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Journal Description

The Journal of Medical Internet Research (JMIR), now in its 21st year, is the pioneer open access eHealth journal and is the flagship journal of JMIR Publications. It is the leading digital health journal globally in terms of quality/visibility (Impact Factor 2018: 4.945, ranked #1 out of 26 journals in the medical informatics category) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As a leading high-impact journal in its disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journals. 

As an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).

We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.

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Recent Articles:

  • Source: ShutterStock; Copyright: Lordn; URL:; License: Licensed by the authors.

    Feasibility of an Electronic Health Tool to Promote Physical Activity in Primary Care: Pilot Cluster Randomized Controlled Trial


    Background: Physical inactivity is associated with increased health risks. Primary care providers (PCPs) are well positioned to support increased physical activity (PA) levels through screening and provision of PA prescriptions. However, PCP counseling on PA is not common. Objective: This study aimed to assess the feasibility of implementing an electronic health (eHealth) tool to support PA counseling by PCPs and estimate intervention effectiveness on patients’ PA levels. Methods: A pragmatic pilot study was conducted using a stepped wedge cluster randomized trial design. The study was conducted at a single primary care clinic, with 4 pre-existing PCP teams. Adult patients who had a periodic health review (PHR) scheduled during the study period were invited to participate. The eHealth tool involved an electronic survey sent to participants before their PHR via an email or a tablet; data were used to automatically produce tailored resources and a PA prescription in the electronic medical record of participants in the intervention arm. Participants assigned to the control arm received usual care from their PCP. Feasibility was assessed by the proportion of completed surveys and patient-reported acceptability and fidelity measures. The primary effectiveness outcome was patient-reported PA at 4 months post-PHR, measured as metabolic equivalent of task (MET) minutes per week. Secondary outcomes assessed determinants of PA, including self-efficacy and intention to change based on the Health Action Process Approach behavior change theory. Results: A total of 1028 patients receiving care from 34 PCPs were invited to participate and 530 (51.55%) consented (intervention [n=296] and control [n=234]). Of the participants who completed a process evaluation, almost half (88/178, 49.4%) stated they received a PA prescription, with only 42 receiving the full intervention including tailored resources from their PCP. A cluster-level linear regression analysis yielded a non–statistically significant positive difference in MET-minutes reported per week at follow-up between intervention and control conditions (mean difference 1027; 95% CI −155 to 2209; P=.09). No statistically significant differences were observed for secondary outcomes. Conclusions: Our results suggest that it is feasible to build an eHealth tool that screens and provides tailored resources for PA in a primary care setting but suboptimal intervention fidelity suggests greater work must be done to address PCP barriers to resource distribution. Participant responses to the primary effectiveness outcome (MET-minutes) were highly variable, reflecting a need for more robust measures of PA in future trials to address limitations in patient-reported data. Trial Registration: NCT03181295;

  • Source: Image created by the Authors; Copyright: Emre Sezgin; URL:; License: Licensed by JMIR.

    Capturing At-Home Health and Care Information for Children With Medical Complexity Using Voice Interactive Technologies: Multi-Stakeholder Viewpoint


    Digital health tools and technologies are transforming health care and making significant impacts on how health and care information are collected, used, and shared to achieve best outcomes. As most of the efforts are still focused on clinical settings, the wealth of health information generated outside of clinical settings is not being fully tapped. This is especially true for children with medical complexity (CMC) and their families, as they frequently spend significant hours providing hands-on medical care within the home setting and coordinating activities among multiple providers and other caregivers. In this paper, a multidisciplinary team of stakeholders discusses the value of health information generated at home, how technology can enhance care coordination, and challenges of technology adoption from a patient-centered perspective. Voice interactive technology has been identified to have the potential to transform care coordination for CMC. This paper shares opinions on the promises, limitations, recommended approaches, and challenges of adopting voice technology in health care, especially for the targeted patient population of CMC.

  • Source: Flickr; Copyright: Erik (HASH) Hersman; URL:; License: Creative Commons Attribution (CC-BY).

