%0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 2 %P e27109 %T A Digital Health Intervention (SweetGoals) for Young Adults With Type 1 Diabetes: Protocol for a Factorial Randomized Trial %A Stanger,Catherine %A Kowatsch,Tobias %A Xie,Haiyi %A Nahum-Shani,Inbal %A Lim-Liberty,Frances %A Anderson,Molly %A Santhanam,Prabhakaran %A Kaden,Sarah %A Rosenberg,Briana %+ Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Lebanon, NH, , United States, 1 603 646 7023, Catherine.stanger@dartmouth.edu %K type 1 diabetes %K mhealth %K incentives %K health coaching %K young adults %D 2021 %7 23.2.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Many young adults with type 1 diabetes (T1D) struggle with the complex daily demands of adherence to their medical regimen and fail to achieve target range glycemic control. Few interventions, however, have been developed specifically for this age group. Objective: In this randomized trial, we will provide a mobile app (SweetGoals) to all participants as a “core” intervention. The app prompts participants to upload data from their diabetes devices weekly to a device-agnostic uploader (Glooko), automatically retrieves uploaded data, assesses daily and weekly self-management goals, and generates feedback messages about goal attainment. Further, the trial will test two unique intervention components: (1) incentives to promote consistent daily adherence to goals, and (2) web health coaching to teach effective problem solving focused on personalized barriers to self-management. We will use a novel digital direct-to-patient recruitment method and intervention delivery model that transcends the clinic. Methods: A 2x2 factorial randomized trial will be conducted with 300 young adults ages 19-25 with type 1 diabetes and (Hb)A1c ≥ 8.0%. All participants will receive the SweetGoals app that tracks and provides feedback about two adherence targets: (a) daily glucose monitoring; and (b) mealtime behaviors. Participants will be randomized to the factorial combination of incentives and health coaching. The intervention will last 6 months. The primary outcome will be reduction in A1c. Secondary outcomes include self-regulation mechanisms in longitudinal mediation models and engagement metrics as a predictor of outcomes. Participants will complete 6- and 12-month follow-up assessments. We hypothesize greater sustained A1c improvements in participants who receive coaching and who receive incentives compared to those who do not receive those components. Results: Data collection is expected to be complete by February 2025. Analyses of primary and secondary outcomes are expected by December 2025. Conclusions: Successful completion of these aims will support dissemination and effectiveness studies of this intervention that seeks to improve glycemic control in this high-risk and understudied population of young adults with T1D. Trial Registration: ClinicalTrials.gov NCT04646473; https://clinicaltrials.gov/ct2/show/NCT04646473 International Registered Report Identifier (IRRID): PRR1-10.2196/27109 %M 33620330 %R 10.2196/27109 %U https://www.researchprotocols.org/2021/2/e27109 %U https://doi.org/10.2196/27109 %U http://www.ncbi.nlm.nih.gov/pubmed/33620330 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 6 %N 1 %P e24030 %T Role of Digital Engagement in Diabetes Care Beyond Measurement: Retrospective Cohort Study %A Fundoiano-Hershcovitz,Yifat %A Hirsch,Abigail %A Dar,Sharon %A Feniger,Eitan %A Goldstein,Pavel %+ DarioHealth, Hatochen, 8, Caesarea, 3088900, Israel, 972 525296979, Yifat@mydario.com %K blood glucose %K mHealth %K diabetes %K self-management %K digital engagement %D 2021 %7 18.2.2021 %9 Original Paper %J JMIR Diabetes %G English %X Background: The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes. Objective: This study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels. Methods: This retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included “nontaggers” (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and “taggers” (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual’s tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout. Results: Analysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=−10.01, P<.001), which was maintained during the following 6 months (t=−1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=−11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20). Conclusions: This study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health. %M 33599618 %R 10.2196/24030 %U http://diabetes.jmir.org/2021/1/e24030/ %U https://doi.org/10.2196/24030 %U http://www.ncbi.nlm.nih.gov/pubmed/33599618 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 2 %P e23252 %T Effect of Telemetric Interventions on Glycated Hemoglobin A1c and Management of Type 2 Diabetes Mellitus: Systematic Meta-Review %A Eberle,Claudia %A Stichling,Stefanie %+ Medicine with Specialization in Internal Medicine and General Medicine, Hochschule Fulda–University of Applied Sciences, Leipziger Strasse 123, Fulda, 36037, Germany, 49 661 9640 ext 6328, claudia.eberle@hs-fulda.de %K telemedicine %K telemetry %K diabetes %D 2021 %7 17.2.2021 %9 Review %J J Med Internet Res %G English %X Background: Diabetes mellitus is a chronic burden, with a prevalence that is increasing worldwide. Telemetric interventions have attracted great interest and may provide effective new therapeutic approaches for improving type 2 diabetes mellitus (T2DM) care. Objective: The objective of this study was to analyze the clinical effectiveness of telemetric interventions on glycated hemoglobin A1c (HbA1c) specifically and T2DM management generally in a systematic meta-review. Methods: A systematic literature search was performed in PubMed, CINAHL, Cochrane Library, Web of Science Core Collection, and EMBASE databases from January 2008 to April 2020. Studies that addressed HbA1c, blood pressure, fasting blood glucose, BMI, diabetes-related and health-related quality of life, cost-effectiveness, time savings, and the clinical effectiveness of telemetric interventions were analyzed. In total, 73 randomized controlled trials (RCTs), 10 systematic reviews/meta-analyses, 9 qualitative studies, 2 cohort studies, 2 nonrandomized controlled studies, 2 observational studies, and 1 noncontrolled intervention study were analyzed. Results: Overall, 1647 citations were identified. After careful screening, 99 studies (n=15,939 patients; n=82,436 patient cases) were selected by two independent reviewers for inclusion in the review. Telemetric interventions were categorized according to communication channels to health care providers: (1) “real-time video” interventions, (2) “real-time audio” interventions, (3) “asynchronous” interventions, and (4) “combined” interventions. To analyze changes in HbA1c, suitable RCTs were pooled and the average was determined. An HbA1c decrease of –1.15% (95% CI –1.84% to –0.45%), yielding an HbA1c value of 6.95% (SD 0.495), was shown in studies using 6-month “real-time video” interventions. Conclusions: Telemetric interventions clearly improve HbA1c values in both the short term and the long term and contribute to the effective management of T2DM. More studies need to be done in greater detail. %M 33595447 %R 10.2196/23252 %U http://www.jmir.org/2021/2/e23252/ %U https://doi.org/10.2196/23252 %U http://www.ncbi.nlm.nih.gov/pubmed/33595447 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 2 %P e14760 %T A Novel Food Record App for Dietary Assessments Among Older Adults With Type 2 Diabetes: Development and Usability Study %A Jung,Hyunggu %A Demiris,George %A Tarczy-Hornoch,Peter %A Zachry,Mark %+ Department of Computer Science and Engineering, University of Seoul, Information and Technology Building, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul, 02504, Republic of Korea, 82 2 6490 2455, hjung@uos.ac.kr %K mobile health %K older adults %K diabetes %K dietary assessment %K smartphone app %K usability test %D 2021 %7 17.2.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: More than 1 in 4 people in the United States aged 65 years and older have type 2 diabetes. For diabetes care, medical nutrition therapy is recommended as a clinically effective intervention. Previous researchers have developed and validated dietary assessment methods using images of food items to improve the accuracy of self-reporting over traditional methods. Nevertheless, little is known about the usability of image-assisted dietary assessment methods for older adults with diabetes. Objective: The aims of this study were (1) to create a food record app for dietary assessments (FRADA) that would support image-assisted dietary assessments, and (2) to evaluate the usability of FRADA for older adults with diabetes. Methods: For the development of FRADA, we identified design principles that address the needs of older adults and implemented three fundamental tasks required for image-assisted dietary assessments: capturing, viewing, and transmitting images of food based on the design principles. For the usability assessment of FRADA, older adults aged 65 to 80 years (11 females and 3 males) were assigned to interact with FRADA in a lab-based setting. Participants’ opinions of FRADA and its usability were determined by a follow-up survey and interview. As an evaluation indicator of usability, the responses to the survey, including an after-scenario questionnaire, were analyzed. Qualitative data from the interviews confirmed the responses to the survey. Results: We developed a smartphone app that enables older adults with diabetes to capture, view, and transmit images of food items they consumed. The findings of this study showed that FRADA and its instructions for capturing, viewing, and transmitting images of food items were usable for older adults with diabetes. The survey showed that participants found FRADA easy to use and would consider using FRADA daily. The analysis of the qualitative data from interviews revealed multiple categories, such as the usability of FRADA, potential benefits of using FRADA, potential features to be added to FRADA, and concerns of older adults with diabetes regarding interactions with FRADA. Conclusions: This study demonstrates in a lab-based setting not only the usability of FRADA by older adults with diabetes but also potential opportunities using FRADA in real-world settings. The findings suggest implications for creating a smartphone app for an image-assisted dietary assessment. Future work still remains to evaluate the feasibility and validity of FRADA with multiple stakeholders, including older adults with diabetes and dietitians. %M 33493129 %R 10.2196/14760 %U http://formative.jmir.org/2021/2/e14760/ %U https://doi.org/10.2196/14760 %U http://www.ncbi.nlm.nih.gov/pubmed/33493129 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 6 %N 1 %P e23687 %T Application of the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies in Assessing Mobile-Delivered Technologies for the Self-Management of Type 2 Diabetes Mellitus: Scoping Review %A Forsyth,Jessica R %A Chase,Hannah %A Roberts,Nia W %A Armitage,Laura C %A Farmer,Andrew J %+ Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617942, laura.armitage@phc.ox.ac.uk %K type 2 diabetes %K health technology %K self-management %K mobile health %K mobile applications %K guidelines %D 2021 %7 16.2.2021 %9 Review %J JMIR Diabetes %G English %X Background: There is a growing role of digital health technologies (DHTs) in the management of chronic health conditions, specifically type 2 diabetes. It is increasingly important that health technologies meet the evidence standards for health care settings. In 2019, the National Institute for Health and Care Excellence (NICE) published the NICE Evidence Standards Framework for DHTs. This provides guidance for evaluating the effectiveness and economic value of DHTs in health care settings in the United Kingdom. Objective: The aim of this study is to assess whether scientific articles on DHTs for the self-management of type 2 diabetes mellitus report the evidence suggested for implementation in clinical practice, as described in the NICE Evidence Standards Framework for DHTs. Methods: We performed a scoping review of published articles and searched 5 databases to identify systematic reviews and primary studies of mobile device–delivered DHTs that provide self-management support for adults with type 2 diabetes mellitus. The evidence reported within articles was assessed against standards described in the NICE framework. Results: The database search yielded 715 systematic reviews, of which, 45 were relevant and together included 59 eligible primary studies. Within these, there were 39 unique technologies. Using the NICE framework, 13 technologies met best practice standards, 3 met minimum standards only, and 23 technologies did not meet minimum standards. Conclusions: On the assessment of peer-reviewed publications, over half of the identified DHTs did not appear to meet the minimum evidence standards recommended by the NICE framework. The most common reasons for studies of DHTs not meeting these evidence standards included the absence of a comparator group, no previous justification of sample size, no measurable improvement in condition-related outcomes, and a lack of statistical data analysis. This report provides information that will enable researchers and digital health developers to address these limitations when designing, delivering, and reporting digital health technology research in the future. %M 33591278 %R 10.2196/23687 %U http://diabetes.jmir.org/2021/1/e23687/ %U https://doi.org/10.2196/23687 %U http://www.ncbi.nlm.nih.gov/pubmed/33591278 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 2 %P e23477 %T Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review %A Eberle,Claudia %A Löhnert,Maxine %A Stichling,Stefanie %+ Medicine with Specialization in Internal Medicine and General Medicine, Hochschule Fulda–University of Applied Sciences, Leipziger Strasse 123, Fulda, 36037, Germany, 49 661 9649 ext 6328, claudia.eberle@hs-fulda.de %K diabetes mellitus %K mobile apps %K mHealth apps %K medical apps %D 2021 %7 15.2.2021 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited. Objective: The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM. Methods: A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c). Results: In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of –0.54% (95% CI –0.8 to –0.28) for T2DM and –0.63% (95% CI –0.93 to –0.32) for T1DM. Conclusions: DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail. %M 33587045 %R 10.2196/23477 %U http://mhealth.jmir.org/2021/2/e23477/ %U https://doi.org/10.2196/23477 %U http://www.ncbi.nlm.nih.gov/pubmed/33587045 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 9 %N 2 %P e23338 %T Efficiency of an mHealth App and Chest-Wearable Remote Exercise Monitoring Intervention in Patients With Type 2 Diabetes: A Prospective, Multicenter Randomized Controlled Trial %A Li,Jing %A Wei,Dong %A Liu,Shuyi %A Li,Mingxia %A Chen,Xi %A Chen,Li %A Wu,Yuelei %A Zhou,Wen %A Ouyang,Lingyun %A Tan,Cuixia %A Meng,Hongdao %A Tong,Nanwei %+ Department of Endocrinology and Metabolism, West China Hospital of Sichuan University, 37 Guoxue Road, Wuhou District, Chengdu, 610041, China, 86 18980601196, tongnw@scu.edu.cn %K type 2 diabetes %K fitness app %K heart rate band %K exercise monitoring %K randomized controlled trial %K mobile phone %D 2021 %7 9.2.2021 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Exercise has been recommended as a cornerstone for diabetes management. Supervised exercise is more efficient than unsupervised exercise but is less convenient and accessible. Objective: We aimed to determine the efficiency of exercise using a fitness app and heart rate band to remotely monitor patients with type 2 diabetes in comparison with that of traditional exercise. Methods: Patients with type 2 diabetes without severe complications or comorbidities were recruited to participate in this multicenter randomized controlled trial and were allocated to either the intervention or control group (1:1 ratio). Participants in both groups were asked to engage in moderate to vigorous physical activity for at least 150 minutes per week; each participant was prescribed individualized exercises. Participants in the intervention group were asked to follow exercise videos on the app and to wear a chest band; heart rate, exercise duration, and exercise intensity were recorded by the app. Participants in the control group self-reported exercise intensity and duration. Cardiopulmonary endurance, body composition, blood glucose level, and insulin level were assessed before and after a 3-month exercise program. Results: Of the 101 participants who were enrolled, the majority of them (85/101, 84.2%) completed the study. Both groups had similar baseline characteristics, with the exception that participants in the intervention group were slightly younger and less likely to have hypertension. Self-reported exercise duration was longer than app-recorded exercise duration (control: mean 214 minutes/week; intervention: mean 193 minutes/week); in addition, a higher proportion of participants in the control group (29/41, 71%) than in the intervention group (18/44, 41%) met the 150-minute target for moderate to vigorous physical activity. However, compared with the control group, the intervention group had a larger increase in cardiopulmonary endurance (mean difference –2.0 bpm [beats per minute] vs 1.0 bpm; P=.02) and a larger decrease in body fat percentage (mean difference –1.8% vs –0.8%; P=.01). There was no difference in hemoglobin A1c level reduction between the two groups, yet more participants in the intervention group stopped taking their antidiabetic drugs or had their dosages lowered by an endocrinologist, compared with those in the control group. There were no serious adverse events in either group. Conclusions: This was the first randomized controlled trial in China, to our knowledge, to test the efficiency of exercise using a fitness app and heart rate band to remotely monitor prescribed exercise in patients with type 2 diabetes. The findings of our study suggest that exercise programs may be more efficient if participants are remotely monitored with an app and heart rate band than if participants are not monitored. Trial Registration: Chinese Clinical Trial Register ChiCTR1800015963; http://www.chictr.org.cn/showprojen.aspx?proj=27080 %M 33560244 %R 10.2196/23338 %U https://mhealth.jmir.org/2021/2/e23338 %U https://doi.org/10.2196/23338 %U http://www.ncbi.nlm.nih.gov/pubmed/33560244 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e17537 %T General Behavioral Engagement and Changes in Clinical and Cognitive Outcomes of Patients with Type 2 Diabetes Using the Time2Focus Mobile App for Diabetes Education: Pilot Evaluation %A Batch,Bryan C %A Spratt,Susan E %A Blalock,Dan V %A Benditz,Chad %A Weiss,Andi %A Dolor,Rowena J %A Cho,Alex H %+ Division of Endocrinology, Metabolism and Nutrition, Duke University School of Medicine, DUMC 3031, Durham, NC, 27710, United States, 1 919 684 4005, bryan.batch@duke.edu %K mobile technology %K diabetes %K self management support %K self efficacy %K illness perception %D 2021 %7 20.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Type 2 diabetes affects 30 million Americans, representing a significant cause of morbidity and mortality. Self-management support is an important component of chronic illness care and is a key pillar of the chronic care model. Face-to-face teaching and patient education materials suffer from being static or incompatible with mobile lifestyles. Digital apps provide a self-management support alternative that is convenient and scalable. Objective: This pilot study tested the real-world deployment of a self-guided mobile app for diabetes education (Time2Focus app; MicroMass Communications Inc, Cary, NC), which utilizes evidence-based content and gamification to deliver an interactive learning experience. Methods: Primary care providers were approached for permission to invite their patients to participate. Eligible patients were 18 to 89 years of age, had a diagnosis of type 2 diabetes, hemoglobin A1c (HbA1c) ≥8% and <12% in the past 3 months, an active online patient portal account (tied to the electronic health record), and access to an iOS or Android smartphone. Interested patients were emailed a baseline survey, and once this was completed, were sent instructions for downloading the Time2Focus app. After completing all 12 levels, participants were sent a follow-up survey. The primary outcome was the change in HbA1c. Secondary outcomes included medication adherence, self-care activities, self-reporting of physical activities, diabetes self-efficacy, illness perceptions, diabetes distress scale, and users’ engagement with and rating of the app. Results: Of 1355 potentially eligible patients screened, 201 were consented. Of these 201 patients, 101 (50.2%) did not download the app. Of the 100 participants (49.8%) who downloaded the app, 16 (16.0%) completed 0 levels, 26 (26.0%) completed 1 to 4 levels, 10 (10.0%) completed 5 to 11 levels, and 48 (48.0%) completed all 12 levels of the app and the follow-up survey. Those completing one or more levels had a mean pre/post-HbA1c change of –0.41% (compared to –0.32% among those who completed zero levels); however, the unadjusted two-tailed t test indicated no significant difference between the two groups (P=.73). Diabetes self-efficacy showed a large and significant increase during app usage for completers (mean change 1.28, P<.001, d=.83). Severity of illness perceptions showed a small but significant decrease during app usage for completers (mean change –0.51, P=.004, d=.43). Diabetes distress showed a small but significant decrease during app usage for completers (mean change –0.45, P=.006, d=.41). The net promoter score was 62.5, indicating that those who completed all levels of the app rated it highly and would recommend it to others. Conclusions: Participants who engaged in all 12 levels of the Time2Focus mobile app showed an improvement in diabetes self-efficacy and a decrease in severity of illness perceptions. The decrease in HbA1c observed in app users relative to nonusers during this limited pilot study was not statistically significant. However, uptake and application of lessons learned from self-management support may be delayed. Further research is needed to address how to increase engagement through self-management support and to investigate if follow up over a longer period demonstrates a significant change in outcomes such as HbA1c. %M 33470947 %R 10.2196/17537 %U http://www.jmir.org/2021/1/e17537/ %U https://doi.org/10.2196/17537 %U http://www.ncbi.nlm.nih.gov/pubmed/33470947 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 6 %N 1 %P e16146 %T Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps %A Flors-Sidro,José Javier %A Househ,Mowafa %A Abd-Alrazaq,Alaa %A Vidal-Alaball,Josep %A Fernandez-Luque,Luis %A Sanchez-Bocanegra,Carlos Luis %+ Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Education City, Doha, , Qatar, 974 55708549, aabdalrazaq@hbku.edu.qa %K diabetes mellitus %K privacy %K mobile apps %K dangerous permissions %D 2021 %7 13.1.2021 %9 Original Paper %J JMIR Diabetes %G English %X Background: Mobile health has become a major vehicle of support for people living with diabetes. Accordingly, the availability of mobile apps for diabetes has been steadily increasing. Most of the previous reviews of diabetes apps have focused on the apps’ features and their alignment with clinical guidelines. However, there is a lack of knowledge on the actual compliance of diabetes apps with privacy and data security guidelines. Objective: The aim of this study was to assess the levels of privacy of mobile apps for diabetes to contribute to the raising of awareness of privacy issues for app users, developers, and governmental data protection regulators. Methods: We developed a semiautomatic app search module capable of retrieving Android apps’ privacy-related information, particularly the dangerous permissions required by apps, with the aim of analyzing privacy aspects related to diabetes apps. Following the research selection criteria, the original 882 apps were narrowed down to 497 apps that were included in the analysis. Results: Approximately 60% of the analyzed diabetes apps requested potentially dangerous permissions, which pose a significant risk to users’ data privacy. In addition, 28.4% (141/497) of the apps did not provide a website for their privacy policy. Moreover, it was found that 40.0% (199/497) of the apps contained advertising, and some apps that claimed not to contain advertisements actually did. Ninety-five percent of the apps were free, and those belonging to the “medical” and “health and fitness” categories were the most popular. However, app users do not always realize that the free apps’ business model is largely based on advertising and, consequently, on sharing or selling their private data, either directly or indirectly, to unknown third parties. Conclusions: The aforementioned findings confirm the necessity of educating patients and health care providers and raising their awareness regarding the privacy aspects of diabetes apps. Therefore, this research recommends properly and comprehensively training users, ensuring that governments and regulatory bodies enforce strict data protection laws, devising much tougher security policies and protocols in Android and in the Google Play Store, and implicating and supervising all stakeholders in the apps’ development process. %M 33439129 %R 10.2196/16146 %U http://diabetes.jmir.org/2021/1/e16146/ %U https://doi.org/10.2196/16146 %U http://www.ncbi.nlm.nih.gov/pubmed/33439129 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 1 %P e21727 %T Evaluation of Self-Care Activities and Quality of Life in Patients With Type 2 Diabetes Mellitus Treated With Metformin Using the 2D Matrix Code of Outer Drug Packages as Patient Identifier: Protocol for the DePRO Proof-of-Concept Observational Study %A Mueller,Christian %A Schauerte,Isabel %A Martin,Stephan %+ Pharmaceuticals Medicine, Pharmaceuticals, Medical Excellence & Innovation Management, Data Generation, Bayer Vital GmbH, Building K 56, 1D321, Leverkusen, 51368, Germany, 49 214 30 46587, christian.mueller4@bayer.com %K self-care activities %K quality of life %K type 2 diabetes mellitus %K patient-reported outcome measures %K digital observational study %K bring your own device %D 2021 %7 11.1.