TY - JOUR AU - Mahmoudi Asl, Aysan AU - Molinari Ulate, Mauricio AU - Franco Martin, Manuel AU - van der Roest, Henriëtte PY - 2022/8/1 TI - Methodologies Used to Study the Feasibility, Usability, Efficacy, and Effectiveness of Social Robots For Elderly Adults: Scoping Review JO - J Med Internet Res SP - e37434 VL - 24 IS - 8 KW - aged KW - dementia KW - social robots KW - pet-bots KW - community settings KW - long-term care KW - methods KW - scoping review N2 - Background: New research fields to design social robots for older people are emerging. By providing support with communication and social interaction, these robots aim to increase quality of life. Because of the decline in functioning due to cognitive impairment in older people, social robots are regarded as promising, especially for people with dementia. Although study outcomes are hopeful, the quality of studies on the effectiveness of social robots for the elderly is still low due to many methodological limitations. Objective: We aimed to review the methodologies used thus far in studies evaluating the feasibility, usability, efficacy, and effectiveness of social robots in clinical and social settings for elderly people, including persons with dementia. Methods: Dedicated search strings were developed. Searches in MEDLINE (PubMed), Web of Science, PsycInfo, and CINAHL were performed on August 13, 2020. Results: In the 33 included papers, 23 different social robots were investigated for their feasibility, usability, efficacy, and effectiveness. A total of 8 (24.2%) studies included elderly persons in the community, 9 (27.3%) included long-term care facility residents, and 16 (48.5%) included people with dementia. Most of the studies had a single aim, of which 7 (21.2%) focused on efficacy and 7 (21.2%) focused on effectiveness. Moreover, forms of randomized controlled trials were the most applied designs. Feasibility and usability were often studied together in mixed methods or experimental designs and were most often studied in individual interventions. Feasibility was often assessed with the Unified Theory of the Acceptance and Use of Technology model. Efficacy and effectiveness studies used a range of psychosocial and cognitive outcome measures. However, the included studies failed to find significant improvements in quality of life, depression, and cognition. Conclusions: This study identified several shortcomings in methodologies used to evaluate social robots, resulting in ambivalent study findings. To improve the quality of these types of studies, efficacy/effectiveness studies will benefit from appropriate randomized controlled trial designs with large sample sizes and individual intervention sessions. Experimental designs might work best for feasibility and usability studies. For each of the 3 goals (efficacy/effectiveness, feasibility, and usability) we also recommend a mixed method of data collection. Multiple interaction sessions running for at least 1 month might aid researchers in drawing significant results and prove the real long-term impact of social robots. UR - https://www.jmir.org/2022/8/e37434 UR - http://dx.doi.org/10.2196/37434 UR - http://www.ncbi.nlm.nih.gov/pubmed/35916695 ID - info:doi/10.2196/37434 ER - TY - JOUR AU - Wannheden, Carolina AU - Åberg-Wennerholm, Matilda AU - Dahlberg, Marie AU - Revenäs, Åsa AU - Tolf, Sara AU - Eftimovska, Elena AU - Brommels, Mats PY - 2022/8/1 TI - Digital Health Technologies Enabling Partnerships in Chronic Care Management: Scoping Review JO - J Med Internet Res SP - e38980 VL - 24 IS - 8 KW - participatory health KW - digital health KW - eHealth KW - collaborative care KW - participatory health informatics KW - cocare KW - partnership care management KW - chronic disease KW - long-term conditions KW - mobile phone KW - scoping review N2 - Background: An increasing number of patients expect and want to play a greater role in their treatment and care decisions. This emphasizes the need to adopt collaborative health care practices, which implies collaboration among interprofessional health care teams and patients, their families, caregivers, and communities. In recent years, digital health technologies that support self-care and collaboration between the community and health care providers (ie, participatory health technologies) have received increasing attention. However, knowledge regarding the features of such technologies that support effective patient-professional partnerships is still limited. Objective: This study aimed to map and assess published studies on participatory health technologies intended to support partnerships among patients, caregivers, and health care professionals in chronic care, focusing specifically on identifying the main features of these technologies. Methods: A scoping review covering scientific publications in English between January 2008 and December 2020 was performed. We searched PubMed and Web of Science databases. Peer-reviewed qualitative, quantitative, and mixed methods studies that evaluated digital health technologies for patient-professional partnerships in chronic care settings were included. The data were charted and analyzed thematically. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was used. Results: This review included 32 studies, reported in 34 papers. The topic of participatory health technologies experienced a slightly increasing trend across publication years, with most papers originating from the United States and Norway. Diabetes and cardiovascular diseases were the most common conditions addressed. Of the 32 studies, 12 (38%) evaluated the influence of participatory health technologies on partnerships, mostly with positive outcomes, although we also identified how partnership relationships and the nature of collaborative work could be challenged when the roles and expectations between users were unclear. Six common features of participatory health technologies were identified: patient-professional communication, self-monitoring, tailored self-care support, self-care education, care planning, and community forums for peer-to-peer interactions. Conclusions: Our findings emphasize the importance of clarifying mutual expectations and carefully considering the implications that the introduction of participatory health technologies may have on the work of patients and health care professionals, both individually and in collaboration. A knowledge gap remains regarding the use of participatory health technologies to effectively support patient-professional partnerships in chronic care management. UR - https://www.jmir.org/2022/8/e38980 UR - http://dx.doi.org/10.2196/38980 UR - http://www.ncbi.nlm.nih.gov/pubmed/35916720 ID - info:doi/10.2196/38980 ER - TY - JOUR AU - Darko, Mirekuwaa Elizabeth AU - Kleib, Manal AU - Olson, Joanne PY - 2022/8/4 TI - Social Media Use for Research Participant Recruitment: Integrative Literature Review JO - J Med Internet Res SP - e38015 VL - 24 IS - 8 KW - advertisement KW - recruitment KW - research participants KW - social media KW - mobile phone N2 - Background: Social media tools have provided health researchers with the opportunity to engage with communities and groups in a nonconventional manner to recruit participants for health research. Using social media to advertise research opportunities and recruit participants facilitates accessibility to participants from broad geographical areas and diverse populations. However, little guidance is provided by ethics review boards for researchers to effectively use this recruitment method in their research. Objective: This study sought to explore the literature on the use of social media for participant recruitment for research studies and identify the best practices for recruiting participants using this method. Methods: An integrative review approach was used to synthesize the literature. A total of 5 health sciences databases, namely, EMBASE (Ovid), MEDLINE (Ovid and EBSCOhost), PsycINFO (Ovid), Scopus (Elsevier), and CINAHL Plus with Full Text (EBSCOhost), were searched using predefined keywords and inclusion and exclusion criteria. The initial search was conducted in October 2020 and was updated in February 2022. Descriptive and content analyses were applied to synthesize the results, and the findings are presented in a narrative and tabular format. Results: A total of 96 records were included in this review, 83 (86%) from the initial search and 13 (14%) from the updated search. The publication year ranged between 2011 and 2022, with most publications (63/96, 66%) being from the United States. Regarding recruitment strategy, 45% (43/96) of the studies exclusively used social media, whereas 51% (49/96) used social media in conjunction with other strategies. The remaining 4% (4/96) provided guidelines and recommendations for social media recruitment. Notably, 38% (36/96) of these studies involved hard-to-reach populations. The findings also revealed that the use of social media is a cost-effective and efficient strategy for recruiting research participants. Despite the expanded use across different populations, there is limited participation of older adults in social media recruitment. Conclusions: This review provides important insights into the current use of social media for health research participant recruitment. Ethics boards and research support services in academic institutions are encouraged to explicitly provide researchers with guidelines on the use of social media for health research participant recruitment. A preliminary guideline prepared based on the findings of this review is proposed to spark further development in this area. UR - https://www.jmir.org/2022/8/e38015 UR - http://dx.doi.org/10.2196/38015 UR - http://www.ncbi.nlm.nih.gov/pubmed/35925655 ID - info:doi/10.2196/38015 ER - TY - JOUR AU - Wang, Tingting AU - Giunti, Guido AU - Melles, Marijke AU - Goossens, Richard PY - 2022/8/4 TI - Digital Patient Experience: Umbrella Systematic Review JO - J Med Internet Res SP - e37952 VL - 24 IS - 8 KW - digital health KW - eHealth KW - telemedicine KW - telehealth KW - mobile health KW - mHealth KW - patient experience KW - user experience KW - influencing factors KW - user-centered design KW - human-computer interaction N2 - 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. UR - https://www.jmir.org/2022/8/e37952 UR - http://dx.doi.org/10.2196/37952 UR - http://www.ncbi.nlm.nih.gov/pubmed/35925651 ID - info:doi/10.2196/37952 ER - TY - JOUR AU - Milne-Ives, Madison AU - Carroll, Camille AU - Meinert, Edward PY - 2022/8/5 TI - Self-management Interventions for People With Parkinson Disease: Scoping Review JO - J Med Internet Res SP - e40181 VL - 24 IS - 8 KW - Parkinson disease KW - self-management KW - self-care KW - home nursing KW - self-efficacy KW - quality of life KW - signs and symptoms KW - health behaviour N2 - Background: Parkinson disease can impose substantial distress and costs on patients, their families and caregivers, and health care systems. To address these burdens for families and health care systems, there is a need to better support patient self-management. To achieve this, an overview of the current state of the literature on self-management is needed to identify what is being done, how well it is working, and what might be missing. Objective: The aim of this scoping review was to provide an overview of the current body of research on self-management interventions for people with Parkinson disease and identify any knowledge gaps. Methods: The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) and Population, Intervention, Comparator, Outcome, and Study type frameworks were used to structure the methodology of the review. Due to time and resource constraints, 1 reviewer systematically searched 4 databases (PubMed, Ovid, Scopus, and Web of Science) for the evaluations of self-management interventions for Parkinson disease published in English. The references were screened using the EndNote X9 citation management software, titles and abstracts were manually reviewed, and studies were selected for inclusion based on the eligibility criteria. Data were extracted into a pre-established form and synthesized in a descriptive analysis. Results: There was variation among the studies on study design, sample size, intervention type, and outcomes measured. The randomized controlled trials had the strongest evidence of effectiveness: 5 out of 8 randomized controlled trials found a significant difference between groups favoring the intervention on their primary outcome, and the remaining 3 had significant effects on at least some of the secondary outcomes. The 2 interventions included in the review that targeted mental health outcomes both found significant changes over time, and the 3 algorithms evaluated performed well. The remaining studies examined patient perceptions, acceptability, and cost-effectiveness and found generally positive results. Conclusions: This scoping review identified a wide variety of interventions designed to support various aspects of self-management for people with Parkinson disease. The studies all generally reported positive results, and although the strength of the evidence varied, it suggests that self-management interventions are promising for improving the care and outcomes of people with Parkinson disease. However, the research tended to focus on the motor aspects of Parkinson disease, with few nonmotor or holistic interventions, and there was a lack of evaluation of cost-effectiveness. This research will be important to providing self-management interventions that meet the varied and diverse needs of people with Parkinson disease and determining which interventions are worth promoting for widespread adoption. UR - https://www.jmir.org/2022/8/e40181 UR - http://dx.doi.org/10.2196/40181 UR - http://www.ncbi.nlm.nih.gov/pubmed/35930315 ID - info:doi/10.2196/40181 ER - TY - JOUR AU - Pedamallu, Havisha AU - Ehrhardt, J. Matthew AU - Maki, Julia AU - Carcone, Idalski April AU - Hudson, M. Melissa AU - Waters, A. Erika PY - 2022/8/9 TI - Technology-Delivered Adaptations of Motivational Interviewing for the Prevention and Management of Chronic Diseases: Scoping Review JO - J Med Internet Res SP - e35283 VL - 24 IS - 8 KW - motivational interviewing KW - technology KW - telehealth KW - health behavior KW - chronic disease KW - socioeconomic factors KW - health promotion KW - disease management KW - primary prevention KW - secondary prevention KW - minority health N2 - Background: Motivational interviewing (MI) can increase health-promoting behaviors and decrease health-damaging behaviors. However, MI is often resource intensive, precluding its use with people with limited financial or time resources. Mobile health?based versions of MI interventions or technology-delivered adaptations of MI (TAMIs) might increase reach. Objective: We aimed to understand the characteristics of existing TAMIs. We were particularly interested in the inclusion of people from marginalized sociodemographic groups, whether the TAMI addressed sociocontextual factors, and how behavioral and health outcomes were reported. Methods: We employed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews to conduct our scoping review. We searched PubMed, CINAHL, and PsycInfo from January 1, 1996, to April 6, 2022, to identify studies that described interventions incorporating MI into a mobile or electronic health platform. For inclusion, the study was required to (1) describe methods/outcomes of an MI intervention, (2) feature an intervention delivered automatically via a mobile or electronic health platform, and (3) report a behavioral or health outcome. The exclusion criteria were (1) publication in a language other than English and (2) description of only in-person intervention delivery (ie, no TAMI). We charted results using Excel (Microsoft Corp). Results: Thirty-four studies reported the use of TAMIs. Sample sizes ranged from 10 to 2069 participants aged 13 to 70 years. Most studies (n=27) directed interventions toward individuals engaging in behaviors that increased chronic disease risk. Most studies (n=22) oversampled individuals from marginalized sociodemographic groups, but few (n=3) were designed specifically with marginalized groups in mind. TAMIs used text messaging (n=8), web-based intervention (n=22), app + text messaging (n=1), and web-based intervention + text messaging (n=3) as delivery platforms. Of the 34 studies, 30 (88%) were randomized controlled trials reporting behavioral and health-related outcomes, 23 of which reported statistically significant improvements in targeted behaviors with TAMI use. TAMIs improved targeted health behaviors in the remaining 4 studies. Moreover, 11 (32%) studies assessed TAMI feasibility, acceptability, or satisfaction, and all rated TAMIs highly in this regard. Among 20 studies with a disproportionately high number of people from marginalized racial or ethnic groups compared with the general US population, 16 (80%) reported increased engagement in health behaviors or better health outcomes. However, no TAMIs included elements that addressed sociocontextual influences on behavior or health outcomes. Conclusions: Our findings suggest that TAMIs may improve some health promotion and disease management behaviors. However, few TAMIs were designed specifically for people from marginalized sociodemographic groups, and none included elements to help address sociocontextual challenges. Research is needed to determine how TAMIs affect individual health outcomes and how to incorporate elements that address sociocontextual factors, and to identify the best practices for implementing TAMIs into clinical practice. UR - https://www.jmir.org/2022/8/e35283 UR - http://dx.doi.org/10.2196/35283 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943775 ID - info:doi/10.2196/35283 ER - TY - JOUR AU - Ahmed, Arfan AU - Aziz, Sarah AU - Abd-alrazaq, Alaa AU - Farooq, Faisal AU - Sheikh, Javaid PY - 2022/8/9 TI - Overview of Artificial Intelligence?Driven Wearable Devices for Diabetes: Scoping Review JO - J Med Internet Res SP - e36010 VL - 24 IS - 8 KW - diabetes KW - artificial intelligence KW - wearable devices KW - machine learning KW - mobile phone N2 - Background: Prevalence of diabetes has steadily increased over the last few decades with 1.5 million deaths reported in 2012 alone. Traditionally, analyzing patients with diabetes has remained a largely invasive approach. Wearable devices (WDs) make use of sensors historically reserved for hospital settings. WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics. Objective: This review aimed to provide an overview of AI-driven WD features for diabetes and their use in monitoring diabetes-related parameters. Methods: We searched 7 of the most popular bibliographic databases using 3 groups of search terms related to diabetes, WDs, and AI. A 2-stage process was followed for study selection: reading abstracts and titles followed by full-text screening. Two reviewers independently performed study selection and data extraction, and disagreements were resolved by consensus. A narrative approach was used to synthesize the data. Results: From an initial 3872 studies, we report the features from 37 studies post filtering according to our predefined inclusion criteria. Most of the studies targeted type 1 diabetes, type 2 diabetes, or both (21/37, 57%). Many studies (15/37, 41%) reported blood glucose as their main measurement. More than half of the studies (21/37, 57%) had the aim of estimation and prediction of glucose or glucose level monitoring. Over half of the reviewed studies looked at wrist-worn devices. Only 41% of the study devices were commercially available. We observed the use of multiple sensors with photoplethysmography sensors being most prevalent in 32% (12/37) of studies. Studies reported and compared >1 machine learning (ML) model with high levels of accuracy. Support vector machine was the most reported (13/37, 35%), followed by random forest (12/37, 32%). Conclusions: This review is the most extensive work, to date, summarizing WDs that use ML for people with diabetes, and provides research direction to those wanting to further contribute to this emerging field. Given the advancements in WD technologies replacing the need for invasive hospital setting devices, we see great advancement potential in this domain. Further work is needed to validate the ML approaches on clinical data from WDs and provide meaningful analytics that could serve as data gathering, monitoring, prediction, classification, and recommendation devices in the context of diabetes. UR - https://www.jmir.org/2022/8/e36010 UR - http://dx.doi.org/10.2196/36010 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943772 ID - info:doi/10.2196/36010 ER - TY - JOUR AU - Davis, A. Jacqueline AU - Ohan, L. Jeneva AU - Gibson, Y. Lisa AU - Prescott, L. Susan AU - Finlay-Jones, L. Amy PY - 2022/8/9 TI - Understanding Engagement in Digital Mental Health and Well-being Programs for Women in the Perinatal Period: Systematic Review Without Meta-analysis JO - J Med Internet Res SP - e36620 VL - 24 IS - 8 KW - digital interventions KW - perinatal KW - mental health KW - well-being KW - logic model KW - systematic review KW - mobile phone N2 - 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 UR - https://www.jmir.org/2022/8/e36620 UR - http://dx.doi.org/10.2196/36620 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943773 ID - info:doi/10.2196/36620 ER - TY - JOUR AU - Schliemann, Désirée AU - Tan, Min Min AU - Hoe, Kok Wilfred Mok AU - Mohan, Devi AU - Taib, Aishah Nur AU - Donnelly, Michael AU - Su, Tin Tin PY - 2022/8/15 TI - mHealth Interventions to Improve Cancer Screening and Early Detection: Scoping Review of Reviews JO - J Med Internet Res SP - e36316 VL - 24 IS - 8 KW - mobile health KW - mHealth KW - cancer screening KW - scoping review of reviews KW - cancer KW - cancer detection KW - oncology KW - digital health KW - scoping review KW - review KW - mobile phone N2 - Background: Cancer screening provision in resource-constrained settings tends to be opportunistic, and uptake tends to be low, leading to delayed presentation and treatment and poor survival. Objective: The aim of this study was to identify, review, map, and summarize findings from different types of literature reviews on the use of mobile health (mHealth) technologies to improve the uptake of cancer screening. Methods: The review methodology was guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Ovid MEDLINE, PyscINFO, and Embase were searched from inception to May 2021. The eligible criteria included reviews that focused on studies of interventions that used mobile phone devices to promote and deliver cancer screening and described the effectiveness or implementation of mHealth intervention outcomes. Key data fields such as study aims, types of cancer, mHealth formats, and outcomes were extracted, and the data were analyzed to address the objective of the review. Results: Our initial search identified 1981 titles, of which 12 (0.61%) reviews met the inclusion criteria (systematic reviews: n=6, 50%; scoping reviews: n=4, 33%; rapid reviews: n=1, 8%; narrative reviews: n=1, 8%). Most (57/67, 85%) of the interventions targeted breast and cervical cancer awareness and screening uptake. The most commonly used mHealth technologies for increasing cancer screening uptake were SMS text messages and telephone calls. Overall, mHealth interventions increased knowledge about screening and had high acceptance among participants. The likelihood of achieving improved uptake-related outcomes increased when interventions used >1 mode of communication (telephone reminders, physical invitation letters, and educational pamphlets) together with mHealth. Conclusions: mHealth interventions increase cancer screening uptake, although multiple modes used in combination seem to be more effective. UR - https://www.jmir.org/2022/8/e36316 UR - http://dx.doi.org/10.2196/36316 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969450 ID - info:doi/10.2196/36316 ER - TY - JOUR AU - Elkefi, Safa AU - Asan, Onur PY - 2022/8/16 TI - Digital Twins for Managing Health Care Systems: Rapid Literature Review JO - J Med Internet Res SP - e37641 VL - 24 IS - 8 KW - health care KW - digital twins KW - safety KW - information management KW - supply chain management KW - operational control KW - well-being promotion KW - human factors KW - technology KW - health informatics KW - literature synthesis KW - scheduling and optimization KW - digital health N2 - Background: Although most digital twin (DT) applications for health care have emerged in precision medicine, DTs can potentially support the overall health care process. DTs (twinned systems, processes, and products) can be used to optimize flows, improve performance, improve health outcomes, and improve the experiences of patients, doctors, and other stakeholders with minimal risk. Objective: This paper aims to review applications of DT systems, products, and processes as well as analyze the potential of these applications for improving health care management and the challenges associated with this emerging technology. Methods: We performed a rapid review of the literature and reported available studies on DTs and their applications in health care management. We searched 5 databases for studies published between January 2002 and January 2022 and included peer-reviewed studies written in English. We excluded studies reporting DT usage to support health care practice (organ transplant, precision medicine, etc). Studies were analyzed based on their contribution toward DT technology to improve user experience in health care from human factors and systems engineering perspectives, accounting for the type of impact (product, process, or performance/system level). Challenges related to the adoption of DTs were also summarized. Results: The DT-related studies aimed at managing health care systems have been growing over time from 0 studies in 2002 to 17 in 2022, with 7 published in 2021 (N=17 studies). The findings reported on applications categorized by DT type (system: n=8; process: n=5; product: n=4) and their contributions or functions. We identified 4 main functions of DTs in health care management including safety management (n=3), information management (n=2), health management and well-being promotion (n=3), and operational control (n=9). DTs used in health care systems management have the potential to avoid unintended or unexpected harm to people during the provision of health care processes. They also can help identify crisis-related threats to a system and control the impacts. In addition, DTs ensure privacy, security, and real-time information access to all stakeholders. Furthermore, they are beneficial in empowering self-care abilities by enabling health management practices and providing high system efficiency levels by ensuring that health care facilities run smoothly and offer high-quality care to every patient. Conclusions: The use of DTs for health care systems management is an emerging topic. This can be seen in the limited literature supporting this technology. However, DTs are increasingly being used to ensure patient safety and well-being in an organized system. Thus, further studies aiming to address the challenges of health care systems challenges and improve their performance should investigate the potential of DT technology. In addition, such technologies should embed human factors and ergonomics principles to ensure better design and more successful impact on patient and doctor experiences. UR - https://www.jmir.org/2022/8/e37641 UR - http://dx.doi.org/10.2196/37641 UR - http://www.ncbi.nlm.nih.gov/pubmed/35972776 ID - info:doi/10.2196/37641 ER - TY - JOUR AU - Ni, Ruping AU - Liu, Maobai AU - Huang, Shunmin AU - Yang, Jing PY - 2022/8/16 TI - Effects of eHealth Interventions on Quality of Life and Psychological Outcomes in Cardiac Surgery Patients: Systematic Review and Meta-analysis JO - J Med Internet Res SP - e40090 VL - 24 IS - 8 KW - eHealth KW - eHealth intervention KW - cardiac surgery KW - depression KW - anxiety KW - quality of life KW - meta-analysis KW - heart disease KW - surgery KW - heart surgery KW - post-operative KW - postoperative KW - mental health KW - home care KW - digital health intervention KW - digital health KW - outcomes KW - psychological KW - physiological KW - physiology KW - psychology KW - compliance N2 - Background: Patients undergoing heart surgery may experience a range of physiological changes, and the postoperative recovery time is long. Patients and their families often have