    Use of Digital Technology to Enhance Tuberculosis Control: Scoping Review


    Background: Tuberculosis (TB) is the leading cause of death from a single infectious agent, with around 1.5 million deaths reported in 2018, and is a major contributor to suffering worldwide, with an estimated 10 million new cases every year. In the context of the World Health Organization’s End TB strategy and the quest for digital innovations, there is a need to understand what is happening around the world regarding research into the use of digital technology for better TB care and control. Objective: The purpose of this scoping review was to summarize the state of research on the use of digital technology to enhance TB care and control. This study provides an overview of publications covering this subject and answers 3 main questions: (1) to what extent has the issue been addressed in the scientific literature between January 2016 and March 2019, (2) which countries have been investing in research in this field, and (3) what digital technologies were used? Methods: A Web-based search was conducted on PubMed and Web of Science. Studies that describe the use of digital technology with specific reference to keywords such as TB, digital health, eHealth, and mHealth were included. Data from selected studies were synthesized into 4 functions using narrative and graphical methods. Such digital health interventions were categorized based on 2 classifications, one by function and the other by targeted user. Results: A total of 145 relevant studies were identified out of the 1005 published between January 2016 and March 2019. Overall, 72.4% (105/145) of the research focused on patient care and 20.7% (30/145) on surveillance and monitoring. Other programmatic functions 4.8% (7/145) and electronic learning 2.1% (3/145) were less frequently studied. Most digital health technologies used for patient care included primarily diagnostic 59.4% (63/106) and treatment adherence tools 40.6% (43/106). On the basis of the second type of classification, 107 studies targeted health care providers (107/145, 73.8%), 20 studies targeted clients (20/145, 13.8%), 17 dealt with data services (17/145, 11.7%), and 1 study was on the health system or resource management. The first authors’ affiliations were mainly from 3 countries: the United States (30/145 studies, 20.7%), China (20/145 studies, 13.8%), and India (17/145 studies, 11.7%). The researchers from the United States conducted their research both domestically and abroad, whereas researchers from China and India conducted all studies domestically. Conclusions: The majority of research conducted between January 2016 and March 2019 on digital interventions for TB focused on diagnostic tools and treatment adherence technologies, such as video-observed therapy and SMS. Only a few studies addressed interventions for data services and health system or resource management.

  • Source: Shopify Partners; Copyright: Burst; URL:; License: Licensed by the authors.

    A Physician-Completed Digital Tool for Evaluating Disease Progression (Multiple Sclerosis Progression Discussion Tool): Validation Study


    Background: Defining the transition from relapsing-remitting multiple sclerosis (RRMS) to secondary progressive multiple sclerosis (SPMS) can be challenging and delayed. A digital tool (MSProDiscuss) was developed to facilitate physician-patient discussion in evaluating early, subtle signs of multiple sclerosis (MS) disease progression representing this transition. Objective: This study aimed to determine cut-off values and corresponding sensitivity and specificity for predefined scoring algorithms, with or without including Expanded Disability Status Scale (EDSS) scores, to differentiate between RRMS and SPMS patients and to evaluate psychometric properties. Methods: Experienced neurologists completed the tool for patients with confirmed RRMS or SPMS and those suspected to be transitioning to SPMS. In addition to age and EDSS score, each patient’s current disease status (disease activity, symptoms, and its impacts on daily life) was collected while completing the draft tool. Receiver operating characteristic (ROC) curves determined optimal cut-off values (sensitivity and specificity) for the classification of RRMS and SPMS. Results: Twenty neurologists completed the draft tool for 198 patients. Mean scores for patients with RRMS (n=89), transitioning to SPMS (n=47), and SPMS (n=62) were 38.1 (SD 12.5), 55.2 (SD 11.1), and 69.6 (SD 12.0), respectively (P<.001, each between-groups comparison). Area under the ROC curve (AUC) including and excluding EDSS were for RRMS (including) AUC 0.91, 95% CI 0.87-0.95, RRMS (excluding) AUC 0.88, 95% CI 0.84-0.93, SPMS (including) AUC 0.91, 95% CI 0.86-0.95, and SPMS (excluding) AUC 0.86, 95% CI 0.81-0.91. In the algorithm with EDSS, the optimal cut-off values were ≤51.6 for RRMS patients (sensitivity=0.83; specificity=0.82) and ≥58.9 for SPMS patients (sensitivity=0.82; specificity=0.84). The optimal cut-offs without EDSS were ≤46.3 and ≥57.8 and resulted in similar high sensitivity and specificity (0.76-0.86). The draft tool showed excellent interrater reliability (intraclass correlation coefficient=.95). Conclusions: The MSProDiscuss tool differentiated RRMS patients from SPMS patients with high sensitivity and specificity. In clinical practice, it may be a useful tool to evaluate early, subtle signs of MS disease progression indicating the evolution of RRMS to SPMS. MSProDiscuss will help assess the current level of progression in an individual patient and facilitate a more informed physician-patient discussion.

  • Woman accessing the virtual multidisciplinary care program. Source: Shutterstock; Copyright: Cricket Health; URL:; License: Licensed by the authors.