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Diabetes mellitus (DM) is one of the most common noncommunicable diseases. DM has a substantial negative impact on patients’ quality of life, which is measured using a variety of diabetes-specific measures covering multiple aspects of patients’ psychological state, behavior, and treatment satisfaction. A fully digital data collection system, including patient identification, would represent a substantial advance in how these patient-reported outcome (PRO) data are measured. Within the European Union, one way to identify patients without the involvement of health care professionals is to use the unique 2D matrix codes on the packaging of prescription medication—for example, metformin, the recommended initial treatment for patients with type 2 DM (T2DM). Objective: In the DePRO study we aim to (1) describe the self-care activities of patients with T2DM using metformin-containing medication; (2) describe the self-reported health status (eg, presence of diabetes complications and quality of life) of these patients; (3) describe associations between self-care activities and demographics and disease characteristics; and (4) assess the usability of the my ePRO app. Methods: DePRO is an observational, multicenter, cross-sectional, digital, patient-driven study conducted in Germany. Patients with a prescription for a metformin-containing medication will be given a postcard by their pharmacist, which will include a download link for the my ePRO app. In total, 12 diabetes-focused pharmacies, selected to represent urban and rural areas, will be recruited. Participants will use their own mobile device (bring your own device) to download the my ePRO app and access the DePRO study, for which they can register using the 2D matrix code on their medication. An electronic informed consent form will be displayed to the patients and only after giving consent will patients be able to complete the study questionnaires. The PRO instruments used in the study are the Summary of Diabetes Self-Care Activities Scale, the Diabetes Treatment Satisfaction Questionnaire, and the 5 level, 5-dimension EuroQol Questionnaire. Patients will also be asked to complete a questionnaire with items addressing demographics, patient characteristics, disease history, complications, and concomitant medications. Data will be transferred to the study database by the app upon completion of each questionnaire. Statistical analyses of primary and secondary endpoints will be exploratory and descriptive. Results: Enrollment began in June 2020. The estimated study completion date is December 31, 2020, and the planned sample size is 300 patients. Conclusions: The DePRO study uses completely digital data collection, including authentication of eligible patients and completion of the study questionnaires. Therefore, the design of the DePRO study represents a substantial advance in the evaluation of the digital capturing of PRO data. Trial Registration: ClinicalTrials.gov NCT04383041; https://clinicaltrials.gov/ct2/show/NCT04383041 International Registered Report Identifier (IRRID): PRR1-10.2196/21727 %M 33427685 %R 10.2196/21727 %U http://www.researchprotocols.org/2021/1/e21727/ %U https://doi.org/10.2196/21727 %U http://www.ncbi.nlm.nih.gov/pubmed/33427685 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 4 %P e19650 %T Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study %A Alhodaib,Hala Ibrahim %A Antza,Christina %A Chandan,Joht Singh %A Hanif,Wasim %A Sankaranarayanan,Sailesh %A Paul,Sunjay %A Sutcliffe,Paul %A Nirantharakumar,Krishnarajah %+ Division of Health Sciences, Warwick Medical School, University of Warwick, Medical School Building, Coventry, CV4 7AL, United Kingdom, 44 2476 574505, P.A.Sutcliffe@warwick.ac.uk %K eHealth %K clinical decision support application %K diabetes mellitus %K chronic kidney disease %K feasibility study %D 2020 %7 18.11.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: Attempts to utilize eHealth in diabetes mellitus (DM) management have shown promising outcomes, mostly targeted at patients; however, few solutions have been designed for health care providers. Objective: The purpose of this study was to conduct a feasibility project developing and evaluating a mobile clinical decision support system (CDSS) tool exclusively for health care providers to manage chronic kidney disease (CKD) in patients with DM. Methods: The design process was based on the 3 key stages of the user-centered design framework. First, an exploratory qualitative study collected the experiences and views of DM specialist nurses regarding the use of mobile apps in clinical practice. Second, a CDSS tool was developed for the management of patients with DM and CKD. Finally, a randomized controlled trial examined the acceptability and impact of the tool. Results: We interviewed 15 DM specialist nurses. DM specialist nurses were not currently using eHealth solutions in their clinical practice, while most nurses were not even aware of existing medical apps. However, they appreciated the potential benefits that apps may bring to their clinical practice. Taking into consideration the needs and preferences of end users, a new mobile CDSS app, “Diabetes & CKD,” was developed based on guidelines. We recruited 39 junior foundation year 1 doctors (44% male) to evaluate the app. Of them, 44% (17/39) were allocated to the intervention group, and 56% (22/39) were allocated to the control group. There was no significant difference in scores (maximum score=13) assessing the management decisions between the app and paper-based version of the app’s algorithm (intervention group: mean 7.24 points, SD 2.46 points; control group: mean 7.39, SD 2.56; t37=–0.19, P=.85). However, 82% (14/17) of the participants were satisfied with using the app. Conclusions: The findings will guide the design of future CDSS apps for the management of DM, aiming to help health care providers with a personalized approach depending on patients’ comorbidities, specifically CKD, in accordance with guidelines. %M 33206055 %R 10.2196/19650 %U https://diabetes.jmir.org/2020/4/e19650 %U https://doi.org/10.2196/19650 %U http://www.ncbi.nlm.nih.gov/pubmed/33206055 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 11 %P e22212 %T Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study %A Böhm,Anna-Katharina %A Jensen,Morten Lind %A Sørensen,Mads Reinholdt %A Stargardt,Tom %+ Hamburg Center for Health Economics, University of Hamburg, Esplanade 36, Hamburg, 20354, Germany, 49 40428381627, Anna-Katharina.Boehm@uni-hamburg.de %K user engagement %K user activity %K mHealth %K diabetes mellitus %K diabetes apps %D 2020 %7 6.11.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Patient support apps have risen in popularity and provide novel opportunities for self-management of diabetes. Such apps offer patients to play an active role in monitoring their condition, thereby increasing their own treatment responsibility. Although many health apps require active user engagement to be effective, there is little evidence exploring engagement with mobile health (mHealth). Objective: This study aims to analyze the extent to which users engage with mHealth for diabetes and identify patient characteristics that are associated with engagement. Methods: The analysis is based on real-world data obtained by Novo Nordisk’s Cornerstones4Care Powered by Glooko diabetes support app. User engagement was assessed as the number of active days and using measures expressing the persistence, longevity, and regularity of interaction within the first 180 days of use. Beta regressions were estimated to assess the associations between user characteristics and engagement outcomes for each module of the app. Results: A total of 9051 individuals initiated use after registration and could be observed for 180 days. Among these, 55.39% (5013/9051) used the app for one specific purpose. The average user activity ratio varied from 0.05 (medication and food) to 0.55 (continuous glucose monitoring), depending on the module of the app. Average user engagement was lower if modules required manual data entries, although the initial uptake was higher for these modules. Regression analyses further revealed that although more women used the app (2075/3649, 56.86%), they engaged significantly less with it. Older people and users who were recently diagnosed tended to use the app more actively. Conclusions: Strategies to increase or sustain the use of apps and availability of health data may target the mode of data collection and content design and should take into account privacy concerns of the users at the same time. Users’ engagement was determined by various user characteristics, indicating that particular patient groups should be targeted or assisted when integrating apps into the self-management of their disease. %M 32975198 %R 10.2196/22212 %U http://mhealth.jmir.org/2020/11/e22212/ %U https://doi.org/10.2196/22212 %U http://www.ncbi.nlm.nih.gov/pubmed/32975198 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 11 %P e19869 %T A Mobile-Based Intervention for Dietary Behavior and Physical Activity Change in Individuals at High Risk for Type 2 Diabetes Mellitus: Randomized Controlled Trial %A Xu,Zidu %A Geng,Ji %A Zhang,Shuai %A Zhang,Kexin %A Yang,Lin %A Li,Jing %A Li,Jiao %+ School of Nursing, Peking Union Medical College, No 33, Badachu Road, Shijingshan District, Beijing, 100144, China, 86 1088771124, annelee13@126.com %K transtheoretical model %K type 2 diabetes mellitus %K high risk %K social media %K dietary behavior %K physical activity %D 2020 %7 3.11.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Intensive lifestyle modifications have proved effective in preventing type 2 diabetes mellitus (T2DM), yet the efficiency and effectiveness of these modifications need to be improved. Emerging social media interventions are considered useful in promoting these lifestyles; nevertheless, few studies have investigated the effectiveness of combining them with behavior theory. Objective: This study aims to examine the effectiveness of a 6-month mobile-based intervention (DHealthBar, a WeChat applet) combined with behavioral theory compared with a printed intervention in improving dietary behaviors, physical activity, and intention to change these behaviors among populations at high risk for T2DM. Methods: Participants aged 23 to 67 years were recruited offline in Beijing, China, and were randomized into the intervention group or the control group, which received educational content via DHealthBar or a printed handbook, respectively. Educational materials were culturally tailored recommendations on improving dietary behaviors, physical activity, and intention to change based on the transtheoretical model. Participants in the intervention arm received push notifications twice per week on WeChat and had access to the educational content for the 6-month study period. Participants in the control arm received the same intervention content through printed materials. The outcomes of participants’ behavior change, intention to change behavior, and anthropometric characteristics were collected via online measuring tools at baseline, 3 months, and 6 months. Results: In this study, 79 enrolled individuals completed baseline information collection (control: n=38 vs intervention: n=41), and 96% (76/79) completed the 6-month follow-up visit. Attrition rates did not differ significantly between the 2 groups (χ21=0.0, P=.61). Baseline equivalence was found. Participants in both groups reported a statistically significant decrease in energy intake at the 2 follow-up assessments compared with baseline (3 months, control: exp[β]=0.83, 95% CI 0.74-0.92 vs intervention: exp[β]=0.76, 95% CI 0.68-0.85; 6 months, control: exp[β]=0.87, 95% CI 0.78-0.96 vs intervention: exp[β]=0.57, 95% CI 0.51-0.64). At 6 months, a significantly larger decrease was observed in the intervention group in energy, fat, and carbohydrate intake, accompanied with a significantly larger increase in moderate-intensity physical activity compared with the control group (energy: exp[β]=0.66, 95% CI 0.56-0.77; fat: exp[β]=0.71, 95% CI 0.54-0.95; carbohydrates: exp[β]=0.83, 95% CI 0.66-1.03; moderate-intensity physical activity: exp[β]=2.05, 95% CI 1.23-3.44). After 6 months of the intervention, participants in the intervention group were more likely to be at higher stages of dietary behaviors (exp[β]=26.80, 95% CI 3.51-204.91) and physical activity (exp[β]=15.60, 95% CI 2.67-91.04) than the control group. Conclusions: DHealthBar was initially effective in improving dietary behavior, physical activity, and intention to change these behaviors among populations who were at high risk of developing T2DM, with significant differences in the changes of outcomes over the 6-month intervention period. Trial Registration: Chinese Clinical Trial Registry ChiCTR2000032323; https://tinyurl.com/y4h8q4uf %M 33141092 %R 10.2196/19869 %U https://mhealth.jmir.org/2020/11/e19869 %U https://doi.org/10.2196/19869 %U http://www.ncbi.nlm.nih.gov/pubmed/33141092 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 11 %P e18922 %T Effectiveness of Internet-Based Multicomponent Interventions for Patients and Health Care Professionals to Improve Clinical Outcomes in Type 2 Diabetes Evaluated Through the INDICA Study: Multiarm Cluster Randomized Controlled Trial %A Ramallo-Fariña,Yolanda %A García-Bello,Miguel Angel %A García-Pérez,Lidia %A Boronat,Mauro %A Wägner,Ana M %A Rodríguez-Rodríguez,Leticia %A de Pablos-Velasco,Pedro %A Llorente Gómez de Segura,Ignacio %A González- Pacheco,Himar %A Carmona Rodríguez,Montserrat %A Serrano-Aguilar,Pedro %A , %+ Canary Islands Health Research Institute Foundation (FIISC), Camino La Candelaria 44, Tenerife, 38109, Spain, 34 +34 922 478266, yramfar@sescs.es %K behavior modification %K primary care %K type 2 diabetes mellitus %K patients adherence %K eHealth %D 2020 %7 2.11.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Type 2 diabetes mellitus (T2DM) is a chronic disease in which health outcomes are related to decision making by patients and health care professionals. Objective: This study aims to assess the effectiveness of internet-based multicomponent interventions to support decision making of all actors involved in the care of patients with T2DM in primary care. Methods: The INDICA study is an open, community-based, multicenter trial with random allocation to usual care or the intervention for patients, the intervention for health care professionals in primary care, or the combined intervention for both. In the intervention for patients, participants received an educational group program and were monitored and supported by logs, a web-based platform, and automated SMS. Those in the intervention for professionals also received an educational program, a decision support tool embedded in the electronic clinical record, and periodic feedback about patients’ results. A total of 2334 people with T2DM, regardless of glycated hemoglobin (HbA1c) levels and without diabetes-related complications, were included. The primary end point was change in HbA1c level. The main analysis was performed using multilevel mixed models. Results: For the overall sample, the intervention for patients attained a significant mean reduction in HbA1c levels of ‒0.27 (95% CI ‒0.45 to ‒0.10) at month 3 and ‒0.26 (95% CI ‒0.44 to ‒0.08) at month 6 compared with usual care, which remained marginally significant at month 12. A clinically relevant reduction in HbA1c level was observed in 35.6% (191/537) of patients in the intervention for patients and 26.0% (152/586) of those in usual care at month 12 (P=.006). In the combined intervention, HbA1c reduction was significant until month 18 (181/557, 32.6% vs 140/586, 23.9%; P=.009). Considering the subgroup of patients uncontrolled at baseline, all interventions produced significant reductions in HbA1c levels across the entire study period: ‒0.49 (95% CI ‒0.70 to ‒0.27) for the intervention for patients, ‒0.35 (95% CI ‒0.59 to ‒0.14) for the intervention for professionals, and ‒0.35 (95% CI ‒0.57 to ‒0.13) for the combined intervention. Differences in HbA1c for the area under the curve considering the entire period were significant for the intervention for patients and the combined intervention compared with usual care (P=.03 for both). Compared with usual care, the intervention for professionals and the combined intervention had significant longer-term reductions in systolic and diastolic blood pressure. Conclusions: In uncontrolled patients, the intervention for patients at baseline provided clinically relevant and significant longer-term reductions of HbA1c levels. The intervention for professionals and combined intervention also improved the cardiovascular risk profile of patients. Trial Registration: ClinicalTrials.gov NCT01657227; https://clinicaltrials.gov/ct2/show/NCT01657227 %M 33136059 %R 10.2196/18922 %U https://mhealth.jmir.org/2020/11/e18922 %U https://doi.org/10.2196/18922 %U http://www.ncbi.nlm.nih.gov/pubmed/33136059 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e20353 %T New Checklist for the Heuristic Evaluation of mHealth Apps (HE4EH): Development and Usability Study %A Khowaja,Kamran %A Al-Thani,Dena %+ Information & Computing Technology, College of Science & Engineering, Hamad Bin Khalifa University, LAS Building, Education City, Doha, , Qatar, 974 66314481, kamran.khowaja@gmail.com %K mHealth %K eHealth %K heuristic evaluation %K expert evaluation %K self-monitoring %K behavior change %K design guidelines %K framework %D 2020 %7 28.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes is one of the leading causes of death in developing countries. Existing mobile health (mHealth) app design guidelines lack a description of the support of continuous self-monitoring of health status, behavior change to improve and adopt a healthy lifestyle, and communication with health educators and health care professionals in case of any need. Objective: This paper presents the development of a specialized set of heuristics called heuristic evaluation for mHealth apps (HE4EH) as an all-in-one tool and its applicability by performing a heuristic evaluation of an mHealth app. Methods: An extensive review of heuristics and checklists was used to develop the HE4EH. The HE4EH was evaluated by domain experts for heuristics, checklist items, severity ratings, and overall satisfaction. The OneTouch app, which helps individuals with diabetes manage their blood glucose levels, was evaluated using HE4EH to identify usability problems that need to be fixed in the app. Results: The expert evaluation of HE4EH revealed that the heuristics were important, relevant, and clear. The checklist items across the heuristics were clear, relevant, and acceptably grouped. In terms of evaluating the OneTouch app using the HE4EH, the most frequently violated heuristics included Content, Visibility, Match, and Self-monitoring. Most of the usability problems found were minor. The system usability scale score indicated that the OneTouch app is marginally acceptable. Conclusions: This heuristic evaluation using the OneTouch app shows that the HE4EH can play a vital role for designers, researchers, and practitioners to use HE4EH heuristics and checklist items as a tool to design a new or evaluate and improve an existing mHealth app. %M 33112252 %R 10.2196/20353 %U http://mhealth.jmir.org/2020/10/e20353/ %U https://doi.org/10.2196/20353 %U http://www.ncbi.nlm.nih.gov/pubmed/33112252 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 10 %P e22074 %T Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial %A Alfonsi,Jeffrey E %A Choi,Elizabeth E Y %A Arshad,Taha %A Sammott,Stacie-Ann S %A Pais,Vanita %A Nguyen,Cynthia %A Maguire,Bryan R %A Stinson,Jennifer N %A Palmert,Mark R %+ Department of Medicine, Schulich School of Medicine & Dentistry, Western University, 1151 Richmond St, Clinical Skills Building, London, ON, N6A 3K7, Canada, 1 647 938 3669, j.alfonsi@utoronto.ca %K carbohydrate counting %K type 1 diabetes %K image recognition %K youth %K digital health applications (apps) %K mHealth %D 2020 %7 28.10.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Carbohydrate counting is an important component of diabetes management, but it is challenging, often performed inaccurately, and can be a barrier to optimal diabetes management. iSpy is a novel mobile app that leverages machine learning to allow food identification through images and that was designed to assist youth with type 1 diabetes in counting carbohydrates. Objective: Our objective was to test the app's usability and potential impact on carbohydrate counting accuracy. Methods: Iterative usability testing (3 cycles) was conducted involving a total of 16 individuals aged 8.5-17.0 years with type 1 diabetes. Participants were provided a mobile device and asked to complete tasks using iSpy app features while thinking aloud. Errors were noted, acceptability was assessed, and refinement and retesting were performed across cycles. Subsequently, iSpy was evaluated in a pilot randomized controlled trial with 22 iSpy users and 22 usual care controls aged 10-17 years. Primary outcome was change in carbohydrate counting ability over 3 months. Secondary outcomes included levels of engagement and acceptability. Change in HbA1c level was also assessed. Results: Use of iSpy was associated with improved carbohydrate counting accuracy (total grams per meal, P=.008), reduced frequency of individual counting errors greater than 10 g (P=.047), and lower HbA1c levels (P=.03). Qualitative interviews and acceptability scale scores were positive. No major technical challenges were identified. Moreover, 43% (9/21) of iSpy participants were still engaged, with usage at least once every 2 weeks, at the end of the study. Conclusions: Our results provide evidence of efficacy and high acceptability of a novel carbohydrate counting app, supporting the advancement of digital health apps for diabetes care among youth with type 1 diabetes. Further testing is needed, but iSpy may be a useful adjunct to traditional diabetes management. Trial Registration: ClinicalTrials.gov NCT04354142; https://clinicaltrials.gov/ct2/show/NCT04354142 %M 33112249 %R 10.2196/22074 %U http://mhealth.jmir.org/2020/10/e22074/ %U https://doi.org/10.2196/22074 %U http://www.ncbi.nlm.nih.gov/pubmed/33112249 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 9 %P e17135 %T Development and Evaluation of a Tailored Mobile Health Intervention to Improve Medication Adherence in Black Patients With Uncontrolled Hypertension and Type 2 Diabetes: Pilot Randomized Feasibility Trial %A Schoenthaler,Antoinette %A Leon,Michelle %A Butler,Mark %A Steinhaeuser,Karsten %A Wardzinski,William %+ Department of Population Health, NYU School of Medicine, Center for Healthful Behavior Change, NYU Langone Health, 180 Madison Ave, 7th floor, New York, NY, 10016, United States, 1 6465013434, antoinette.schoenthaler@nyumc.org %K mHealth %K medication adherence %K hypertension %K type 2 diabetes %K African Americans %D 2020 %7 23.9.