedicine completion rate. Telemedicine will likely continue to have an integral role in health care, and these results should be used as an important guide to improvement efforts. As a first step toward increasing completion rates, health care systems should focus on improvement of patient portal usage and use of previsit reminders. Optimization and intervention are necessary for those that are struggling with implementing telemedicine. We advise setting up a standardized workflow for staff. %M 34254936 %R 10.2196/27977 %U https://medinform.jmir.org/2021/8/e27977 %U https://doi.org/10.2196/27977 %U http://www.ncbi.nlm.nih.gov/pubmed/34254936 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e21686 %T The Effectiveness of a Web-Based Self-Help Program to Reduce Alcohol Use Among Adults With Drinking Patterns Considered Harmful, Hazardous, or Suggestive of Dependence in Four Low- and Middle-Income Countries: Randomized Controlled Trial %A Schaub,Michael P %A Tiburcio,Marcela %A Martínez-Vélez,Nora %A Ambekar,Atul %A Bhad,Roshan %A Wenger,Andreas %A Baumgartner,Christian %A Padruchny,Dzianis %A Osipchik,Sergey %A Poznyak,Vladimir %A Rekve,Dag %A Landi Moraes,Fabricio %A Monezi Andrade,André Luiz %A Oliveira Souza-Formigoni,Maria Lucia %A , %+ Swiss Research Institute for Public Health and Addiction, University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 44 448 22 60, michael.schaub@isgf.uzh.ch %K alcohol %K internet %K public health %K self-help %K World Health Organization %D 2021 %7 27.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Given the scarcity of alcohol prevention and use disorder treatments in many low- and middle-income countries (LMICs), the World Health Organization has launched an eHealth portal that includes the web-based self-help program “Alcohol e-Health.” Objective: We aimed to test the effectiveness of the Alcohol e-Health program in a randomized controlled trial. Methods: This was a two-arm, individually randomized, and controlled trial across four LMICs comparing the self-help program and a psychoeducation and internet access as usual waiting list. Participants were broadly recruited from community samples in Belarus, Brazil, India, and Mexico from January 2016 through January 2019. The primary outcome measure was change in the Alcohol Use Disorders Identification Test (AUDIT) score with a time frame of 6 months between baseline and follow-up. Secondary outcomes included self-reported numbers of standard drinks over the previous week and cessation of harmful or hazardous drinking (AUDIT score <8). Results: For this study, we recruited 1400 predominantly male (n=982, 70.1%) at least harmful or hazardous alcohol drinkers. The mean age was 37.6 years (SD 10.5). The participants were recruited from Brazil (n=587), Mexico (n=509), India (n=212), and Belarus (n=92). Overall, complete case analysis identified higher AUDIT changes in the intervention group (B=−4.18, 95% CI −5.42 to −2.93, P<.001, d=0.56) that were mirrored by changes in weekly standard drinks (B=−9.34, 95% CI −15.90 to −2.77, P=.005, d=0.28) and cessation rates for harmful or hazardous drinking (χ21=14.56, N=561, P<.001). The supplementary intention-to-treat analyses largely confirmed these initial results. Conclusions: The expansion of the Alcohol e-Health program to other LMICs with underdeveloped alcohol prevention and treatment systems for alcohol use disorders should be considered after successful replication of the present results. Trial Registration: ISRCTN ISRCTN14037475; https://www.isrctn.com/ISRCTN14037475 International Registered Report Identifier (IRRID): RR2-10.1111/add.14034 %M 34448710 %R 10.2196/21686 %U https://www.jmir.org/2021/8/e21686 %U https://doi.org/10.2196/21686 %U http://www.ncbi.nlm.nih.gov/pubmed/34448710 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e29299 %T Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study %A Li,Jia %A Yu,Kanghui %A Bao,Xinyu %A Liu,Xuan %A Yao,Junping %+ Xi'an Research Institute of High Technology, No.2 Tongxin Road, Xi'an, 710025, China, 86 18702963951, junpingy200225@163.com %K engagement %K clickstream data %K cross-site visit %K platform %K channel %K mobile phone %D 2021 %7 13.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: User engagement is a key performance variable for eHealth websites. However, most existing studies on user engagement either focus on a single website or depend on survey data. To date, we still lack an overview of user engagement on multiple eHealth websites derived from objective data. Therefore, it is relevant to provide a holistic view of user engagement on multiple eHealth websites based on cross-site clickstream data. Objective: This study aims to describe the patterns of user engagement on eHealth websites and investigate how platforms, channels, sex, and income influence user engagement on eHealth websites. Methods: The data used in this study were the clickstream data of 1095 mobile users, which were obtained from a large telecom company in Shanghai, China. The observation period covered 8 months (January 2017 to August 2017). Descriptive statistics, two-tailed t tests, and an analysis of variance were used for data analysis. Results: The medical category accounted for most of the market share of eHealth website visits (134,009/184,826, 72.51%), followed by the lifestyle category (46,870/184,826, 25.36%). The e-pharmacy category had the smallest market share, accounting for only 2.14% (3947/184,826) of the total visits. eHealth websites were characterized by very low visit penetration and relatively high user penetration. The distribution of engagement intensity followed a power law distribution. Visits to eHealth websites were highly concentrated. User engagement was generally high on weekdays but low on weekends. Furthermore, user engagement gradually increased from morning to noon. After noon, user engagement declined until it reached its lowest level at midnight. Lifestyle websites, followed by medical websites, had the highest customer loyalty. e-Pharmacy websites had the lowest customer loyalty. Popular eHealth websites, such as medical websites, can effectively provide referral traffic for lifestyle and e-pharmacy websites. However, the opposite is also true. Android users were more engaged in eHealth websites than iOS users. The engagement volume of app users was 4.85 times that of browser users, and the engagement intensity of app users was 4.22 times that of browser users. Male users had a higher engagement intensity than female users. Income negatively moderated the influence that platforms (Android vs iOS) had on user engagement. Low-income Android users were the most engaged in eHealth websites. Conversely, low-income iOS users were the least engaged in eHealth websites. Conclusions: Clickstream data provide a new way to derive an overview of user engagement patterns on eHealth websites and investigate the influence that various factors (eg, platform, channel, sex, and income) have on engagement behavior. Compared with self-reported data from a questionnaire, cross-site clickstream data are more objective, accurate, and appropriate for pattern discovery. Many user engagement patterns and findings regarding the influential factors revealed by cross-site clickstream data have not been previously reported. %M 34397392 %R 10.2196/29299 %U https://www.jmir.org/2021/8/e29299 %U https://doi.org/10.2196/29299 %U http://www.ncbi.nlm.nih.gov/pubmed/34397392 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e24546 %T The Impact of Gamification-Induced Users' Feelings on the Continued Use of mHealth Apps: A Structural Equation Model With the Self-Determination Theory Approach %A Wang,Tong %A Fan,Lingye %A Zheng,Xu %A Wang,Wei %A Liang,Jun %A An,Kai %A Ju,Mei %A Lei,Jianbo %+ Institute of Medical Technology, Health Science Center, Peking University, 38 Xueyuan Rd, Haidian District, Beijing, China, 86 82805901, jblei@hsc.pku.edu.cn %K mHealth app %K continued use %K continuance intention %K gamification %K self-determination theory (SDT) %K expectation confirmation model of information system continuance (ECM-ISC) %K PLS-SEM %D 2021 %7 12.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Continued use of mHealth apps can achieve better effects in health management. Gamification is an important factor in promoting users’ intention to continue using mHealth apps. Past research has rarely explored the factors underlying the continued use of mobile health (mHealth) apps and gamification’s impact mechanism or path on continued use. Objective: This study aimed to explore the factors influencing mHealth app users’ intention to continue using mHealth apps and the impact mechanism and path of users’ feelings induced by gamification on continued mHealth app use. Methods: First, based on the expectation confirmation model of information system continuance, we built a theoretical model for continued use of mHealth apps based on users’ feelings toward gamification. We used self-determination theory to analyze gamification’s impact on user perceptions and set the resulting feelings (competence, autonomy, and relatedness) as constructs in the model. Second, we used the survey method to validate the research model, and we used partial least squares to analyze the data. Results: A total of 2988 responses were collected from mHealth app users, and 307 responses were included in the structural equation model after passing the acceptance criteria. The intrinsic motivation for using mHealth apps is significantly affected by autonomy (β=.312; P<.001), competence (β=.346; P<.001), and relatedness (β=.165; P=.004) induced by gamification. The intrinsic motivation for using mHealth apps has a significant impact on satisfaction (β=.311, P<.001) and continuance intention (β=.142; P=.045); furthermore, satisfaction impacts continuance intention significantly (β=.415; P<.001). Confirmation has a significant impact on perceived usefulness (β=.859; P<.001) and satisfaction (β=.391; P<.001), and perceived usefulness has a significant impact on satisfaction (β=.269; P<.001) and continuance intention (β=.273; P=.001). The mediating effect analysis showed that in the impact path of the intrinsic motivation for using the mHealth apps on continuance intention, satisfaction plays a partial mediating role (β=.129; P<.001), with a variance accounted for of 0.466. Conclusions: This study explored the impact path of users’ feelings induced by gamification on the intention of continued mHealth app use. We confirmed that perceived usefulness, confirmation, and satisfaction in the classical continued use theory for nonmedical information systems positively affect continuance intention. We also found that the path and mechanism of users' feelings regarding autonomy, competence, and relatedness generated during interactions with different gamification elements promote the continued use of mHealth apps. %M 34387550 %R 10.2196/24546 %U https://www.jmir.org/2021/8/e24546 %U https://doi.org/10.2196/24546 %U http://www.ncbi.nlm.nih.gov/pubmed/34387550 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 8 %P e26852 %T Patients’ Experiences of Using a Self-help App for Posttraumatic Stress Disorder: Qualitative Study %A Riisager,Lisa H G %A Christensen,Anne Bryde %A Scharff,Frederik Bernt %A Arendt,Ida-Marie T P %A Ismail,Israa %A Lau,Marianne Engelbrecht %A Moeller,Stine Bjerrum %+ Department of Psychology, University of Southern Denmark, Campusvej 55, Odense, 5230, Denmark, 45 25300977, lisagr@health.sdu.dk %K app %K PTSD %K mHealth %K qualitative analysis %K patient experience %K posttraumatic stress disorder %K thematic analysis %K smartphone %K intervention %K mobile phone %D 2021 %7 4.8.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Posttraumatic stress disorder (PTSD) is a common disorder that requires more treatment options. Mobile health (mHealth) app interventions are promising for patients with PTSD, as they can provide easily accessible support, strategies, and information. However, knowledge about mHealth interventions is sparse and primarily based on quantitative studies. Objective: The aim of this study is to qualitatively explore the experiences of patients with PTSD with regard to using an mHealth app as a stand-alone intervention before commencing psychotherapeutic treatment. Methods: We conducted semistructured interviews with 14 participants 6 weeks after they received the app. The participants were all referred to PTSD treatment and were waiting to commence psychotherapeutic treatment. During this waiting time, the participants had no contact with the health staff. Interviews were transcribed and were analyzed using thematic analysis. Results: A total of 3 themes were identified—the use of app, being a patient, and the overall evaluation of the app. The use of the app was described with the subtheme of habits, and the theme of being a patient included the subthemes of having negative experiences with the app and being a part of a research project. The use of the app encompassed how psychological factors and technical problems could interfere with the use of the app. The theme of being a patient depicted that the waiting time before starting treatment was long, and a subgroup of patients experienced feeling worse during this time, which they partly attributed to using the app. Several suggestions for change have been described in the overall evaluation of the app. Conclusions: The findings in this study revealed that emotional arousal influenced the use of the app and that it was difficult for participants to establish a habit of using the app, thus reflecting the importance of supporting habit formation when implementing an mHealth app in mental health care services. This study makes an important contribution to the field of mHealth research, as it revealed that some participants had negative experiences resulting from using the app, thus reflecting the potential harm of having an mHealth app without the support of a clinician. It is therefore recommended to use a blended care treatment or an approach in which mental health care professionals prescribe an mHealth app for relevant patients to avoid increased suicidal risk. %M 34346896 %R 10.2196/26852 %U https://formative.jmir.org/2021/8/e26852 %U https://doi.org/10.2196/26852 %U http://www.ncbi.nlm.nih.gov/pubmed/34346896 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 8 %P e29126 %T Examining the Mental Workload Associated With Digital Health Technologies in Health Care: Protocol for a Systematic Review Focusing on Assessment Methods %A Kremer,Lisanne %A Lipprandt,Myriam %A Röhrig,Rainer %A Breil,Bernhard %+ Faculty of Health Care, Niederrhein University of Applied Sciences, Reinarzstr. 49, Krefeld, 47805, Germany, 49 21518226678, lisanne.kremer@hs-niederrhein.de %K mental workload %K cognitive load %K assessment %K healthcare workers %K health information system %K digital health technology %K health care professionals %K stress %K eyetracking %D 2021 %7 3.8.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The workload in health care is high; physicians and nurses report high stress levels due to a demanding environment where they often have to perform multiple tasks simultaneously. As a result, mental health issues among health care professionals (HCPs) are on the rise and the prevalence of errors in their daily tasks could increase. Processes of demographic change are partly responsible for even higher stress levels among HCPs. The digitization of patient care is intended to counteract these processes. However, it remains unclear whether these health information systems (HIS) and digital health technologies (DHT) support the HCPs and relieve stress, or if they represent a further burden. The mental construct that describes this burden of technologies is mental workload (MWL). Work in the clinic can be viewed as working in safety-critical environments. Particularly in this sensitive setting, the measurement methods of MWL are relevant, mainly due to their strongly differing levels of intrusiveness and sensitivity. The method of eye tracking could be a useful way to measure MWL directly in the field. Objective: The systematic review aims to address the following questions: (1) In which manner do DHT contribute to the overall MWL of HCPs? (2) Can we observe a direct or indirect effect of DHT on MWL? (3) Which aspects or factors of DHT contribute to an increase in MWL? (4) Which methods/assessments are applied to measure MWL related to HIS/DHT? (5) What role does eye tracking/pupillometry play in the context of measuring MWL? (6) Which outcomes are being assessed via eye tracking? Methods: Following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement, we will conduct a systematic review. Based on the research questions, we define keywords that we then combine in search terms. The review follows the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis, and data synthesis. Results: We expect results as well as a finalization of the review in the summer of 2021. Conclusions: This review will evaluate the impact of DHT on the MWL of HCPs. In addition, assessment methods of MWL in the context of digital technologies will be systematically analyzed. Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271 International Registered Report Identifier (IRRID): DERR1-10.2196/29126 %M 34342590 %R 10.2196/29126 %U https://www.researchprotocols.org/2021/8/e29126 %U https://doi.org/10.2196/29126 %U http://www.ncbi.nlm.nih.gov/pubmed/34342590 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 7 %P e27436 %T Determining Acceptance of e-Mental Health Interventions in Digital Psychodiabetology Using a Quantitative Web-Based Survey: Cross-sectional Study %A Damerau,Mirjam %A Teufel,Martin %A Musche,Venja %A Dinse,Hannah %A Schweda,Adam %A Beckord,Jil %A Steinbach,Jasmin %A Schmidt,Kira %A Skoda,Eva-Maria %A Bäuerle,Alexander %+ Clinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg Essen, Virchowstr. 174, Essen, 45147, Germany, 49 201 438755 228, mirjam.damerau@uni-due.de %K e-mental health %K acceptance %K UTAUT %K mental health %K diabetes %K e-mental health intervention %K psychodiabetology %D 2021 %7 30.7.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Diabetes is a very common chronic disease that exerts massive physiological and psychological burdens on patients. The digitalization of mental health care has generated effective e-mental health approaches, which offer an indubitable practical value for patient treatment. However, before implementing and optimizing e-mental health tools, their acceptance and underlying barriers and resources should be first determined for developing and establishing effective patient-oriented interventions. Objective: This study aims to assess the acceptance of e-mental health interventions among patients with diabetes and explore its underlying barriers and resources. Methods: A cross-sectional study was conducted in Germany from April 9, 2020, to June 15, 2020, through a web-based survey for which patients were recruited via web-based diabetes channels. The eligibility requirements were adult age (18 years or older), a good command of the German language, internet access, and a diagnosis of diabetes. Acceptance was measured using a modified questionnaire, which was based on the well-established Unified Theory of Acceptance and Use of Technology (UTAUT) and assessed health-related internet use, acceptance of e-mental health interventions, and its barriers and resources. Mental health was measured using validated and established instruments, namely the Generalized Anxiety Disorder Scale-7, Patient Health Questionnaire-2, and Distress Thermometer. In addition, sociodemographic and medical data regarding diabetes were collected. Results: Of the 340 participants who started the survey, 261 (76.8%) completed it and the final sample comprised 258 participants with complete data sets. The acceptance of e-mental health interventions in patients with diabetes was overall moderate (mean 3.02, SD 1.14). Gender and having a mental disorder had a significant influence on acceptance (P<.001). In an extended UTAUT regression model (UTAUT predictors plus sociodemographics and mental health variables), distress (β=.11; P=.03) as well as the UTAUT predictors performance expectancy (β=.50; P<.001), effort expectancy (β=.15; P=.001), and social influence (β=.28; P<.001) significantly predicted acceptance. The comparison between an extended UTAUT regression model (13 predictors) and the UTAUT-only regression model (performance expectancy, effort expectancy, social influence) revealed no significant difference in explained variance (F10,244=1.567; P=.12). Conclusions: This study supports the viability of the UTAUT model and its predictors in assessing the acceptance of e-mental health interventions among patients with diabetes. Three UTAUT predictors reached a notable amount of explained variance of 75% in the acceptance, indicating that it is a very useful and efficient method for measuring e-mental health intervention acceptance in patients with diabetes. Owing to the close link between acceptance and use, acceptance-facilitating interventions focusing on these three UTAUT predictors should be fostered to bring forward the highly needed establishment of effective e-mental health interventions in psychodiabetology. %M 34328429 %R 10.2196/27436 %U https://formative.jmir.org/2021/7/e27436 %U https://doi.org/10.2196/27436 %U http://www.ncbi.nlm.nih.gov/pubmed/34328429 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e21202 %T Preadolescent Students’ Engagement With an mHealth Intervention Fostering Social Comparison for Health Behavior Change: Crossover Experimental Study %A Nuijten,Raoul Ceasar Yannic %A Van Gorp,Pieter %A Borghouts,Tom %A Le Blanc,Pascale %A Van den Berg,Pauline %A Kemperman,Astrid %A Hadian,Ehsan %A Simons,Monique %+ Department of Industrial Engineering, Eindhoven University of Technology, Groene Loper 3, Eindhoven, 5612 AE, Netherlands, 31 0614906142, r.c.y.nuijten@tue.nl %K mHealth %K health promotion %K social comparison %K competitiveness %K collaboration %K gamification %K preadolescents %K high school students %D 2021 %7 29.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Contemporary mobile health (mHealth) interventions use various behavior change techniques to promote healthier lifestyles. Social comparison is one of the techniques that is consensually agreed to be effective in engaging the general population in mHealth interventions. However, it is unclear how this strategy can be best used to engage preadolescents. Nevertheless, this strategy has great potential for this target audience, as they are particularly developing their social skills. Objective: This study aims to evaluate how social comparison drives preadolescents’ engagement with an mHealth app. Methods: We designed a 12-week crossover experiment in which we studied 3 approaches to implementing behavior change via social comparison. This study was hosted in a school environment to leverage naturally existing social structures among preadolescents. During the experiment, students and teachers used an mHealth tool that awarded points for performing healthy activities. Participants could read their aggregated scores on a leaderboard and compare their performance with others. In particular, these leaderboards were tweaked to implement 3 approaches of the social comparison technique. The first approach focused on intragroup comparison (ie, students and teachers competing against each other to obtain the most points), whereas the other two approaches focused on intergroup comparison (ie, classes of students and their mentoring teachers collaborating to compete against other classes). Additionally, in the third approach, the performance of teachers was highlighted to further increase students’ engagement through teachers’ natural exemplary function. To obtain our results, we used linear modeling techniques to analyze the dropout rates and engagement levels for the different approaches. In such analyses, we also considered individual participant traits. Results: Our sample included 313 participants—290 students (92.7%) and 23 teachers (7.3%). It was found that student engagement levels dropped over time and declined during holidays. However, students seemed to monitor the intergroup competitions more closely than the intragroup competitions, as they, on average, checked the mHealth app more often when they were engaged in team-based comparisons. Students, on average, performed the most unique activities when they were engaged in the second intergroup setting, perhaps because their teachers were most active in this setting. Moreover, teachers seemed to play an important role in engaging their students, as their relationship with their students influenced the engagement of the students. Conclusions: When using social comparison to engage preadolescents with an mHealth tool, an intergroup setting, rather than an intragroup competition, motivated them to engage with the app but did not necessarily motivate them to perform more activities. It seems that the number of unique activities that preadolescents perform depends on the activeness of a role model. Moreover, this effect is amplified by preadolescents’ perceptions of closeness to that role model. %M 34326041 %R 10.2196/21202 %U https://www.jmir.org/2021/7/e21202 %U https://doi.org/10.2196/21202 %U http://www.ncbi.nlm.nih.gov/pubmed/34326041 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e25973 %T Turn on, Tune in, and Drop out: Predictors of Attrition in a Prospective Observational Cohort Study on Psychedelic Use %A Hübner,Sebastian %A Haijen,Eline %A Kaelen,Mendel %A Carhart-Harris,Robin Lester %A Kettner,Hannes %+ Centre for Psychedelic Research, Imperial College London, Du Cane Rd, Burlington Danes Building, London, W12 0TY, United Kingdom, 44 020 7589 5111, hannes.kettner17@imperial.ac.uk %K attrition %K digital data %K dropout %K educational level %K personality %K psychedelics %K web-based research %K web-based survey %D 2021 %7 28.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The resurgence of research and public interest in the positive psychological effects of psychedelics, together with advancements in digital data collection techniques, have brought forth a new type of research design, which involves prospectively gathering large-scale naturalistic data from psychedelic users; that is, before and after the use of a psychedelic compound. A methodological limitation of such studies is their high attrition rate, particularly owing to participants who stop responding after initial study enrollment. Importantly, study dropout can introduce systematic biases that may affect the interpretability of results. Objective: Based on a previously collected sample (baseline n=654), here we investigated potential determinants of study attrition in web-based prospective studies on psychedelic use. Methods: Logistic regression models were used to examine demographic, psychological trait and state, and psychedelic-specific predictors of dropout. Predictors were assessed 1 week before, 1 day after, and 2 weeks after psychedelic use, with attrition being defined as noncompletion of the key endpoint 4 weeks post experience. Results: Predictors of attrition were found among demographic variables including age (β=0.024; P=.007) and educational levels, as well as personality traits, specifically conscientiousness (β=–0.079; P=.02) and extraversion (β=0.082; P=.01). Contrary to prior hypotheses, neither baseline attitudes toward psychedelics nor the intensity of acute challenging experiences were predictive of dropout. Conclusions: The baseline predictors of attrition identified here are consistent with those reported in longitudinal studies in other scientific disciplines, suggesting their transdisciplinary relevance. Moreover, the lack of an association between attrition and psychedelic advocacy or negative drug experiences in our sample contextualizes concerns about problematic biases in these and related data. %M 34319246 %R 10.2196/25973 %U https://www.jmir.org/2021/7/e25973 %U https://doi.org/10.2196/25973 %U http://www.ncbi.nlm.nih.gov/pubmed/34319246 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 7 %P e25177 %T Digital Health Interventions in Physiotherapy: Development of Client and Health Care Provider Survey Instruments %A Merolli,Mark %A Hinman,Rana S %A Lawford,Belinda J %A Choo,Dawn %A Gray,Kathleen %+ Centre for Digital Transformation of Health, Faculty of Medicine Dentistry & Health Sciences, The University of Melbourne, Level 7, 161 Barry St, Carlton, Melbourne, Victoria, 3053, Australia, 61 383443689, merollim@unimelb.edu.au %K digital health interventions %K surveys and questionnaires %K World Health Organization %K physiotherapy %K physical therapy %K musculoskeletal %K mobile phone %D 2021 %7 28.7.2021 %9 Early Report %J JMIR Res Protoc %G English %X Background: The advancement of digital health has widened the scope of technology use across multiple frontiers of health care services, including personalized therapeutics, mobile health, eHealth record management, and telehealth consultations. The World Health Organization (WHO) responded to this in 2018 by publishing an inaugural broad classification framework of digital health interventions (DHIs) used to address contemporary health system needs. Objective: This study aims to describe the systematic development of dual survey instruments (clinician and patient) to support data collection, administered in a physiotherapy setting, about perceptions toward DHIs. This is achieved by adapting the WHO framework classification for DHIs for application in real-world research. Methods: Using a qualitative item review approach, WHO DHI descriptors were adapted and refined systematically to be used in a survey form. This approach was designed to align with the processes of delivering and receiving care in clinical practice, using musculoskeletal physiotherapy as a practical case scenario. Results: Complementary survey instruments (for health care providers and clients) were developed by adapting descriptor items. These instruments will be used in a larger study exploring the willingness of physiotherapists and patients to use digital technologies in the management of musculoskeletal conditions. Conclusions: This study builds on the WHO-standardized DHI framework. We developed dual novel survey instruments by adapting and refining the functions of DHIs. These may be deployed to explore the perceived usefulness and application of DHIs for different clinical care functions. Researchers may wish to use these survey instruments to examine digital health use systematically in a variety of clinical fields or technology scenarios in a way that is standardized and generalizable. %M 34319242 %R 10.2196/25177 %U https://www.researchprotocols.org/2021/7/e25177 %U https://doi.org/10.2196/25177 %U http://www.ncbi.nlm.nih.gov/pubmed/34319242 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 7 %P e27227 %T Safety and Acceptability of a Natural Language Artificial Intelligence Assistant to Deliver Clinical Follow-up to Cataract Surgery Patients: Proposal %A de Pennington,Nick %A Mole,Guy %A Lim,Ernest %A Milne-Ives,Madison %A Normando,Eduardo %A Xue,Kanmin %A Meinert,Edward %+ Centre for Health Technology, University of Plymouth, 6 Kirkby Place, Plymouth, PL4 6DR, United Kingdom, 44 7824446808, edward.meinert@plymouth.ac.uk %K artificial intelligence %K natural language processing %K telemedicine %K cataract %K aftercare %K speech recognition software %K medical informatics %K health services %K health communication %K delivery of health care %K patient acceptance of health care %K mental health %K cell phone %K internet %K conversational agent %K chatbot %K expert systems %K dialogue system %K relational agent %D 2021 %7 28.7.2021 %9 Proposal %J JMIR Res Protoc %G English %X Background: Due to an aging population, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high-volume workloads, driving increasing costs for providers. Artificial intelligence (AI), in the form of conversational agents, presents a possible opportunity to enable efficiency in the delivery of care. Objective: This study aims to evaluate the effectiveness, usability, and acceptability of Dora agent: Ufonia’s autonomous voice conversational agent, an AI-enabled autonomous telemedicine call for the detection of postoperative cataract surgery patients who require further assessment. The objectives of this study are to establish Dora’s efficacy in comparison with an expert clinician, determine baseline sensitivity and specificity for the detection of true complications, evaluate patient acceptability, collect evidence for cost-effectiveness, and capture data to support further development and evaluation. Methods: Using an implementation science construct, the interdisciplinary study will be a mixed methods phase 1 pilot establishing interobserver reliability of the system, usability, and acceptability. This will be done using the following scales and frameworks: the system usability scale; assessment of Health Information Technology Interventions in Evidence-Based Medicine Evaluation Framework; the telehealth usability questionnaire; and the Non-Adoption, Abandonment, and Challenges to the Scale-up, Spread and Suitability framework. Results: The evaluation is expected to show that conversational technology can be used to conduct an accurate assessment and that it is acceptable to different populations with different backgrounds. In addition, the results will demonstrate how successfully the system can be delivered in organizations with different clinical pathways and how it can be integrated with their existing platforms. Conclusions: The project’s key contributions will be evidence of the effectiveness of AI voice conversational agents and their associated usability and acceptability. International Registered Report Identifier (IRRID): PRR1-10.2196/27227 %M 34319248 %R 10.2196/27227 %U https://www.researchprotocols.org/2021/7/e27227 %U https://doi.org/10.2196/27227 %U http://www.ncbi.nlm.nih.gov/pubmed/34319248 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e23029 %T A Brief Intervention to Increase Uptake and Adherence of an Internet-Based Program for Depression and Anxiety (Enhancing Engagement With Psychosocial Interventions): Randomized Controlled Trial %A Batterham,Philip J %A Calear,Alison L %A Sunderland,Matthew %A Kay-Lambkin,Frances %A Farrer,Louise M %A Christensen,Helen %A Gulliver,Amelia %+ Centre for Mental Health Research, Research School of Population Health, The Australian National University, 63 Eggleston Rd, Acton, Canberra, 2601, Australia, 61 02612 ext 51031, philip.batterham@anu.edu.au %K implementation %K mental health %K adherence %K uptake %K engagement-facilitation intervention %K internet %K randomized controlled trial %D 2021 %7 27.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Psychosocial, self-guided, internet-based programs are effective in treating depression and anxiety. However, the community uptake of these programs is poor. Recent approaches to increasing engagement (defined as both uptake and adherence) in internet-based programs include brief engagement facilitation interventions (EFIs). However, these programs require evaluation to assess their efficacy. Objective: The aims of this hybrid implementation effectiveness trial are to examine the effects of a brief internet-based EFI presented before an internet-based cognitive behavioral therapy self-help program (myCompass 2) in improving engagement (uptake and adherence) with that program (primary aim), assess the relative efficacy of the myCompass 2 program, and determine whether greater engagement was associated with improved efficacy (greater reduction in depression or anxiety symptoms) relative to the control (secondary aim). Methods: A 3-arm randomized controlled trial (N=849; recruited via social media) assessed the independent efficacy of the EFI and myCompass 2. The myCompass 2 program was delivered with or without the EFI; both conditions were compared with an attention control condition. The EFI comprised brief (5 minutes), tailored audio-visual content on a series of click-through linear webpages. Results: Uptake was high in all groups; 82.8% (703/849) of participants clicked through the intervention following the pretest survey. However, the difference in uptake between the EFI + myCompass 2 condition (234/280, 83.6%) and the myCompass 2 alone condition (222/285, 77.9%) was not significant (n=565; χ21=29.2; P=.09). In addition, there was no significant difference in the proportion of participants who started any number of modules (1-14 modules) versus those who started none between the EFI + myCompass 2 (214/565, 37.9%) and the myCompass 2 alone (210/565, 37.2%) conditions (n=565; χ21<0.1; P=.87). Finally, there was no significant difference between the EFI + myCompass 2 and the myCompass 2 alone conditions in the number of modules started (U=39366.50; z=−0.32; P=.75) or completed (U=39494.0; z=−0.29; P=.77). The myCompass 2 program was not found to be efficacious over time for symptoms of depression (F4,349.97=1.16; P=.33) or anxiety (F4,445.99=0.12; P=.98). However, planned contrasts suggested that myCompass 2 may have been effective for participants with elevated generalized anxiety disorder symptoms (F4,332.80=3.50; P=.01). Conclusions: This brief internet-based EFI did not increase the uptake of or adherence to an existing internet-based program for depression and anxiety. Individuals’ motivation to initiate and complete internet-based self-guided interventions is complex and remains a significant challenge for self-guided interventions. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12618001565235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375839 %M 34313595 %R 10.2196/23029 %U https://www.jmir.org/2021/7/e23029 %U https://doi.org/10.2196/23029 %U http://www.ncbi.nlm.nih.gov/pubmed/34313595 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 7 %P e24634 %T Feasibility, Efficacy, and Efficiency of eHealth-Supported Pediatric Asthma Care: Six-Month Quasi-Experimental Single-Arm Pretest-Posttest Study %A van der Kamp,Mattienne %A Reimering Hartgerink,Pamela %A Driessen,Jean %A Thio,Bernard %A Hermens,Hermie %A Tabak,Monique %+ Department of Pediatrics, Medisch Spectrum Twente, Koningsplein 1, Enschede, 7512KZ, Netherlands, 31 534872310, mattienne@gmail.com %K telemedicine %K feasibility studies %K child %K self-management %K asthma %K patient acceptance of health care %K ambulatory care %K remote sensing technology %K cost-benefit analysis %K health care costs %D 2021 %7 26.7.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Early detection of loss of asthma control can effectively reduce the burden of the disease. However, broad implementation in clinical practice has not been accomplished so far. We are in need of research investigating the operationalization of eHealth pediatric asthma care in practice, which can provide the most potential benefits in terms of adoption, efficiency, and effectiveness. Objective: The aim of this study was to investigate the technical and clinical feasibility, including an exploration of the efficacy and cost-efficiency, of an eHealth program implemented in daily clinical pediatric asthma practice. Methods: We designed an eHealth-supported pediatric asthma program facilitating early detection of loss of asthma control while increasing symptom awareness and self-management. In the 6-month program, asthma control was monitored by 4 health care professionals (HCPs) by using objective home measurements and the web-based Puffer app to allow timely medical anticipation and prevent treatment delay. Technical feasibility was assessed by technology use, system usability, and technology acceptance. Clinical feasibility was assessed by participation and patient-reported health and care outcomes and via a focus group with HCPs regarding their experiences of implementing eHealth in daily practice. The efficacy and cost-efficiency were explored by comparing pretest-posttest program differences in asthma outcomes (asthma control, lung function, and therapy adherence) and medical consumption. Results: Of 41 children, 35 children with moderate-to-severe asthma volunteered for participation. With regard to technical feasibility, the Puffer app scored a good usability score of 78 on the System Usability Scale and a score of 70 for technology acceptance on a scale of 1 to 100. Approximately 75% (18/24) of the children indicated that eHealth helped them to control their asthma during the program. HCPs indicated that home measurements and real time communication enabled them to make safe and substantiated medical decisions during symptom manifestations. With an average time commitment of 15 minutes by patients, eHealth care led to a 80% gross reduction (from €71,784 to €14,018, US $1=€0.85) in health care utilization, 8.6% increase (from 18.6 to 20.2, P=.40) in asthma control, 25.0% increase (from 2.8 to 3.5, P=.04) in the self-management level, and 20.4% improved (from 71.2 to 76.8, P=.02) therapy adherence. Conclusions: eHealth asthma care seems to be technically and clinically feasible, enables safe remote care, and seems to be beneficial for pediatric asthma care in terms of health outcomes and health care utilization. Follow-up research should focus on targeted effectiveness studies with the lessons learned, while also enabling individualization of eHealth for personalized health care. %M 34309568 %R 10.2196/24634 %U https://formative.jmir.org/2021/7/e24634 %U https://doi.org/10.2196/24634 %U http://www.ncbi.nlm.nih.gov/pubmed/34309568 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e22203 %T Uptake of and Engagement With an Online Sexual Health Intervention (HOPE eIntervention) Among African American Young Adults: Mixed Methods Study %A Williamson,Alicia %A Barbarin,Andrea %A Campbell,Bettina %A Campbell,Terrance %A Franzen,Susan %A Reischl,Thomas M %A Zimmerman,Marc %A Veinot,Tiffany Christine %+ School of Information, University of Michigan, 4314 North Quad, 105 S State Street, Ann Arbor, MI, 48109-1285, United States, 1 734 615 8281, tveinot@umich.edu %K HIV prevention %K consumer health informatics %K sexual health %K health equity %K technology adoption %K technology usage %D 2021 %7 16.