    A Virtual Multidisciplinary Care Program for Management of Advanced Chronic Kidney Disease: Matched Cohort Study


    Background: It is not well established whether a virtual multidisciplinary care program for persons with advanced chronic kidney disease (CKD) can improve their knowledge about their disease, increase their interest in home dialysis therapies, and result in more planned outpatient (versus inpatient) dialysis starts. Objective: We aimed to evaluate the feasibility and preliminary associations of program participation with disease knowledge, home dialysis modality preference, and outpatient dialysis initiation among persons with advanced CKD in a community-based nephrology practice. Methods: In a matched prospective cohort, we enrolled adults aged 18 to 85 years with at least two estimated glomerular filtration rates (eGFRs) of less than 30 mL/min/1.73 m2 into the Cricket Health program and compared them with controls receiving care at the same clinic, matched on age, gender, eGFR, and presence of heart failure and diabetes. The intervention included online education materials, a virtual multidisciplinary team (nurse, pharmacist, social worker, dietician), and patient mentors. Prespecified follow-up time was nine months with extended follow-up to allow adequate time to determine the dialysis start setting. CKD knowledge and dialysis modality choice were evaluated in a pre-post survey among intervention participants. Results: Thirty-seven participants were matched to 61 controls by age (mean 67.2, SD 10.4 versus mean 68.8, SD 9.5), prevalence of diabetes (54%, 20/37 versus 57%, 35/61), congestive heart failure (22%, 8/37 versus 25%, 15/61), and baseline eGFR (mean 19, SD 6 versus mean 21, SD 5 mL/min/1.73 m2), respectively. At nine-month follow-up, five patients in each group started dialysis (P=.62). Among program participants, 80% (4/5) started dialysis as an outpatient compared with 20% (1/5) of controls (OR 6.28, 95% CI 0.69-57.22). In extended follow-up (median 15.7, range 11.7 to 18.1 months), 19 of 98 patients started dialysis; 80% (8/10) of the intervention group patients started dialysis in the outpatient setting versus 22% (2/9) of control patients (hazard ratio 6.89, 95% CI 1.46-32.66). Compared to before participation, patients who completed the program had higher disease knowledge levels (mean 52%, SD 29% versus mean 94%, SD 14% of questions correct on knowledge-based survey, P<.001) and were more likely to choose a home modality as their first dialysis choice (36%, 7/22 versus 68%, 15/22, P=.047) after program completion. Conclusions: The Cricket Health program can improve patient knowledge about CKD and increase interest in home dialysis modalities, and may increase the proportion of dialysis starts in the outpatient setting.

  • Source: freepik; Copyright: freepik; URL:; License: Licensed by JMIR.

    Measuring Interests Not Minutes: Development and Validation of the Adolescents’ Digital Technology Interactions and Importance Scale (ADTI)


    Background: Interactive digital technology use is integral to adolescents’ lives and has been associated with both health benefits and risks. Previous studies have largely focused on measuring the quantity of technology use or understanding the use of specific platforms. To better understand adolescents’ interactive digital technology use, we need new approaches that consider technology interactions and their importance. Objective: This study aimed to develop an assessment tool to evaluate adolescents’ digital technology interactions and their perceived importance. Methods: We used a validated scale development approach comprising 2 initial steps to create an item pool: item pool development and item pool refinement. These steps relied upon empirical literature review and an expert convening. We then evaluated the item pool using a Web-based survey. Data were collected via Qualtrics panel recruitment from a national sample of 12- to 18-year-olds. Participant data were randomly split into a development subsample for exploratory factor analysis (EFA) and a test subsample for confirmatory factor analysis (CFA). We assessed Cronbach alpha as well as model fit characteristics including root mean square error of approximation (RMSEA) and comparative fit index (CFI). Results: Our initial item pool had 71 items and the refined item pool contained 40. A total of 761 adolescents assessed the item pool via Web-based survey. Participants had a mean age of 14.8 (SD 1.7) years and were 52.8% (402/761) female and 77.5% (590/761) white. The EFA analysis included 500 participants and an 18-item draft scale was created. The CFA included 261 participants to test the draft scale. Adequate model fit for the scale was indicated by an RMSEA of 0.063 and a CFI of 0.95. The final scale included 18 items in a 3-factor model, with Cronbach alpha for the 3 factors of .87 (factor 1), .90 (factor 2) and .82 (factor 3). The 3 factors were named (1) technology to bridge online and offline experiences, (2) technology to go outside one’s identity or offline environment, and (3) technology for social connection. Conclusions: The resulting Adolescents’ Digital Technology Interactions and Importance (ADTI) scale is a promising and psychometrically validated tool for identifying the importance of distinct technology interactions. The scale is informed by relevant theory and expert input. The 3 subscales have utility for future studies to understand whether certain subscale score ranges are associated with health or well-being outcomes.