concerns about quality of life (QoL) after discharge. eHealth interventions may improve patient participation, ensure positive and effective health management, improve the quality of at-home care and the patient's quality of life, and reduce rates of depression. Objective: The purpose of this study was to evaluate the effects of eHealth interventions on the physiology, psychology, and compliance of adult patients after cardiac surgery to provide a theoretical basis for clinical practice. Methods: We conducted systematic searches of the following 4 electronic databases: PubMed, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Mean (SD) values were used to calculate the pooled effect sizes for all consecutive data, including QoL, anxiety, and depression. Where the same results were obtained using different instruments, we chose the standardized mean difference with a 95% CI to represent the combined effect size; otherwise, the mean difference (MD) with a 95% CI was used. Odds ratios were used to calculate the combined effect size for all dichotomous data. The Cohen Q test for chi-square distribution and an inconsistency index (I2) were used to test for heterogeneity among the studies. We chose a fixed-effects model to estimate the effect size if there was no significant heterogeneity in the data (I2?50%); otherwise, a random-effects model was used. The quality of the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). Results: The search identified 3632 papers, of which 19 met the inclusion criteria. In terms of physical outcomes, the score of the control group was lower than that of the intervention group (MD 0.15, 95% CI 0.03-0.27, I2=0%, P=.02). There was no significant difference in the mental outcomes between the intervention and control groups (MD 0.10, 95% CI ?0.03 to 0.24, I2=46.4%, P=.14). The control group?s score was lower than that of the intervention group for the depression outcomes (MD ?0.53, 95% CI ?0.89 to ?0.17, I2=57.1%, P=.004). Compliance outcomes improved in most intervention groups. The results of the sensitivity analysis were robust. Nearly half of the included studies (9/19, 47%) had a moderate to high risk of bias. The quality of the evidence was medium to low. Conclusions: eHealth improved the physical component of quality of life and depression after cardiac surgery; however, there was no statistical difference in the mental component of quality of life. The effectiveness of eHealth on patient compliance has been debated. Further high-quality studies on digital health are required. Trial Registration: PROSPERO CRD42022327305; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=327305 UR - https://www.jmir.org/2022/8/e40090 UR - http://dx.doi.org/10.2196/40090 UR - http://www.ncbi.nlm.nih.gov/pubmed/35972792 ID - info:doi/10.2196/40090 ER - TY - JOUR AU - Longhini, Jessica AU - Rossettini, Giacomo AU - Palese, Alvisa PY - 2022/8/18 TI - Digital Health Competencies Among Health Care Professionals: Systematic Review JO - J Med Internet Res SP - e36414 VL - 24 IS - 8 KW - eHealth literacy KW - eHealth competencies KW - digital health KW - competencies KW - eHealth KW - health literacy KW - digital technology KW - health care professionals KW - health care workers KW - review KW - systematic review N2 - Background: Digitalization is not fully implemented in clinical practice, and several factors have been identified as possible barriers, including the competencies of health care professionals. However, no summary of the available evidence has been provided to date to depict digital health competencies that have been investigated among health care professionals, the tools used in assessing such competencies, and the effective interventions to improve them. Objective: This review aims to summarize digital health competencies investigated to date and the tools used to assess them among health care professionals. Methods: A systematic review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was performed. The MEDLINE, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, and Scopus databases were accessed up to September 4, 2021. Studies assessing digital health competencies with quantitative designs, targeting health care professionals, and written in English were included. The methodological quality of included studies was evaluated using the Joanna Briggs Institute tools. Results: A total of 26 studies, published from 1999 to 2021, met the inclusion criteria, and the majority were cross sectional in design, while only 2 were experimental study designs. Most studies were assessed with moderate to low methodological quality; 4 categories and 9 subcategories of investigated digital health competencies have been identified. The most investigated category was ?Self-rated competencies,? followed by ?Psychological and emotional aspects toward digital technologies,? ?Use of digital technologies,? and ?Knowledge about digital technologies.? In 35% (9/26) of the studies, a previously validated tool was used to measure the competencies assessed, while others developed ad hoc questionnaires. Conclusions: Mainly descriptive studies with issues regarding methodology quality have been produced to date investigating 4 main categories of digital health competencies mostly with nonvalidated tools. Competencies investigated might be considered while designing curricula for undergraduate, postgraduate, and continuing education processes, whereas the methodological lacks detected might be addressed with future research. There is a need to expand research on psychological and emotional elements and the ability to use digital technology to self-learn and teach others. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021282775; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282775 UR - https://www.jmir.org/2022/8/e36414 UR - http://dx.doi.org/10.2196/36414 UR - http://www.ncbi.nlm.nih.gov/pubmed/35980735 ID - info:doi/10.2196/36414 ER - TY - JOUR AU - Al-Dhahir, Isra AU - Reijnders, Thomas AU - Faber, S. Jasper AU - van den Berg-Emons, J. Rita AU - Janssen, R. Veronica AU - Kraaijenhagen, A. Roderik AU - Visch, T. Valentijn AU - Chavannes, H. Niels AU - Evers, M. Andrea W. PY - 2022/8/24 TI - The Barriers and Facilitators of eHealth-Based Lifestyle Intervention Programs for People With a Low Socioeconomic Status: Scoping Review JO - J Med Internet Res SP - e34229 VL - 24 IS - 8 KW - eHealth KW - lifestyle interventions KW - health behaviors KW - low socioeconomic status KW - intervention development KW - barriers KW - facilitators KW - prevention KW - intervention evaluation N2 - Background: Promoting health behaviors and preventing chronic diseases through a healthy lifestyle among those with a low socioeconomic status (SES) remain major challenges. eHealth interventions are a promising approach to change unhealthy behaviors in this target group. Objective: This review aims to identify key components, barriers, and facilitators in the development, reach, use, evaluation, and implementation of eHealth lifestyle interventions for people with a low SES. This review provides an overview for researchers and eHealth developers, and can assist in the development of eHealth interventions for people with a low SES. Methods: We performed a scoping review based on Arksey and O?Malley?s framework. A systematic search was conducted on PubMed, MEDLINE (Ovid), Embase, Web of Science, and the Cochrane Library, using terms related to a combination of the following key constructs: eHealth, lifestyle, low SES, development, reach, use, evaluation, and implementation. There were no restrictions on the date of publication for articles retrieved upon searching the databases. Results: The search identified 1323 studies, of which 42 met our inclusion criteria. An update of the search led to the inclusion of 17 additional studies. eHealth lifestyle interventions for people with a low SES were often delivered via internet-based methods (eg, websites, email, Facebook, and smartphone apps) and offline methods, such as texting. A minority of the interventions combined eHealth lifestyle interventions with face-to-face or telephone coaching, or wearables (blended care). We identified the use of different behavioral components (eg, social support) and technological components (eg, multimedia) in eHealth lifestyle interventions. Facilitators in the development included iterative design, working with different disciplines, and resonating intervention content with users. Facilitators for intervention reach were use of a personal approach and social network, reminders, and self-monitoring. Nevertheless, barriers, such as technological challenges for developers and limited financial resources, may hinder intervention development. Furthermore, passive recruitment was a barrier to intervention reach. Technical difficulties and the use of self-monitoring devices were common barriers for users of eHealth interventions. Only limited data on barriers and facilitators for intervention implementation and evaluation were available. Conclusions: While we found large variations among studies regarding key intervention components, and barriers and facilitators, certain factors may be beneficial in building and using eHealth interventions and reaching people with a low SES. Barriers and facilitators offer promising elements that eHealth developers can use as a toolbox to connect eHealth with low SES individuals. Our findings suggest that one-size-fits-all eHealth interventions may be less suitable for people with a low SES. Future research should investigate how to customize eHealth lifestyle interventions to meet the needs of different low SES groups, and should identify the components that enhance their reach, use, and effectiveness. UR - https://www.jmir.org/2022/8/e34229 UR - http://dx.doi.org/10.2196/34229 UR - http://www.ncbi.nlm.nih.gov/pubmed/36001380 ID - info:doi/10.2196/34229 ER - TY - JOUR AU - Lam, T. Thomas Y. AU - Cheung, K. Max F. AU - Munro, L. Yasmin AU - Lim, Meng Kong AU - Shung, Dennis AU - Sung, Y. Joseph J. PY - 2022/8/25 TI - Randomized Controlled Trials of Artificial Intelligence in Clinical Practice: Systematic Review JO - J Med Internet Res SP - e37188 VL - 24 IS - 8 KW - artificial intelligence KW - randomized controlled trial KW - systematic review KW - clinical KW - gastroenterology KW - clinical informatics KW - mobile phone N2 - Background: The number of artificial intelligence (AI) studies in medicine has exponentially increased recently. However, there is no clear quantification of the clinical benefits of implementing AI-assisted tools in patient care. Objective: This study aims to systematically review all published randomized controlled trials (RCTs) of AI-assisted tools to characterize their performance in clinical practice. Methods: CINAHL, Cochrane Central, Embase, MEDLINE, and PubMed were searched to identify relevant RCTs published up to July 2021 and comparing the performance of AI-assisted tools with conventional clinical management without AI assistance. We evaluated the primary end points of each study to determine their clinical relevance. This systematic review was conducted following the updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Results: Among the 11,839 articles retrieved, only 39 (0.33%) RCTs were included. These RCTs were conducted in an approximately equal distribution from North America, Europe, and Asia. AI-assisted tools were implemented in 13 different clinical specialties. Most RCTs were published in the field of gastroenterology, with 15 studies on AI-assisted endoscopy. Most RCTs studied biosignal-based AI-assisted tools, and a minority of RCTs studied AI-assisted tools drawn from clinical data. In 77% (30/39) of the RCTs, AI-assisted interventions outperformed usual clinical care, and clinically relevant outcomes improved with AI-assisted intervention in 70% (21/30) of the studies. Small sample size and single-center design limited the generalizability of these studies. Conclusions: There is growing evidence supporting the implementation of AI-assisted tools in daily clinical practice; however, the number of available RCTs is limited and heterogeneous. More RCTs of AI-assisted tools integrated into clinical practice are needed to advance the role of AI in medicine. Trial Registration: PROSPERO CRD42021286539; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=286539 UR - https://www.jmir.org/2022/8/e37188 UR - http://dx.doi.org/10.2196/37188 UR - http://www.ncbi.nlm.nih.gov/pubmed/35904087 ID - info:doi/10.2196/37188 ER - TY - JOUR AU - Crossnohere, L. Norah AU - Elsaid, Mohamed AU - Paskett, Jonathan AU - Bose-Brill, Seuli AU - Bridges, P. John F. PY - 2022/8/25 TI - Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks JO - J Med Internet Res SP - e36823 VL - 24 IS - 8 KW - artificial intelligence KW - translational science KW - translational research KW - ethics KW - engagement KW - reproducibility KW - transparency KW - effectiveness KW - medicine KW - health care KW - AI N2 - Background: Artificial intelligence (AI) is rapidly expanding in medicine despite a lack of consensus on its application and evaluation. Objective: We sought to identify current frameworks guiding the application and evaluation of AI for predictive analytics in medicine and to describe the content of these frameworks. We also assessed what stages along the AI translational spectrum (ie, AI development, reporting, evaluation, implementation, and surveillance) the content of each framework has been discussed. Methods: We performed a literature review of frameworks regarding the oversight of AI in medicine. The search included key topics such as ?artificial intelligence,? ?machine learning,? ?guidance as topic,? and ?translational science,? and spanned the time period 2014-2022. Documents were included if they provided generalizable guidance regarding the use or evaluation of AI in medicine. Included frameworks are summarized descriptively and were subjected to content analysis. A novel evaluation matrix was developed and applied to appraise the frameworks? coverage of content areas across translational stages. Results: Fourteen frameworks are featured in the review, including six frameworks that provide descriptive guidance and eight that provide reporting checklists for medical applications of AI. Content analysis revealed five considerations related to the oversight of AI in medicine across frameworks: transparency, reproducibility, ethics, effectiveness, and engagement. All frameworks include discussions regarding transparency, reproducibility, ethics, and effectiveness, while only half of the frameworks discuss engagement. The evaluation matrix revealed that frameworks were most likely to report AI considerations for the translational stage of development and were least likely to report considerations for the translational stage of surveillance. Conclusions: Existing frameworks for the application and evaluation of AI in medicine notably offer less input on the role of engagement in oversight and regarding the translational stage of surveillance. Identifying and optimizing strategies for engagement are essential to ensure that AI can meaningfully benefit patients and other end users. UR - https://www.jmir.org/2022/8/e36823 UR - http://dx.doi.org/10.2196/36823 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006692 ID - info:doi/10.2196/36823 ER - TY - JOUR AU - Ichimiya, Megumi AU - Gerard, Raquel AU - Mills, Sarah AU - Brodsky, Alexa AU - Cantrell, Jennifer AU - Evans, Douglas W. PY - 2022/8/25 TI - The Measurement of Dose and Response for Smoking Behavior Change Interventions in the Digital Age: Systematic Review JO - J Med Internet Res SP - e38470 VL - 24 IS - 8 KW - digital health KW - digital media KW - social media KW - behavior change interventions KW - smoking KW - vaping KW - dose-response KW - telehealth KW - mobile health KW - mHealth KW - mobile phone N2 - Background: There is little consensus regarding effective digital health interventions for diverse populations, which is due in part to the difficulty of quantifying the impact of various media and content and the lack of consensus on evaluating dosage and outcomes. In particular, digital smoking behavior change intervention is an area where consistency of measurement has been a challenge because of emerging products and rapid policy changes. This study reviewed the contents and outcomes of digital smoking interventions and the consistency of reporting to inform future research. Objective: This study aims to systematically review digital smoking behavior change interventions and evaluate the consistency in measuring and reporting intervention contents, channels, and dose and response outcomes. Methods: PubMed, Embase, Scopus, PsycINFO, and PAIS databases were used to search the literature between January and May 2021. General and journal-based searches were combined. All records were imported into Covidence systematic review software (Veritas Health Innovation) and duplicates were removed. Titles and abstracts were screened by 4 trained reviewers to identify eligible full-text literature. The data synthesis scheme was designed based on the concept that exposure to digital interventions can be divided into intended doses that were planned by the intervention and enacted doses that were completed by participants. The intended dose comprised the frequency and length of the interventions, and the enacted dose was assessed as the engagement. Response measures were assessed for behaviors, intentions, and psychosocial outcomes. Measurements of the dose-response relationship were reviewed for all studies. Results: A total of 2916 articles were identified through a database search. Of these 2916 articles, the title and abstract review yielded 324 (11.11%) articles for possible eligibility, and 19 (0.65%) articles on digital smoking behavior change interventions were ultimately included for data extraction and synthesis. The analysis revealed a lack of prevention studies (0/19, 0%) and dose-response studies (3/19, 16%). Of the 19 studies, 6 (32%) reported multiple behavioral measures, and 5 (23%) reported multiple psychosocial measures as outcomes. For dosage measures, 37% (7/19) of studies used frequency of exposure, and 21% (4/19) of studies mentioned the length of exposure. The assessment of clarity of reporting revealed that the duration of intervention and data collection tended to be reported vaguely in the literature. Conclusions: This review revealed a lack of studies assessing the effects of digital media interventions on smoking outcomes. Data synthesis showed that measurement and reporting were inconsistent across studies, illustrating current challenges in this field. Although most studies focused on reporting outcomes, the measurement of exposure, including intended and enacted doses, was unclear in a large proportion of studies. Clear and consistent reporting of both outcomes and exposures is needed to develop further evidence in intervention research on digital smoking behavior change. UR - https://www.jmir.org/2022/8/e38470 UR - http://dx.doi.org/10.2196/38470 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006682 ID - info:doi/10.2196/38470 ER - TY - JOUR AU - Sparks, B. Jordan AU - Klamerus, L. Mandi AU - Caverly, J. Tanner AU - Skurla, E. Sarah AU - Hofer, P. Timothy AU - Kerr, A. Eve AU - Bernstein, J. Steven AU - Damschroder, J. Laura PY - 2022/8/26 TI - Planning and Reporting Effective Web-Based RAND/UCLA Appropriateness Method Panels: Literature Review and Preliminary Recommendations JO - J Med Internet Res SP - e33898 VL - 24 IS - 8 KW - quality indicators KW - health care KW - web-based KW - virtual KW - RAND/UCLA appropriateness method KW - research design KW - de-implementation KW - digital health KW - health research KW - virtual health research KW - health technology KW - researchers KW - medical professionals N2 - Background: The RAND/UCLA Appropriateness Method (RAM), a variant of the Delphi Method, was developed to synthesize existing evidence and elicit the clinical judgement of medical experts on the appropriate treatment of specific clinical presentations. Technological advances now allow researchers to conduct expert panels on the internet, offering a cost-effective and convenient alternative to the traditional RAM. For example, the Department of Veterans Affairs recently used a web-based RAM to validate clinical recommendations for de-intensifying routine primary care services. A substantial literature describes and tests various aspects of the traditional RAM in health research; yet we know comparatively less about how researchers implement web-based expert panels. Objective: The objectives of this study are twofold: (1) to understand how the web-based RAM process is currently used and reported in health research and (2) to provide preliminary reporting guidance for researchers to improve the transparency and reproducibility of reporting practices. Methods: The PubMed database was searched to identify studies published between 2009 and 2019 that used a web-based RAM to measure the appropriateness of medical care. Methodological data from each article were abstracted. The following categories were assessed: composition and characteristics of the web-based expert panels, characteristics of panel procedures, results, and panel satisfaction and engagement. Results: Of the 12 studies meeting the eligibility criteria and reviewed, only 42% (5/12) implemented the full RAM process with the remaining studies opting for a partial approach. Among those studies reporting, the median number of participants at first rating was 42. While 92% (11/12) of studies involved clinicians, 50% (6/12) involved multiple stakeholder types. Our review revealed that the studies failed to report on critical aspects of the RAM process. For example, no studies reported response rates with the denominator of previous rounds, 42% (5/12) did not provide panelists with feedback between rating periods, 50% (6/12) either did not have or did not report on the panel discussion period, and 25% (3/12) did not report on quality measures to assess aspects of the panel process (eg, satisfaction with the process). Conclusions: Conducting web-based RAM panels will continue to be an appealing option for researchers seeking a safe, efficient, and democratic process of expert agreement. Our literature review uncovered inconsistent reporting frameworks and insufficient detail to evaluate study outcomes. We provide preliminary recommendations for reporting that are both timely and important for producing replicable, high-quality findings. The need for reporting standards is especially critical given that more people may prefer to participate in web-based rather than in-person panels due to the ongoing COVID-19 pandemic. UR - https://www.jmir.org/2022/8/e33898 UR - http://dx.doi.org/10.2196/33898 UR - http://www.ncbi.nlm.nih.gov/pubmed/36018626 ID - info:doi/10.2196/33898 ER - TY - JOUR AU - Lewinski, A. Allison AU - Walsh, Conor AU - Rushton, Sharron AU - Soliman, Diana AU - Carlson, M. Scott AU - Luedke, W. Matthew AU - Halpern, J. David AU - Crowley, J. Matthew AU - Shaw, J. Ryan AU - Sharpe, A. Jason AU - Alexopoulos, Anastasia-Stefania AU - Tabriz, Alishahi Amir AU - Dietch, R. Jessica AU - Uthappa, M. Diya AU - Hwang, Soohyun AU - Ball Ricks, A. Katharine AU - Cantrell, Sarah AU - Kosinski, S. Andrzej AU - Ear, Belinda AU - Gordon, M. Adelaide AU - Gierisch, M. Jennifer AU - Williams Jr, W. John AU - Goldstein, M. Karen PY - 2022/8/26 TI - Telehealth for the Longitudinal Management of Chronic Conditions: Systematic Review JO - J Med Internet Res SP - e37100 VL - 24 IS - 8 KW - telemedicine KW - diabetes mellitus, type 2 KW - heart failure KW - pulmonary disease KW - chronic obstructive KW - veterans KW - delivery of health care KW - systematic review N2 - Background: Extensive literature support telehealth as a supplement or adjunct to in-person care for the management of chronic conditions such as congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM). Evidence is needed to support the use of telehealth as an equivalent and equitable replacement for in-person care and to assess potential adverse effects. Objective: We conducted a systematic review to address the following question: among adults, what is the effect of synchronous telehealth (real-time response among individuals via phone or phone and video) compared with in-person care (or compared with phone, if synchronous video care) for chronic management of CHF, chronic obstructive pulmonary disease, and T2DM on key disease-specific clinical outcomes and health care use? Methods: We followed systematic review methodologies and searched two databases (MEDLINE and Embase). We included randomized or quasi-experimental studies that evaluated the effect of synchronously delivered telehealth for relevant chronic conditions that occurred over ?2 encounters and in which some or all in-person care was supplanted by care delivered via phone or video. We assessed the bias using the Cochrane Effective Practice and Organization of Care risk of bias (ROB) tool and the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation. We described the findings narratively and did not conduct meta-analysis owing to the small number of studies and the conceptual heterogeneity of the identified interventions. Results: We identified 8662 studies, and 129 (1.49%) were reviewed at the full-text stage. In total, 3.9% (5/129) of the articles were retained for data extraction, all of which (5/5, 100%) were randomized controlled trials. The CHF study (1/5, 20%) was found to have high ROB and randomized patients (n=210) to receive quarterly automated asynchronous web-based review and follow-up of telemetry data versus synchronous personal follow-up (in-person vs phone-based) for 1 year. A 3-way comparison across study arms found no significant differences in clinical outcomes. Overall, 80% (4/5) of the studies (n=466) evaluated synchronous care for patients with T2DM (ROB was judged to be low for 2, 50% of studies and high for 2, 50% of studies). In total, 20% (1/5) of the studies were adequately powered to assess the difference in glycosylated hemoglobin level between groups; however, no significant difference was found. Intervention design varied greatly from remote monitoring of blood glucose combined with video versus in-person visits to an endocrinology clinic to a brief, 3-week remote intervention to stabilize uncontrolled diabetes. No articles were identified for chronic obstructive pulmonary disease. Conclusions: This review found few studies with a variety of designs and interventions that used telehealth as a replacement for in-person care. Future research should consider including observational studies and studies on additional highly prevalent chronic diseases. UR - https://www.jmir.org/2022/8/e37100 UR - http://dx.doi.org/10.2196/37100 UR - http://www.ncbi.nlm.nih.gov/pubmed/36018711 ID - info:doi/10.2196/37100 ER - TY - JOUR AU - Hodkinson, Alexander AU - Kontopantelis, Evangelos AU - Zghebi, S. Salwa AU - Grigoroglou, Christos AU - McMillan, Brian AU - Marwijk, van Harm AU - Bower, Peter AU - Tsimpida, Dialechti AU - Emery, F. Charles AU - Burge, R. Mark AU - Esmiol, Hunter AU - Cupples, E. Margaret AU - Tully, A. Mark AU - Dasgupta, Kaberi AU - Daskalopoulou, S. Stella AU - Cooke, B. Alexandra AU - Fayehun, F. Ayorinde AU - Houle, Julie AU - Poirier, Paul AU - Yates, Thomas AU - Henson, Joseph AU - Anderson, R. Derek AU - Grey, B. Elisabeth AU - Panagioti, Maria PY - 2022/8/30 TI - Association Between Patient Factors and the Effectiveness of Wearable Trackers at Increasing the Number of Steps per Day Among Adults With Cardiometabolic Conditions: Meta-analysis of Individual Patient Data From Randomized Controlled Trials JO - J Med Internet Res SP - e36337 VL - 24 IS - 8 KW - systematic review KW - individual patient data KW - meta-analysis KW - steps/day KW - wearable tracker KW - cardiometabolic conditions KW - diabetes KW - obesity KW - cardiovascular disease N2 - Background: Current evidence supports the use of wearable trackers by people with cardiometabolic conditions. However, as the health benefits are small and confounded by heterogeneity, there remains uncertainty as to which patient groups are most helped by wearable trackers. Objective: This study examined the effects of wearable trackers in patients with cardiometabolic conditions to identify subgroups of patients who most benefited and to understand interventional differences. Methods: We obtained individual participant data from randomized controlled trials of wearable trackers that were conducted before December 2020 and measured steps per day as the primary outcome in participants with cardiometabolic conditions including diabetes, overweight or obesity, and cardiovascular disease. We used statistical models to account for clustering of participants within trials and heterogeneity across trials to estimate mean differences with the 95% CI. Results: Individual participant data were obtained from 9 of 25 eligible randomized controlled trials, which included 1481 of 3178 (47%) total participants. The wearable trackers revealed that over the median duration of 12 weeks, steps per day increased by 1656 (95% CI 918-2395), a significant change. Greater increases in steps per day from interventions using wearable trackers were observed in men (interaction coefficient ?668, 95% CI ?1157 to ?180), patients in age categories over 50 years (50-59 years: interaction coefficient 1175, 95% CI 377-1973; 60-69 years: interaction coefficient 981, 95% CI 222-1740; 70-90 years: interaction coefficient 1060, 95% CI 200-1920), White patients (interaction coefficient 995, 95% CI 360-1631), and patients with fewer comorbidities (interaction coefficient ?517, 95% CI ?1188 to ?11) compared to women, those aged below 50, non-White patients, and patients with multimorbidity. In terms of interventional differences, only face-to-face delivery of the tracker impacted the effectiveness of the interventions by increasing steps per day. Conclusions: In patients with cardiometabolic conditions, interventions using wearable trackers to improve steps per day mostly benefited older White men without multimorbidity. Trial Registration: PROSPERO CRD42019143012; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=143012 UR - https://www.jmir.org/2022/8/e36337 UR - http://dx.doi.org/10.2196/36337 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040779 ID - info:doi/10.2196/36337 ER - TY - JOUR AU - Jardine, Jacinta AU - Bowman, Robert AU - Doherty, Gavin PY - 2022/8/30 TI - Digital Interventions to Enhance Readiness for Psychological Therapy: Scoping Review JO - J Med Internet Res SP - e37851 VL - 24 IS - 8 KW - readiness for change KW - stages of change KW - digital KW - motivation KW - engagement KW - uptake KW - mental health KW - mental illness KW - mobile phone N2 - Background: Psychological therapy is an effective treatment method for mental illness; however, many people with mental illness do not seek treatment or drop out of treatment early. Increasing client uptake and engagement in therapy is key to addressing the escalating global problem of mental illness. Attitudinal barriers, such as a lack of motivation, are a leading cause of low engagement in therapy. Digital interventions to increase motivation and readiness for change hold promise as accessible and scalable solutions; however, little is known about the range of interventions being used and their feasibility as a means to increase engagement with therapy. Objective: This review aimed to define the emerging field of digital interventions to enhance readiness for psychological therapy and detect gaps in the literature. Methods: A literature search was conducted in PubMed, PsycINFO, PsycARTICLES, Scopus, Embase, ACM Guide to Computing Literature, and IEEE Xplore Digital Library from January 1, 2006, to November 30, 2021. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) methodology was applied. Publications were included when they concerned a digitally delivered intervention, a specific target of which was enhancing engagement with further psychological treatment, and when this intervention occurred before the target psychological treatment. Results: A total of 45 publications met the inclusion criteria. The conditions included depression, unspecified general mental health, comorbid anxiety and depression, smoking, eating disorders, suicide, social anxiety, substance use, gambling, and psychosis. Almost half of the interventions (22/48, 46%) were web-based programs; the other formats included screening tools, videos, apps, and websites. The components of the interventions included psychoeducation, symptom assessment and feedback, information on treatment options and referrals, client testimonials, expectation management, and pro-con lists. Regarding feasibility, of the 16 controlled studies, 7 (44%) measuring actual behavior or action showed evidence of intervention effectiveness compared with controls, 7 (44%) found no differences, and 2 (12%) indicated worse behavioral outcomes. In general, the outcomes were mixed and inconclusive owing to variations in trial designs, control types, and outcome measures. Conclusions: Digital interventions to enhance readiness for psychological therapy are broad and varied. Although these easily accessible digital approaches show potential as a means of preparing people for therapy, they are not without risks. The complex nature of stigma, motivation, and individual emotional responses toward engaging in treatment for mental health difficulties suggests that a careful approach is needed when developing and evaluating digital readiness interventions. Further qualitative, naturalistic, and longitudinal research is needed to deepen our knowledge in this area. UR - https://www.jmir.org/2022/8/e37851 UR - http://dx.doi.org/10.2196/37851 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040782 ID - info:doi/10.2196/37851 ER - TY - JOUR AU - Han, Areum AU - Kim, Hui Tae PY - 2022/8/30 TI - The Effects of Internet-Based Acceptance and Commitment Therapy on Process Measures: Systematic Review and Meta-analysis JO - J Med Internet Res SP - e39182 VL - 24 IS - 8 KW - acceptance and commitment therapy KW - process measure KW - internet-based intervention KW - digital mental health KW - meta-analysis KW - mindfulness KW - systematic review N2 - Background: Acceptance and commitment therapy (ACT) is based on a psychological flexibility model that encompasses 6 processes: acceptance, cognitive defusion, self-as-context, being present, values, and committed action. Objective: This systematic review and meta-analysis of randomized controlled trials (RCTs) aimed to examine the effects of internet-based ACT (iACT) on process measures. Methods: A comprehensive search was conducted using 4 databases. The quality of the included RCTs was assessed using the Cochrane Collaboration Risk of Bias Tool. A random-effects or fixed-effects model was used. Subgroup analyses for each outcome were conducted according to the type of control group, use of therapist guidance, delivery modes, and use of targeted participants, when applicable. Results: A total of 34 RCTs met the inclusion criteria. This meta-analysis found that iACT had a medium effect on psychological flexibility and small effects on mindfulness, valued living, and cognitive defusion at the immediate posttest. In addition, iACT had a small effect on psychological flexibility at follow-up. The overall risk of bias across studies was unclear. Conclusions: Relatively few studies have compared the effects of iACT with active control groups and measured the effects on mindfulness, valued living, and cognitive defusion. These findings support the processes of change in iACT, which mental health practitioners can use to support the use of iACT. UR - https://www.jmir.org/2022/8/e39182 UR - http://dx.doi.org/10.2196/39182 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040783 ID - info:doi/10.2196/39182 ER - TY - JOUR AU - Rogulji?, Marija AU - ?imunovi?, Dina AU - Poklepovi? Peri?i?, Tina AU - Vi?ak, Marin AU - Utrobi?i?, Ana AU - Maru?i?, Matko AU - Maru?i?, Ana PY - 2022/8/31 TI - Publishing Identifiable Patient Photographs in Scientific Journals: Scoping Review of Policies and Practices JO - J Med Internet Res SP - e37594 VL - 24 IS - 8 KW - identifiable patient photographs KW - medical photography KW - data protection KW - patient privacy KW - confidentiality KW - informed consent KW - ethical publishing KW - scientific journals KW - open access KW - scoping review KW - mobile phone N2 - Background: Publishing identifiable patient data in scientific journals may jeopardize patient privacy and confidentiality if best ethical practices are not followed. Current journal practices show considerable diversity in the publication of identifiable patient photographs, and different stakeholders may have different opinions of and practices in publishing patient photographs. Objective: This scoping review aimed to identify existing evidence and map knowledge gaps in medical research on the policies and practices of publishing identifiable photographs in scientific articles. Methods: We performed a comprehensive search of the Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL with Full Text, Database of Abstracts of Reviews of Effects, Ovid MEDLINE, and Scopus. The Open Science Framework, PROSPERO, BASE, Google Scholar, OpenGrey, ClinicalTrials.gov, the Campbell Collaboration Library, and Science.gov were also searched. Results: After screening the initial 15,949 titles and abstracts, 98 (0.61%) publications were assessed for eligibility at the full-text level, and 30 (0.19%) publications were included in this review. The studies were published between 1994 and 2020; most had a cross-sectional design and were published in journals covering different medical disciplines. We identified 3 main topics. The first included ethical aspects of the use of facial photographs in publications. In different clinical settings, the consent process was not conducted properly, and health professionals did not recognize the importance of obtaining written patient consent for taking and using patient medical photographs. They often considered verbal consent sufficient or even used the photographs without consent. The second topic included studies that investigated the practices and use of medical photography in publishing. Both patients and doctors asked for confidential storage and maintenance of medical photographs. Patients preferred to be photographed by their physicians using an institutional camera and preferred nonidentifiable medical photographs not only for publication but also in general. Conventional methods of deidentification of facial photographs concealing the eye area were recognized as unsuccessful in protecting patient privacy. The third topic emerged from studies investigating medical photography in journal articles. These studies showed great diversity in publishing practices regarding consent for publication of medical photographs. Journal policies regarding the consent process and consent forms were insufficient, and existing ethical professional guidelines were not fully implemented in actual practices. Patients? photographs from open-access medical journals were found on public web-based platforms. Conclusions: This scoping review showed a diversity of practices in publishing identifiable patient photographs and an unsatisfactory level of knowledge of this issue among different stakeholders despite existing standards. Emerging issues include the availability of patients? photographs from open-access journals or preprints in the digital environment. There is a need to improve standards and processes to obtain proper consent to fully protect the privacy of patients in published articles. UR - https://www.jmir.org/2022/8/e37594 UR - http://dx.doi.org/10.2196/37594 UR - http://www.ncbi.nlm.nih.gov/pubmed/36044262 ID - info:doi/10.2196/37594 ER - TY - JOUR AU - Park, Yoonseo AU - Park, Sewon AU - Lee, Munjae PY - 2022/8/17 TI - Digital Health Care Industry Ecosystem: Network Analysis JO - J Med Internet Res SP - e37622 VL - 24 IS - 8 KW - digital health care KW - industrial ecosystem KW - network analysis KW - topic modeling KW - South Korea N2 - Background: As the need for digital health care based on mobile devices is increasing, with the rapid development of digital technologies, especially in the face of the COVID-19 pandemic, gaining a better understanding of the industrial structure is needed to activate the use of digital health care. Objective: The aim of this study was to suggest measures to revitalize the digital health care industry by deriving the stakeholders and major issues with respect to the ecosystem of the industry. Methods: A total of 1822 newspaper articles were collected using Big Kings, a big data system for news, for a limited period from 2016 to August 2021, when the mobile health care project was promoted in Korea centered on public health centers. The R and NetMiner programs were used for network analysis. Results: The Korean government and the Ministry of Health and Welfare showed the highest centrality and appeared as major stakeholders, and their common major issues were ?reviewing the introduction of telemedicine,? ?concerns about bankruptcy of local clinics,? and ?building an integrated platform for precision medicine.? In addition, the major stakeholders of medical institutions and companies were Seoul National University Hospital, Kangbuk Samsung Hospital, Ajou University Hospital, Samsung, and Vuno Inc. Conclusions: This analysis confirmed that the issues related to digital health care are largely composed of telemedicine, data, and health care business. For digital health care to develop as a national innovative growth engine and to be institutionalized, the development of a digital health care fee model that can improve the regulatory system and the cost-effectiveness of patient care, centering on the Ministry of Health and Welfare as a key stakeholder, is essential. UR - https://www.jmir.org/2022/8/e37622 UR - http://dx.doi.org/10.2196/37622 UR - http://www.ncbi.nlm.nih.gov/pubmed/35976690 ID - info:doi/10.2196/37622 ER - TY - JOUR AU - Meskó, Bertalan AU - deBronkart, Dave PY - 2022/8/31 TI - Patient Design: The Importance of Including Patients in Designing Health Care JO - J Med Internet Res SP - e39178 VL - 24 IS - 8 KW - patient KW - patient design KW - user design KW - patient centric KW - patient focus KW - digital health KW - future KW - empowerment KW - involvement KW - participatory KW - engagement KW - participation KW - patient centred KW - patient centered UR - https://www.jmir.org/2022/8/e39178 UR - http://dx.doi.org/10.2196/39178 UR - http://www.ncbi.nlm.nih.gov/pubmed/36044250 ID - info:doi/10.2196/39178 ER - TY - JOUR AU - Bauermeister, Jose AU - Choi, Ki Seul AU - Bruehlman-Senecal, Emma AU - Golinkoff, Jesse AU - Taboada, Arianna AU - Lavra, Joshua AU - Ramazzini, Lionel AU - Dillon, Fred AU - Haritatos, Jana PY - 2022/8/1 TI - An Identity-Affirming Web Application to Help Sexual and Gender Minority Youth Cope With Minority Stress: Pilot Randomized Controlled Trial JO - J Med Internet Res SP - e39094 VL - 24 IS - 8 KW - lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority KW - LGBTQ+ KW - youth KW - adolescence KW - discrimination KW - minority stress KW - mental health KW - resilience KW - sexual and gender minority KW - SGM KW - intersectionality N2 - Background: Efficacious mental health interventions for sexual and gender minority youth have had limited reach, given their delivery as time-intensive, in-person sessions. Internet-based interventions may facilitate reach to sexual and gender minority youth; however, there is little research examining their efficacy. Objective: This study aims to describe the results of a pilot randomized controlled trial of imi, a web application designed to improve mental health by supporting lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority identity affirmation, coping self-efficacy, and coping skill practice. Methods: Sexual and gender minority youth (N=270) aged 13 to 19 (mean 16.5, SD 1.5) years and living in the United States were recruited through Instagram advertisements. Approximately 78% (210/270) of the sample identified as racial or ethnic minorities. Participants were randomized in a 1:1 fashion to the full imi intervention web application (treatment; 135/270, 50%) or a resource page?only version of the imi site (control; 135/270, 50%). The imi application covered four topical areas: gender identity; lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority identity; stress and coping; and internalized homophobia and transphobia. Participants explored these areas by engaging with informational resources, exercises, and peer stories at a self-guided pace. Both arms were assessed via web-based surveys at baseline and 4-week follow-up for intervention satisfaction, stress appraisals (ie, challenge, threat, and resource), coping skills (ie, instrumental support, positive reframing, and planning), and mental health symptoms among other outcomes. Main intent-to-treat analyses compared the arms at week 4, controlling for baseline values on each outcome. Results: Survey retention was 90.4% (244/270) at week 4. Participants in the treatment arm reported greater satisfaction with the intervention than participants in the control arm (t241=?2.98; P=.003). The treatment arm showed significantly greater improvement in challenge appraisals (ie, belief in one?s coping abilities) than the control (Cohen d=0.26; P=.008). There were no differences between the arms for threat (d=0.10; P=.37) or resource (d=0.15; P=.14) appraisals. The treatment arm showed greater increases in coping skills than the control arm (instrumental support: d=0.24, P=.005; positive reframing: d=0.27, P=.02; planning: d=0.26, P=.02). Mental health symptoms improved across both the treatment and control arms; however, there were no differences between arms. Within the treatment arm, higher engagement with imi (?5 sessions, >10 minutes, or >10 pages) predicted greater improvement in stress appraisals (all P values <.05). Conclusions: The results provide initial evidence that asynchronous psychosocial interventions delivered via a web application to sexual and gender minority youth can support their ability to cope with minority stress. Further research is needed to examine the long-term effects of the imi application. Trial Registration: ClinicalTrials.gov NCT05061966; https://clinicaltrials.gov/ct2/show/NCT05061966 UR - https://www.jmir.org/2022/8/e39094 UR - http://dx.doi.org/10.2196/39094 UR - http://www.ncbi.nlm.nih.gov/pubmed/35916700 ID - info:doi/10.2196/39094 ER - TY - JOUR AU - Lin, Bing AU - Liu, Jiaxiu AU - He, Wei AU - Pan, Haiying AU - Ma, Yingjie AU - Zhong, Xiaoni PY - 2022/8/11 TI - Effect of a Reminder System on Pre-exposure Prophylaxis Adherence in Men Who Have Sex With Men: Prospective Cohort Study Based on WeChat Intervention JO - J Med Internet Res SP - e37936 VL - 24 IS - 8 KW - pre-exposure prophylaxis (PrEP) KW - adherence KW - reminder system KW - men who have sex with men (MSM) KW - WeChat KW - oral PrEP KW - HIV prevention KW - MSM KW - reminder KW - message N2 - Background: The efficacy of pre-exposure prophylaxis (PrEP) is highly dependent on adherence, and one of the main reasons for poor adherence is forgetfulness. Therefore, it is important to explore how to remind users to take their medicine on time. Objective: This study aims to explore the effect of a reminder system on PrEP adherence in men who have sex with men (MSM) to improve adherence. The main function of the reminder system based on the WeChat social media app is to send daily messages to PrEP users reminding them to take their medicine. Methods: An open-label, multicenter, prospective cohort study of PrEP in HIV-negative MSM was conducted from November 2019 to June 2021. Study participants who met the criteria were randomly divided into 2 groups: no-reminder group and reminder group. Both groups received daily oral PrEP with follow-up every 3 months. Adherence was measured on the basis of self-report and was defined as the percentage of medications taken on time. Participants in the reminder group scanned a WeChat QR code and received a reminder message every day. Participants in the no-reminder group took daily oral medicines without reminders. The longitudinal trajectories of adherence for both groups were displayed to compare the variability in adherence at each time point. The association between the changes in adherence (no change, improvement, decline) at each time point and the use of the reminder system was analyzed by multinomial logistic regression models to further explore the effectiveness of the system. Results: A total of 716 MSM were included in the analysis, that is, 372 MSM in the no-reminder group and 344 MSM in the reminder group. Adherence in the no-reminder group fluctuated between 0.75 and 0.80 and that in the reminder group gradually increased over time from 0.76 to 0.88. Adherence at each time point was not statistically different between the 2 groups. Further analysis showed that an improvement in adherence in the early stage was associated with the use of the reminder system (odds ratio [OR] 1.65, 95% CI 1.01-2.70; P=.04). An improvement in average adherence compared to initial adherence was positively associated with the use of the reminder system (OR 1.82, 95% CI 1.10-3.01; P=.02). Conclusions: The effect of the reminder system on PrEP adherence in MSM was more significant in the early stage, which is related to the increased motivation of users and the development of medicine-taking habits. The reminder system is potentially effective for early-stage medicine management, encouraging users to develop healthy medicine-taking habits and to increase their adherence. Trial Registration: Chinese Clinical Trial ChiCTR190026414; http://www.chictr.org.cn/showproj.aspx?proj=35077 UR - https://www.jmir.org/2022/8/e37936 UR - http://dx.doi.org/10.2196/37936 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969436 ID - info:doi/10.2196/37936 ER - TY - JOUR AU - Fong, C. Tiffany H. AU - Mak, S. Winnie W. PY - 2022/8/12 TI - The Effects of Internet-Based Storytelling Programs (Amazing Adventure Against Stigma) in Reducing Mental Illness Stigma With Mediation by Interactivity and Stigma Content: Randomized Controlled Trial JO - J Med Internet Res SP - e37973 VL - 24 IS - 8 KW - mental illness stigma KW - internet-based KW - interactivity KW - storytelling KW - social distance KW - microaggression N2 - Background: Mental illness stigma has been a global concern, owing to its adverse effects on the recovery of people with mental illness, and may delay help-seeking for mental health because of the concern of being stigmatized. With technological advancement, internet-based interventions for the reduction of mental illness stigma have been developed, and these effects have been promising. Objective: This study aimed to examine the differential effects of internet-based storytelling programs, which varied in the levels of interactivity and stigma content, in reducing mental illness stigma. Methods: Using an experimental design, this study compared the effects of 4 storytelling websites that varied in the levels of interactivity and stigma content. Specifically, the conditions included an interactive website with stigma-related content (combo condition), a noninteractive website with stigma-related content (stigma condition), an interactive website without stigma-related content (interact condition), and a noninteractive website without stigma-related content (control condition). Participants were recruited via mass emails to all students and staff of a public university and via social networking sites. Eligible participants were randomized into the following four conditions: combo (n=67), stigma (n=65), interact (n=64), or control (n=67). The participants of each group viewed the respective web pages at their own pace. Public stigma, microaggression, and social distance were measured on the web before the experiment, after the experiment, and at the 1-week follow-up. Perceived autonomy and immersiveness, as mediators, were assessed after the experiment. Results: Both the combo (n=66) and stigma (n=65) conditions were effective in reducing public stigma and microaggression toward people with mental illness after the experiment and at the 1-week follow-up. However, none of the conditions had significant time×condition effects in reducing the social distance from people with mental illness. The interact condition (n=64) significantly reduced public stigma after the experiment (P=.02) but not at the 1-week follow-up (P=.22). The control condition (n=67) did not significantly reduce all outcomes associated with mental illness stigma. Perceived autonomy was found to mediate the effect of public stigma (P=.56), and immersiveness mediated the effect of microaggression (P=.99). Conclusions: Internet-based storytelling programs with stigma-related content and interactivity elicited the largest effects in stigma reduction, including reductions in public stigma and microaggression, although only its difference with internet-based storytelling programs with stigma-related content was not statistically significant. In other words, although interactivity could strengthen the stigma reduction effect, stigma-related content was more critical than interactivity in reducing stigma. Future stigma reduction efforts should prioritize the production of effective stigma content on their web pages, followed by considering the value of incorporating interactivity in future internet-based storytelling programs. Trial Registration: ClinicalTrials.gov NCT05333848; https://clinicaltrials.gov/ct2/show/NCT05333848 UR - https://www.jmir.org/2022/8/e37973 UR - http://dx.doi.org/10.2196/37973 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969460 ID - info:doi/10.2196/37973 ER - TY - JOUR AU - Nardi, William AU - Roy, Alexandra AU - Dunsiger, Shira AU - Brewer, Judson PY - 2022/8/15 TI - Analyzing the Impact of Mobile App Engagement on Mental Health Outcomes: Secondary Analysis of the Unwinding Anxiety Program JO - J Med Internet Res SP - e33696 VL - 24 IS - 8 KW - anxiety KW - worry KW - engagement KW - mobile app KW - mental health KW - mobile phone N2 - 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 ?=.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. UR - https://www.jmir.org/2022/8/e33696 UR - http://dx.doi.org/10.2196/33696 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969440 ID - info:doi/10.2196/33696 ER - TY - JOUR AU - Zheng, Meihua AU - Zhang, Xiaoling AU - Xiao, Huimin PY - 2022/8/25 TI - Effects of a WeChat-Based Life Review Program for Patients With Digestive System Cancer: 3-Arm Parallel Randomized Controlled Trial JO - J Med Internet Res SP - e36000 VL - 24 IS - 8 KW - digestive system cancer KW - life review KW - digital technology KW - anxiety KW - depression KW - hope KW - self-transcendence KW - cancer KW - randomized controlled trial KW - distress KW - psychological KW - digestive system N2 - Background: Patients with digestive system cancer often experience psychospiritual distress. Life review is an evidence-based psychological intervention for patients with cancer, but the effects of digital life review programs are unclear, especially for patients with digestive system cancer. Objective: We examined the effects of a WeChat-based life review program on the psychospiritual well-being of patients with digestive system cancer. Methods: This study was a 3-arm parallel randomized controlled trial. Eligible patients with digestive system cancer were recruited from a university hospital in Fujian, China. They were randomized to a life review group and 2 control groups. All participants received routine care, and the life review group also received the 4-week WeChat-based life review program. Control group 1 also received a 4-week program of friendly visiting. Anxiety, depression, hope, and self-transcendence were measured at baseline and 2 days, 1 month, and 6 months after the intervention. Results: A total of 150 participants were randomly allocated to the WeChat-based life review group (n=50), control group 1 (n=50), or control group 2 (n=50). The overall dropout rate was 10% (15/150), and 92% (46/50) of participants in the the life review group completed the intervention. Significant interaction effects for time and group membership were found for anxiety (P<.001), depression (P<.001), hope (P<.001), and self-transcendence (P<.001) at all follow-up time points. For anxiety and depression, the scores did not differ significantly between the life review group and control group 1 on day 2 (P=.80 for anxiety, P=.51 for depression), but the scores were significantly lower in the life review group at month 1 and month 6 (P=.02 for anxiety at both months 1 and 6; P=.003 and P<.001 for depression at months 1 and 6, respectively). Significant increases in hope and self-transcendence were revealed in the life review group compared to control group participants at all follow-up sessions. Conclusions: The WeChat-based life review program was effective in reducing anxiety and depressive symptoms and in improving the level of hope and self-transcendence among patients with digestive system cancer. Though friendly visiting can also help to relieve anxiety, its effects are short-term. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IOR-17011998; https://tinyurl.com/5acycpd4 UR - https://www.jmir.org/2022/8/e36000 UR - http://dx.doi.org/10.2196/36000 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006665 ID - info:doi/10.2196/36000 ER - TY - JOUR AU - Sarker, Rahman Mohammad Habibur AU - Moriyama, Michiko AU - Rashid, Ur Harun AU - Rahman, Moshiur Md AU - Chisti, Jobayer Mohammod AU - Das, Kumar Sumon AU - Saha, Kumar Samir AU - Arifeen, El Shams AU - Ahmed, Tahmeed AU - Faruque, G. A. S. PY - 2022/8/11 TI - Chronic Kidney Disease Awareness Campaign and Mobile Health Education to Improve Knowledge, Quality of Life, and Motivation for a Healthy Lifestyle Among Patients With Chronic Kidney Disease in Bangladesh: Randomized Controlled Trial JO - J Med Internet Res SP - e37314 VL - 24 IS - 8 KW - Bangladesh KW - health education KW - health knowledge KW - quality of life KW - motivation KW - randomized controlled trial KW - RCT KW - campaign KW - chronic kidney disease KW - knowledge KW - mobile health KW - mHealth KW - kidney KW - chronic disease KW - chronic condition KW - patient education KW - patient knowledge KW - low- and middle-income countries KW - LMIC N2 - Background: Chronic kidney disease (CKD) is linked to major health consequences and a poor quality of life. Despite the fact that CKD is becoming more prevalent, public knowledge of the disease remains low. Objective: This study aimed to evaluate the outcome of a health education intervention designed to enhance knowledge, health-related quality of life (QOL), and motivation about healthy lifestyle among adults with CKD. Methods: This study was a parallel-group (1:1), randomized controlled trial in the Mirzapur subdistrict of Bangladesh that compared 2 groups of patients with CKD. Adults with CKD (stages 1-3) were enrolled in November 2020 and randomly assigned the intervention or control group. The intervention group received health education through a CKD awareness campaign and mobile health technologies and was observed for 6 months, whereas the control group received standard treatment. The primary outcome was the evaluation of improved scores on the CKD knowledge questionnaire, and the secondary outcomes were improved QOL and changes in the levels of blood pressure (BP), BMI, serum creatinine, fasting blood sugar (FBS), hemoglobin, cholesterol, high-density lipoprotein cholesterol, triglyceride, serum uric acid, blood urea nitrogen (BUN), and albumin-to-creatinine ratio. Results: The study enrolled 126 patients (control: n=63; intervention: n=63) and performed intention-to-treat analysis. The analyses included repeated measures ANOVA, and the results were observed to be significantly different from within groups (P<.001), between groups (P<.001), and the interaction of group × time factor (P<.001) for knowledge score. Diastolic BP and BMI showed significant differences arising from within groups (P<.001 and P=.01, respectively) and the interaction of group × time factor (P=.001 and P=.02, respectively); food salinity and hip circumferences showed significant differences arising from within groups (P=.001 and P=.03, respectively) and between groups (P=.001 and P=.02, respectively). Moreover, systolic BP and waist circumference showed significant differences from within groups (P<.001 and P=.003, respectively). However, no significant differences were found arising from within groups, between groups, and the interactions of group × time for QOL, urine salinity, and mid-upper arm circumference. Regarding the laboratory findings, from baseline to 6 months, the mean (SD) FBS decreased by 0.51 (3.77) mmol/L in the intervention group and 0.10 (1.44) mmol/L in the control group (P=.03); however, blood urea nitrogen increased by 3.64 (7.17) mg/dL in the intervention group and 1.68 (10.10) mg/dL in the control group (P=.01). Conclusions: The health education strategy, which included a campaign and mobile health, showed promise for enhancing CKD knowledge among patients with CKD. This strategy may also aid patients with CKD in controlling their FBS and BP. The combined health education initiatives give evidence for scaling them up in Bangladesh and possibly other low- and middle-income countries, particularly in rural and peri-urban settings. Trial Registration: ClinicalTrials.gov NCT04094831; https://clinicaltrials.gov/ct2/show/NCT04094831. International Registered Report Identifier (IRRID): RR2-10.2196/30191 UR - https://www.jmir.org/2022/8/e37314 UR - http://dx.doi.org/10.2196/37314 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969429 ID - info:doi/10.2196/37314 ER - TY - JOUR AU - Bricker, B. Jonathan AU - Mull, E. Kristin AU - Santiago-Torres, Margarita AU - Miao, Zhen AU - Perski, Olga AU - Di, Chongzhi PY - 2022/8/18 TI - Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial JO - J Med Internet Res SP - e39208 VL - 24 IS - 8 KW - acceptance and commitment therapy KW - ACT KW - digital interventions KW - eHealth KW - engagement KW - iCanQuit KW - QuitGuide KW - mobile health KW - mHealth KW - smartphone apps KW - trajectories KW - tobacco KW - smoking KW - mobile phone N2 - Background: Little is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes. Objective: In the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership. Methods: Functional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app. Results: For iCanQuit, participants were clustered into 3 groups: ?1-week users? (610/1069, 57.06%), ?4-week users? (303/1069, 28.34%), and ?26-week users? (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: ?1-week users? (695/1064, 65.32%) and ?3-week users? (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app. Conclusions: Patterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful. UR - https://www.jmir.org/2022/8/e39208 UR - http://dx.doi.org/10.2196/39208 UR - http://www.ncbi.nlm.nih.gov/pubmed/35831180 ID - info:doi/10.2196/39208 ER - TY - JOUR AU - Stephan, Paul AU - Wortmann, Felix AU - Koch, Kevin PY - 2022/8/30 TI - Understanding the Interactions Between Driving Behavior and Well-being in Daily Driving: Causal Analysis of a Field Study JO - J Med Internet Res SP - e36314 VL - 24 IS - 8 KW - well-being KW - daily driving KW - causal inference KW - commute KW - field study KW - directed acyclic graph KW - just-in-time interventions KW - mental well-being KW - stress KW - mental health N2 - Background: Investigating ways to improve well-being in everyday situations as a means of fostering mental health has gained substantial interest in recent years. For many people, the daily commute by car is a particularly straining situation of the day, and thus researchers have already designed various in-vehicle well-being interventions for a better commuting experience. Current research has validated such interventions but is limited to isolating effects in controlled experiments that are generally not representative of real-world driving conditions. Objective: The aim of the study is to identify cause?effect relationships between driving behavior and well-being in a real-world setting. This knowledge should contribute to a better understanding of when to trigger interventions. Methods: We conducted a field study in which we provided a demographically diverse sample of 10 commuters with a car for daily driving over a period of 4 months. Before and after each trip, the drivers had to fill out a questionnaire about their state of well-being, which was operationalized as arousal and valence. We equipped the cars with sensors that recorded driving behavior, such as sudden braking. We also captured trip-dependent factors, such as the length of the drive, and predetermined factors, such as the weather. We conducted a causal analysis based on a causal directed acyclic graph (DAG) to examine cause?effect relationships from the observational data and to isolate the causal chains between the examined variables. We did so by applying the backdoor criterion to the data-based graphical model. The hereby compiled adjustment set was used in a multiple regression to estimate the causal effects between the variables. Results: The causal analysis showed that a higher level of arousal before driving influences driving behavior. Higher arousal reduced the frequency of sudden events (P=.04) as well as the average speed (P=.001), while fostering active steering (P<.001). In turn, more frequent braking (P<.001) increased arousal after the drive, while a longer trip (P<.001) with a higher average speed (P<.001) reduced arousal. The prevalence of sunshine (P<.001) increased arousal and of occupants (P<.001) increased valence (P<.001) before and after driving. Conclusions: The examination of cause?effect relationships unveiled significant interactions between well-being and driving. A low level of predriving arousal impairs driving behavior, which manifests itself in more frequent sudden events and less anticipatory driving. Driving has a stronger effect on arousal than on valence. In particular, monotonous driving situations at high speeds with low cognitive demand increase the risk of the driver becoming tired (low arousal), thus impairing driving behavior. By combining the identified causal chains, states of vulnerability can be inferred that may form the basis for timely delivered interventions to improve well-being while driving. UR - https://www.jmir.org/2022/8/e36314 UR - http://dx.doi.org/10.2196/36314 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040791 ID - info:doi/10.2196/36314 ER - TY - JOUR AU - Stemmer, Maya AU - Parmet, Yisrael AU - Ravid, Gilad PY - 2022/8/2 TI - Identifying Patients With Inflammatory Bowel Disease on Twitter and Learning From Their Personal Experience: Retrospective Cohort Study JO - J Med Internet Res SP - e29186 VL - 24 IS - 8 KW - patient identification KW - inflammatory bowel disease KW - IBD KW - user classification KW - Twitter KW - natural language processing KW - NLP KW - sentiment analysis N2 - Background: Patients use social media as an alternative information source, where they share information and provide social support. Although large amounts of health-related data are posted on Twitter and other social networking platforms each day, research using social media data to understand chronic conditions and patients? lifestyles is limited. Objective: In this study, we contributed to closing this gap by providing a framework for identifying patients with inflammatory bowel disease (IBD) on Twitter and learning from their personal experiences. We enabled the analysis of patients? tweets by building a classifier of Twitter users that distinguishes patients from other entities. This study aimed to uncover the potential of using Twitter data to promote the well-being of patients with IBD by relying on the wisdom of the crowd to identify healthy lifestyles. We sought to leverage posts describing patients? daily activities and their influence on their well-being to characterize lifestyle-related treatments. Methods: In the first stage of the study, a machine learning method combining social network analysis and natural language processing was used to automatically classify users as patients or not. We considered 3 types of features: the user?s behavior on Twitter, the content of the user?s tweets, and the social structure of the user?s network. We compared the performances of several classification algorithms within 2 classification approaches. One classified each tweet and deduced the user?s class from their tweet-level classification. The other aggregated tweet-level features to user-level features and classified the users themselves. Different classification algorithms were examined and compared using 4 measures: precision, recall, F1 score, and the area under the receiver operating characteristic curve. In the second stage, a classifier from the first stage was used to collect patients' tweets describing the different lifestyles patients adopt to deal with their disease. Using IBM Watson Service for entity sentiment analysis, we calculated the average sentiment of 420 lifestyle-related words that patients with IBD use when describing their daily routine. Results: Both classification approaches showed promising results. Although the precision rates were slightly higher for the tweet-level approach, the recall and area under the receiver operating characteristic curve of the user-level approach were significantly better. Sentiment analysis of tweets written by patients with IBD identified frequently mentioned lifestyles and their influence on patients? well-being. The findings reinforced what is known about suitable nutrition for IBD as several foods known to cause inflammation were pointed out in negative sentiment, whereas relaxing activities and anti-inflammatory foods surfaced in a positive context. Conclusions: This study suggests a pipeline for identifying patients with IBD on Twitter and collecting their tweets to analyze the experimental knowledge they share. These methods can be adapted to other diseases and enhance medical research on chronic conditions. UR - https://www.jmir.org/2022/8/e29186 UR - http://dx.doi.org/10.2196/29186 UR - http://www.ncbi.nlm.nih.gov/pubmed/35917151 ID - info:doi/10.2196/29186 ER - TY - JOUR AU - Metzler, Hannah AU - Baginski, Hubert AU - Niederkrotenthaler, Thomas AU - Garcia, David PY - 2022/8/17 TI - Detecting Potentially Harmful and Protective Suicide-Related Content on Twitter: Machine Learning Approach JO - J Med Internet Res SP - e34705 VL - 24 IS - 8 KW - suicide prevention KW - Twitter KW - social media KW - machine learning KW - deep learning N2 - Background: Research has repeatedly shown that exposure to suicide-related news media content is associated with suicide rates, with some content characteristics likely having harmful and others potentially protective effects. Although good evidence exists for a few selected characteristics, systematic and large-scale investigations are lacking. Moreover, the growing importance of social media, particularly among young adults, calls for studies on the effects of the content posted on these platforms. Objective: This study applies natural language processing and machine learning methods to classify large quantities of social media data according to characteristics identified as potentially harmful or beneficial in media effects research on suicide and prevention. Methods: We manually labeled 3202 English tweets using a novel annotation scheme that classifies suicide-related tweets into 12 categories. Based on these categories, we trained a benchmark of machine learning models for a multiclass and a binary classification task. As models, we included a majority classifier, an approach based on word frequency (term frequency-inverse document frequency with a linear support vector machine) and 2 state-of-the-art deep learning models (Bidirectional Encoder Representations from Transformers [BERT] and XLNet). The first task classified posts into 6 main content categories, which are particularly relevant for suicide prevention based on previous evidence. These included personal stories of either suicidal ideation and attempts or coping and recovery, calls for action intending to spread either problem awareness or prevention-related information, reporting of suicide cases, and other tweets irrelevant to these 5 categories. The second classification task was binary and separated posts in the 11 categories referring to actual suicide from posts in the off-topic category, which use suicide-related terms in another meaning or context. Results: In both tasks, the performance of the 2 deep learning models was very similar and better than that of the majority or the word frequency classifier. BERT and XLNet reached accuracy scores above 73% on average across the 6 main categories in the test set and F1-scores between 0.69 and 0.85 for all but the suicidal ideation and attempts category (F1=0.55). In the binary classification task, they correctly labeled around 88% of the tweets as about suicide versus off-topic, with BERT achieving F1-scores of 0.93 and 0.74, respectively. These classification performances were similar to human performance in most cases and were comparable with state-of-the-art models on similar tasks. Conclusions: The achieved performance scores highlight machine learning as a useful tool for media effects research on suicide. The clear advantage of BERT and XLNet suggests that there is crucial information about meaning in the context of words beyond mere word frequencies in tweets about suicide. By making data labeling more efficient, this work has enabled large-scale investigations on harmful and protective associations of social media content with suicide rates and help-seeking behavior. UR - https://www.jmir.org/2022/8/e34705 UR - http://dx.doi.org/10.2196/34705 UR - http://www.ncbi.nlm.nih.gov/pubmed/35976193 ID - info:doi/10.2196/34705 ER - TY - JOUR AU - Hsu, Tze-Hou Jerome AU - Tsai, Tzong-Han Richard PY - 2022/8/9 TI - Increased Online Aggression During COVID-19 Lockdowns: Two-Stage Study of Deep Text Mining and Difference-in-Differences Analysis JO - J Med Internet Res SP - e38776 VL - 24 IS - 8 KW - natural language processing KW - lockdown KW - online aggression KW - infoveillance KW - causal relationship KW - social media KW - neural networks KW - computer KW - pandemic KW - COVID-19 KW - emotions KW - internet KW - sentiment analysis KW - Twitter KW - content analysis KW - infodemiology N2 - Background: The COVID-19 pandemic caused a critical public health crisis worldwide, and policymakers are using lockdowns to control the virus. However, there has been a noticeable increase in aggressive social behaviors that threaten social stability. Lockdown measures might negatively affect mental health and lead to an increase in aggressive emotions. Discovering the relationship between lockdown and increased aggression is crucial for formulating appropriate policies that address these adverse societal effects. We applied natural language processing (NLP) technology to internet data, so as to investigate the social and emotional impacts of lockdowns. Objective: This research aimed to understand the relationship between lockdown and increased aggression using NLP technology to analyze the following 3 kinds of aggressive emotions: anger, offensive language, and hate speech, in spatiotemporal ranges of tweets in the United States. Methods: We conducted a longitudinal internet study of 11,455 Twitter users by analyzing aggressive emotions in 1,281,362 tweets they posted from 2019 to 2020. We selected 3 common aggressive emotions (anger, offensive language, and hate speech) on the internet as the subject of analysis. To detect the emotions in the tweets, we trained a Bidirectional Encoder Representations from Transformers (BERT) model to analyze the percentage of aggressive tweets in every state and every week. Then, we used the difference-in-differences estimation to measure the impact of lockdown status on increasing aggressive tweets. Since most other independent factors that might affect the results, such as seasonal and regional factors, have been ruled out by time and state fixed effects, a significant result in this difference-in-differences analysis can not only indicate a concrete positive correlation but also point to a causal relationship. Results: In the first 6 months of lockdown in 2020, aggression levels in all users increased compared to the same period in 2019. Notably, users under lockdown demonstrated greater levels of aggression than those not under lockdown. Our difference-in-differences estimation discovered a statistically significant positive correlation between lockdown and increased aggression (anger: P=.002, offensive language: P<.001, hate speech: P=.005). It can be inferred from such results that there exist causal relations. Conclusions: Understanding the relationship between lockdown and aggression can help policymakers address the personal and societal impacts of lockdown. Applying NLP technology and using big data on social media can provide crucial and timely information for this effort. UR - https://www.jmir.org/2022/8/e38776 UR - http://dx.doi.org/10.2196/38776 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943771 ID - info:doi/10.2196/38776 ER - TY - JOUR AU - Kling, R. Samantha M. AU - Saliba-Gustafsson, A. Erika AU - Winget, Marcy AU - Aleshin, A. Maria AU - Garvert, W. Donn AU - Amano, Alexis AU - Brown-Johnson, G. Cati AU - Kwong, Y. Bernice AU - Calugar, Ana AU - El-Banna, Ghida AU - Shaw, G. Jonathan AU - Asch, M. Steven AU - Ko, M. Justin PY - 2022/8/3 TI - Teledermatology to Facilitate Patient Care Transitions From Inpatient to Outpatient Dermatology: Mixed Methods Evaluation JO - J Med Internet Res SP - e38792 VL - 24 IS - 8 KW - teledermatology KW - telemedicine KW - telehealth KW - video visits KW - care transitions KW - care coordination KW - discharge planning KW - follow-up KW - inpatient KW - outpatient KW - mixed methods KW - dermatology KW - mobile phone KW - smartphone N2 - Background: Both clinicians and patients have increasingly turned to telemedicine to improve care access, even in physical examination?dependent specialties such as dermatology. However, little is known about whether teledermatology supports effective and timely transitions from inpatient to outpatient care, which is a common care coordination gap. Objective: Using mixed methods, this study sought to retrospectively evaluate how teledermatology affected clinic capacity, scheduling efficiency, and timeliness of follow-up care for patients transitioning from inpatient to outpatient dermatology care. Methods: Patient-level encounter scheduling data were used to compare the number and proportion of patients who were scheduled and received in-clinic or video dermatology follow-ups within 14 and 90 days after discharge across 3 phases: June to September 2019 (before teledermatology), June to September 2020 (early teledermatology), and February to May 2021 (sustained teledermatology). The time from discharge to scheduling and completion of patient follow-up visits for each care modality was also compared. Dermatology clinicians and schedulers were also interviewed between April and May 2021 to assess their perceptions of teledermatology for postdischarge patients. Results: More patients completed follow-up within 90 days after discharge during early (n=101) and sustained (n=100) teledermatology use than at baseline (n=74). Thus, the clinic?s capacity to provide follow-up to patients transitioning from inpatient increased from baseline by 36% in the early (101 from 74) and sustained (100 from 74) teledermatology periods. During early teledermatology use, 61.4% (62/101) of the follow-ups were conducted via video. This decreased significantly to 47% (47/100) in the following year, when COVID-19?related restrictions started to lift (P=.04), indicating more targeted but still substantial use. The proportion of patients who were followed up within the recommended 14 days after discharge did not differ significantly between video and in-clinic visits during the early (33/62, 53% vs 15/39, 38%; P=.15) or sustained (26/53, 60% vs 28/47, 49%; P=.29) teledermatology periods. Interviewees agreed that teledermatology would continue to be offered. Most considered postdischarge follow-up patients to be ideal candidates for teledermatology as they had undergone a recent in-person assessment and might have difficulty attending in-clinic visits because of competing health priorities. Some reported patients needing technological support. Ultimately, most agreed that the choice of follow-up care modality should be the patient?s own. Conclusions: Teledermatology could be an important tool for maintaining accessible, flexible, and convenient care for recently discharged patients needing follow-up care. Teledermatology increased clinic capacity, even during the pandemic, although the timeliness of care transitions did not improve. Ultimately, the care modality should be determined through communication with patients to incorporate their and their caregivers? preferences. UR - https://www.jmir.org/2022/8/e38792 UR - http://dx.doi.org/10.2196/38792 UR - http://www.ncbi.nlm.nih.gov/pubmed/35921146 ID - info:doi/10.2196/38792 ER - TY - JOUR AU - Tzeng, Yun-Hsuan AU - Yin, Wei-Hsian AU - Lin, Kuan-Chia AU - Wei, Jeng AU - Liou, Hao-Ren AU - Sung, Hung-Ju AU - Lang, Hui-Chu PY - 2022/8/12 TI - Factors Associated With the Utilization of Outpatient Virtual Clinics: Retrospective Observational Study Using Multilevel Analysis JO - J Med Internet Res SP - e40288 VL - 24 IS - 8 KW - telemedicine KW - remote consultation KW - e-consult KW - virtual clinic KW - outpatient KW - virtual care KW - virtual consult KW - physicians KW - health policy KW - health care delivery KW - COVID-19 KW - multilevel analysis KW - outpatient clinic KW - telehealth KW - virtual health KW - health care system KW - adoption KW - attitude KW - perception N2 - Background: Although the COVID-19 pandemic has accelerated the adoption of telemedicine and virtual consultations worldwide, complex factors that may affect the use of virtual clinics are still unclear. Objective: This study aims to identify factors associated with the utilization of virtual clinics in the experience of virtual clinic service implementation in Taiwan. Methods: We retrospectively analyzed a total of 187,742 outpatient visits (176,815, 94.2%, in-person visits and 10,927, 5.8%, virtual visits) completed at a large general hospital in Taipei City from May 19 to July 31, 2021, after rapid implementation of virtual outpatient clinic visits due to the COVID-19 pandemic. Data of patients? demographic characteristics, disease type, physicians? features, and specialties/departments were collected, and physicians? opinions regarding virtual clinics were surveyed and evaluated using a 5-point Likert scale. Multilevel analysis was conducted to determine the factors associated with the utilization of virtual clinics. Results: Patient-/visit-, physician-, and department-level factors accounted for 67.5%, 11.1%, and 21.4% of the total variance in the utilization of virtual clinics, respectively. Female sex (odds ratio [OR] 1.27, 95% CI 1.22-1.33, P<.001); residing at a greater distance away from the hospital (OR 2.36, 95% CI 2.15-2.58 if distance>50 km, P<.001; OR 3.95, 95% CI 3.11-5.02 if extensive travel required, P<.001); reimbursement by the National Health Insurance (NHI; OR 7.29, 95% CI 5.71-9.30, P<.001); seeking care for a major chronic disease (OR 1.33, 95% CI 1.24-1.42, P<.001); the physician?s positive attitude toward virtual clinics (OR 1.50, 95% CI 1.16-1.93, P=.002); and visits within certain departments, including the heart center, psychiatry, and internal medicine (OR 2.55, 95% CI 1.46-4.46, P=.004), were positively associated with the utilization of virtual clinics. The patient?s age, the physician?s age, and the physician?s sex were not associated with the utilization of virtual clinics in our study. Conclusions: Our results show that in addition to previously demonstrated patient-level factors that may influence telemedicine use, including the patient?s sex and distance from the hospital, factors at the visit level (insurance type, disease type), physician level (physician?s attitude toward virtual clinics), and department level also contribute to the utilization of virtual clinics. Although there was a more than 300-fold increase in the number of virtual visits during the pandemic compared with the prepandemic period, the majority (176,815/187,742, 94.2%) of the outpatient visits were still in-person visits during the study period. Therefore, it is of great importance to understand the factors impacting the utilization of virtual clinics to accelerate the implementation of telemedicine. The findings of our study may help direct policymaking for expanding the use of virtual clinics, especially in countries struggling with the development and promotion of telemedicine virtual clinic services. UR - https://www.jmir.org/2022/8/e40288 UR - http://dx.doi.org/10.2196/40288 UR - http://www.ncbi.nlm.nih.gov/pubmed/35917486 ID - info:doi/10.2196/40288 ER - TY - JOUR AU - Lin, L. Jody AU - Huber, Bernd AU - Amir, Ofra AU - Gehrmann, Sebastian AU - Ramirez, S. Kimberly AU - Ochoa, M. Kimberly