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Regarding health technologies, African American young adults have low rates of uptake, ongoing usage, and engagement, which may widen sexual health inequalities. Objective: We aimed to examine rates of uptake and ongoing usage, and factors influencing uptake, ongoing usage, and engagement for a consumer health informatics (CHI) intervention for HIV/sexually transmitted infection (STI) prevention among African American young adults, using the diffusion of innovation theory, trust-centered design framework, and O’Brien and Toms’ model of engagement. Methods: This community-based participatory mixed methods study included surveys at four time points (n=315; 280 African American participants) among young adults aged 18 to 24 years involved in a blended offline/online HIV/STI prevention intervention (HIV Outreach, Prevention, and Education [HOPE] eIntervention), which was described as a “HOPE party.” Qualitative interviews were conducted with a subset of participants (n=19) after initial surveys and website server logs indicated low uptake and ongoing usage. A generalized linear mixed-effects model identified predictors of eIntervention uptake, server logs were summarized to describe use over time, and interview transcripts were coded and thematically analyzed to identify factors affecting uptake and engagement. Results: Participants’ initial self-reported eIntervention uptake was low, but increased significantly over time, although uptake never reached expectations. The most frequent activity was visiting the website. Demographic factors and HOPE party social network characteristics were not significantly correlated with uptake, although participant education and party network gender homophily approached significance. According to interviews, one factor driving uptake was the desire to share HIV/STI prevention information with others. Survey and interview results showed that technology access, perceived time, and institutional and technological trust were necessary conditions for uptake. Interviews revealed that factors undermining uptake were insufficient promotion and awareness building, and the platform of the intervention, with social media being less appealing due to previous negative experiences concerning discussion of sexuality on social media. During the interaction with the eIntervention, interview data showed that factors driving initial engagement were audience-targeted website esthetics and appealing visuals. Ongoing usage was impeded by insufficiently frequent updates. Similarly, lack of novelty drove disengagement, although a social media contest for sharing intervention content resulted in some re-engagement. Conclusions: To encourage uptake, CHI interventions for African American young adults can better leverage users’ desires to share information about HIV/STI prevention with others. Ensuring implementation through trusted organizations is also important, though vigorous promotion is needed. Visual appeal and targeted content foster engagement at first, but ongoing usage may require continual content changes. A thorough analysis of CHI intervention use can inform the development of future interventions to promote uptake and engagement. To guide future analyses, we present an expanded uptake and engagement model for CHI interventions targeting African American young adults based on our empirical results. %M 34269689 %R 10.2196/22203 %U https://www.jmir.org/2021/7/e22203 %U https://doi.org/10.2196/22203 %U http://www.ncbi.nlm.nih.gov/pubmed/34269689 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e23227 %T The Effects of Continuous Usage of a Diabetes Management App on Glycemic Control in Real-world Clinical Practice: Retrospective Analysis %A Tu,Yu-Zhen %A Chang,Ya-Ting %A Chiou,Hung-Yi %A Lai,Ken %+ H2 Inc, 4F, No 32, Aly 18, Ln 478, Ruiguang Rd, Neihu Dist, Taipei, Taiwan, 886 287976661 ext 105, klai@health2sync.com %K app %K diabetes care %K diabetes %K digital intervention %K digital therapeutics %K glycemic control %K mobile app %K mHealth %K real-world data %K therapy %D 2021 %7 15.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The efficacy of digital technology in improving diabetes management has typically been demonstrated through studies such as randomized controlled trials, which have reported a steeper reduction in hemoglobin A1c (HbA1c) values for patients who adopted a digital solution. However, evidence from real-world clinical practice is still limited. Objective: This study aimed to evaluate the effectiveness of digital interventions by tracking HbA1c improvements over 1 year in real-world clinical settings. Methods: Patients used the Health2Sync mobile app to track self-measured outcomes and communicate with health care professionals (HCPs). HCPs used the web-based Patient Management Platform to monitor patient data, view test results from clinical laboratories, and communicate with patients. Patients who have been onboarded for at least 13 months and have consecutive HbA1c findings for 5 quarters were included in the analysis. They were then stratified into 3 groups (high, mid, and low retention) based on their level of use of Health2Sync in the first 6 months of onboarding. A mixed model was built to compare the slopes of the rate of reduction in HbA1c among the groups. In addition, these patients’ retention on the app from the seventh to the 12th month was verified through multiple comparisons. Results: A sample of 2036 users was included in the analysis. With the mixed model coefficient estimates, we found that app users had significant HbA1c percentage reductions as the passed quarter count increased (t=–9.869; P<.001), and that effectiveness increased in the high (t=–5.173) and mid retention (t=–6.620) groups as the interaction effects were significantly negative compared to that in the low retention group (P<.001) in the passed quarter count. The low retention group also had the highest average HbA1c value at the end of 13 months (high: 7.01%, SD 1.02%; mid: 6.99%, SD 1.00%; low: 7.17%, SD 1.14%) (Bonferroni correction: high vs low, P=.07; mid vs low, P=.02; high vs mid, P>.99). The level of use of the app remained consistent in the seventh to the 12th month after onboarding (high: 5.23 [SD 1.37] months, mid: 2.43 [SD 1.68] months, low: 0.41 [SD 0.97] months) (P<.001). Conclusions: Our analysis shows that continuous usage of the diabetes management app is associated with better glycemic control in real-world clinical practice. Further studies are required to reveal the efficacy for specific diabetes types and to observe effects beyond 1 year. %M 34264192 %R 10.2196/23227 %U https://www.jmir.org/2021/7/e23227 %U https://doi.org/10.2196/23227 %U http://www.ncbi.nlm.nih.gov/pubmed/34264192 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 7 %P e16949 %T Barriers to the Use of Web-Based Mental Health Programs for Preventing Depression: Qualitative Study %A Eccles,Heidi %A Nannarone,Molly %A Lashewicz,Bonnie %A Attridge,Mark %A Marchand,Alain %A Aiken,Alice %A Ho,Kendall %A Wang,JianLi %+ The Institute of Mental Health Research, University of Ottawa, Room 5404, 1145 Carling Ave, Ottawa, ON, K1Z 7K4, Canada, 1 6137226521 ext 6057, jlwang@ucalgary.ca %K prevention %K mental health %K depression %K problem solving therapy %K barriers %K web-based program %K qualitative study %D 2021 %7 15.7.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Depression has a profound impact on population health. Although using web-based mental health programs to prevent depression has been found to be effective in decreasing depression incidence, there are obstacles preventing their use, as reflected by the low rates of use and adherence. Objective: The aims of the study are to understand the barriers to using web-based mental health programs for the prevention of depression and the possible dangers or concerns regarding the use of such programs. Methods: BroMatters and HardHat were two randomized controlled trials (RCTs) that evaluated the effectiveness of e–mental health programs for preventing workplace depression. In the BroMatters RCT, only working men who were at high risk of having a major depressive episode were included. The participants were assigned to either the control group or 1 of 2 intervention groups. The control participants had access to the general depression information on the BroMatters website. Intervention group 1 had access to BroMatters and BroHealth—the depression prevention program. Intervention group 2 had access to BroMatters and BroHealth along with weekly access to a qualified coach through telephone calls. The HardHat trial targeted both men and women at high risk of having a major depressive episode. The participants in the intervention group were given access to the HardHat depression prevention program (which included a web-based coach), whereas HardHat access was only granted to the control group once the study was completed. This qualitative study recruited male participants from the intervention groups of the two RCTs. A total of 2 groups of participants were recruited from the BroMatters study (after a baseline interview: n=41; 1 month after the RCT: n=20; 61/744, 8.2%), and 1 group was recruited from the HardHat RCT 1 month after the initial quantitative interview (9/103, 8.7%). Semistructured interviews were performed with the participants (70/847, 8.3%) and analyzed using content analysis. Results: There were both personal and program-level barriers to program use. The three personal barriers included time, stress level, and the perception of depression prevention. Content, functionality, and dangers were the program-level barriers to the use of web-based mental health programs. Large amounts of text and functionality issues within the programs decreased participants’ engagement. The dangers associated with web-based mental health programs included privacy breaches and inadequate help for severe symptoms. Conclusions: There are personal and program-level barriers to the use of web-based mental health programs. The stigmatization of help seeking for depression symptoms affects the time spent on the program, as does the public perception of depression. Certain barriers may be mitigated by program updates, whereas others may require a complete shift in the perception of depression prevention. %M 34264195 %R 10.2196/16949 %U https://formative.jmir.org/2021/7/e16949 %U https://doi.org/10.2196/16949 %U http://www.ncbi.nlm.nih.gov/pubmed/34264195 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e26670 %T Measuring Success of Patients’ Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation %A Song,Ting %A Deng,Ning %A Cui,Tingru %A Qian,Siyu %A Liu,Fang %A Guan,Yingping %A Yu,Ping %+ Centre for Digital Transformation, School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Northfields Avenue, Wollongong, 2522, Australia, 61 2 4221 5412, ping@uow.edu.au %K mobile health %K service %K smartphone %K mobile application %K continuous use %K high blood pressure %K chronic disease %K PLS %D 2021 %7 13.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health services are gradually being introduced to support patients’ self-management of chronic conditions. The success of these services is contingent upon patients’ continuous use of them. Objective: This study aims to develop a model to measure the success of patients’ continuous use of mobile health services for the self-management of chronic conditions. Methods: The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. Results: The model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients’ intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (β=.195, P=.03), perceived usefulness (β=.307, P=.004), and user satisfaction (β=.254, P=.04) with the mobile health service. Information quality (β=.235, P=.005), system quality (β=.192, P=.02), and service quality (β=.494, P<.001) had a significantly positive influence on perceived usefulness but not on user satisfaction. Perceived usefulness had a significantly positive influence on user satisfaction (β=.664, P<.001). In a result opposite to the original hypothesis, perceived health status did not negatively influence patients’ intention to continue using the mobile health service but showed a significantly positive correlation. Conclusions: This study developed a theoretical model to predict and explain patients’ continuous use of mobile health services for self-management of chronic conditions and empirically tested the model. Perceived usefulness, user satisfaction, and health status contributed to patients’ intention to make continuous use of mobile health services for self-managing their chronic conditions. %M 34255685 %R 10.2196/26670 %U https://www.jmir.org/2021/7/e26670 %U https://doi.org/10.2196/26670 %U http://www.ncbi.nlm.nih.gov/pubmed/34255685 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 7 %P e23959 %T Recruitment and Retention Strategies Among Racial and Ethnic Minorities in Web-Based Intervention Trials: Retrospective Qualitative Analysis %A Hwang,DaSol Amy %A Lee,Alex %A Song,Jae Min %A Han,Hae-Ra %+ Johns Hopkins University School of Nursing, 525 N Wolfe St, Room 533, Baltimore, MD, 21205, United States, 1 410 614 2669, hhan3@jh.edu %K recruitment and retention %K web-based intervention %K clinical trial %K Korean American %K racial/ethnic minority %D 2021 %7 12.7.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Racial and ethnic minority groups are underrepresented in health research, contributing to persistent health disparities in the United States. Identifying effective recruitment and retention strategies among minority groups and their subpopulations is an important research agenda. Web-based intervention approaches are becoming increasingly popular with the ubiquitous use of the internet. However, it is not completely clear which recruitment and retention strategies have been successful in web-based intervention trials targeting racial and ethnic minorities. Objective: This study aims to describe lessons learned in recruiting and retaining one of the understudied ethnic minority women—Korean Americans—enrolled in a web-based intervention trial and to compare our findings with the strategies reported in relevant published web-based intervention trials. Methods: Multiple sources of data were used to address the objectives of this study, including the study team’s meeting minutes, participant tracking and contact logs, survey reports, and postintervention interviews. In addition, an electronic search involving 2 databases (PubMed and CINAHL) was performed to identify published studies using web-based interventions. Qualitative analysis was then performed to identify common themes addressing recruitment and retention strategies across the trials using web-based intervention modalities. Results: A total of 9 categories of recruitment and retention strategies emerged: authentic care; accommodation of time, place, and transportation; financial incentives; diversity among the study team; multiple, yet standardized modes of communication; mobilizing existing community relationships with efforts to build trust; prioritizing features of web-based intervention; combined use of web-based and direct recruitment; and self-directed web-based intervention with human support. Although all the studies included in the analysis combined multiple strategies, prioritizing features of web-based intervention or use of human support were particularly relevant for promoting recruitment and retention of racial and ethnic minorities in web-based intervention trials. Conclusions: The growing prevalence of internet use among racial and ethnic minority populations represents an excellent opportunity to design and deliver intervention programs via the internet. Future research should explore and compare successful recruitment and retention methods among race and ethnic groups for web-based interventions. Trial Registration: ClinicalTrials.gov NCT03726619; https://clinicaltrials.gov/ct2/show/NCT03726619. %M 34255658 %R 10.2196/23959 %U https://www.jmir.org/2021/7/e23959 %U https://doi.org/10.2196/23959 %U http://www.ncbi.nlm.nih.gov/pubmed/34255658 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 7 %P e25616 %T The Digital Engagement of Older People: Systematic Scoping Review Protocol %A Kebede,Abraham Sahilemichael %A Ozolins,Lise-Lotte %A Holst,Hanna %A Galvin,Kathleen %+ School of Health Sciences, University of Brighton, Village Way, Brighton, BN1 9PH, United Kingdom, 44 7502375585, a.s.kebede@brighton.ac.uk %K digital divide %K digital engagement %K digital inclusion %K initial adoption %K older people %K older users %K sustained engagement %K technological nonuse %K older adults %D 2021 %7 5.7.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: There is an ongoing negative narrative about aging that portrays older people as a socioeconomic burden on society. However, increased longevity and good health will allow older adults to contribute meaningfully to society and maximize their well-being. As such, a paradigm shift toward healthy and successful aging can be potentially facilitated by the growing digital technology use for mainstream (day-to-day activities) and assisted living (health and social care). Despite the rising digital engagement trend, digital inequality between the age groups persists. Objective: The aims of this scoping review are to identify the extent and breadth of existing literature of older people’s perspectives on digital engagement and summarize the barriers and facilitators for technological nonuse, initial adoption, and sustained digital technology engagement. Methods: This review will be based on the Arksey and O’Malley framework for scoping reviews. The 6-stage framework includes: identifying research questions, identifying relevant studies, study selection, charting the data, summarizing and reporting the results, and a consultation exercise. Published literature will be searched on primary electronic databases such as the Association of Computing Machinery, Web of Science, MEDLINE, PsycINFO, CINAHL, and ScienceDirect. Common grey literature sources will complement the database search on the topic. A two-stage (title/abstract and full article) screening will be conducted to obtain eligible studies for final inclusion. A standardized data extraction tool will be used to extract variables such as the profile of the study population, technologies under investigation, stage of digital engagement, and the barriers and facilitators. Identified and eligible studies will be analyzed using a quantitative (ie, frequency analysis) and qualitative (ie, content analysis) approach suitable for comparing and evaluating literature to provide an evaluation of the current state of the older person’s digital engagement. Inclusion will be based on the Joanna Briggs Institute–recommended participant, concept, and context framework. Articles on older people (65 years and older), on digital technology engagement, and from a global context will be included in our review. Results: The results of this review are expected in July 2021. Conclusions: The findings from this review will identify the extent and nature of empirical evidence on how older people digitally engage and the associated barriers and facilitators. International Registered Report Identifier (IRRID): PRR1-10.2196/25616 %M 36260392 %R 10.2196/25616 %U https://www.researchprotocols.org/2021/7/e25616 %U https://doi.org/10.2196/25616 %U http://www.ncbi.nlm.nih.gov/pubmed/36260392 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 2 %P e26544 %T Patient-Reported Outcomes From Patients With Heart Failure Participating in the Future Patient Telerehabilitation Program: Data From the Intervention Arm of a Randomized Controlled Trial %A Skov Schacksen,Cathrine %A Dyrvig,Anne-Kirstine %A Henneberg,Nanna Celina %A Dam Gade,Josefine %A Spindler,Helle %A Refsgaard,Jens %A Hollingdal,Malene %A Dittman,Lars %A Dremstrup,Kim %A Dinesen,Birthe %+ Laboratory for Welfare Technology - Telehealth & Telerehabilitation, Sport Sciences - Performance and Technology, Department of Health Science and Technology, Aalborg University, Fredrik Bajers Vej 7, Bld A1, Aalborg East, 9220, Denmark, 45 61285904, cass@hst.aau.dk %K adherence %K cardiology %K cardiomyopathy %K compliance %K heart failure %K heart %K Kansas City Cardiomyopathy Questionnaire %K monitoring %K patient-reported outcome %K patients %K quality of life %K rehabilitation %K self-reporting %K telehealth %K telemonitoring %D 2021 %7 2.7.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: More than 37 million people worldwide have been diagnosed with heart failure, which is a growing burden on the health sector. Cardiac rehabilitation aims to improve patients’ recovery, functional capacity, psychosocial well-being, and health-related quality of life. However, cardiac rehabilitation programs have poor compliance and adherence. Telerehabilitation may be a solution to overcome some of these challenges to cardiac rehabilitation by making it more individualized. As part of the Future Patient Telerehabilitation program, a digital toolbox aimed at enabling patients with heart failure to monitor and evaluate their own current status has been developed and tested using data from a patient-reported outcome questionnaire that the patient filled in every alternate week for 1 year. Objective: The aim of this study is to evaluate the changes in quality of life and well-being among patients with heart failure, who are participants in the Future Patient Telerehabilitation program over the course of 1 year. Methods: In total, 140 patients were enrolled in the Future Patient Telerehabilitation program and randomized into either the telerehabilitation group (n=70) or the control group (n=70). Of the 70 patients in the telerehabilitation group, 56 (80.0%) answered the patient-reported outcome questionnaire and completed the program, and these 56 patients comprised the study population. The patient-reported outcomes consisted of three components: (1) questions regarding the patients’ sleep patterns assessed using the Spiegel Sleep Questionnaire; (2) measurements of physical limitations, symptoms, self-efficacy, social interaction, and quality of life assessed using the Kansas City Cardiomyopathy Questionnaire in 10 dimensions; and (3) 5 additional questions regarding psychological well-being that were developed by the research group. Results: The changes in scores during 1 year of the study were examined using 1-sample Wilcoxon signed-rank tests. There were significant differences in the scores for most of the slopes of the scores from the dimensions of the Kansas City Cardiomyopathy Questionnaire (P<.05). Conclusions: There was a significant increase in clinical and social well-being and quality of life during the 1-year period of participating in a telerehabilitation program. These results suggest that patient-reported outcome questionnaires may be used as a tool for patients in a telerehabilitation program that can both monitor and guide patients in mastering their own symptoms. Trial Registration: ClinicalTrials.gov NCT03388918; https://clinicaltrials.gov/ct2/show/NCT03388918 %M 34255642 %R 10.2196/26544 %U https://cardio.jmir.org/2021/2/e26544 %U https://doi.org/10.2196/26544 %U http://www.ncbi.nlm.nih.gov/pubmed/34255642 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e27218 %T Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial %A Kim,Meelim %A Yang,Jaeyeong %A Ahn,Woo-Young %A Choi,Hyung Jin %+ Department of Biomedical Sciences, Seoul National University College of Medicine, 28 Yungun-Dong, Chongno-Gu, Seoul, Republic of Korea, 82 27408204, hjchoi@snu.ac.kr %K digital phenotype %K clinical efficacy %K in-app engagement %K machine learning analysis %K mobile phone %D 2021 %7 24.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes. Objective: This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy. Methods: We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics. Results: A higher engagement rate was associated with higher weight loss at 8 weeks (r=−0.59; P<.001) and 24 weeks (r=−0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011). Conclusions: Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics. Trial Registration: ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306 %M 34184991 %R 10.2196/27218 %U https://www.jmir.org/2021/6/e27218/ %U https://doi.org/10.2196/27218 %U http://www.ncbi.nlm.nih.gov/pubmed/34184991 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e25470 %T Fidelity of Delivery and Contextual Factors Influencing Children’s Level of Engagement: Process Evaluation of the Online Remote Behavioral Intervention for Tics Trial %A Khan,Kareem %A Hollis,Chris %A Hall,Charlotte L %A Murray,Elizabeth %A Davies,E Bethan %A Andrén,Per %A Mataix-Cols,David %A Murphy,Tara %A Glazebrook,Cris %+ Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Jubilee Campus, University of Nottingham Innovation Park, Triumph Road, Nottingham, NG7 2TU, United Kingdom, 44 0115 823 1294, kareem.khan@nottingham.ac.uk %K process evaluation %K implementation fidelity %K Tourette syndrome %K chronic tic disorders %K online behavioral intervention %K mixed methods %K children and young people %D 2021 %7 21.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The Online Remote Behavioral Intervention for Tics (ORBIT) study was a multicenter randomized controlled trial of a complex intervention that consisted of a web-based behavioral intervention for children and young people with tic disorders. In the first part of a two-stage process evaluation, we conducted a mixed methods study exploring the reach, dose, and fidelity of the intervention and contextual factors influencing engagement. Objective: This study aims to explore the fidelity of delivery and contextual factors underpinning the ORBIT trial. Methods: Baseline study data and intervention usage metrics from participants in the intervention arm were used as quantitative implementation data (N=112). The experiences of being in the intervention were explored through semistructured interviews with children (n=20) and parent participants (n=20), therapists (n=4), and referring clinicians (n=6). A principal component analysis was used to create a comprehensive, composite measure of children and young people’s engagement with the intervention. Engagement factor scores reflected relative uptake as assessed by a range of usage indices, including chapters accessed, number of pages visited, and number of log-ins. The engagement factor score was used as the dependent variable in a multiple linear regression analysis with various contextual variables as independent variables to assess if there were any significant predictors of engagement. Results: The intervention was implemented with high fidelity, and participants deemed the intervention acceptable and satisfactory. The engagement was high, with child participants completing an average of 7.5 of 10 (SD 2.7) chapters, and 88.4% (99/112) of participants completed the minimum of the first four chapters—the predefined threshold effective dose. Compared with the total population of children with tic disorders, participants in the sample tended to have more educated parents and lived in more economically advantaged areas; however, socioeconomic factors were not related to engagement factor scores. Factors associated with higher engagement factor scores included participants enrolled at the London site versus the Nottingham site (P=.01), self-referred versus clinic referred (P=.04), higher parental engagement as evidenced by the number of parental chapters completed (n=111; ρ=0.73; P<.001), and more therapist time for parents (n=111; ρ=0.46; P<.001). A multiple linear regression indicated that parents’ chapter completion (β=.69; t110=10.18; P<.001) and therapist time for parents (β=.19; t110=2.95; P=.004) were the only significant independent predictors of child engagement factor scores. Conclusions: Overall, the intervention had high fidelity of delivery and was evaluated positively by participants, although reach may have been constrained by the nature of the randomized controlled trial. Parental engagement and therapist time for parents were strong predictors of intervention implementation, which has important implications for designing and implementing digital therapeutic interventions in child and adolescent mental health services. International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3974-3 %M 34152270 %R 10.2196/25470 %U https://www.jmir.org/2021/6/e25470 %U https://doi.org/10.2196/25470 %U http://www.ncbi.nlm.nih.gov/pubmed/34152270 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e22151 %T The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical Activity Program: Observational Study %A Rayward,Anna T %A Vandelanotte,Corneel %A Van Itallie,Anetta %A Duncan,Mitch J %+ School of Health, Medical and Applied Sciences, Central Queensland University, Bruce Highway, Rockhampton, 4700, Australia, 61 240553239, anna.rayward@newcastle.edu.au %K physical activity intervention %K activity trackers %K engagement %K Fitbit %K pedometer %K eHealth %K mobile phone %D 2021 %7 18.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Engagement is positively associated with the effectiveness of digital health interventions. It is unclear whether tracking devices that automatically synchronize data (eg, Fitbit) produce different engagement levels compared with manually entering data. Objective: This study examines how different step logging methods in the freely available 10,000 Steps physical activity program differ according to age and gender and are associated with program engagement. Methods: A subsample of users (n=22,142) of the free 10,000 Steps physical activity program were classified into one of the following user groups based on the step-logging method: Website Only (14,617/22,142, 66.01%), App Only (2100/22,142, 9.48%), Fitbit Only (1705/22,142, 7.7%), Web and App (2057/22,142, 9.29%), and Fitbit Combination (combination of web, app, and Fitbit; 1663/22,142, 7.51%). Generalized linear regression and binary logistic regression were used to examine differences between user groups’ engagement and participation parameters. The time to nonusage attrition was assessed using Cox proportional hazards regression. Results: App Only users were significantly younger and Fitbit user groups had higher proportions of women compared with other groups. The following outcomes were significant and relative to the Website Only group. The App Only group had fewer website sessions (odds ratio [OR] −6.9, 95% CI −7.6 to −6.2), whereas the Fitbit Only (OR 10.6, 95% CI 8.8-12.3), Web and App (OR 1.5, 95% CI 0.4-2.6), and Fitbit Combination (OR 8.0; 95% CI 6.2-9.7) groups had more sessions. The App Only (OR −0.7, 95% CI −0.9 to −0.4) and Fitbit Only (OR −0.5, 95% CI −0.7 to −0.2) groups spent fewer minutes on the website per session, whereas the Fitbit Combination group (OR 0.2, 95% CI 0.0-0.5) spent more minutes. All groups, except the Fitbit Combination group, viewed fewer website pages per session. The mean daily step count was lower for the App Only (OR −201.9, 95% CI −387.7 to −116.0) and Fitbit Only (OR −492.9, 95% CI −679.9 to −305.8) groups but higher for the Web and App group (OR 258.0, 95% CI 76.9-439.2). The Fitbit Only (OR 5.0, 95% CI 3.4-6.6), Web and App (OR 7.2, 95% CI 5.9-8.6), and Fitbit Combination (OR 15.6, 95% CI 13.7-17.5) groups logged a greater number of step entries. The App Only group was less likely (OR 0.65, 95% CI 0.46-0.94) and other groups were more likely to participate in Challenges. The mean time to nonusage attrition was 35 (SD 26) days and was lower than average in the Website Only and App Only groups and higher than average in the Web and App and Fitbit Combination groups. Conclusions: Using a Fitbit in combination with the 10,000 Steps app or website enhanced engagement with a real-world physical activity program. Integrating tracking devices that synchronize data automatically into real-world physical activity interventions is one strategy for improving engagement. %M 34142966 %R 10.2196/22151 %U https://www.jmir.org/2021/6/e22151 %U https://doi.org/10.2196/22151 %U http://www.ncbi.nlm.nih.gov/pubmed/34142966 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e26749 %T Data Missing Not at Random in Mobile Health Research: Assessment of the Problem and a Case for Sensitivity Analyses %A Goldberg,Simon B %A Bolt,Daniel M %A Davidson,Richard J %+ Department of Counseling Psychology, University of Wisconsin - Madison, 335 Education Building, 1000 Bascom Mall, University of Wisconsin-Madison, Madison, WI, 53706, United States, 1 6082658986, sbgoldberg@wisc.edu %K missing data %K randomized controlled trial %K differential attrition %K sensitivity analysis %K statistical methodology %K mobile phone %D 2021 %7 15.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Missing data are common in mobile health (mHealth) research. There has been little systematic investigation of how missingness is handled statistically in mHealth randomized controlled trials (RCTs). Although some missing data patterns (ie, missing at random [MAR]) may be adequately addressed using modern missing data methods such as multiple imputation and maximum likelihood techniques, these methods do not address bias when data are missing not at random (MNAR). It is typically not possible to determine whether the missing data are MAR. However, higher attrition in active (ie, intervention) versus passive (ie, waitlist or no treatment) conditions in mHealth RCTs raise a strong likelihood of MNAR, such as if active participants who benefit less from the intervention are more likely to drop out. Objective: This study aims to systematically evaluate differential attrition and methods used for handling missingness in a sample of mHealth RCTs comparing active and passive control conditions. We also aim to illustrate a modern model-based sensitivity analysis and a simpler fixed-value replacement approach that can be used to evaluate the influence of MNAR. Methods: We reanalyzed attrition rates and predictors of differential attrition in a sample of 36 mHealth RCTs drawn from a recent meta-analysis of smartphone-based mental health interventions. We systematically evaluated the design features related to missingness and its handling. Data from a recent mHealth RCT were used to illustrate 2 sensitivity analysis approaches (pattern-mixture model and fixed-value replacement approach). Results: Attrition in active conditions was, on average, roughly twice that of passive controls. Differential attrition was higher in larger studies and was associated with the use of MAR-based multiple imputation or maximum likelihood methods. Half of the studies (18/36, 50%) used these modern missing data techniques. None of the 36 mHealth RCTs reviewed conducted a sensitivity analysis to evaluate the possible consequences of data MNAR. A pattern-mixture model and fixed-value replacement sensitivity analysis approaches were introduced. Results from a recent mHealth RCT were shown to be robust to missing data, reflecting worse outcomes in missing versus nonmissing scores in some but not all scenarios. A review of such scenarios helps to qualify the observations of significant treatment effects. Conclusions: MNAR data because of differential attrition are likely in mHealth RCTs using passive controls. Sensitivity analyses are recommended to allow researchers to assess the potential impact of MNAR on trial results. %M 34128810 %R 10.2196/26749 %U https://www.jmir.org/2021/6/e26749 %U https://doi.org/10.2196/26749 %U http://www.ncbi.nlm.nih.gov/pubmed/34128810 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 6 %P e27496 %T Wireless Home Blood Pressure Monitoring System With Automatic Outcome-Based Feedback and Financial Incentives to Improve Blood Pressure in People With Hypertension: Protocol for a Randomized Controlled Trial %A Bilger,Marcel %A Koong,Agnes Ying Leng %A Phoon,Ian Kwong Yun %A Tan,Ngiap Chuan %A Bahadin,Juliana %A Bairavi,Joann %A Batcagan-Abueg,Ada Portia M %A Finkelstein,Eric A %+ Health Economics and Policy, Vienna University of Economics and Business, Welthandelsplatz 1, Building D4, Room: Third Floor / D4.3.280, Vienna, Austria, 1020, Austria, 43 1 31336 5861, marcel.bilger@wu.ac.at %K telemedicine %K home blood pressure monitoring %K behavior change %K hypertension %K financial incentive %K medication adherence %K remote titration %D 2021 %7 9.6.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Hypertension is prevalent in Singapore and is a major risk factor for cardiovascular morbidity and mortality and increased health care costs. Strategies to lower blood pressure include lifestyle modifications and home blood pressure monitoring. Nonetheless, adherence to home blood pressure monitoring remains low. This protocol details an algorithm for remote management of primary care patients with hypertension. Objective: The objective of this study was to determine whether wireless home blood pressure monitoring with or without financial incentives is more effective at reducing systolic blood pressure than nonwireless home blood pressure monitoring (usual care). Methods: This study was designed as a randomized controlled open-label superiority study. A sample size of 224 was required to detect differences of 10 mmHg in average systolic blood pressure. Participants were to be randomized, in the ratio of 2:3:3, into 1 of 3 parallel study arms :(1) usual care, (2) wireless home blood pressure monitoring, and (3) wireless home blood pressure monitoring with financial incentives. The primary outcome was the mean change in systolic blood pressure at month 6. The secondary outcomes were the mean reduction in diastolic blood pressure, cost of financial incentives, time taken for the intervention, adherence to home blood pressure monitoring, effectiveness of the framing of financial incentives in decreasing nonadherence to blood pressure self-monitoring and the adherence to antihypertensive medication at month 6. Results: This study was approved by SingHealth Centralised Institutional Review Board and registered. Between January 24, 2018 and July 10, 2018, 42 participants (18.75% of the required sample size) were enrolled, and 33 participants completed the month 6 assessment by January 31, 2019. Conclusions: Due to unforeseen events, the study was stopped prematurely; therefore, no results are available. Depending on the blood pressure information received from the patients, the algorithm can trigger immediate blood pressure advice (eg, Accident and Emergency department visit advice for extremely high blood pressure), weekly feedback on blood pressure monitoring, medication titration, or skipping of routine follow-ups. The inclusion of financial incentives framed as health capital provides a novel idea on how to promote adherence to remote monitoring, and ultimately, improve chronic disease management. Trial Registration: ClinicalTrials.gov NCT 03368417; https://clinicaltrials.gov/ct2/show/NCT03368417 International Registered Report Identifier (IRRID): DERR1-10.2196/27496 %M 34106085 %R 10.2196/27496 %U https://www.researchprotocols.org/2021/6/e27496 %U https://doi.org/10.2196/27496 %U http://www.ncbi.nlm.nih.gov/pubmed/34106085 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 6 %P e23986 %T Factors Predicting Trial Engagement, Treatment Satisfaction, and Health-Related Quality of Life During a Web-Based Treatment and Social Networking Trial for Binge Drinking and Depression in Young Adults: Secondary Analysis of a Randomized Controlled Trial %A Sanatkar,Samineh %A Heinsch,Milena %A Baldwin,Peter Andrew %A Rubin,Mark %A Geddes,Jenny %A Hunt,Sally %A Baker,Amanda L %A Woodcock,Kathryn %A Lewin,Terry J %A Brady,Kathleen %A Deady,Mark %A Thornton,Louise %A Teesson,Maree %A Kay-Lambkin,Frances %+ Centre for Brain and Mental Health Research, School of Medicine and Public Health, The University of Newcastle, University Drive, Callaghan, 2308, Australia, 61 02 9065 9179, samineh.sanatkar@uon.edu.au %K digital mental health %K personality %K negative affect %K study engagement %K life quality %D 2021 %7 7.6.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Mental health and alcohol use problems are among the most common causes of disease burden in young Australians, frequently co-occur (comorbidity), and lead to significant lifetime burden. However, comorbidities remain significantly underdetected and undertreated in health settings. Digital mental health tools designed to identify at-risk individuals, encourage help-seeking, or deliver treatment for comorbidity have the potential to address this service gap. However, despite a strong body of evidence that digital mental health programs provide an effective treatment option for a range of mental health and alcohol use problems in young adults, research shows that uptake rates can be low. Thus, it is important to understand the factors that influence treatment satisfaction and quality-of-life outcomes for young adults who access e–mental health interventions for comorbidity. Objective: In this study, we seek to understand the factors that influence treatment satisfaction and quality-of-life outcomes for young adults who access e–mental health interventions for comorbid alcohol and mood disorders. The aim is to determine the importance of personality (ie, Big Five personality traits and intervention attitudes), affective factors (ie, depression, anxiety, and stress levels), and baseline alcohol consumption in predicting intervention trial engagement at sign-up, satisfaction with the online tool, and quality of life at the end of the iTreAD (Internet Treatment for Alcohol and Depression) trial. Methods: Australian adults (N=411) aged between 18 and 30 years who screened positive for depression and alcohol use problems signed up for the iTreAD project between August 2014 and October 2015. During registration, participants provided information about their personality, current affective state, alcohol use, treatment expectations, and basic demographic information. Subsequent follow-up surveys were used to gauge the ongoing trial engagement. The last follow-up questionnaire, completed at 64 weeks, assessed participants’ satisfaction with web-based treatment and quality-of-life outcomes. Results: Multiple linear regression analyses were used to assess the relative influence of predictor variables on trial engagement, treatment satisfaction, and quality-of-life outcomes. The analyses revealed that the overall predictive effects of personality and affective factors were 20% or lower. Neuroticism constituted a unique predictor of engagement with the iTreAD study in that neuroticism facilitated the return of web-based self-assessments during the study. The return of incentivized follow-up assessments predicted treatment satisfaction, and state-based depression predicted variance in quality-of-life reports at study completion. Conclusions: Our findings suggest that traditional predictors of engagement observed in face-to-face research may not be easily transferable to digital health interventions, particularly those aimed at comorbid mental health concerns and alcohol misuse among young adults. More research is needed to identify what determines engagement in this population to optimally design and execute digital intervention studies with multiple treatment aims. Trial Registration: Australian New Zealand Clinical Trials Registry (ACTRN): 12614000310662; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=365137&isReview=true. International Registered Report Identifier (IRRID): RR2-10.1186/s12889-015-2365-2 %M 34096873 %R 10.2196/23986 %U https://mental.jmir.org/2021/6/e23986 %U https://doi.org/10.2196/23986 %U http://www.ncbi.nlm.nih.gov/pubmed/34096873 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e26421 %T Influence of Baseline User Characteristics and Early Use Patterns (24-Hour) on Long-Term Adherence and Effectiveness of a Web-Based Weight Loss Randomized Controlled Trial: Latent Profile Analysis %A Andrade,Andre Q %A Beleigoli,Alline %A Diniz,Maria De Fatima %A Ribeiro,Antonio Luiz %+ Flinders Digital Health Research Centre, Flinders University, Tonsley Boulevard, Tonsley, Adelaide, , Australia, 61 08 2013303, alline.beleigoli@flinders.edu.au %K obesity %K overweight %K web platform %K digital health %K engagement %K latent profile analysis %K online interventions %K use data %K weight loss %K weight loss platform %D 2021 %7 3.