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Research has underscored the need to develop socioculturally tailored interventions to improve adherence behaviors in minority patients with hypertension (HTN) and type 2 diabetes (T2D). Novel mobile health (mHealth) approaches are potential methods for delivering tailored interventions to minority patients with increased cardiovascular risk. Objective: This study aims to develop and evaluate the acceptability and preliminary efficacy of a tailored mHealth adherence intervention versus attention control (AC) on medication adherence, systolic blood pressure (SBP), diastolic blood pressure (DBP), and hemoglobin A1c (HbA1c) at 3 months in 42 Black patients with uncontrolled HTN and/or T2D who were initially nonadherent to their medications. Methods: This was a two-phase pilot study consisting of a formative phase and a clinical efficacy phase. The formative phase consisted of qualitative interviews with 10 members of the target patient population (7/10, 70% female; mean age 65.8 years, SD 5.6) to tailor the intervention based on the Information-Motivation-Behavioral skills model of adherence. The clinical efficacy phase consisted of a 3-month pilot randomized controlled trial to evaluate the tailored mHealth intervention versus an AC. The tablet-delivered intervention included a tailoring survey, an individualized adherence profile, and a personalized list of interactive adherence-promoting modules, whereas AC included the tailoring survey and health education videos delivered on the tablet. Acceptability was assessed through semistructured exit interviews. Medication adherence was assessed using the 8-item Morisky Medication Adherence Scale, whereas blood pressure and HbA1c were assessed using automated devices. Results: In phase 1, thematic analysis of the semistructured interviews revealed the following 5 major barriers to adherence: disruptions in daily routine, forgetfulness, concerns about adverse effects, preference for natural remedies, and burdens of medication taking. Patients recommended the inclusion of modules that address improving patient-provider communication, peer vignettes, and stress reduction strategies to facilitate adherence. A total of 42 Black patients (23/42, 55% male; mean age 57.6 years, SD 11.1) participated in the clinical efficacy pilot trial. At 3 months, both groups showed significant improvements in adherence (mean 1.35, SD 1.60; P<.001) and SBP (−4.76 mm Hg; P=.04) with no between-group differences (P=.50 and P=.10). The decreases in DBP and HbA1c over time were nonsignificant (−1.97 mm Hg; P=.20; and −0.2%; P=.45, respectively). Patients reported high acceptability of the intervention for improving their adherence. Conclusions: This pilot study demonstrated preliminary evidence on the acceptability of a tailored mHealth adherence intervention among a sample of Black patients with uncontrolled HTN and T2D who were initially nonadherent to their medications. Future research should explore whether repeated opportunities to use the mHealth intervention would result in improvements in behavioral and clinical outcomes over time. Modifications to the intervention as a result of the pilot study should guide future efforts. Trial Registration: ClinicalTrials.gov NCT01643473; http://clinicaltrials.gov/ct2/show/ NCT01643473 %M 32965230 %R 10.2196/17135 %U http://mhealth.jmir.org/2020/9/e17135/ %U https://doi.org/10.2196/17135 %U http://www.ncbi.nlm.nih.gov/pubmed/32965230 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 3 %P e18660 %T The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study %A Kriventsov,Stan %A Lindsey,Alexander %A Hayeri,Amir %+ Bio Conscious Technologies Inc, 555 W Hastings St, Suite #1200, Vancouver, BC, V6B 4N6, Canada, 1 604 729 4747, stan@bioconscious.tech %K blood glucose predictions %K type 1 diabetes %K artificial intelligence %K machine learning %K digital health %K mobile phone %D 2020 %7 22.9.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: Diabetes mellitus, which causes dysregulation of blood glucose in humans, is a major public health challenge. Patients with diabetes must monitor their glycemic levels to keep them in a healthy range. This task is made easier by using continuous glucose monitoring (CGM) devices and relaying their output to smartphone apps, thus providing users with real-time information on their glycemic fluctuations and possibly predicting future trends. Objective: This study aims to discuss various challenges of predictive monitoring of glycemia and examines the accuracy and blood glucose control effects of Diabits, a smartphone app that helps patients with diabetes monitor and manage their blood glucose levels in real time. Methods: Using data from CGM devices and user input, Diabits applies machine learning techniques to create personalized patient models and predict blood glucose fluctuations up to 60 min in advance. These predictions give patients an opportunity to take pre-emptive action to maintain their blood glucose values within the reference range. In this retrospective observational cohort study, the predictive accuracy of Diabits and the correlation between daily use of the app and blood glucose control metrics were examined based on real app users’ data. Moreover, the accuracy of predictions on the 2018 Ohio T1DM (type 1 diabetes mellitus) data set was calculated and compared against other published results. Results: On the basis of more than 6.8 million data points, 30-min Diabits predictions evaluated using Parkes Error Grid were found to be 86.89% (5,963,930/6,864,130) clinically accurate (zone A) and 99.56% (6,833,625/6,864,130) clinically acceptable (zones A and B), whereas 60-min predictions were 70.56% (4,843,605/6,864,130) clinically accurate and 97.49% (6,692,165/6,864,130) clinically acceptable. By analyzing daily use statistics and CGM data for the 280 most long-standing users of Diabits, it was established that under free-living conditions, many common blood glucose control metrics improved with increased frequency of app use. For instance, the average blood glucose for the days these users did not interact with the app was 154.0 (SD 47.2) mg/dL, with 67.52% of the time spent in the healthy 70 to 180 mg/dL range. For days with 10 or more Diabits sessions, the average blood glucose decreased to 141.6 (SD 42.0) mg/dL (P<.001), whereas the time in euglycemic range increased to 74.28% (P<.001). On the Ohio T1DM data set of 6 patients with type 1 diabetes, 30-min predictions of the base Diabits model had an average root mean square error of 18.68 (SD 2.19) mg/dL, which is an improvement over the published state-of-the-art results for this data set. Conclusions: Diabits accurately predicts future glycemic fluctuations, potentially making it easier for patients with diabetes to maintain their blood glucose in the reference range. Furthermore, an improvement in glucose control was observed on days with more frequent Diabits use. %M 32960180 %R 10.2196/18660 %U http://diabetes.jmir.org/2020/3/e18660/ %U https://doi.org/10.2196/18660 %U http://www.ncbi.nlm.nih.gov/pubmed/32960180 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 9 %P e16745 %T One Drop App With an Activity Tracker for Adults With Type 1 Diabetes: Randomized Controlled Trial %A Osborn,Chandra Y %A Hirsch,Ashley %A Sears,Lindsay E %A Heyman,Mark %A Raymond,Jennifer %A Huddleston,Brian %A Dachis,Jeff %+ Lirio, 901 Woodland Street, Nashville, TN, 37206, United States, 1 8604242858, cosborn@lirio.co %K diabetes %K type 1 diabetes %K digital therapy %K mobile app %K coaching %K glucometer %K activity tracker %D 2020 %7 17.9.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In 2017, mobile app support for managing diabetes was available to 64% of the global population of adults with diabetes. One Drop’s digital therapeutics solution includes an evidence-based mobile app with global reach, a Bluetooth-connected glucometer, and in-app coaching from Certified Diabetes Educators. Among people with type 1 diabetes and an estimated hemoglobin A1c level≥7.5%, using One Drop for 3 months has been associated with an improved estimated hemoglobin A1c level of 22.2 mg/dL (–0.80%). However, the added value of integrated activity trackers is unknown. Objective: We conducted a pragmatic, remotely administered randomized controlled trial to evaluate One Drop with a new-to-market activity tracker against One Drop only on the 3-month hemoglobin A1c level of adults with type 1 diabetes. Methods: Social media advertisements and online newsletters were used to recruit adults (≥18 years old) diagnosed (≥1 year) with T1D, naïve to One Drop’s full solution and the activity tracker, with a laboratory hemoglobin A1c level≥7%. Participants (N=99) were randomized to receive One Drop and the activity tracker or One Drop only at the start of the study. The One Drop only group received the activity tracker at the end of the study. Multiple imputation, performed separately by group, was used to correct for missing data. Analysis of covariance models, controlling for baseline hemoglobin A1c, were used to evaluate 3-month hemoglobin A1c differences in intent-to-treat (ITT) and per protocol (PP) analyses. Results: The enrolled sample (N=95) had a mean age of 41 (SD 11) years, was 73% female, 88% White, diagnosed for a mean of 20 (SD 11) years, and had a mean hemoglobin A1c level of 8.4% (SD 1.2%); 11% of the participants did not complete follow up. Analysis of covariance assumptions were met for the ITT and PP models. In ITT analysis, participants in the One Drop and activity tracker condition had a significantly lower 3-month hemoglobin A1c level (mean 7.9%, SD 0.60%, 95% CI 7.8-8.2) than that of the participants in the One Drop only condition (mean 8.4%, SD 0.62%, 95% CI 8.2-8.5). In PP analysis, participants in the One Drop and activity tracker condition also had a significantly lower 3-month hemoglobin A1c level (mean 7.9%, SD 0.59%, 95% CI 7.7-8.1) than that of participants in the One Drop only condition (mean 8.2%, SD 0.58%, 95% CI 8.0-8.4). Conclusions: Participants exposed to One Drop and the activity tracker for the 3-month study period had a significantly lower 3-month hemoglobin A1c level compared to that of participants exposed to One Drop only during the same timeframe. One Drop and a tracker may work better together than alone in helping people with type 1 diabetes. Trial Registration: ClinicalTrials.gov NCT03459573; https://clinicaltrials.gov/ct2/show/NCT03459573. %M 32540842 %R 10.2196/16745 %U http://mhealth.jmir.org/2020/9/e16745/ %U https://doi.org/10.2196/16745 %U http://www.ncbi.nlm.nih.gov/pubmed/32540842 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e16053 %T Cost-Effectiveness of a Continuous Glucose Monitoring Mobile App for Patients With Type 2 Diabetes Mellitus: Analysis Simulation %A Tsuji,Shintaro %A Ishikawa,Tomoki %A Morii,Yasuhiro %A Zhang,Hongjian %A Suzuki,Teppei %A Tanikawa,Takumi %A Nakaya,Jun %A Ogasawara,Katsuhiko %+ Graduate School of Health Sciences, Hokkaido University, N12-W5, Kita-ku, Sapporo, 060-0812, Japan, 81 117063409, oga@hs.hokudai.ac.jp %K Markov model %K telehealth %K continuous glucose monitoring (CGM) %K type 2 diabetes mellitus %K cost-effectiveness %K incremental cost and effective ratio (ICER) %D 2020 %7 17.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Apps for real-time continuous glucose monitoring (CGM) on smartphones and other devices linked to CGM systems have recently been developed, and such CGM apps are also coming into use in Japan. In comparison with conventional retrospective CGM, the use of CGM apps improves patients’ own blood glucose control, which is expected to help slow the progression of type 2 diabetes mellitus (DM) and prevent complications, but the effect of their introduction on medical costs remains unknown. Objective: Our objective in this study was to perform an economic appraisal of CGM apps from the viewpoint of assessing public medical costs associated with type 2 DM, using the probability of developing type 2 DM–associated complications, and data on medical costs and utility value to carry out a medical cost simulation using a Markov model in order to ascertain the cost-effectiveness of the apps. Methods: We developed a Markov model with the transition states of insulin therapy, nephrosis, dialysis, and cardiovascular disease, all of which have a major effect on medical costs, to identify changes in medical costs and utility values resulting from the introduction of a CGM app and calculated the incremental cost-effectiveness ratio (ICER). Results: The ICER for CGM app use was US $33,039/quality-adjusted life year (QALY). Conclusions: Sensitivity analyses showed that, with the exception of conditions where the transition probability of insulin therapy, utility value, or increased medical costs increases, the ICER for the introduction of CGM apps was below the threshold of US $43,478/QALY used by the Central Social Insurance Medical Council. Our results provide basic data on the cost-effectiveness of introducing CGM apps, which are currently starting to come into use. %M 32940613 %R 10.2196/16053 %U https://www.jmir.org/2020/9/e16053 %U https://doi.org/10.2196/16053 %U http://www.ncbi.nlm.nih.gov/pubmed/32940613 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 9 %P e17083 %T Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach %A Alenazi,Hanan A %A Jamal,Amr %A Batais,Mohammed A %+ National Health Information Center, Saudi Health Council, Riyadh, 13315, Saudi Arabia, 966 502025959, H.Alenazi@shc.gov.sa %K diabetes %K mobile features %K engagement strategies %K mobile app %K Delphi consensus %D 2020 %7 11.9.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) offers improved and cost-effective care to people with T2DM. However, the efficiency of engagement strategies and features of this technology need to be reviewed and standardized according to stakeholder and expert perspectives. Objective: The main objective of this study was to identify the most agreed-upon features for T2DM self-management mobile apps; the secondary objective was to identify the most agreed-upon strategies that prompt users to use these apps. Methods: In this study, a 4-round modified Delphi method was applied by experts in the domain of diabetes care. Results: In total, 11 experts with a mean age of 47.09 years (SD 11.70) consented to participate in the study. Overall, 36 app features were generated. The group of experts displayed weak agreement in their ranking of intervention components (Kendall W=0.275; P<.001). The top 5 features included insulin dose adjustment according to carbohydrate counting and blood glucose readings (5.36), alerting a caregiver of abnormal or critical readings (6.09), nutrition education (12.45), contacts for guidance if required (12.64), and offering patient-specific education tailored to the user’s goals, needs, and blood glucose readings (12.90). In total, 21 engagement strategies were generated. Overall, the experts showed a moderate degree of consensus in their strategy rankings (Kendall W=0.454; P<.001). The top 5 engagement strategies included a user-friendly design (educational and age-appropriate design; 2.82), a free app (3.73), allowing the user to communicate or send information/data to a health care provider (HCP; 5.36), HCPs prescribing the mobile app in the clinic and asking about patients’ app use compliance during clinical visits (6.91), and flexibility and customization (7.91). Conclusions: This is the first study in the region consisting of a local panel of experts from the diabetes field gathering together. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could thus be useful for health app developers and HCPs and inform future decision making on the topic. %M 32678798 %R 10.2196/17083 %U http://mhealth.jmir.org/2020/9/e17083/ %U https://doi.org/10.2196/17083 %U http://www.ncbi.nlm.nih.gov/pubmed/32678798 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 8 %P e17709 %T Influence of Personality on mHealth Use in Patients with Diabetes: Prospective Pilot Study %A Su,Jingyuan %A Dugas,Michelle %A Guo,Xitong %A Gao,Guodong (Gordon) %+ eHealth Research Institute, School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin, , China, 86 451 86414022, xitongguo@hit.edu.cn %K mHealth %K diabetes %K adoption %K active utilization %K personality traits %K app %D 2020 %7 10.8.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile technology for health (mHealth) interventions are increasingly being used to help improve self-management among patients with diabetes; however, these interventions have not been adopted by a large number of patients and often have high dropout rates. Patient personality characteristics may play a critical role in app adoption and active utilization, but few studies have focused on addressing this question. Objective: This study aims to address a gap in understanding of the relationship between personality traits and mHealth treatment for patients with diabetes. We tested the role of the five-factor model of personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) in mHealth adoption preference and active utilization. Methods: We developed an mHealth app (DiaSocial) aimed to encourage diabetes self-management. We recruited 98 patients with diabetes—each patient freely chose whether to receive the standard care or the mHealth app intervention. Patient demographic information and patient personality characteristics were assessed at baseline. App usage data were collected to measure user utilization of the app. Patient health outcomes were assessed with lab measures of glycated hemoglobin (HbA1c level). Logistic regression models and linear regression were employed to explore factors predicting the relationship between mHealth use (adoption and active utilization) and changes in health outcome. Results: Of 98 study participants, 46 (47%) downloaded and used the app. Relatively younger patients with diabetes were 9% more likely to try and use the app (P=.02, odds ratio [OR] 0.91, 95% CI 0.85-0.98) than older patients with diabetes were. Extraversion was negatively associated with adoption of the mHealth app (P=.04, OR 0.71, 95% CI 0.51-0.98), and openness to experience was positively associated with adoption of the app (P=.03, OR 1.73, 95% CI 1.07-2.80). Gender (P=.43, OR 0.66, 95% CI 0.23-1.88), education (senior: P=.99, OR 1.00, 95% CI 0.32-3.11; higher: P=.21, OR 2.51, 95% CI 0.59-10.66), and baseline HbA1c level (P=.36, OR 0.79, 95% CI 0.47-1.31) were not associated with app adoption. Among those who adopted the app, a low education level (senior versus primary P=.003; higher versus primary P=.03) and a high level of openness to experience (P=.048, OR 2.01, 95% CI 1.01-4.00) were associated with active app utilization. Active users showed a significantly greater decrease in HbA1c level than other users (ΔHbA1c=−0.64, P=.05). Conclusions: This is one of the first studies to investigate how different personality traits influence the adoption and active utilization of an mHealth app among patients with diabetes. The research findings suggest that personality is a factor that should be considered when trying to identify patients who would benefit the most from apps for diabetes management. %M 32773382 %R 10.2196/17709 %U https://mhealth.jmir.org/2020/8/e17709 %U https://doi.org/10.2196/17709 %U http://www.ncbi.nlm.nih.gov/pubmed/32773382 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e17534 %T User Engagement Among Diverse Adults in a 12-Month Text Message–Delivered Diabetes Support Intervention: Results from a Randomized Controlled Trial %A Nelson,Lyndsay A %A Spieker,Andrew %A Greevy,Robert %A LeStourgeon,Lauren M %A Wallston,Kenneth A %A Mayberry,Lindsay S %+ Department of Medicine, Vanderbilt University Medical Center, 2525 West End Ave, Suite 450, Nashville, TN, 37203, United States, 1 6158757621, lyndsay.a.nelson@vumc.org %K engagement %K text messaging %K mobile health %K mHealth %K mobile phone %K technology %K diabetes mellitus, type 2 %K self-management %K self-care %K medication adherence %D 2020 %7 21.7.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Text message–delivered interventions are a feasible and scalable approach for improving chronic disease self-care and reducing health disparities; however, information on long-term user engagement with these interventions is limited. Objective: The aim of this study is to examine user engagement in a 12-month text message–delivered intervention supporting diabetes self-care, called REACH (Rapid Education/Encouragement And Communications for Health), among racially and socioeconomically diverse patients with type 2 diabetes (T2D). We explored time trends in engagement, associations between patient characteristics and engagement, and whether the addition of a human component or allowing patients to change their text frequency affected engagement. Qualitative data informed patients’ subjective experience of their engagement. Methods: We recruited patients with T2D for a randomized trial evaluating mobile phone support relative to enhanced treatment as usual. This analysis was limited to participants assigned to the intervention. Participants completed a survey and hemoglobin A1c (HbA1c) test and received REACH text messages, including self-care promotion texts, interactive texts asking about medication adherence, and adherence feedback texts. For the first 6 months, texts were sent daily, and half of the participants also received monthly phone coaching. After 6 months, coaching stopped, and participants had the option to receive fewer texts for the subsequent 6 months. We defined engagement via responses to the interactive texts and responses to a follow-up interview. We used regression models to analyze associations with response rate and thematic and structural analysis to understand participants’ reasons for responding to the texts and their preferred text frequency. Results: The participants were, on average, aged 55.8 (SD 9.8) years, 55.2% (137/248) female, and 52.0% (129/248) non-White; 40.7% (101/248) had ≤ a high school education, and 40.7% (101/248) had an annual household income 10 years. In total, 2 themes were constructed from interview data: (1) the moderating effect of diabetes self-management styles on needs, preferences, and expectations and (2) factors influencing users’ engagement with the app: one size does not fit all. Conclusions: User characteristics, the context of use, and features of the app interact and influence engagement. Promoting engagement is vital if diabetes self-management apps are to become a useful complement to clinical care in supporting optimal self-management. Trial Registration: Australia New Zealand Clinical Trials Registry CTRN126140012296; URL https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366925&isReview=true %M 32706649 %R 10.2196/16692 %U http://diabetes.jmir.org/2020/3/e16692/ %U https://doi.org/10.2196/16692 %U http://www.ncbi.nlm.nih.gov/pubmed/32706649 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e15448 %T A Wearable Technology Delivering a Web-Based Diabetes Prevention Program to People at High Risk of Type 2 Diabetes: Randomized Controlled Trial %A Staite,Emily %A Bayley,Adam %A Al-Ozairi,Ebaa %A Stewart,Kurtis %A Hopkins,David %A Rundle,Jennifer %A Basudev,Neel %A Mohamedali,Zahra %A Ismail,Khalida %+ Institute of Psychiatry, Psychology and Neurosciences, King's College London, Western Education Centre, 10 Cutcombe Road, London, SE5 9RJ, United Kingdom, 44 207 848 5131, khalida.2.ismail@kcl.ac.uk %K motivational interviewing %K lifestyle %K diabetes prevention program %K theory of planned behavior %K type 2 diabetes mellitus %K wearable technology %K mobile phone %D 2020 %7 15.7.