AU - Asch, M. Steven AU - Gajos, Z. Krzysztof AU - Grosz, J. Barbara AU - Sanders, M. Lee PY - 2022/8/23 TI - Barriers and Facilitators to the Implementation of Family-Centered Technology in Complex Care: Feasibility Study JO - J Med Internet Res SP - e30902 VL - 24 IS - 8 KW - care coordination KW - implementation science KW - chronic illness KW - pediatric KW - family medicine KW - barrier KW - complex care KW - children KW - families KW - parents KW - care providers KW - chronic disease KW - coordination KW - implementation KW - improvement KW - technology KW - feasibility KW - acceptability KW - monitoring N2 - Background: Care coordination is challenging but crucial for children with medical complexity (CMC). Technology-based solutions are increasingly prevalent but little is known about how to successfully deploy them in the care of CMC. Objective: The aim of this study was to assess the feasibility and acceptability of GoalKeeper (GK), an internet-based system for eliciting and monitoring family-centered goals for CMC, and to identify barriers and facilitators to implementation. Methods: We used the Consolidated Framework for Implementation Research (CFIR) to explore the barriers and facilitators to the implementation of GK as part of a clinical trial of GK in ambulatory clinics at a children?s hospital (NCT03620071). The study was conducted in 3 phases: preimplementation, implementation (trial), and postimplementation. For the trial, we recruited providers at participating clinics and English-speaking parents of CMC<12 years of age with home internet access. All participants used GK during an initial clinic visit and for 3 months after. We conducted preimplementation focus groups and postimplementation semistructured exit interviews using the CFIR interview guide. Participant exit surveys assessed GK feasibility and acceptability on a 5-point Likert scale. For each interview, 3 independent coders used content analysis and serial coding reviews based on the CFIR qualitative analytic plan and assigned quantitative ratings to each CFIR construct (?2 strong barrier to +2 strong facilitator). Results: Preimplementation focus groups included 2 parents (1 male participant and 1 female participant) and 3 providers (1 in complex care, 1 in clinical informatics, and 1 in neurology). From focus groups, we developed 3 implementation strategies: education (parents: 5-minute demo; providers: 30-minute tutorial and 5-minute video on use in a clinic visit; both: instructional manual), tech support (in-person, virtual), and automated email reminders for parents. For implementation (April 1, 2019, to December 21, 2020), we enrolled 11 providers (7 female participants, 5 in complex care) and 35 parents (mean age 38.3, SD 7.8 years; n=28, 80% female; n=17, 49% Caucasian; n=16, 46% Hispanic; and n=30, 86% at least some college). One parent-provider pair did not use GK in the clinic visit, and few used GK after the visit. In 18 parent and 9 provider exit interviews, the key facilitators were shared goal setting, GK?s internet accessibility and email reminders (parents), and GK?s ability to set long-term goals and use at the end of visits (providers). A key barrier was GK?s lack of integration into the electronic health record or patient portal. Most parents (13/19) and providers (6/9) would recommend GK to their peers. Conclusions: Family-centered technologies like GK are feasible and acceptable for the care of CMC, but sustained use depends on integration into electronic health records. Trial Registration: ClinicalTrials.gov NCT03620071; https://clinicaltrials.gov/ct2/show/NCT03620071 UR - https://www.jmir.org/2022/8/e30902 UR - http://dx.doi.org/10.2196/30902 UR - http://www.ncbi.nlm.nih.gov/pubmed/35998021 ID - info:doi/10.2196/30902 ER - TY - JOUR AU - Torp, Cæsar Daniel AU - Sandbæk, Annelli AU - Prætorius, Thim PY - 2022/8/30 TI - The Technology Acceptance of Video Consultations for Type 2 Diabetes Care in General Practice: Cross-sectional Survey of Danish General Practitioners JO - J Med Internet Res SP - e37223 VL - 24 IS - 8 KW - video consultations KW - telemedicine KW - diabetes KW - chronic diseases KW - general practice KW - technology acceptance KW - technology acceptance model N2 - Background: During the COVID-19 pandemic, video consultations became a common method of delivering care in general practice. To date, research has mostly studied acute or subacute care, thereby leaving a knowledge gap regarding the potential of using video consultations to manage chronic diseases. Objective: This study aimed to examine general practitioners? technology acceptance of video consultations for the purpose of managing type 2 diabetes in general practice. Methods: A web-based survey based on the technology acceptance model measuring 4 dimensions?perceived usefulness, perceived ease of use, attitude, and behavioral intention to use?was sent to all general practices (N=1678) in Denmark to elicit user perspectives. The data were analyzed using structural equation modeling. Results: The survey sample comprised 425 general practitioners who were representative of the population. Structural equation modeling showed that 4 of the 5 hypotheses in the final research model were statistically significant (P<.001). Perceived ease of use had a positive influence on perceived usefulness and attitude. Attitude was positively influenced by perceived usefulness. Attitude had a positive influence on behavioral intention to use, although perceived usefulness did not. Goodness-of-fit indices showed acceptable fits for the structural equation modeling estimation. Conclusions: Perceived usefulness was the primary driver of general practitioners? positive attitude toward video consultations for type 2 diabetes care. The study suggests that to improve attitude and technology use, decision-makers should focus on improving usefulness, that is, how it can improve treatment and make it more effective and easier. UR - https://www.jmir.org/2022/8/e37223 UR - http://dx.doi.org/10.2196/37223 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040765 ID - info:doi/10.2196/37223 ER - TY - JOUR AU - Dahne, Jennifer AU - Player, S. Marty AU - Strange, Charlie AU - Carpenter, J. Matthew AU - Ford, W. Dee AU - King, Kathryn AU - Miller, Sarah AU - Kruis, Ryan AU - Hawes, Elizabeth AU - Hidalgo, E. Johanna AU - Diaz, A. Vanessa PY - 2022/8/30 TI - Proactive Electronic Visits for Smoking Cessation and Chronic Obstructive Pulmonary Disease Screening in Primary Care: Randomized Controlled Trial of Feasibility, Acceptability, and Efficacy JO - J Med Internet Res SP - e38663 VL - 24 IS - 8 KW - electronic visits KW - e-visit KW - COPD KW - chronic obstructive pulmonary disease KW - smoking cessation KW - telehealth KW - electronic health record KW - patient portal KW - EHR KW - feasibility KW - efficacy KW - intervention KW - screening KW - diagnosis KW - prevention KW - treatment KW - management KW - acceptability KW - pulmonary KW - function N2 - Background: Most smokers with chronic obstructive pulmonary disease (COPD) have not yet been diagnosed, a statistic that has remained unchanged for over two decades. A dual-focused telehealth intervention that promotes smoking cessation, while also facilitating COPD screening, could help address national priorities to improve the diagnosis, prevention, treatment, and management of COPD. The purpose of this study was to preliminarily evaluate an integrated asynchronous smoking cessation and COPD screening e-visit (electronic visit) that could be delivered proactively to adult smokers at risk for COPD, who are treated within primary care. Objective: The aims of this study were (1) to examine e-visit feasibility and acceptability, particularly as compared to in-lab diagnostic pulmonary function testing (PFT), and (2) to examine the efficacy of smoking cessation e-visits relative to treatment as usual (TAU), all within primary care. Methods: In a randomized clinical trial, 125 primary care patients who smoke were randomized 2:1 to receive either proactive e-visits or TAU. Participants randomized to the e-visit condition were screened for COPD symptoms via the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE). Those with scores ?2 were invited to complete both home spirometry and in-lab PFTs, in addition to two smoking cessation e-visits. Smoking cessation e-visits assessed smoking history and motivation to quit and included completion of an algorithm to determine the best Food and Drug Administration?approved cessation medication to prescribe. Primary outcomes included measures related to (1) e-visit acceptability, feasibility, and treatment metrics; (2) smoking cessation outcomes (cessation medication use, 24-hour quit attempts, smoking reduction ?50%, self-reported abstinence, and biochemically confirmed abstinence); and (3) COPD screening outcomes. Results: Of 85 participants assigned to the e-visits, 64 (75.3%) were invited to complete home spirometry and in-lab PFTs based on CAPTURE. Among those eligible for spirometry, 76.6% (49/64) completed home spirometry, and 35.9% (23/64) completed in-lab PFTs. At 1 month, all cessation outcomes favored the e-visit, with a significant effect for cessation medication use (odds ratio [OR]=3.22). At 3 months, all cessation outcomes except for 24-hour quit attempts favored the e-visit, with significant effects for cessation medication use (OR=3.96) and smoking reduction (OR=3.09). Conclusions: A proactive, asynchronous e-visit for smoking cessation and COPD screening may offer a feasible, efficacious approach for broad interventions within primary care. Trial Registration: ClinicalTrials.gov NCT04155073; https://clinicaltrials.gov/ct2/show/NCT04155073 UR - https://www.jmir.org/2022/8/e38663 UR - http://dx.doi.org/10.2196/38663 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040766 ID - info:doi/10.2196/38663 ER - TY - JOUR AU - Sun, Y. Enid AU - Alvarez, Carolina AU - Callahan, F. Leigh AU - Sheikh, Z. Saira PY - 2022/8/31 TI - The Disparities in Patient Portal Use Among Patients With Rheumatic and Musculoskeletal Diseases: Retrospective Cross-sectional Study JO - J Med Internet Res SP - e38802 VL - 24 IS - 8 KW - COVID-19 KW - telemedicine KW - telehealth KW - health technology KW - health care disparities KW - patient portal KW - rheumatology KW - musculoskeletal diseases KW - chronic disease KW - digital health KW - MyChart KW - rural area KW - minority population KW - virtual care N2 - Background: During the COVID-19 pandemic, the shift to virtual care became essential for the continued care of patients. Individuals with rheumatic and musculoskeletal diseases (RMDs) especially require frequent provider visits and close monitoring. To date, there have been limited studies examining inequities in health technology use among patients with RMDs. Objective: Our goal was to identify characteristics associated with patient portal use before and after the COVID-19 pandemic in a convenience sample of patients with RMDs from a large academic medical center. Methods: In this cross-sectional study, Epic electronic medical record data were queried to identify established patients of the University of North Carolina Hospitals adult rheumatology clinic between November 1, 2017, through November 30, 2019. Demographic and clinical data were collected to compare MyChart (Epic?s patient portal) users with nonusers before and after the COVID-19 pandemic. MyChart activation and use were modeled using logistic regression and adjusted odds ratios, and confidence intervals were estimated. Results: We identified 5075 established patients with RMDs who met the inclusion criteria. Prior to the pandemic, we found that younger age (P<.001), suburban residence (P=.05), commercial/state insurance (P<.001), military insurance (P=.05), and median income >US $50,000 (P<.001) were associated with significantly higher odds of MyChart activation. Male sex (P<.001), being of Black or African American (P<.001) or ?other? race (P<.001), Spanish as a primary language (P<.001), rural residence (P=.007), Medicaid insurance (P<.001), and median income of .05) between group A and group B or among the 4 subgroups. Pretest digital device experience and amount of time spent using digital devices during the test had no significant impacts on the cognitive development of the children. Conversely, the multivariate analyses showed that cognitive function was associated with educational expenses per child, school (location), family type, and family income. Conclusions: These results provide evidence to policy makers and practitioners on the importance of improving socioeconomic conditions, leading to investment in education by implementing programs for children?s cognitive development through digital devices in LMICs. UR - https://www.jmir.org/2022/8/e31206 UR - http://dx.doi.org/10.2196/31206 UR - http://www.ncbi.nlm.nih.gov/pubmed/36044246 ID - info:doi/10.2196/31206 ER - TY - JOUR AU - Dixon, Emma AU - Anderson, Jesse AU - Blackwelder, C. Diana AU - Radnofsky, L. Mary AU - Lazar, Amanda PY - 2022/8/11 TI - The Human Need for Equilibrium: Qualitative Study on the Ingenuity, Technical Competency, and Changing Strategies of People With Dementia Seeking Health Information JO - J Med Internet Res SP - e35072 VL - 24 IS - 8 KW - dementia KW - health information behavior KW - action research KW - equilibrium KW - postdiagnostic experience KW - mobile phone N2 - Background: Prior research on health information behaviors of people with dementia has primarily focused on examining the types of information exchanged by people with dementia using various web-based platforms. A previous study investigated the information behaviors of people with dementia within a month of their diagnosis. There is an empirical gap in the literature regarding the evolution of health information needs and behaviors of people with dementia as their condition progresses. Objective: Our work primarily investigated the information behaviors of people with dementia who have been living with the condition for several (4 to 26) years. We also aimed to identify their motivations for changing their information behaviors over time. Our primary research questions were as follows: how do people with dementia get informed about their condition, and why do people with dementia seek information about their condition? Methods: We adopted an action research approach by including 2 people with dementia as members of our research team. Collaboratively, we conducted 16 remote 1-hour contextual inquiry sessions with people living with mild to moderate dementia. During the study sessions, the first 40 minutes included semistructured interviews with participants concerning their information behaviors, followed by a 20-minute demonstration of their information-seeking strategies. Data from these interviews were analyzed using a constructivist grounded theory approach. Results: Participants described their information needs in terms of managing the disrupted physiological, emotional, and social aspects of their lives following a diagnosis of dementia. They used various information behaviors, including active search, ongoing search, monitoring, proxy search, information avoidance, and selective exposure. These information behaviors were not stagnant; however, they were adapted to accommodate the changing circumstances of their dementia and their lives as they worked to re-establish equilibrium to continue to engage in life while living with a degenerative neurological condition. Conclusions: Our research revealed the motivations, changing abilities, and chosen strategies of people with dementia in their search for information as their condition evolves. This knowledge can be used to develop and improve person-centered information and support services for people with dementia so that they can more easily re-establish equilibrium and continue to engage in life. UR - https://www.jmir.org/2022/8/e35072 UR - http://dx.doi.org/10.2196/35072 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969426 ID - info:doi/10.2196/35072 ER - TY - JOUR AU - Krnic Martinic, Marina AU - ?ivljak, Marta AU - Maru?i?, Ana AU - Sapunar, Damir AU - Poklepovi? Peri?i?, Tina AU - Buljan, Ivan AU - Tokali?, Ru?ica AU - Mali?a, Snje?ana AU - Neuberg, Marijana AU - Ivani?evi?, Kata AU - Aranza, Diana AU - Skitareli?, Nata?a AU - Zorani?, Sanja AU - Mik?i?, ?tefica AU - ?avi?, Dalibor AU - Puljak, Livia PY - 2022/8/25 TI - Web-Based Educational Intervention to Improve Knowledge of Systematic Reviews Among Health Science Professionals: Randomized Controlled Trial JO - J Med Internet Res SP - e37000 VL - 24 IS - 8 KW - educational intervention KW - systematic review KW - health science professionals KW - knowledge KW - randomized controlled trial N2 - Background: Lack of knowledge of systematic reviews (SRs) could prevent individual health care professionals from using SRs as a source of information in their clinical practice or discourage them from participating in such research. Objective: In this randomized controlled trial, we evaluated the effect of a short web-based educational intervention on short-term knowledge of SRs. Methods: Eligible participants were 871 Master?s students of university health sciences studies in Croatia; 589 (67.6%) students who agreed to participate in the trial were randomized using a computer program into 2 groups. Intervention group A (294/589, 49.9%) received a short web-based educational intervention about SR methodology, and intervention group B (295/589, 50.1%) was presented with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The participants? knowledge of SRs was assessed before and after the intervention. The participants could not be blinded because of the nature of the intervention. The primary outcome was the difference in the percentage of correct answers about SR methodology per participant between the groups after the intervention, expressed as relative risk and 95% CI. Results: Results from 162 and 165 participants in the educational intervention and PRISMA checklist groups, respectively, were available for analysis. Most of them (educational intervention group: 130/162, 80.2%; PRISMA checklist group: 131/165, 79.4%) were employed as health care professionals in addition to being health sciences students. After the intervention, the educational intervention group had 23% (relative risk percentage) more correct answers in the postintervention questionnaire than the PRISMA checklist group (relative risk=1.23, 95% CI 1.17-1.29). Conclusions: A short web-based educational intervention about SRs is an effective tool for short-term improvement of knowledge of SRs among health care studies students, most of whom were also employed as health care professionals. Further studies are needed to explore the long-term effects of the tested education. Trial Registration: OSF Registries 10.17605/OSF.IO/RYMVC; https://osf.io/rymvc UR - https://www.jmir.org/2022/8/e37000 UR - http://dx.doi.org/10.2196/37000 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006686 ID - info:doi/10.2196/37000 ER - TY - JOUR AU - Tang, W. Wymann S. AU - Ng, Y. Tricia J. AU - Wong, A. Joseph Z. AU - Ho, H. Cyrus S. PY - 2022/8/29 TI - The Role of Serious Video Games in the Treatment of Disordered Eating Behaviors: Systematic Review JO - J Med Internet Res SP - e39527 VL - 24 IS - 8 KW - serious video games KW - serious games KW - video games KW - gamification KW - digital health KW - eHealth KW - mobile health KW - mHealth KW - disordered eating KW - eating disorders N2 - Background: Eating disorders and other forms of disordered eating cause significant complications and comorbidities in patients. However, full remission with current standard treatment remains low. Challenges to treatment include underdiagnosis and high dropout rates, as well as difficulties in addressing underlying emotion dysregulation, poor impulse control, and personality traits. Serious video games (SVGs), which have the advantages of being highly engaging and accessible, may be potential tools for delivering various forms of treatment in addressing the underlying psychopathology of disordered eating. Objective: This review aims to provide an overview of the possible mechanisms by which SVGs may affect the clinical course of disordered eating, while evaluating the outcomes of studies that have assessed the role of SVGs in the treatment of disordered eating. Methods: A systematic search was performed on PubMed, PsycINFO, and Embase, using keywords related to SVGs, disordered eating, and eating disorders. A narrative synthesis was subsequently carried out. Results: In total, 2151 papers were identified, of which 11 (0.51%) were included. Of these 11 studies, 10 (91%) were randomized controlled trials, and 1 (9%) was a quasi-experimental study. The types of SVG interventions varied across the studies and targeted different mechanisms of disordered eating, ranging from addressing problem-solving and emotion regulation skills to neurocognitive training for inhibitory control. Most (10/11, 91%) of the studies showed some benefit of the SVGs in improving certain physical, behavioral, or psychological outcomes related to disordered eating. Some (4/11, 36%) of the studies also showed encouraging evidence of the retention of these benefits at follow-up. Conclusions: The studies included in this review provide collective evidence to suggest the various roles SVGs can play in plugging potential gaps in conventional therapy. Nonetheless, challenges exist in designing these games to prevent potential pitfalls, such as excessive stress arising from the SVGs themselves or potential gaming addiction. Further studies will also be required to assess the long-term benefits of SVGs as well as explore their potential preventive, and not just curative, effects on disordered eating. UR - https://www.jmir.org/2022/8/e39527 UR - http://dx.doi.org/10.2196/39527 UR - http://www.ncbi.nlm.nih.gov/pubmed/36036967 ID - info:doi/10.2196/39527 ER - TY - JOUR AU - Naserianhanzaei, Elahe AU - Koschate-Reis, Miriam PY - 2022/8/22 TI - Effects of Substance Use, Recovery, and Non?Drug-Related Online Community Participation on the Risk of a Use Episode During Remission From Opioid Use Disorder: Longitudinal Observational Study JO - J Med Internet Res SP - e36555 VL - 24 IS - 8 KW - online communities KW - opioid addiction KW - recovery capital KW - social identity KW - Reddit KW - social media N2 - Background: Opioid addiction is currently one of the most pressing public health issues. Despite several treatment options for opioid addiction, the recurrence of use episodes during remission remains high. Research indicates that meaningful membership in various social groups underpins the successful transition from addiction to long-term remission. However, much of the current literature focuses on online peer-support groups for individuals in remission from substance use, sometimes also called recovery groups, a term we will use in line with the terminology used by the online community we studied. In contrast, online group memberships that promote substance use and groups that are unrelated to substance use and remission (non?drug-related groups) are rarely studied. Objective: This study aims to understand whether engagement with a variety of Reddit subforums (subreddits) provides those in remission from opioid use disorder (OUD) with social capital, thereby reducing their risk of a use episode over several years. More specifically, it aims to examine the different effects of engagement with substance use, recovery, and non?drug-related subreddits. Methods: A data set of 457 individuals in remission from OUD who posted their remission start date on Reddit was collected, of whom 219 (47.9%) indicated at least one use episode during the remission period. Using a Cox proportional hazards model, the effects of the number of non?drug-related, recovery, and substance use subreddits an individual had engaged with on the risk of a use episode were tested. Group engagement was assessed both in terms of the absolute number of subreddits and as a proportion of the total number of subreddits in which an individual had posted. Results: Engagement with a larger number of non?drug-related online communities reduced the likelihood of a use episode irrespective of the number of posts and comments made in these forums. This was true for both the absolute number of non?drug-related communities (P<.001) and the proportion of communities with which a person engaged (P<.001). The findings were less conclusive for recovery support and substance use groups; although participating in more recovery support subreddits reduced the risk of a use episode (P<.001), being part of a higher proportion of recovery support groups relative to other subreddits increased the risk (P=.01). A higher proportion of substance use subreddits marginally increased the risk of a use episode (P=.06); however, the absolute number of substance use subreddits significantly reduced the risk of a use episode (P=.002). Conclusions: Our work indicates that even minimal regular engagement with several non?drug-related online forums may provide those in remission from OUD with an opportunity to grow their social capital and reduce the risk of a use episode over several years. UR - https://www.jmir.org/2022/8/e36555 UR - http://dx.doi.org/10.2196/36555 UR - http://www.ncbi.nlm.nih.gov/pubmed/35994333 ID - info:doi/10.2196/36555 ER - TY - JOUR AU - Ashtari, Sadaf AU - Taylor, Daniel Adam PY - 2022/8/25 TI - The Internet Knows More Than My Physician: Qualitative Interview Study of People With Rare Diseases and How They Use Online Support Groups JO - J Med Internet Res SP - e39172 VL - 24 IS - 8 KW - online peer support group KW - genetic disorders KW - pain management KW - Ehlers-Danlos syndrome KW - EDS KW - chronic pain KW - health care provider KW - pain mitigation techniques N2 - Background: Patients struggling with rare diseases may face challenges caused by care providers being unfamiliar with their condition. The life span of people with rare diseases may be the same as that of healthy people, but their quality of life is different. Patients with chronic pain are constantly looking for ways to mitigate their pain. Pain killers are not a permanent solution. In addition to the medical and nonmedical costs of rare diseases for both patients and health care providers, there is a need for sustainable sources of information that are available to help with pain and improve their quality of life, with the goal of reducing physician visits and hospital admissions. Objective: This study investigated the challenges that patients with genetic disorders face in managing their health conditions and finding disease-related information as well as the effect of online peer support groups on pain mitigation and care management. Methods: Interviews were conducted via Zoom between July 2021 and December 2021. Eligible participants were those who were aged >18 years, had a medical diagnosis of any type of Ehlers-Danlos syndrome (EDS) with chronic pain, and were members of any support group. Participants were recruited through an announcement in the research and survey section of The Ehlers-Danlos Syndrome Society web page. Interviews were analyzed using the framework approach. Data were systematically searched to identify patterns, analyze them, and identify themes. Interview audio files were transcribed and independently coded by two researchers (SA and AT). Through an iterative process, a final coding table was agreed upon by the researchers and used to thematically analyze the data. Results: We interviewed 30 participants (mean age 37.7, SD 15 years; n=28, 93% were women; n=23, 77% were residing in the United States). Thematic analysis revealed that participants (patients with EDS) were constantly in pain and most of them have not received accurate and timely diagnoses for many years. They expressed their challenges with health care providers regarding diagnosis and treatment, and complained about their providers? lack of support and knowledge. Participants? main sources of information were web-based searches, academic journals, The Ehlers-Danlos Syndrome Society web page, and online peer support groups on Facebook, Reddit, Twitter, and Instagram. Although pain killers, cannabis, and opioids are providing some pain relief, most patients (28/30, 93%) focused on nonmedical approaches, such as hot or ice packs, physical therapy, exercises, massage, mindfulness, and meditation. Conclusions: This study highlights the information gap between health care providers and patients