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Low adherence to real-world online weight loss interventions reduces long-term efficacy. Baseline characteristics and use patterns are determinants of long-term adherence, but we lack cohesive models to guide how to adapt interventions to users’ needs. We also lack information whether very early use patterns (24 hours) help describe users and predict interventions they would benefit from. Objective: We aim to understand the impact of users’ baseline characteristics and early (initial 24 hours) use patterns of a web platform for weight loss on user adherence and weight loss in the long term (24 weeks). Methods: We analyzed data from the POEmaS randomized controlled trial, a study that compared the effectiveness of a weight loss platform with or without coaching and a control approach. Data included baseline behavior and use logs from the initial 24 hours after platform access. Latent profile analysis (LPA) was used to identify classes, and Kruskal-Wallis was used to test whether class membership was associated with long-term (24 weeks) adherence and weight loss. Results: Among 828 participants assigned to intervention arms, 3 classes were identified through LPA: class 1 (better baseline health habits and high 24-hour platform use); class 2 (better than average health habits, but low 24-hour platform use); class 3 (worse baseline health habits and low 24-hour platform use). Class membership was associated with long-term adherence (P<.001), and class 3 members had the lowest adherence. Weight loss was not associated with class membership (P=.49), regardless of the intervention arm (platform only or platform + coach). However, class 2 users assigned to platform + coach lost more weight than those assigned to platform only (P=.02). Conclusions: Baseline questionnaires and use data from the first 24 hours after log-in allowed distinguishing classes, which were associated with long-term adherence. This suggests that this classification might be a useful guide to improve adherence and assign interventions to individual users. Trial Registration: ClinicalTrials.gov NCT03435445; https://clinicaltrials.gov/ct2/show/NCT03435445 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5882-y %M 34081012 %R 10.2196/26421 %U https://www.jmir.org/2021/6/e26421 %U https://doi.org/10.2196/26421 %U http://www.ncbi.nlm.nih.gov/pubmed/34081012 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 6 %P e19941 %T Motivating Adherence to Exercise Plans Through a Personalized Mobile Health App: Enhanced Action Design Research Approach %A Sun,Ruo-Ting %A Han,Wencui %A Chang,Hsin-Lu %A Shaw,Michael J %+ Department of Management Information Systems, National Chengchi University, 64, Sec 2, Chinan Rd,, Taipei, 116, Taiwan, 886 2 29393091 ext 81214, hlchang@nccu.edu.tw %K adherence %K mobile health %K motivation %K personality %K MBTI %K action design research %K mobile phone %D 2021 %7 2.6.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Physical inactivity is a global issue that affects people’s health and productivity. With the advancement of mobile technologies, many apps have been developed to facilitate health self-management. However, few studies have examined the effectiveness of these mobile health (mHealth) apps in motivating exercise adherence. Objective: This study aims to demonstrate the enhanced action design research (ADR) process and improve the design of mHealth apps for exercise self-management. Specifically, we investigate whether sending motivational messages improves adherence to exercise plans, whether the motivational effect is affected by personality, the impact of message type and repetition, and the process of involving a field experiment in the design process and learning new design principles from the results. Methods: This formative research was conducted by proposing an enhanced ADR process. We incorporated a field experiment into the process to iteratively refine and evaluate the design until it converges into a final mHealth app. We used the Apple ResearchKit to develop the mHealth app and promoted it via trainers at their gyms. We targeted users who used the app for at least two months. Participants were randomly assigned to 1 of the 12 groups in a 2×3×2 factorial design and remained blinded to the assigned intervention. The groups were defined based on personality type (thinking or feeling), message type (emotional, logical, or none), and repetition (none or once). Participants with different personality types received tailored and repeated messages. Finally, we used the self-reported completion rate to measure participants’ adherence level to exercise plans. By analyzing users’ usage patterns, we could verify, correct, and enhance the mHealth app design principles. Results: In total, 160 users downloaded the app, and 89 active participants remained during the 2-month period. The results suggest a significant main effect of personality type and repetition and a significant interaction effect between personality type and repetition. The adherence rate of people with feeling personality types was 18.15% higher than that of people with thinking types. Emotional messages were more effective than logical messages in motivating exercise adherence. Although people received repeated messages, they were more likely to adhere to exercise plans. With repeated reminders, the adherence rates of people with thinking personality types were significantly improved by 27.34% (P<.001). Conclusions: This study contributes to the literature on mHealth apps. By incorporating a field experiment into the ADR process, we demonstrate the benefit of combining design science and field experiments. This study also contributes to the research on mHealth apps. The principles learned from this study can be applied to improve the effectiveness of mHealth apps. The app design can be considered a foundation for the development of more advanced apps for specific diseases, such as diabetes and asthma, in future research. %M 34076580 %R 10.2196/19941 %U https://mhealth.jmir.org/2021/6/e19941 %U https://doi.org/10.2196/19941 %U http://www.ncbi.nlm.nih.gov/pubmed/34076580 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 5 %P e28007 %T The Effect of Training on Participant Adherence With a Reporting Time Frame for Momentary Subjective Experiences in Ecological Momentary Assessment: Cognitive Interview Study %A Wen,Cheng K Fred %A Junghaenel,Doerte U %A Newman,David B %A Schneider,Stefan %A Mendez,Marilyn %A Goldstein,Sarah E %A Velasco,Sarah %A Smyth,Joshua M %A Stone,Arthur A %+ Dornsife Center for Self-Report Science, University of Southern California, 635 Downey Way, Verna and Peter Dauterive Hall 405H, Los Angeles, CA, 90089, United States, 1 2138212894, chengkuw@usc.edu %K ecological momentary assessment %K EMA %K cognitive interview %K participant training %K reporting period %D 2021 %7 26.5.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Ecological momentary assessment (EMA) has the potential to minimize recall bias by having people report on their experiences in the moment (momentary model) or over short periods (coverage model). This potential hinges on the assumption that participants provide their ratings based on the reporting time frame instructions prescribed in the EMA items. However, it is unclear what time frames participants actually use when answering the EMA questions and whether participant training improves participants’ adherence to the reporting instructions. Objective: This study aims to investigate the reporting time frames participants used when answering EMA questions and whether participant training improves participants’ adherence to the EMA reporting timeframe instructions. Methods: Telephone-based cognitive interviews were used to investigate the research questions. In a 2×2 factorial design, participants (n=100) were assigned to receive either basic or enhanced EMA training and randomized to rate their experiences using a momentary (at the moment you were called) or a coverage (since the last phone call) model. Participants received five calls over the course of a day to provide ratings; after each rating, participants were immediately interviewed about the time frame they used to answer the EMA questions. A total of 2 raters independently coded the momentary interview responses into time frame categories (Cohen κ=0.64, 95% CI 0.55-0.73). Results: The results from the momentary conditions showed that most of the calls referred to the period during the call (57/199, 28.6%) or just before the call (98/199, 49.2%) to provide ratings; the remainder were from longer reporting periods. Multinomial logistic regression results indicated a significant training effect (χ21=16.6; P<.001) in which the enhanced training condition yielded more reports within the intended reporting time frames for momentary EMA reports. Cognitive interview data from the coverage model did not lend themselves to reliable coding and were not analyzed. Conclusions: The results of this study provide the first evidence about adherence to EMA instructions to reporting periods and that enhanced participant training improves adherence to the time frame specified in momentary EMA studies. %M 34037524 %R 10.2196/28007 %U https://formative.jmir.org/2021/5/e28007 %U https://doi.org/10.2196/28007 %U http://www.ncbi.nlm.nih.gov/pubmed/34037524 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 5 %P e23499 %T Maximizing Participant Engagement, Participation, and Retention in Cohort Studies Using Digital Methods: Rapid Review to Inform the Next Generation of Very Large Birth Cohorts %A Nkyekyer,Joanna %A Clifford,Susan A %A Mensah,Fiona K %A Wang,Yichao %A Chiu,Lauren %A Wake,Melissa %+ Murdoch Children’s Research Institute, 50 Flemington Road, Parkville, VIC 3052, Australia, 61 3 9345 5937, melissa.wake@mcri.edu.au %K cohort studies %K communication modes %K digital study %K mobile phone %K participant engagement %K research methodology %K retention %K systematic reviews %D 2021 %7 14.5.2021 %9 Review %J J Med Internet Res %G English %X Background: Many current research needs can only be addressed using very large cohorts. In such studies, traditional one-on-one phone, face-to-face, or paper-based engagement may not be feasible. The only realistic mechanism for maintaining engagement and participation at this scale is via digital methods. Given the substantial investment being made into very large birth cohort studies, evidence for optimal methods of participant engagement, participation, and retention over sustained periods without in-person contact from researchers is paramount. Objective: This study aims to provide an overview of systematic reviews and meta-analyses evaluating alternative strategies for maximizing participant engagement and retention rates in large-scale studies using digital methods. Methods: We used a rapid review method by searching PubMed and Ovid MEDLINE databases from January 2012 to December 2019. Studies evaluating at least 1 e-engagement, participation, or retention strategy were eligible. Articles were screened for relevance based on preset inclusion and exclusion criteria. The methodological quality of the included reviews was assessed using the AMSTAR-2 (Assessing the Methodological Quality of Systematic Reviews 2) measurement tool, and a narrative synthesis of the data was conducted. Results: The literature search yielded 19 eligible reviews. Overall, 63% (n=12) of these reviews reported on the effectiveness of e-engagement or participation promotion strategies. These evaluations were generally not conducted within very large observational digital cohorts. Most of the contributing reviews included multipurpose cohort studies (with both observational and interventional elements) conducted in clinical and research settings. Email or SMS text message reminders, SMS text messages or voice notifications, and incentives were the most commonly used design features to engage and retain participants. For parental outcomes, engagement-facilitation interventions influenced uptake and behavior change, including video feedback, goal setting, and intensive human facilitation and support. Participant-stated preferences for content included new knowledge, reminders, solutions, and suggestions about health issues presented in a clear, short, and personalized way. Perinatal and postpartum women valued self-monitoring and personalized feedback. Digital reminders and multiple SMS text messages were specific strategies that were found to increase adherence to medication and clinic attendance, respectively. Conclusions: This review adds to the growing literature evaluating methods to optimize engagement and participation that may apply to large-scale studies using digital methods; it is promising that most e-engagement and participation promotion strategies appear to be effective. However, these reviews canvassed relatively few strategies, suggesting that few alternative strategies have been experimentally evaluated. The reviews also revealed a dearth of experimental evidence generated within very large observational digital cohort studies, which may reflect the small number of such studies worldwide. Thus, very large studies may need to proactively build in experimental opportunities to test engagement and retention approaches to enhance the success of their own and other large digital contact studies. %M 33988509 %R 10.2196/23499 %U https://www.jmir.org/2021/5/e23499 %U https://doi.org/10.2196/23499 %U http://www.ncbi.nlm.nih.gov/pubmed/33988509 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 5 %P e21831 %T Influence Mechanism of the Affordances of Chronic Disease Management Apps on Continuance Intention: Questionnaire Study %A Liu,Yongmei %A Jiang,Fei %A Lin,Peiyang %+ Business School of Central South University, No 932, Lushan South Road, Yuelu District, Hunan Province, Changsha City, China, 86 15116112197, linpeiyangcn@163.com %K health empowerment %K perceived affordances %K uses and gratifications %K S-O-R framework %K continuance intention %K chronic disease management app %D 2021 %7 13.5.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health apps are becoming increasingly popular, and they provide opportunities for effective health management. Existing chronic disease management (CDM) apps cannot meet users’ practical and urgent needs, and user adhesion is poor. Few studies, however, have investigated the factors that influence the continuance intention of CDM app users. Objective: Starting from the affordances of CDM apps, this study aimed to analyze how such apps can influence continuance intention through the role of health empowerment. Methods: Adopting a stimulus-organism-response framework, an antecedent model was established for continuance intention from the perspective of perceived affordances, uses and gratifications theory, and health empowerment. Perceived affordances were used as the “stimulus,” users’ gratifications and health empowerment were used as the “organism,” and continuance intention was used as the “response.” Data were collected online through a well-known questionnaire survey platform in China, and 323 valid questionnaires were obtained. The theoretical model was tested using structural equation modeling. Results: Perceived connection affordances were found to have significant positive effects on social interactivity gratification (t717=6.201, P<.001) and informativeness gratification (t717=5.068, P<.001). Perceived utilitarian affordances had significant positive effects on informativeness gratification (t717=7.029, P<.001), technology gratification (t717=8.404, P<.001), and function gratification (t717=9.812, P<.001). Perceived hedonic affordances had significant positive effects on function gratification (t717=5.305, P<.001) and enjoyment gratification (t717=13.768, P<.001). Five gratifications (t717=2.767, P=.005; t717=4.632, P<.001; t717=7.608, P<.001; t717=2.496, P=.012; t717=5.088, P<.001) had significant positive effects on health empowerment. Social interactivity gratification, informativeness gratification, and function gratification had significant positive effects on continuance intention. Technology gratification and enjoyment gratification did not have a significant effect on continuance intention. Health empowerment had a significant positive effect on continuance intention. Health empowerment and gratifications play mediating roles in the influence of affordances on continuance intention. Conclusions: Health empowerment and gratifications of users’ needs are effective ways to promote continuance intention. The gratifications of users’ needs can realize health empowerment and then inspire continuance intention. Affordances are key antecedents that affect gratifications of users’ needs, health empowerment, and continuance intention. %M 33983126 %R 10.2196/21831 %U https://mhealth.jmir.org/2021/5/e21831 %U https://doi.org/10.2196/21831 %U http://www.ncbi.nlm.nih.gov/pubmed/33983126 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 5 %P e13391 %T Predictors of Walking App Users With Comparison of Current Users, Previous Users, and Informed Nonusers in a Sample of Dutch Adults: Questionnaire Study %A De Bruijn,Gert-Jan %A Dallinga,Joan Martine %A Deutekom,Marije %+ Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Nieuwe Achtergracht 166, Amsterdam, 1018 WV, Netherlands, 31 205252636, g.j.debruijn@uva.nl %K technology %K walking %K health %K adult %K survey %K questionnaires %D 2021 %7 12.5.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The last decade has seen a substantial increase in the use of mobile health apps and research into the effects of those apps on health and health behaviors. In parallel, research has aimed at identifying population subgroups that are more likely to use those health apps. Current evidence is limited by two issues. First, research has focused on broad health apps, and little is known about app usage for a specific health behavior. Second, research has focused on comparing current users and current nonusers, without considering subgroups of nonusers. Objective: We aimed to provide profile distributions of current users, previous users, and informed nonusers, and to identify predictor variables relevant for profile classification. Methods: Data were available from 1683 people who participated in a Dutch walking event in Amsterdam that was held in September 2017. They provided information on demographics, self-reported walking behavior, and walking app usage, as well as items from User Acceptance of Information Technology, in an online survey. Data were analyzed using discriminant function analysis and multinomial logistic regression analysis. Results: Most participants were current walking app users (899/1683, 53.4%), while fewer participants were informed nonusers (663/1683, 39.4%) and very few were previous walking app users (121/1683, 7.2%). Current walking app users were more likely to report walking at least 5 days per week and for at least 30 minutes per bout (odds ratio [OR] 1.44, 95% CI 1.11-1.85; P=.005) and more likely to be overweight (OR 1.72, 95% CI 1.24-2.37; P=.001) or obese (OR 1.49, 95% CI 1.08-2.08; P=.005) as compared with informed nonusers. Further, current walking app users perceived their walking apps to be less boring, easy to use and retrieve information, and more helpful to achieve their goals. Effect sizes ranged from 0.10 (95% CI 0.08-0.30) to 1.58 (95% CI 1.47-1.70). Conclusions: The distributions for walking app usage appeared different from the distributions for more general health app usage. Further, the inclusion of two specific subgroups of nonusers (previous users and informed nonusers) provides important information for health practitioners and app developers to stimulate continued walking app usage, including making information in those apps easy to understand and making it easy to obtain information from the apps, as well as preventing apps from becoming boring and difficult to use for goal attainment. %M 33978595 %R 10.2196/13391 %U https://mhealth.jmir.org/2021/5/e13391 %U https://doi.org/10.2196/13391 %U http://www.ncbi.nlm.nih.gov/pubmed/33978595 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 5 %P e24520 %T Engagement With a Health Information Technology–Augmented Self-Management Support Program in a Population With Limited English Proficiency: Observational Study %A Machen,Leah %A Handley,Margaret A %A Powe,Neil %A Tuot,Delphine %+ University of California, San Francisco, 1001 Potrero Ave, San Francisco, CA, 94110, United States, 1 415 206 3784, Delphine.tuot@ucsf.edu %K automated telehealth intervention %K limited English proficiency %K mHealth %K language problems %K telehealth %K SMS %K text message %D 2021 %7 11.5.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Limited English proficiency (LEP) is an important driver of health disparities. Many successful patient-level interventions to prevent chronic disease progression and complications have used automated telephone self-management support, which relies on patient activation and communication to achieve improved health outcomes. It is not clear whether these interventions are similarly applicable to patients with LEP compared to patients with English proficiency. Objective: The objectives of this study were as follows: (1) To examine the impact of LEP on patient engagement (primary outcome) with a 12-month language-concordant self-management program that included automated telephone self-management support, designed for patients with chronic kidney disease (CKD). (2) To assess the impact of LEP on change in systolic blood pressure (SBP) and albuminuria (secondary outcomes) resulting from the self-management program. Methods: This was a secondary analysis of the Kidney Awareness Registry and Education (KARE) pilot trial (NCT01530958) which was funded by the National Institutes of Health in August 2011, approved by the University of California Institutional Review Board in October 2011 (No. 11-07399), and executed between 2013 and 2015. Multivariable logistic and linear models were used to examine various facets of patient engagement with the CKD self-management support program by LEP status. Patient engagement was defined by patient’s use of educational materials, completion of a health coaching action plan, and degree of participation with automated telephone self-management support. Changes in SBP and albuminuria at 12 months by LEP status were determined using multivariable linear mixed models. Results: Of 137 study participants, 53 (38.7%) reported LEP, of which 45 (85%) were Spanish speaking and 8 (15%) Cantonese speaking. While patients with LEP and English proficiency similarly used the program’s educational materials (85% [17/20] vs 88% [30/34], P=.69) and completed an action plan (81% [22/27] vs 74% [35/47], P=.49), those with LEP engaged more with the automated telephone self-management support component. Average call completion was 66% among patients with LEP compared with 57% among those with English proficiency; patients with LEP requested more health coach telephone calls (P=.08) and had a significantly longer average automated call duration (3.3 [SD 1.4] min vs 2.2 [1.1 min], P<.001), indicating higher patient engagement. Patients with LEP randomized to self-management support had a larger, though nonstatistically significant (P=.74), change in SBP (–4.5 mmHg; 95% CI –9.4 to 0.3) and albuminuria (–72.4 mg/dL; 95% CI –208.9 to 64.1) compared with patients with English proficiency randomized to self-management support (–2.1 mmHg; 95% CI –8.6 to 4.3 and –11.1 mg/dL; 95% CI –166.9 to 144.7). Conclusions: Patients with LEP with CKD were equally or more engaged with a language-concordant, culturally appropriate telehealth intervention compared with their English-speaking counterparts. Augmented telehealth may be useful in mitigating communication barriers among patients with LEP. Trial Registration: ClinicalTrials.gov NCT01530958; https://clinicaltrials.gov/ct2/show/NCT01530958 %M 33973868 %R 10.2196/24520 %U https://mhealth.jmir.org/2021/5/e24520 %U https://doi.org/10.2196/24520 %U http://www.ncbi.nlm.nih.gov/pubmed/33973868 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 4 %P e26699 %T Long-term Effectiveness of mHealth Physical Activity Interventions: Systematic Review and Meta-analysis of Randomized Controlled Trials %A Mönninghoff,Annette %A Kramer,Jan Niklas %A Hess,Alexander Jan %A Ismailova,Kamila %A Teepe,Gisbert W %A Tudor Car,Lorainne %A Müller-Riemenschneider,Falk %A Kowatsch,Tobias %+ Institute for Customer Insight, University of St. Gallen, Bahnhofstrasse 8, St. Gallen, 9000, Switzerland, 41 76 229 3150, Annette.Moenninghoff@unisg.ch %K mHealth %K physical activity %K systematic review %K meta-analysis %K mobile phone %D 2021 %7 30.4.2021 %9 Review %J J Med Internet Res %G English %X Background: Mobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood. Objective: The primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators. Methods: We performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool. Results: Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence. Conclusions: mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects. %M 33811021 %R 10.2196/26699 %U https://www.jmir.org/2021/4/e26699 %U https://doi.org/10.2196/26699 %U http://www.ncbi.nlm.nih.gov/pubmed/33811021 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 4 %P e25299 %T Conducting Internet-Based Visits for Onboarding Populations With Limited Digital Literacy to an mHealth Intervention: Development of a Patient-Centered Approach %A Hernandez-Ramos,Rosa %A Aguilera,Adrian %A Garcia,Faviola %A Miramontes-Gomez,Jose %A Pathak,Laura Elizabeth %A Figueroa,Caroline Astrid %A Lyles,Courtney Rees %+ Division of General Internal Medicine, Zuckerberg San Francisco General Hospital, University of California, San Francisco, 1001 Potrero Ave, Bldg 10, Ward 13, Box 1364, San Francisco, CA, 94110, United States, 1 628 206 6483, courtney.Lyles@ucsf.edu %K digital literacy %K digital divide %K underserved %K patient-centered %K digital health %K mhealth %K intervention %K telehealth %K COVID-19 %D 2021 %7 29.4.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The COVID-19 pandemic has propelled patient-facing research to shift to digital and telehealth strategies. If these strategies are not adapted for minority patients of lower socioeconomic status, health inequality will further increase. Patient-centered models of care can successfully improve access and experience for minority patients. Objective: This study aims to present the development process and preliminary acceptability of altering in-person onboarding procedures into internet-based, remote procedures for a mobile health (mHealth) intervention in a population with limited digital literacy. Methods: We actively recruited safety-net patients (English- and Spanish-speaking adults with diabetes and depression who were receiving care at a public health care delivery system in San Francisco, United States) into a randomized controlled trial of text messaging support for physical activity. Because of the COVID-19 pandemic, we modified the in-person recruitment and onboarding procedures to internet-based, remote processes with human support. We conducted a preliminary evaluation of how the composition of the recruited cohort might have changed from the pre–COVID-19 period to the COVID-19 enrollment period. First, we analyzed the digital profiles of patients (n=32) who had participated in previous in-person onboarding sessions prior to the COVID-19 pandemic. Next, we documented all changes made to our onboarding processes to account for remote recruitment, especially those needed to support patients who were not very familiar with downloading apps onto their mobile phones on their own. Finally, we used the new study procedures to recruit patients (n=11) during the COVID-19 social distancing period. These patients were also asked about their experience enrolling into a fully digitized mHealth intervention. Results: Recruitment across both pre–COVID-19 and COVID-19 periods (N=43) demonstrated relatively high rates of smartphone ownership but lower self-reported digital literacy, with 32.6% (14/43) of all patients reporting they needed help with using their smartphone and installing apps. Significant changes were made to the onboarding procedures, including facilitating app download via Zoom video call and/or a standard phone call and implementing brief, one-on-one staff-patient interactions to provide technical assistance personalized to each patient’s digital literacy skills. Comparing recruitment during pre–COVID-19 and COVID-19 periods, the proportion of patients with digital literacy barriers reduced from 34.4% (11/32) in the pre–COVID-19 cohort to 27.3% (3/11) in the COVID-19 cohort. Differences in digital literacy scores between both cohorts were not significant (P=.49). Conclusions: Patients of lower socioeconomic status have high interest in using digital platforms to manage their health, but they may require additional upfront human support to gain access. One-on-one staff-patient partnerships allowed us to provide unique technical assistance personalized to each patient’s digital literacy skills, with simple strategies to troubleshoot patient barriers upfront. These additional remote onboarding strategies can mitigate but not eliminate digital barriers for patients without extensive technology experience. Trial Registration: Clinicaltrials.gov NCT0349025, https://clinicaltrials.gov/ct2/show/NCT03490253 %M 33872184 %R 10.2196/25299 %U https://formative.jmir.org/2021/4/e25299 %U https://doi.org/10.2196/25299 %U http://www.ncbi.nlm.nih.gov/pubmed/33872184 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 4 %P e25358 %T Participant Perceptions of Facilitators and Barriers to Adherence in a Digital Mental Health Intervention for a Nonclinical Cohort: Content Analysis %A Renfrew,Melanie Elise %A Morton,Darren Peter %A Northcote,Maria %A Morton,Jason Kyle %A Hinze,Jason Scott %A Przybylko,Geraldine %+ Lifestyle Medicine and Health Research Centre, Avondale University College, 582 Freemans Drive, Cooranbong, NSW, 2265, Australia, 61 405445151, melanie.renfrew@avondale.edu.au %K web-based mental health %K health promotion %K eHealth %K adherence %K participant perceptions %K mobile phone %D 2021 %7 14.4.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Digital mental health promotion interventions (MHPIs) present a scalable opportunity to attenuate the risk of mental health distress among nonclinical cohorts. However, adherence is frequently suboptimal, and little is known about participants’ perspectives concerning facilitators and barriers to adherence in community-based settings. Objective: This study aimed to examine participants’ perceptions of facilitators and barriers to adherence in a web- and mobile app–based MHPI for a nonclinical cohort. Methods: This qualitative study used inductive, reflexive thematic analysis to explore free-text responses in a postintervention evaluation of a 10-week digital MHPI. The intervention was administered using a web and mobile app from September to December 2018. Participants (N=320) were Australian and New Zealand members of a faith-based organization who self-selected into the study, owned a mobile phone with messaging capability, had an email address and internet access, were fluent in English, provided informed consent, and gave permission for their data to be used for research. The postintervention questionnaire elicited participants’ perceptions of facilitators and barriers to adherence during the intervention period. Results: Key factors that facilitated adherence were engaging content, time availability and management, ease of accessibility, easy or enjoyable practical challenges, high perceived value, and personal motivation to complete the intervention. The primary perceived barrier to adherence was the participants’ lack of time. Other barriers included completing and recording practical activities, length of video content, technical difficulties, and a combination of personal factors. Conclusions: Time scarcity was the foremost issue for the nonclinical cohort engaged in this digital MHPI. Program developers should streamline digital interventions to minimize the time investment for participants. This may include condensed content, optimization of intuitive web and app design, simplified recording of activities, and greater participant autonomy in choosing optional features. Nonetheless, participants identified a multiplicity of other interindividual factors that facilitated or inhibited adherence. %M 33851925 %R 10.2196/25358 %U https://www.jmir.org/2021/4/e25358 %U https://doi.org/10.2196/25358 %U http://www.ncbi.nlm.nih.gov/pubmed/33851925 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 4 %P e21444 %T Reasons for Discontinuing Active Participation on the Internet Forum Tinnitus Talk: Mixed Methods Citizen Science Study %A Budimir,Sanja %A Kuska,Martin %A Spiliopoulou,Myra %A Schlee,Winfried %A Pryss,Rüdiger %A Andersson,Gerhard %A Goedhart,Hazel %A Harrison,Stephen %A Vesala,Markku %A Hegde,Gourish %A Langguth,Berthold %A Pieh,Christoph %A Probst,Thomas %+ Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, Dr.-Karl-Dorrek-Strasse 30, Krems an der Donau, 3500, Austria, 43 27328932531, sanja.budimir@donau-uni.ac.at %K tinnitus %K Tinnitus Talk %K Internet forum %K dropout %K reasons for discontinuation %D 2021 %7 8.4.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Tinnitus Talk is a nonprofit online self-help forum. Asking inactive users about their reasons for discontinued usage of health-related online platforms such as Tinnitus Talk is important for quality assurance. Objective: The aim of this study was to explore reasons for discontinued use of Tinnitus Talk, and their associations to the perceptions of Tinnitus Talk and the age of users who ceased logging on to the platform. Methods: Initially, 13,745 users that did not use Tinnitus Talk within the previous 2 months were contacted and the response rate was 20.47% (n=2814). After dataset filtering, a total of 2172 past members of Tinnitus Talk were included in the analyses. Nine predefined reasons for discontinued usage of Tinnitus Talk were included in the survey as well as one open question. Moreover, there were 14 predefined questions focusing on perception of Tinnitus Talk (usefulness, content, community, and quality of members’ posts). Mixed methods analyses were performed. Frequencies and correlation coefficients were calculated for quantitative data, and grounded theory methodology was utilized for exploration of the qualitative data. Results: Quantitative analysis revealed reasons for discontinued use of Tinnitus Talk as well as associations of these reasons with perceptions of Tinnitus Talk and age. Among the eight predefined reasons for discontinued use of Tinnitus Talk, the most frequently reported was not finding the information they were looking for (451/2695, 16.7%). Overall, the highest rated perception of Tinnitus Talk was content-related ease of understanding (mean 3.9, SD 0.64). A high number (nearly 40%) of participants provided additional free text explaining why they discontinued use. Qualitative analyses identified a total of 1654 specific reasons, more than 93% of which (n=1544) could be inductively coded. The coding system consisted of 33 thematically labeled codes clustered into 10 categories. The most frequent additional reason for discontinuing use was thinking that there is no cure or help for tinnitus symptoms (375/1544, 24.3%). Significant correlations (P<.001) were observed between reasons for discontinued usage and perception of Tinnitus Talk. Several reasons for discontinued usage were associated with the examined dimensions of perception of Tinnitus Talk (usefulness, content, community, as well as quality of members’ posts). Moreover, significant correlations (P<.001) between age and reasons for discontinued use were found. Older age was associated with no longer using Tinnitus Talk because of not finding what they were looking for. In addition, older participants had a generally less positive perception of Tinnitus Talk than younger participants (P<.001). Conclusions: This study contributes to understanding the reasons for discontinued usage of online self-help platforms, which are typically only reported according to the dropout rates. Furthermore, specific groups of users who did not benefit from Tinnitus Talk were identified, and several practical implications for improvement of the structure, content, and goals of Tinnitus Talk were suggested. %M 33830060 %R 10.2196/21444 %U https://formative.jmir.org/2021/4/e21444 %U https://doi.org/10.2196/21444 %U http://www.ncbi.nlm.nih.gov/pubmed/33830060 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 4 %P e23447 %T Postsecondary Student Engagement With a Mental Health App and Online Platform (Thought Spot): Qualitative Study of User Experience %A Wong,Howard W %A Lo,Brian %A Shi,Jenny %A Hollenberg,Elisa %A Abi-Jaoude,Alexxa %A Johnson,Andrew %A Chaim,Gloria %A Cleverley,Kristin %A Henderson,Joanna %A Levinson,Andrea %A Robb,Janine %A Voineskos,Aristotle %A Wiljer,David %+ UHN Digital, University Health Network, R. Fraser Elliott Building RFE 3-411, 190 Elizabeth Street, Toronto, ON, M5G 2C4, Canada, 1 416 340 6322, david.wiljer@uhn.ca %K transition-aged youth %K qualitative study %K user experience %K help-seeking %K mental health %K postsecondary %K mobile apps %K adolescent %D 2021 %7 2.4.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: There is growing interest in using mobile apps and online tools to support postsecondary student mental health, but most of these solutions have suboptimal user engagement in real-world settings. Poor engagement can limit long-term effectiveness and usefulness of these tools. Previous literature has proposed several theories that link factors such as low usability and poor user-centered design to app disengagement. However, few studies provide direct evidence showing what factors contribute to suboptimal user engagement in the context of mobile mental health apps for postsecondary students. Objective: This study focuses on understanding postsecondary students’ attitudes and behaviors when using Thought Spot, a co-designed mental health app and online platform, to understand factors related to engagement and user experience. Methods: Students who were given access to Thought Spot for 6 months during a randomized trial of the intervention were invited to participate in one-on-one semistructured interviews. The interviews explored participants’ overall experiences and perceptions of the app, along with factors that affected their usage of various features. All interviews were recorded, and template analysis was used to analyze transcripts. Results: User satisfaction was mixed among users of Thought Spot. The degree of engagement with the app appeared to be affected by factors that can be grouped into 5 themes: (1) Students valued detailed, inclusive, and relevant content; (2) Technical glitches and a lack of integration with other apps affected the overall user experience and satisfaction with the app; (3) Using the app to support peers or family can increase engagement; (4) Crowdsourced information from peers about mental health resources drove user engagement, but was difficult to obtain; and (5) Users often turned to the app when they had an immediate need for mental health information, rather than using it to track mental health information over time. Conclusions: Content, user experience, user-centeredness, and peer support are important determinants of user engagement with mobile mental health apps among postsecondary students. In this study, participants disengaged when the app did not meet their expectations on these determinants. Future studies on user engagement should further explore the effectiveness of different features and the relative importance of various criteria for high-quality apps. Further focus on these issues may inform the creation of interventions that increase student engagement and align with their mental health needs. Trial Registration: ClinicalTrials.gov NCT03412461; https://clinicaltrials.gov/ct2/show/NCT03412461 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.6446 %M 33797395 %R 10.2196/23447 %U https://mental.jmir.org/2021/4/e23447 %U https://doi.org/10.2196/23447 %U http://www.ncbi.nlm.nih.gov/pubmed/33797395 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 3 %P e24871 %T Optimizing Engagement in an Online Dietary Intervention for Depression (My Food & Mood Version 3.0): Cohort Study %A Young,Claire Louise %A Mohebbi,Mohammadreza %A Staudacher,Heidi M %A Kay-Lambkin,Frances %A Berk,Michael %A Jacka,Felice Nellie %A O'Neil,Adrienne %+ Food & Mood Centre, Institute for Mental and Physical Health and Clinical Translation, Deakin University, PO Box 281, Geelong, Victoria, 3220, Australia, 61 406754668, youngc@deakin.edu.au %K online intervention %K nutritional psychiatry %K depression %K low mood %K dietary intervention %K eHealth %K mHealth %K dietary intervention %K engagement %K nonusage attrition %D 2021 %7 31.3.