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Intensive lifestyle interventions are effective in reducing the risk of type 2 diabetes, but the implementation of learnings from landmark studies is expensive and time consuming. The availability of digital lifestyle interventions is increasing, but evidence of their effectiveness is limited. Objective: This randomized controlled trial (RCT) aimed to test the feasibility of a web-based diabetes prevention program (DPP) with step-dependent feedback messages versus a standard web-based DPP in people with prediabetes. Methods: We employed a two-arm, parallel, single-blind RCT for people at high risk of developing diabetes. Patients with a hemoglobin A1c (HbA1c) level of 39-47 mmol/mol were recruited from 21 general practices in London. The intervention integrated a smartphone app delivering a web-based DPP course with SMS texts incorporating motivational interviewing techniques and step-dependent feedback messages delivered via a wearable device over 12 months. The control group received the wearable technology and access to the web-based DDP but not the SMS texts. As this was a feasibility study, the primary aim was to estimate potential sample size at different stages of the study, including the size of the target study population and the proportion of participants who consented, were randomized, and completed follow-up. We also measured the main outcomes for a full-scale RCT, namely, change in weight and physical activity at 6- and 12-month follow-ups, and secondary outcomes, including changes in the HbA1c level, blood pressure, waist circumference, waist-to-hip ratio, and lipid levels. Results: We enrolled 200 participants: 98 were randomized to the intervention and 102 were randomized to the control group. The follow-up rate was higher in the control group (87/102, 85.3%) than in the intervention group (69/98, 70%) at 12 months. There was no treatment effect on weight at 6 months (mean difference 0.15; 95% CI −0.93 to 1.23) or 12 months (mean difference 0.07 kg; 95% CI −1.29 to 1.44) or for physical activity levels at 6 months (mean difference −382.90 steps; 95% CI −860.65 to 94.85) or 12 months (mean difference 92.64 steps; 95% CI −380.92 to 566.20). We did not observe a treatment effect on the secondary outcomes measured at the 6-month or 12-month follow-up. For the intervention group, the mean weight was 92.33 (SD 15.67) kg at baseline, 91.34 (SD 16.04) kg at 6 months, and 89.41 (SD 14.93) kg at 12 months. For the control group, the mean weight was 92.59 (SD 17.43) kg at baseline, 91.71 (SD 16.48) kg at 6 months, and 91.10 (SD 15.82) kg at 12 months. In the intervention group, the mean physical activity was 7308.40 (SD 4911.93) steps at baseline, 5008.76 (SD 2733.22) steps at 6 months, and 4814.66 (SD 3419.65) steps at 12 months. In the control group, the mean physical activity was 7599.28 (SD 3881.04) steps at baseline, 6148.83 (SD 3433.77) steps at 6 months, and 5006.30 (SD 3681.1) steps at 12 months. Conclusions: This study demonstrates that it is feasible to successfully recruit and retain patients in an RCT of a web-based DPP. Trial Registration: ClinicalTrials.gov NCT02919397; http://clinicaltrials.gov/ct2/show/NCT02919397 %M 32459651 %R 10.2196/15448 %U https://mhealth.jmir.org/2020/7/e15448 %U https://doi.org/10.2196/15448 %U http://www.ncbi.nlm.nih.gov/pubmed/32459651 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 3 %P e18208 %T Web-Based and mHealth Technologies to Support Self-Management in People Living With Type 2 Diabetes: Validation of the Diabetes Self-Management and Technology Questionnaire (DSMT-Q) %A Kelly,Laura %A Jenkinson,Crispin %A Morley,David %+ Health Services Research Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Oxford, OX3 7LF, United Kingdom, 44 (0)1865 289425, laura.kelly@ndph.ox.ac.uk %K mHealth %K self-care %K type 2 diabetes %K self-monitoring %K questionnaire %D 2020 %7 9.7.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: A growing number of web-based and mobile health (mHealth) technologies have been developed to support type 2 diabetes self-management. Little is known about individuals’ experiences with these technologies and how they support self-management. Appropriate tools are needed to understand how web-based and mHealth interventions may impact self-management. Objective: This study aimed to develop an instrument, the Diabetes Self-Management and Technology Questionnaire (DSMT-Q), to assess self-management among people living with type 2 diabetes who use web-based and mHealth technologies. Methods: A total of 36 candidate questionnaire items, drafted previously, were refined using cognitive debriefing interviews (n=8), expert consultation, and public patient involvement feedback. Item reduction steps were performed on survey data (n=250), and tests of validity and reliability were subsequently performed. Results: Following amendments, patients and experts found 21 items relevant and acceptable for inclusion in the instrument. Survey participants included 104 (41.6%) women and 146 (58.4%) men. Two subscales with high construct validity, internal consistency, and test-retest reliability were identified: “Understanding individual health and making informed decisions” and “Confidence to reach and sustain goals.” Conclusions: Analyses confirmed good psychometric properties in the DSMT-Q scales. This tool will facilitate the measurement of self-management in people living with type 2 diabetes who use web-based or mHealth technologies. %M 32673214 %R 10.2196/18208 %U https://diabetes.jmir.org/2020/3/e18208 %U https://doi.org/10.2196/18208 %U http://www.ncbi.nlm.nih.gov/pubmed/32673214 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 7 %P e17842 %T Mobile Delivery of the Diabetes Prevention Program in People With Prediabetes: Randomized Controlled Trial %A Toro-Ramos,Tatiana %A Michaelides,Andreas %A Anton,Maria %A Karim,Zulekha %A Kang-Oh,Leah %A Argyrou,Charalambos %A Loukaidou,Elisavet %A Charitou,Marina M %A Sze,Wilson %A Miller,Joshua D %+ Noom, Inc, 229 W 28th St, New York, NY, , United States, 1 5168087328, andreas@noom.com %K prediabetes %K body weight %K mHealth %K mobile app %K mobile phone %K randomized controlled trial %D 2020 %7 8.7.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The Centers for Disease Control and Prevention (CDC) diabetes prevention program (DPP) has formed the foundation for Type 2 Diabetes Mellitus (T2DM) prevention efforts and lifestyle change modifications in multiple care settings. To our knowledge, no randomized controlled trial has verified the efficacy of a fully mobile version of CDC’s diabetes prevention program (DPP). Objective: This study aimed to investigate the long-term weight loss and glycemic efficacy of a mobile-delivered DPP compared with a control group receiving usual medical care. Methods: Adults with prediabetes (N=202) were recruited from a clinic and randomized to either a mobile-delivered, coach-guided DPP (Noom) or a control group that received regular medical care including a paper-based DPP curriculum and no formal intervention. The intervention group learned how to use the Noom program, how to interact with their coach, and the importance of maintaining motivation. They had access to an interactive coach-to-participant interface and group messaging, daily challenges for behavior change, DPP-based education articles, food logging, and automated feedback. Primary outcomes included changes in weight and hemoglobin A1c (HbA1c) levels at 6 and 12 months, respectively. Exploratory secondary outcomes included program engagement as a predictor of changes in weight and HbA1c levels. Results: A total of 202 participants were recruited and randomized into the intervention (n=101) or control group (n=99). In the intention-to-treat (ITT) analyses, changes in the participants’ weight and BMI were significantly different at 6 months between the intervention and control groups, but there was no difference in HbA1c levels (mean difference 0.004%, SE 0.05; P=.94). Weight and BMI were lower in the intervention group by −2.64 kg (SE 0.71; P<.001) and −0.99 kg/m2 (SE 0.29; P=.001), respectively. These differences persisted at 12 months. However, in the analyses that did not involve ITT, program completers achieved a significant weight loss of 5.6% (SE 0.81; P<.001) at 6 months, maintaining 4.7% (SE 0.88; P<.001) of their weight loss at 12 months. The control group lost −0.15% at 6 months (SE 0.64; P=.85) and gained 0.33% (SE 0.70; P=.63) at 12 months. Those randomized to the intervention group who did not start the program had no meaningful weight or HbA1c level change, similar to the control group. At 1 year, the intervention group showed a 0.23% reduction in HbA1c levels; those who completed the intervention showed a 0.28% reduction. Those assigned to the control group had a 0.16% reduction in HbA1c levels. Conclusions: This novel mobile-delivered DPP achieved significant weight loss reductions for up to 1 year compared with usual care. This type of intervention reduces the risk of overt diabetes without the added barriers of in-person interventions. Trial Registration: ClinicalTrials.gov NCT03865342; https://clinicaltrials.gov/ct2/show/NCT03865342 %M 32459631 %R 10.2196/17842 %U https://mhealth.jmir.org/2020/7/e17842 %U https://doi.org/10.2196/17842 %U http://www.ncbi.nlm.nih.gov/pubmed/32459631 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18480 %T Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review %A Larbi,Dillys %A Randine,Pietro %A Årsand,Eirik %A Antypas,Konstantinos %A Bradway,Meghan %A Gabarron,Elia %+ Norwegian Centre for E-health Research, University Hospital of North Norway, Forskningsparken i Breivika 3rd Fl, Sykehusveien 23, Tromsø, 9019, Norway, 47 91193393, meghan.bradway@ehealthresearch.no %K self-management %K diabetes mellitus %K mobile applications %K computer communication networks %K mHealth %K eHealth %K health care evaluation mechanisms %D 2020 %7 6.7.2020 %9 Review %J J Med Internet Res %G English %X Background: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients’ skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions. Objective: This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations. Methods: We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies’ quality, methods of evaluation, and evaluation criteria. Results: Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence. Conclusions: There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management. %M 32628125 %R 10.2196/18480 %U https://www.jmir.org/2020/7/e18480 %U https://doi.org/10.2196/18480 %U http://www.ncbi.nlm.nih.gov/pubmed/32628125 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 6 %P e14486 %T Barriers to Gestational Diabetes Management and Preferred Interventions for Women With Gestational Diabetes in Singapore: Mixed Methods Study %A Hewage,Sumali %A Audimulam,Jananie %A Sullivan,Emily %A Chi,Claudia %A Yew,Tong Wei %A Yoong,Joanne %+ Saw Swee Hock School of Public Health, National University of Singapore, Tahir Foundation Building, 12 Science Drive 2, #10-01, Singapore, 117549, Singapore, 65 65164988, sumali_hewage@u.nus.edu %K gestational diabetes %K pregnancy %K telemedicine %K self-management %K patient-centered care %K mobile phone %D 2020 %7 30.6.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Gestational diabetes mellitus (GDM) is associated with risks for both the mother and child. The escalated prevalence of GDM because of obesity and changes in screening criteria demands for greater health care needs than before. Objective: This study aimed to understand the perception of patients and health care providers of the barriers to GDM management and preferred interventions to manage GDM in an Asian setting. Methods: This mixed methods study used a convergent parallel design. Survey data were collected from 216 women with GDM, and semistructured interviews were conducted with 15 women and with 8 health care providers treating patients with GDM. Participants were recruited from 2 specialized GDM clinics at the National University Hospital, Singapore. Results: The patients were predominantly Chinese (102/214, 47.6%), employed (201/272, 73.9%), with higher education (150/216, 69.4%) and prenatal attendance at a private clinic (138/214, 64.2%), already on diet control (210/214, 98.1%), and receiving support and information from the GDM clinic (194/215, 90.2%) and web-based sources (131/215, 60.9%). In particular, working women reported barriers to GDM management, including the lack of reminders for blood glucose monitoring, diet control, and insufficient time for exercise. Most women preferred getting such support directly from health care providers, whether at the GDM clinic (174/215, 80.9%) or elsewhere (116/215, 53.9%). Smartphone apps were the preferred means of additional intervention. Desirable intervention features identified by patients included more information on GDM, diet and exercise options, reminders for blood glucose testing, a platform to record blood glucose readings and illustrate or understand trends, and a means to communicate with care providers. Conclusions: A GDM-focused smartphone app that is able to integrate testing, education, and communication may be a feasible and acceptable intervention to provide support to women with GDM, particularly for working women. %M 32602845 %R 10.2196/14486 %U http://formative.jmir.org/2020/6/e14486/ %U https://doi.org/10.2196/14486 %U http://www.ncbi.nlm.nih.gov/pubmed/32602845 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 2 %P e17890 %T Diabetes Management Experience and the State of Hypoglycemia: National Online Survey Study %A Zahed,Karim %A Sasangohar,Farzan %A Mehta,Ranjana %A Erraguntla,Madhav %A Qaraqe,Khalid %+ Department of Industrial and Systems Engineering, Texas A&M University, 3131 TAMU, College Station, TX, 77843, United States, 1 979 458 2337, sasangohar@tamu.edu %K tremor %K hypoglycemia %K diabetes mellitus %K remote sensing technology %K survey methods %K mobile phone %D 2020 %7 17.6.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: Hypoglycemia, or low blood sugar levels, in people with diabetes can be a serious life-threatening condition, and serious outcomes can be avoided if low levels of blood sugar are proactively detected. Although technologies exist to detect the onset of hypoglycemia, they are invasive or costly or exhibit a high incidence of false alarms. Tremors are commonly reported symptoms of hypoglycemia and may be used to detect hypoglycemic events, yet their onset is not well researched or understood. Objective: This study aimed to understand diabetic patients’ perceptions of hypoglycemic tremors, as well as their user experiences with technology to manage diabetes, and expectations from a self-management tool to ultimately inform the design of a noninvasive and cost-effective technology that detects tremors associated with hypoglycemia. Methods: A cross-sectional internet panel survey was administered to adult patients with type 1 diabetes using the Qualtrics platform in May 2019. The questions focused on 3 main constructs: (1) perceived experiences of hypoglycemia, (2) experiences and expectations about a diabetes management device and mobile app, and (3) beliefs and attitudes regarding intention to use a diabetes management device. The analysis in this paper focuses on the first two constructs. Nonparametric tests were used to analyze the Likert scale data, with a Mann-Whitney U test, Kruskal-Wallis test, and Games-Howell post hoc test as applicable, for subgroup comparisons to highlight differences in perceived frequency, severity, and noticeability of hypoglycemic tremors across age, gender, years living with diabetes, and physical activity. Results: Data from 212 respondents (129 [60.8%] females) revealed statistically significant differences in perceived noticeability of tremors by gender, whereby males noticed their tremors more (P<.001), and age, with the older population reporting lower noticeability than the young and middle age groups (P<.001). Individuals living longer with diabetes noticed their tremors significantly less than those with diabetes for ≤1 year but not in terms of frequency or severity. Additionally, the majority of our participants (150/212, 70.7%) reported experience with diabetes-monitoring devices. Conclusions: Our findings support the need for cost-efficient and noninvasive continuous monitoring technologies. Although hypoglycemic tremors were perceived to occur frequently, such tremors were not found to be severe compared with other symptoms such as sweating, which was the highest rated symptom in our study. Using a combination of tremor and galvanic skin response sensors may show promise in detecting the onset of hypoglycemic events. %M 32442145 %R 10.2196/17890 %U http://diabetes.jmir.org/2020/2/e17890/ %U https://doi.org/10.2196/17890 %U http://www.ncbi.nlm.nih.gov/pubmed/32442145 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 6 %P e17802 %T User Retention and Engagement With a Mobile App Intervention to Support Self-Management in Australians With Type 1 or Type 2 Diabetes (My Care Hub): Mixed Methods Study %A Adu,Mary D %A Malabu,Usman H %A Malau-Aduli,Aduli EO %A Drovandi,Aaron %A Malau-Aduli,Bunmi S %+ College of Medicine and Dentistry, James Cook University, 1 James Cook Drive, Townsville, 4811, Australia, 61 747814418, bunmi.malauaduli@jcu.edu.au %K mobile apps %K engagement %K retention %K diabetes mellitus, self-management %K behavioral intervention technology %D 2020 %7 11.6.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health apps are commonly used to support diabetes self-management (DSM). However, there is limited research assessing whether such apps are able to meet the basic requirements of retaining and engaging users. Objective: This study aimed to evaluate participants’ retention and engagement with My Care Hub, a mobile app for DSM. Methods: The study employed an explanatory mixed methods design. Participants were people with type 1 or type 2 diabetes who used the health app intervention for 3 weeks. Retention was measured by completion of the postintervention survey. Engagement was measured using system log indices and interviews. Retention and system log indices were presented using descriptive statistics. Transcripts were analyzed using content analysis to develop themes interpreted according to the behavioral intervention technology theory. Results: Of the 50 individuals enrolled, 42 (84%) adhered to the study protocol. System usage data showed multiple and frequent interactions with the app by most of the enrolled participants (42/50, 84%). Two-thirds of participants who inputted data during the first week returned to use the app after week 1 (36/42, 85%) and week 2 (30/42, 71%) of installation. Most daily used features were tracking of blood glucose (BG; 28/42, 68%) and accessing educational information (6/42, 13%). The interview results revealed the app’s potential as a behavior change intervention tool, particularly because it eased participants’ self-care efforts and improved their engagement with DSM activities such as BG monitoring, physical exercise, and healthy eating. Participants suggested additional functionalities such as extended access to historical analytic data, automated data transmission from the BG meter, and periodic update of meals and corresponding nutrients to further enhance engagement with the app. Conclusions: The findings of this short-term intervention study suggested acceptable levels of participant retention and engagement with My Care Hub, indicating that it may be a promising tool for extending DSM support and education beyond the confines of a physical clinic. %M 32525491 %R 10.2196/17802 %U https://mhealth.jmir.org/2020/6/e17802 %U https://doi.org/10.2196/17802 %U http://www.ncbi.nlm.nih.gov/pubmed/32525491 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 6 %P e17730 %T Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis %A Yang,Qing %A Hatch,Daniel %A Crowley,Matthew J %A Lewinski,Allison A %A Vaughn,Jacqueline %A Steinberg,Dori %A Vorderstrasse,Allison %A Jiang,Meilin %A Shaw,Ryan J %+ School of Nursing, Duke University, 307 Trent Drive, Durham, NC, 27710, United States, 1 9196139768, qing.yang@duke.edu %K digital phenotype %K latent class growth analysis %K type 2 diabetes %K self-management %K self-monitoring %K Mobile Health %D 2020 %7 11.6.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Sustained self-monitoring and self-management behaviors are crucial to maintain optimal health for individuals with type 2 diabetes mellitus (T2DM). As smartphones and mobile health (mHealth) devices become widely available, self-monitoring using mHealth devices is an appealing strategy in support of successful self-management of T2DM. However, research indicates that engagement with mHealth devices decreases over time. Thus, it is important to understand engagement trajectories to provide varying levels of support that can improve self-monitoring and self-management behaviors. Objective: The aims of this study were to develop (1) digital phenotypes of the self-monitoring behaviors of patients with T2DM based on their engagement trajectory of using multiple mHealth devices, and (2) assess the association of individual digital phenotypes of self-monitoring behaviors with baseline demographic and clinical characteristics. Methods: This longitudinal observational feasibility study included 60 participants with T2DM who were instructed to monitor their weight, blood glucose, and physical activity using a wireless weight scale, phone-tethered glucometer, and accelerometer, respectively, over 6 months. We used latent class growth analysis (LCGA) with multitrajectory modeling to associate the digital phenotypes of participants’ self-monitoring behaviors based on their engagement trajectories with multiple mHealth devices. Associations between individual characteristics and digital phenotypes on participants’ self-monitoring behavior were assessed by analysis of variance or the Chi square test. Results: The engagement with accelerometers to monitor daily physical activities was consistently high for all participants over time. Three distinct digital phenotypes were identified based on participants’ engagement with the wireless weight scale and glucometer: (1) low and waning engagement group (24/60, 40%), (2) medium engagement group (20/60, 33%), and (3) consistently high engagement group (16/60, 27%). Participants that were younger, female, nonwhite, had a low income, and with a higher baseline hemoglobin A1c level were more likely to be in the low and waning engagement group. Conclusions: We demonstrated how to digitally phenotype individuals’ self-monitoring behavior based on their engagement trajectory with multiple mHealth devices. Distinct self-monitoring behavior groups were identified. Individual demographic and clinical characteristics were associated with different self-monitoring behavior groups. Future research should identify methods to provide tailored support for people with T2DM to help them better monitor and manage their condition. International Registered Report Identifier (IRRID): RR2-10.2196/13517 %M 32525492 %R 10.2196/17730 %U https://mhealth.jmir.org/2020/6/e17730 %U https://doi.org/10.2196/17730 %U http://www.ncbi.nlm.nih.gov/pubmed/32525492 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 6 %P e14024 %T Comparing a Social and Communication App, Telephone Intervention, and Usual Care for Diabetes Self-Management: 3-Arm Quasiexperimental Evaluation Study %A Chiu,Ching-Ju %A Yu,Yung-Chen %A Du,Ye-Fong %A Yang,Yi-Ching %A Chen,Jou-Yin %A Wong,Li-Ping %A Tanasugarn,Chanuantong %+ Division of Endocrinology and Metabolism, Department of Internal Medicine, National Cheng Kung University Hospital, No. 138, Shengli Road, North District, Tainan, 70403, Taiwan, 886 6 2353535 ext 4577, n043328@mail.hosp.ncku.edu.tw %K diabetes %K self-management %K depression symptoms %K distress %K middle-aged and older adults %D 2020 %7 2.6.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Many technology-assisted innovations have been used to manage disease. However, most of these innovations are not broadly used by older adults due to their cost. Additionally, disease management through technology-assisted innovations has not been compared with other interventions. Objective: In this study, we tested the employment of a free and widely used social and communication app to help older adults with diabetes manage their distress and glycemic control. We also compared the effectiveness of the app with 2 other methods, namely telephone and conventional health education, and determined which subgroup experiences the most effects within each intervention. Methods: Adults aged ≥50 years with type 2 diabetes were recruited from Southern Taiwan (N=231) and were allocated to different 3-month interventions. Informed consent was obtained at the Ministry of Science and Technology and approved by the National Cheng Kung University Hospital Institutional Review Board (No. A-ER-102-425). Results: Participants in the mobile-based group had significant reductions in hemoglobin A1c compared with the telephone-based and usual care groups (mean changes of –0.4%, 0.1%, and 0.03%, respectively; P=.02). Diabetes-specific distress decreased to a greater extent in the mobile-based group compared to the other 2 groups (mean changes of –5.16, –3.49, and –2.44, respectively, P=.02). Subgroup analyses further revealed that the effects on reducing blood glucose levels in the social and communication app groups were especially evident in patients with lower distress scores, and diabetes-related distress was especially evident in participants who were younger than 60 years or had higher educational levels. Conclusions: The findings of this study inform more flexible use of social and communication apps with in-person diabetes education and counselling. %M 32484448 %R 10.2196/14024 %U https://mhealth.jmir.org/2020/6/e14024 %U https://doi.org/10.2196/14024 %U http://www.ncbi.nlm.nih.gov/pubmed/32484448 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 5 %P e17968 %T Enhancing Patient Activation and Self-Management Activities in Patients With Type 2 Diabetes Using the US Department of Defense Mobile Health Care Environment: Feasibility Study %A Gimbel,Ronald W %A Rennert,Lior M %A Crawford,Paul %A Little,Jeanette R %A Truong,Khoa %A Williams,Joel E %A Griffin,Sarah F %A Shi,Lu %A Chen,Liwei %A Zhang,LingLing %A Moss,Jennie B %A Marshall,Robert C %A Edwards,Karen W %A Crawford,Kristy J %A Hing,Marie %A Schmeltz,Amanda %A Lumsden,Brandon %A Ashby,Morgan %A Haas,Elizabeth %A Palazzo,Kelly %+ Department of Public Health Sciences, Clemson University, 501 Edwards Hall, Clemson, SC, 29634, United States, 1 5405223759, rgimbel@clemson.edu %K mHealth %K diabetes mellitus %K patient activation %K patient-centered care %K eHealth %D 2020 %7 26.5.