with genetic disorders. Patients with EDS seek access to information from different web-based sources. To meet the needs of patients with genetic disorders, future interventions via web-based resources for improving the quality of care must be considered by health care professionals and government agencies. UR - https://www.jmir.org/2022/8/e39172 UR - http://dx.doi.org/10.2196/39172 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006679 ID - info:doi/10.2196/39172 ER - TY - JOUR AU - Li, Mingda AU - Shi, Jinhe AU - Chen, Yi PY - 2022/8/31 TI - Identifying Influences in Patient Decision-making Processes in Online Health Communities: Data Science Approach JO - J Med Internet Res SP - e30634 VL - 24 IS - 8 KW - influence relationship KW - decision-making threads KW - online health communities KW - patient engagement KW - deep learning KW - text relevance measurement N2 - Background: In recent years, an increasing number of users have joined online health communities (OHCs) to obtain information and seek support. Patients often look for information and suggestions to support their health care decision-making. It is important to understand patient decision-making processes and identify the influences that patients receive from OHCs. Objective: We aimed to identify the posts in discussion threads that have influence on users who seek help in their decision-making. Methods: We proposed a definition of influence relationship of posts in discussion threads. We then developed a framework and a deep learning model for identifying influence relationships. We leveraged the state-of-the-art text relevance measurement methods to generate sparse feature vectors to present text relevance. We modeled the probability of question and action presence in a post as dense features. We then used deep learning techniques to combine the sparse and dense features to learn the influence relationships. Results: We evaluated the proposed techniques on discussion threads from a popular cancer survivor OHC. The empirical evaluation demonstrated the effectiveness of our approach. Conclusions: It is feasible to identify influence relationships in OHCs. Using the proposed techniques, a significant number of discussions on an OHC were identified to have had influence. Such discussions are more likely to affect user decision-making processes and engage users? participation in OHCs. Studies on those discussions can help improve information quality, user engagement, and user experience. UR - https://www.jmir.org/2022/8/e30634 UR - http://dx.doi.org/10.2196/30634 UR - http://www.ncbi.nlm.nih.gov/pubmed/36044266 ID - info:doi/10.2196/30634 ER - TY - JOUR AU - Huang, Yanqun AU - Zheng, Zhimin AU - Ma, Moxuan AU - Xin, Xin AU - Liu, Honglei AU - Fei, Xiaolu AU - Wei, Lan AU - Chen, Hui PY - 2022/8/3 TI - Improving the Performance of Outcome Prediction for Inpatients With Acute Myocardial Infarction Based on Embedding Representation Learned From Electronic Medical Records: Development and Validation Study JO - J Med Internet Res SP - e37486 VL - 24 IS - 8 KW - representation learning KW - skip-gram KW - feature association strengths KW - feature importance KW - mortality risk prediction KW - acute myocardial infarction N2 - Background: The widespread secondary use of electronic medical records (EMRs) promotes health care quality improvement. Representation learning that can automatically extract hidden information from EMR data has gained increasing attention. Objective: We aimed to propose a patient representation with more feature associations and task-specific feature importance to improve the outcome prediction performance for inpatients with acute myocardial infarction (AMI). Methods: Medical concepts, including patients? age, gender, disease diagnoses, laboratory tests, structured radiological features, procedures, and medications, were first embedded into real-value vectors using the improved skip-gram algorithm, where concepts in the context windows were selected by feature association strengths measured by association rule confidence. Then, each patient was represented as the sum of the feature embeddings weighted by the task-specific feature importance, which was applied to facilitate predictive model prediction from global and local perspectives. We finally applied the proposed patient representation into mortality risk prediction for 3010 and 1671 AMI inpatients from a public data set and a private data set, respectively, and compared it with several reference representation methods in terms of the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and F1-score. Results: Compared with the reference methods, the proposed embedding-based representation showed consistently superior predictive performance on the 2 data sets, achieving mean AUROCs of 0.878 and 0.973, AUPRCs of 0.220 and 0.505, and F1-scores of 0.376 and 0.674 for the public and private data sets, respectively, while the greatest AUROCs, AUPRCs, and F1-scores among the reference methods were 0.847 and 0.939, 0.196 and 0.283, and 0.344 and 0.361 for the public and private data sets, respectively. Feature importance integrated in patient representation reflected features that were also critical in prediction tasks and clinical practice. Conclusions: The introduction of feature associations and feature importance facilitated an effective patient representation and contributed to prediction performance improvement and model interpretation. UR - https://www.jmir.org/2022/8/e37486 UR - http://dx.doi.org/10.2196/37486 UR - http://www.ncbi.nlm.nih.gov/pubmed/35921141 ID - info:doi/10.2196/37486 ER - TY - JOUR AU - Gray, Caroline AU - Wray, Charlie AU - Tisdale, Rebecca AU - Chaudary, Camila AU - Slightam, Cindie AU - Zulman, Donna PY - 2022/8/24 TI - Factors Influencing How Providers Assess the Appropriateness of Video Visits: Interview Study With Primary and Specialty Health Care Providers JO - J Med Internet Res SP - e38826 VL - 24 IS - 8 KW - virtual care KW - decision-making KW - qualitative KW - virtual visits KW - web-based KW - carer KW - video KW - telephone KW - telemedicine KW - appointments KW - caregiver N2 - Background: The rapid implementation of virtual care (ie, telephone or video-based clinic appointments) during the COVID-19 pandemic resulted in many providers offering virtual care with little or no formal training and without clinical guidelines and tools to assist with decision-making. As new guidelines for virtual care provision take shape, it is critical that they are informed by an in-depth understanding of how providers make decisions about virtual care in their clinical practices. Objective: In this paper, we sought to identify the most salient factors that influence how providers decide when to offer patients video appointments instead of or in conjunction with in-person care. Methods: We conducted semistructured interviews with 28 purposefully selected primary and specialty health care providers from the US Department of Veteran?s Affairs health care system. We used an inductive approach to identify factors that impact provider decision-making. Results: Qualitative analysis revealed distinct clinical, patient, and provider factors that influence provider decisions to initiate or continue with virtual visits. Clinical factors include patient acuity, the need for additional tests or labs, changes in patients? health status, and whether the patient is new or has no recent visit. Patient factors include patients? ability to articulate symptoms or needs, availability and accessibility of technology, preferences for or against virtual visits, and access to caregiver assistance. Provider factors include provider comfort with and acceptance of virtual technology as well as virtual physical exam skills and training. Conclusions: Providers within the US Department of Veterans Affairs health administration system consider a complex set of factors when deciding whether to offer or continue a video or telephone visit. These factors can inform the development and further refinement of decision tools, guides, and other policies to ensure that virtual care expands access to high-quality care. UR - https://www.jmir.org/2022/8/e38826 UR - http://dx.doi.org/10.2196/38826 UR - http://www.ncbi.nlm.nih.gov/pubmed/36001364 ID - info:doi/10.2196/38826 ER - TY - JOUR AU - Lowe, Cabella AU - Browne, Mitchell AU - Marsh, William AU - Morrissey, Dylan PY - 2022/8/30 TI - Usability Testing of a Digital Assessment Routing Tool for Musculoskeletal Disorders: Iterative, Convergent Mixed Methods Study JO - J Med Internet Res SP - e38352 VL - 24 IS - 8 KW - mobile health KW - mHealth KW - eHealth KW - digital health KW - digital technology KW - musculoskeletal KW - triage KW - physiotherapy triage KW - usability KW - acceptability KW - mobile phone N2 - Background: Musculoskeletal disorders negatively affect millions of patients worldwide, placing significant demand on health care systems. Digital technologies that improve clinical outcomes and efficiency across the care pathway are development priorities. We developed the musculoskeletal Digital Assessment Routing Tool (DART) to enable self-assessment and immediate direction to the right care. Objective: We aimed to assess and resolve all serious DART usability issues to create a positive user experience and enhance system adoption before conducting randomized controlled trials for the integration of DART into musculoskeletal management pathways. Methods: An iterative, convergent mixed methods design was used, with 22 adult participants assessing 50 different clinical presentations over 5 testing rounds across 4 DART iterations. Participants were recruited using purposive sampling, with quotas for age, habitual internet use, and English-language ability. Quantitative data collection was defined by the constructs within the International Organization for Standardization 9241-210-2019 standard, with user satisfaction measured by the System Usability Scale. Study end points were resolution of all grade 1 and 2 usability problems and a mean System Usability Scale score of ?80 across a minimum of 3 user group sessions. Results: All participants (mean age 48.6, SD 15.2; range 20-77 years) completed the study. Every assessment resulted in a recommendation with no DART system errors and a mean completion time of 5.2 (SD 4.44, range 1-18) minutes. Usability problems were reduced from 12 to 0, with trust and intention to act improving during the study. The relationship between eHealth literacy and age, as explored with a scatter plot and calculation of the Pearson correlation coefficient, was performed for all participants (r=?0.2; 20/22, 91%) and repeated with a potential outlier removed (r=?0.23), with no meaningful relationships observed or found for either. The mean satisfaction for daily internet users was highest (19/22, 86%; mean 86.5, SD 4.48; 90% confidence level [CL] 1.78 or ?1.78), with nonnative English speakers (6/22, 27%; mean 78.1, SD 4.60; 90% CL 3.79 or ?3.79) and infrequent internet users scoring the lowest (3/22, 14%; mean 70.8, SD 5.44; 90% CL 9.17 or ?9.17), although the CIs overlap. The mean score across all groups was 84.3 (SD 4.67), corresponding to an excellent system, with qualitative data from all participants confirming that DART was simple to use. Conclusions: All serious DART usability issues were resolved, and a good level of satisfaction, trust, and willingness to act on the DART recommendation was demonstrated, thus allowing progression to randomized controlled trials that assess safety and effectiveness against usual care comparators. The iterative, convergent mixed methods design proved highly effective in fully evaluating DART from a user perspective and could provide a blueprint for other researchers of mobile health systems. International Registered Report Identifier (IRRID): RR2-10.2196/27205 UR - https://www.jmir.org/2022/8/e38352 UR - http://dx.doi.org/10.2196/38352 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040787 ID - info:doi/10.2196/38352 ER - TY - JOUR AU - Lamaj, Ganimete AU - Pablo-Trinidad, Alberto AU - Butterworth, Ian AU - Bell, Nolan AU - Benasutti, Ryan AU - Bourquard, Aurelien AU - Sanchez-Ferro, Alvaro AU - Castro-Gonzalez, Carlos AU - Jiménez-Ubieto, Ana AU - Baumann, Tycho AU - Rodriguez-Izquierdo, Antonia AU - Pottier, Elizabeth AU - Shelton, Anthony AU - Martinez-Lopez, Joaquin AU - Sloan, Mark John PY - 2022/8/9 TI - Usability Evaluation of a Noninvasive Neutropenia Screening Device (PointCheck) for Patients Undergoing Cancer Chemotherapy: Mixed Methods Observational Study JO - J Med Internet Res SP - e37368 VL - 24 IS - 8 KW - digital health KW - usability KW - patient-centered care KW - remote monitoring KW - decision support systems KW - white blood cells KW - diagnosis KW - medical device KW - cancer KW - chemotherapy KW - infection KW - white blood cell KW - technology N2 - Background: Patients with cancer undergoing cytotoxic chemotherapy face an elevated risk of developing serious infection as a consequence of their treatment, which lowers their white blood cell count and, more specifically, their absolute neutrophil count. This condition is known as neutropenia. Neutropenia accompanied by a fever is referred to as febrile neutropenia, a common side effect of chemotherapy with a high mortality rate. The timely detection of severe neutropenia (<500 absolute neutrophil count/?L) is critical in detecting and managing febrile neutropenia. Current methods rely on blood draws, which limit them to clinical settings and do not allow frequent or portable monitoring. In this study, we demonstrated the usability of PointCheck, a noninvasive device for neutropenia screening, in a simulated home environment without clinical supervision. PointCheck automatically performs microscopy through the skin of the finger to image the blood flowing through superficial microcapillaries and enables the remote monitoring of neutropenia status, without requiring venipuncture. Objective: This study aimed to evaluate the usability of PointCheck, a noninvasive optical technology for screening severe neutropenia, with the goal of identifying potential user interface, functionality, and design issues from the perspective of untrained users. Methods: We conducted a multicenter study using quantitative and qualitative approaches to evaluate the usability of PointCheck across 154 untrained participants. We used a mixed method approach to gather usability data through user testing observations, a short-answer qualitative questionnaire, and a standardized quantitative System Usability Scale (SUS) survey to assess perceived usability and satisfaction. Results: Of the 154 participants, we found that 108 (70.1%) scored above 80.8 on the SUS across all sites, with a mean SUS score of 86.1 across all sites. Furthermore, the SUS results indicated that, out of the 151 users who completed the SUS survey, 145 (96%) found that they learned how to use PointCheck very quickly, and 141 (93.4%) felt very confident when using the device. Conclusions: We have shown that PointCheck, a novel technology for noninvasive, home-based neutropenia detection, can be safely and effectively operated by first-time users. In a simulated home environment, these users found it easy to use, with a mean SUS score of 86.1, indicating an excellent perception of usability and placing this device within the top tenth percentile of systems evaluated for usability by the SUS. Trial Registration: ClinicalTrials.gov NCT04448314; https://clinicaltrials.gov/ct2/show/NCT04448314 (Hospital Universitario 12 de Octubre registration) and NCT04448301; https://clinicaltrials.gov/ct2/show/NCT04448301 (Boston Medical Center registration) UR - https://www.jmir.org/2022/8/e37368 UR - http://dx.doi.org/10.2196/37368 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943786 ID - info:doi/10.2196/37368 ER - TY - JOUR AU - Stoffel, T. Sandro AU - Law, Hui Jing AU - Kerrison, Robert AU - Brewer, R. Hannah AU - Flanagan, M. James AU - Hirst, Yasemin PY - 2022/8/26 TI - Testing the Effectiveness of an Animated Decision Aid to Improve Recruitment of Control Participants in a Case-Control Study: Web-Based Experiment JO - J Med Internet Res SP - e40015 VL - 24 IS - 8 KW - animation KW - research participation KW - online experiment KW - case-control KW - recruitment KW - decision KW - effectiveness KW - epidemiology KW - online KW - experiment KW - volunteer KW - survey KW - willingness KW - data KW - health research KW - research N2 - Background: Participation in case-control studies is crucial in epidemiological research. The self-sampling bias, low response rate, and poor recruitment of population representative controls are often reported as limitations of case-control studies with limited strategies to improve participation. With greater use of web-based methods in health research, there is a further need to understand the effectiveness of different tools to enhance informed decision-making and willingness to take part in research. Objective: This study tests whether the inclusion of an animated decision aid in the recruitment page of a study website can increase participants? intentions to volunteer as controls. Methods: A total of 1425 women were included in a web-based experiment and randomized to one of two experimental conditions: one in which they were exposed to a simulated website that included the animation (animation; n=693, 48.6%), and one in which they were exposed to the simulated website without the animation (control; n=732, 51.4%). The simulated website was adapted from a real website for a case-control study, which invites people to consider taking part in a study that investigates differences in purchasing behaviors between women with and without ovarian cancer and share their loyalty card data collected through 2 high street retailers with the researchers. After exposure to the experimental manipulation, participants were asked to state (1) their intention to take part in the case-control study, (2) whether they would be willing to share their loyalty card for research, and (3) their willingness to be redirected to the real website after completing the survey. Data were assessed using ordinal and binary logistic regression, reported in percentages (%), adjusted odds ratio (AOR), and 95% confidence intervals. Results: Including the animation in the simulated website did not increase intentions to participate in the study (AOR 1.09; 95% CI 0.88-1.35) or willingness to visit the real study website after the survey (control 50.5% vs animation 52.6%, AOR 1.08; 95% CI 0.85-1.37). The animation, however, increased the participants? intentions to share the data from their loyalty cards for research in general (control 17.9% vs animation 26%; AOR 1.64; 95% CI 1.23-2.18). Conclusions: While the results of this study indicate that the animated decision aid did not lead to greater intention to take part in our web-based case-control study, they show that they can be effective in increasing people?s willingness to share sensitive data for health research. UR - https://www.jmir.org/2022/8/e40015 UR - http://dx.doi.org/10.2196/40015 UR - http://www.ncbi.nlm.nih.gov/pubmed/36018628 ID - info:doi/10.2196/40015 ER - TY - JOUR AU - Ma, Ming AU - Yin, Saifu AU - Zhu, Mengli AU - Fan, Yu AU - Wen, Xi AU - Lin, Tao AU - Song, Turun PY - 2022/8/9 TI - Evaluation of Medical Information on Male Sexual Dysfunction on Baidu Encyclopedia and Wikipedia: Comparative Study JO - J Med Internet Res SP - e37339 VL - 24 IS - 8 KW - sexual dysfunction KW - digital health KW - Baidu Encyclopedia KW - Wikipedia KW - internet KW - health information KW - DISCERN instrument N2 - Background: Sexual dysfunction is a private set of disorders that may cause stigma for patients when discussing their private problems with doctors. They might also feel reluctant to initiate a face-to-face consultation. Internet searches are gradually becoming the first choice for people with sexual dysfunction to obtain health information. Globally, Wikipedia is the most popular and consulted validated encyclopedia website in the English-speaking world. Baidu Encyclopedia is becoming the dominant source in Chinese-speaking regions; however, the objectivity and readability of the content are yet to be evaluated. Objective: Hence, we aimed to evaluate the reliability, readability, and objectivity of male sexual dysfunction content on Wikipedia and Baidu Encyclopedia. Methods: The Chinese Baidu Encyclopedia and English Wikipedia were investigated. All possible synonymous and derivative keywords for the most common male sexual dysfunction, erectile dysfunction, premature ejaculation, and their most common complication, chronic prostatitis/chronic pelvic pain syndrome, were screened. Two doctors evaluated the articles on Chinese Baidu Encyclopedia and English Wikipedia. The Journal of the American Medical Association (JAMA) scoring system, DISCERN instrument, and Global Quality Score (GQS) were used to assess the quality of disease-related articles. Results: The total DISCERN scores (P=.002) and JAMA scores (P=.001) for Wikipedia were significantly higher than those of Baidu Encyclopedia; there was no statistical difference between the GQS scores (P=.31) for these websites. Specifically, the DISCERN Section 1 score (P<.001) for Wikipedia was significantly higher than that of Baidu Encyclopedia, while the differences between the DISCERN Section 2 and 3 scores (P=.14 and P=.17, respectively) were minor. Furthermore, Wikipedia had a higher proportion of high total DISCERN scores (P<.001) and DISCERN Section 1 scores (P<.001) than Baidu Encyclopedia. Baidu Encyclopedia and Wikipedia both had low DISCERN Section 2 and 3 scores (P=.49 and P=.99, respectively), and most of these scores were low quality. Conclusions: Wikipedia provides more reliable, higher quality, and more objective information than Baidu Encyclopedia. Yet, there are opportunities for both platforms to vastly improve their content quality. Moreover, both sites had similar poor quality content on treatment options. Joint efforts of physicians, physician associations, medical institutions, and internet platforms are needed to provide reliable, readable, and objective knowledge about diseases. UR - https://www.jmir.org/2022/8/e37339 UR - http://dx.doi.org/10.2196/37339 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943768 ID - info:doi/10.2196/37339 ER - TY - JOUR AU - Köngeter, Anja AU - Schickhardt, Christoph AU - Jungkunz, Martin AU - Bergbold, Susanne AU - Mehlis, Katja AU - Winkler, C. Eva PY - 2022/8/25 TI - Patients? Willingness to Provide Their Clinical Data for Research Purposes and Acceptance of Different Consent Models: Findings From a Representative Survey of Patients With Cancer JO - J Med Internet Res SP - e37665 VL - 24 IS - 8 KW - secondary use KW - consent KW - data sharing KW - data access KW - research benefit and control of data KW - health data KW - clinical data KW - private sector KW - international data sharing KW - patient perspective N2 - Background: Secondary use of clinical data for biomedical research purposes holds great potential for various types of noninterventional, data-driven studies. Patients? willingness to support research with their clinical data is a crucial prerequisite for research progress. Objective: The aim of the study was to learn about patients? attitudes and expectations regarding secondary use of their clinical data. In a next step, our results can inform the development of an appropriate governance framework for secondary use of clinical data for research purposes. Methods: A questionnaire was developed to assess the willingness of patients with cancer to provide their clinical data for biomedical research purposes, considering different conditions of data sharing and consent models. The Cancer Registry of the German federal state of Baden-Württemberg recruited a proportionally stratified random sample of patients with cancer and survivors of cancer based on a full census. Results: In total, 838 participants completed the survey. Approximately all participants (810/838, 96.7%) showed general willingness to make clinical data available for biomedical research purposes; however, they expected certain requirements to be met, such as comparable data protection standards for data use abroad and the possibility to renew consent at regular time intervals. Most participants (620/838, 73.9%) supported data use also by researchers in commercial companies. More than half of the participants (503/838, 60%) were willing to give up control over clinical data in favor of research benefits. Most participants expressed acceptance of the broad consent model (494/838, 58.9%), followed by data use by default (with the option to opt out at any time; 419/838, 50%); specific consent for every study showed the lowest acceptance rate (327/838, 39%). Patients expected physicians to share their data (763/838, 91.1%) and their fellow patients to support secondary use with their clinical data (679/838, 81%). Conclusions: Although patients? general willingness to make their clinical data available for biomedical research purposes is very high, the willingness of a substantial proportion of patients depends on additional requirements. Taking these perspectives into account is essential for designing trustworthy governance of clinical data reuse and sharing. The willingness to accept the loss of control over clinical data to enhance the benefits of research should be given special consideration. UR - https://www.jmir.org/2022/8/e37665 UR - http://dx.doi.org/10.2196/37665 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006690 ID - info:doi/10.2196/37665 ER - TY - JOUR AU - Kaur, Manpreet AU - Costello, Jeremy AU - Willis, Elyse AU - Kelm, Karen AU - Reformat, Z. Marek AU - Bolduc, V. Francois PY - 2022/8/5 TI - Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing JO - J Med Internet Res SP - e39888 VL - 24 IS - 8 KW - concept map KW - neurodevelopmental disorder KW - knowledge graph KW - text analysis KW - semantic relatedness KW - PubMed KW - forums KW - mental model N2 - Background: Understanding how individuals think about a topic, known as the mental model, can significantly improve communication, especially in the medical domain where emotions and implications are high. Neurodevelopmental disorders (NDDs) represent a group of diagnoses, affecting up to 18% of the global population, involving differences in the development of cognitive or social functions. In this study, we focus on 2 NDDs, attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), which involve multiple symptoms and interventions requiring interactions between 2 important stakeholders: parents and health professionals. There is a gap in our understanding of differences between mental models for each stakeholder, making communication between stakeholders more difficult than it could be. Objective: We aim to build knowledge graphs (KGs) from web-based information relevant to each stakeholder as proxies of mental models. These KGs will accelerate the identification of shared and divergent concerns between stakeholders. The developed KGs can help improve knowledge mobilization, communication, and care for individuals with ADHD and ASD. Methods: We created 2 data sets by collecting the posts from web-based forums and PubMed abstracts related to ADHD and ASD. We utilized the Unified Medical Language System (UMLS) to detect biomedical concepts and applied Positive Pointwise Mutual Information followed by truncated Singular Value Decomposition to obtain corpus-based concept embeddings for each data set. Each data set is represented as a KG using a property graph model. Semantic relatedness between concepts is calculated to rank the relation strength of concepts and stored in the KG as relation weights. UMLS disorder-relevant semantic types are used to provide additional categorical information about each concept?s domain. Results: The developed KGs contain concepts from both data sets, with node sizes representing the co-occurrence frequency of concepts and edge sizes representing relevance between concepts. ADHD- and ASD-related concepts from different semantic types shows diverse areas of concerns and complex needs of the conditions. KG identifies converging and diverging concepts between health professionals literature (PubMed) and parental concerns (web-based forums), which may correspond to the differences between mental models for each stakeholder. Conclusions: We show for the first time that generating KGs from web-based data can capture the complex needs of families dealing with ADHD or ASD. Moreover, we