  • Algometer used to cause mild pain to be recorded with the e-VAS. Source: Image created by the Authors; Copyright: Carles Escalona-Marfil; URL:; License: Creative Commons Attribution (CC-BY).

    Validation of an Electronic Visual Analog Scale mHealth Tool for Acute Pain Assessment: Prospective Cross-Sectional Study


    Background: Accurate measurement of pain is required to improve its management and in research. The visual analog scale (VAS) on paper format has been shown to be an accurate, valid, reliable, and reproducible way to measure pain intensity. However, some limitations should be considered, some of which can be implemented with the introduction of an electronic VAS version, suitable to be used both in a tablet and a smartphone. Objective: This study aimed to validate a new method of recording pain level by comparing the traditional paper VAS with the pain level module on the newly designed Interactive Clinics app. Methods: A prospective observational cross-sectional study was designed. The sample consisted of 102 participants aged 18 to 65 years. A Force Dial FDK 20 algometer (Wagner Instruments) was employed to induce mild pressure symptoms on the participants’ thumbs. Pain was measured using a paper VAS (10 cm line) and the app. Results: Intermethod reliability estimated by ICC(3,1) was 0.86 with a 95% confidence interval of 0.81 to 0.90, indicating good reliability. Intramethod reliability estimated by ICCa(3,1) was 0.86 with a 95% confidence interval of 0.81 to 0.90, also indicating good reliability. Bland-Altman analysis showed a difference of 0.175 (0.49), and limits of agreement ranged from –0.79 to 1.14. Conclusions: The pain level module on the app is highly reliable and interchangeable with the paper VAS version. This tool could potentially help clinicians and researchers precisely assess pain in a simple, economic way with the use of a ubiquitous technology.

  • Run4Love. Source: Image created by the Authors; Copyright: Yan Guo; URL:; License: Licensed by JMIR.

    Effect of a WeChat-Based Intervention (Run4Love) on Depressive Symptoms Among People Living With HIV in China: Randomized Controlled Trial


    Background: People living with HIV (PLWH) have high rates of depressive symptoms. However, only a few effective mental health interventions exist for this vulnerable population. Objective: The aim of this study was to assess the efficacy of a WeChat-based intervention, Run4Love, with a randomized controlled trial among 300 people living with HIV and depression (PLWHD) in China. Methods: We recruited PLWH from the HIV outpatient clinic in South China. Participants were screened based on the Center for Epidemiologic Studies-Depression (CES-D) scale. Those who scored 16 or higher were eligible to participate. A total of 300 eligible patients were enrolled. After obtaining informed consent from the participants, completion of a baseline survey, and collection of participants’ hair samples for measuring cortisol, the participants were randomly assigned to an intervention or a control group in a 1:1 ratio. The intervention group received the Run4Love program, delivered via the popular social media app WeChat. Cognitive behavioral stress management courses and weekly reminders of exercise were delivered in a multimedia format. Participants’ progress was monitored with timely and tailored feedback. The control group received usual care and a brochure on nutrition for PLWH. Data were collected at 3, 6, and 9 months. The primary outcome was depression, which was measured by a validated instrument. Results: Participants in the intervention and control groups were comparable at baseline; about 91.3% (139/150), 88.3% (132/150), and 86.7% (130/150) participants completed the 3-, 6-, and 9-month follow-ups, respectively. At the 3-month follow-up, a significant reduction in CES-D score was observed in the intervention group (from 23.9 to 17.7 vs from 24.3 to 23.8; mean difference=−5.77, 95% CI −7.82 to −3.71; P<.001; standard effect size d=0.66). The mean changes in CES-D score from baseline to the 6- and 9-month follow-ups between the two groups remained statistically significant. No adverse events were reported. Conclusions: The WeChat-based mobile health (mHealth) intervention Run4Love significantly reduced depressive symptoms among PLWHD, and the effect was sustained. An app-based mHealth intervention could provide a feasible therapeutic option for many PLWHD in resource-limited settings. Further research is needed to assess generalizability and cost-effectiveness of this intervention. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IPR-17012606; (Archived by WebCite at

  • Constant Therapy in use (montage). Source: The Authors/Getty Images; Copyright: Farknot_Architect; URL:; License: Licensed by JMIR.