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Past mobile health (mHealth) efforts to empower type 2 diabetes (T2D) self-management include portals, text messaging, collection of biometric data, electronic coaching, email, and collection of lifestyle information. Objective: The primary objective was to enhance patient activation and self-management of T2D using the US Department of Defense’s Mobile Health Care Environment (MHCE) in a patient-centered medical home setting. Methods: A multisite study, including a user-centered design and a controlled trial, was conducted within the US Military Health System. Phase I assessed preferences regarding the enhancement of the enabling technology. Phase II was a single-blinded 12-month feasibility study that randomly assigned 240 patients to either the intervention (n=123, received mHealth technology and behavioral messages tailored to Patient Activation Measure [PAM] level at baseline) or the control group (n=117, received equipment but not messaging. The primary outcome measure was PAM scores. Secondary outcome measures included Summary of Diabetes Self-Care Activities (SDSCA) scores and cardiometabolic outcomes. We used generalized estimating equations to estimate changes in outcomes. Results: The final sample consisted of 229 patients. Participants were 61.6% (141/229) male, had a mean age of 62.9 years, mean glycated hemoglobin (HbA1c) of 7.5%, mean BMI of 32.7, and a mean duration of T2D diagnosis of 9.8 years. At month 12, the control group showed significantly greater improvements compared with the intervention group in PAM scores (control mean 7.49, intervention mean 1.77; P=.007), HbA1c (control mean −0.53, intervention mean −0.11; P=.006), and low-density lipoprotein cholesterol (control mean −7.14, intervention mean 4.38; P=.01). Both groups showed significant improvement in SDSCA, BMI, waist size, and diastolic blood pressure; between-group differences were not statistically significant. Except for patients with the highest level of activation (PAM level 4), intervention group patients exhibited significant improvements in PAM scores. For patients with the lowest level of activation (PAM level 1), the intervention group showed significantly greater improvement compared with the control group in HbA1c (control mean −0.09, intervention mean −0.52; P=.04), BMI (control mean 0.58, intervention mean −1.22; P=.01), and high-density lipoprotein cholesterol levels (control mean −4.86, intervention mean 3.56; P<.001). Significant improvements were seen in AM scores, SDSCA, and waist size for both groups and in diastolic and systolic blood pressure for the control group; the between-group differences were not statistically significant. The percentage of participants who were engaged with MHCE for ≥50% of days period was 60.7% (68/112; months 0-3), 57.4% (62/108; months 3-6), 49.5% (51/103; months 6-9), and 43% (42/98; months 9-12). Conclusions: Our study produced mixed results with improvement in PAM scores and outcomes in both the intervention and control groups. Structural design issues may have hampered the influence of tailored behavioral messaging within the intervention group. Trial Registration: ClinicalTrials.gov NCT02949037; https://clinicaltrials.gov/ct2/show/NCT02949037 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.6993 %M 32329438 %R 10.2196/17968 %U http://www.jmir.org/2020/5/e17968/ %U https://doi.org/10.2196/17968 %U http://www.ncbi.nlm.nih.gov/pubmed/32329438 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 5 %N 2 %P e14396 %T Health App Use and Its Correlates Among Individuals With and Without Type 2 Diabetes: Nationwide Population-Based Survey %A Stühmann,Lena M %A Paprott,Rebecca %A Heidemann,Christin %A Baumert,Jens %A Hansen,Sylvia %A Zahn,Daniela %A Scheidt-Nave,Christa %A Gellert,Paul %+ Institute for Medical Sociology and Rehabilitation Science, Charité – Universitätsmedizin Berlin, Charitéplatz 1, Berlin, 10117, Germany, 49 30 450 529215, lena.stuehmann@charite.de %K mobile app %K smartphone %K diabetes mellitus %K type 2 diabetes %K risk factors %K health-related behavior %K health promotion %D 2020 %7 20.5.2020 %9 Original Paper %J JMIR Diabetes %G English %X Background: Evidence suggests that mobile health app use is beneficial for the prevention and management of type 2 diabetes (T2D) and its associated complications; however, population-based research on specific determinants of health app use in people with and without T2D is scarce. Objective: This cross-sectional study aimed to provide population-based evidence on rates and determinants of health app use among adults with and without T2D, thereby covering a prevention perspective and a diabetes management perspective, respectively. Methods: The study population included 2327 adults without a known diabetes diagnosis and 1149 adults with known T2D from a nationwide telephone survey in Germany conducted in 2017. Rates of smartphone ownership and health app use were estimated based on weighted sample proportions. Among smartphone owners, determinants of health app use were identified for both groups separately in multivariable logistic regression models. Sociodemographic factors, diabetes-related factors or indicators, psychological and health-related factors, and physician-provided information were selected as potential determinants. Results: Among participants without known diabetes, 74.72% (1690/2327) were smartphone owners. Of those, 49.27% (717/1690) used health apps, most often to improve regular physical activity. Among participants with T2D, 42.26% (481/1149) were smartphone owners. Of those, 41.1% (171/481) used health apps, most commonly to target a healthy diet. Among people without known diabetes, determinants significantly (all P values <.05) associated with an increased likelihood of health app use compared with their reference group were as follows: younger and middle age of 18 to 44 or 45 to 64 years (odds ratios [ORs] 3.89; P<.001 and 1.76; P=.004, respectively), overweight or obesity (ORs 1.58; P<.001 and 2.07; P<.001, respectively), hypertension diagnosis (OR 1.31; P=.045), former or current smoking (ORs 1.51; P=.002 and 1.58; P<.001, respectively), perceiving health as very good (OR 2.21; P<.001), other chronic diseases (OR 1.48; P=.002), and having received health advice from a physician (OR 1.48; P<.001). A slight or high perceived diabetes risk (ORs 0.78; P=.04 and 0.23; P<.001, respectively) was significantly associated with a decreased likelihood of health app use. Among people with T2D, younger and middle age (18-64 years; OR 1.84; P=.007), female gender (OR 1.61; P=.02), and using a glucose sensor in addition or instead of a glucose meter (OR 2.74; P=.04) were significantly positively associated with health app use. Conclusions: In terms of T2D prevention, age, diabetes-related risk factors, psychological and health-related factors, and medical health advice may inform app development for specific target groups. In addition, health professionals may encourage health app use when giving advice on health behaviors. Concerning T2D management, only a few determinants seem relevant for explaining health app use among people with T2D, indicating a need for more future research on which people with T2D use health apps and why. %M 32432555 %R 10.2196/14396 %U http://diabetes.jmir.org/2020/2/e14396/ %U https://doi.org/10.2196/14396 %U http://www.ncbi.nlm.nih.gov/pubmed/32432555 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 5 %P e16658 %T Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies %A Tan,Choon Han %A Kyaw,Bhone Myint %A Smith,Helen %A Tan,Colin S %A Tudor Car,Lorainne %+ Family Medicine and Primary Care, Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Singapore, Singapore, 65 6904 1258, lorainne.tudor.car@ntu.edu.sg %K diabetic retinopathy %K smartphone %K mobile phone %K ophthalmoscopy %K artificial intelligence %K telemedicine %D 2020 %7 15.5.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Diabetic retinopathy (DR), a common complication of diabetes mellitus, is the leading cause of impaired vision in adults worldwide. Smartphone ophthalmoscopy involves using a smartphone camera for digital retinal imaging. Utilizing smartphones to detect DR is potentially more affordable, accessible, and easier to use than conventional methods. Objective: This study aimed to determine the diagnostic accuracy of various smartphone ophthalmoscopy approaches for detecting DR in diabetic patients. Methods: We performed an electronic search on the Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, and Cochrane Library for literature published from January 2000 to November 2018. We included studies involving diabetic patients, which compared the diagnostic accuracy of smartphone ophthalmoscopy for detecting DR to an accurate or commonly employed reference standard, such as indirect ophthalmoscopy, slit-lamp biomicroscopy, and tabletop fundus photography. Two reviewers independently screened studies against the inclusion criteria, extracted data, and assessed the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies–2 tool, with disagreements resolved via consensus. Sensitivity and specificity were pooled using the random effects model. A summary receiver operating characteristic (SROC) curve was constructed. This review is reported in line with the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies guidelines. Results: In all, nine studies involving 1430 participants were included. Most studies were of high quality, except one study with limited applicability because of its reference standard. The pooled sensitivity and specificity for detecting any DR was 87% (95% CI 74%-94%) and 94% (95% CI 81%-98%); mild nonproliferative DR (NPDR) was 39% (95% CI 10%-79%) and 95% (95% CI 91%-98%); moderate NPDR was 71% (95% CI 57%-81%) and 95% (95% CI 88%-98%); severe NPDR was 80% (95% CI 49%-94%) and 97% (95% CI 88%-99%); proliferative DR (PDR) was 92% (95% CI 79%-97%) and 99% (95% CI 96%-99%); diabetic macular edema was 79% (95% CI 63%-89%) and 93% (95% CI 82%-97%); and referral-warranted DR was 91% (95% CI 86%-94%) and 89% (95% CI 56%-98%). The area under SROC curve ranged from 0.879 to 0.979. The diagnostic odds ratio ranged from 11.3 to 1225. Conclusions: We found heterogeneous evidence showing that smartphone ophthalmoscopy performs well in detecting DR. The diagnostic accuracy for PDR was highest. Future studies should standardize reference criteria and classification criteria and evaluate other available forms of smartphone ophthalmoscopy in primary care settings. %M 32347810 %R 10.2196/16658 %U http://www.jmir.org/2020/5/e16658/ %U https://doi.org/10.2196/16658 %U http://www.ncbi.nlm.nih.gov/pubmed/32347810 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 4 %P e13536 %T Facilitators and Barriers to Chronic Disease Self-Management and Mobile Health Interventions for People Living With Diabetes and Hypertension in Cambodia: Qualitative Study %A Steinman,Lesley %A Heang,Hen %A van Pelt,Maurits %A Ide,Nicole %A Cui,Haixia %A Rao,Mayuree %A LoGerfo,James %A Fitzpatrick,Annette %+ Department of Health Services, University of Washington, 1107 NE 45th St Suite 400, Seattle, WA, 98105, United States, 1 2065439837, lesles@uw.edu %K diabetes mellitus %K hypertension %K chronic disease %K noncommunicable diseases %K health educators %K mHealth %K qualitative %K disease management %K developing countries %D 2020 %7 24.4.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In many low- and middle-income countries (LMICs), heart disease and stroke are the leading causes of death as cardiovascular risk factors such as diabetes and hypertension rapidly increase. The Cambodian nongovernmental organization, MoPoTsyo, trains local residents with diabetes to be peer educators (PEs) to deliver chronic disease self-management training and medications to 14,000 people with hypertension and/or diabetes in Cambodia. We collaborated with MoPoTsyo to develop a mobile-based messaging intervention (mobile health; mHealth) to link MoPoTsyo’s database, PEs, pharmacies, clinics, and people living with diabetes and/or hypertension to improve adherence to evidence-based treatment guidelines. Objective: This study aimed to understand the facilitators and barriers to chronic disease management and the acceptability, appropriateness, and feasibility of mHealth to support chronic disease management and strengthen community-clinical linkages to existing services. Methods: We conducted an exploratory qualitative study using semistructured interviews and focus groups with PEs and people living with diabetes and/or hypertension. Interviews were recorded and conducted in Khmer script, transcribed and translated into the English language, and uploaded into Atlas.ti for analysis. We used a thematic analysis to identify key facilitators and barriers to disease management and opportunities for mHealth content and format. The information-motivation-behavioral model was used to guide data collection, analysis, and message development. Results: We conducted six focus groups (N=59) and 11 interviews in one urban municipality and five rural operating districts from three provinces in October 2016. PE network participants desired mHealth to address barriers to chronic disease management through reminders about medications, laboratory tests and doctor’s consultations, education on how to incorporate self-management into their daily lives, and support for obstacles to disease management. Participants preferred mobile-based voice messages to arrive at dinnertime for improved phone access and family support. They desired voice messages over texts to communicate trust and increase accessibility for persons with limited literacy, vision, and smartphone access. PEs shared similar views and perceived mHealth as acceptable and feasible for supporting their work. We developed 34 educational, supportive, and reminder mHealth messages based on these findings. Conclusions: These mHealth messages are currently being tested in a cluster randomized controlled trial (#1R21TW010160) to improve diabetes and hypertension control in Cambodia. This study has implications for practice and policies in Cambodia and other LMICs and low-resource US settings that are working to engage PEs and build community-clinical linkages to facilitate chronic disease management. %M 32329737 %R 10.2196/13536 %U http://mhealth.jmir.org/2020/4/e13536/ %U https://doi.org/10.2196/13536 %U http://www.ncbi.nlm.nih.gov/pubmed/32329737 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 4 %P e15789 %T British South Asian Patients’ Perspectives on the Relevance and Acceptability of Mobile Health Text Messaging to Support Medication Adherence for Type 2 Diabetes: Qualitative Study %A Prinjha,Suman %A Ricci-Cabello,Ignacio %A Newhouse,Nikki %A Farmer,Andrew %+ Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, , United Kingdom, 44 (0)7774 629231, suman.prinjha@phc.ox.ac.uk %K type 2 diabetes %K South Asians %K text messages %K self-management %K medication adherence %K mobile health %K mHealth %K eHealth %D 2020 %7 20.4.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The prevalence of type 2 diabetes (T2D) is greater in South Asian populations and health outcomes are poorer compared with other ethnic groups. British South Asians are up to six times more likely to have T2D than the general population, to develop the condition at a younger age, and to experience diabetes-related complications. Interventions to support people in managing their condition can potentially reduce debilitating complications. Evidence to support the use of digital devices in T2D management, including mobile phones, has shown positive impacts on glycemic control. There is increasing recognition that health interventions that are culturally adapted to the needs of specific groups are more likely to be relevant and acceptable, but evidence to support the effectiveness of adapted interventions is limited and inconclusive. Objective: This formative study aimed to explore the perceptions and views of British South Asian patients with T2D on mobile health SMS text messaging to support medication adherence, aimed at the general UK population. Methods: Eight exploratory focus groups were conducted in Leicester, the United Kingdom, between September 2017 and March 2018. A diverse sample of 67 adults took part. Results: British South Asian people with T2D who use digital devices, including mobile phones, felt that short messages to support medication adherence would be acceptable and relevant, but they also wanted messages that would support other aspects of self-management too. Participants were particularly interested in content that met their information needs, including information about South Asian foods, commonly used herbs and spices, natural and herbal approaches used in the United Kingdom and in South Asia, and religious fasting. Short messages delivered in English were perceived to be acceptable, often because family members could translate for those unable to read or understand the messages. Suggestions to support patients unable to understand short messages in English included having them available in different formats, and disseminated in face-to-face groups for those who did not use digital devices. Conclusions: Exploring the views of British South Asian patients about SMS text messaging aimed at the general UK population is important in maximizing the potential of such an intervention. For such a digital system to meet the needs of UK South Asian populations, it may also have to include culturally relevant messages sent to those who opt to receive them. It is equally important to consider how to disseminate message content to patients who do not use digital devices to help reduce health inequalities. %M 32310150 %R 10.2196/15789 %U http://mhealth.jmir.org/2020/4/e15789/ %U https://doi.org/10.2196/15789 %U http://www.ncbi.nlm.nih.gov/pubmed/32310150 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 4 %P e14836 %T Quality, Functionality, and Features of Chinese Mobile Apps for Diabetes Self-Management: Systematic Search and Evaluation of Mobile Apps %A Gong,Enying %A Zhang,Zongmuyu %A Jin,Xurui %A Liu,Yishan %A Zhong,Lumin %A Wu,Yao %A Zhong,Xuefeng %A Yan,Lijing L. %A Oldenburg,Brian %+ Melbourne School of Population and Global Health, University of Melbourne, 333 Exhibition Street, Melbourne, Victoria, Australia, 61 0452389420, egong@student.unimelb.edu.au %K diabetes mellitus %K self-management %K mobile apps %K China %D 2020 %7 7.4.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The emergence and advancement of mobile technologies offer a promising opportunity for people with diabetes to improve their self-management. Despite the proliferation of mobile apps, few studies have evaluated the apps that are available to the millions of people with diabetes in China. Objective: This study aimed to conduct a systematic search of Chinese mobile apps for diabetes self-management and to evaluate their quality, functionality, and features by using validated rating scales. Methods: A systematic search was conducted to identify Chinese apps for diabetes self-management in the four most popular Chinese language mobile app stores. Apps were included if they were designed for diabetes self-management and contained at least one of the following components: blood glucose management, dietary and physical activity management, medication taking, and prevention of diabetes-related comorbidities. Apps were excluded if they were unrelated to health, not in Chinese, or the targeted users are health care professionals. Apps meeting the identified inclusion criteria were downloaded and evaluated by a team of 5 raters. The quality, functionalities, and features of these apps were assessed by using the Mobile App Rating Scale (MARS), the IMS Institute for Healthcare Informatics Functionality score, and a checklist of self-management activities developed based on the Chinese diabetes self-management guideline, respectively. Results: Among 2072 apps searched, 199 were eligible based on the inclusion criteria, and 67 apps were successfully downloaded for rating. These 67 apps had an average MARS score of 3.42 out of 5, and 76% (51/67) of the apps achieved an acceptable quality (MARS score >3.0). The scores for the four subdomains of MARS were 3.97 for functionality, 3.45 for aesthetics, 3.21 for information, and 3.07 for engagement. On average, reviewed apps applied five out of the 19 examined behavior change techniques, whereas the average score on the subjective quality for the potential impact on behavior change is 3 out of 5. In addition, the average score on IMS functionality was 6 out of 11. Functionalities in collecting, recording, and displaying data were mostly presented in the reviewed apps. Most of the apps were multifeatured with monitoring blood glucose and tracking lifestyle behaviors as common features, but some key self-management activities recommended by clinical guidelines, such as stress and emotional management, were rarely presented in these apps. Conclusions: The general quality of the reviewed apps for diabetes self-management is suboptimal, although the potential for improvement is significant. More attention needs to be paid to the engagement and information quality of these apps through co-design with researchers, public health practitioners, and consumers. There is also a need to promote the awareness of the public on the benefit and potential risks of utilizing health apps for self-management. %M 32255432 %R 10.2196/14836 %U https://mhealth.jmir.org/2020/4/e14836 %U https://doi.org/10.2196/14836 %U http://www.ncbi.nlm.nih.gov/pubmed/32255432 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 3 %P e16683 %T Using Mobile Health Tools to Engage Rural Underserved Individuals in a Diabetes Education Program in South Texas: Feasibility Study %A Yin,Zenong %A Lesser,Janna %A Paiva,Kristi A %A Zapata Jr,Jose %A Moreno-Vasquez,Andrea %A Grigsby,Timothy J %A Ryan-Pettes,Stacy R %A Parra-Medina,Deborah %A Estrada,Vanessa %A Li,Shiyu %A Wang,Jing %+ School of Nursing, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, United States, 1 210 450 8561, wangj1@uthscsa.edu %K Screening, Brief Intervention, and Referral to Treatment (SBIRT) %K Hispanic Americans %K behavioral economics %K rural population %K diabetes %K screening %D 2020 %7 24.3.