showed points of convergence between families and health professionals? KGs. Natural language processing?based KG provides access to a large sample size, which is often a limiting factor for traditional in-person mental model mapping. Our work offers a high throughput access to mental model maps, which could be used for further in-person validation, knowledge mobilization projects, and basis for communication about potential blind spots from stakeholders in interactions about NDDs. Future research will be needed to identify how concepts could interact together differently for each stakeholder. UR - https://www.jmir.org/2022/8/e39888 UR - http://dx.doi.org/10.2196/39888 UR - http://www.ncbi.nlm.nih.gov/pubmed/35930346 ID - info:doi/10.2196/39888 ER - TY - JOUR AU - Park, Ta Van AU - Tsoh, Y. Janice AU - Dougan, Marcelle AU - Nam, Bora AU - Tzuang, Marian AU - Park, G. Linda AU - Vuong, N. Quyen AU - Bang, Joon AU - Meyer, L. Oanh PY - 2022/8/9 TI - Racial Bias Beliefs Related to COVID-19 Among Asian Americans, Native Hawaiians, and Pacific Islanders: Findings From the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS) JO - J Med Internet Res SP - e38443 VL - 24 IS - 8 KW - COVID-19 KW - racial bias KW - Asian American KW - Native Hawaiian and Pacific Islander KW - mobile phone N2 - Background: During the COVID-19 pandemic, there have been increased reports of racial biases against Asian American and Native Hawaiian and Pacific Islander individuals. However, the extent to which different Asian American and Native Hawaiian and Pacific Islander groups perceive and experience (firsthand or as a witness to such experiences) how COVID-19 has negatively affected people of their race has not received much attention. Objective: This study used data from the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS), a nationwide, multilingual survey, to empirically examine COVID-19?related racial bias beliefs among Asian American and Native Hawaiian and Pacific Islander individuals and the factors associated with these beliefs. Methods: COMPASS participants were Asian American and Native Hawaiian and Pacific Islander adults who were able to speak English, Chinese (Cantonese or Mandarin), Korean, Samoan, or Vietnamese and who resided in the United States during the time of the survey (October 2020 to May 2021). Participants completed the survey on the web, via phone, or in person. The Coronavirus Racial Bias Scale (CRBS) was used to assess COVID-19?related racial bias beliefs toward Asian American and Native Hawaiian and Pacific Islander individuals. Participants were asked to rate the degree to which they agreed with 9 statements on a 5-point Likert scale (ie, 1=strongly disagree to 5=strongly agree). Multivariable linear regression was used to examine the associations between demographic, health, and COVID-19?related characteristics and perceived racial bias. Results: A total of 5068 participants completed the survey (mean age 45.4, SD 16.4 years; range 18-97 years). Overall, 73.97% (3749/5068) agreed or strongly agreed with ?1 COVID-19?related racial bias belief in the past 6 months (during the COVID-19 pandemic). Across the 9 racial bias beliefs, participants scored an average of 2.59 (SD 0.96, range 1-5). Adjusted analyses revealed that compared with Asian Indians, those who were ethnic Chinese, Filipino, Hmong, Japanese, Korean, Vietnamese, and other or multicultural had significantly higher mean CRBS scores, whereas no significant differences were found among Native Hawaiian and Pacific Islander individuals. Nonheterosexual participants had statistically significant and higher mean CRBS scores than heterosexual participants. Compared with participants aged ?60 years, those who were younger (aged <30, 30-39, 40-49, and 50-59 years) had significantly higher mean CRBS scores. US-born participants had significantly higher mean CRBS scores than foreign-born participants, whereas those with limited English proficiency (relative to those reporting no limitation) had lower mean CRBS scores. Conclusions: Many COMPASS participants reported racial bias beliefs because of the COVID-19 pandemic. Relevant sociodemographic contexts and pre-existing and COVID-19?specific factors across individual, community, and society levels were associated with the perceived racial bias of being Asian during the pandemic. The findings underscore the importance of addressing the burden of racial bias on Asian American and Native Hawaiian and Pacific Islander communities among other COVID-19?related sequelae. UR - https://www.jmir.org/2022/8/e38443 UR - http://dx.doi.org/10.2196/38443 UR - http://www.ncbi.nlm.nih.gov/pubmed/35658091 ID - info:doi/10.2196/38443 ER - TY - JOUR AU - Vargas-Herrera, Javier AU - Meneses, Giovanni AU - Cortez-Escalante, Juan PY - 2022/8/15 TI - Physicians? Perceptions as Predictors of the Future Use of the National Death Information System in Peru: Cross-sectional Study JO - J Med Internet Res SP - e34858 VL - 24 IS - 8 KW - death certificates KW - health information system KW - mortality KW - vital statistics KW - Technology Acceptance Model KW - model KW - acceptance model KW - certificates KW - information system KW - physicians KW - predictors KW - cross-sectional study KW - analysis KW - death N2 - Background: A computer application called the National Death Information System (SINADEF) was implemented in Peru so that physicians can prepare death certificates in electronic format and the information is available online. In 2018, only half of the estimated deaths in Peru were certified using SINADEF. When a death is certified in paper format, the probability being entered in the mortality database decreases. It is important to know, from the user?s perspective, the factors that can influence the successful implementation of SINADEF. SINADEF can only be successfully implemented if it is known whether physicians believe that it is useful and easy to operate. Objective: The aim of this study was to identify the perceptions of physicians and other factors as predictors of their behavioral intention to use SINADEF to certify a death. Methods: This study had an observational, cross-sectional design. A survey was provided to physicians working in Peru, who used SINADEF to certify a death for a period of 12 months, starting in November 2019. A questionnaire was adapted based on the Technology Acceptance Model. The questions measured the dimensions of subjective norm, image, job relevance, output quality, demonstrability of results, perceived usefulness, perceived ease of use, and behavioral intention to use. Chi-square and logistic regression tests were used in the analysis, and a confidence level of 95% was chosen to support a significant association. Results: In this study, 272 physicians responded to the survey; 184 (67.6%) were men and the average age was 45.3 (SD 10.1) years. The age range was 24 to 73 years. In the bivariate analysis, the intention to use SINADEF was found to be associated with (1) perceived usefulness, expressed as ?using SINADEF avoids falsifying a death certificate? (P<.001), ?using SINADEF reduces the risk of errors? (P<.001), and ?using SINADEF allows for filling out a certificate in less time? (P<.001); and (2) perceived ease of use, expressed as ?I think SINADEF is easy to use? (P<.001). In the logistic regression, perceived usefulness (odds ratio [OR] 8.5, 95% CI 2.2-32.3; P=.002), perceived ease of use (OR 10.1, 95% CI 2.4-41.8; P=.001), and training in filling out death certificates (OR 8.3, 95% CI 1.6-42.8; P=.01) were found to be predictors of the behavioral intention to use SINADEF. Conclusions: The behavioral intention to use SINADEF was related to the perception that it is an easy-to-use system, the belief that it improves the performance of physicians in carrying out the task at hand, and with training in filling out death certificates. UR - https://www.jmir.org/2022/8/e34858 UR - http://dx.doi.org/10.2196/34858 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969435 ID - info:doi/10.2196/34858 ER - TY - JOUR AU - Xu, Xianglong AU - Yu, Zhen AU - Ge, Zongyuan AU - Chow, F. Eric P. AU - Bao, Yining AU - Ong, J. Jason AU - Li, Wei AU - Wu, Jinrong AU - Fairley, K. Christopher AU - Zhang, Lei PY - 2022/8/25 TI - Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study JO - J Med Internet Res SP - e37850 VL - 24 IS - 8 KW - HIV KW - sexually transmitted infections KW - syphilis KW - gonorrhea KW - chlamydia KW - sexual health KW - sexual transmission KW - sexually transmitted KW - prediction KW - web-based KW - risk assessment KW - machine learning KW - model KW - algorithm KW - predictive KW - risk KW - development KW - validation N2 - Background: HIV and sexually transmitted infections (STIs) are major global public health concerns. Over 1 million curable STIs occur every day among people aged 15 years to 49 years worldwide. Insufficient testing or screening substantially impedes the elimination of HIV and STI transmission. Objective: The aim of our study was to develop an HIV and STI risk prediction tool using machine learning algorithms. Methods: We used clinic consultations that tested for HIV and STIs at the Melbourne Sexual Health Centre between March 2, 2015, and December 31, 2018, as the development data set (training and testing data set). We also used 2 external validation data sets, including data from 2019 as external ?validation data 1? and data from January 2020 and January 2021 as external ?validation data 2.? We developed 34 machine learning models to assess the risk of acquiring HIV, syphilis, gonorrhea, and chlamydia. We created an online tool to generate an individual?s risk of HIV or an STI. Results: The important predictors for HIV and STI risk were gender, age, men who reported having sex with men, number of casual sexual partners, and condom use. Our machine learning?based risk prediction tool, named MySTIRisk, performed at an acceptable or excellent level on testing data sets (area under the curve [AUC] for HIV=0.78; AUC for syphilis=0.84; AUC for gonorrhea=0.78; AUC for chlamydia=0.70) and had stable performance on both external validation data from 2019 (AUC for HIV=0.79; AUC for syphilis=0.85; AUC for gonorrhea=0.81; AUC for chlamydia=0.69) and data from 2020-2021 (AUC for HIV=0.71; AUC for syphilis=0.84; AUC for gonorrhea=0.79; AUC for chlamydia=0.69). Conclusions: Our web-based risk prediction tool could accurately predict the risk of HIV and STIs for clinic attendees using simple self-reported questions. MySTIRisk could serve as an HIV and STI screening tool on clinic websites or digital health platforms to encourage individuals at risk of HIV or an STI to be tested or start HIV pre-exposure prophylaxis. The public can use this tool to assess their risk and then decide if they would attend a clinic for testing. Clinicians or public health workers can use this tool to identify high-risk individuals for further interventions. UR - https://www.jmir.org/2022/8/e37850 UR - http://dx.doi.org/10.2196/37850 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006685 ID - info:doi/10.2196/37850 ER - TY - JOUR AU - Jewer, Jennifer PY - 2022/8/25 TI - Investigating a Work System Approach to Implement an Emergency Department Surge Management System: Case Study JO - J Med Internet Res SP - e37472 VL - 24 IS - 8 KW - emergency department KW - surge management KW - work system KW - system implementation KW - emergency department information system KW - mobile phone N2 - Background: Emergency department (ED) crowding is a global health care issue. eHealth systems have the potential to reduce crowding; however, the true benefits are seldom realized because the systems are not integrated into clinicians? work. We sought a deep understanding of how an eHealth system implementation can be structured to truly integrate the system into the workflow. Objective: The specific objectives of this study were to examine whether work system theory (WST) is a good approach to structure the implementation of an eHealth system by incorporating the entire work system, and not just the eHealth system, in the implementation framework; identify the role that specific elements of WST?s static framework and dynamic work system life cycle model play in the implementation; and demonstrate how WST can be applied in the health care setting to guide the implementation of an eHealth system. Methods: Through a case study of an ED in a rural hospital, we used a mixed methods approach to examine the implementation of a surge management system through the lens of WST. We conducted 14 hours of observation in the ED; 20 interviews with clinicians, management, and members of the implementation team; and a survey of 23 clinicians; reviewed related documentation; and analyzed ED data to measure wait times. We used template analysis based on WST to structure our analysis of qualitative data and descriptive statistics for quantitative data. Results: The surge management system helped to reduce crowding in the ED, staff was satisfied with the implementation, and wait time improvements have been maintained for several years. Although study participants indicated changes to their workflow, 72% (13/18) of survey participants were satisfied with their use of the system, and 82% (14/17) indicated that it was integrated with their workflow. Examining the implementation through the lens of WST enabled us to identify the aspects of the implementation that made it so successful. By applying the WST static framework, we saw how the implementation team incorporated the elements of the ED work system, assessed their alignment, and designed interventions to address areas of misalignment. The dynamic work system life cycle model captured how planned and unplanned changes were managed throughout the iterative implementation cycle?83% (15/18) of participants indicated that there was sufficient management support for the changes and 80% (16/20) indicated the change served an important purpose. Conclusions: The broad scope and holistic approach of WST is well suited to guide eHealth system implementations as it focuses efforts on the entire work system and not just the IT artifact. We broaden the focus of WST by applying it to the implementation of an ED surge management system. These findings will guide further studies and implementations of eHealth systems using WST. UR - https://www.jmir.org/2022/8/e37472 UR - http://dx.doi.org/10.2196/37472 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006684 ID - info:doi/10.2196/37472 ER - TY - JOUR AU - Moshe, Isaac AU - Terhorst, Yannik AU - Paganini, Sarah AU - Schlicker, Sandra AU - Pulkki-Råback, Laura AU - Baumeister, Harald AU - Sander, B. Lasse AU - Ebert, Daniel David PY - 2022/8/30 TI - 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 JO - J Med Internet Res SP - e38261 VL - 24 IS - 8 KW - adherence KW - dropout KW - law of attrition KW - attrition KW - digital health KW - internet intervention KW - depression KW - back pain KW - comorbidity KW - mental health KW - eHealth KW - mobile phone N2 - 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. UR - https://www.jmir.org/2022/8/e38261 UR - http://dx.doi.org/10.2196/38261 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040780 ID - info:doi/10.2196/38261 ER - TY - JOUR AU - Lalloo, Chitra AU - Nishat, Fareha AU - Zempsky, William AU - Bakshi, Nitya AU - Badawy, Sherif AU - Ko, Joo Yeon AU - Dampier, Carlton AU - Stinson, Jennifer AU - Palermo, M. Tonya PY - 2022/8/30 TI - 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 JO - J Med Internet Res SP - e40096 VL - 24 IS - 8 KW - engagement KW - adolescents KW - caregivers KW - sickle cell KW - pain KW - mHealth KW - self-management KW - digital health analytics KW - mixed methods KW - youth KW - management KW - disease KW - acute pain KW - chronic pain KW - coping KW - North America KW - intervention KW - child KW - digital health KW - program N2 - 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 (?21=6.6; P=.01; ?=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 UR - https://www.jmir.org/2022/8/e40096 UR - http://dx.doi.org/10.2196/40096 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040789 ID - info:doi/10.2196/40096 ER - TY - JOUR AU - Saukkonen, Petra AU - Elovainio, Marko AU - Virtanen, Lotta AU - Kaihlanen, Anu-Marja AU - Nadav, Janna AU - Lääveri, Tinja AU - Vänskä, Jukka AU - Viitanen, Johanna AU - Reponen, Jarmo AU - Heponiemi, Tarja PY - 2022/8/17 TI - The Interplay of Work, Digital Health Usage, and the Perceived Effects of Digitalization on Physicians? Work: Network Analysis Approach JO - J Med Internet Res SP - e38714 VL - 24 IS - 8 KW - network analysis KW - mixed graphical model KW - physicians KW - health care digitalization KW - digitalization of work KW - work in transformation KW - digital health N2 - Background: In health care, the benefits of digitalization need to outweigh the risks, but there is limited knowledge about the factors affecting this balance in the work environment of physicians. To achieve the benefits of digitalization, a more comprehensive understanding of this complex phenomenon related to the digitalization of physicians? work is needed. Objective: The aim of this study was to examine physicians? perceptions of the effects of health care digitalization on their work and to analyze how these perceptions are associated with multiple factors related to work and digital health usage. Methods: A representative sample of 4630 (response rate 24.46%) Finnish physicians (2960/4617, 64.11% women) was used. Statements measuring the perceived effects of digitalization on work included the patients? active role, preventive work, interprofessional cooperation, decision support, access to patient information, and faster consultations. Network analysis of the perceived effects of digitalization and factors related to work and digital health usage was conducted using mixed graphical modeling. Adjusted and standardized regression coefficients are denoted by b. Centrality statistics were examined to evaluate the relative influence of each variable in terms of node strength. Results: Nearly half of physicians considered that digitalization has promoted an active role for patients in their own care (2104/4537, 46.37%) and easier access to patient information (1986/4551, 43.64%), but only 1 in 10 (445/4529, 9.82%) felt that the impact has been positive on consultation times with patients. Almost half of the respondents estimated that digitalization has neither increased nor decreased the possibilities for preventive work (2036/4506, 45.18%) and supportiveness of clinical decision support systems (1941/4458, 43.54%). When all variables were integrated into the network, the most influential variables were purpose of using health information systems, employment sector, and specialization status. However, the grade given to the electronic health record (EHR) system that was primarily used had the strongest direct links to faster consultations (b=0.32) and facilitated access to patient information (b=0.28). At least 6 months of use of the main EHR was associated with facilitated access to patient information (b=0.18). Conclusions: The results highlight the complex interdependence of multiple factors associated with the perceived effects of digitalization on physicians? work. It seems that a high-quality EHR system is critical for promoting smooth clinical practice. In addition, work-related factors may influence other factors that affect digital health success. These factors should be considered when developing and implementing new digital health technologies or services for physicians? work. The adoption of digital health is not just a technological project but a project that changes existing work practices. UR - https://www.jmir.org/2022/8/e38714 UR - http://dx.doi.org/10.2196/38714 UR - http://www.ncbi.nlm.nih.gov/pubmed/35976692 ID - info:doi/10.2196/38714 ER - TY - JOUR AU - Noori, Ayush AU - Magdamo, Colin AU - Liu, Xiao AU - Tyagi, Tanish AU - Li, Zhaozhi AU - Kondepudi, Akhil AU - Alabsi, Haitham AU - Rudmann, Emily AU - Wilcox, Douglas AU - Brenner, Laura AU - Robbins, K. Gregory AU - Moura, Lidia AU - Zafar, Sahar AU - Benson, M. Nicole AU - Hsu, John AU - R Dickson, John AU - Serrano-Pozo, Alberto AU - Hyman, T. Bradley AU - Blacker, Deborah AU - Westover, Brandon M. AU - Mukerji, S. Shibani AU - Das, Sudeshna PY - 2022/8/30 TI - Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study JO - J Med Internet Res SP - e40384 VL - 24 IS - 8 KW - chart review KW - cognition KW - cognitive status KW - dementia KW - diagnostic KW - electronic health record KW - health care KW - natural language processing KW - research cohort N2 - Background: Electronic health records (EHRs) with large sample sizes and rich information offer great potential for dementia research, but current methods of phenotyping cognitive status are not scalable. Objective: The aim of this study was to evaluate whether natural language processing (NLP)?powered semiautomated annotation can improve the speed and interrater reliability of chart reviews for phenotyping cognitive status. Methods: In this diagnostic study, we developed and evaluated a semiautomated NLP-powered annotation tool (NAT) to facilitate phenotyping of cognitive status. Clinical experts adjudicated the cognitive status of 627 patients at Mass General Brigham (MGB) health care, using NAT or traditional chart reviews. Patient charts contained EHR data from two data sets: (1) records from January 1, 2017, to December 31, 2018, for 100 Medicare beneficiaries from the MGB Accountable Care Organization and (2) records from 2 years prior to COVID-19 diagnosis to the date of COVID-19 diagnosis for 527 MGB patients. All EHR data from the relevant period were extracted; diagnosis codes, medications, and laboratory test values were processed and summarized; clinical notes were processed through an NLP pipeline; and a web tool was developed to present an integrated view of all data. Cognitive status was rated as cognitively normal, cognitively impaired, or undetermined. Assessment time and interrater agreement of NAT compared to manual chart reviews for cognitive status phenotyping was evaluated. Results: NAT adjudication provided higher interrater agreement (Cohen ?=0.89 vs ?=0.80) and significant speed up (time difference mean 1.4, SD 1.3 minutes; P<.001; ratio median 2.2, min-max 0.4-20) over manual chart reviews. There was moderate agreement with manual chart reviews (Cohen ?=0.67). In the cases that exhibited disagreement with manual chart reviews, NAT adjudication was able to produce assessments that had broader clinical consensus due to its integrated view of highlighted relevant information and semiautomated NLP features. Conclusions: NAT adjudication improves the speed and interrater reliability for phenotyping cognitive status compared to manual chart reviews. This study underscores the potential of an NLP-based clinically adjudicated method to build large-scale dementia research cohorts from EHRs. UR - https://www.jmir.org/2022/8/e40384 UR - http://dx.doi.org/10.2196/40384 UR - http://www.ncbi.nlm.nih.gov/pubmed/36040790 ID - info:doi/10.2196/40384 ER - TY - JOUR AU - Powell-Wiley, M. Tiffany AU - Martinez, F. Marie AU - Tamura, Kosuke AU - Neally, J. Sam AU - O'Shea, J. Kelly AU - Curlin, Kaveri AU - Albarracin, Yardley AU - Vijayakumar, P. Nithya AU - Morgan, Matthew AU - Ortiz-Chaparro, Erika AU - Bartsch, M. Sarah AU - Osei Baah, Foster AU - Wedlock, T. Patrick AU - Ortiz-Whittingham, R. Lola AU - Scannell, Sheryl AU - Potharaju, A. Kameswari AU - Randall, Samuel AU - Solano Gonzales, Mario AU - Domino, Molly AU - Ranganath, Kushi AU - Hertenstein, Daniel AU - Syed, Rafay AU - Weatherwax, Colleen AU - Lee, Y. Bruce PY - 2022/8/22 TI - The Impact of a Place-Tailored Digital Health App Promoting Exercise Classes on African American Women?s Physical Activity and Obesity: Simulation Study JO - J Med Internet Res SP - e30581 VL - 24 IS - 8 KW - computational modeling KW - digital health KW - physical activity KW - BMI KW - obesity KW - built environment KW - impact KW - app KW - exercise KW - simulation KW - intervention KW - women KW - African American KW - agent N2 - Background: The increasing prevalence of smartphone apps to help people find different services raises the question of whether apps to help people find physical activity (PA) locations would help better prevent and control having overweight or obesity. Objective: The aim of this paper is to determine and quantify the potential impact of a digital health intervention for African American women prior to allocating financial resources toward implementation. Methods: We developed our Virtual Population Obesity Prevention, agent-based model of Washington, DC, to simulate the impact of a place-tailored digital health app that provides information about free recreation center classes on PA, BMI, and overweight and obesity prevalence among African American women. Results: When the app is introduced at the beginning of the simulation, with app engagement at 25% (eg, 25% [41,839/167,356] of women aware of the app; 25% [10,460/41,839] of those aware downloading the app; and 25% [2615/10,460] of those who download it receiving regular push notifications), and a 25% (25/100) baseline probability to exercise (eg, without the app), there are no statistically significant increases in PA levels or decreases in BMI or obesity prevalence over 5 years across the population. When 50% (83,678/167,356) of women are aware of the app; 58.23% (48,725/83,678) of those who are aware download it; and 55% (26,799/48,725) of those who download it receive regular push notifications, in line with existing studies on app usage, introducing the app on average increases PA and decreases weight or obesity prevalence, though the changes are not statistically significant. When app engagement increased to 75% (125,517/167,356) of women who were aware, 75% (94,138/125,517) of those who were aware downloading it, and 75% (70,603/94,138) of those who downloaded it opting into the app?s push notifications, there were statistically significant changes in PA participation, minutes of PA and obesity prevalence. Conclusions: Our study shows that a digital health app that helps identify recreation center classes does not result in substantive population-wide health effects at lower levels of app engagement. For the app to result in statistically significant increases in PA and reductions in obesity prevalence over 5 years, there needs to be at least 75% (125,517/167,356) of women aware of the app, 75% (94,138/125,517) of those aware of the app download it, and 75% (70,603/94,138) of those who download it opt into push notifications. Nevertheless, the app cannot fully overcome lack of access to recreation centers; therefore, public health administrators as well as parks and recreation agencies might consider incorporating this type of technology into multilevel interventions that also target the built environment and other social determinants of health. UR - https://www.jmir.org/2022/8/e30581 UR - http://dx.doi.org/10.2196/30581 UR - http://www.ncbi.nlm.nih.gov/pubmed/35994313 ID - info:doi/10.2196/30581 ER - TY - JOUR AU - Yu, Fangzhou AU - Wu, Peixia AU - Deng, Haowen AU - Wu, Jingfang AU - Sun, Shan AU - Yu, Huiqian AU - Yang, Jianming AU - Luo, Xianyang AU - He, Jing AU - Ma, Xiulan AU - Wen, Junxiong AU - Qiu, Danhong AU - Nie, Guohui AU - Liu, Rizhao AU - Hu, Guohua AU - Chen, Tao AU - Zhang, Cheng AU - Li, Huawei PY - 2022/8/3 TI - A Questionnaire-Based Ensemble Learning Model to Predict the Diagnosis of Vertigo: Model Development and Validation Study JO - J Med Internet Res SP - e34126 VL - 24 IS - 8 KW - vestibular disorders KW - machine learning KW - diagnostic model KW - vertigo KW - ENT KW - questionnaire N2 - Background: Questionnaires have been used in the past 2 decades to predict the diagnosis of vertigo and assist clinical decision-making. A questionnaire-based machine learning model is expected to improve the efficiency of diagnosis of vestibular disorders. Objective: This study aims to develop and validate a questionnaire-based machine learning model that predicts the diagnosis of vertigo. Methods: In this multicenter prospective study, patients presenting with vertigo entered a consecutive cohort at their first visit to the ENT and vertigo clinics of 7 tertiary referral centers from August 2019 to March 2021, with a follow-up period of 2 months. All participants completed a diagnostic questionnaire after eligibility screening. Patients who received only 1 final diagnosis by their treating