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Online interventions can be a cost-effective and efficient way to deliver programs to large numbers of people regardless of geographic location. However, attrition in web-based interventions is often an issue. Developing ways to keep participants engaged is important for ensuring validity and limiting potential biases. We developed a web-based dietary intervention as part of The My Food & Mood study which aimed to optimize ways to engage participants with low mood or depressive symptoms to promote dietary behavior change. Different versions of the My Food & Mood program were tested during optimization. Iterations were developed based on user feedback and usage analysis. Objective: The purpose of this study was to compare engagement and nonusage attrition across 4 program iterations—which differed by platform format, delivery mode, and activity type—to create an optimized version. Methods: Each program version contained modular videos with key activities with respect to implementing behavior change techniques of equivalent levels of required participation and length: version 1.0, desktop program and smartphone app; version 2.1, desktop or smartphone program; version 2.2, desktop program; and version 3.0, smartphone app. Adults with PHQ-8 scores of 5 or greater were recruited online and assigned to 1 of the 4 versions. Participants were asked to use the program for 8 weeks and complete measures at weeks 4 and 8. Engagement data were collected from the web-based platform system logs and customized reports. Cox regression survival analysis examined nonusage attrition and Kruskal-Wallis tests compared engagement across each cohort. Results: A total of 614 adults participated. Kruskal-Wallis tests showed significant differences across the 4 cohorts in all engagement measures. The smartphone app (version 3.0) had the greatest engagement as measured by weeks engaged, total usage time, total time key activities, number of active sessions, percentage of activities completed against protocol, goals completed, and percentage of videos watched. Cox regression multivariate survival analysis showed referral from a health practitioner (hazard ratio [HR] 0.344, P=.001) and greater proficiency with computers (HR 0.796, P=.049) reduced the risk of nonusage attrition. Computer confidence was associated with an increased risk of nonusage attrition. Conclusions: My Food & Mood version 3.0, a dietary intervention delivered via smartphone app with self-monitoring tools for diet quality and mood monitoring, was the version with greatest engagement in a population with low mood or depression. The iterative design techniques employed and analysis of feedback from participants resulted in a program that achieved lower rates of nonusage attrition and higher rates of intensity of use. %M 33787501 %R 10.2196/24871 %U https://mental.jmir.org/2021/3/e24871 %U https://doi.org/10.2196/24871 %U http://www.ncbi.nlm.nih.gov/pubmed/33787501 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e25810 %T Development of Coaching Support for LiveWell: A Smartphone-Based Self-Management Intervention for Bipolar Disorder %A Dopke,Cynthia A %A McBride,Alyssa %A Babington,Pamela %A Jonathan,Geneva K %A Michaels,Tania %A Ryan,Chloe %A Duffecy,Jennifer %A Mohr,David C %A Goulding,Evan H %+ Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, 303 E Chicago Ave., Suite 7-102, Chicago, IL, 60611, United States, 1 3125031189, e-goulding@fsm.northwestern.edu %K human support %K adherence %K self-management %K behavior change %K mHealth %K bipolar disorder %D 2021 %7 24.3.2021 %9 Viewpoint %J JMIR Form Res %G English %X Despite effective pharmacological treatment, bipolar disorder is a leading cause of disability due to recurrence of episodes, long episode durations, and persistence of interepisode symptoms. While adding psychotherapy to pharmacotherapy improves outcomes, the availability of adjunctive psychotherapy is limited. To extend the accessibility and functionality of psychotherapy for bipolar disorder, we developed LiveWell, a smartphone-based self-management intervention. Unfortunately, many mental health technology interventions suffer from high attrition rates, with users rapidly failing to maintain engagement with the intervention technology. Human support reduces this commonly observed engagement problem but does not consistently improve clinical and recovery outcomes. To facilitate ongoing efforts to develop human support for digital mental health technologies, this paper describes the design decisions, theoretical framework, content, mode, timing of delivery, and the training and supervision for coaching support of the LiveWell technology. This support includes clearly defined and structured roles that aim to encourage the use of the technology, self-management strategies, and communication with care providers. A clear division of labor is established between the coaching support roles and the intervention technology to allow lay personnel to serve as coaches and thereby maximize accessibility to the LiveWell intervention. %M 33759798 %R 10.2196/25810 %U https://formative.jmir.org/2021/3/e25810 %U https://doi.org/10.2196/25810 %U http://www.ncbi.nlm.nih.gov/pubmed/33759798 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e26355 %T Designing an mHealth Intervention for People With Visible Differences Based on Acceptance and Commitment Therapy: Participatory Study Gaining Stakeholders’ Input %A Zucchelli,Fabio %A Donnelly,Olivia %A Rush,Emma %A Smith,Harriet %A Williamson,Heidi %A , %+ The Centre for Appearance Research, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, United Kingdom, 44 11732 83882, fabio.zucchelli@uwe.ac.uk %K mobile health %K acceptance and commitment therapy %K appearance %K qualitative %K participatory design %K mobile phone %D 2021 %7 24.3.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Given their growing popularity, mobile health (mHealth) apps may offer a viable method of delivering psychological interventions for people with an atypical appearance (ie, visible difference) who struggle with appearance-related distress. Acceptance and Commitment Therapy (ACT), a third-wave cognitive behavioral approach, has been used effectively in mHealth and is being increasingly applied clinically to common psychosocial difficulties associated with visible differences. We planned to design an ACT-based mHealth intervention (ACT It Out) for this population. Objective: The aim of this study is to gain key stakeholder input from user representatives and psychological clinicians to optimize the intervention’s design for future development and uptake. To do so, we explored considerations relating to mHealth as a delivery platform for adults with visible differences and elicited stakeholders’ design preferences and ideas based on initial author-created content. Methods: Within a participatory design framework, we used a mix of qualitative methods, including usability sessions and a focus group in a face-to-face workshop, and interviews and textual feedback collected remotely, all analyzed using template analysis. A total of 6 user representatives and 8 clinicians were recruited for this study. Results: Our findings suggest that there are likely to be strengths and challenges of mHealth as an intervention platform for the study population, with key concerns being user safeguarding and program adherence. Participants expressed design preferences toward relatable human content, interactive and actionable features, flexibility of use, accessibility, and engaging content. Conclusions: The findings offer valuable design directions for ACT It Out and related interventions, emphasizing the need to carefully guide users through the intervention while acknowledging the limited time and space that mHealth affords. %M 33759791 %R 10.2196/26355 %U https://formative.jmir.org/2021/3/e26355 %U https://doi.org/10.2196/26355 %U http://www.ncbi.nlm.nih.gov/pubmed/33759791 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 3 %P e24590 %T Commencement of and Retention in Web-Based Interventions and Response to Prompts and Reminders: Longitudinal Observational Study Based on Two Randomized Controlled Trials %A Andriopoulos,Athanasios %A Olsson,Erik M G %A Hägg Sylvén,Ylva %A Sjöström,Jonas %A Johansson,Birgitta %A von Essen,Louise %A Grönqvist,Helena %+ Department of Women's and Children's Health, Uppsala University, Akademiska sjukhuset, Uppsala, 75185, Sweden, 46 736236500, helena.gronqvist@kbh.uu.se %K log data analysis %K use pattern %K retention %K dropout %K attrition %K online intervention %K online data %D 2021 %7 12.3.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Web-based interventions are effective for several psychological problems. However, recruitment, adherence, and missing data are challenges when evaluating these interventions. Objective: This study aimed to describe the use patterns during the commencement phase, possible retention patterns (continuation of data provision), and responses to prompts and reminders among participants in 2 randomized controlled trials (RCTs) evaluating web-based interventions. Methods: Data on use patterns logged in 2 RCTs aiming to reduce symptoms of anxiety and depression among adult patients recently diagnosed with cancer (AdultCan RCT) and patients with a recent myocardial infarction (Heart RCT) were analyzed. The web-based intervention in the AdultCan trial consisted of unguided self-help and psychoeducation and that in the Heart trial consisted of therapist-supported cognitive behavioral therapy. In total, 2360 participants’ use patterns at first log-in, including data collection at baseline (ie, commencement) and at 2 follow-ups, were analyzed. Both the intervention and comparison groups were analyzed. Results: At commencement, 70.85% (909/1283) and 86.82% (935/1077) of the participants in AdultCan and Heart RCTs, respectively, logged in and completed baseline data collection after receiving a welcome email with log-in credentials. The median duration of the first log-in was 44 minutes and 38 minutes in AdultCan and Heart RCTs, respectively. Slightly less than half of the participants’ first log-ins were completed outside standard office hours. More than 80% (92/114 and 103/111) of the participants in both trials explored the intervention within 2 weeks of being randomized to the treatment group, with a median duration of 7 minutes and 47 minutes in AdultCan and Heart RCTs, respectively. There was a significant association between intervention exploration time during the first 2 weeks and retention in the Heart trial but not in the AdultCan trial. However, the control group was most likely to retain and provide complete follow-up data. Across the 3 time points of data collection explored in this study, the proportion of participants responding to all questionnaires within 1 week from the prompt, without a reminder, varied between 35.45% (413/1165) and 66.3% (112/169). After 2 reminders, up to 97.6% (165/169) of the participants responded. Conclusions: Most participants in both RCTs completed the baseline questionnaires within 1 week of receiving the welcome email. Approximately half of them answered questions at baseline data collection outside office hours, suggesting that the time flexibility inherent in web-based interventions contributes to commencement and use. In contrast to what was expected, the intervention groups generally had lower completion rates than the comparison groups. About half of the participants completed the questionnaires without a reminder, but thereafter, reminders contributed to both baseline and follow-up retention, suggesting they were effective. Strategies to increase commencement of and retention in eHealth interventions are important for the future development of effective interventions and relevant research. %M 33709937 %R 10.2196/24590 %U https://www.jmir.org/2021/3/e24590 %U https://doi.org/10.2196/24590 %U http://www.ncbi.nlm.nih.gov/pubmed/33709937 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 3 %P e18348 %T e-Mental Health Program Usage Patterns in Randomized Controlled Trials and in the General Public to Inform External Validity Considerations: Sample Groupings Using Cluster Analyses %A Sanatkar,Samineh %A Baldwin,Peter %A Huckvale,Kit %A Christensen,Helen %A Harvey,Samuel %+ Black Dog Institute, The University of New South Wales Sydney, Hospital Road, Randwick, 2031, Australia, 61 9382 4368, s.sanatkar@unsw.edu.au %K e-mental health %K engagement patterns %K external validity %K randomized controlled trial %K community sample %D 2021 %7 11.3.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Randomized controlled trials (RCTs) with vigorous study designs are vital for determining the efficacy of treatments. Despite the high internal validity attributed to RCTs, external validity concerns limit the generalizability of results to the general population. Bias can be introduced, for example, when study participants who self-select into a trial are more motivated to comply with study conditions than are other individuals. These external validity considerations extend to e-mental health (eMH) research, especially when eMH tools are designed for public access and provide minimal or no supervision. Objective: Clustering techniques were employed to identify engagement profiles of RCT participants and community users of a self-guided eMH program. This exploratory approach inspected actual, not theorized, RCT participant and community user engagement patterns. Both samples had access to the eMH program over the same time period and received identical usage recommendations on the eMH program website. The aim of this study is to help gauge expectations of similarities and differences in usage behaviors of an eMH tool across evaluation and naturalistic contexts. Methods: Australian adults signed up to myCompass, a self-guided online treatment program created to reduce mild to moderate symptoms of negative emotions. They did so either by being part of an RCT onboarding (160/231, 69.6% female) or by accessing the program freely on the internet (5563/8391, 66.30% female) between October 2011 and October 2012. During registration, RCT participants and community users provided basic demographic information. Usage metrics (number of logins, trackings, and learning activities) were recorded by the system. Results: Samples at sign-up differed significantly in age (P=.003), with community users being on average 3 years older (mean 41.78, SD 13.64) than RCT participants (mean 38.79, SD 10.73). Furthermore, frequency of program use was higher for RCT participants on all usage metrics compared to community users through the first 49 days after registration (all P values <.001). Two-step cluster analyses revealed 3 user groups in the RCT sample (Nonstarters, 10-Timers, and 30+-Timers) and 2 user groups in the community samples (2-Timers and 20-Timers). Groups seemed comparable in patterns of use but differed in magnitude, with RCT participant usage groups showing more frequent engagement than community usage groups. Only the high-usage group among RCT participants approached myCompass usage recommendations. Conclusions: Findings suggested that external validity concerns of RCT designs may arise with regards to the predicted magnitude of eMH program use rather than overall usage styles. Following up RCT nonstarters may help provide unique insights into why individuals choose not to engage with an eMH program despite generally being willing to participate in an eMH evaluation study. Overestimating frequency of engagement with eMH tools may have theoretical implications and potentially impact economic considerations for plans to disseminate these tools to the general public. %M 33704070 %R 10.2196/18348 %U https://www.jmir.org/2021/3/e18348 %U https://doi.org/10.2196/18348 %U http://www.ncbi.nlm.nih.gov/pubmed/33704070 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 3 %P e26528 %T User Engagement and Clinical Impact of the Manage My Pain App in Patients With Chronic Pain: A Real-World, Multi-site Trial %A Bhatia,Anuj %A Kara,Jamal %A Janmohamed,Tahir %A Prabhu,Atul %A Lebovic,Gerald %A Katz,Joel %A Clarke,Hance %+ Department of Anesthesia and Pain Medicine, University Health Network, University of Toronto, McL 2-405, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada, 1 4166035800 ext 6136, anuj.bhatia@uhn.ca %K pain %K psychology %K patient-oriented research %K quality of life %K digital health %K chronic pain %K pain app %K virtual care %K mHealth %K pain management %K chronic disease management %K remote monitoring %K app %K engagement %K impact %K outcome %D 2021 %7 4.3.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Chronic pain imposes a large burden on individuals and society. A patient-centric digital chronic pain management app called Manage My Pain (MMP) can be used to enhance communication between providers and patients and promote self-management. Objective: The purpose of this study was to evaluate the real-world engagement of patients in urban and rural settings in Ontario, Canada with the MMP app alongside their standard of care and assess the impact of its usage on clinical outcomes of pain and related mental health. Methods: A total of 246 participants with chronic pain at a rural and 2 urban pain clinics were recruited into this prospective, open-label, exploratory study that compared the use of MMP, a digital health app for pain that incorporates validated questionnaires and provides patients with summarized reports of their progress in combination with standard care (app group), against data entered on paper-based questionnaires (nonapp group). Participants completed validated questionnaires on anxiety, depression, pain catastrophizing, satisfaction, and daily opioid consumption up to 4.5 months after the initial visit (short-term follow-up) and between 4.5 and 7 months after the initial visit (long-term follow-up). Engagement and clinical outcomes were compared between participants in the two groups. Results: A total of 73.6% (181/246) of the participants agreed to use the app, with 63.4% (111/175) of them using it for at least one month. Individuals who used the app rated lower anxiety (reduction in Generalized Anxiety Disorder 7-item questionnaire score by 2.10 points, 95% CI –3.96 to –0.24) at short-term follow-up and had a greater reduction in pain catastrophizing (reduction in Pain Catastrophizing Scale score by 5.23 points, 95% CI –9.55 to –0.91) at long-term follow-up relative to patients with pain who did not engage with the MMP app. Conclusions: The use of MMP by patients with chronic pain is associated with engagement and improvements in self-reported anxiety and pain catastrophizing. Further research is required to understand factors that impact continued engagement and clinical outcomes in patients with chronic pain. Trial Registration: ClinicalTrials.gov NCT04762329; https://clinicaltrials.gov/ct2/show/NCT04762329 %M 33661130 %R 10.2196/26528 %U https://mhealth.jmir.org/2021/3/e26528 %U https://doi.org/10.2196/26528 %U http://www.ncbi.nlm.nih.gov/pubmed/33661130 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e25235 %T Feasibility and Acceptability of a Digital Intervention to Support Shared Decision-making in Children’s and Young People’s Mental Health: Mixed Methods Pilot Randomized Controlled Trial %A Liverpool,Shaun %A Edbrooke-Childs,Julian %+ Evidence-Based Practice Unit, Anna Freud National Centre for Children and Families, University College London, 4-8 Rodney Street, The Kantor Centre of Excellence, London, N1 9JH, United Kingdom, 44 7539468630, shaun.liverpool.14@ucl.ac.uk %K mental health %K pilot projects %K child %K adolescent %K parents %K shared decision making %D 2021 %7 2.3.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Interventions to involve parents in decisions regarding children’s and young people’s mental health are associated with positive outcomes. However, appropriately planning effectiveness studies is critical to ensure that meaningful evidence is collected. It is important to conduct pilot studies to evaluate the feasibility and acceptability of the intervention itself and the feasibility of the protocol to test effectiveness. Objective: This paper reports the findings from a feasibility and acceptability study of Power Up for Parents, an intervention to promote shared decision-making (SDM) and support parents and caregivers making decisions regarding children’s and young people’s mental health. Methods: A mixed method study design was adopted. In stage 1, health care professionals and parents provided feedback on acceptability, usefulness, and suggestions for further development. Stage 2 was a multicenter, 3-arm, individual, and cluster randomized controlled pilot feasibility trial with parents accessing services related to children’s and young people’s mental health. Outcome measures collected data on demographics, participation rates, SDM, satisfaction, and parents’ anxiety. Qualitative data were analyzed using thematic analysis. Google Analytics estimates were used to report engagement with the prototype. Outcomes from both stages were tested against a published set of criteria for proceeding to a randomized controlled trial. Results: Despite evidence suggesting the acceptability of Power Up for Parents, the findings suggest that recruitment modifications are needed to enhance the feasibility of collecting follow-up data before scaling up to a fully powered randomized controlled trial. On the basis of the Go or No-Go criteria, only 50% (6/12) of the sites successfully recruited participants, and only 38% (16/42) of parents completed follow-up measures. Nonetheless, health care practitioners and parents generally accessed and used the intervention. Themes describing appearance and functionality, perceived need and general helpfulness, accessibility and appropriateness, and a wish list for improvement emerged, providing valuable information to inform future development and refinement of the intervention. Conclusions: Owing to the high attrition observed in the trial, proceeding directly to a full randomized controlled trial may not be feasible with this recruitment strategy. Nonetheless, with some minor adjustments and upgrades to the intervention, this pilot study provides a platform for future evaluations of Power Up for Parents. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN) 39238984; http://www.isrctn.com/ISRCTN39238984. International Registered Report Identifier (IRRID): RR2-10.2196/14571 %M 33650973 %R 10.2196/25235 %U https://formative.jmir.org/2021/3/e25235 %U https://doi.org/10.2196/25235 %U http://www.ncbi.nlm.nih.gov/pubmed/33650973 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 2 %P e17573 %T A Novel User Utility Score for Diabetes Management Using Tailored Mobile Coaching: Secondary Analysis of a Randomized Controlled Trial %A Lee,Min-Kyung %A Lee,Da Young %A Ahn,Hong-Yup %A Park,Cheol-Young %+ Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul, 03181, Republic of Korea, 82 2 2001 1869, cydoctor@chol.com %K type 2 diabetes %K mobile applications %K diabetes management %K patient engagement %D 2021 %7 24.2.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health applications have been developed to support diabetes self-management, but their effectiveness could depend on patient engagement. Therefore, patient engagement must be examined through multifactorial tailored behavioral interventions from an individual perspective. Objective: This study aims to evaluate the usefulness of a novel user utility score (UUS) as a tool to measure patient engagement by using a mobile health application for diabetes management. Methods: We conducted a subanalysis of results from a 12-month randomized controlled trial of a tailored mobile coaching (TMC) system among insurance policyholders with type 2 diabetes. UUS was calculated as the sum of the scores for 4 major core components (range 0-8): frequency of self-monitoring blood glucose testing, dietary and exercise records, and message reading rate. We explored the association between UUS for the first 3 months and glycemic control over 12 months. In addition, we investigated the relationship of UUS with blood pressure, lipid profile, and self-report scales assessing diabetes self-management. Results: We divided 72 participants into 2 groups based on UUS for the first 3 months: UUS:0-4 (n=38) and UUS:5-8 (n=34). There was a significant between-group difference in glycated hemoglobin test (HbA1c) levels for the 12-months study period (P=.011). The HbA1c decrement at 12 months in the UUS:5-8 group was greater than that of the UUS:0-4 group [–0.92 (SD 1.24%) vs –0.33 (SD 0.80%); P=.049]. After adjusting for confounding factors, UUS was significantly associated with changes in HbA1c at 3, 6, and 12 months; the regression coefficients were –0.113 (SD 0.040; P=.006), –0.143 (SD 0.045; P=.002), and –0.136 (SD 0.052; P=.011), respectively. Change differences in other health outcomes between the 2 groups were not observed throughout a 12-month follow-up. Conclusions: UUS as a measure of patient engagement was associated with changes in HbA1c over the study period of the TMC system and could be used to predict improved glycemic control in diabetes self-management through mobile health interventions. Trial Registration: ClinicalTrial.gov NCT03033407; https://clinicaltrials.gov/ct2/show/NCT03033407 %M 33625363 %R 10.2196/17573 %U https://mhealth.jmir.org/2021/2/e17573 %U https://doi.org/10.2196/17573 %U http://www.ncbi.nlm.nih.gov/pubmed/33625363 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 2 %P e27109 %T A Digital Health Intervention (SweetGoals) for Young Adults With Type 1 Diabetes: Protocol for a Factorial Randomized Trial %A Stanger,Catherine %A Kowatsch,Tobias %A Xie,Haiyi %A Nahum-Shani,Inbal %A Lim-Liberty,Frances %A Anderson,Molly %A Santhanam,Prabhakaran %A Kaden,Sarah %A Rosenberg,Briana %+ Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Lebanon, NH, , United States, 1 603 646 7023, Catherine.stanger@dartmouth.edu %K type 1 diabetes %K mhealth %K incentives %K health coaching %K young adults %D 2021 %7 23.2.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Many young adults with type 1 diabetes (T1D) struggle with the complex daily demands of adherence to their medical regimen and fail to achieve target range glycemic control. Few interventions, however, have been developed specifically for this age group. Objective: In this randomized trial, we will provide a mobile app (SweetGoals) to all participants as a “core” intervention. The app prompts participants to upload data from their diabetes devices weekly to a device-agnostic uploader (Glooko), automatically retrieves uploaded data, assesses daily and weekly self-management goals, and generates feedback messages about goal attainment. Further, the trial will test two unique intervention components: (1) incentives to promote consistent daily adherence to goals, and (2) web health coaching to teach effective problem solving focused on personalized barriers to self-management. We will use a novel digital direct-to-patient recruitment method and intervention delivery model that transcends the clinic. Methods: A 2x2 factorial randomized trial will be conducted with 300 young adults ages 19-25 with type 1 diabetes and (Hb)A1c ≥ 8.0%. All participants will receive the SweetGoals app that tracks and provides feedback about two adherence targets: (a) daily glucose monitoring; and (b) mealtime behaviors. Participants will be randomized to the factorial combination of incentives and health coaching. The intervention will last 6 months. The primary outcome will be reduction in A1c. Secondary outcomes include self-regulation mechanisms in longitudinal mediation models and engagement metrics as a predictor of outcomes. Participants will complete 6- and 12-month follow-up assessments. We hypothesize greater sustained A1c improvements in participants who receive coaching and who receive incentives compared to those who do not receive those components. Results: Data collection is expected to be complete by February 2025. Analyses of primary and secondary outcomes are expected by December 2025. Conclusions: Successful completion of these aims will support dissemination and effectiveness studies of this intervention that seeks to improve glycemic control in this high-risk and understudied population of young adults with T1D. Trial Registration: ClinicalTrials.gov NCT04646473; https://clinicaltrials.gov/ct2/show/NCT04646473 International Registered Report Identifier (IRRID): PRR1-10.2196/27109 %M 33620330 %R 10.2196/27109 %U https://www.researchprotocols.org/2021/2/e27109 %U https://doi.org/10.2196/27109 %U http://www.ncbi.nlm.nih.gov/pubmed/33620330 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 2 %P e23180 %T Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis %A Mclaughlin,Matthew %A Delaney,Tessa %A Hall,Alix %A Byaruhanga,Judith %A Mackie,Paul %A Grady,Alice %A Reilly,Kathryn %A Campbell,Elizabeth %A Sutherland,Rachel %A Wiggers,John %A Wolfenden,Luke %+ School of Medicine and Public Health, University of Newcastle, University Drive, Callaghan, 2308, Australia, 61 02 4924 6477, Matthew.Mclaughlin1@health.nsw.gov.au %K engagement %K adherence %K digital health intervention %K digital behavior change intervention %K physical activity %K sedentary behavior %K mobile phone %D 2021 %7 19.2.2021 %9 Review %J J Med Internet Res %G English %X Background: The effectiveness of digital health interventions is commonly assumed to be related to the level of user engagement with the digital health intervention, including measures of both digital health intervention use and users’ subjective experience. However, little is known about the relationships between the measures of digital health intervention engagement and physical activity or sedentary behavior. Objective: This study aims to describe the direction and strength of the association between engagement with digital health interventions and physical activity or sedentary behavior in adults and explore whether the direction of association of digital health intervention engagement with physical activity or sedentary behavior varies with the type of engagement with the digital health intervention (ie, subjective experience, activities completed, time, and logins). Methods: Four databases were searched from inception to December 2019. Grey literature and reference lists of key systematic reviews and journals were also searched. Studies were eligible for inclusion if they examined a quantitative association between a measure of engagement with a digital health intervention targeting physical activity and a measure of physical activity or sedentary behavior in adults (aged ≥18 years). Studies that purposely sampled or recruited individuals on the basis of pre-existing health-related conditions were excluded. In addition, studies were excluded if the individual engaging with the digital health intervention was not the target of the physical activity intervention, the study had a non–digital health intervention component, or the digital health interventions targeted multiple health behaviors. A random effects meta-analysis and direction of association vote counting (for studies not included in meta-analysis) were used to address objective 1. Objective 2 used vote counting on the direction of the association. Results: Overall, 10,653 unique citations were identified and 375 full texts were reviewed. Of these, 19 studies (26 associations) were included in the review, with no studies reporting a measure of sedentary behavior. A meta-analysis of 11 studies indicated a small statistically significant positive association between digital health engagement (based on all usage measures) and physical activity (0.08, 95% CI 0.01-0.14, SD 0.11). Heterogeneity was high, with 77% of the variation in the point estimates explained by the between-study heterogeneity. Vote counting indicated that the relationship between physical activity and digital health intervention engagement was consistently positive for three measures: subjective experience measures (2 of 3 associations), activities completed (5 of 8 associations), and logins (6 of 10 associations). However, the direction of associations between physical activity and time-based measures of usage (time spent using the intervention) were mixed (2 of 5 associations supported the hypothesis, 2 were inconclusive, and 1 rejected the hypothesis). Conclusions: The findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak. %M 33605897 %R 10.2196/23180 %U http://www.jmir.org/2021/2/e23180/ %U https://doi.org/10.2196/23180 %U http://www.ncbi.nlm.nih.gov/pubmed/33605897 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 6 %N 1 %P e24030 %T Role of Digital Engagement in Diabetes Care Beyond Measurement: Retrospective Cohort Study %A Fundoiano-Hershcovitz,Yifat %A Hirsch,Abigail %A Dar,Sharon %A Feniger,Eitan %A Goldstein,Pavel %+ DarioHealth, Hatochen, 8, Caesarea, 3088900, Israel, 972 525296979, Yifat@mydario.com %K blood glucose %K mHealth %K diabetes %K self-management %K digital engagement %D 2021 %7 18.2.2021 %9 Original Paper %J JMIR Diabetes %G English %X Background: The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes. Objective: This study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels. Methods: This retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included “nontaggers” (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and “taggers” (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual’s tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout. Results: Analysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=−10.01, P<.001), which was maintained during the following 6 months (t=−1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=−11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20). Conclusions: This study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health. %M 33599618 %R 10.2196/24030 %U http://diabetes.jmir.org/2021/1/e24030/ %U https://doi.org/10.2196/24030 %U http://www.ncbi.nlm.nih.gov/pubmed/33599618 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 2 %P e18385 %T Improving Efficiency of Clinical Studies Using a Total Digital Approach: Prospective Observational Study %A Schenck-Gustafsson,Karin %A Carnlöf,Carina %A Jensen-Urstad,Mats %A Insulander,Per %+ Heart and Vascular Theme, Karolinska University Hospital, Karolinska Institutet, Norrbacka S1:02, Stockholm, S 17176, Sweden, 46 707686487, karin.schenck-gustafsson@ki.se %K ECG recordings %K women %K palpitations %K full digitalization %K eAuthentication %K BankID %K clinical trial %K mHealth %K electrocardiogram %D 2021 %7 18.2.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: In general, most clinical studies have long recruitment periods. Signing the informed consent is particularly time-consuming when the participant must meet physically with the researchers. Therefore, introducing fully web-based techniques with the use of eAuthentication (BankID) and new digital electrocardiogram (ECG) monitoring could speed up inclusion time, increase adherence, and also reach out to more remote regions. Objective: The objectives of this study were to explore whether inclusion of a large number of participants could be realized quickly by using a total digital approach both for information and signing of informed consent, along with ECG monitoring and instant feedback on a mobile device. We also explored whether this approach can increase adherence in registration of ECG recordings and answering questionnaires, and if it would result in a more geographically uniform distribution of participants covering a wide age span. Methods: Women with palpitations were intensively studied over 2 months by means of a handheld ECG monitoring device (Coala Heart Monitor). The device connects to a smartphone or tablet, which allows the participants to obtain the results immediately. Recruitment, study information, and signing the informed consent form with the help of BankID were performed in a completely digital manner. Results: Between March and May 2018, 2424 women indicated their interest in participating in the study. On June 19, 2018, presumptive participants were invited to log in and register. After 25 days, 1082 women were included in the study; among these, 1020 women fulfilled the inclusion criteria, 913 of whom completed all phases of the study: recording ECG using the handheld device, completion of the prestudy questionnaires, and completion of the poststudy questionnaires 2 months after the ECG recordings. The dropout rate was 9%. In total, 101,804 ECG recordings were made. The mean age was 56 (SD 11) years (range 21-88 years) and 35 participants were 75 years or older. The participants were evenly distributed between living in the countryside and in cities. Conclusions: Total digital inclusion recruitment of 1082 participants was achieved in only 25 days, and resulted in a good geographical distribution, excellent adherence, and ability to reach a vast age span, including elderly women. Studies using a total digital design would be particularly appealing during a pandemic since physical contact should be avoided as much as possible. Trial Registration: ISRCTN Registry ISRCTN22495299; http://www.isrctn.com/ISRCTN22495299 %M 33599617 %R 10.2196/18385 %U http://formative.jmir.org/2021/2/e18385/ %U https://doi.org/10.2196/18385 %U http://www.ncbi.nlm.nih.gov/pubmed/33599617 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 2 %P e21432 %T Usage and Weekly Attrition in a Smartphone-Based Health Behavior Intervention for Adolescents: Pilot Randomized Controlled Trial %A Egilsson,Erlendur %A Bjarnason,Ragnar %A Njardvik,Urdur %+ Department of Psychology, University of Iceland, Sturlugata 1, Reykjavik, 101, Iceland, 354 6184805, erlendu@hi.is %K mHealth %K intervention %K adolescent %K attrition %K self-efficacy %K mental health %K physical activity %K young adult %K behavior %D 2021 %7 17.2.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The majority of adolescents own smartphones, although only 8% of them use health apps. Attrition rates from adolescent mobile health (mHealth) interventions for treating mental health problems such as anxiety and depression are an issue with a high degree of variation. Attrition in mHealth interventions targeting adolescent populations is frequently presented in a two-point fashion, from initiation of the intervention to the end of treatment, lacking more time-specific information on usage and times of attrition. Self-efficacy could provide an avenue to lower attrition rates, although a better understanding of the relationship between mental health factors and time-specific attrition rates is needed. Objective: The aims of this study were to obtain time-specific attrition rates among adolescents in an mHealth intervention, and to describe the intervention’s usage and feasibility in relation to adolescent self-efficacy levels, and emotional and physical health. Methods: A single-center randomized controlled public school pilot trial was undertaken with 41 adolescents. Outcome measures were assessed at baseline and after 6 weeks, while in-app activity and attrition rates were continually assessed throughout the intervention period. The primary outcome was attrition based on time and type of in-app health behavior usage, and feasibility of the mHealth app. Secondary outcome measures were self-efficacy levels, depressive and anxiety symptoms, as well as standardized BMI and sleep. Analyses of group mean variances with adjusted α levels through Bonferroni corrections were used to assess main outcome effects. Results: The attrition from initiation of the intervention to 6-week follow up was 35%. Attrition started in the third week of the intervention and was related to daily time of app usage (Rt=0.43, P<.001). The number of average weekly in-app health exercises completed decreased significantly from the first week of the intervention (mean 55.25, SD 10.96) to the next week (mean 13.63, SD 2.94). However, usage increased by 22% between week 2 and the last week of the intervention (mean 16.69, SD 8.37). Usability measures revealed satisfactory scores (mean 78.09, SD 9.82) without gender differences (P=.85). Self-reported daily physical activity increased by 19.61% in the intervention group but dropped by 26.21% among controls. Self-efficacy levels increased by 8.23% in the invention arm compared to a 3.03% decrease in the control group. Conclusions: This pilot study demonstrated the feasibility and usability of an mHealth intervention among adolescent participants. Indications were toward beneficial effects on physical and mental health that warrant further research. Focus on time-specific attrition measures alongside daily times of usage and ways to increase participants’ self-efficacy levels appear to be a promising avenue for research on mHealth interventions for adolescent populations with the aim to ultimately lower attrition rates. %M 33481750 %R 10.2196/21432 %U http://formative.jmir.org/2021/2/e21432/ %U https://doi.org/10.2196/21432 %U http://www.ncbi.nlm.nih.gov/pubmed/33481750 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 2 %P e26750 %T Effectiveness of an Integrated Engagement Support System to Facilitate Patient Use of Digital Diabetes Prevention Programs: Protocol for a Randomized Controlled Trial %A Lawrence,Katharine %A Rodriguez,Danissa V %A Feldthouse,Dawn M %A Shelley,Donna %A Yu,Jonathan L %A Belli,Hayley M %A Gonzalez,Javier %A Tasneem,Sumaiya %A Fontaine,Jerlisa %A Groom,Lisa L %A Luu,Son %A Wu,Yinxiang %A McTigue,Kathleen M %A Rockette-Wagner,Bonny %A Mann,Devin M %+ Healthcare Innovation Bridging Research, Informatics, and Design Lab, Department of Population Health, NYU Langone Health, 227 E 30th St, New York, NY, 10016, United States, 1 646 929 7870, hibrid.lab@nyulangone.org %K mobile health %K mHealth %K eHealth %K diabetes prevention %K type 2 diabetes mellitus %K mobile phone %D 2021 %7 9.2.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Digital diabetes prevention programs (dDPPs) are effective behavior change tools to prevent disease progression in patients at risk for diabetes. At present, these programs are poorly integrated into existing health information technology infrastructure and clinical workflows, resulting in barriers to provider-level knowledge of, interaction with, and support of patients who use dDPPs. Tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient engagement and adherence to these programs and improved health outcomes. Objective: This study aims to use a rigorous, user-centered design (UCD) methodology to develop a theory-driven system that supports patient engagement with dDPPs and their primary care providers with their care. Methods: This study will be conducted in 3 phases. In phase 1, we will use systematic UCD, Agile software development, and qualitative research methods to identify key user (patients, providers, clinical staff, digital health technologists, and content experts) requirements, constraints, and prioritization of high-impact features to design, develop, and refine a viable intervention prototype for the engagement system. In phase 2, we will conduct a single-arm feasibility pilot of the engagement system among patients with prediabetes and their primary care providers. In phase 3, we will conduct a 2-arm randomized controlled trial using the engagement system. Primary outcomes will be weight, BMI, and A1c at 6 and 12 months. Secondary outcomes will be patient engagement (use and activity) in the dDPP. The mediator variables (self-efficacy, digital health literacy, and patient-provider relationship) will be measured. Results: The project was initiated in 2018 and funded in September 2019. Enrollment and data collection for phase 1 began in September 2019 under an Institutional Review Board quality improvement waiver granted in July 2019. As of December 2020, 27 patients have been enrolled and first results are expected to be submitted for publication in early 2021. The study received Institutional Review Board approval for phases 2 and 3 in December 2020, and phase 2 enrollment is expected to begin in early 2021. Conclusions: Our findings will provide guidance for the design and development of technology to integrate dDPP platforms into existing clinical workflows. This will facilitate patient engagement in digital behavior change interventions and provider engagement in patients’ use of dDPPs. Integrated clinical tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient adherence to these programs and improved health outcomes by addressing barriers faced by both patients and providers. Further evaluation with pilot testing and a clinical trial will assess the effectiveness and implementation of these tools. Trial Registration: ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500 International Registered Report Identifier (IRRID): DERR1-10.2196/26750 %M 33560240 %R 10.2196/26750 %U http://www.researchprotocols.org/2021/2/e26750/ %U https://doi.org/10.2196/26750 %U http://www.ncbi.nlm.nih.gov/pubmed/33560240 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 2 %P e22220 %T A Web-Based Self-Management Support Prototype for Adults With Chronic Kidney Disease (My Kidneys My Health): Co-Design and Usability Testing %A Donald,Maoliosa %A Beanlands,Heather %A Straus,Sharon E %A Smekal,Michelle %A Gil,Sarah %A Elliott,Meghan J %A Herrington,Gwen %A Harwood,Lori %A Waldvogel,Blair %A Delgado,Maria %A Sparkes,Dwight %A Tong,Allison %A Grill,Allan %A Novak,Marta %A James,Matthew Thomas %A Brimble,K Scott %A Samuel,Susan %A Tu,Karen %A Farragher,Janine %A Hemmelgarn,Brenda R %+ Faculty of Medicine and Dentistry, University of Alberta, 2J2.01 Walter C MacKenzie Health Sciences Centre, Edmonton, AB, T6G 2B7, Canada, 1 780 492 9728, Brenda.Hemmelgarn@albertahealthservices.ca %K chronic kidney disease %K knowledge-to-action framework %K integrated knowledge translation %K patient engagement %K patient-oriented research %K self-management %K web-based intervention %D 2021 %7 9.2.