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Access to diabetes education and resources for diabetes self-management is limited in rural communities, despite higher rates of diabetes in rural populations compared with urban populations. Technology and mobile health (mHealth) interventions can reduce barriers and improve access to diabetes education in rural communities. Screening, Brief Intervention, and Referral to Treatment (SBIRT) and financial incentives can be used with mHealth interventions to increase the uptake of diabetes education; however, studies have not examined their combined use for diabetes self-management in rural settings. Objective: This two-phase Stage 1 feasibility study aimed to use a mixed methods design to examine the feasibility and acceptability of an mHealth diabetes education program combining SBIRT and financial incentives to engage rural individuals. Methods: In Phase 1, we aimed to develop, adapt, and refine the intervention protocol. In Phase 2, a 3-month quasi-experimental study was conducted with individuals from 2 rural communities in South Texas. Study participants were individuals who attended free diabetes screening events in their community. Those with low or medium risk received health education material, whereas those with high risk or those with a previous diagnosis of diabetes participated in motivational interviewing and enrolled in the 6-week mHealth Diabetes Self-Management Education Program under either an unconditional or aversion incentive contract. The participants returned for a 3-month follow-up. Feasibility and acceptability of the intervention were determined by the rate of participant recruitment and retention, the fidelity of program delivery and compliance, and the participant’s satisfaction with the intervention program. Results: Of the 98 screened rural community members in South Texas, 72 individuals met the study eligibility and 62 individuals agreed to enroll in the study. The sample was predominately female and Hispanic, with an average age of 52.6 years. The feedback from study participants indicated high levels of satisfaction with the mHealth diabetes education program. In the poststudy survey, the participants reported high levels of confidence to continue lifestyle modifications, that is, weight loss, physical activity, and diet. The retention rate was 50% at the 3-month follow-up. Participation in the intervention was high at the beginning and dissipated in the later weeks regardless of the incentive contract type. Positive changes were observed in weight (mean -2.64, SD 6.01; P<.05) and glycemic control index (-.30; P<.05) in all participants from baseline to follow-up. Conclusions: The finding showed strong feasibility and acceptability of study recruitment and enrollment. The participants’ participation and retention were reasonable given the unforeseen events that impacted the study communities during the study period. Combining mHealth with SBIRT has the potential to reach individuals with need to participate in diabetes education in rural communities. %M 32207694 %R 10.2196/16683 %U http://mhealth.jmir.org/2020/3/e16683/ %U https://doi.org/10.2196/16683 %U http://www.ncbi.nlm.nih.gov/pubmed/32207694 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 3 %P e15390 %T A Mobile-Based Intervention for Glycemic Control in Patients With Type 2 Diabetes: Retrospective, Propensity Score-Matched Cohort Study %A Li,Jing %A Sun,Li %A Wang,Yaogang %A Guo,Lichuan %A Li,Daiqing %A Liu,Chang %A Sun,Ning %A Xu,Zheng %A Li,Shu %A Jiang,Yunwen %A Wang,Yuan %A Zhang,Shunming %A Chen,Liming %+ National Health Commission Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, No 6, Huanruibei Road, Beichen District, Tianjin, 300134, China, 86 13920979401, xfx22081@vip.163.com %K mobile health %K glycemic control %K type 2 diabetes %K propensity score matching %D 2020 %7 11.3.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile-based interventions appear to be promising in ameliorating huge burdens experienced by patients with type 2 diabetes. However, it is unclear how effective mobile-based interventions are in glycemic management of patients with type 2 diabetes based on real-world evidence. Objective: This study aimed to evaluate the effectiveness of a mobile-based intervention on glycemic control in patients with type 2 diabetes based on real-world population data. Methods: This retrospective, propensity score-matched cohort study analyzed longitudinal data from a clinical electronic health database. The study population included 37,913 patients with type 2 diabetes at cohort entry between October 1, 2016, and July 31, 2018. A total of 2400 patients were matched 1:1, using propensity score matching, into the usual care and mobile health (mHealth) groups. The primary outcomes of glycemic control included control rates of glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and postprandial 2-hour blood glucose (P2BG). Mean values and variation trends of difference with 95% CI were the secondary outcomes. The general linear model was used to calculate repeated-measures analyses of variance to examine the differences between the two groups. Subgroup and sensitivity analyses were performed. Results: Of the 2400 patients included in the analysis, 1440 (60.00%) were male and the mean age was 52.24 years (SD 11.56). At baseline, the control rates of HbA1c, FBG, and P2BG in the mHealth and usual care groups were 45.75% versus 47.00% (P=.57), 38.03% versus 32.76% (P=.07), and 47.32% versus 47.89% (P=.83), respectively. At the 3-, 6-, 9-, and 12-month follow-ups, the mHealth group reported higher control rates of HbA1c than did the usual care group: 69.97% versus 46.06% (P<.001), 71.89% versus 61.24% (P=.004), 75.38% versus 53.44% (P<.001), and 72.31% versus 46.70% (P<.001), respectively. At the four follow-up sessions, the control rates of FBG in the mHealth and usual care groups were statistically different: 59.24% versus 34.21% (P<.001), 56.61% versus 35.14% (P<.001), 59.54% versus 34.99% (P<.001), and 59.77% versus 32.83% (P<.001), respectively. At the four follow-up sessions, the control rates of P2BG in the mHealth group were statistically higher than in the usual care group: 79.72% versus 48.75% (P<.001), 80.20% versus 57.45% (P<.001), 81.97% versus 54.07% (P<.001), and 76.19% versus 54.21% (P=.001), respectively. At the four follow-up sessions, the percentages of HbA1c reduction in the mHealth group were 8.66% (95% CI 6.69-10.63), 10.60% (95% CI 8.66-12.54), 10.64% (95% CI 8.70-12.58), and 8.11% (95% CI 6.08-10.14), respectively. At the four follow-up sessions, the percentages of P2BG reduction in the mHealth group were 8.44% (95% CI 7.41-10.73), 17.77% (95% CI 14.98-20.23), 16.23% (95% CI 13.05-19.35), and 16.91% (95% CI 13.17-19.84), respectively. Starting from the sixth month, the mean HbA1c and P2BG values in the two groups increased slightly. Conclusions: This mobile-based intervention delivered by a multidisciplinary team can better improve glycemic control rates of patients with type 2 diabetes than usual care. These effects were best sustained within the first 6 months. Starting from the sixth month, intensive management needs to be conducted to maintain long-term effectiveness of the mobile-based intervention. %M 32159518 %R 10.2196/15390 %U http://mhealth.jmir.org/2020/3/e15390/ %U https://doi.org/10.2196/15390 %U http://www.ncbi.nlm.nih.gov/pubmed/32159518 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 3 %P e17455 %T Effectiveness of Lilly Connected Care Program (LCCP) App-Based Diabetes Education for Patients With Type 2 Diabetes Treated With Insulin: Retrospective Real-World Study %A Zhang,Yiyu %A Liu,Chaoyuan %A Luo,Shuoming %A Huang,Jin %A Li,Xia %A Zhou,Zhiguang %+ Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No 139, Renmin Road, Changsha, , China, 86 073185292154, zhouzhiguang@csu.edu.cn %K diabetes mellitus %K mobile app %K diabetes self-management education %K glycemic control %D 2020 %7 6.3.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes poses heavy economic and social burdens worldwide. Mobile apps show great potential for diabetes self-management education. However, there is limited evidence for the effectiveness of providing general diabetes education through mobile apps. Objective: The aim of this study was to clarify the effectiveness of Lilly Connected Care Program (LCCP) app-based diabetes education for glycemic control. Methods: This retrospective cohort study included patients with diabetes recruited to the LCCP platform from September 1, 2018, to May 31, 2019. Each patient was followed for 12 weeks. According to the number of diabetes education courses they had completed, the patients were divided into the following three groups: group A (0-4 courses), group B (5-29 courses), and group C (≥30 courses). The main outcomes were the change in blood glucose at the 12th week compared with baseline and the differences in blood glucose at the 12th week among the three groups. The associations of the number of diabetes education courses completed with the average blood glucose and frequency of self-monitoring of blood glucose (SMBG) at the 12th week were assessed by multivariate linear regression analyses controlling for other confounding covariates. Univariate and multivariate linear regression analyses were used to assess factors influencing patients’ engagement in the diabetes education courses. Results: A total of 5011 participants were enrolled. Their mean fasting blood glucose (FBG) and postprandial blood glucose (PBG) were significantly lower at the 12th week than at baseline (FBG, 7.46 [standard deviation (SD) 1.95] vs 7.79 [SD 2.18] mmol/L, P<.001; PBG, 8.94 [SD 2.74] vs 9.53 [SD 2.81] mmol/L, P<.001). The groups that completed more diabetes education courses had lower FBG (group B, β=−0.14, 95% CI −0.26 to −0.03; group C, β=−0.29, 95% CI −0.41 to −0.16; P for trend <.001) and PBG (group B, β=−0.29, 95% CI −0.46 to −0.11; group C, β=−0.47, 95% CI −0.66 to −0.28; P for trend <.001) and a higher frequency of SMBG at the 12th week (group B, β=1.17, 95% CI 0.81-1.53; group C, β=4.21, 95% CI 3.81-4.62; P for trend <.001) when compared with the findings in group A. Age and education were related to patients’ engagement in the diabetes education courses. Middle-aged patients (35-59 years old) and elderly patients (≥60 years old) completed more diabetes education courses (middle-aged group, β=2.22, P=.01; elderly group, β=2.42, P=.02) than young patients (18-34 years old). Conclusions: LCCP app-based diabetes education is effective for glycemic control and SMBG behavior improvement in patients with type 2 diabetes receiving insulin therapy. Young patients’ engagement in the education courses was relatively low. We need to conduct in-depth interviews with users to further improve the curriculum. %M 32141838 %R 10.2196/17455 %U https://mhealth.jmir.org/2020/3/e17455 %U https://doi.org/10.2196/17455 %U http://www.ncbi.nlm.nih.gov/pubmed/32141838 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 2 %P e15364 %T Medication Management Apps for Diabetes: Systematic Assessment of the Transparency and Reliability of Health Information Dissemination %A Huang,Zhilian %A Lum,Elaine %A Car,Josip %+ Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Clinical Sciences Building, Level 18, Singapore, 308322, Singapore, 65 65923945, ZHUANG014@e.ntu.edu.sg %K health apps %K digital health %K diabetes %K privacy %K evidence-based guidance %D 2020 %7 19.2.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Smartphone apps are increasingly used for diabetes self-management because of their ubiquity and ability to help users to personalize health care management. The number of diabetes apps has proliferated in recent years, but only a small subset of apps that pose a higher risk are regulated by governmental agencies. The transparency and reliability of information sources are unclear for apps that provide health care advice and are not regulated by governmental agencies. Objective: This study aimed to assess the transparency and reliability of information disseminated via diabetes apps against 8 criteria adapted from the Health On the Net code of conduct (HONcode) principles. Methods: English-language diabetes-related terms were searched on a market explorer (42matters) on June 12, 2018. Apps with medication and blood glucose management features were downloaded and evaluated against the App-HONcode criteria adapted from the 8 HONcode principles: authoritative, complementarity, privacy, attribution, justifiability, transparency, financial disclosure, and advertising policy. Apps were profiled by operating platforms (ie, Android and iOS) and the number of downloads (ie, Android only: ≥100,000 downloads and <100,000 downloads). Results: A total of 143 apps (81 Android and 62 iOS) were downloaded and assessed against the adapted App-HONcode criteria. Most of the apps on the Android and iOS platforms fulfilled between 2 and 6 criteria, but few (20/143, 14.0%) apps mentioned the qualifications of individuals who contributed to app development. Less than half (59/143, 39.2%) of the apps disclaimed that the information provided or app functions do not replace the advice of the health care provider. A higher proportion of iOS apps fulfilled 5 or more App-HONcode criteria compared with Android apps. However, Android apps were more likely to have the developer’s email listed on the app store (Android: 75/81, 98%; and iOS: 52/62, 84%; P=.005) compared with iOS apps. Of the Android apps assessed, a significantly higher proportion of highly downloaded apps had a privacy and confidentiality clause (high downloads: 15/17, 88%; and low downloads: 33/64, 52%; P=.006) and were more likely to discuss their financial sources (high downloads: 14/17, 82%; and low downloads: 32/64, 50%; P=.03) compared with apps with a low number of downloads. Conclusions: Gaps in the disclosure of the developer’s qualification, funding source, and the complementary role of the app in disease management were identified. App stores, developers, and medical providers should collaborate to close these gaps and provide more transparency and reliability to app users. Future work can further examine the consent-seeking process for data collection, data management policies, the appropriateness of advertising content, and clarity of privacy clause of these apps. %M 32130163 %R 10.2196/15364 %U http://mhealth.jmir.org/2020/2/e15364/ %U https://doi.org/10.2196/15364 %U http://www.ncbi.nlm.nih.gov/pubmed/32130163 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 12 %P e15401 %T Effectiveness of Smartphone App–Based Interactive Management on Glycemic Control in Chinese Patients With Poorly Controlled Diabetes: Randomized Controlled Trial %A Zhang,Lei %A He,Xingxing %A Shen,Yun %A Yu,Haoyong %A Pan,Jiemin %A Zhu,Wei %A Zhou,Jian %A Bao,Yuqian %+ Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 600 Yishan Road, Shanghai, 200233, China, 86 2164369181, zhoujian@sjtu.edu.cn %K app %K self-management %K interactive management %K guidance %K glycated hemoglobin A1c %K diabetes %D 2019 %7 9.12.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: In recent years, the rapid development of mobile medical technology has provided multiple ways for the long-term management of chronic diseases, especially diabetes. As a new type of management model, smartphone apps are global, convenient, cheap, and interactive. Although apps were proved to be more effective at glycemic control, compared with traditional computer- and Web-based telemedicine technologies, how to gain a further and sustained improvement is still being explored. Objective: The objective of this study was to investigate the effectiveness of an app-based interactive management model by a professional health care team on glycemic control in Chinese patients with poorly controlled diabetes. Methods: This study was a 6-month long, single-center, prospective randomized controlled trial. A total of 276 type 1 or type 2 diabetes patients were enrolled and randomized to the control group (group A), app self-management group (group B), and app interactive management group (group C) in a 1:1:1 ratio. The primary outcome was the change in glycated hemoglobin (HbA1c) level. Missing data were handled by multiple imputation. Results: At months 3 and 6, all 3 groups showed significant decreases in HbA1c levels (all P<.05). Patients in the app interactive management group had a significantly lower HbA1clevel than those in the app self-management group at 6 months (P=.04). The average HbA1c reduction in the app interactive management group was larger than that in the app self-management and control groups at both months 3 and 6 (all P<.05). However, no differences in HbA1c reduction were observed between the app self-management and control groups at both months 3 and 6 (both P>.05). Multivariate line regression analyses also showed that the app interactive management group was associated with the larger reduction of HbA1c compared with groups A and B at both months 3 and 6 (all P>.05). In addition, the app interactive management group had better control of triglyceride and high-density lipoprotein cholesterol levels at both months 3 and 6 compared with baseline (both P<.05). Conclusions: In Chinese patients with poorly controlled diabetes, it was difficult to achieve long-term effective glucose improvement by using app self-management alone, but combining it with interactive management can help achieve rapid and sustained glycemic control. Trial Registration: ClinicalTrials.gov NCT02589730; https://clinicaltrials.gov/ct2/show/NCT02589730. %M 31815677 %R 10.2196/15401 %U https://www.jmir.org/2019/12/e15401 %U https://doi.org/10.2196/15401 %U http://www.ncbi.nlm.nih.gov/pubmed/31815677 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 11 %P e14452 %T Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial %A Faruqui,Syed Hasib Akhter %A Du,Yan %A Meka,Rajitha %A Alaeddini,Adel %A Li,Chengdong %A Shirinkam,Sara %A Wang,Jing %+ Center on Smart and Connected Health Technologies, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, United States, 1 210 450 8561, wangj1@uthscsa.edu %K type 2 diabetes %K long short-term memory (LSTM)-based recurrent neural networks (RNNs) %K glucose level prediction %K mobile health lifestyle data %D 2019 %7 1.11.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Type 2 diabetes mellitus (T2DM) is a major public health burden. Self-management of diabetes including maintaining a healthy lifestyle is essential for glycemic control and to prevent diabetes complications. Mobile-based health data can play an important role in the forecasting of blood glucose levels for lifestyle management and control of T2DM. Objective: The objective of this work was to dynamically forecast daily glucose levels in patients with T2DM based on their daily mobile health lifestyle data including diet, physical activity, weight, and glucose level from the day before. Methods: We used data from 10 T2DM patients who were overweight or obese in a behavioral lifestyle intervention using mobile tools for daily monitoring of diet, physical activity, weight, and blood glucose over 6 months. We developed a deep learning model based on long short-term memory–based recurrent neural networks to forecast the next-day glucose levels in individual patients. The neural network used several layers of computational nodes to model how mobile health data (food intake including consumed calories, fat, and carbohydrates; exercise; and weight) were progressing from one day to another from noisy data. Results: The model was validated based on a data set of 10 patients who had been monitored daily for over 6 months. The proposed deep learning model demonstrated considerable accuracy in predicting the next day glucose level based on Clark Error Grid and ±10% range of the actual values. Conclusions: Using machine learning methodologies may leverage mobile health lifestyle data to develop effective individualized prediction plans for T2DM management. However, predicting future glucose levels is challenging as glucose level is determined by multiple factors. Future study with more rigorous study design is warranted to better predict future glucose levels for T2DM management. %M 31682586 %R 10.2196/14452 %U https://mhealth.jmir.org/2019/11/e14452 %U https://doi.org/10.2196/14452 %U http://www.ncbi.nlm.nih.gov/pubmed/31682586 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 3 %P e12600 %T Acceptability of Mobile Health Interventions to Increase Diabetic Risk Factor Awareness Among the Commuter Population in Johannesburg: Descriptive Cross-Sectional Study %A Fischer,Alex %A Chadyiwa,Martha %A Tshuma,Ndumiso %A Nkosi,Vusumuzi %+ Department of Environmental Health, Faculty of Health Sciences, University of Johannesburg, John Orr Building, Doornfontein Campus, Doornfontein, Johannesburg, 2094, South Africa, 27 0737762705, afischer@wrhi.ac.za %K mHealth %K diabetes mellitus %K noncommunicable disease %K South Africa %D 2019 %7 20.09.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: Developing countries are experiencing a shift from infectious diseases such as HIV and tuberculosis to noncommunicable diseases (NCDs) such as diabetes. Diabetes accounts for more disability-adjusted life years than any other NCD in South Africa, and research has identified a number of preventable risk factors; however, there is not enough evidence from lower resource settings as to how best to disseminate this information to the population. Today, 90% of the world’s population lives in mobile phone coverage areas, and this provides a unique opportunity to reach large populations with health information. Objective: This study aimed to investigate how potential mobile health (mHealth) platforms should be paired with diabetes risk factor education so that at-risk communities are empowered with information to prevent and manage diabetes. Methods: A Likert-style survey was distributed to commuters in the City of Johannesburg in July 2018 that explored participants’ background characteristics as well as their knowledge and awareness surrounding diabetic risk factors (such as exercise, smoking, and hypertension) and their comfort level with various information delivery methods (such as WhatsApp, short message service, and email). The grouped variables from diabetic risk factors and information delivery methods were described with mean Likert scores and then investigated for relationships with Spearman Rho correlation coefficients. Results: Background characteristics revealed that the self-reported prevalence of diabetes was twice as high in this studied commuter population than the national average. WhatsApp was the most favorable mHealth information delivery method and had a moderate correlation coefficient with diet and nutrition (0.338; P<.001) as well as a weaker correlation with physical activity (0.243; P<.001). Although not as robust as the WhatsApp correlations, each of the other information delivery methods also showed weaker, yet statistically significant, relationships with one or more of the risk factors. Conclusions: The elevated self-reported diabetes prevalence reinforces the need for diabetes risk factor education in the studied commuter population of Johannesburg. The most feasible mHealth intervention for diabetic risk factor education should focus on WhatsApp messaging while also offering content across other mHealth and traditional platforms to remove barriers to access and enhance the user experience. The content should emphasize diet and nutrition as well as physical activity while also incorporating information on secondary risk factors. %M 31586363 %R 10.2196/12600 %U http://diabetes.jmir.org/2019/3/e12600/ %U https://doi.org/10.2196/12600 %U http://www.ncbi.nlm.nih.gov/pubmed/31586363 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 9 %P e14914 %T A Smartphone App to Improve Medication Adherence in Patients With Type 2 Diabetes in Asia: Feasibility Randomized Controlled Trial %A Huang,Zhilian %A Tan,Eberta %A Lum,Elaine %A Sloot,Peter %A Boehm,Bernhard Otto %A Car,Josip %+ Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Level 18, 11 Mandalay Road, Singapore, 308232, Singapore, 65 65141221, zhuang014@e.ntu.edu.sg %K smartphone apps %K mobile phone apps %K medication adherence %K type 2 diabetes %K feasibility trial %K pilot study %D 2019 %7 12.09.