    Closing the Digital Divide in Speech, Language, and Cognitive Therapy: Cohort Study of the Factors Associated With Technology Usage for Rehabilitation


    Background: For stroke, traumatic brain injury (TBI), and other neurologic conditions associated with speech-language disorders, speech and language therapy is the standard of care for promoting recovery. However, barriers such as clinician time constraints and insurance reimbursement can inhibit a patient’s ability to receive the support needed to optimize functional gain. Although digital rehabilitation has the potential to increase access to therapy by allowing patients to practice at home, the clinical and demographic characteristics that impact a patient’s level of engagement with technology-based therapy are currently unknown. Objective: This study aimed to evaluate whether the level of engagement with digital therapy differs by various patient characteristics, including age, gender, diagnosis, time from disease onset, and geographic location (urban vs rural). Methods: Data for patients with stroke or TBI that initiated the use of Constant Therapy, a remotely delivered, cloud-based rehabilitation program for patients with speech-language disorders, were retrospectively analyzed. Only data from therapeutic sessions completed at home were included. The following three activity metrics were evaluated: (1) the number of active weeks of therapy, (2) the average number of active therapy days per week, and (3) the total number of therapeutic sessions completed during the first 20 weeks of program access. An active day or week was defined as having at least one completed therapeutic session. Separate multiple linear regression models were performed with each activity measure as the dependent variable and all available patient demographics as model covariates. Results: Data for 2850 patients with stroke or TBI were analyzed, with the average patient completing 8.6 weeks of therapy at a frequency of 1.5 days per week. Contrary to known barriers to technological adoption, older patients were more active during their first 20 weeks of program access, with those aged 51 to 70 years completing 5.01 more sessions than patients aged 50 years or younger (P=.04). Similarly, patients living in a rural area, who face greater barriers to clinic access, were more digitally engaged than their urban counterparts, with rural patients completing 11.54 more (P=.001) sessions during their first 20 weeks of access, after controlling for other model covariates. Conclusions: An evaluation of real-world data demonstrated that patients with stroke and TBI use digital therapy frequently for cognitive and language rehabilitation at home. Usage was higher in areas with limited access to clinical services and was unaffected by typical barriers to technological adoption, such as age. These findings will help guide the direction of future research in digital rehabilitation therapy, including the impact of demographics on recovery outcomes and the design of large, randomized controlled trials.

  • TOC image. Source: iStock; Copyright: Rawpixel Ltd; URL:; License: Licensed by the authors.

    Impact of a Knowledge Translation Intervention on Physical Activity and Mobility in Older Adults (the Move4Age Study): Randomized Controlled Trial


    Background: The McMaster Optimal Aging Portal (the Portal) was launched in 2014 as a knowledge translation (KT) tool to increase access to evidence-based health information. Objective: The purpose of this study was to understand if and how dissemination of mobility information through the Portal impacts physical activity (PA) in older adults. Methods: In this randomized controlled trial, participants (n=510) were assigned to a 12-week mobility-focused KT intervention or self-serve control group. The intervention included weekly email alerts and a study-specific social media hashtag linking to mobility-focused Portal materials. The control group was able to access the Portal on their own but did not receive targeted KT strategies. Participants completed questionnaires (including the Rapid Assessment of Physical Activity to quantify PA) at baseline, end of the study, and 3-month follow-up. Results: Participants were predominantly female (430/510, 84.3%), mean age 64.7 years, with no baseline differences between groups. Over half (277/510, 54.3%) of the participants were classified as “active” at baseline. There was no significant between-group difference in the PA category. Overall, both groups increased their PA with improvements maintained at 3-month follow-up (P<.001). In planned subgroup analyses, the KT intervention had a significant effect for those with poor or fair baseline self-rated health (P=.03). Conclusions: No differences were found between those who received the targeted intervention and a control group with self-serve access to the Portal, except in subgroups with low self-rated health. Both groups did report increases in PA that were sustained beyond participation in a research study. Findings suggest that different KT strategies may be needed for different types of users, with more intense interventions being most impactful for certain groups (ie, those with lower self-rated health). Trial Registration: NCT02947230;

  • Source: Image created by the Authors / Placeit; Copyright: The Authors / Placeit; URL:; License: Creative Commons Attribution (CC-BY).

    Real-Time Access to Electronic Health Record via a Patient Portal in a Tertiary Hospital: Is it Harmful? A Retrospective Mixed Methods Observational Study