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Supporting patients to self-manage their chronic kidney disease (CKD) has been identified as a research priority by patients with CKD and those who care for them. Self-management has been shown to slow CKD progression and improve the quality of life of individuals living with the disease. Previous work has identified a need for a person-centered, theory-informed, web-based tool for CKD self-management that can be individualized to a patient’s unique situation, priorities, and preferences. We addressed this gap using an integrated knowledge translation method and patient engagement principles. Objective: The aim of this study is to conduct systematic co-design and usability testing of a web-based self-management prototype for adults with CKD (nondialysis and nontransplant) and their caregivers to enhance self-management support. Methods: A multistep, iterative system development cycle was used to co-design and test the My Kidneys My Health prototype. The 3-step process included creating website features and content using 2 sequential focus groups with patients with CKD and caregivers, heuristic testing using the 10 heuristic principles by Nielsen, and usability testing through in-person 60-minute interviews with patients with CKD and their caregivers. Patients with CKD, caregivers, clinicians, researchers, software developers, graphic designers, and policy makers were involved in all steps of this study. Results: In step 1, 18 participants (14 patients and 4 caregivers) attended one of the 2 sequential focus groups. The participants provided specific suggestions for simplifying navigation as well as suggestions to incorporate video, text, audio, interactive components, and visuals to convey information. A total of 5 reviewers completed the heuristic analysis (step 2), identifying items mainly related to navigation and functionality. Furthermore, 5 participants completed usability testing (step 3) and provided feedback on video production, navigation, features and functionality, and branding. Participants reported visiting the website repeatedly for the following features: personalized food tool, my health care provider question list, symptom guidance based on CKD severity, and medication advice. Usability was high, with a mean system usability score of 90 out of 100. Conclusions: The My Kidneys My Health prototype is a systematically developed, multifaceted, web-based CKD self-management support tool guided by the theory and preferences of patients with CKD and their caregivers. The website is user friendly and provides features that improve user experience by tailoring the content and resources to their needs. A feasibility study will provide insights into the acceptability of and engagement with the prototype and identify preliminary patient-reported outcomes (eg, self-efficacy) as well as potential factors related to implementation. This work is relevant given the shift to virtual care during the current pandemic times and provides patients with support when in-person care is restricted. %M 33560245 %R 10.2196/22220 %U https://formative.jmir.org/2021/2/e22220 %U https://doi.org/10.2196/22220 %U http://www.ncbi.nlm.nih.gov/pubmed/33560245 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 2 %P e12218 %T Effectiveness of Text Message Reminders on Adherence to Inhaled Therapy in Patients With Asthma: Prospective Multicenter Randomized Clinical Trial %A Almonacid,Carlos %A Melero,Carlos %A López Viña,Antolín %A Cisneros,Carolina %A Pérez de Llano,Luis %A Plaza,Vicente %A García-Rivero,Juan Luis %A Romero Falcón,Auxiliadora %A Ramos,Jacinto %A Bazús González,Teresa %A Andrés Prado,María %A Muriel,Alfonso %+ Department of Respiratory Medicine, Instituto Ramón y Cajal de Investigación Sanitaria, University of Alcala de Henares, Ctra. De Colmenar Viejo, km. 9,100, Madrid, , Spain, 34 655 534 475, caralmsan@gmail.com %K asthma %K adherence %K SMS %K control %K cell phone %K inhaler %K Smartinhaler %D 2021 %7 9.2.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Poor adherence to inhaled medication in asthma patients is of great concern. It is one of the main reasons for inadequate asthma control. Objective: The goal of the research was to determine if motivational messages using short message service (SMS, or text) improved adherence to inhaled medication in patients with asthma. Methods: A prospective multicenter randomized parallel-group clinical trial was conducted in 10 asthma clinics in Spain. Adherence was assessed with electronic monitors (Smartinhaler, Adherium Ltd) connected to inhalers. Patients in the SMS group received psychologist-developed motivational messages every 3 days for 6 months. Results: There were 53 patients in the SMS group and 88 patients in the control group. After 6 months, mean electronic adherence was 70% (SD 17%) in the intervention group and 69% (SD 17%) in the control group (P=.82). Significant differences between the study groups in morning and evening adherence to inhaled therapy, asthma control, exhaled nitric oxide levels, or improvement of lung functions were not observed. Conclusions: Motivational messages were not useful to improve adherence to inhaled asthma medication compared with usual care. %M 33560235 %R 10.2196/12218 %U http://formative.jmir.org/2021/2/e12218/ %U https://doi.org/10.2196/12218 %U http://www.ncbi.nlm.nih.gov/pubmed/33560235 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 2 %P e22700 %T Predictors, Outcomes, and Statistical Solutions of Missing Cases in Web-Based Psychotherapy: Methodological Replication and Elaboration Study %A Karin,Eyal %A Crane,Monique Frances %A Dear,Blake Farran %A Nielssen,Olav %A Heller,Gillian Ziona %A Kayrouz,Rony %A Titov,Nickolai %+ Department of Psychology, Macquarie University, MindSpot Clinic, North Ryde, NSW, Macquarie Park, 2113, Australia, 61 448697082, eyal.karin@mq.edu.au %K psychotherapy %K treatment adherence and compliance %K missing data %K treatment evaluation %K statistical bias %D 2021 %7 5.2.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Missing cases present a challenge to our ability to evaluate the effects of web-based psychotherapy trials. As missing cases are often lost to follow-up, less is known about their characteristics, their likely clinical outcomes, or the likely effect of the treatment being trialed. Objective: The aim of this study is to explore the characteristics of missing cases, their likely treatment outcomes, and the ability of different statistical models to approximate missing posttreatment data. Methods: A sample of internet-delivered cognitive behavioral therapy participants in routine care (n=6701, with 36.26% missing cases at posttreatment) was used to identify predictors of dropping out of treatment and predictors that moderated clinical outcomes, such as symptoms of psychological distress, anxiety, and depression. These variables were then incorporated into a range of statistical models that approximated replacement outcomes for missing cases, and the results were compared using sensitivity and cross-validation analyses. Results: Treatment adherence, as measured by the rate of progress of an individual through the treatment modules, and higher pretreatment symptom scores were identified as the dominant predictors of missing cases probability (Nagelkerke R2=60.8%) and the rate of symptom change. Low treatment adherence, in particular, was associated with increased odds of presenting as missing cases during posttreatment assessment (eg, odds ratio 161.1:1) and, at the same time, attenuated the rate of symptom change across anxiety (up to 28% of the total symptom with 48% reduction effect), depression (up to 41% of the total with 48% symptom reduction effect), and psychological distress symptom outcomes (up to 52% of the total with 37% symptom reduction effect) at the end of the 8-week window. Reflecting this pattern of results, statistical replacement methods that overlooked the features of treatment adherence and baseline severity underestimated missing case symptom outcomes by as much as 39% at posttreatment. Conclusions: The treatment outcomes of the cases that were missing at posttreatment were distinct from those of the remaining observed sample. Thus, overlooking the features of missing cases is likely to result in an inaccurate estimate of the effect of treatment. %M 33544080 %R 10.2196/22700 %U https://mental.jmir.org/2021/2/e22700 %U https://doi.org/10.2196/22700 %U http://www.ncbi.nlm.nih.gov/pubmed/33544080 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 2 %P e21207 %T Optimizing the Context of Support to Improve Outcomes of Internet-Based Self-help in Individuals With Depressive Symptoms: Protocol for a Randomized Factorial Trial %A Bur,Oliver Thomas %A Krieger,Tobias %A Moritz,Steffen %A Klein,Jan Philipp %A Berger,Thomas %+ Department of Clinical Psychology and Psychotherapy, University of Bern, Fabrikstrasse 8, Bern, 3012, Switzerland, 41 31 631 54 13, oliver.bur@psy.unibe.ch %K depression %K self-help %K adherence %K internet-based intervention %K factorial design %K problem-solving therapy %K online %K mental health %K multiphase optimization strategy %K digital health %D 2021 %7 2.2.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Internet-based self-help interventions for individuals with depressive symptoms, in which the main component is often a web-based self-help program, have been shown to be efficacious in many controlled trials. However, there are also trials on self-help programs showing no significant effect when delivered in routine care, and some studies report high dropout and low adherence rates. Research suggests that these findings do not emerge primarily due to the specific content of a self-help program. It seems more important how a program is embedded in the context of human and automated support before and during the use of a self-help program. Objective: This study aims to better understand the effects of 4 supportive contextual factors on outcomes of and adherence to a web-based self-help program for depressive symptoms. In a factorial experiment, 2 of 4 supportive factors, for which there is evidence for their role on outcomes and adherence, are realized during the intervention—personal guidance and automated email reminders. The other 2 factors are realized before the intervention—a diagnostic interview and a preintervention module aimed at increasing the motivation to use the program with motivational interviewing techniques. Methods: The study is a full factorial randomized trial. Adults with mild to moderate depressive symptoms (Patient Health Questionnaire–9 score: 5-14) are recruited from the community through the internet and conventional media. All participants receive access to a web-based self-help program based on problem-solving therapy. They are randomized across 4 experimental factors, each reflecting the presence versus absence of a supportive factor (guidance, automated reminders, diagnostic interview, preintervention module) resulting in a 16-condition balanced factorial design. The primary outcome is depressive symptoms at 10 weeks post assessment. Secondary outcomes include adherence to the program, anxiety, stress, health-related quality of life, possible negative effects, and treatment satisfaction. Potential moderators and mediators (eg, treatment expectancy, problem-solving skills, working alliance with the study team) will also be investigated. Results: Ethical approval was received on January 20, 2020. The study was initiated in February 2020, and 240 participants have been enrolled in the study as of November 1, 2020. Recruitment for a total of 255 participants is ongoing. Data collection is expected to be completed by May 2021. Conclusions: A better understanding of relevant supportive factors in the dissemination of web-based interventions is necessary to improve outcomes of and adherence to web-based self-help programs. This study may inform health care systems and guide decisions to optimize the implementation context of web-based self-help programs for depressive symptoms. Trial Registration: ClinicalTrials.gov NCT04318236; https://clinicaltrials.gov/ct2/show/NCT04318236 International Registered Report Identifier (IRRID): DERR1-10.2196/21207 %M 33528377 %R 10.2196/21207 %U http://www.researchprotocols.org/2021/2/e21207/ %U https://doi.org/10.2196/21207 %U http://www.ncbi.nlm.nih.gov/pubmed/33528377 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e21636 %T Factors Associated With Dropout of Participants in an App-Based Child Injury Prevention Study: Secondary Data Analysis of a Cluster Randomized Controlled Trial %A Li,Jie %A Ning,Peishan %A Cheng,Peixia %A Schwebel,David C %A Yang,Yang %A Wei,Xiang %A He,Jieyi %A Wang,Wanhui %A Li,Ruotong %A Hu,Guoqing %+ Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, 110 Xiangya Road, Changsha, 410078, China, 86 731 84805414, huguoqing009@gmail.com %K app-based intervention %K unintentional injury %K attrition %K influencing factors %D 2021 %7 29.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Mobile health (mHealth) interventions offer great potential to reach large populations and improve public health. However, high attrition rates threaten evaluation and implementation of mHealth intervention studies. Objective: We explored factors associated with attrition of study participants in an mHealth randomized controlled trial (RCT) evaluating an intervention to reduce unintentional child injury risk in China. Methods: The cluster RCT compared two groups of an app-based intervention for caregivers of 3-6–year-old children (Bao Hu San). The intervention group received unintentional child injury and parenting education, whereas only parenting education was implemented in the control group. The trial included 2920 study participants in Changsha, China, and lasted 6 months. Data on participant engagement (using the app) were collected electronically throughout the 6-month period. Associations between participant attrition and demographic characteristics, and between attrition and intervention engagement were tested and quantified separately for the intervention and control groups using the adjusted odds ratio (aOR) based on generalized linear mixed models. Results: In total, 2920 caregivers from 20 eligible preschools participated, with 1510 in the intervention group and 1410 in the control group. The 6-month attrition rate differed significantly between the two groups (P<.001), at 28.9% (437/1510) in the intervention group and 35.7% (503/1410) in the control group. For the intervention group, the only significant predictor of attrition risk was participants who learned fewer knowledge segments (aOR 2.69, 95% CI 1.19-6.09). For the control group, significant predictors of attrition risk were lower monthly login frequency (aOR 1.48, 95% CI 1.00-2.18), learning fewer knowledge segments (aOR 1.70, 95% CI 1.02-2.81), and shorter learning durations during app engagement (aOR 2.39, 95% CI 1.11-5.15). Demographic characteristics were unrelated to attrition. Conclusions: Engagement in the app intervention was associated with participant attrition. Researchers and practitioners should consider how to best engage participants in app-based interventions to reduce attrition. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IOR-17010438; http://www.chictr.org.cn/showproj.aspx?proj=17376 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5790-1 %M 33512318 %R 10.2196/21636 %U https://www.jmir.org/2021/1/e21636 %U https://doi.org/10.2196/21636 %U http://www.ncbi.nlm.nih.gov/pubmed/33512318 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 1 %P e24662 %T Association Between Care Utilization and Anxiety Outcomes in an On-Demand Mental Health System: Retrospective Observational Study %A Kunkle,Sarah %A Yip,Manny %A Hunt,Justin %A Ξ,Watson %A Udall,Dana %A Arean,Patricia %A Nierenberg,Andrew %A Naslund,John A %+ Ginger, 116 New Montgomery Street, San Francisco, CA, United States, 1 7175197355, sarah@ginger.io %K mental health %K digital health %K anxiety %K telehealth %K virtual care %K utilization %K outcome %K retrospective %K observational %D 2021 %7 26.1.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Anxiety is an extremely prevalent condition, and yet, it has received notably less attention than depression and other mental health conditions from a research, clinical, and public health perspective. The COVID-19 pandemic has only exacerbated growing concerns about the burden of anxiety due to the confluence of physical health risks, economic stressors, social isolation, and general disruption of daily activities. Objective: This study examines differences in anxiety outcomes by care modality (coaching, teletherapy and telepsychiatry, and combined care) within an on-demand mental health system. We also explore the association between levels of engagement within each care modality and odds of improvement in symptoms of anxiety. Methods: We conducted a retrospective observational study of individuals who accessed Ginger, an on-demand mental health system. Data were collected from 1611 Ginger members between January 1, 2018, and December 31, 2019. We used logistic regression to assess the association between care modality and improvement in anxiety symptoms. Within each modality, we assessed the association between level of engagement and improvement. Results: Of 1611 Ginger members, 761 (47.0%) experienced a decrease in anxiety symptoms, as measured by a change from a positive to a negative 2-item Generalized Anxiety Disorder (GAD-2) screen. Among members who still screened positive at follow-up (865/1611, 53%), a total of 192 members (11.9%) experienced a clinically significant score reduction in the full GAD-7 (ie, a score reduction of >5 points), even though their GAD-2 scores were still positive. All modalities showed increased odds of improvement compared to those who were not engaged with coaching or clinical services (“app-only”). Higher GAD-7 intake scores were also associated with decreased odds of improvement. Conclusions: This study found increased odds of anxiety improvement for all care modalities compared to those who did not engage in care, with larger effect sizes for higher utilization within all care modalities. Additionally, there is a promising observation that those engaged in combined care (teletherapy and text-based coaching) had the greatest odds of anxiety improvement. Future directions include more detailed classifications of utilization patterns and an exploration of explanations and solutions for lower-utilization members. %M 33496679 %R 10.2196/24662 %U http://formative.jmir.org/2021/1/e24662/ %U https://doi.org/10.2196/24662 %U http://www.ncbi.nlm.nih.gov/pubmed/33496679 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e23946 %T Impact of COVID-19 on Physical Activity Among 10,000 Steps Members and Engagement With the Program in Australia: Prospective Study %A To,Quyen G %A Duncan,Mitch J %A Van Itallie,Anetta %A Vandelanotte,Corneel %+ Appleton Institute, School of Health, Medical and Applied Sciences, Central Queensland University, 554-700 Yaamba Rd, Rockhampton, 4701, Australia, 61 7 4930 6456, q.to@cqu.edu.au %K exercise %K pandemic %K lockdown %K eHealth %K physical activity %K COVID-19 %K engagement %K behavior %D 2021 %7 25.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Physical activity is an important health behavior, due to its association with many physical and mental health conditions. During distressing events, such as the COVID-19 pandemic, there is a concern that physical activity levels may be negatively impacted. However, recent studies have shown inconsistent results. Additionally, there is a lack of studies in Australia on this topic. Objective: The aim of this study is to investigate changes in physical activity reported through the 10,000 Steps program and changes in engagement with the program during the COVID-19 pandemic. Methods: Data between January 1, 2018, and June 30, 2020, from registered members of the 10,000 Steps program, which included 3,548,825 days with step data, were used. The number of daily steps were logged manually by the members or synced automatically from their activity trackers connected to the program. Measures on program usage were the number of new registered members per day, the number of newly registered organizations per day, the number of steps logged per day, and the number of step entries per day. Key dates used for comparison were as follows: the first case with symptoms in Wuhan, China; the first case reported in Australia; the implementation of a 14-day ban for noncitizens arriving in Australia from China; the start of the lockdown in Australia; and the relaxing of restrictions by the Australian Government. Wilcoxon signed-rank tests were used to test for significant differences in number of steps between subgroups, between engagement measures in 2019 versus 2020, and before and after an event. Results: A decrease in steps was observed after the first case in Australia was reported (1.5%; P=.02) and after the start of the lockdown (3.4%; P<.001). At the time that the relaxing of restrictions started, the steps had already recovered from the lockdown. Additionally, the trends were consistent across genders and age groups. New South Wales, Australian Capital Territory, and Victoria had the greatest step reductions, with decreases of 7.0% (P<.001), 6.2% (P=.02), and 4.7% (P<.001), respectively. During the lockdown, the use of the program increased steeply. On the peak day, there were more than 9000 step entries per day, with nearly 100 million steps logged per day; in addition, more than 450 new users and more than 15 new organizations registered per day, although the numbers decreased quickly when restrictions were relaxed. On average per day, there were about 55 new registered users (P<.001), 2 new organizations (P<.001), 25.6 million steps (P<.001), and 2672 log entries (P<.001) more in 2020 compared to the same period in 2019. Conclusions: The pandemic has had negative effects on steps among Australians across age groups and genders. However, the effect was relatively small, with steps recovering quickly after the lockdown. There was a large increase in program usage during the pandemic, which might help minimize the health impact of the lockdown and confirms the important role of physical activity programs during times of distress and lockdowns. %M 33449907 %R 10.2196/23946 %U http://www.jmir.org/2021/1/e23946/ %U https://doi.org/10.2196/23946 %U http://www.ncbi.nlm.nih.gov/pubmed/33449907 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 1 %P e19384 %T Improving Treatment Adherence and Retention of HIV-Positive Women Through Behavioral Change Interventions Aimed at Their Male Partners: Protocol for a Prospective, Controlled Before-and-After Study %A Orlando,Stefano %A Palla,Ilaria %A Ciccacci,Fausto %A Triulzi,Isotta %A Thole,Darlington %A Sangaré,Hawa Mamary %A Marazzi,Maria Cristina %A Nielsen-Saines,Karin %A Turchetti,Giuseppe %A Palombi,Leonardo %+ Department of Biomedicine, University of Tor Vergata, Via Montpellier 1, Rome, 00133, Italy, 39 067259 ext 6798, stefano.orlando@uniroma2.it %K retention in care %K therapeutic adherence and compliance %K men's role %K acquired immunodeficiency syndrome %K AIDS %K HIV %K behavior %K intervention study %K health education %K community health education %K Malawi %K mother-to-child transmission %K health-related behavior %K social ecology %D 2021 %7 25.1.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: According to the World Health Organization, in 2018, 37.9 million people were living with HIV globally. More than two-thirds were residing in sub-Saharan Africa, where the HIV prevalence in the adult population (aged 15-49 years) was 3.9%. This population included 1.3 million pregnant women, of whom 82% had received antiretroviral therapy (ART) for the prevention of HIV mother-to-child transmission. In these countries, one challenge is an insufficient level of treatment adherence, particularly in HIV-positive pregnant women. Among the causes, the lack of involvement from a male partner is a significant contributor to the problem. This issue has strongly emerged in Malawi, one of the countries with the highest HIV prevalence in the world: 9.2% of its adult population were living with HIV in 2018. Objective: This study aims to assess 3 interventions that are aimed at improving ART adherence and retention among HIV-positive women through engagement with their male partners in 4 Malawian health care centers. Methods: The prospective, controlled before-and-after study is conducted in 3 phases (total duration: 24 months): preintervention, intervention, and postintervention analyses. The number of selected clusters (clinical centers) is limited to 4: one for each intervention, plus a cluster where no intervention is performed (control arm). The interventions are as follows: opening the facility on one Saturday per month only for men, defined as a special day; testing peer-to-peer counseling among men, male champions; and providing a noneconomic incentive to all women who are accompanied by their partners to the facility, nudge. The primary outcome of the study is to evaluate the differences in retention in care and adherence to therapeutic protocols among women; the intermediate outcome is the assessment of differences in male involvement. The level of male involvement in the health of their partners (intermediate outcome) will be evaluated through a dedicated questionnaire administered at baseline and in the postintervention phase. Data will be collected at the clinical centers and stored in 2 electronic databases managed using 2 different types of software. Results: The analysis of data collected in the 4 centers during the preintervention phase is ongoing, as enrollment ended on March 31, 2020. The total number of patients enrolled was 452 (Namandanje: 133; Kapeni: 78; Kapire: 75; and Balaka: 166). Meanwhile, several meetings have been conducted to organize the intervention phase. Conclusions: The study will identify the best intervention that enhances the involvement of male partners in women’s health, using an approach that considers a broad spectrum of behaviors. An important aspect is the use of educational tools focused on messages, thereby initiating a reflective discussion of stereotypes and false beliefs related to the idea of masculinity present in the Malawian culture. International Registered Report Identifier (IRRID): DERR1-10.2196/19384 %M 33492232 %R 10.2196/19384 %U http://www.researchprotocols.org/2021/1/e19384/ %U https://doi.org/10.2196/19384 %U http://www.ncbi.nlm.nih.gov/pubmed/33492232 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 1 %P e20860 %T A Blended Electronic Illness Management and Recovery Program for People With Severe Mental Illness: Qualitative Process Evaluation Alongside a Randomized Controlled Trial %A Beentjes,Titus A A %A van Gaal,Betsie G I %A Vermeulen,Hester %A Nijhuis-van der Sanden,Maria W G %A Goossens,Peter J J %+ Dimence Group Mental Health Care Centre, Pikeursbaan 3, Deventer, 7411 GT, Netherlands, 31 651284459, titus.beentjes@radboudumc.nl %K mental health recovery %K self-management %K telemedicine %K mental health services %K qualitative research %D 2021 %7 20.1.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: We conducted a trial to test the electronic Illness Management and Recovery (e-IMR) intervention to provide conclusions on the potential efficacy of eHealth for people with severe mental illness (SMI). In the e-IMR intervention, we used the standard IMR program content and methodology and combined face-to-face sessions with internet-based strategies on the constructed e-IMR internet platform. During the trial, the e-IMR platform was sparsely used. Objective: This study aimed to evaluate the added value of the e-IMR intervention and the barriers and facilitators that can explain the low use of the e-IMR platform. Methods: This process evaluation was designed alongside a multicenter, cluster randomized controlled trial. In this study, we included all available participants and trainers from the intervention arm of the trial. Baseline characteristics were used to compare users with nonusers. Qualitative data were gathered at the end of the semistructured interviews. Using theoretical thematic analyses, the data were analyzed deductively using a pre-existing coding frame. Results: Out of 41 eligible participants and 14 trainers, 27 participants and 11 trainers were interviewed. Of the 27 participants, 10 were identified as users. eHealth components that had added value were the persuasive nature of the goal-tracking sheets, monitoring, and the peer testimonials, which had the potential to enhance group discussions and disclosure by participants. The low use of the e-IMR platform was influenced by the inflexibility of the platform, the lack of information technology (IT) resources, the group context, participants’ low computer skills and disabilities, and the hesitant eHealth attitude of the trainers. Conclusions: The extent of eHealth readiness and correlations with vulnerabilities in persons with SMI need further investigation. This study shows that flexible options were needed for the use of e-IMR components and that options should be provided only in response to a participant’s need. Use of the e-IMR intervention in the future is preconditioned by checking the available IT resources (such as tablets for participants) providing computer or internet guidance to participants outside the group sessions, evaluating the eHealth attitude and skills of trainers, and tailoring eHealth training to increase the skills of future e-IMR trainers. Trial Registration: Netherlands Trial Register NTR4772; https://www.trialregister.nl/trial/4621 International Registered Report Identifier (IRRID): RR2-10.1186/s12913-016-1267-z %M 33470945 %R 10.2196/20860 %U http://mental.jmir.org/2021/1/e20860/ %U https://doi.org/10.2196/20860 %U http://www.ncbi.nlm.nih.gov/pubmed/33470945 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e24773 %T Adherence of Mobile App-Based Surveys and Comparison With Traditional Surveys: eCohort Study %A Pathiravasan,Chathurangi H %A Zhang,Yuankai %A Trinquart,Ludovic %A Benjamin,Emelia J %A Borrelli,Belinda %A McManus,David D %A Kheterpal,Vik %A Lin,Honghuang %A Sardana,Mayank %A Hammond,Michael M %A Spartano,Nicole L %A Dunn,Amy L %A Schramm,Eric %A Nowak,Christopher %A Manders,Emily S %A Liu,Hongshan %A Kornej,Jelena %A Liu,Chunyu %A Murabito,Joanne M %+ Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Crosstown 2, 201 Massachusetts Ave, Boston, MA, 02118, United States, 1 508 935 3461, murabito@bu.edu %K eCohort %K mobile health %K mHealth %K smartphone %K survey %K app %K Framingham Heart Study %K adherence %K agreement %K cardiovascular disease %D 2021 %7 20.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: eCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection. Objective: The aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center. Methods: We defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC). Results: Among the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77). Conclusions: We observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors. %M 33470944 %R 10.2196/24773 %U http://www.jmir.org/2021/1/e24773/ %U https://doi.org/10.2196/24773 %U http://www.ncbi.nlm.nih.gov/pubmed/33470944 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 1 %P e19465 %T Habits Heart App for Patient Engagement in Heart Failure Management: Pilot Feasibility Randomized Trial %A Wei,Kevin S %A Ibrahim,Nasrien E %A Kumar,Ashok A %A Jena,Sidhant %A Chew,Veronica %A Depa,Michal %A Mayanil,Namrata %A Kvedar,Joseph C %A Gaggin,Hanna K %+ Cardiology Division, Massachusetts General Hospital, 55 Fruit Street, Yawkey 5B, Boston, MA, 02114, United States, 1 617 726 2709, HGAGGIN@mgh.harvard.edu %K heart failure %K smartphone application %K heart failure management %D 2021 %7 20.1.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Due to the complexity and chronicity of heart failure, engaging yet simple patient self-management tools are needed. Objective: This study aimed to assess the feasibility and patient engagement with a smartphone app designed for heart failure. Methods: Patients with heart failure were randomized to intervention (smartphone with the Habits Heart App installed and Bluetooth-linked scale) or control (paper education material) groups. All intervention group patients were interviewed and monitored closely for app feasibility while receiving standard of care heart failure management by cardiologists. The Atlanta Heart Failure Knowledge Test, a quality of life survey (Kansas City Cardiomyopathy Questionnaire), and weight were assessed at baseline and final visits. Results: Patients (N=28 patients; intervention: n=15; control: n=13) with heart failure (with reduced ejection fraction: 15/28, 54%; male: 20/28, 71%, female: 8/28, 29%; median age 63 years) were enrolled, and 82% of patients (N=23; intervention: 12/15, 80%; control: 11/13, 85%) completed both baseline and final visits (median follow up 60 days). In the intervention group, 2 out of the 12 patients who completed the study did not use the app after study onboarding due to illnesses and hospitalizations. Of the remaining 10 patients who used the app, 5 patients logged ≥1 interaction with the app per day on average, and 2 patients logged an interaction with the app every other day on average. The intervention group averaged 403 screen views (per patient) in 56 distinct sessions, 5-minute session durations, and 22 weight entries per patient. There was a direct correlation between duration of app use and improvement in heart failure knowledge (Atlanta Heart Failure Knowledge Test score; ρ=0.59, P=.04) and quality of life (Kansas City Cardiomyopathy Questionnaire score; ρ=0.63, P=.03). The correlation between app use and weight change was ρ=–0.40 (P=.19). Only 1 out of 11 patients in the control group retained education material by the follow-up visit. Conclusions: The Habits Heart App with a Bluetooth-linked scale is a feasible way to engage patients in heart failure management, and barriers to app engagement were identified. A larger multicenter study may be warranted to evaluate the effectiveness of the app. Trial Registration: ClinicalTrials.gov NCT03238729; http://clinicaltrials.gov/ct2/show/NCT03238729 %M 33470941 %R 10.2196/19465 %U http://mhealth.jmir.org/2021/1/e19465/ %U https://doi.org/10.2196/19465 %U http://www.ncbi.nlm.nih.gov/pubmed/33470941 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e17500 %T Patients’ Perspectives About Factors Affecting Their Use of Electronic Personal Health Records in England: Qualitative Analysis %A Abd-Alrazaq,Alaa %A Safi,Zeineb %A Bewick,Bridgette M %A Househ,Mowafa %A Gardner,Peter H %+ Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, LAS Building,, Education city, Doha, RD5256, Qatar, 974 55708549, alaa_alzoubi88@yahoo.com %K electronic personal health records %K tethered personal health records %K patient portal %K patient online %K technology acceptance %K technology adoption %K qualitative research %K mobile phone %D 2021 %7 13.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: General practices (GPs) in England have recently introduced a nationwide electronic personal health record (ePHR) system called Patient Online or GP online services, which allows patients to view parts of their medical records, book appointments, and request prescription refills. Although this system is free of charge, its adoption rates are low. To improve patients’ adoption and implementation success of the system, it is important to understand the factors affecting their use of the system. Objective: The aim of this study is to explore patients’ perspectives of factors affecting their use of ePHRs in England. Methods: A cross-sectional survey was carried out between August 21 and September 26, 2017. A questionnaire was used in this survey to collect mainly quantitative data through closed-ended questions in addition to qualitative data through an open-ended question. A convenience sample was recruited in 4 GPs in West Yorkshire, England. Given that the quantitative data were analyzed in a previous study, we analyzed the qualitative data using thematic analysis. Results: Of the 800 eligible patients invited to participate in the survey, 624 (78.0%) returned a fully completed questionnaire. Of those returned questionnaires, the open-ended question was answered by 136/624 (21.8%) participants. A total of 2 meta-themes emerged from participants’ responses. The first meta-theme comprises 5 themes about why patients do not use Patient Online: concerns about using Patient Online, lack of awareness of Patient Online, challenges regarding internet and computers, perceived characteristics of nonusers, and preference for personal contact. The second meta-theme contains 1 theme about why patients use Patient Online: encouraging features of Patient Online. Conclusions: The challenges and concerns that impede the use of Patient Online seem to be of greater importance than the facilitators that encourage its use. There are practical considerations that, if incorporated into the system, are likely to improve its adoption rate: Patient Online should be useful, easy to use, secure, and easy to access. Different channels should be used to increase the awareness of the system, and GPs should ease registration with the system and provide manuals, training sessions, and technical support. More research is needed to assess the effect of the new factors found in this study (eg, lack of trust, difficulty registering with Patient Online) and factors affecting the continuing use of the system. %M 33439126 %R 10.2196/17500 %U http://www.jmir.org/2021/1/e17500/ %U https://doi.org/10.2196/17500 %U http://www.ncbi.nlm.nih.gov/pubmed/33439126 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 1 %P e18021 %T Assessing the Effectiveness and Acceptability of a Personalized Mobile Phone App in Improving Adherence to Oral Hygiene Advice in Orthodontic Patients: Protocol for a Feasibility Study and a Randomized Controlled Trial %A Sharif,Mohammad Owaise %A Newton,Jonathon Timothy %A Cunningham,Susan J %+ Eastman Dental Institute, University College London, Rockefeller Building, 21 University Street, London, WC1E 6DE, United Kingdom, 44 02034561067, mohammad.sharif.16@ucl.ac.uk %K orthodontics %K adherence %K smartphone apps %K mobile phone apps %K personalized health care %K information provision %D 2021 %7 13.1.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Orthodontic treatment is a common health care intervention; treatment duration can be lengthy (2-3 years on average), and adherence to treatment advice is therefore essential for successful outcomes. It has been reported that up to 43% of patients fail to complete treatment, and there are currently no useful predictors of noncompletion. Given that the National Health Service England annual expenditure on primary-care orthodontic treatment is in excess of £200 million (US $267 million), noncompletion of treatment represents a significant inefficient use of public resources. Improving adherence to treatment is therefore essential. This necessitates behavior change, and interventions that improve adherence and are designed to elicit behavioral change must address an individual’s capability, opportunity, and motivation. Mobile phones are potentially an invaluable tool in this regard, as they are readily available and can be used in a number of ways to address an individual’s capability, opportunity, and motivation. Objective: This study will assess the effectiveness and acceptability of a personalized mobile phone app in improving adherence to orthodontic treatment advice by way of a randomized controlled trial. Methods: This study will be conducted in 2 phases at the Eastman Dental Hospital, University College London Hospitals Foundation Trust. Phase 1 is feasibility testing of the My Braces app. Participants will be asked to complete the user version of the Mobile Application Rating Scale. The app will be amended following analysis of the responses, if appropriate. Phase 2 is a randomized controlled trial to test the effectiveness and acceptability of the My Braces app. Results: This study was approved by the London – Bloomsbury Research Ethics Committee on November 5, 2019 (reference 19/LO/1555). No patients have been recruited to date. The anticipated start date for recruitment to phase 1 is October 2020. Conclusions: Given the availability, affordability, and versatility of mobile phones, it is proposed that they will aid in improving adherence to treatment advice and hence improve treatment completion rates. If effective, the applicability of this methodology to developing behavior change/modification interventions and improving adherence to treatment across health care provides an exciting opportunity. Trial Registration: ClinicalTrials.gov NCT04184739; https://clinicaltrials.gov/ct2/show/NCT04184739 International Registered Report Identifier (IRRID): PRR1-10.2196/18021 %M 33439142 %R 10.2196/18021 %U http://www.researchprotocols.org/2021/1/e18021/ %U https://doi.org/10.2196/18021 %U http://www.ncbi.nlm.nih.gov/pubmed/33439142 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e22184 %T Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study %A Kwon,Hongwook %A Kim,Ho Heon %A An,Jaeil %A Lee,Jae-Ho %A Park,Yu Rang %+ Department of Biomedical Systems Informatics, College of Medicine, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea, 82 2 2228 2493, yurangpark@yuhs.ac %K churn prediction %K digital health care %K life-log data %K topic modeling %K recurrent neural network %K deep learning interpretation %K attribution method %K integrated gradients %K digital health %K prediction %K model %K data %K app %K observational %K time-series %K neural network %D 2021 %7 6.