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The efficacy of smartphone apps for improving medication adherence in type 2 diabetes is not well studied in Asian populations. Objective: This study aimed to determine the feasibility, acceptability, and clinical outcomes of using a smartphone app to improve medication adherence in a multiethnic Asian population with type 2 diabetes. Methods: We block randomized 51 nonadherent and digitally literate patients with type 2 diabetes between the ages of 21 and 75 years into two treatment arms (control: usual care; intervention: usual care+Medisafe app) and followed them up for 12 weeks. Recruitment occurred at a public tertiary diabetes specialist outpatient center in Singapore. The intervention group received email reminders to complete online surveys monthly, while the control group only received an email reminder(s) at the end of the study. Barriers to medication adherence and self-appraisal of diabetes were assessed using the Adherence Starts with Knowledge-12 (ASK-12) and Appraisal of Diabetes Scale (ADS) questionnaires at baseline and poststudy in both groups. Perception toward medication adherence and app usage, attitude, and satisfaction were assessed in the intervention group during and after the follow-up period. Sociodemographic data were collected at baseline. Clinical data (ie, hemoglobin A1c, body mass index, low-density lipoprotein, high-density lipoprotein, and total cholesterol levels) were extracted from patients’ electronic medical records. Results: A total of 51 (intervention group: 25 [49%]; control group: 26 [51%]) participants were randomized, of which 41 (intervention group: 22 [88.0%]; control group: 19 [73.1%]) completed the poststudy survey. The baseline-adjusted poststudy ASK-12 score was significantly lower in the intervention group than in the control group (mean difference: 4.7, P=.01). No changes were observed in the clinical outcomes. The average 12-week medication adherence rate of participants tracked by the app was between 38.3% and 100% in the intervention group. The majority (>80%) of the participants agreed that the app was easy to use and made them more adherent to their medication. Conclusions: Our feasibility study showed that among medication-nonadherent patients with type 2 diabetes, a smartphone app intervention was acceptable, improved awareness of medication adherence, and reduced self-reported barriers to medication adherence, but did not improve clinical outcomes in a developed Asian setting. %M 31516127 %R 10.2196/14914 %U http://mhealth.jmir.org/2019/9/e14914/ %U https://doi.org/10.2196/14914 %U http://www.ncbi.nlm.nih.gov/pubmed/31516127 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 8 %P e13971 %T A Comparison of Functional Features in Chinese and US Mobile Apps for Diabetes Self-Management: A Systematic Search in App Stores and Content Analysis %A Wu,Yuan %A Zhou,Yiling %A Wang,Xuan %A Zhang,Qi %A Yao,Xun %A Li,Xiaodan %A Li,Jianshu %A Tian,Haoming %A Li,Sheyu %+ Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, 37# Guoxue Road, Wuhou District, Chengdu, 610041, China, 86 13194874843, lisheyu@gmail.com %K diabetes mellitus %K self-management %K mobile apps %K risk assessment %K prevalence %K China %K United States %D 2019 %7 28.08.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health interventions are widely used for self-management of diabetes, which is one of the most burdensome noncommunicable chronic diseases worldwide. However, little is known about the distribution of characteristics and functions of in-store mobile apps for diabetes. Objective: This study aimed to investigate the distribution of characteristics and functions of the in-store mobile apps for self-management of diabetes in the United States and China using a predefined functional taxonomy, which was developed and published in our previous study. Methods: We identified apps by searching diabetes in English or Chinese in the Apple iTunes Store and Android Markets (both in the United States and China) and included apps for diabetes self-management. We examined the validity and reliability of the predefined functional taxonomy with 3 dimensions: clinical module, functional module, and potential risk. We then classified all functions in the included apps according to the predefined taxonomy and compared the differences in the features of these apps between the United States and China. Results: We included 171 mobile diabetes apps, with 133 from the United States and 38 from China. Apps from both countries faced the challenges of evidence-based information, proper risk assessment, and declaration, especially Chinese apps. More Chinese apps provide app-based communication functions (general communication: Chinese vs US apps, 39%, 15/38 vs 18.0%, 24/133; P=.006 and patient-clinician communication: Chinese vs US apps, 68%, 26/38 vs 6.0%, 8/133; P<.001), whereas more US apps provide the decision-making module (Chinese vs US apps, 0%, 0/38 vs 23.3%, 31/133; P=.001), which is a high-risk module. Both complication prevention (Chinese vs US apps, 8%, 3/38 vs 3.8%, 5/133; P=.50) and psychological care (Chinese vs US apps, 0%, 0/38 vs 0.8%, 1/133; P>.99) are neglected by the 2 countries. Conclusions: The distribution of characteristics and functions of in-store mobile apps for diabetes self-management in the United States was different from China. The design of in-store diabetes apps needs to be monitored closely. %M 31464191 %R 10.2196/13971 %U http://mhealth.jmir.org/2019/8/e13971/ %U https://doi.org/10.2196/13971 %U http://www.ncbi.nlm.nih.gov/pubmed/31464191 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 8 %P e15023 %T Factors Influencing Patients’ Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey %A Zhang,Yiyu %A Liu,Chaoyuan %A Luo,Shuoming %A Xie,Yuting %A Liu,Fang %A Li,Xia %A Zhou,Zhiguang %+ Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No 139, Renmin Road, Changsha, 410011, China, 86 073185292154, zhouzhiguang@csu.edu.cn %K diabetes mellitus %K mobile applications %K survey %K structural equation modeling %K China %D 2019 %7 13.08.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Diabetes poses heavy social and economic burdens worldwide. Diabetes management apps show great potential for diabetes self-management. However, the adoption of diabetes management apps by diabetes patients is poor. The factors influencing patients’ intention to use these apps are unclear. Understanding the patients’ behavioral intention is necessary to support the development and promotion of diabetes app use. Objective: This study aimed to identify the determinants of patients’ intention to use diabetes management apps based on an integrated theoretical model. Methods: The hypotheses of our research model were developed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). From April 20 to May 20, 2019, adult patients with diabetes across China, who were familiar with diabetes management apps, were surveyed using the Web-based survey tool Sojump. Structural equation modeling was used to analyze the data. Results: A total of 746 participants who met the inclusion criteria completed the survey. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=0.482; P=.001). Performance expectancy (β=0.482; P=.001), social influence (β=0.223; P=.003), facilitating conditions (β=0.17; P=.006), perceived disease threat (β=0.073; P=.005), and perceived privacy risk (β=–0.073; P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy, and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=0.259; P=.001). Conclusions: Performance expectancy and social influence are the most important determinants of the intention to use diabetes management apps. Health care technology companies should improve the usefulness of apps and carry out research to provide clinical evidence for the apps’ effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients’ intention to use diabetes management apps. Context-related determinants should also be taken into consideration. %M 31411146 %R 10.2196/15023 %U http://www.jmir.org/2019/8/e15023/ %U https://doi.org/10.2196/15023 %U http://www.ncbi.nlm.nih.gov/pubmed/31411146 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 7 %P e13906 %T Barriers and Facilitators to the Implementation of a Mobile Insulin Titration Intervention for Patients With Uncontrolled Diabetes: A Qualitative Analysis %A Rogers,Erin %A Aidasani,Sneha R %A Friedes,Rebecca %A Hu,Lu %A Langford,Aisha T %A Moloney,Dana N %A Orzeck-Byrnes,Natasha %A Sevick,Mary Ann %A Levy,Natalie %+ Department of Population Health, New York University School of Medicine, 180 Madison Avenue, New York, NY, 10016, United States, 1 646 501 3556, erin.rogers@nyulangone.org %K type 2 diabetes %K telemedicine %K implementation science %D 2019 %7 31.07.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In 2016, a short message service text messaging intervention to titrate insulin in patients with uncontrolled type 2 diabetes was implemented at two health care facilities in New York City. Objective: This study aimed to conduct a qualitative evaluation assessing barriers to and the facilitators of the implementation of the Mobile Insulin Titration Intervention (MITI) program into usual care. Methods: We conducted in-depth interviews with 36 patients enrolled in the MITI program and the staff involved in MITI (n=19) in the two health care systems. Interviews were transcribed and iteratively coded by two study investigators, both inductively and deductively using a codebook guided by the Consolidated Framework for Implementation Research. Results: Multiple facilitator themes emerged: (1) MITI had strong relative advantages to in-person titration, including its convenience and time-saving design, (2) the free cost of MITI was important to the patients, (3) MITI was easy to use and the patients were confident in their ability to use it, (4) MITI was compatible with the patients’ home routines and clinic workflow, (5) the patients and staff perceived MITI to have value beyond insulin titration by reminding and motivating the patients to engage in healthy behaviors and providing a source of patient support, and (6) implementation in clinics was made easy by having a strong implementation climate, communication networks to spread information about MITI, and a strong program champion. The barriers identified included the following: (1) language limitations, (2) initial nurse concerns about the scope of practice changes required to deliver MITI, (3) initial provider knowledge gaps about the program, and (4) provider perceptions that MITI might not be appropriate for some patients (eg, older or not tech-savvy). There was also a theme that emerged during the patient and staff interviews of an unmet need for long-term additional diabetes management support among this population, specifically diet, nutrition, and exercise support. Conclusions: The patients and staff were overwhelmingly supportive of MITI and believed that it had many benefits and that it was compatible with the clinic workflow and patients’ lives. Initial implementation efforts should address staff training and nurse concerns. Future research should explore options for integrating additional diabetes support for patients. %M 31368439 %R 10.2196/13906 %U http://mhealth.jmir.org/2019/7/e13906/ %U https://doi.org/10.2196/13906 %U http://www.ncbi.nlm.nih.gov/pubmed/31368439 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 3 %P e12936 %T An Evaluation of Digital Health Tools for Diabetes Self-Management in Hispanic Adults: Exploratory Study %A Yingling,Leah %A Allen,Nancy A %A Litchman,Michelle L %A Colicchio,Vanessa %A Gibson,Bryan S %+ Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way #140, Salt Lake City, UT, 84108, United States, 1 801 582 1565, bryan.gibson@utah.edu %K type 2 diabetes %K Hispanic %K blood glucose self-monitoring %K culturally appropriate technology %K mobile app %D 2019 %7 16.07.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: Although multiple self-monitoring technologies for type 2 diabetes mellitus (T2DM) show promise for improving T2DM self-care behaviors and clinical outcomes, they have been understudied in Hispanic adult populations who suffer disproportionately from T2DM. Objective: The objective of this study was to evaluate the acceptability, feasibility, and potential integration of wearable sensors for diabetes self-monitoring among Hispanic adults with self-reported T2DM. Methods: We conducted a pilot study of T2DM self-monitoring technologies among Hispanic adults with self-reported T2DM. Participants (n=21) received a real-time continuous glucose monitor (RT-CGM), a wrist-worn physical activity (PA) tracker, and a tablet-based digital food diary to self-monitor blood glucose, PA, and food intake, respectively, for 1 week. The RT-CGM captured viewable blood glucose concentration (mg/dL) and PA trackers collected accelerometer-based data, viewable on the device or an associated tablet app. After 1 week of use, we conducted a semistructured interview with each participant to understand experiences and thoughts on integration of the data from the devices into a technology-facilitated T2DM self-management intervention. We also conducted a brief written questionnaire to understand participants’ self-reported T2DM history and past experience using digital health tools for T2DM self-management. Feasibility was measured by device utilization and objective RT-CGM, PA tracker, and diet logging data. Acceptability and potential integration were evaluated through thematic analysis of verbatim interview transcripts. Results: Participants (n=21, 76% female, 50.4 [SD 11] years) had a mean self-reported hemoglobin A1c of 7.4 [SD 1.8] mg/dL and had been diagnosed with T2DM for 7.4 [SD 5.2] years (range: 1-16 years). Most (89%) were treated with oral medications, whereas the others self-managed through diet and exercise. Nearly all participants (n=20) used both the RT-CGM and PA tracker, and 52% (11/21) logged at least one meal, with 33% (7/21) logging meals for 4 or more days. Of the 8 possible days, PA data were recorded for 7.1 [SD 1.8] days (range: 2-8), and participants averaged 7822 [SD 3984] steps per day. Interview transcripts revealed that participants felt most positive about the RT-CGM as it unveiled previously unknown relationships between lifestyle and health and contributed to changes in T2DM-related thoughts and behaviors. Participants felt generally positive about incorporating the wearable sensors and mobile apps into a future intervention if support were provided by a health coach or health care provider, device training were provided, apps were tailored to their language and culture, and content were both actionable and delivered on a single platform. Conclusions: Sensor-based tools for facilitating T2DM self-monitoring appear to be a feasible and acceptable technology among low-income Hispanic adults. We identified barriers to acceptability and highlighted preferences for wearable sensor integration in a community-based intervention. These findings have implications for the design of T2DM interventions targeting Hispanic adults. %M 31313657 %R 10.2196/12936 %U http://diabetes.jmir.org/2019/3/e12936/ %U https://doi.org/10.2196/12936 %U http://www.ncbi.nlm.nih.gov/pubmed/31313657 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 7 %P e11527 %T Customizing the Types of Technologies Used by Patients With Type 1 Diabetes Mellitus for Diabetes Treatment: Case Series on Patient Experience %A Holubová,Anna %A Vlasáková,Martina %A Mužík,Jan %A Brož,Jan %+ Spin-off Company and Research Results Commercialization Center, First Faculty of Medicine, Charles University, Studnickova 2028/7, Prague, 12800, Czech Republic, 420 224 968 574, holubann@gmail.com %K type 1 diabetes mellitus %K technology %K self-management %K wearable electronic devices %K education %K telemedicine %D 2019 %7 09.07.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Despite the fact there are many wearable and mobile medical devices that enable patients to better self-manage their diabetes, not many patients are aware of all the options they have. In addition, there are those who are not fully satisfied with the devices they use, and those who often do not use them effectively. Objective: The study aimed to propose possible changes to the combination of devices used by 6 specific patients for diabetes self-management. We assessed the suitability of selected technical devices for diabetes control. Methods: Data of 6 patients (3 men and 3 women) with type 1 diabetes mellitus, who had been using the Diani telemedicine system for at least 3 months, were analyzed. The suitability of selected technical devices for diabetes control was ascertained using the data obtained via the Diani telemedicine system, as well as the patients’ subjective feelings and statements, their everyday life habits, and self-management of diabetes. Informed consent was signed and obtained from each of the patients included. Results: Each of the presented case studies describes how a given patient handled the system and its specific components based on his or her lifestyle, level of education, habits related to diabetes management, personality type, and other factors. At the conclusion of each case study, the best composition of devices for patients with similar personal descriptions was suggested. Conclusions: We believe this study can provide relevant guidance on how to help particular patients choose the technology that is best suited for their needs, based on the specific patient information we are able to obtain from them. Furthermore, clinicians or educators should be aware of available technologies a given patient can choose from. In addition, there is a substantial need for proper patient education in order for them to effectively use devices for diabetes self-management. %M 31290400 %R 10.2196/11527 %U https://mhealth.jmir.org/2019/7/e11527/ %U https://doi.org/10.2196/11527 %U http://www.ncbi.nlm.nih.gov/pubmed/31290400 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 3 %P e14032 %T Experiences of Adults With Type 1 Diabetes Using Glucose Sensor–Based Mobile Technology for Glycemic Variability: Qualitative Study %A Ritholz,Marilyn D %A Henn,Owen %A Atakov Castillo,Astrid %A Wolpert,Howard %A Edwards,Stephanie %A Fisher,Lawrence %A Toschi,Elena %+ Joslin Diabetes Center, 1 Joslin Place, Boston, MA, 02215, United States, 1 6173094196, marilyn.ritholz@joslin.harvard.edu %K diabetes mellitus, type 1 %K educational technology %K blood glucose self-monitoring %K qualitative research %D 2019 %7 08.07.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: Adults with type 1 diabetes (PWDs) face challenging self-management regimens including monitoring their glucose values multiple times a day to assist with achieving glycemic targets and reduce the risk of long-term diabetes complications. Recent advances in diabetes technology have reportedly improved glycemia, but little is known about how PWDs utilize mobile technology to make positive changes in their diabetes self-management. Objective: The aim of this qualitative study was to explore PWDs’ experiences using Sugar Sleuth, a glucose sensor–based mobile app and Web-based reporting system, integrated with the FreeStyle Libre glucose monitor that provides feedback about glycemic variability. Methods: We used a qualitative descriptive research design and conducted semistructured interviews with 10 PWDs (baseline mean glycated hemoglobin, HbA1c) 8.0%, (SD 0.45); 6 males and 4 females, aged 52 years (SD 15), type 1 diabetes (T1D) duration 31 years (SD 13), 40% (4/10, insulin pump) following a 14-week intervention during which they received clinical support and used Sugar Sleuth to evaluate and understand their glucose data. Audio-recorded interviews were transcribed, coded, and analyzed using thematic analysis and NVivo 11 (QSR International Pty Ltd). Results: A total of 4 main themes emerged from the data. Participants perceived Sugar Sleuth as an Empowering Tool that served to inform lifestyle choices and diabetes self-management tasks, promoted preemptive self-care actions, and improved discussions with clinicians. They also described Sugar Sleuth as providing a Source of Psychosocial Support and offering relief from worry, reducing glycemic uncertainty, and supporting positive feelings about everyday life with diabetes. Participants varied in their Approaches to Glycemic Data: 40% (4/10) described using Sugar Sleuth to review data, understand glycemic cause and effect, and plan for future self-care. On the contrary, 60% (6/10) were reluctant to review past data; they described receiving benefits from the immediate numbers and trend arrows, but the app still prompted them to enter in the suspected causes of glucose excursions within hours of their occurrence. Finally, only 2 participants voiced Concerns About Use of Sugar Sleuth; they perceived the app as sometimes too demanding of information or as not attuned to the socioeconomic backgrounds of PWDs from diverse populations. Conclusions: Results suggest that Sugar Sleuth can be an effective educational tool to enhance both patient-clinician collaboration and diabetes self-management. Findings also highlight the importance of exploring psychosocial and socioeconomic factors that may advance the understanding of PWDs’ individual differences when using glycemic technology and may promote the development of customized mobile tools to improve diabetes self-management. %M 31287065 %R 10.2196/14032 %U http://diabetes.jmir.org/2019/3/e14032/ %U https://doi.org/10.2196/14032 %U http://www.ncbi.nlm.nih.gov/pubmed/31287065 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 6 %N 6 %P e11701 %T Addressing Depression Comorbid With Diabetes or Hypertension in Resource-Poor Settings: A Qualitative Study About User Perception of a Nurse-Supported Smartphone App in Peru %A Brandt,Lena R %A Hidalgo,Liliana %A Diez-Canseco,Francisco %A Araya,Ricardo %A Mohr,David C %A Menezes,Paulo R %A Miranda,J Jaime %+ CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Avenida Armendariz 497, Miraflores, Lima, Peru, 51 12416978, fdiezcanseco@gmail.com %K mental health %K depression %K noncommunicable diseases %K mHealth %K smartphone %K developing countries %D 2019 %7 18.06.2019 %9 Original Paper %J JMIR Ment Health %G English %X Background: Smartphone apps could constitute a cost-effective strategy to overcome health care system access barriers to mental health services for people in low- and middle-income countries. Objective: The aim of this paper was to explore the patients’ perspectives of CONEMO (Emotional Control, in Spanish: Control Emocional), a technology-driven, psychoeducational, and nurse-supported intervention delivered via a smartphone app aimed at reducing depressive symptoms in people with diabetes, hypertension or both who attend public health care centers, as well as the nurses’ feedback about their role and its feasibility to be scaled up. Methods: This study combines data from 2 pilot studies performed in Lima, Peru, between 2015 and 2016, to test the feasibility of CONEMO. Interviews were conducted with 29 patients with diabetes, hypertension or both with comorbid depressive symptoms who used CONEMO and 6 staff nurses who accompanied the intervention. Using a content analysis approach, interview notes from patient interviews were transferred to a digital format, coded, and categorized into 6 main domains: the perceived health benefit, usability, adherence, user satisfaction with the app, nurse’s support, and suggestions to improve the intervention. Interviews with nurses were analyzed by the same approach and categorized into 4 domains: general feedback, evaluation of training, evaluation of study activities, and feasibility of implementing this intervention within the existing structures of health system. Results: Patients perceived improvement in their emotional health because of CONEMO, whereas some also reported better physical health. Many encountered some difficulties with using CONEMO, but resolved them with time and practice. However, the interactive elements of the app, such as short message service, android notifications, and pop-up messages were mostly perceived as challenging. Satisfaction with CONEMO was high, as was the self-reported adherence. Overall, patients evaluated the nurse accompaniment positively, but they suggested improvements in the technological training and an increase in the amount of contact. Nurses reported some difficulties in completing their tasks and explained that the CONEMO intervention activities competed with their everyday work routine. Conclusions: Using a nurse-supported smartphone app to reduce depressive symptoms among people with chronic diseases is possible and mostly perceived beneficial by the patients, but it requires context-specific adaptations regarding the implementation of a task shifting approach within the public health care system. These results provide valuable information about user feedback for those building mobile health interventions for depression. %M 31215511 %R 10.2196/11701 %U https://mental.jmir.org/2019/6/e11701/ %U https://doi.org/10.2196/11701 %U http://www.ncbi.nlm.nih.gov/pubmed/31215511 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 8 %N 6 %P e12377 %T Mobile Messaging Support Versus Usual Care for People With Type 2 Diabetes on Glycemic Control: Protocol for a Multicenter Randomized Controlled Trial %A Farmer,Andrew %A Bobrow,Kirsty %A Leon,Natalie %A Williams,Nicola %A Phiri,Enita %A Namadingo,Hazel %A Cooper,Sara %A Prince,John %A Crampin,Amelia %A Besada,Donela %A Daviaud,Emmanuelle %A Yu,Ly-Mee %A Ngoma,Jonathan %A Springer,David %A Pauly,Bruno %A Norris,Shane %A Tarassenko,Lionel %A Nyirenda,Moffat %A Levitt,Naomi %+ Nuffield Department of Primary Care Health Sciences, University of Oxford, Primary Care Building, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 289280, andrew.farmer@phc.ox.ac.uk %K randomized controlled trial %K diabetes mellitus %K type 2 diabetes %K mobile health %K treatment adherence %D 2019 %7 30.5.2019 %9 Protocol %J JMIR Res Protoc %G English %X Background: Health outcomes for people treated for type 2 diabetes could be substantially improved in sub-Saharan Africa. Failure to take