    Background: The rapid implementation of patient portals, through which patients can view their electronic health record, creates possibilities for information exchange and communication between patients and health care professionals. However, real-time disclosure of test results and clinical reports poses a source of concern. Objective: This study aimed to examine negative experiences resulting from real-time disclosure of medical information through a patient portal. Methods: Data were collected over a 2-year period in 4 datasets consisting of incidents reported by health care professionals, complaints of patients, patient issues at a portal helpdesk, and a survey among health care professionals. Incidents, complaints, issues, and answers on the survey were counted and analyzed through an iterative process of coding. Results: Within the chosen time frame of 2 years, on average, 7978 patients per month logged into the portal at least once. The amount of negative incidents and complaints was limited. A total of 6 incidents, 4 complaints, and 2506 issues at the helpdesk concerning the patient portal were reported, of which only 2, 1, and 3 cases of these respective databases concerned real-time disclosure of medical information through the patient portal. Moreover, 32 out of 216 health care professionals reported patients that had negative experiences with real-time disclosure. Most negative consequences concerned confused and anxious patients when confronted with unexpected or incomprehensible results. Conclusions: Real-time access through a patient portal did not substantially result in negative consequences. The negative consequences that did occur can be mitigated by adequate preparation and instruction of patients concerning the various functionalities of the patient portal, real-time disclosure of test results in particular, and can also be managed through educating health care professionals about the patient portal and making adjustments in the daily practice of health care professionals.

  • Source:; Copyright: Burst; URL:; License: Licensed by the authors.

    Responses of Conversational Agents to Health and Lifestyle Prompts: Investigation of Appropriateness and Presentation Structures


    Background: Conversational agents (CAs) are systems that mimic human conversations using text or spoken language. Their widely used examples include voice-activated systems such as Apple Siri, Google Assistant, Amazon Alexa, and Microsoft Cortana. The use of CAs in health care has been on the rise, but concerns about their potential safety risks often remain understudied. Objective: This study aimed to analyze how commonly available, general-purpose CAs on smartphones and smart speakers respond to health and lifestyle prompts (questions and open-ended statements) by examining their responses in terms of content and structure alike. Methods: We followed a piloted script to present health- and lifestyle-related prompts to 8 CAs. The CAs’ responses were assessed for their appropriateness on the basis of the prompt type: responses to safety-critical prompts were deemed appropriate if they included a referral to a health professional or service, whereas responses to lifestyle prompts were deemed appropriate if they provided relevant information to address the problem prompted. The response structure was also examined according to information sources (Web search–based or precoded), response content style (informative and/or directive), confirmation of prompt recognition, and empathy. Results: The 8 studied CAs provided in total 240 responses to 30 prompts. They collectively responded appropriately to 41% (46/112) of the safety-critical and 39% (37/96) of the lifestyle prompts. The ratio of appropriate responses deteriorated when safety-critical prompts were rephrased or when the agent used a voice-only interface. The appropriate responses included mostly directive content and empathy statements for the safety-critical prompts and a mix of informative and directive content for the lifestyle prompts. Conclusions: Our results suggest that the commonly available, general-purpose CAs on smartphones and smart speakers with unconstrained natural language interfaces are limited in their ability to advise on both the safety-critical health prompts and lifestyle prompts. Our study also identified some response structures the CAs employed to present their appropriate responses. Further investigation is needed to establish guidelines for designing suitable response structures for different prompt types.

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  • Applying digital information delivery to convert habits of antibiotics use in primary care in Germany: Mixed-methods study

    Date Submitted: Feb 11, 2020

    Open Peer Review Period: Feb 11, 2020 - Apr 7, 2020

    Background: Antimicrobial resistance remains high on the global health agenda. In Germany, the national agenda supports various interventions to convert habits of antibiotics use. The CHANGE-3 study (...

    Background: Antimicrobial resistance remains high on the global health agenda. In Germany, the national agenda supports various interventions to convert habits of antibiotics use. The CHANGE-3 study (‘Converting Habits of Antibiotic Use for Respiratory Tract Infections in German Primary Care’, 2017-2020) applied digital information delivery using tablet computers in primary care practices, e-learning platforms for medical professionals and a website for the public to promote awareness and health literacy among primary care physicians, their teams and patients. Objective: Embedded in the process evaluation of the CHANGE-3 study, this present study aimed at evaluating the acceptance and uptake of digital devices for the delivery of health-related information to enhance awareness and change habits of antibiotics use in primary care in Germany. Methods: For this study, audio-recorded telephone interviews were conducted with physicians, non-physician health professionals and patients in the CHANGE-3 program. Pseudonymized verbatim transcripts were coded using thematic analysis. In-depth analysis was based on the inductive category ‘information provision via digital information tools’. Identified themes were related to main postulates of the Diffusion of Innovation Theory. In addition, data generated through a structured survey with physicians and non-physician health professionals in the program were analyzed descriptively. Results: Findings regarding acceptance and uptake of digital devices mirrored in three postulates of the Diffusion of Innovation Theory: innovation characteristics, communication channels and unanticipated consequences. Participants considered the provided digital educative solutions as supportive for promoting health literacy regarding a conversion of habits of antibiotics use. However, health care professionals also found it challenging to integrate these into existing routines in primary care and to align these with their professional values. Low technology affinity was a major barrier to the use of digital information in primary care as well. Patients welcomed the general idea of introducing health-related information in digital formats, but had concerns about device-related hygiene and their appropriateness for older patients. Conclusions: Patients and medical professionals in primary care are reluctant to use digital devices that aim to promote awareness and health literacy regarding a rational use of antibiotics. Using a Diffusion of Innovation approach can support assessment of existing barriers and provide information about setting-specific pre-conditions necessary for future tailoring of implementation strategies Clinical Trial: ISRCTN, ISRCTN15061174. Registered 13 July 2018 – Retrospectively registered