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Customer churn is the rate at which customers stop doing business with an entity. In the field of digital health care, user churn prediction is important not only in terms of company revenue but also for improving the health of users. Churn prediction has been previously studied, but most studies applied time-invariant model structures and used structured data. However, additional unstructured data have become available; therefore, it has become essential to process daily time-series log data for churn predictions. Objective: We aimed to apply a recurrent neural network structure to accept time-series patterns using lifelog data and text message data to predict the churn of digital health care users. Methods: This study was based on the use data of a digital health care app that provides interactive messages with human coaches regarding food, exercise, and weight logs. Among the users in Korea who enrolled between January 1, 2017 and January 1, 2019, we defined churn users according to the following criteria: users who received a refund before the paid program ended and users who received a refund 7 days after the trial period. We used long short-term memory with a masking layer to receive sequence data with different lengths. We also performed topic modeling to vectorize text messages. To interpret the contributions of each variable to model predictions, we used integrated gradients, which is an attribution method. Results: A total of 1868 eligible users were included in this study. The final performance of churn prediction was an F1 score of 0.89; that score decreased by 0.12 when the data of the final week were excluded (F1 score 0.77). Additionally, when text data were included, the mean predicted performance increased by approximately 0.085 at every time point. Steps per day had the largest contribution (0.1085). Among the topic variables, poor habits (eg, drinking alcohol, overeating, and late-night eating) showed the largest contribution (0.0875). Conclusions: The model with a recurrent neural network architecture that used log data and message data demonstrated high performance for churn classification. Additionally, the analysis of the contribution of the variables is expected to help identify signs of user churn in advance and improve the adherence in digital health care. %M 33404511 %R 10.2196/22184 %U https://www.jmir.org/2021/1/e22184 %U https://doi.org/10.2196/22184 %U http://www.ncbi.nlm.nih.gov/pubmed/33404511 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 8 %N 4 %P e23734 %T Effects of a Mobile App Called Quittr, Which Utilizes Premium Currency and Games Features, on Improving Engagement With Smoking Cessation Intervention: Pilot Randomized Controlled Trial %A Bindoff,Ivan %A Ling,Tristan R %A Gee,Peter %A Geelan,Benjamin %A Ferguson,Stuart G %A Peterson,Gregory M %+ School of Pharmacy and Pharmacology, University of Tasmania, 1 Churchill Ave, Sandy Bay, 7005, Australia, 61 408528276, Ivan.Bindoff@utas.edu.au %K smoking %K cessation %K Quittr %K engagement %K retention %K churn %K cigarette %K mHealth %K game %D 2020 %7 14.12.2020 %9 Original Paper %J JMIR Serious Games %G English %X Background: Numerous mobile health (mHealth) apps have been developed to support smokers attempting to quit smoking. Although these apps have been reported to be successful, only modest improvements in the quit rate have been measured. It has been proposed that efforts to improve user engagement and retention may improve the quit rate further. Owing to the high cost of smoking-related disease, it is considered worthwhile to pursue even small improvements. Objective: The aim of this study was to test a novel smartphone app that leverages premium currency strategies developed by the mobile games industry in an attempt to improve engagement and retention with a smoking cessation intervention. Methods: We designed and developed a smoking cessation app called “Quittr” in line with previously developed smoking cessation mHealth apps. In addition to this established framework, we added a stand-alone fully featured city-building clicker-style game called “Tappy Town,” and a premium virtual currency called “QuitCoins.” The user earns QuitCoins for using the app in a way that contributes positively toward their quit attempt, and they can redeem these coins in Tappy Town for bonuses. To establish whether these features improved engagement and retention, we ran a 5-month randomized controlled trial where the intervention group had the full app with the extra games features, while the control group had the standard app only. Recruitment was performed via web-based advertising. Participants (N=175) had no direct contact with the researchers or other support staff. Results: No significant differences in terms of engagement, retention, or smoking outcomes were found between the control and intervention groups. However, survey data indicated that the majority of the participants valued Tappy Town (10/17, 59%) and the QuitCoins rewards system (13/17, 77%). Usage data also suggested that Tappy Town was widely played and was generally appealing to users (mean total time spent in app, control group: 797 seconds vs intervention group: 3502 seconds, P<.001). Analysis of the results suggests that users in the intervention group may have been negatively affected by the aspects of the chosen design, and some theories were explored to explain this unexpected outcome. Conclusions: Although the novel features of the Quittr app failed to improve the key outcomes measured in this study, there were enough positive indications to warrant further exploration of the concept. Additional research will be required to identify and correct any design flaws that may have adversely affected our participants before a follow-up study can be completed. Trial Registration: Australian and New Zealand Clinical Trials Register ACTRN12617000491369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372661&isReview=true %M 33315016 %R 10.2196/23734 %U http://games.jmir.org/2020/4/e23734/ %U https://doi.org/10.2196/23734 %U http://www.ncbi.nlm.nih.gov/pubmed/33315016 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e23369 %T Engagement With a Behavior Change App for Alcohol Reduction: Data Visualization for Longitudinal Observational Study %A Bell,Lauren %A Garnett,Claire %A Qian,Tianchen %A Perski,Olga %A Williamson,Elizabeth %A Potts,Henry WW %+ Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom, 44 02076368636, lauren.bell@lshtm.ac.uk %K mobile health %K behavior change %K apps %K digital health %K data visualizations %K engagement %K micro-randomized trial %K push notifications %K just-in-time adaptive interventions %D 2020 %7 11.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Behavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich. Objective: This study aims to visualize behavioral engagement with Drink Less, a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom. Methods: We explored behavioral engagement among 19,233 existing users of Drink Less. Users were included in the sample if they were from the United Kingdom; were 18 years or older; were interested in reducing their alcohol consumption; had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking; and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots. Results: The daily 11 AM notification is strongly associated with a change in engagement in the following hour; reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download; identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users); and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the Self-monitoring and Feedback module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings. Conclusions: Visualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with Drink Less. Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within Drink Less by tailoring to contextual circumstances of individuals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT. %M 33306026 %R 10.2196/23369 %U http://www.jmir.org/2020/12/e23369/ %U https://doi.org/10.2196/23369 %U http://www.ncbi.nlm.nih.gov/pubmed/33306026 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e21687 %T Design Features for Improving Mobile Health Intervention User Engagement: Systematic Review and Thematic Analysis %A Wei,Yanxia %A Zheng,Pinpin %A Deng,Hui %A Wang,Xihui %A Li,Xiaomei %A Fu,Hua %+ School of Public Health, Fudan University, 138 Yixueyuan Road, Shanghai, 200030, China, 86 021 54237202, zpinpin@shmu.edu.cn %K mHealth %K design feature %K user engagement %K thematic synthesis analysis %D 2020 %7 9.12.2020 %9 Review %J J Med Internet Res %G English %X Background: Well-designed mobile health (mHealth) interventions support a positive user experience; however, a high rate of disengagement has been reported as a common concern regarding mHealth interventions. To address this issue, it is necessary to summarize the design features that improve user engagement based on research over the past 10 years, during which time the popularity of mHealth interventions has rapidly increased due to the use of smartphones. Objective: The aim of this review was to answer the question “Which design features improve user engagement with mHealth interventions?” by summarizing published literature with the purpose of guiding the design of future mHealth interventions. Methods: This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. Databases, namely, PubMed, Web of Science, Cochrane Library, Ovid EMBASE, and Ovid PsycINFO, were searched for English and Chinese language papers published from January 2009 to June 2019. Thematic analysis was undertaken to assess the design features in eligible studies. The Mixed Methods Appraisal Tool was used to assess study quality. Results: A total of 35 articles were included. The investigated mHealth interventions were mainly used in unhealthy lifestyle (n=17) and chronic disease (n=10) prevention programs. Mobile phone apps (n=24) were the most common delivery method. Qualitative (n=22) and mixed methods (n=9) designs were widely represented. We identified the following 7 themes that influenced user engagement: personalization (n=29), reinforcement (n=23), communication (n=20), navigation (n=17), credibility (n=16), message presentation (n=16), and interface aesthetics (n=7). A checklist was developed that contained these 7 design features and 29 corresponding specific implementations derived from the studies. Conclusions: This systematic review and thematic synthesis identified useful design features that make an mHealth intervention more user friendly. We generated a checklist with evidence-based items to enable developers to use our findings easily. Future evaluations should use more robust quantitative approaches to elucidate the relationships between design features and user engagement. %M 33295292 %R 10.2196/21687 %U https://www.jmir.org/2020/12/e21687 %U https://doi.org/10.2196/21687 %U http://www.ncbi.nlm.nih.gov/pubmed/33295292 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e19150 %T A Mobile- and Web-Based Health Intervention Program for Diabetes and Prediabetes Self-Management (BetaMe/Melon): Process Evaluation Following a Randomized Controlled Trial %A Signal,Virginia %A McLeod,Melissa %A Stanley,James %A Stairmand,Jeannine %A Sukumaran,Nitin %A Thompson,Donna-Marie %A Henderson,Kelly %A Davies,Cheryl %A Krebs,Jeremy %A Dowell,Anthony %A Grainger,Rebecca %A Sarfati,Diana %+ Department of Public Health, University of Otago Wellington, 23a Mein Street, Newtown, Wellington, , New Zealand, 64 212631385, virginia.signal@otago.ac.nz %K diabetes mellitus %K prediabetes %K self-management %K eHealth %K mobile apps %K evaluation %K diabetes %K digital health %K app %K utilization %K user perception %K user %D 2020 %7 1.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Technology-assisted self-management programs are increasingly recommended to patients with long-term conditions such as diabetes. However, there are a number of personal and external factors that affect patients’ abilities to engage with and effectively utilize such programs. A randomized controlled trial of a multi-modal online program for diabetes self-management (BetaMe/Melon) was conducted in a primary care setting, and a process evaluation was completed at the end of the study period. Objective: This process evaluation aimed to examine the utilization patterns of BetaMe/Melon, identify which components participants found most (and least) useful, and identify areas of future improvement. Methods: Process evaluation data were collected for intervention arm participants from 3 sources: (1) the mobile/web platform (to identify key usage patterns over the 16-week core program), (2) an online questionnaire completed during the final study assessment, and (3) interviews conducted with a subset of participants following the study period. Participants were classified as “actively engaged” if any usage data was recorded for the participant (in any week), and patterns were reported by age, gender, ethnicity, and diabetes/prediabetes status. The online questionnaire asked participants about the usefulness of the program and whether they would recommend BetaMe/Melon to others according to a 5-point Likert Scale. Of 23 invited participants, 18 participated in a digitally recorded, semistructured telephone interview. Interview data were thematically analyzed. Results: Out of the 215 participants, 198 (92%) received an initial health coaching session, and 160 (74%) were actively engaged with the program at some point during the 16-week core program. Engagement varied by demographic, with women, younger participants, and ethnic majority populations having higher rates of engagement. Usage steadily declined from 50% at Week 0 to 23% at Week 15. Participants ranked component usefulness as education resources (63.7%), health coaches (59.2%), goal tracking (48.8%), and online peer support (42.1%). Although 53% agreed that the program was easy to use, 64% would recommend the program to others. Interview participants found BetaMe/Melon useful overall, with most identifying beneficial outcomes such as increased knowledge, behavioral changes, and weight loss. Barriers to engagement were program functionality, internet connectivity, incomplete delivery of all program components, and participant motivation. Participants suggested a range of improvements to the BetaMe/Melon program. Conclusions: The program was generally well received by participants; active engagement was initially high, although it declined steadily. Maintaining participant engagement over time, individualizing programs, and addressing technical barriers are important to maximize potential health benefits from online diabetes self-management programs. Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12617000549325; https://tinyurl.com/y622b27q %M 33258776 %R 10.2196/19150 %U https://www.jmir.org/2020/12/e19150 %U https://doi.org/10.2196/19150 %U http://www.ncbi.nlm.nih.gov/pubmed/33258776 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 11 %P e16309 %T Assessing User Retention of a Mobile App: Survival Analysis %A Lin,Yu-Hsuan %A Chen,Si-Yu %A Lin,Pei-Hsuan %A Tai,An-Shun %A Pan,Yuan-Chien %A Hsieh,Chang-En %A Lin,Sheng-Hsuan %+ Institute of Statistics, National Chiao Tung University, 1001 University Road, Hsinchu, 300, Taiwan, 886 (3) 5712121 ext 56822, shenglin@nctu.edu.tw %K smartphone %K passive data, user retention %K mobile application %K app %K survival analysis %K work hours %D 2020 %7 26.11.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: A mobile app generates passive data, such as GPS data traces, without any direct involvement from the user. These passive data have transformed the manner of traditional assessments that require active participation from the user. Passive data collection is one of the most important core techniques for mobile health development because it may promote user retention, which is a unique characteristic of a software medical device. Objective: The primary aim of this study was to quantify user retention for the “Staff Hours” app using survival analysis. The secondary aim was to compare user retention between passive data and active data, as well as factors associated with the survival rates of user retention. Methods: We developed an app called “Staff Hours” to automatically calculate users’ work hours through GPS data (passive data). “Staff Hours” not only continuously collects these passive data but also sends an 11-item mental health survey to users monthly (active data). We applied survival analysis to compare user retention in the collection of passive and active data among 342 office workers from the “Staff Hours” database. We also compared user retention on Android and iOS platforms and examined the moderators of user retention. Results: A total of 342 volunteers (224 men; mean age 33.8 years, SD 7.0 years) were included in this study. Passive data had higher user retention than active data (P=.011). In addition, user retention for passive data collected via Android devices was higher than that for iOS devices (P=.015). Trainee physicians had higher user retention for the collection of active data than trainees from other occupations, whereas no significant differences between these two groups were observed for the collection of passive data (P=.700). Conclusions: Our findings demonstrated that passive data collected via Android devices had the best user retention for this app that records GPS-based work hours. %M 33242023 %R 10.2196/16309 %U http://mhealth.jmir.org/2020/11/e16309/ %U https://doi.org/10.2196/16309 %U http://www.ncbi.nlm.nih.gov/pubmed/33242023 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 11 %P e18826 %T Engagement With a Web-Based Intervention to Reduce Harmful Drinking: Secondary Analysis of a Randomized Controlled Trial %A Nordholt,Paul U %A Christalle,Eva %A Zill,Jördis M %A Dirmaier,Jörg %+ Institute and Outpatient Clinic of Medical Psychology, University Medical Center Hamburg-Eppendorf, Department of Medical Psychology, Martinistr 52, Hamburg, 20246, Germany, 49 407410 ext 59137, dirmaier@uke.de %K engagement %K usage %K alcohol %K eHealth %K mHealth %K readiness to change %K self-efficacy %K outcome expectancy %D 2020 %7 20.11.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Engagement with digital behavior change interventions (DBCIs) is considered a prerequisite for intervention efficacy. However, in many trials on DBCIs, participants use the intervention either only little or not at all. Objective: To analyze engagement with a web-based intervention to reduce harmful drinking, we explored (1) whether engagement with a web-based alcohol intervention is related to drinking outcomes, (2) which user characteristics are associated with measures of engagement, and (3) whether reported outcomes are associated with data captured by voluntary intervention questionnaires. Methods: We analyzed data of the intervention arm of a randomized controlled trial on a DBCI to reduce risky alcohol consumption. Data were collected at baseline (T0), after 90 days (T1), and at the end of the 180-day usage period (T2). Engagement with the intervention was measured via system usage data as well as self-reported usage. Drinking behavior was measured as average daily alcohol consumption as well as the number of binge drinking days. User characteristics included demographics, baseline drinking behavior, readiness to change, alcohol-related outcome expectancies, and alcohol abstinence self-efficacy. Following a bivariate approach, we performed two-tailed Welch’s t tests and Wilcoxon signed rank/Mann-Whitney U tests or calculated correlation coefficients. Results: The data of 306 users were analyzed. Time spent engaging with the intervention as measured by system usage did not match self-reported usage. Higher self-reported usage was associated with higher reductions in average daily alcohol consumption (T1: ρ=0.39, P<.001; T2: ρ=0.29, P=.015) and in binge drinking days (T1: ρ=0.62, P<.001; T2: ρ=0.3, P=.006). Higher usage was reported from users who were single (T1: P<.001; T2: P<.001), users without children (T1: P<.001; T2: P<.001), users who did not start or finish secondary education (T1: P<.001; T2: P<.001), users without academic education (T1: P<.001; T2: P<.001), and those who worked (T1: P=.001; T2: P=.004). Relationships between self-reported usage and clinical or psychological baseline characteristics were complex. For system usage, the findings were mixed. Reductions in drinking captured by intervention questionnaires were associated with reported outcomes. Conclusions: Though self-reported usage could be consistently linked to better outcomes and multiple user characteristics, our findings add to the overall inconclusive evidence that can be found throughout the literature. Our findings indicate potential benefits of self-reports as measures of engagement and intervention questionnaires as a basis for tailoring of intervention content. Future studies should adopt a theory-driven approach to engagement research utilizing psychometrically sound self-report questionnaires and include short ecological momentary assessments within the DBCIs. Trial Registration: German Clinical Trials Register DRKS00006104; https://tinyurl.com/y22oc5jo %M 33216008 %R 10.2196/18826 %U https://www.jmir.org/2020/11/e18826 %U https://doi.org/10.2196/18826 %U http://www.ncbi.nlm.nih.gov/pubmed/33216008 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 11 %P e22212 %T Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study %A Böhm,Anna-Katharina %A Jensen,Morten Lind %A Sørensen,Mads Reinholdt %A Stargardt,Tom %+ Hamburg Center for Health Economics, University of Hamburg, Esplanade 36, Hamburg, 20354, Germany, 49 40428381627, Anna-Katharina.Boehm@uni-hamburg.de %K user engagement %K user activity %K mHealth %K diabetes mellitus %K diabetes apps %D 2020 %7 6.11.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Patient support apps have risen in popularity and provide novel opportunities for self-management of diabetes. Such apps offer patients to play an active role in monitoring their condition, thereby increasing their own treatment responsibility. Although many health apps require active user engagement to be effective, there is little evidence exploring engagement with mobile health (mHealth). Objective: This study aims to analyze the extent to which users engage with mHealth for diabetes and identify patient characteristics that are associated with engagement. Methods: The analysis is based on real-world data obtained by Novo Nordisk’s Cornerstones4Care Powered by Glooko diabetes support app. User engagement was assessed as the number of active days and using measures expressing the persistence, longevity, and regularity of interaction within the first 180 days of use. Beta regressions were estimated to assess the associations between user characteristics and engagement outcomes for each module of the app. Results: A total of 9051 individuals initiated use after registration and could be observed for 180 days. Among these, 55.39% (5013/9051) used the app for one specific purpose. The average user activity ratio varied from 0.05 (medication and food) to 0.55 (continuous glucose monitoring), depending on the module of the app. Average user engagement was lower if modules required manual data entries, although the initial uptake was higher for these modules. Regression analyses further revealed that although more women used the app (2075/3649, 56.86%), they engaged significantly less with it. Older people and users who were recently diagnosed tended to use the app more actively. Conclusions: Strategies to increase or sustain the use of apps and availability of health data may target the mode of data collection and content design and should take into account privacy concerns of the users at the same time. Users’ engagement was determined by various user characteristics, indicating that particular patient groups should be targeted or assisted when integrating apps into the self-management of their disease. %M 32975198 %R 10.2196/22212 %U http://mhealth.jmir.org/2020/11/e22212/ %U https://doi.org/10.2196/22212 %U http://www.ncbi.nlm.nih.gov/pubmed/32975198 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 10 %P e22528 %T Consumer-Guided Development of an Engagement-Facilitation Intervention for Increasing Uptake and Adherence for Self-Guided Web-Based Mental Health Programs: Focus Groups and Online Evaluation Survey %A Gulliver,Amelia %A Calear,Alison L %A Sunderland,Matthew %A Kay-Lambkin,Frances %A Farrer,Louise M %A Banfield,Michelle %A Batterham,Philip J %+ Centre for Mental Health Research, Research School of Population Health, The Australian National University, Acton, Canberra, 2601, Australia, 61 26125 ext 9472, amelia.gulliver@anu.edu.au %K mental health %K internet %K anxiety %K depression %K technology %K treatment adherence and compliance %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Self-guided web-based mental health programs are effective in treating and preventing mental health problems. However, current engagement with these programs in the community is suboptimal, and there is limited evidence indicating how to increase the use of existing evidence-based programs. Objective: This study aims to investigate the views of people with lived experience of depression and anxiety on factors influencing their engagement with self-guided web-based mental health (e–mental health) programs and to use these perspectives to develop an engagement-facilitation intervention (EFI) to increase engagement (defined as both uptake and adherence) with these programs. Methods: A total of 24 community members (female=21; male=3) with lived experience of depression and anxiety or depression or anxiety alone participated in 1 of 4 focus groups discussing the factors influencing their engagement with self-guided e–mental health programs and the appearance, delivery mode, and functionality of content for the proposed EFI. A subsequent evaluation survey of the focus group participants (n=14) was conducted to evaluate the resultant draft EFI. Data were thematically analyzed using both inductive and deductive qualitative methods. Results: Participants suggested that the critical component of an EFI was information that would challenge personal barriers to engagement, including receiving personalized symptom feedback, information regarding the program’s content or effectiveness and data security, and normalization of using e–mental health programs (eg, testimonials). Reminders, rewards, feedback about progress, and coaching were all mentioned as facilitating adherence. Conclusions: EFIs have the potential to improve community uptake of e–mental health programs. They should focus on providing information on the content and effectiveness of e–mental health programs and normalizing their use. Given that the sample comprised predominantly young females, this study may not be generalizable to other population groups. There is a strong value in involving people with a lived experience in the design and development of EFIs to maximize their effectiveness. %M 33118939 %R 10.2196/22528 %U http://formative.jmir.org/2020/10/e22528/ %U https://doi.org/10.2196/22528 %U http://www.ncbi.nlm.nih.gov/pubmed/33118939 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e20847 %T Relationship Between Patient Engagement and Depressive Symptoms Among People Living With HIV in a Mobile Health Intervention: Secondary Analysis of a Randomized Controlled Trial %A Zeng,Yu %A Guo,Yan %A Li,Linghua %A Hong,Y Alicia %A Li,Yiran %A Zhu,Mengting %A Zeng,Chengbo %A Zhang,Hanxi %A Cai,Weiping %A Liu,Cong %A Wu,Shaomin %A Chi,Peilian %A Monroe-Wise,Aliza %A Hao,Yuantao %A Ho,Rainbow Tin Hung %+ Department of Medical Statistics, School of Public Health, Sun Yat-sen University, No.74, 2nd Zhongshan Road, Guangzhou, 510000, China, 86 13501502582, guoy8@mail.sysu.edu.cn %K mHealth %K patient engagement %K latent growth curve model %K depressive symptoms %K HIV %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Associations between higher levels of patient engagement and better health outcomes have been found in face-to-face interventions; studies on such associations with mobile health (mHealth) interventions have been limited and the results are inconclusive. Objective: The objective of this study is to investigate the relationship between patient engagement in an mHealth intervention and depressive symptoms using repeated measures of both patient engagement and patient outcomes at 4 time points. Methods: Data were drawn from a randomized controlled trial (RCT) of an mHealth intervention aimed at reducing depressive symptoms among people living with HIV and elevated depressive symptoms. We examined the association between patient engagement and depressive symptoms in the intervention group (n=150) where participants received an adapted cognitive-behavioral stress management (CBSM) course and physical activity promotion on their WeChat social media app. Depressive symptoms were repeatedly measured using the Patient Health Questionnaire (PHQ-9) at baseline and 1 month, 2 months, and 3 months. Patient engagement was correspondingly measured by the completion rate, frequency of items completed, and time spent on the program at 1 month, 2 months, and 3 months. Latent growth curve models (LGCMs) were used to explore the relationship between patient engagement and depressive symptoms at multiple time points in the intervention. Results: The mean PHQ-9 scores were 10.2 (SD 4.5), 7.7 (SD 4.8), 6.5 (SD 4.7), and 6.7 (SD 4.1) at baseline, 1 month, 2 months, and 3 months, respectively. The mean completion rates were 50.6% (SD 31.8%), 51.5% (SD 32.2%), and 50.8% (SD 33.7%) at 1, 2, and 3 months, respectively; the average frequencies of items completed were 18.0 (SD 14.6), 32.6 (SD 24.8), and 47.5 (SD 37.2) at 1, 2, and 3 months, respectively, and the mean times spent on the program were 32.7 (SD 66.7), 65.4 (SD 120.8), and 96.4 (SD 180.4) minutes at 1, 2, and 3 months, respectively. LGCMs showed good model fit and indicated that a higher completion rate (β at 3 months=–2.184, P=.048) and a greater frequency of items completed (β at 3 months=–0.018, P=.04) were associated with fewer depressive symptoms at 3 months. Although not significant, similar trends were found in the abovementioned relationships at 1 and 2 months. There was no significant relationship between time spent on the program and depressive symptoms. Conclusions: This study revealed a positive association between patient engagement and health outcomes at 3 months of an mHealth intervention using LGCMs and repeated measures data. The results underscore the importance of improving patient engagement in mHealth interventions to improve patient-centered health outcomes. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://tinyurl.com/yxb64mef International Registered Report Identifier (IRRID): RR2-10.1186/s12889-018-5693-1 %M 33118956 %R 10.2196/20847 %U http://mhealth.jmir.org/2020/10/e20847/ %U https://doi.org/10.2196/20847 %U http://www.ncbi.nlm.nih.gov/pubmed/33118956 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e20631 %T Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care %A Baumel,Amit %A Fleming,Theresa %A Schueller,Stephen M %+ University of Haifa, Abba Khoushy Ave 199, Haifa, 3498838, Israel, 972 48240111, abaumel@univ.haifa.ac.il %K micro intervention %K mental health %K mhealth %K eHealth %K engagement %K intervention %K adherence %K behavior change %K behavioral health %D 2020 %7 29.10.2020 %9 Viewpoint %J J Med Internet Res %G English %X Although many people access publicly available digital behavioral and mental health interventions, most do not invest as much effort in these interventions as hoped or intended by intervention developers, and ongoing engagement is often low. Thus, the impact of such interventions is minimized by a misalignment between intervention design and user behavior. Digital micro interventions are highly focused interventions delivered in the context of a person’s daily life with little burden on the individual. We propose that these interventions have the potential to disruptively expand the reach of beneficial therapeutics by lowering the bar for entry to an intervention and the effort needed for purposeful engagement. This paper provides a conceptualization of digital micro interventions, their component parts, and principles guiding their use as building blocks of a larger therapeutic process (ie, digital micro intervention care). The model represented provides a structure that could improve the design, delivery, and research on digital micro interventions and ultimately improve behavioral and mental health care and care delivery. %M 33118946 %R 10.2196/20631 %U http://www.jmir.org/2020/10/e20631/ %U https://doi.org/10.2196/20631 %U http://www.ncbi.nlm.nih.gov/pubmed/33118946 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e15076 %T Evaluating Asthma Mobile Apps to Improve Asthma Self-Management: User Ratings and Sentiment Analysis of Publicly Available Apps %A Camacho-Rivera,Marlene %A Vo,Huy %A Huang,Xueqi %A Lau,Julia %A Lawal,Adeola %A Kawaguchi,Akira %+ Department of Community Health Sciences, SUNY Downstate Health Sciences University, 450 Clarkson Avenue, MSC 43, Brooklyn, NY, 11203, United States, 1 7182704386, marlene.camacho-rivera@downstate.edu %K mHealth %K asthma apps %K sentiment analysis %K user ratings %K smartphone %K mobile phone %D 2020 %7 29.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The development and use of mobile health (mHealth) apps for asthma management have risen dramatically over the past two decades. Asthma apps vary widely in their content and features; however, prior research has rarely examined preferences of users of publicly available apps. Objective: The goals of this study were to provide a descriptive overview of asthma mobile apps that are publicly available and to assess the usability of asthma apps currently available on the market to identify content and features of apps associated with positive and negative user ratings. Methods: Reviews were collected on June 23, 2020, and included publicly posted reviews until June 21, 2020. To characterize features associated with high or low app ratings, we first dichotomized the average user rating of the asthma app into 2 categories: a high average rating and a low average rating. Asthma apps with average ratings of 4 and above were categorized as having a high average rating. Asthma apps with average ratings of less than 4 were categorized as having a low average rating. For the sentiment analysis, we modeled both 2-word (bi-gram) and 3-word (tri-gram) phrases which commonly appeared across highly rated and lowly rated apps. Results: Of the 10 apps that met the inclusion criteria, a total of 373 reviews were examined across all apps. Among apps reviewed, 53.4% (199/373) received high ratings (average ratings of 4 or 5) and 47.2% (176/373) received low ratings (average ratings of 3 or less). The number of ratings across all apps ranged from 188 (AsthmaMD) to 10 (My Asthma App); 30% (3/10) of apps were available on both Android and iOS. From the sentiment analysis, key features of asthma management that were common among highly rated apps included the tracking of peak flow readings (n=48), asthma symptom monitoring (n=11), and action plans (n=10). Key features related to functionality that were common among highly rated apps included ease of use (n=5). Users most commonly reported loss of data (n=14) and crashing of app (n=12) as functionality issues among poorly rated asthma apps. Conclusions: Our study results demonstrate that asthma app quality, maintenance, and updates vary widely across apps and platforms. These findings may call into question the long-term engagement with asthma apps, a crucial factor for determining their potential to improve asthma self-management and asthma clinical outcomes. %M 33118944 %R 10.2196/15076 %U http://mhealth.jmir.org/2020/10/e15076/ %U https://doi.org/10.2196/15076 %U http://www.ncbi.nlm.nih.gov/pubmed/33118944 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e17738 %T Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach %A Bremer,Vincent %A Chow,Philip I %A Funk,Burkhardt %A Thorndike,Frances P %A Ritterband,Lee M %+ Institute of Information Systems, Leuphana University Lüneburg, C4.320, Lüneburg, 21335, Germany, 49 41316771157, vincent.bremer@leuphana.de %K dropout %K digital health %K machine learning %D 2020 %7 28.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: User dropout is a widespread concern in the delivery and evaluation of digital (ie, web and mobile apps) health interventions. Researchers have yet to fully realize the potential of the large amount of data generated by these technology-based programs. Of particular interest is the ability to predict who will drop out of an intervention. This may be possible through the analysis of user journey data—self-reported as well as system-generated data—produced by the path (or journey) an individual takes to navigate through a digital health intervention. Objective: The purpose of this study is to provide a step-by-step process for the analysis of user journey data and eventually to predict dropout in the context of digital health interventions. The process is applied to data from an internet-based intervention for insomnia as a way to illustrate its use. The completion of the program is contingent upon completing 7 sequential cores, which include an initial tutorial core. Dropout is defined as not completing the seventh core. Methods: Steps of user journey analysis, including data transformation, feature engineering, and statistical model analysis and evaluation, are presented. Dropouts were predicted based on data from 151 participants from a fully automated web-based program (Sleep Healthy Using the Internet) that delivers cognitive behavioral therapy for insomnia. Logistic regression with L1 and L2 regularization, support vector machines, and boosted decision trees were used and evaluated based on their predictive performance. Relevant features from the data are reported that predict user dropout. Results: Accuracy of predicting dropout (area under the curve [AUC] values) varied depending on the program core and the machine learning technique. After model evaluation, boosted decision trees achieved AUC values ranging between 0.6 and 0.9. Additional handcrafted features, including time to complete certain steps of the intervention, time to get out of bed, and days since the last interaction with the system, contributed to the prediction performance. Conclusions: The results support the feasibility and potential of analyzing user journey data to predict dropout. Theory-driven handcrafted features increased the prediction performance. The ability to predict dropout at an individual level could be used to enhance decision making for researchers and clinicians as well as inform dynamic intervention regimens. %M 33112241 %R 10.2196/17738 %U http://www.jmir.org/2020/10/e17738/ %U https://doi.org/10.2196/17738 %U http://www.ncbi.nlm.nih.gov/pubmed/33112241 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e16255 %T Tailored Web-Based Smoking Interventions and Reduced Attrition: Systematic Review and Meta-Analysis %A Shah,Amika %A Chaiton,Michael %A Baliunas,Dolly %A Schwartz,Robert %+ Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON, M5S 2S1, Canada, 1 416 978 7096, michael.chaiton@camh.ca %K internet %K world wide web %K smoking cessation %K web-based intervention %D 2020 %7 19.10.2020 %9 Review %J J Med Internet Res %G English %X Background: The increasing number of internet users presents an opportunity to deliver health interventions to large populations. Despite their potential, many web-based interventions, including those for smoking cessation, face high rates of attrition. Further consideration of how intervention features impact attrition is needed. Objective: The aim of this systematic review is to investigate whether tailored web-based smoking cessation interventions for smokers are associated with reduced rates of attrition compared with active or passive untailored web-based interventions. The outcomes of interest were dropout attrition at 1-, 3-, 6-, and 12-month follow-ups. Methods: Literature searches were conducted in May 2018 and updated in May 2020 on MEDLINE (Medical Literature Analysis and Retrieval System Online), PsycINFO (Psychological Information), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulated Index to Nursing and Allied Health Literature), Scopus, and the Cochrane Tobacco Addiction Group Specialized Register with the following search terms: smoking cessation, tailored, or web- or internet-based. Included studies were published in English before or in May 2020 using a randomized controlled trial design. Studies were restricted to those with web-based delivery, a tailored intervention group, an untailored control group, and a reported outcome of smoking cessation. Studies were assessed for methodological quality using the Cochrane Risk of Bias tool. Two reviewers independently extracted the study characteristics and the number of participants lost to follow-up for each treatment group. Results: A total of 13 studies were included in the systematic review, of which 11 (85%) were included in the meta-analysis. Tailoring had no statistically significant effect on dropout attrition at 1-month (risk ratio [RR]=1.02, 95% CI 0.95-1.09; P=.58; I2=78%), 3-month (RR=0.99, 95% CI 0.95-1.04; P=.80; I2=73%), 6-month (RR=1.00, 95% CI 0.95-1.05; P=.90; I2=43%), or 12-month (RR=0.97, 95% CI 0.92-1.02; P=.26; I2=28%) follow-ups. Subgroup analyses suggested that there was a statistically significant effect of tailoring between the active and passive subgroups at 1-month (P=.03), 3-month (P<.001), and 6-month (P=.02) follow-ups but not at 12-month follow-up (P=.25). Conclusions: The results suggest that tailoring of web-based smoking cessation interventions may not be associated with reduced rates of dropout attrition at 1-, 3-, 6-, or 12-month follow-ups. Significant differences between studies that include untailored active and passive control groups suggest that the role of tailoring may be more prominent when studies include a passive control group. These findings may be because of variability in the presence of additional features, the definition of smokers used, and the duration of smoking abstinence measured. Future studies should incorporate active web-based controls, compare the impact of different tailoring strategies, and include populations outside of the Western countries. %M 33074158 %R 10.2196/16255 %U https://www.jmir.org/2020/10/e16255 %U https://doi.org/10.2196/16255 %U http://www.ncbi.nlm.nih.gov/pubmed/33074158 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e17377 %T Challenges in Acceptance and Compliance in Digital Health Assessments During Pregnancy: Prospective Cohort Study %A Brusniak,Katharina %A Arndt,Hannah Maria %A Feisst,Manuel %A Haßdenteufel,Kathrin %A Matthies,Lina Maria %A Deutsch,Thomas Maximilian %A Hudalla,Hannes %A Abele,Harald %A Wallwiener,Markus %A Wallwiener,Stephanie %+ Department of Gynecology and Obstetrics, University Hospital Heidelberg, Im Neuenheimer Feld 440, Heidelberg, 69120, Germany, 49 6221 5637551, Stephanie.Wallwiener@med.uni-heidelberg.de %K eHealth %K compliance %K pregnancy %K digital assessments %D 2020 %7 14.