specialists for their primary complaint were included in model development and validation. The data of patients enrolled before February 1, 2021 were used for modeling and cross-validation, while patients enrolled afterward entered external validation. Results: A total of 1693 patients were enrolled, with a response rate of 96.2% (1693/1760). The median age was 51 (IQR 38-61) years, with 991 (58.5%) females; 1041 (61.5%) patients received the final diagnosis during the study period. Among them, 928 (54.8%) patients were included in model development and validation, and 113 (6.7%) patients who enrolled later were used as a test set for external validation. They were classified into 5 diagnostic categories. We compared 9 candidate machine learning methods, and the recalibrated model of light gradient boosting machine achieved the best performance, with an area under the curve of 0.937 (95% CI 0.917-0.962) in cross-validation and 0.954 (95% CI 0.944-0.967) in external validation. Conclusions: The questionnaire-based light gradient boosting machine was able to predict common vestibular disorders and assist decision-making in ENT and vertigo clinics. Further studies with a larger sample size and the participation of neurologists will help assess the generalization and robustness of this machine learning method. UR - https://www.jmir.org/2022/8/e34126 UR - http://dx.doi.org/10.2196/34126 UR - http://www.ncbi.nlm.nih.gov/pubmed/35921135 ID - info:doi/10.2196/34126 ER - TY - JOUR AU - Li, Jili AU - Liu, Siru AU - Hu, Yundi AU - Zhu, Lingfeng AU - Mao, Yujia AU - Liu, Jialin PY - 2022/8/9 TI - Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study JO - J Med Internet Res SP - e38082 VL - 24 IS - 8 KW - heart failure KW - mortality KW - intensive care unit KW - prediction KW - XGBoost KW - SHAP KW - SHapley Additive exPlanation N2 - Background: Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF mortality prediction models have not yet reached clinical practice. Objective: We aimed to develop an interpretable model to predict the mortality risk for patients with HF in intensive care units (ICUs) and used the SHapley Additive exPlanation (SHAP) method to explain the extreme gradient boosting (XGBoost) model and explore prognostic factors for HF. Methods: In this retrospective cohort study, we achieved model development and performance comparison on the eICU Collaborative Research Database (eICU-CRD). We extracted data during the first 24 hours of each ICU admission, and the data set was randomly divided, with 70% used for model training and 30% used for model validation. The prediction performance of the XGBoost model was compared with three other machine learning models by the area under the curve. We used the SHAP method to explain the XGBoost model. Results: A total of 2798 eligible patients with HF were included in the final cohort for this study. The observed in-hospital mortality of patients with HF was 9.97%. Comparatively, the XGBoost model had the highest predictive performance among four models with an area under the curve (AUC) of 0.824 (95% CI 0.7766-0.8708), whereas support vector machine had the poorest generalization ability (AUC=0.701, 95% CI 0.6433-0.7582). The decision curve showed that the net benefit of the XGBoost model surpassed those of other machine learning models at 10%~28% threshold probabilities. The SHAP method reveals the top 20 predictors of HF according to the importance ranking, and the average of the blood urea nitrogen was recognized as the most important predictor variable. Conclusions: The interpretable predictive model helps physicians more accurately predict the mortality risk in ICU patients with HF, and therefore, provides better treatment plans and optimal resource allocation for their patients. In addition, the interpretable framework can increase the transparency of the model and facilitate understanding the reliability of the predictive model for the physicians. UR - https://www.jmir.org/2022/8/e38082 UR - http://dx.doi.org/10.2196/38082 UR - http://www.ncbi.nlm.nih.gov/pubmed/35943767 ID - info:doi/10.2196/38082 ER - TY - JOUR AU - Isbanner, Sebastian AU - O?Shaughnessy, Pauline AU - Steel, David AU - Wilcock, Scarlet AU - Carter, Stacy PY - 2022/8/22 TI - The Adoption of Artificial Intelligence in Health Care and Social Services in Australia: Findings From a Methodologically Innovative National Survey of Values and Attitudes (the AVA-AI Study) JO - J Med Internet Res SP - e37611 VL - 24 IS - 8 KW - artificial intelligence KW - surveys and questionnaires KW - consumer health informatics KW - social welfare KW - bioethics KW - social values N2 - Background: Artificial intelligence (AI) for use in health care and social services is rapidly developing, but this has significant ethical, legal, and social implications. Theoretical and conceptual research in AI ethics needs to be complemented with empirical research to understand the values and judgments of members of the public, who will be the ultimate recipients of AI-enabled services. Objective: The aim of the Australian Values and Attitudes on AI (AVA-AI) study was to assess and compare Australians? general and particular judgments regarding the use of AI, compare Australians? judgments regarding different health care and social service applications of AI, and determine the attributes of health care and social service AI systems that Australians consider most important. Methods: We conducted a survey of the Australian population using an innovative sampling and weighting methodology involving 2 sample components: one from an omnibus survey using a sample selected using scientific probability sampling methods and one from a nonprobability-sampled web-based panel. The web-based panel sample was calibrated to the omnibus survey sample using behavioral, lifestyle, and sociodemographic variables. Univariate and bivariate analyses were performed. Results: We included weighted responses from 1950 Australians in the web-based panel along with a further 2498 responses from the omnibus survey for a subset of questions. Both weighted samples were sociodemographically well spread. An estimated 60% of Australians support the development of AI in general but, in specific health care scenarios, this diminishes to between 27% and 43% and, for social service scenarios, between 31% and 39%. Although all ethical and social dimensions of AI presented were rated as important, accuracy was consistently the most important and reducing costs the least important. Speed was also consistently lower in importance. In total, 4 in 5 Australians valued continued human contact and discretion in service provision more than any speed, accuracy, or convenience that AI systems might provide. Conclusions: The ethical and social dimensions of AI systems matter to Australians. Most think AI systems should augment rather than replace humans in the provision of both health care and social services. Although expressing broad support for AI, people made finely tuned judgments about the acceptability of particular AI applications with different potential benefits and downsides. Further qualitative research is needed to understand the reasons underpinning these judgments. The participation of ethicists, social scientists, and the public can help guide AI development and implementation, particularly in sensitive and value-laden domains such as health care and social services. UR - https://www.jmir.org/2022/8/e37611 UR - http://dx.doi.org/10.2196/37611 UR - http://www.ncbi.nlm.nih.gov/pubmed/35994331 ID - info:doi/10.2196/37611 ER - TY - JOUR AU - Partogi, Michelle AU - Gaviria-Valencia, Simon AU - Alzate Aguirre, Mateo AU - Pick, J. Nancy AU - Bhopalwala, M. Huzefa AU - Barry, A. Barbara AU - Kaggal, C. Vinod AU - Scott, G. Christopher AU - Kessler, E. Maya AU - Moore, M. Matthew AU - Mitchell, D. Jay AU - Chaudhry, Rajeev AU - Bonacci, P. Robert AU - Arruda-Olson, M. Adelaide PY - 2022/8/22 TI - Sociotechnical Intervention for Improved Delivery of Preventive Cardiovascular Care to Rural Communities: Participatory Design Approach JO - J Med Internet Res SP - e27333 VL - 24 IS - 8 KW - sociotechnical KW - secondary prevention KW - atherosclerotic cardiovascular diseases KW - community health KW - rural health KW - participatory design KW - team-based care N2 - Background: Clinical practice guidelines recommend antiplatelet and statin therapies as well as blood pressure control and tobacco cessation for secondary prevention in patients with established atherosclerotic cardiovascular diseases (ASCVDs). However, these strategies for risk modification are underused, especially in rural communities. Moreover, resources to support the delivery of preventive care to rural patients are fewer than those for their urban counterparts. Transformative interventions for the delivery of tailored preventive cardiovascular care to rural patients are needed. Objective: A multidisciplinary team developed a rural-specific, team-based model of care intervention assisted by clinical decision support (CDS) technology using participatory design in a sociotechnical conceptual framework. The model of care intervention included redesigned workflows and a novel CDS technology for the coordination and delivery of guideline recommendations by primary care teams in a rural clinic. Methods: The design of the model of care intervention comprised 3 phases: problem identification, experimentation, and testing. Input from team members (n=35) required 150 hours, including observations of clinical encounters, provider workshops, and interviews with patients and health care professionals. The intervention was prototyped, iteratively refined, and tested with user feedback. In a 3-month pilot trial, 369 patients with ASCVDs were randomized into the control or intervention arm. Results: New workflows and a novel CDS tool were created to identify patients with ASCVDs who had gaps in preventive care and assign the right care team member for delivery of tailored recommendations. During the pilot, the intervention prototype was iteratively refined and tested. The pilot demonstrated feasibility for successful implementation of the sociotechnical intervention as the proportion of patients who had encounters with advanced practice providers (nurse practitioners and physician assistants), pharmacists, or tobacco cessation coaches for the delivery of guideline recommendations in the intervention arm was greater than that in the control arm. Conclusions: Participatory design and a sociotechnical conceptual framework enabled the development of a rural-specific, team-based model of care intervention assisted by CDS technology for the transformation of preventive health care delivery for ASCVDs. UR - https://www.jmir.org/2022/8/e27333 UR - http://dx.doi.org/10.2196/27333 UR - http://www.ncbi.nlm.nih.gov/pubmed/35994324 ID - info:doi/10.2196/27333 ER - TY - JOUR AU - Singh, Lisa AU - Gresenz, Roan Carole AU - Wang, Yanchen AU - Hu, Sonya PY - 2022/8/25 TI - Assessing Social Media Data as a Resource for Firearm Research: Analysis of Tweets Pertaining to Firearm Deaths JO - J Med Internet Res SP - e38319 VL - 24 IS - 8 KW - firearms KW - fatalities KW - Twitter KW - firearm research KW - social media data N2 - Background: Historic constraints on research dollars and reliable information have limited firearm research. At the same time, interest in the power and potential of social media analytics, particularly in health contexts, has surged. Objective: The aim of this study is to contribute toward the goal of establishing a foundation for how social media data may best be used, alone or in conjunction with other data resources, to improve the information base for firearm research. Methods: We examined the value of social media data for estimating a firearm outcome for which robust benchmark data exist?specifically, firearm mortality, which is captured in the National Vital Statistics System (NVSS). We hand curated tweet data from the Twitter application programming interface spanning January 1, 2017, to December 31, 2018. We developed machine learning classifiers to identify tweets that pertain to firearm deaths and develop estimates of the volume of Twitter firearm discussion by month. We compared within-state variation over time in the volume of tweets pertaining to firearm deaths with within-state trends in NVSS-based estimates of firearm fatalities using Pearson linear correlations. Results: The correlation between the monthly number of firearm fatalities measured by the NVSS and the monthly volume of tweets pertaining to firearm deaths was weak (median 0.081) and highly dispersed across states (range ?0.31 to 0.535). The median correlation between month-to-month changes in firearm fatalities in the NVSS and firearm deaths discussed in tweets was moderate (median 0.30) and exhibited less dispersion among states (range ?0.06 to 0.69). Conclusions: Our findings suggest that Twitter data may hold value for tracking dynamics in firearm-related outcomes, particularly for relatively populous cities that are identifiable through location mentions in tweet content. The data are likely to be particularly valuable for understanding firearm outcomes not currently measured, not measured well, or not measurable through other available means. This research provides an important building block for future work that continues to develop the usefulness of social media data for firearm research. UR - https://www.jmir.org/2022/8/e38319 UR - http://dx.doi.org/10.2196/38319 UR - http://www.ncbi.nlm.nih.gov/pubmed/36006693 ID - info:doi/10.2196/38319 ER - TY - JOUR AU - van Steenbergen, Gijs AU - van Veghel, Dennis AU - van Lieshout, Dideke AU - Sperwer, Merel AU - ter Woorst, Joost AU - Dekker, Lukas PY - 2022/8/26 TI - Effects of Video-Based Patient Education and Consultation on Unplanned Health Care Utilization and Early Recovery After Coronary Artery Bypass Surgery (IMPROV-ED): Randomized Controlled Trial JO - J Med Internet Res SP - e37728 VL - 24 IS - 8 KW - e-Health KW - eHealth KW - digital health KW - patient education KW - coronary artery bypass surgery KW - cardiac surgery KW - health care utilization KW - costs KW - cost KW - economic KW - coronary KW - cardiology KW - heart KW - surgery KW - bypass KW - RCT KW - randomized controlled trial KW - video consultation KW - telehealth KW - telemedicine KW - patient-reported KW - recovery KW - expense N2 - Background: Health care utilization after coronary artery bypass graft (CABG) surgery is high and is partly of an unplanned nature. eHealth applications have been proposed to reduce care consumption, which involve and assist patients in their recovery. In this way, health care expenses could be reduced and quality of care could be improved. Objective: The aim of this study was to evaluate if an eHealth program can reduce unplanned health care utilization and improve mental and physical health in the first 6 weeks after CABG surgery. Methods: A single-blind randomized controlled trial was performed, in which patients scheduled for nonacute CABG surgery were included from a single center in the Netherlands between February 2020 and October 2021. Participants in the intervention group had, alongside standard care, access to an eHealth program consisting of online education videos and video consultations developed in conjunction with the Dutch Heart Foundation. The control group received standard care. The primary outcome was the volume and costs of a composite of unplanned health care utilization, including emergency department visits, outpatient clinic visits, rehospitalization, patient-initiated telephone consultations, and visits to a general practitioner, measured using the Medical Technology Assessment Medical Consumption Questionnaire. Patient-reported anxiety and recovery were also assessed. Intention-to-treat and ?users-only? analyses were used. Results: During the study period, 280 patients were enrolled and randomly allocated at a 1:1 ratio to the intervention or control group. The intention-to-treat analysis consisted of 136 and 135 patients in the intervention and control group, respectively. At 6 weeks, the primary endpoint had occurred in 43 of 136 (31.6%) patients in the intervention group and in 61 of 135 (45.2%) patients in the control group (hazard ratio 0.56, 95% CI 0.34-0.92). Recovery was faster in the intervention group, whereas anxiety was similar between study groups. ?Users-only? analysis yielded similar results. Conclusions: An eHealth strategy comprising educational videos and video consultations can reduce unplanned health care utilization and can aid in faster patient-reported recovery in patients following CABG surgery. Trial Registration: Netherlands Trial Registry NL8510; https://trialsearch.who.int/Trial2.aspx?TrialID=NL8510 International Registered Report Identifier (IRRID): RR2-10.1007/s12471-020-01508-9 UR - https://www.jmir.org/2022/8/e37728 UR - http://dx.doi.org/10.2196/37728 UR - http://www.ncbi.nlm.nih.gov/pubmed/36018625 ID - info:doi/10.2196/37728 ER - TY - JOUR AU - Arellano Carmona, Kimberly AU - Chittamuru, Deepti AU - Kravitz, L. Richard AU - Ramondt, Steven AU - Ramírez, Susana A. PY - 2022/8/19 TI - Health Information Seeking From an Intelligent Web-Based Symptom Checker: Cross-sectional Questionnaire Study JO - J Med Internet Res SP - e36322 VL - 24 IS - 8 KW - health information seeking KW - health information KW - information seeking KW - information seeker KW - information behavior KW - artificial intelligence KW - medical information system KW - digital divide KW - information inequality KW - digital epidemiology KW - symptom checker KW - digital health KW - eHealth KW - online health information KW - user demographic KW - health information resource KW - health information tool KW - digital health assistant N2 - Background: The ever-growing amount of health information available on the web is increasing the demand for tools providing personalized and actionable health information. Such tools include symptom checkers that provide users with a potential diagnosis after responding to a set of probes about their symptoms. Although the potential for their utility is great, little is known about such tools? actual use and effects. Objective: We aimed to understand who uses a web-based artificial intelligence?powered symptom checker and its purposes, how they evaluate the experience of the web-based interview and quality of the information, what they intend to do with the recommendation, and predictors of future use. Methods: Cross-sectional survey of web-based health information seekers following the completion of a symptom checker visit (N=2437). Measures of comprehensibility, confidence, usefulness, health-related anxiety, empowerment, and intention to use in the future were assessed. ANOVAs and the Wilcoxon rank sum test examined mean outcome differences in racial, ethnic, and sex groups. The relationship between perceptions of the symptom checker and intention to follow recommended actions was assessed using multilevel logistic regression. Results: Buoy users were well-educated (1384/1704, 81.22% college or higher), primarily White (1227/1693, 72.47%), and female (2069/2437, 84.89%). Most had insurance (1449/1630, 88.89%), a regular health care provider (1307/1709, 76.48%), and reported good health (1000/1703, 58.72%). Three types of symptoms?pain (855/2437, 35.08%), gynecological issues (293/2437, 12.02%), and masses or lumps (204/2437, 8.37%)?accounted for almost half (1352/2437, 55.48%) of site visits. Buoy?s top three primary recommendations split across less-serious triage categories: primary care physician in 2 weeks (754/2141, 35.22%), self-treatment (452/2141, 21.11%), and primary care in 1 to 2 days (373/2141, 17.42%). Common diagnoses were musculoskeletal (303/2437, 12.43%), gynecological (304/2437, 12.47%) and skin conditions (297/2437, 12.19%), and infectious diseases (300/2437, 12.31%). Users generally reported high confidence in Buoy, found it useful and easy to understand, and said that Buoy made them feel less anxious and more empowered to seek medical help. Users for whom Buoy recommended ?Waiting/Watching? or ?Self-Treatment? had strongest intentions to comply, whereas those advised to seek primary care had weaker intentions. Compared with White users, Latino and Black users had significantly more confidence in Buoy (P<.05), and the former also found it significantly more useful (P<.05). Latino (odds ratio 1.96, 95% CI 1.22-3.25) and Black (odds ratio 2.37, 95% CI 1.57-3.66) users also had stronger intentions to discuss recommendations with a provider than White users. Conclusions: Results demonstrate the potential utility of a web-based health information tool to empower people to seek care and reduce health-related anxiety. However, despite encouraging results suggesting the tool may fulfill unmet health information needs among women and Black and Latino adults, analyses of the user base illustrate persistent second-level digital divide effects. UR - https://www.jmir.org/2022/8/e36322 UR - http://dx.doi.org/10.2196/36322 UR - http://www.ncbi.nlm.nih.gov/pubmed/35984690 ID - info:doi/10.2196/36322 ER - TY - JOUR AU - Skafle, Ingjerd AU - Nordahl-Hansen, Anders AU - Quintana, S. Daniel AU - Wynn, Rolf AU - Gabarron, Elia PY - 2022/8/4 TI - Misinformation About COVID-19 Vaccines on Social Media: Rapid Review JO - J Med Internet Res SP - e37367 VL - 24 IS - 8 KW - social media KW - misinformation KW - COVID-19 vaccines KW - vaccination hesitancy KW - autism spectrum disorder N2 - Background: The development of COVID-19 vaccines has been crucial in fighting the pandemic. However, misinformation about the COVID-19 pandemic and vaccines is spread on social media platforms at a rate that has made the World Health Organization coin the phrase infodemic. False claims about adverse vaccine side effects, such as vaccines being the cause of autism, were already considered a threat to global health before the outbreak of COVID-19. Objective: We aimed to synthesize the existing research on misinformation about COVID-19 vaccines spread on social media platforms and its effects. The secondary aim was to gain insight and gather knowledge about whether misinformation about autism and COVID-19 vaccines is being spread on social media platforms. Methods: We performed a literature search on September 9, 2021, and searched PubMed, PsycINFO, ERIC, EMBASE, Cochrane Library, and the Cochrane COVID-19 Study Register. We included publications in peer-reviewed journals that fulfilled the following criteria: original empirical studies, studies that assessed social media and misinformation, and studies about COVID-19 vaccines. Thematic analysis was used to identify the patterns (themes) of misinformation. Narrative qualitative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 Statement and the Synthesis Without Meta-analysis reporting guideline. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tool. Ratings of the certainty of evidence were based on recommendations from the Grading of Recommendations Assessment, Development and Evaluation Working Group. Results: The search yielded 757 records, with 45 articles selected for this review. We identified 3 main themes of misinformation: medical misinformation, vaccine development, and conspiracies. Twitter was the most studied social media platform, followed by Facebook, YouTube, and Instagram. A vast majority of studies were from industrialized Western countries. We identified 19 studies in which the effect of social media misinformation on vaccine hesitancy was measured or discussed. These studies implied that the misinformation spread on social media had a negative effect on vaccine hesitancy and uptake. Only 1 study contained misinformation about autism as a side effect of COVID-19 vaccines. Conclusions: To prevent these misconceptions from taking hold, health authorities should openly address and discuss these false claims with both cultural and religious awareness in mind. Our review showed that there is a need to examine the effect of social media misinformation on vaccine hesitancy with a more robust experimental design. Furthermore, this review also demonstrated that more studies are needed from the Global South and on social media platforms other than the major platforms such as Twitter and Facebook. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021277524; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021277524 International Registered Report Identifier (IRRID): RR2-10.31219/osf.io/tyevj UR - https://www.jmir.org/2022/8/e37367 UR - http://dx.doi.org/10.2196/37367 UR - http://www.ncbi.nlm.nih.gov/pubmed/35816685 ID - info:doi/10.2196/37367 ER - TY - JOUR AU - Suarez-Lledo, Victor AU - Alvarez-Galvez, Javier PY - 2022/8/25 TI - Assessing the Role of Social Bots During the COVID-19 Pandemic: Infodemic, Disagreement, and Criticism JO - J Med Internet Res SP - e36085 VL - 24 IS - 8 KW - infodemics KW - social media KW - misinformation KW - epidemics KW - outbreaks KW - COVID-19 KW - infodemiology KW - health promotion KW - pandemic KW - chatbot KW - social media bot KW - Twitter stream KW - Botometer KW - peer support N2 - Background: Social media has changed the way we live and communicate, as well as offering unprecedented opportunities to improve many aspects of our lives, including health promotion and disease prevention. However, there is also a darker side to social media that is not always as evident as its possible benefits. In fact, social media has also opened the door to new social and health risks that are linked to health misinformation. Objective: This study aimed to study the role of social media bots during the COVID-19 outbreak. Methods: The Twitter streaming API was used to collect tweets regarding COVID-19 during the early stages of the outbreak. The Botometer tool was then used to obtain the likelihood of whether each account is a bot or not. Bot classification and topic-modeling techniques were used to interpret the Twitter conversation. Finally, the sentiment associated with the tweets was compared depending on the source of the tweet. Results: Regarding the conversation topics, there were notable differences between the different accounts. The content of nonbot accounts was associated with the evolution of the pandemic, support, and advice. On the other hand, in the case of self-declared bots, the content consisted mainly of news, such as the existence of diagnostic tests, the evolution of the pandemic, and scientific findings. Finally, in the case of bots, the content was mostly political. Above all, there was a general overriding tone of criticism and disagreement. In relation to the sentiment analysis, the main differences were associated with the tone of the conversation. In the case of self-declared bots, this tended to be neutral, whereas the conversation of normal users scored positively. In contrast, bots tended to score negatively. Conclusions: By classifying the accounts according to their likelihood of being bots and performing topic modeling, we were able to segment the Twitter conversation regarding COVID-19. Bot accounts tended to criticize the measures imposed to curb the pandemic, express disagreement with politicians, or question the veracity of the information shared on social media. UR - https://www.jmir.org/2022/8/e36085 UR - http://dx.doi.org/10.2196/36085 UR - http://www.ncbi.nlm.nih.gov/pubmed/35839385 ID - info:doi/10.2196/36085 ER - TY - JOUR AU - Kim, Hyeon-Joo AU - Kim, Hyejoo AU - Park, Jinyoon AU - Oh, Bumjo AU - Kim, Seung-Chan PY - 2022/8/24 TI - Recognition of Gait Patterns in Older Adults Using Wearable Smartwatch Devices: Observational Study JO - J Med Internet Res SP - e39190 VL - 24 IS - 8 KW - activity recognition KW - machine learning KW - health monitoring KW - gait analysis KW - wearable KW - sequence classification KW - mobile health KW - mHealth KW - neural network UR - https://www.jmir.org/2022/8/e39190 UR - http://dx.doi.org/10.2196/39190 UR - http://www.ncbi.nlm.nih.gov/pubmed/36001374 ID - info:doi/10.2196/39190 ER - TY - JOUR AU - Tornberg, N. Haley AU - Moezinia, Carine AU - Wei, Chapman AU - Bernstein, A. Simone AU - Wei, Chaplin AU - Al-Beyati, Refka AU - Quan, Theodore AU - Diemert, J. David PY - 2022/8/10 TI - Retraction: ?Assessing the Dissemination of COVID-19 Articles Across Social Media With Altmetric and PlumX Metrics: Correlational Study? JO - J Med Internet Res SP - e41544 VL - 24 IS - 8 UR - https://www.jmir.org/2022/8/e41544 UR - http://dx.doi.org/10.2196/41544 UR - http://www.ncbi.nlm.nih.gov/pubmed/35947853 ID - info:doi/10.2196/41544 ER -