  • Smartphone remote monitoring app to follow-up colorectal cancer survivors: a requirement analysis

    Date Submitted: Feb 2, 2020

    Open Peer Review Period: Feb 10, 2020 - Apr 10, 2020

    Background: Colorectal survivors after discharge face multiple challenges and eHealth may potentially support them through providing tools such as smartphone apps. They have lots of capabilities to ex...

    Background: Colorectal survivors after discharge face multiple challenges and eHealth may potentially support them through providing tools such as smartphone apps. They have lots of capabilities to exchange information and could be used for remote monitoring of these patients. Objective: In this study, we addressed required features for apps designed to follow-up colorectal cancer patients. Methods: Features of related apps were extracted through the literature; the features were categorized and then they were modified. A questionnaire is designed containing the features listed and prioritized based on MoScoW technique and an open question for each category. The link of the questionnaire is shared among oncological surgeons and related clinical experts in the country. The answers were analyzed using CVR and the minimum feature set of a monitoring app to follow-up colorectal cancer patients were obtained. Results: The questionnaire contained ten sections evaluating nine categories of features. Eighteen experts filled the questionnaire. the minimum features of the app identified as: patient information registration, sign and symptoms monitoring, education, reminders, and patient evaluation (0.42<CVR<0.85). Features including physical activity, personalized advice, and social network did not get the minimum score (-0.11<CVR<0.39). Conclusions: The requirements set could be used for designing an app for the targeted population. Further research might address patient’s concerns on such an app also the extensibility of this features to other types of cancer.

  • Developing a virtual reality exergame to engage adolescents with physical activity: early intervention development process

    Date Submitted: Feb 7, 2020

    Open Peer Review Period: Feb 7, 2020 - Apr 3, 2020

    Background: Adolescence (13-17 years) is a key developmental stage for physical activity promotion (PA), but it remains unclear what works to change PA in this group. Virtual reality (VR) exergaming i...

    Background: Adolescence (13-17 years) is a key developmental stage for physical activity promotion (PA), but it remains unclear what works to change PA in this group. Virtual reality (VR) exergaming is a promising intervention strategy to engage adolescents with physical activity. Objective: We hypothesise that a multicomponent intervention with VR exergaming at the core could increase physical activity in adolescents. However, substantial intervention development work is required. Methods: The vEngage study involves collaboration between academics and commercial games designers and employs a staged, mixed-methods approach to intervention development, combining traditional research processes and iterative game design processes. This protocol reports on our experiences of the methods and procedures for the initial development phases of the intervention. Ethics and Dissemination: The results from each work package have been disseminated through peer-review publications and scientific presentations. Ethical approval for each work package has been obtained through the University College London Research Ethics Committee. Results: This project developed a novel intervention involving VR exergaming with embedded elements designed to engage adolescents in physical activity. The unique academic and industry partnership from the outset, support from public health funders, and involvement of users and stakeholders throughout has been crucial to success. Conclusions: This project is a world first attempt to develop a VR exergame designed to engage adolescents with PA, embracing academic-industry collaboration. We proposed and described very early development work in order to raise awareness of the study, and still open up possibilities and invite other researchers and industry partners to link with us. As such we welcome potential collaboration, and input on our planned and future work.

  • Wechat App Combined Case-Based Learning in Clinical Training of Oral Medicine: Comparison and Feasibility Study

    Date Submitted: Feb 6, 2020

    Open Peer Review Period: Feb 5, 2020 - Apr 1, 2020

    Background: Case Based Learning (CBL) is being hottly used in student-centered medical education worldwide. In China, Wechat is the most popular communication app in China and is widely used in all wa...