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Pregnant women are increasingly using mobile apps to access health information during the antenatal period. Therefore, digital health solutions can potentially be used as monitoring instruments during pregnancy. However, a main factor of success is high user engagement. Objective: The aim of this study was to analyze engagement and factors influencing compliance in a longitudinal study targeting pregnant women using a digital health app with self-tracking. Methods: Digitally collected data concerning demographics, medical history, technical aspects, and mental health from 585 pregnant women were analyzed. Patients filling out ≥80% of items at every study visit were considered to be highly compliant. Factors associated with high compliance were identified using logistic regression. The effect of a change in mental and physical well-being on compliance was assessed using a one-sample t test. Results: Only 25% of patients could be considered compliant. Overall, 63% left at least one visit blank. Influential variables for higher engagement included higher education, higher income, private health insurance, nonsmoking, and German origin. There was no relationship between a change in the number of physical complaints or depressive symptoms and study dropout. Conclusions: Maintaining high engagement with digital monitoring devices over a long time remains challenging. As cultural and socioeconomic background factors had the strongest influence, more effort needs to be directed toward understanding the needs of patients from different demographic backgrounds to ensure high-quality care for all patients. More studies need to report on compliance to disclose potential demographic bias. %M 33052134 %R 10.2196/17377 %U https://mhealth.jmir.org/2020/10/e17377 %U https://doi.org/10.2196/17377 %U http://www.ncbi.nlm.nih.gov/pubmed/33052134 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e17757 %T Psychometric Evaluation of the TWente Engagement with Ehealth Technologies Scale (TWEETS): Evaluation Study %A Kelders,Saskia Marion %A Kip,Hanneke %A Greeff,Japie %+ Center for eHealth and Wellbeing Research, Department of Psychology, Health, and Technology, University of Twente, PO Box 217, Enschede, 7500AE, Netherlands, 31 534896055, s.m.kelders@utwente.nl %K engagement %K attrition %K eHealth %K adoption %K adherence %K questionnaire %K scale validation %K digital health interventions %D 2020 %7 9.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Engagement emerges as a predictor for the effectiveness of digital health interventions. However, a shared understanding of engagement is missing. Therefore, a new scale has been developed that proposes a clear definition and creates a tool to measure it. The TWente Engagement with Ehealth Technologies Scale (TWEETS) is based on a systematic review and interviews with engaged health app users. It defines engagement as a combination of behavior, cognition, and affect. Objective: This paper aims to evaluate the psychometric properties of the TWEETS. In addition, a comparison is made with the experiential part of the Digital Behavior Change Intervention Engagement Scale (DBCI-ES-Ex), a scale that showed some issues in previous psychometric analyses. Methods: In this study, 288 participants were asked to use any step counter app on their smartphones for 2 weeks. They completed online questionnaires at 4 time points: T0=baseline, T1=after 1 day, T2=1 week, and T3=2 weeks. At T0, demographics and personality (conscientiousness and intellect/imagination) were assessed; at T1-T3, engagement, involvement, enjoyment, subjective usage, and perceived behavior change were included as measures that are theoretically related to our definition of engagement. Analyses focused on internal consistency, reliability, and the convergent, divergent, and predictive validity of both engagement scales. Convergent validity was assessed by correlating the engagement scales with involvement, enjoyment, and subjective usage; divergent validity was assessed by correlating the engagement scales with personality; and predictive validity was assessed by regression analyses using engagement to predict perceived behavior change at later time points. Results: The Cronbach alpha values of the TWEETS were .86, .86, and .87 on T1, T2, and T3, respectively. Exploratory factor analyses indicated that a 1-factor structure best fits the data. The TWEETS is moderately to strongly correlated with involvement and enjoyment (theoretically related to cognitive and affective engagement, respectively; P<.001). Correlations between the TWEETS and frequency of use were nonsignificant or small, and differences between adherers and nonadherers on the TWEETS were significant (P<.001). Correlations between personality and the TWEETS were nonsignificant. The TWEETS at T1 was predictive of perceived behavior change at T3, with an explained variance of 16%. The psychometric properties of the TWEETS and the DBCI-ES-Ex seemed comparable in some aspects (eg, internal consistency), and in other aspects, the TWEETS seemed somewhat superior (divergent and predictive validity). Conclusions: The TWEETS performs quite well as an engagement measure with high internal consistency, reasonable test-retest reliability and convergent validity, good divergent validity, and reasonable predictive validity. As the psychometric quality of a scale is a reflection of how closely a scale matches the conceptualization of a concept, this paper is also an attempt to conceptualize and define engagement as a unique concept, providing a first step toward an acceptable standard of defining and measuring engagement. %M 33021487 %R 10.2196/17757 %U https://www.jmir.org/2020/10/e17757 %U https://doi.org/10.2196/17757 %U http://www.ncbi.nlm.nih.gov/pubmed/33021487 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e18514 %T Help-Seeking Behaviors of Transition-Aged Youth for Mental Health Concerns: Qualitative Study %A Stunden,Chelsea %A Zasada,Julie %A VanHeerwaarden,Nicole %A Hollenberg,Elisa %A Abi-Jaoudé,Alexxa %A Chaim,Gloria %A Cleverley,Kristin %A Henderson,Joanna %A Johnson,Andrew %A Levinson,Andrea %A Lo,Brian %A Robb,Janine %A Shi,Jenny %A Voineskos,Aristotle %A Wiljer,David %+ Education, Technology & Innovation, University Health Network, R. Fraser Elliot Building RFE 3E-411, 190 Elizabeth Street, Toronto, ON, M5G 2C4, Canada, 1 416 340 4800 ext 6322, David.Wiljer@uhn.ca %K mental health %K students %K adolescent %K substance abuse %K eHealth %K mHealth %K mobile apps %K help-seeking behavior %K social stigma %K social support %D 2020 %7 5.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Transition-aged youth are particularly vulnerable to mental health problems, yet they are one of the least likely demographic groups to seek help. Objective: The aim of this study is to explore the influences on and patterns in help-seeking for mental health concerns among transition-aged youth who attend postsecondary schools in Canada. Methods: A qualitative research design was used, involving 12 semistructured focus groups with transition-aged youth (17-29 years) who attended postsecondary schools in Canada. A thematic analysis was conducted to code the transcripts and develop themes. Results: Four main themes and subthemes regarding the process and experience of help-seeking were generated: (1) the influence of formal service providers (accessibility and experiences), (2) the influence of social factors (system navigation and stigma), (3) the influence of health literacy (symptom recognition, acting on symptoms, digital tools and the internet, and mental health awareness campaigns), and (4) the influence of low-intensity sources of support, namely, self-help. Conclusions: Transition-aged youth seek help for mental health problems in different ways. Despite efforts to improve access to mental health services, transition-aged youth continue to face barriers to accessing these services, especially formal sources of support. The factors identified in this study that either hinder or facilitate help-seeking have pragmatic implications for developing help-seeking interventions and delivering mental health services for this population. In addition to other facilitators, family physicians are an important resource in the help-seeking process. Furthermore, digital help-seeking tools have unique characteristics that may make them an important source of support for transition-aged youth. %M 33016882 %R 10.2196/18514 %U https://www.jmir.org/2020/10/e18514 %U https://doi.org/10.2196/18514 %U http://www.ncbi.nlm.nih.gov/pubmed/33016882 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e18122 %T The Role of Information Technology Mindfulness in the Postadoption Stage of Using Personal Health Devices: Cross-Sectional Questionnaire Study in Mobile Health %A Esmaeilzadeh,Pouyan %+ Department of Information Systems and Business Analytics, Florida International University, Modesto A. Maidique Campus 11200 S.W. 8th St, Miami, FL, 33199, United States, 1 3053483302, pesmaeil@fiu.edu %K IT identity %K IT mindfulness %K personal health devices %K perceived health status %K post-adoption behaviors %K mHealth %K mobile phone %D 2020 %7 5.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Although personal health devices (for example, smartwatches, fitness trackers and intelligent bracelets) offer great potential to monitor personal fitness and health parameters, many users discontinue using them after a few months. Thus, it is critical to study the postadoption behaviors of current users to enhance their engagement with personal health devices and use behaviors. However, there is little empirical research on the factors affecting users’ engagement in beneficial use behaviors. Mindfulness and identity are not new topics, but the applications of these concepts in the field of information systems are emerging themes. Information technology (IT) mindfulness has been conceptualized in previous studies; however, little is known about the antecedents and consequences of IT mindfulness in the mobile health (mHealth) context. Objective: The main aim of this study is to explore both IT identity and IT mindfulness to develop a new ground for research in the domain of mHealth postadoption. Thus, we aim to explain why users should be fully mindful of their engagement with PHDs and what could be the consequences and implications. Methods: This study proposes that IT mindfulness can play an important role in improving the use behaviors of users. Through a web-based survey with 450 current users of a personal health device, this paper tests the relationship between IT identity and IT mindfulness in the postadoption stage of using personal health devices. Results: We found that IT identity significantly shapes IT mindfulness associated with PHDs. Moreover, the IT identity–IT mindfulness relationship is negatively moderated by individuals’ perceived health status (P=.003). Finally, the results of this study show that IT mindfulness can significantly predict automatic use behaviors (eg, continued intention to use), active use behaviors (eg, feature use and enhanced use behaviors), and commitment behaviors in using personal health devices (eg, positive word-of-mouth intention). Conclusions: The findings of this study provide implications for both research and practice. This study can contribute to our current understanding of IT mindfulness by developing and empirically testing a research model that explains the determinants and outcomes of the IT mindfulness construct in the context of personal health devices. The results imply that IT mindfulness significantly helps individuals express their alertness, awareness, openness, and orientation in the present in their postadoption interactions with smart devices used for health care purposes. Finally, our findings may assist practitioners and IT developers in designing mindfulness-supporting PHDs. Owing to the impact of IT mindfulness on postadoption behaviors, its 4 dimensions could be used for developing PHD technologies. Moreover, PHD developers may need to direct their efforts toward increasing IT mindfulness by reinforcing IT identity to serve and retain a wide range of target users. %M 33016884 %R 10.2196/18122 %U http://mhealth.jmir.org/2020/10/e18122/ %U https://doi.org/10.2196/18122 %U http://www.ncbi.nlm.nih.gov/pubmed/33016884 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e17526 %T Predictors and Effects of Usage of an Online Mindfulness Intervention for Distressed Cancer Patients: Usability Study %A Cillessen,Linda %A van de Ven,Monique OM %A Compen,Félix R %A Bisseling,Else M %A van der Lee,Marije L %A Speckens,Anne EM %+ Department of Psychiatry, Center for Mindfulness, Radboud University Medical Center, Postbus 9101, Nijmegen, 6500 HB, Netherlands, 31 (0)24 361 5445, linda.cillessen@radboudumc.nl %K internet intervention %K eHealth %K mindfulness %K mindfulness-based cognitive therapy %K usage %K log data %K uptake %K adherence %K cancer %K oncology %D 2020 %7 2.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: One in three cancer patients experience high psychological distress. Mindfulness-based interventions are effective in reducing psychological distress in this patient group. However, these interventions lack availability and flexibility, which may compromise participation in the intervention for cancer patients experiencing late symptoms like fatigue or pain. Therefore, mindfulness-based interventions are increasingly offered via the internet. However, little is known about the usage of these online mindfulness-based interventions. Objective: The aim of this study was to (1) predict uptake of and adherence to online mindfulness-based cognitive therapy (eMBCT) using baseline patient characteristics (demographic, cancer-related, personality, and psychological variables) and (2) examine the relations between adherence and treatment outcomes in eMBCT for cancer patients. Methods: A total of 125 cancer patients were assigned to eMBCT in a parent randomized controlled trial comparing MBCT and eMBCT with treatment as usual in distressed cancer patients. Various usage measures of eMBCT were automatically tracked within the online program. Based on activity of use, participants were classified as nonusers, minimal users, low users, and intended users. Questionnaires were used to assess baseline characteristics (preintervention) and outcomes (pre- and postintervention). To answer the research questions, data were analyzed with t tests, χ2 tests, and linear regression models. Results: Based on weekly activity, participants were classified as nonusers (n=17, 13.6%), who completed no exercises in MBCT; minimal users (n=31, 24.8%), who completed at least one exercise of one to three sessions; low users (n=12, 9.6%), who completed at least one exercise of four to seven sessions; and intended users (n=65, 52.0%), who completed at least one exercise of eight to nine sessions. Nonusers had more fear of cancer recurrence at baseline than users (uptake), and intended users were more conscientious than minimal and low users (adherence). Intended users reported a larger reduction in psychological distress and more improvement of positive mental health (ie, emotional, psychological, and social well-being) after the intervention than other participants. Conclusions: This study showed that adherence was related to improved patient outcomes. Patients with strong fear of recurrence or low levels of conscientiousness should receive extra attention, as they are less likely to respectively start or complete eMBCT. Future research may focus on the development of flexible and adaptive eMBCT programs to fit individual needs. %M 33006567 %R 10.2196/17526 %U https://www.jmir.org/2020/10/e17526 %U https://doi.org/10.2196/17526 %U http://www.ncbi.nlm.nih.gov/pubmed/33006567 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e19945 %T The Influence of Three Modes of Human Support on Attrition and Adherence to a Web- and Mobile App–Based Mental Health Promotion Intervention in a Nonclinical Cohort: Randomized Comparative Study %A Renfrew,Melanie Elise %A Morton,Darren Peter %A Morton,Jason Kyle %A Hinze,Jason Scott %A Przybylko,Geraldine %A Craig,Bevan Adrian %+ Lifestyle and Health Research Centre, Avondale University College, 582 Freemans Drive, Cooranbong, NSW, Australia, 61 405445151, melanie.renfrew@avondale.edu.au %K human support %K adherence %K attrition %K engagement %K web-based mental health %K health promotion %K eHealth %K SMS %K videoconferencing %D 2020 %7 29.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The escalating prevalence of mental health disorders necessitates a greater focus on web- and mobile app–based mental health promotion initiatives for nonclinical groups. However, knowledge is scant regarding the influence of human support on attrition and adherence and participant preferences for support in nonclinical settings. Objective: This study aimed to compare the influence of 3 modes of human support on attrition and adherence to a digital mental health intervention for a nonclinical cohort. It evaluated user preferences for support and assessed whether adherence and outcomes were enhanced when participants received their preferred support mode. Methods: Subjects participated in a 10-week digital mental health promotion intervention and were randomized into 3 comparative groups: standard group with automated emails (S), standard plus personalized SMS (S+pSMS), and standard plus weekly videoconferencing support (S+VCS). Adherence was measured by the number of video lessons viewed, points achieved for weekly experiential challenge activities, and the total number of weeks that participants recorded a score for challenges. In the postquestionnaire, participants ranked their preferred human support mode from 1 to 4 (S, S+pSMS, S+VCS, S+pSMS & VCS combined). Stratified analysis was conducted for those who received their first preference. Preintervention and postintervention questionnaires assessed well-being measures (ie, mental health, vitality, depression, anxiety, stress, life satisfaction, and flourishing). Results: Interested individuals (N=605) enrolled on a website and were randomized into 3 groups (S, n=201; S+pSMS, n=202; S+VCS, n=201). Prior to completing the prequestionnaire, a total of 24.3% (147/605) dropped out. Dropout attrition between groups was significantly different (P=.009): 21.9% (44/201) withdrew from the S group, 19.3% (39/202) from the S+pSMS group, and 31.6% (64/202) from the S+VCS group. The remaining 75.7% (458/605) registered and completed the prequestionnaire (S, n=157; S+pSMS, n=163; S+VCS, n=138). Of the registered participants, 30.1% (138/458) failed to complete the postquestionnaire (S, n=54; S+pSMS, n=49; S+VCS, n=35), but there were no between-group differences (P=.24). For the 69.9% (320/458; S, n=103; S+pSMS, n=114; S+VCS, n=103) who completed the postquestionnaire, no between-group differences in adherence were observed for mean number of videos watched (P=.42); mean challenge scores recorded (P=.71); or the number of weeks that challenge scores were logged (P=.66). A total of 56 participants (17.5%, 56/320) received their first preference in human support (S, n=22; S+pSMS, n=26; S+VCS, n=8). No differences were observed between those who received their first preference and those who did not with regard to video adherence (P=.91); challenge score adherence (P=.27); or any of the well-being measures including, mental health (P=.86), vitality (P=.98), depression (P=.09), anxiety (P=.64), stress (P=.55), life satisfaction (P=.50), and flourishing (P=.47). Conclusions: Early dropout attrition may have been influenced by dissatisfaction with the allocated support mode. Human support mode did not impact adherence to the intervention, and receiving the preferred support style did not result in greater adherence or better outcomes. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR): 12619001009101; http://www.anzctr.org.au/ACTRN12619001009101.aspx %M 32990633 %R 10.2196/19945 %U http://www.jmir.org/2020/9/e19945/ %U https://doi.org/10.2196/19945 %U http://www.ncbi.nlm.nih.gov/pubmed/32990633 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e15307 %T Identifying Mobile Health Engagement Stages: Interviews and Observations for Developing Brief Message Content %A Burns,Kara %A Nicholas,Rebekah %A Beatson,Amanda %A Chamorro-Koc,Marianella %A Blackler,Alethea %A Gottlieb,Udo %+ School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology, George St, Brisbane, QLD, 4000, Australia, 61 414294967, drkaraburns@gmail.com %K mobile health %K text messaging %K social media %K mobile phone %K health communication %D 2020 %7 22.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Interest in mobile health (mHealth) has increased recently, and research suggests that mHealth devices can enhance end-user engagement, especially when used in conjunction with brief message content. Objective: This research aims to explore the stages of engagement framework for mHealth devices and develop a method to generate brief message content to promote sustained user engagement. This study uses the framework by O’Brien and Toms as a point of departure, where engagement is defined as the uptake or the use of an mHealth device. The framework is a linear repeatable process, including point of engagement, period of engagement, disengagement, and re-engagement. Each stage is characterized by attributes related to a person’s technology experience. Although the literature has identified stages of engagement for health-related technology, few studies explore mHealth engagement. Furthermore, little research has determined a method for creating brief message content at each stage in this engagement journey. Methods: Interviews and observations from 19 participants who used mHealth technologies (apps, devices, or wellness websites) in a solo capacity were recruited for sample group 1. In sample group 2, interviews, and observations from 25 participants using mHealth technologies in a group capacity through the Global Corporate Challenge were used. These samples were investigated at 3 time points in both research contexts. The results underwent deductive-inductive thematic analysis for the engagement stages’ framework and attributes. Results: In addition to the 4 stages identified by O’Brien and Toms, 2 additional stages, self-management and limited engagement, were identified. Self-management captures where users had disengaged from their technology but were still engaged with their health activity. Limited engagement captures where group mHealth users had minimal interaction with their mHealth technology but continued to engage in a group fitness activity. The results revealed that mHealth engagement stages were nonlinear and embedded in a wider engagement context and that each stage was characterized by a combination of 49 attributes that could be organized into 8 themes. Themes documented the total user experience and included technology usability, technology features, technology aesthetics, use motivations, health awareness, goal setting, social support, and interruptions. Different themes were found to have more relevance at different engagement stages. Knowing themes and attributes at all engagement stages allows technology developers and health care professionals to generate relevant brief message content informed by a person-centered approach. Conclusions: This research extends an existing engagement stages framework and identifies attributes and themes relevant to mHealth technology users’ total user experience and incorporates concepts derived from health, business studies, and information systems literature. In addition, we offer a practical 5-step process based on a person-centered approach to develop mHealth technology brief message content for sustained engagement. %M 32960181 %R 10.2196/15307 %U http://www.jmir.org/2020/9/e15307/ %U https://doi.org/10.2196/15307 %U http://www.ncbi.nlm.nih.gov/pubmed/32960181 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e17164 %T Nonprofessional Peer Support to Improve Mental Health: Randomized Trial of a Scalable Web-Based Peer Counseling Course %A Bernecker,Samantha L %A Williams,Joseph Jay %A Caporale-Berkowitz,Norian A %A Wasil,Akash R %A Constantino,Michael J %+ Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA, 02115-5899, United States, 1 8145749625, samantha.bernecker@gmail.com %K online learning %K nonprofessional education %K educational technology %K computer-assisted instruction %K social support %K mental health %K psychological stress %K eHealth %K internet %D 2020 %7 21.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Millions of people worldwide are underserved by the mental health care system. Indeed, most mental health problems go untreated, often because of resource constraints (eg, limited provider availability and cost) or lack of interest or faith in professional help. Furthermore, subclinical symptoms and chronic stress in the absence of a mental illness diagnosis often go unaddressed, despite their substantial health impact. Innovative and scalable treatment delivery methods are needed to supplement traditional therapies to fill these gaps in the mental health care system. Objective: This study aims to investigate whether a self-guided web-based course can teach pairs of nonprofessional peers to deliver psychological support to each other. Methods: In this experimental study, a community sample of 30 dyads (60 participants, mostly friends), many of whom presented with mild to moderate psychological distress, were recruited to complete a web-based counseling skills course. Dyads were randomized to either immediate or delayed access to training. Before and after training, dyads were recorded taking turns discussing stressors. Participants’ skills in the helper role were assessed before and after taking the course: the first author and a team of trained research assistants coded recordings for the presence of specific counseling behaviors. When in the client role, participants rated the session on helpfulness in resolving their stressors and supportiveness of their peers. We hypothesized that participants would increase the use of skills taught by the course and decrease the use of skills discouraged by the course, would increase their overall adherence to the guidelines taught in the course, and would perceive posttraining counseling sessions as more helpful and their peers as more supportive. Results: The course had large effects on most helper-role speech behaviors: helpers decreased total speaking time, used more restatements, made fewer efforts to influence the speaker, and decreased self-focused and off-topic utterances (ds=0.8-1.6). When rating the portion of the session in which they served as clients, participants indicated that they made more progress in addressing their stressors during posttraining counseling sessions compared with pretraining sessions (d=1.1), but they did not report substantive changes in feelings of closeness and supportiveness of their peers (d=0.3). Conclusions: The results provide proof of concept that nonprofessionals can learn basic counseling skills from a scalable web-based course. The course serves as a promising model for the development of web-based counseling skills training, which could provide accessible mental health support to some of those underserved by traditional psychotherapy. %M 32955451 %R 10.2196/17164 %U http://www.jmir.org/2020/9/e17164/ %U https://doi.org/10.2196/17164 %U http://www.ncbi.nlm.nih.gov/pubmed/32955451 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e21276 %T Regulatory Sandboxes: A Cure for mHealth Pilotitis? %A Bhatia,Abhishek %A Matthan,Rahul %A Khanna,Tarun %A Balsari,Satchit %+ FXB Center for Health and Human Rights, Harvard TH Chan School of Public Health, 651 Huntington Avenue, 703C, Boston, MA, , United States, 1 6174951000, balsari@hsph.harvard.edu %K COVID-19 %K mHealth %K digital health %K design thinking %K regulation %K intervention %K regulatory sandbox %D 2020 %7 15.9.2020 %9 Viewpoint %J J Med Internet Res %G English %X Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments and philanthropic foundations. The implementation of digital health tools has suffered from 2 limitations: (1) the interventions commonly ignore the “law of amplification” that states that technology is most likely to succeed when it seeks to augment and not alter human behavior; and (2) end-user needs and clinical gaps are often poorly understood while designing solutions, contributing to a substantial decrease in usage, referred to as the “law of attrition” in eHealth. The COVID-19 pandemic has addressed the first of the 2 problems—technology solutions, such as telemedicine, that were struggling to find traction are now closely aligned with health-seeking behavior. The second problem (poorly designed solutions) persists, as demonstrated by a plethora of poorly designed epidemic prediction tools and digital contact-tracing apps, which were deployed at scale, around the world, with little validation. The pandemic has accelerated the Indian state’s desire to build the nation’s digital health ecosystem. We call for the inclusion of regulatory sandboxes, as successfully done in the fintech sector, to provide a real-world testing environment for mHealth solutions before deploying them at scale. %M 32763889 %R 10.2196/21276 %U http://www.jmir.org/2020/9/e21276/ %U https://doi.org/10.2196/21276 %U http://www.ncbi.nlm.nih.gov/pubmed/32763889 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e18986 %T Identification of Patient Perceptions That Can Affect the Uptake of Interventions Using Biometric Monitoring Devices: Systematic Review of Randomized Controlled Trials %A Perlmutter,Alexander %A Benchoufi,Mehdi %A Ravaud,Philippe %A Tran,Viet-Thi %+ Department of Epidemiology, Mailman School of Public Health, Columbia University, Room 720.10, 722 W 168th St, New York, NY, 10032, United States, 1 703 336 9067, asp2183@cumc.columbia.edu %K systematic review %K patient perceptions %K biometric monitoring device %K randomized controlled trials %K accelerometer %K pedometer %K ecological momentary assessment %K electrochemical biosensor %K adoption %K uptake %K real-world %D 2020 %7 11.9.2020 %9 Review %J J Med Internet Res %G English %X Background: Biometric monitoring devices (BMDs) are wearable or environmental trackers and devices with embedded sensors that can remotely collect high-frequency objective data on patients’ physiological, biological, behavioral, and environmental contexts (for example, fitness trackers with accelerometer). The real-world effectiveness of interventions using biometric monitoring devices depends on patients’ perceptions of these interventions. Objective: We aimed to systematically review whether and how recent randomized controlled trials (RCTs) evaluating interventions using BMDs assessed patients’ perceptions toward the intervention. Methods: We systematically searched PubMed (MEDLINE) from January 1, 2017, to December 31, 2018, for RCTs evaluating interventions using BMDs. Two independent investigators extracted the following information: (1) whether the RCT collected information on patient perceptions toward the intervention using BMDs and (2) if so, what precisely was collected, based on items from questionnaires used and/or themes and subthemes identified from qualitative assessments. The two investigators then synthesized their findings in a schema of patient perceptions of interventions using BMDs. Results: A total of 58 RCTs including 10,071 participants were included in the review (the median number of randomized participants was 60, IQR 37-133). BMDs used in interventions were accelerometers/pedometers (n=35, 60%), electrochemical biosensors (eg, continuous glucose monitoring; n=18, 31%), or ecological momentary assessment devices (eg, carbon monoxide monitors for smoking cessation; n=5, 9%). Overall, 26 (45%) trials collected information on patient perceptions toward the intervention using BMDs and allowed the identification of 76 unique aspects of patient perceptions that could affect the uptake of these interventions (eg, relevance of the information provided, alarm burden, privacy and data handling, impact on health outcomes, independence, interference with daily life). Patient perceptions were unevenly collected in trials. For example, only 5% (n=3) of trials assessed how patients felt about privacy and data handling aspects of the intervention using BMDs. Conclusions: Our review showed that less than half of RCTs evaluating interventions using BMDs assessed patients’ perceptions toward interventions using BMDs. Trials that did assess perceptions often only assessed a fraction of them. This limits the extrapolation of the results of these RCTs to the real world. We thus provide a comprehensive schema of aspects of patient perceptions that may affect the uptake of interventions using BMDs and which should be considered in future trials. Trial Registration: PROSPERO CRD42018115522; https://tinyurl.com/y5h8fjgx %M 32915153 %R 10.2196/18986 %U http://www.jmir.org/2020/9/e18986/ %U https://doi.org/10.2196/18986 %U http://www.ncbi.nlm.nih.gov/pubmed/32915153 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 9 %P e17083 %T Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach %A Alenazi,Hanan A %A Jamal,Amr %A Batais,Mohammed A %+ National Health Information Center, Saudi Health Council, Riyadh, 13315, Saudi Arabia, 966 502025959, H.Alenazi@shc.gov.sa %K diabetes %K mobile features %K engagement strategies %K mobile app %K Delphi consensus %D 2020 %7 11.9.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) offers improved and cost-effective care to people with T2DM. However, the efficiency of engagement strategies and features of this technology need to be reviewed and standardized according to stakeholder and expert perspectives. Objective: The main objective of this study was to identify the most agreed-upon features for T2DM self-management mobile apps; the secondary objective was to identify the most agreed-upon strategies that prompt users to use these apps. Methods: In this study, a 4-round modified Delphi method was applied by experts in the domain of diabetes care. Results: In total, 11 experts with a mean age of 47.09 years (SD 11.70) consented to participate in the study. Overall, 36 app features were generated. The group of experts displayed weak agreement in their ranking of intervention components (Kendall W=0.275; P<.001). The top 5 features included insulin dose adjustment according to carbohydrate counting and blood glucose readings (5.36), alerting a caregiver of abnormal or critical readings (6.09), nutrition education (12.45), contacts for guidance if required (12.64), and offering patient-specific education tailored to the user’s goals, needs, and blood glucose readings (12.90). In total, 21 engagement strategies were generated. Overall, the experts showed a moderate degree of consensus in their strategy rankings (Kendall W=0.454; P<.001). The top 5 engagement strategies included a user-friendly design (educational and age-appropriate design; 2.82), a free app (3.73), allowing the user to communicate or send information/data to a health care provider (HCP; 5.36), HCPs prescribing the mobile app in the clinic and asking about patients’ app use compliance during clinical visits (6.91), and flexibility and customization (7.91). Conclusions: This is the first study in the region consisting of a local panel of experts from the diabetes field gathering together. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could thus be useful for health app developers and HCPs and inform future decision making on the topic. %M 32678798 %R 10.2196/17083 %U http://mhealth.jmir.org/2020/9/e17083/ %U https://doi.org/10.2196/17083 %U http://www.ncbi.nlm.nih.gov/pubmed/32678798 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 3 %P e15835 %T Intervention Enhancement Strategies Among Adults With Type 2 Diabetes in a Very Low–Carbohydrate Web-Based Program: Evaluating the Impact With a Randomized Trial %A Saslow,Laura R %A Moskowitz,Judith Tedlie %A Mason,Ashley E %A Daubenmier,Jennifer %A Liestenfeltz,Bradley %A Missel,Amanda L %A Bayandorian,Hovig %A Aikens,James E %A Kim,Sarah %A Hecht,Frederick M %+ Department of Health Behavior and Biological Sciences, School of Nursing, University of Michigan, 2178 400 North Ingalls Street, Ann Arbor, MI, 48109, United States, 1 7347647836, saslowl@umich.edu %K type 2 diabetes %K diet, ketogenic %K text messages %K self-management %D 2020 %7 9.9.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: Adults with type 2 diabetes may experience health benefits, including glycemic control and weight loss, from following a very low–carbohydrate, ketogenic (VLC) diet. However, it is unclear which ancillary strategies may enhance these effects. Objective: This pilot study aims to estimate the effect sizes of 3 intervention enhancement strategies (text messages, gifts, and breath vs urine ketone self-monitoring) that may improve outcomes of a 12-month web-based ad libitum VLC diet and lifestyle intervention for adults with type 2 diabetes. The primary intervention also included other components to improve adherence and well-being, including positive affect and mindfulness as well as coaching. Methods: Overweight or obese adults (n=44; BMI 25-45 kg/m2) with type 2 diabetes (glycated hemoglobin [HbA1c] ≥6.5%), who had been prescribed either no glucose-lowering medications or metformin alone, participated in a 12-month web-based intervention. Using a 2×2×2 randomized factorial design, we compared 3 enhancement strategies: (1) near-daily text messages about the intervention’s recommended behaviors (texts n=22 vs no texts n=22), (2) mailed gifts of diet-relevant foods and cookbooks (6 rounds of mailed gifts n=21 vs no gifts n=23), and (3) urine- or breath-based ketone self-monitoring (urine n=21 vs breath n=23). We assessed HbA1c and weight at baseline and at 4, 8, and 12 months. We evaluated whether each strategy exerted a differential impact on HbA1c and weight at 12 months against an a priori threshold of Cohen d of 0.5 or greater. Results: We retained 73% (32/44) of the participants at 12 months. The intervention, across all conditions, led to improvements in glucose control and reductions in body weight at the 12-month follow-up. In intent-to-treat (ITT) analyses, the mean HbA1c reduction was 1.0% (SD 1.6) and the mean weight reduction was 5.3% (SD 6.0), whereas among study completers, these reductions were 1.2% (SD 1.7) and 6.3% (SD 6.4), respectively, all with a P value of less than .001. In ITT analyses, no enhancement strategy met the effect size threshold. Considering only study completers, 2 strategies showed a differential effect size of at least a d value of 0.5 or greater Conclusions: Text messages, gifts of food and cookbooks, and urine-based ketone self-monitoring may potentially enhance the glycemic or weight loss benefits of a web-based VLC diet and lifestyle intervention for individuals with type 2 diabetes. Future research could investigate other enhancement strategies to help create even more effective solutions for the treatment of type 2 diabetes. Trial Registration: ClinicalTrials.gov NCT02676648; http://clinicaltrials.gov/ct2/show/NCT02676648 %M 32902391 %R 10.2196/15835 %U http://diabetes.jmir.org/2020/3/e15835/ %U https://doi.org/10.2196/15835 %U http://www.ncbi.nlm.nih.gov/pubmed/32902391 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e18355 %T Understanding Self-Guided Web-Based Educational Interventions for Patients With Chronic Health Conditions: Systematic Review of Intervention Features and Adherence %A Xie,Li Feng %A Itzkovitz,Alexandra %A Roy-Fleming,Amelie %A Da Costa,Deborah %A Brazeau,Anne-Sophie %+ School of Human Nutrition, McGill University, 21111 Lakeshore, Ste-Anne-de-Bellevue, Sainte-Anne-de-Bellevue, QC, H9X 3V9, Canada, 1 514 398 7848, anne-sophie.brazeau@mcgill.ca %K chronic disease %K online learning %K self-management %K mobile phone %D 2020 %7 13.8.2020 %9 Review %J J Med Internet Res %G English %X Background: Chronic diseases contribute to 71% of deaths worldwide every year, and an estimated 15 million people between the ages of 30 and 69 years die mainly because of cardiovascular disease, cancer, chronic respiratory diseases, or diabetes. Web-based educational interventions may facilitate disease management. These are also considered to be a flexible and low-cost method to deliver tailored information to patients. Previous studies concluded that the implementation of different features and the degree of adherence to the intervention are key factors in determining the success of the intervention. However, limited research has been conducted to understand the acceptability of specific features and user adherence to self-guided web interventions. Objective: This systematic review aims to understand how web-based intervention features are evaluated, to investigate their acceptability, and to describe how adherence to web-based self-guided interventions is defined and measured. Methods: Studies published on self-guided web-based educational interventions for people (≥14 years old) with chronic health conditions published between January 2005 and June 2020 were reviewed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement protocol. The search was performed using the PubMed, Cochrane Library, and EMBASE (Excerpta Medica dataBASE) databases; the reference lists of the selected articles were also reviewed. The comparison of the interventions and analysis of the features were based on the published content from the selected articles. Results: A total of 20 studies were included. Seven principal features were identified, with goal setting, self-monitoring, and feedback being the most frequently used. The acceptability of the features was measured based on the comments collected from users, their association with clinical outcomes, or device adherence. The use of quizzes was positively reported by participants. Self-monitoring, goal setting, feedback, and discussion forums yielded mixed results. The negative acceptability was related to the choice of the discussion topic, lack of face-to-face contact, and technical issues. This review shows that the evaluation of adherence to educational interventions was inconsistent among the studies, limiting comparisons. A clear definition of adherence to an intervention is lacking. Conclusions: Although limited information was available, it appears that features related to interaction and personalization are important for improving clinical outcomes and users’ experience. When designing web-based interventions, the selection of features should be based on the targeted population’s needs, the balance between positive and negative impacts of having human involvement in the intervention, and the reduction of technical barriers. There is a lack of consensus on the method of evaluating adherence to an intervention. Both investigations of the acceptability features and adherence should be considered when designing and evaluating web-based interventions. A proof-of-concept or pilot study would be useful for establishing the required level of engagement needed to define adherence. %M 32788152 %R 10.2196/18355 %U http://www.jmir.org/2020/8/e18355/ %U https://doi.org/10.2196/18355 %U http://www.ncbi.nlm.nih.gov/pubmed/32788152 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e17058 %T Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study %A Crafoord,Marie-Therése %A Fjell,Maria %A Sundberg,Kay %A Nilsson,Marie %A Langius-Eklöf,Ann %+ Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Alfred Nobels Allé 23, Stockholm, 14183, Sweden, 46 8524 837 49, marie-therese.crafoord@ki.se %K engagement %K adherence %K mHealth %K mobile app %K cancer supportive care %K symptom management %K usage metrics %K breast cancer %K prostate cancer %D 2020 %7 10.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Using mobile technology for symptom management and self-care can improve patient-clinician communication and clinical outcomes in patients with cancer. The interactive app Interaktor has been shown to reduce symptom burden during cancer treatment. It includes symptom assessment, an alert system for contact with health care professionals, access to self-care advice, and visualization of symptom history. It is essential to understand how digital interventions operate; one approach is to examine engagement by assessing usage and exploring user experiences. Actual usage in relation to the intended use—adherence—is an essential factor of engagement. Objective: This study aimed to describe engagement with the Interaktor app among patients with breast or prostate cancer during treatment. Methods: Patients from the intervention groups of two separate randomized controlled trials were included: patients with breast cancer receiving neoadjuvant chemotherapy (n=74) and patients with locally advanced prostate cancer receiving treatment with radiotherapy (n=75). The patients reported their symptoms daily. Sociodemographic and clinical data were obtained from baseline questionnaires and medical records. Logged data usage was retrieved from the server and analyzed descriptively and with multiple regression analysis. Telephone interviews were conducted with patients about their perceptions of using the app and analyzed using content analysis. Results: The median adherence percentage to daily symptom reporting was 83%. Most patients used the self-care advice and free text message component. Among the patients treated for breast cancer, higher age predicted a lower total number of free text messages sent (P=.04). Among the patients treated for prostate cancer, higher age (P=.01) and higher education level (P=.04), predicted an increase in total views on self-care advice, while higher comorbidity (P=.004) predicted a decrease in total views on self-care advice. Being married or living with a partner predicted a higher adherence to daily symptom reporting (P=.02). Daily symptom reporting created feelings of having continuous contact with health care professionals, being acknowledged, and safe. Being contacted by a nurse after a symptom alert was considered convenient and highly valued. Treatment and time-related aspects influenced engagement. Daily symptom reporting was perceived as particularly meaningful at the beginning of treatment. Requests were made for advice on diet and psychological symptoms, as well as for more comprehensive and detailed information as the patient progressed through treatment. Conclusions: Patient engagement in the interactive app Interaktor was high. The app promoted patient participation in their care through continuous and convenient contact with health care professionals. The predictive ability of demographic variables differed between patient groups, but higher age and a higher educational level predicted usage of specific app functions for both patient groups. Patients’ experience of relevance and interactivity influenced their engagement positively. %M 32663140 %R 10.2196/17058 %U https://www.jmir.org/2020/8/e17058 %U https://doi.org/10.2196/17058 %U http://www.ncbi.nlm.nih.gov/pubmed/32663140 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17709 %T Influence of Personality on mHealth Use in Patients with Diabetes: Prospective Pilot Study %A Su,Jingyuan %A Dugas,Michelle %A Guo,Xitong %A Gao,Guodong (Gordon) %+ eHealth Research Institute, School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin, , China, 86 451 86414022, xitongguo@hit.edu.cn %K mHealth %K diabetes %K adoption %K active utilization %K personality traits %K app %D 2020 %7 10.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile technology for health (mHealth) interventions are increasingly being used to help improve self-management among patients with diabetes; however, these interventions have not been adopted by a large number of patients and often have high dropout rates. Patient personality characteristics may play a critical role in app adoption and active utilization, but few studies have focused on addressing this question. Objective: This study aims to address a gap in understanding of the relationship between personality traits and mHealth treatment for patients with diabetes. We tested the role of the five-factor model of personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) in mHealth adoption preference and active utilization. Methods: We developed an mHealth app (DiaSocial) aimed to encourage diabetes self-management. We recruited 98 patients with diabetes—each patient freely chose whether to receive the standard care or the mHealth app intervention. Patient demographic information and patient personality characteristics were assessed at baseline. App usage data were collected to measure user utilization of the app. Patient health outcomes were assessed with lab measures of glycated hemoglobin (HbA1c level). Logistic regression models and linear regression were employed to explore factors predicting the relationship between mHealth use (adoption and active utilization) and changes in health outcome. Results: Of 98 study participants, 46 (47%) downloaded and used the app. Relatively younger patients with diabetes were 9% more likely to try and use the app (P=.02, odds ratio [OR] 0.91, 95% CI 0.85-0.98) than older patients with diabetes were. Extraversion was negatively associated with adoption of the mHealth app (P=.04, OR 0.71, 95% CI 0.51-0.98), and openness to experience was positively associated with adoption of the app (P=.03, OR 1.73, 95% CI 1.07-2.80). Gender (P=.43, OR 0.66, 95% CI 0.23-1.88), education (senior: P=.99, OR 1.00, 95% CI 0.32-3.11; higher: P=.21, OR 2.51, 95% CI 0.59-10.66), and baseline HbA1c level (P=.36, OR 0.79, 95% CI 0.47-1.31) were not associated with app adoption. Among those who adopted the app, a low education level (senior versus primary P=.003; higher versus primary P=.03) and a high level of openness to experience (P=.048, OR 2.01, 95% CI 1.01-4.00) were associated with active app utilization. Active users showed a significantly greater decrease in HbA1c level than other users (ΔHbA1c=−0.64, P=.05). Conclusions: This is one of the first studies to investigate how different personality traits influence the adoption and active utilization of an mHealth app among patients with diabetes. The research findings suggest that personality is a factor that should be considered when trying to identify patients who would benefit the most from apps for diabetes management. %M 32773382 %R 10.2196/17709 %U https://mhealth.jmir.org/2020/8/e17709 %U https://doi.org/10.2196/17709 %U http://www.ncbi.nlm.nih.gov/pubmed/32773382 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e16797 %T Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study %A Brower,Jacob %A LaBarge,Monica C %A White,Lauren %A Mitchell,Marc S %+ Smith School of Business, Queen's University, 805 Johnson St, Kingston, ON, K7L2B6, Canada, 1 6132174726, jbrower@queensu.ca %K mHealth %K behavioral economics %K public health %K incentives %K mobile apps %K mobile phone %D 2020 %7 10.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The Carrot Rewards app was developed as part of a public-private partnership to reward Canadians with loyalty points for downloading the app, referring friends, completing educational health quizzes, and health-related behaviors with long-term objectives of increasing health knowledge and encouraging healthy behaviors. During the first 3 months after program rollout in British Columbia, a number of program design elements were adjusted, creating observed differences between groups of users with respect to the potential impact of program features on user engagement levels. Objective: This study examines the impact of reducing reward size over time and explored the influence of other program features such as quiz timing, health intervention content, and type of reward program on user engagement with a mobile health (mHealth) app. Methods: Participants in this longitudinal, nonexperimental observational study included British Columbia citizens who downloaded the app between March and July 2016. A regression methodology was used to examine the impact of changes to several program design features on quiz offer acceptance and engagement with this mHealth app. Results: Our results, based on the longitudinal app use of 54,917 users (mean age 35, SD 13.2 years; 65.03% [35,647/54,917] female), indicated that the key drivers of the likelihood of continued user engagement, in order of greatest to least impact, were (1) type of rewards earned by users (eg, movies [+355%; P<.001], air travel [+210%; P<.001], and grocery [+140%; P<.001] relative to gas), (2) time delay between early offers (−64%; P<.001), (3) the content of the health intervention (eg, healthy eating [−10%; P<.001] vs exercise [+20%, P<.001] relative to health risk assessments), and (4) changes in the number of points offered. Our results demonstrate that reducing the number of points associated with a particular quiz by 10% only led to a 1% decrease in the likelihood of offer response (P<.001) and that each of the other design features had larger impacts on participant retention than did changes in the number of points. Conclusions: The results of this study demonstrate that this program, built around the principles of behavioral economics in the form of the ongoing awarding of a small number of reward points instantly following the completion of health interventions, was able to drive significantly higher engagement levels than those demonstrated in previous literature exploring the intersection of mHealth apps and financial incentives. Previous studies have demonstrated the presence of incentive matters to user engagement; however, our results indicate that the number of points offered for these reward point–based health interventions is less important than other program design features such as the type of reward points being offered, the timing of intervention and reward offers, and the content of the health interventions in driving continued engagement by users. %M 32773371 %R 10.2196/16797 %U https://www.jmir.org/2020/8/e16797 %U https://doi.org/10.2196/16797 %U http://www.ncbi.nlm.nih.gov/pubmed/32773371 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 9 %N 8 %P e18690 %T Notifications to Improve Engagement With an Alcohol Reduction App: Protocol for a Micro-Randomized Trial %A Bell,Lauren %A Garnett,Claire %A Qian,Tianchen %A Perski,Olga %A Potts,Henry W W %A Williamson,Elizabeth %+ Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom, 44 02076368636, lauren.bell@lshtm.ac.uk %K mobile health %K digital behavior change %K engagement %K micro-randomized trial %K push notifications %K excessive alcohol consumption %K smartphone app %K alcohol %K mHealth %D 2020 %7 7.8.2020 %9 Protocol %J JMIR Res Protoc %G English %X Background: Drink Less is a behavior change app that aims to help users in the general adult population reduce hazardous and harmful alcohol consumption. The app includes a daily push notification, delivered at 11 am, asking users to “Please complete your mood and drinking diaries.” Previous analysis of Drink Less engagement data suggests the current notification strongly influences how users engage with the app in the subsequent hour. To exploit a potential increase of vulnerability of excess drinking and opportunity to engage with the app in the evenings, we changed the delivery time from 11 am to 8 pm. We now aim to further optimise the content and sequence of notifications, testing 30 new evidence-informed notifications targeting the user’s perceived usefulness of the app. Objective: The primary objective is to assess whether sending a notification at 8 pm increases behavioral engagement (opening the app) in the subsequent hour. Secondary objectives include comparing the effect of the new bank of messages with the standard message and effect moderation over time. We also aim to more generally understand the role notifications have on the overall duration, depth, and frequency of engagement with Drink Less over the first 30 days after download. Methods: This is a protocol for a micro-randomized trial with two additional parallel arms. Inclusion criteria are Drink Less users who (1) consent to participate in the trial; (2) self-report a baseline Alcohol Use Disorders Identification Test score of 8 or above; (3) reside in the United Kingdom; (4) age ≥18 years and; (5) report interest in drinking less alcohol. In the micro-randomized trial, participants will be randomized daily at 8 pm to receive no notification, a notification with text from the new message bank, or the standard message. The primary outcome is the time-varying, binary outcome of “Did the user open the app in the hour from 8 pm to 9 pm?”. The primary analysis will estimate the marginal relative risk for the notifications using an estimator developed for micro-randomized trials with binary outcomes. Participants randomized to the parallel arms will receive no notifications (Secondary Arm A), or the standard notification delivered daily at 11 am (Secondary Arm B) over 30 days, allowing the comparison of overall engagement between different notification delivery strategies. Results: Approval was granted by the University College of London’s Departmental Research Ethics Committee (CEHP/2016/556) on October 11, 2019, and The London School of Hygiene and Tropical Medicine Interventions Research Ethics Committee (17929) on November 27, 2019. Recruitment began on January 2, 2020, and is ongoing. Conclusions: Understanding how push notifications may impact engagement with a behavior change app can lead to further improvements in engagement, and ultimately help users reduce their alcohol consumption. This understanding may also be generalizable to other apps that target a variety of behavior changes. International Registered Report Identifier (IRRID): DERR1-10.2196/18690 %M 32763878 %R 10.2196/18690 %U https://www.researchprotocols.org/2020/8/e18690 %U https://doi.org/10.2196/18690 %U http://www.ncbi.nlm.nih.gov/pubmed/32763878 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e15156 %T Rams Have Heart, a Mobile App Tracking Activity and Fruit and Vegetable Consumption to Support the Cardiovascular Health of College Students: Development and Usability Study %A Krzyzanowski,Michelle C %A Kizakevich,Paul N %A Duren-Winfield,Vanessa %A Eckhoff,Randall %A Hampton,Joel %A Blackman Carr,Loneke T %A McCauley,Georgia %A Roberson,Kristina B %A Onsomu,Elijah O %A Williams,John %A Price,Amanda Alise %+ RTI International, 3040 Conwallis Rd, Research Triangle Park, NC, 27709, United States, 1 919 485 5648, mkrzyzanowski@rti.org %K exercise %K cardiovascular disease %K diary %K diet %K mHealth %K mobile phone %D 2020 %7 5.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: With the increasing use of mobile devices to access the internet and as the main computing system of apps, there is a growing market for mobile health apps to provide self-care advice. Their effectiveness with regard to diet and fitness tracking, for example, needs to be examined. The majority of American adults fail to meet daily recommendations for healthy behavior. Testing user engagement with an app in a controlled environment can provide insight into what is effective and not effective in an app focused on improving diet and exercise. Objective: We developed Rams Have Heart, a mobile app, to support a cardiovascular disease (CVD) intervention course. The app tracks healthy behaviors, including fruit and vegetable consumption and physical activity, throughout the day. This paper aimed to present its functionality and evaluated adherence among the African American college student population. Methods: We developed the app using the Personal Health Informatics and Intervention Toolkit, a software framework. Rams Have Heart integrates self-reported health screening with health education, diary tracking, and user feedback modules to acquire data and assess progress. The parent study, conducted at a historically black college and university-designated institution in southeastern United States, consisted of a semester-long intervention administered as an academic course in the fall, for 3 consecutive years. Changes were made after the cohort 1 pilot study, so results only include cohorts 2 and 3, comprising a total of 115 students (n=55 intervention participants and n=54 control participants) aged from 17 to 24 years. Data collected over the study period were transferred using the secure Hypertext Transfer Protocol Secure protocol and stored in a secure Structured Query Language server database accessible only to authorized persons. SAS software was used to analyze the overall app usage and the specific results collected. Results: Of the 55 students in the intervention group, 27 (49%) students in cohort 2 and 25 (45%) in cohort 3 used the Rams Have Heart app at least once. Over the course of the fall semester, app participation dropped off gradually until exam week when most students no longer participated. The average fruit and vegetable intake increased slightly, and activity levels decreased over the study period. Conclusions: Rams Have Heart was developed to allow daily tracking of fruit and vegetable intake and physical activity to support a CVD risk intervention for a student demographic susceptible to obesity, heart disease, and type 2 diabetes. We conducted an analysis of app usage, function, and user results. Although a mobile app provides privacy and flexibility for user participation in a research study, Rams Have Heart did not improve compliance or user outcomes. Health-oriented research studies relying on apps in support of user goals need further evaluation. %M 32755883 %R 10.2196/15156 %U https://mhealth.jmir.org/2020/8/e15156 %U https://doi.org/10.2196/15156 %U http://www.ncbi.nlm.nih.gov/pubmed/32755883 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e19216 %T Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial %A Damschroder,Laura J %A Buis,Lorraine R %A McCant,Felicia A %A Kim,Hyungjin Myra %A Evans,Richard %A Oddone,Eugene Z %A Bastian,Lori A %A Hooks,Gwendolyn %A Kadri,Reema %A White-Clark,Courtney %A Richardson,Caroline R %A Gierisch,Jennifer M %+ Veterans Affairs Center for Clinical Management Research, Ann Arbor Healthcare System, 2215 Fuller Rd (152), Ann Arbor, MI, 48105, United States, 1 7348453603, laura.damschroder@va.gov %K exercise %K veterans %K smartphones %K wearable physical activity tracker %K behavior change %K mobile phone %K online %K app %K mobile app %K wearable %D 2020 %7 4.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Though maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical activity tracker, a Bluetooth-enabled scale, and an app-based dashboard. We tested whether adding personalized coaching components (Stay Strong+Coaching) would improve physical activity compared to Stay Strong alone. Objective: The goal of this study is to compare 12-month outcomes from Stay Strong alone versus Stay Strong+Coaching. Methods: Participants (n=357) were recruited from a national random sample of US veterans of recent wars and randomly assigned to the Stay Strong app alone (n=179) or Stay Strong+Coaching (n=178); both programs lasted 12 months. Personalized coaching components for Stay Strong+Coaching comprised of automated in-app motivational messages (3 per week), telephone-based human health coaching (up to 3 calls), and personalized weekly goal setting. All aspects of the enrollment process and program delivery were accomplished virtually for both groups, except for the telephone-based coaching. The primary outcome was change in physical activity at 12 months postbaseline, measured by average weekly Active Minutes, captured by the Fitbit Charge 2 device. Secondary outcomes included changes in step counts, weight, and patient activation. Results: The average age of participants was 39.8 (SD 8.7) years, and 25.2% (90/357) were female. Active Minutes decreased from baseline to 12 months for both groups (P<.001) with no between-group differences at 6 months (P=.82) or 12 months (P=.98). However, at 12 months, many participants in both groups did not record Active Minutes, leading to missing data in 67.0% (120/179) for Stay Strong and 61.8% (110/178) for Stay Strong+Coaching. Average baseline weight for participants in Stay Strong and Stay Strong+Coaching was 214 lbs and 198 lbs, respectively, with no difference at baseline (P=.54) or at 6 months (P=.28) or 12 months (P=.18) postbaseline based on administrative weights, which had lower rates of missing data. Changes in the number of steps recorded and patient activation also did not differ by arm. Conclusions: Adding personalized health coaching comprised of in-app automated messages, up to 3 coaching calls, plus automated weekly personalized goals, did not improve levels of physical activity compared to using a smartphone app alone. Physical activity in both groups decreased over time. Sustaining long-term adherence and engagement in this mHealth intervention proved difficult; approximately two-thirds of the trial’s 357 participants failed to sync their Fitbit device at 12 months and, thus, were lost to follow-up. Trial Registration: ClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293 International Registered Report Identifier (IRRID): RR2-10.2196/12526 %M 32687474 %R 10.2196/19216 %U http://www.jmir.org/2020/8/e19216/ %U https://doi.org/10.2196/19216 %U http://www.ncbi.nlm.nih.gov/pubmed/32687474 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 9 %N 7 %P e16471 %T Developing Effective Methods for Electronic Health Personalization: Protocol for Health Telescope, a Prospective Interventional Study %A Willemse,Bastiaan Johannes Paulus Cornelis %A Kaptein,Maurits Clemens %A Hasaart,Fleur %+ Jheronimus Academy of Data Science, Sint Janssingel 92, 's-Hertogenbosch, 5211 DA, Netherlands, 31 073 614 5515, b.j.p.c.willemse@tilburguniversity.edu %K eHealth %K mHealth %K personalization %K longitudinal study %K wearables %K panel study %K persuasive technology %K gdpr %D 2020 %7 31.7.2020 %9 Protocol %J JMIR Res Protoc %G English %X Background: Existing evaluations of the effects of mobile apps to encourage physical activity have been criticized owing to their common lack of external validity, their short duration, and their inability to explain the drivers of the observed effects. This protocol describes the setup of Health Telescope, a longitudinal panel study in which the long-term effects of mobile electronic health (eHealth) apps are investigated. By setting up Health Telescope, we aim to (1) understand more about the long-term use of eHealth apps in an externally valid setting, (2) understand the relationships between short-term and long-term outcomes of the usage of eHealth apps, and (3) test different ways in which eHealth app allocation can be personalized. Objective: The objectives of this paper are to (1) demonstrate and motivate the validity of the many choices that we made in setting up an intensive longitudinal study, (2) provide a resource for researchers interested in using data generated by our study, and (3) act as a guideline for researchers interested in setting up their own longitudinal data collection using wearable devices. For the third objective, we explicitly discuss the General Data Protection Regulation and ethical requirements that need to be addressed. Methods: In this 4-month study, a group of approximately 450 participants will have their daily step count measured and will be asked daily about their mood using experience sampling. Once per month, participants will receive an intervention containing a recommendation to download an app that focuses on increasing physical activity. The mechanism for assigning recommendations to participants will be personalized over time, using contextual data obtained from previous interventions. Results: The data collection software has been developed, and all the legal and ethical checks are in place. Recruitment will start in Q4 of 2020. The initial results will be published in 2021. Conclusions: The aim of Health Telescope is to investigate how different individuals respond to different ways of being encouraged to increase their physical activity. In this paper, we detail the setup, methods, and analysis plan that will enable us to reach this aim. International Registered Report Identifier (IRRID): PRR1-10.2196/16471 %M 32734930 %R 10.2196/16471 %U http://www.researchprotocols.org/2020/7/e16471/ %U https://doi.org/10.2196/16471 %U http://www.ncbi.nlm.nih.gov/pubmed/32734930 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18338 %T Effects of Incentives on Adherence to a Web-Based Intervention Promoting Physical Activity: Naturalistic Study %A Wurst,Ramona %A Maliezefski,Anja %A Ramsenthaler,Christina %A Brame,Judith %A Fuchs,Reinhard %+ Department of Sport and Sport Science, University of Freiburg, Schwarzwaldstrasse 175, Freiburg, 79117, Germany, 49 7612034563, ramona.wurst@sport.uni-freiburg.de %K internet-based intervention %K adherence %K incentive %K reward %K mHealth %K eHealth %K exercise %K dropout rate %K usage %K attrition %K telemedicine %D 2020 %7 30.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite many advantages of web-based health behavior interventions such as wide accessibility or low costs, these interventions are often accompanied by high attrition rates, particularly in usage under real-life conditions. It would therefore be helpful to implement strategies such as the use of financial incentives to motivate program participation and increase adherence. Objective: This naturalistic study examined real-life usage data of a 12-week web-based physical activity (PA) intervention (Fitness Coach) among insurants who participated in an additional incentive program (incentive group) and those who did not (nonincentive group). Users in the incentive group had the perspective of receiving €30 (about US $33) cash back at the end of the intervention. Methods: Registration and real-life usage data as part of routine data management and evaluation of the Fitness Coach were analyzed between September 2016 and June 2018. Depending on the duration of use and the weekly recording of tasks, 4 adherence groups (low, occasional, strong, and complete adherence) were defined. Demographic characteristics were collected by a self-reported questionnaire at registration. We analyzed baseline predictors and moderators of complete adherence such as participation in the program, age, gender, and BMI using binary logistic regressions. Results: A total of 18,613 eligible persons registered for the intervention. Of these, 15,482 users chose to participate in the incentive program (incentive group): mean age 42.4 (SD 14.4) years, mean BMI 24.5 (SD 4.0) kg/m2, median (IQR) BMI 23.8 (21.7-26.4) kg/m2; 65.12% (10,082/15,482) female; and 3131 users decided not to use the incentive program (nonincentive group): mean age 40.7 (SD 13.4) years, mean BMI 26.2 (SD 5.0) kg/m2, median BMI 25.3 (IQR 22.6-28.7) kg/m2; 72.18% (2260/3131) female. At the end of the intervention, participants in the incentive program group showed 4.8 times higher complete adherence rates than those in the nonincentive program group (39.2% vs 8.1%), also yielding significantly higher odds to complete the intervention (odds ratio [OR] 12.638) for the incentive program group. Gender significantly moderated the effect with men in the incentive group showing higher odds to be completely adherent than women overall and men in the nonincentive group (OR 1.761). Furthermore, older age and male gender were significant predictors of complete adherence for all participants, whereas BMI did not predict intervention completion. Conclusions: This is the first naturalistic study in the field of web-based PA interventions that shows the potential of even small financial incentives to increase program adherence. Male users, in particular, seem to be strongly motivated by incentives to complete the intervention. Based on these findings, health care providers can use differentiated incentive systems to increase regular participation in web-based PA interventions. %M 32729835 %R 10.2196/18338 %U http://www.jmir.org/2020/7/e18338/ %U https://doi.org/10.2196/18338 %U http://www.ncbi.nlm.nih.gov/pubmed/32729835 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e16856 %T Perceptions and Acceptability of Digital Interventions Among Tuberculosis Patients in Cambodia: Qualitative Study of Video-Based Directly Observed Therapy %A Rabinovich,Lila %A Molton,James Steven %A Ooi,Wei Tsang %A Paton,Nicholas Iain %A Batra,Shelly %A Yoong,Joanne %+ Center for Economic and Social Research, University of Southern California, 1090 Vermont Avenue, NW, Washington, DC, 20005, United States, 1 2138210537, lilarabi@usc.edu %K directly observed therapy %K video recording %K telemedicine %K mobile health %K mHealth %K tuberculosis %K low-income settings %K developing countries %K patient acceptance of health care %K patient acceptability %K Cambodia %D 2020 %7 27.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite the development of effective drugs for treatment, tuberculosis remains one of the leading causes of death from an infectious disease worldwide. One of the greatest challenges to tuberculosis control is patient adherence to treatment. Recent research has shown that video-based directly observed therapy is a feasible and effective approach to supporting treatment adherence in high-income settings. However, few studies have explored the potential for such a solution in a low- or middle-income country setting. Globally, these countries’ rapidly rising rate of mobile penetration suggests that the potential for translation of these results may be high. Objective: We sought to examine patient perceptions related to the use of mobile health, and specifically video-based directly observed therapy, in a previously unstudied patient demographic: patients with tuberculosis in a low-income country setting (Cambodia). Methods: We conducted a cross-sectional qualitative study in urban and periurban areas in Cambodia, consisting of 6 focus groups with tuberculosis patients who were receiving treatment (standard directly observed therapy) through a nongovernmental organization. Results: Familiarity with mobile technology and apps was widespread in this population, and overall willingness to consider a mobile app for video-based directly observed therapy was high. However, we identified potential challenges. First, patients very much valued their frequent in-person interactions with their health care provider, which may be reduced with the video-based directly observed therapy intervention. Second, there may be technical issues to address, including how to make the app suitable for illiterate participants. Conclusions: While video-based directly observed therapy is a promising technology, even in country settings where mobile penetration is reportedly almost universal, it should be introduced with caution. However, the results were generally promising and yielded important insights that not only will be translated into the further adaptation of key features of video-based directly observed therapy for tuberculosis patients in Cambodia, but also can inform the future design and successful implementation of video-based directly observed therapy interventions in low- and middle-income settings more generally. %M 32716309 %R 10.2196/16856 %U https://www.jmir.org/2020/7/e16856 %U https://doi.org/10.2196/16856 %U http://www.ncbi.nlm.nih.gov/pubmed/32716309 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e14315 %T mHealth and Engagement Concerning Persons With Chronic Somatic Health Conditions: Integrative Literature Review %A Tuvesson,Hanna %A Eriksén,Sara %A Fagerström,Cecilia %+ Department of Health and Caring Sciences, Linnaeus University, Universitetsplatsen 1, Växjö, Sweden, 46 0480446915, hanna.tuvesson@lnu.se %K engagement %K eHealth %K mHealth %K somatic disease %K integrative literature review %K telehealth %D 2020 %7 24.7.2020 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Chronic somatic health conditions are a global public health challenge. Being engaged in one’s own health management for such conditions is important, and mobile health (mHealth) solutions are often suggested as key to promoting engagement. Objective: The aim of this study was to review, critically appraise, and synthesize the available research regarding engagement through mHealth for persons with chronic somatic health conditions. Methods: An integrative literature review was conducted. The PubMed, CINAHL, and Inspec databases were used for literature searches. Quality assessment was done with the guidance of Critical Appraisal Skills Programme (CASP) checklists. We used a self-designed study protocol comprising 4 engagement aspects—cognitive, behavioral and emotional, interactional, and the usage of mHealth—as part of the synthesis and analysis. Results: A total of 44 articles met the inclusion criteria and were included in the analysis. mHealth usage was the most commonly occurring engagement aspect, behavioral and emotional aspects the second, cognitive aspects the third, and interactional aspects of engagement the least common aspect in the included articles. The results showed that there is a mix of enablers and barriers to engagement in relation to the 4 engagement aspects. The perceived meaningfulness and need for the solution and its content were important to create and maintain engagement. When perceived as meaningful, suitable, and usable, mHealth can support knowledge gain and learning, facilitate emotional and behavioral aspects such as a sense of confidence, and improve interactions and communications with health care professionals. Conclusions: mHealth solutions have the potential to support health care engagement for persons with chronic somatic conditions. More research is needed to further understand how, by which means, when, and among whom mHealth could further improve engagement for this population. %M 32706686 %R 10.2196/14315 %U http://mhealth.jmir.org/2020/7/e14315/ %U https://doi.org/10.2196/14315 %U http://www.ncbi.nlm.nih.gov/pubmed/32706686 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e17207 %T Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence: Randomized Controlled Trial %A Siemer,Lutz %A Brusse-Keizer,Marjolein G J %A Postel,Marloes G %A Ben Allouch,Somaya %A Sanderman,Robbert %A Pieterse,Marcel E %+ Technology, Health & Care Research Group, Saxion University of Applied Sciences, MH Tromplaan 28, Enschede, 7513 AB, Netherlands, 31 17678025906, l.siemer@utwente.nl %K blended treatment %K smoking cessation %K adherence %K predictors %K tobacco %K prevention %D 2020 %7 23.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. Objective: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. Methods: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. Results: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164). Conclusions: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. Trial Registration: Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113 %M 32459643 %R 10.2196/17207 %U http://www.jmir.org/2020/7/e17207/ %U https://doi.org/10.2196/17207 %U http://www.ncbi.nlm.nih.gov/pubmed/32459643 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e15732 %T Scheduled Telephone Support for Internet Cognitive Behavioral Therapy for Depression in Patients at Risk for Dropout: Pragmatic Randomized Controlled Trial %A Pihlaja,Satu %A Lahti,Jari %A Lipsanen,Jari Olavi %A Ritola,Ville %A Gummerus,Eero-Matti %A Stenberg,Jan-Henry %A Joffe,Grigori %+ Department of Psychiatry, University of Helsinki and Helsinki University Hospital, Hospital District of Helsinki and Uusimaa, PO Box 590, Helsinki, 00029 HUS, Finland, 358 40 513 6500, Grigori.joffe@hus.fi %K internet CBT %K depression %K scheduled telephone support %K adherence %K routine clinical practice %D 2020 %7 23.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Therapist-supported, internet-delivered cognitive behavioral therapy (iCBT) is efficient in the treatment of depression. However, the optimal mode and intensity of therapist support remain to be identified. Scheduled telephone support (STS) may improve adherence and outcomes but, as it is time- and resource-consuming, should be reserved for patients for whom the usual support may be insufficient. Objective: This paper aims to reveal whether add-on STS for patients at risk of dropping out improves treatment adherence and symptoms in iCBT for depression. Methods: Among patients participating in an ongoing large observational routine clinical practice study of iCBT for depression delivered nationwide by Helsinki University Hospital (HUS-iCBT), those demonstrating a ≥14-day delay in initiation of treatment received invitations to this subsidiary STS study. A total of 100 consenting patients were randomly allocated to either HUS-iCBT as usual (control group, n=50) or HUS-iCBT plus add-on STS (intervention group, n=50). Proportions of those reaching midtreatment and treatment end point served as the primary outcome; secondary outcomes were change in Beck Depression Inventory (BDI)–measured depressive symptoms and time spent in treatment. Results: Add-on STS raised the proportion of patients reaching midtreatment compared with HUS-iCBT as usual (29/50, 58% vs 18/50, 36%; P=.045) and treatment end point (12/50, 24% vs 3/50, 6%; P=.02). Change in BDI score also favored add-on STS (3.63 points vs 1.1 points; P=.049), whereas duration of treatment did not differ. Conclusions: Add-on STS enhances adherence and symptom improvement of patients at risk of dropping out of iCBT for depression in routine clinical practice. Trial Registration: International Standard Randomised Controlled Trial Number (ISRCTN) 55123131; http://www.isrctn.com/ISRCTN55123131. %M 32706658 %R 10.2196/15732 %U http://www.jmir.org/2020/7/e15732/ %U https://doi.org/10.2196/15732 %U http://www.ncbi.nlm.nih.gov/pubmed/32706658 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e17534 %T User Engagement Among Diverse Adults in a 12-Month Text Message–Delivered Diabetes Support Intervention: Results from a Randomized Controlled Trial %A Nelson,Lyndsay A %A Spieker,Andrew %A Greevy,Robert %A LeStourgeon,Lauren M %A Wallston,Kenneth A %A Mayberry,Lindsay S %+ Department of Medicine, Vanderbilt University Medical Center, 2525 West End Ave, Suite 450, Nashville, TN, 37203, United States, 1 6158757621, lyndsay.a.nelson@vumc.org %K engagement %K text messaging %K mobile health %K mHealth %K mobile phone %K technology %K diabetes mellitus, type 2 %K self-management %K self-care %K medication adherence %D 2020 %7 21.7.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Text message–delivered interventions are a feasible and scalable approach for improving chronic disease self-care and reducing health disparities; however, information on long-term user engagement with these interventions is limited. Objective: The aim of this study is to examine user engagement in a 12-month text message–delivered intervention supporting diabetes self-care, called REACH (Rapid Education/Encouragement And Communications for Health), among racially and socioeconomically diverse patients with type 2 diabetes (T2D). We explored time trends in engagement, associations between patient characteristics and engagement, and whether the addition of a human component or allowing patients to change their text frequency affected engagement. Qualitative data informed patients’ subjective experience of their engagement. Methods: We recruited patients with T2D for a randomized trial evaluating mobile phone support relative to enhanced treatment as usual. This analysis was limited to participants assigned to the intervention. Participants completed a survey and hemoglobin A1c (HbA1c) test and received REACH text messages, including self-care promotion texts, interactive texts asking about medication adherence, and adherence feedback texts. For the first 6 months, texts were sent daily, and half of the participants also received monthly phone coaching. After 6 months, coaching stopped, and participants had the option to receive fewer texts for the subsequent 6 months. We defined engagement via responses to the interactive texts and responses to a follow-up interview. We used regression models to analyze associations with response rate and thematic and structural analysis to understand participants’ reasons for responding to the texts and their preferred text frequency. Results: The participants were, on average, aged 55.8 (SD 9.8) years, 55.2% (137/248) female, and 52.0% (129/248) non-White; 40.7% (101/248) had ≤ a high school education, and 40.7% (101/248) had an annual household income