    Background: Case Based Learning (CBL) is being hottly used in student-centered medical education worldwide. In China, Wechat is the most popular communication app in China and is widely used in all walks of life. We have practiced several years combining Wechat and CBL in the clinical training of oral medicine, promoting outcomes in traditional bedside training. Objective: This study aimed to demonstrate the acceptability and merits of Wechat CBL in the clinical training of oral medicine. Methods: A total of eighty students and two tutors participated in this study within a 2-month training during Jan. 2018 and Jan. 2020. The control group used bedside mode and the experimental group used bedside plus Wechat CBL mode. The evaluations included participation passion and routine and finial test. The students of clerkship as 10 and residents as 30 in same number respectively between experiment and control groups. Results: The participants in the experimental group had a higher degree of participation in the discussion. And the daily assessment and final examination scores of the participants in the experimental group were significantly better than those in the control group (P<0.001). Conclusions: Wechat CBL mode has a positive effect on students’ learning enthusiasm and knowledge assessments & technology evaluations in clinical training of oral medicine.

  • Signal Quality Evaluation of Single-period Radial Artery Pulse Wave Based on Machine Learning

    Date Submitted: Feb 5, 2020

    Open Peer Review Period: Feb 5, 2020 - Apr 1, 2020

    Background: Radial artery pulse wave is a widely used physiological signal for disease diagnosis and personal health monitoring as it contains a lot of important information concerning the heart and b...

    Background: Radial artery pulse wave is a widely used physiological signal for disease diagnosis and personal health monitoring as it contains a lot of important information concerning the heart and blood vessels. Periodic radial artery pulse signal is needed to be decomposed into single pulse wave periods (segments) for physiological parameter evaluations. It is inevitable to get abnormal periods in this process because of the quality of pulse wave signals, external interference and imperfections of segmentation methods. Objective: The objective of this paper is to develop a machine learning model to detect abnormal pulse periods from real clinical data. Methods: Various machine learning models such as k-Nearest Neighbor (KNN), logistic regression (LR) and support vector machines (SVM) are applied to classify the normal and abnormal periods in 8561 segments extracted from radical pulse wave of 390 outpatients. The recursive feature elimination (RFE) method is used to simplify the classifier. Results: It was found that a logistic regression model with only 4 input features can achieve a satisfactory result. The area under curve (AUC) of receiver operating characteristic (ROC) curve from the test set is 0.9920. In addition, these classifiers can be easily interpreted. Conclusions: It is expected that the model can be used in smart sport watch/band applications to accurately evaluate human health status.

  • Improving the primary care consultation through digital medical interview assistant systems - the cases of diabetes and depression: A narrative review

    Date Submitted: Feb 4, 2020

    Open Peer Review Period: Feb 4, 2020 - Mar 31, 2020

    Digital medical interview assistant (DMIA, also known as computer-assisted history taking (CAHT)) systems have the potential to improve the quality of care and the medical consultation by exploring a...

    Digital medical interview assistant (DMIA, also known as computer-assisted history taking (CAHT)) systems have the potential to improve the quality of care and the medical consultation by exploring a larger number of aspects related to the patient without time constraints, and therefore acquiring more and better quality information, prior to the face-to-face consultation. The consultation in primary care (PC) is the broadest in terms of the amount of topics to be covered and, at the same time, the shortest in term of time spent with the patient. In this study, we explore how DMIA systems may be used specifically in the context of PC, to improve the consultations for diabetes and depression, as exemplars for chronic conditions. A narrative review was conducted focusing on (1) the characteristics of the primary care consultation in general and for diabetes and depression specifically, and on (2) the impact of DMIA/CAHT systems on the medical consultation. Through thematic analysis, we identified the characteristics of the PC consultation that a DMIA system would be able to improve and developed a sample questionnaire for diabetes and depression to illustrate how such a system may work. A DMIA system, prior to the first consultation, could aid in the essential PC tasks of case finding/screening, diagnosing and, if needed, timely referral to specialists or urgent care. Similarly, for follow up consultations, a DMIA system can aid with the control/monitoring of these conditions, help check for additional health issues and for updating the PC provider about visits to other providers or further testing. The successful implementation of a DMIA system for these aspects of the PC consultation would improve the quality of the data obtained, which means earlier diagnosis and treatment; would improve the use of face-to-face consultation time, streamlining the interaction and allowing the focus to be the patient's needs, which ultimately would lead to better health outcomes and patient satisfaction. However, in order for such a system to be successfully incorporated, there are important considerations to be taken into account, such as the language to be used and the challenges for implementing eHealth innovations in primary care or healthcare in general. Given the benefits explored here, we foresee that DMIA systems could have an important impact in the PC consultation for diabetes and depression and, potentially, for other chronic conditions. Earlier case finding and a more accurate diagnosis, due to more and better-quality data, paired with improved monitoring of disease progress, should improve the quality of care and keep the management of chronic conditions at the primary care level. A somewhat simple, easily scalable technology could go a long way to improve the health of the millions of people affected with chronic conditions, especially if working in conjunction with already established health technologies such as EMRs and CDSS.