medicine regularly to treat diabetes has been identified as a major problem. Resources to identify and support patients who are not making the best use of medicine in low- and middle-income settings are scarce. Mobile phones are widely available in these settings, including among people with diabetes; linked technologies, such as short message service (SMS) text messaging, have shown promise in delivering low-cost interventions efficiently. However, evidence showing that these interventions will work when carried out at a larger scale and measuring the extent to which they will improve health outcomes when added to usual care is limited. Objective: The objective of this trial is to test the effectiveness of sending brief, automated SMS text messages for improving health outcomes and medication adherence in patients with type 2 diabetes compared to an active control. Methods: We will carry out a randomized trial recruiting from clinics in two contrasting settings in sub-Saharan Africa: Cape Town, South Africa, and Lilongwe, Malawi. Intervention messages will advise people about the benefits of their diabetes treatment and offer motivation and encouragement around lifestyle and use of medication. We allocated patients, using randomization with a minimization algorithm, to receive either three to four intervention messages per week or non-health-related messages every 6 weeks. We will follow up with participants for 12 months, measuring important risk factors for poor health outcomes and complications in diabetes. This will enable us to estimate potential health benefits, including the primary outcome of hemoglobin A1c (HbA1c) levels as a marker for long-term blood glucose control and a secondary outcome of blood pressure control. We will record the costs of performing these activities and estimate cost-effectiveness. We will also use process evaluation to capture the collection of medication and assess the reception of the intervention by participants and health care workers. Results: Recruitment to the trial began in September 2016 and follow-up of participants was completed in October 2018. Data collection from electronic health records and other routinely collected sources is continuing. The database lock is anticipated in June 2019, followed by analysis and disclosing of group allocation. Conclusions: The knowledge gained from this study will have wide applications and advance the evidence base for effectiveness of mobile phone-based, brief text messaging on clinical outcomes and in large-scale, operational settings. It will provide evidence for cost-effectiveness and acceptability that will further inform policy development and decision making. We will work with a wide network that includes patients, clinicians, academics, industry, and policy makers to help us identify opportunities for informing people about the work and raise awareness of what is being developed and studied. Trial Registration: ISRCTN Registry ISRCTN70768808; http://www.isrctn.com/ISRCTN70768808 (Archived by WebCite at http://www.webcitation.org/786316Zqk) International Registered Report Identifier (IRRID): DERR1-10.2196/12377 %M 31199346 %R 10.2196/12377 %U https://www.researchprotocols.org/2019/6/e12377/ %U https://doi.org/10.2196/12377 %U http://www.ncbi.nlm.nih.gov/pubmed/31199346 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 5 %P e13615 %T Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study %A Hansen,Anne Helen %A Bradway,Meghan %A Broz,Jan %A Claudi,Tor %A Henriksen,Øystein %A Wangberg,Silje C %A Årsand,Eirik %+ Centre for Quality Improvement and Development, University Hospital of North Norway, PO Box 35, Tromsø, 9038, Norway, 47 91619655, anne.helen.hansen@unn.no %K inequalities %K eHealth %K internet %K health care utilization %K cross-sectional study %K diabetes mellitus, type 1 %K diabetes mellitus, type 2 %K education %K income %K Norway %D 2019 %7 29.05.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes. Objective: The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and the association with socioeconomic status (SES) among people diagnosed with type 1 and type 2 diabetes mellitus (T1D and T2D, respectively). Methods: We used email survey data from 1250 members of the Norwegian Diabetes Association (aged 18-89 years), collected in 2018. Eligible for analyses were the 1063 respondents having T1D (n=523) and T2D (n=545). 5 respondents reported having both diabetes types and thus entered into both groups. Using descriptive statistics, we estimated the use of the different types of eHealth. By logistic regressions, we studied the associations between the use of these types of eHealth and SES (education and household income), adjusted for gender, age, and self-rated health. Results: We found that 87.0% (447/514) of people with T1D and 77.7% (421/542) of people with T2D had used 1 or more forms of eHealth sometimes or often during the previous year. The proportion of people using search engines was the largest in both diagnostic groups, followed by apps, social media, and video services. We found a strong association between a high level of education and the use of search engines, whereas there were no educational differences for the use of apps, social media, or video services. In both diagnostic groups, high income was associated with the use of apps. In people with T1D, lower income was associated with the use of video services. Conclusions: This paper indicates a digital divide among people with diabetes in Norway, with consequences that may contribute to sustaining and shaping inequalities in health outcomes. The strong relationship between higher education and the use of search engines, along with the finding that the use of apps, social media, and video services was not associated with education, indicates that adequate communication strategies for audiences with varying education levels should be a focus in future efforts to reduce inequalities in health outcomes. %M 31144669 %R 10.2196/13615 %U http://www.jmir.org/2019/5/e13615/ %U https://doi.org/10.2196/13615 %U http://www.ncbi.nlm.nih.gov/pubmed/31144669 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 5 %P e12965 %T A Mobile Lifestyle Management Program (GlycoLeap) for People With Type 2 Diabetes: Single-Arm Feasibility Study %A Koot,David %A Goh,Paul Soo Chye %A Lim,Robyn Su May %A Tian,Yubing %A Yau,Teng Yan %A Tan,Ngiap Chuan %A Finkelstein,Eric Andrew %+ Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore,, Singapore, 65 6516 2338, eric.finkelstein@duke-nus.edu.sg %K type 2 diabetes mellitus %K self-management %K mobile health %K mHealth %K mobile phone app %K mobile apps %K health coaching %K blood glucose %K single-arm feasibility study %K RE-AIM %D 2019 %7 24.05.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Singapore’s current prevalence of diabetes exceeds 13.6%. Although lifestyle modification can be effective for reducing the risks for complications of type 2 diabetes mellitus (T2DM), traditional lifestyle interventions are often difficult to administer in the primary care setting due to limited resources. Mobile health apps can address these limitations by offering low-cost, adaptable, and accessible platforms for disseminating lifestyle management interventions. Objective: Using the RE-AIM evaluation framework, this study assessed the potential effectiveness and feasibility of GlycoLeap, a mobile lifestyle management program for people with T2DM, as an add-on to standard care. Methods: This single-arm feasibility study recruited 100 patients with T2DM and glycated hemoglobin (HbA1c) levels of ≥7.5% from a single community health care facility in Singapore. All participants were given access to a 6-month mobile lifestyle management program, GlycoLeap, comprising online lessons and the Glyco mobile phone app with a health coaching feature. The GlycoLeap program was evaluated using 4 relevant dimensions of the RE-AIM framework: (1) reach (percentage who consented to participate out of all patients approached), (2) effectiveness (percentage point change in HbA1c [primary outcome] and weight loss [secondary outcome]), (3) implementation (program engagement as assessed by various participatory metrics), and (4) maintenance (postintervention user satisfaction surveys to predict the sustainability of GlycoLeap). Participants were assessed at baseline and at follow-up (≥12 weeks after starting the intervention). Results: A total of 785 patients were approached of whom 104 consented to participate, placing the reach at 13.2%. Four were excluded after eligibility screening, and 100 patients were recruited. Program engagement (implementation) started out high but decreased with time for all evaluated components. Self-reported survey data suggest that participants monitored their blood glucose on more days in the past week at follow-up compared to baseline (P<.001) and reported positive changes to their diet due to app engagement (P<.001) (implementation). Primary outcome data were available for 83 participants. Statistically significant improvements were observed for HbA1c (–1.3 percentage points, P<.001) with greater improvements for those who logged their weight more often (P=.007) (effectiveness). Participants also had a 2.3% reduction in baseline weight (P<.001) (effectiveness). User satisfaction was high with 74% (59/80) and 79% (63/80) of participants rating the app good or very good and claiming that they would probably or definitely recommend the app to others, respectively (maintenance). Conclusions: Although measures of program engagement decreased with time, clinically significant improvements in HbA1c were achieved with the potential for broader implementation. However, we cannot rule out that these improvements were due to factors unrelated to GlycoLeap. Therefore, we would recommend evaluating the effectiveness and cost effectiveness of GlycoLeap using a randomized controlled trial of at least 12 months. Trial Registration: ClinicalTrials.gov NCT03091517; https://clinicaltrials.gov/ct2/show/NCT03091517 (Archived by WebCite at http://www.webcitation.org/77rNqhwRn) %M 31127720 %R 10.2196/12965 %U http://mhealth.jmir.org/2019/5/e12965/ %U https://doi.org/10.2196/12965 %U http://www.ncbi.nlm.nih.gov/pubmed/31127720 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 2 %P e11017 %T Enhanced Self-Efficacy and Behavioral Changes Among Patients With Diabetes: Cloud-Based Mobile Health Platform and Mobile App Service %A Chao,Dyna YP %A Lin,Tom MY %A Ma,Wen-Ya %+ Healthcare Solution Center, Health Inventor of Taipei, 5F, No.22, Fushan Rd, Wenshan Dist, Taipei City, 116, Taiwan, 886 917508975, dynachao@gmail.com %K type 2 diabetes mellitus %K self-management %K health literacy %K patient engagement %K intervention %K word-of-mouth %D 2019 %7 10.05.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: The prevalence of chronic disease is increasing rapidly. Health promotion models have shifted toward patient-centered care and self-efficacy. Devices and mobile app in the Internet of Things (IoT) have become critical self-management tools for collecting and analyzing personal data to improve individual health outcomes. However, the precise effects of Web-based interventions on self-efficacy and the related motivation factors behind individuals’ behavioral changes have not been determined. Objective: The objective of this study was to gain insight into patients' self-efficacy with newly diagnosed diabetes (type 2 diabetes mellitus) and analyze the association of patient-centered health promotion behavior and to examine the implications of the results for IoT and mobile health mobile app features. Methods: The study used data from the electronic health database (n=3128). An experimental design (n=121) and randomized controlled trials were employed to determine patient preferences in the health promotion program (n=62) and mobile self-management education (n=28). The transtheoretical model was used as a framework for observing self-management behavior for the improvement of individual health, and the theory of planned behavior was used to evaluate personal goals, execution, outcome, and personal preferences. A mobile app was used to determine individualized health promotion interventions and to apply these interventions to improve patients’ self-management and self-efficacy. Results: Mobile questionnaires were administered for pre- and postintervention assessment through mobile app. A dynamic questionnaire allocation method was used to follow up and monitor patient behavioral changes in the subsequent 6 to 18 months. Participants at a high risk of problems related to blood pressure (systolic blood pressure ≥120 mm Hg) and body mass index (≥23 kg/m2) indicated high motivation to change and to achieve high scores in the self-care knowledge assessment (n=49, 95% CI −0.26% to −0.24%, P=.052). The associated clinical outcomes in the case group with the mobile-based intervention were slightly better than in the control group (glycated hemoglobin mean −1.25%, 95% CI 6.36 to 7.47, P=.002). In addition, 86% (42/49) of the participants improved their health knowledge through the mobile-based app and information and communications technology. The behavior-change compliance rate was higher among the women than among the men. In addition, the personal characteristics of steadiness and dominance corresponded with a higher compliance rate in the dietary and wellness intervention (83%, 81/98). Most participants (71%, 70/98) also increased their attention to healthy eating, being active, and monitoring their condition (30% 21/70, 21% 15/70, and 20% 14/70, respectively). Conclusions: The overall compliance rate was discovered to be higher after the mobile app–based health intervention. Various intervention strategies based on patient characteristics, health care–related word-of-mouth communication, and social media may be used to increase self-efficacy and improve clinical outcomes. Additional research should be conducted to determine the most influential factors and the most effective adherence management techniques. %M 31094324 %R 10.2196/11017 %U http://diabetes.jmir.org/2019/2/e11017/ %U https://doi.org/10.2196/11017 %U http://www.ncbi.nlm.nih.gov/pubmed/31094324 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 2 %P e11462 %T Influence of Patient Characteristics and Psychological Needs on Diabetes Mobile App Usability in Adults With Type 1 or Type 2 Diabetes: Crossover Randomized Trial %A Fu,Helen NC %A Adam,Terrence J %A Konstan,Joseph A %A Wolfson,Julian A %A Clancy,Thomas R %A Wyman,Jean F %+ Center for Aging Science and Care Innovation, School of Nursing, University of Minnesota, 308 Harvard Street SE, Minneapolis, MN, 55455, United States, 1 612 624 2132, helen007@umn.edu %K mHealth %K diabetes %K self-management %K usability %K Self-Determination Theory %K mobile apps %K user satisfaction %D 2019 %7 30.04.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: More than 1100 diabetes mobile apps are available, but app usage by patients is low. App usability may be influenced by patient factors such as age, sex, and psychological needs. Objective: Guided by Self-Determination Theory, the purposes of this study were to (1) assess the effect of patient characteristics on app usability, and (2) determine whether patient characteristics and psychological needs (competence, autonomy, and connectivity)—important for motivation in diabetes care—are associated with app usability. Methods: Using a crossover randomized design, 92 adults with type 1 or 2 diabetes tested two Android apps (mySugr and OnTrack) for seven tasks including data entry, blood glucose (BG) reporting, and data sharing. We used multivariable linear regression models to examine associations between patient characteristics, psychological needs, user satisfaction, and user performance (task time, success, and accuracy). Results: Participants had a mean age of 54 (range 19-74) years, and were predominantly white (62%, 57/92), female (59%, 54/92), with type 2 diabetes (70%, 64/92), and had education beyond high school (67%, 61/92). Participants rated an overall user satisfaction score of 62 (SD 18), which is considered marginally acceptable. The satisfaction mean score for each app was 55 (SD 18) for mySugr and 68 (SD 15) for OnTrack. The mean task completion time for all seven tasks was 7 minutes, with a mean task success of 82% and an accuracy rate of 68%. Higher user satisfaction was observed for patients with less education (P=.04) and those reporting more competence (P=.02), autonomy (P=.006), or connectivity with a health care provider (P=.03). User performance was associated with age, sex, education, diabetes duration, and autonomy. Older patients required more time (95% CI 1.1-3.2) and had less successful task completion (95% CI 3.5-14.3%). Men needed more time (P=.01) and more technical support than women (P=.04). High school education or less was associated with lower task success (P=.003). Diabetes duration of ≥10 years was associated with lower task accuracy (P=.02). Patients who desired greater autonomy and were interested in learning their patterns of BG and carbohydrates had greater task success (P=.049). Conclusions: Diabetes app usability was associated with psychological needs that are important for motivation. To enhance patient motivation to use diabetes apps for self-management, clinicians should address competence, autonomy, and connectivity by teaching BG pattern recognition and lifestyle planning, customizing BG targets, and reviewing home-monitored data via email. App usability could be improved for older male users and those with less education and greater diabetes duration by tailoring app training and providing ongoing technical support. %M 31038468 %R 10.2196/11462 %U https://diabetes.jmir.org/2019/2/e11462/ %U https://doi.org/10.2196/11462 %U http://www.ncbi.nlm.nih.gov/pubmed/31038468 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 4 %P e11959 %T A Noninvasive, Economical, and Instant-Result Method to Diagnose and Monitor Type 2 Diabetes Using Pulse Wave: Case-Control Study %A Hao,Yiming %A Cheng,Feng %A Pham,Minh %A Rein,Hayley %A Patel,Devashru %A Fang,Yuchen %A Feng,Yiyi %A Yan,Jin %A Song,Xueyang %A Yan,Haixia %A Wang,Yiqin %+ Shanghai Key Laboratory of Health Identification and Assessment/Laboratory of Traditional Chinese Medicine Four Diagnostic Information, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai,, China, 86 21 51322447, wangyiqin2380@sina.com %K type 2 diabetes %K hypertension %K hyperlipidemia %K pulse wave analysis %K diagnosis %D 2019 %7 23.04.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: We should pay more attention to the long-term monitoring and early warning of type 2 diabetes and its complications. The traditional blood glucose tests are traumatic and cannot effectively monitor the development of diabetic complications. The development of mobile health is changing rapidly. Therefore, we are interested in developing a new noninvasive, economical, and instant-result method to accurately diagnose and monitor type 2 diabetes and its complications. Objective: We aimed to determine whether type 2 diabetes and its complications, including hypertension and hyperlipidemia, could be diagnosed and monitored by using pulse wave. Methods: We collected the pulse wave parameters from 50 healthy people, 139 diabetic patients without hypertension and hyperlipidemia, 133 diabetic patients with hypertension, 70 diabetic patients with hyperlipidemia, and 75 diabetic patients with hypertension and hyperlipidemia. The pulse wave parameters showing significant differences among these groups were identified. Various machine learning models such as linear discriminant analysis, support vector machines (SVMs), and random forests were applied to classify the control group, diabetic patients, and diabetic patients with complications. Results: There were significant differences in several pulse wave parameters among the 5 groups. The parameters height of tidal wave (h3), time distance between the start point of pulse wave and dominant wave (t1), and width of percussion wave in its one-third height position (W) increase and the height of dicrotic wave (h5) decreases when people develop diabetes. The parameters height of dominant wave (h1), h3, and height of dicrotic notch (h4) are found to be higher in diabetic patients with hypertension, whereas h5 is lower in diabetic patients with hyperlipidemia. For detecting diabetes, the method with the highest out-of-sample prediction accuracy is SVM with polynomial kernel. The algorithm can detect diabetes with 96.35% accuracy. However, all the algorithms have a low accuracy when predicting diabetic patients with hypertension and hyperlipidemia (below 70%). Conclusions: The results demonstrated that the noninvasive and convenient pulse-taking diagnosis described in this paper has the potential to become a low-cost and accurate method to monitor the development of diabetes. We are collecting more data to improve the accuracy for detecting hypertension and hyperlipidemia among diabetic patients. Mobile devices such as sport bands, smart watches, and other diagnostic tools are being developed based on the pulse wave method to improve the diagnosis and monitoring of diabetes, hypertension, and hyperlipidemia. %M 31012863 %R 10.2196/11959 %U http://mhealth.jmir.org/2019/4/e11959/ %U https://doi.org/10.2196/11959 %U http://www.ncbi.nlm.nih.gov/pubmed/31012863 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 4 %P e11879 %T Assessing the Need for Mobile Health (mHealth) in Monitoring the Diabetic Lower Extremity %A Wallace,David %A Perry,Julie %A Yu,Janelle %A Mehta,Joshua %A Hunter,Paul %A Cross,Karen Michelle %+ Division of Plastic Surgery, St. Michael's Hospital, 30 Bond Street, Toronto, ON, M5B 1W8, Canada, 1 416 864 6060 ext 77074, karen@drkarencross.ca %K mHealth %K diabetes %K diabetic foot ulcers %D 2019 %7 16.04.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Complications of the diabetic lower extremity (such as diabetic foot ulcers, DFUs) occur when monitoring is infrequent, and often result in serious sequelae like amputation or even death. Objective: To evaluate the potential application of mobile health (mHealth) to diabetic foot monitoring. We surveyed the self-management routines of a group of diabetic patients, as well as patient and clinician opinions on the use of mHealth in this context. Methods: Patients with DFUs in Toronto, Ontario, Canada completed a 25-item questionnaire addressing their foot care practices, mobile phone use, and views on mHealth. Wound care clinicians across Canada were also surveyed using a 9-item questionnaire. Results: Of the patients surveyed, 59/115 (51.3%) spend less than a minute checking their feet, and 17/115 (15%) of patients find it difficult to see their doctor or get to the hospital regularly. Mobile phone use was widespread in our patient cohort (93/115, 80.9%). Of mobile phone users, 68/93 (73.1%) would use a device on their mobile phone to help them check their feet. Of the clinicians who completed the questionnaire, only 7/202 (3.5%) were familiar with mHealth; however, 181/202 (92%) of clinicians expressed interest in using mHealth to monitor their patients between visits. Conclusions: Patient education or motivation and clinician training were identified as the major barriers to mHealth use in the diabetic lower extremity, which may be a viable mechanism to improve DFU monitoring practices. %M 30990455 %R 10.2196/11879 %U https://mhealth.jmir.org/2019/4/e11879/ %U https://doi.org/10.2196/11879 %U http://www.ncbi.nlm.nih.gov/pubmed/30990455 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 4 %P e12541 %T Addressing Diabetes and Poorly Controlled Hypertension: Pragmatic mHealth Self-Management Intervention %A Lewinski,Allison A %A Patel,Uptal D %A Diamantidis,Clarissa J %A Oakes,Megan %A Baloch,Khaula %A Crowley,Matthew J %A Wilson,Jonathan %A Pendergast,Jane %A Biola,Holly %A Boulware,L Ebony %A Bosworth,Hayden B %+ Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Attn: HSR&D COIN (558/152), 508 Fulton St, Durham, NC,, United States, 1 919 286 0411 ext 7101, hayden.bosworth@duke.edu %K telemedicine %K cardiovascular diseases %K diabetes mellitus type 2 %K vulnerable populations %K renal insufficiency %K professional-patient relations %K hypertension %D 2019 %7 09.04.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients with diabetes and poorly controlled hypertension are at increased risk for adverse renal and cardiovascular outcomes. Identifying these patients early and addressing modifiable risk factors is central to delaying renal complications such as diabetic kidney disease. Mobile health (mHealth), a relatively inexpensive and easily scalable technology, can facilitate patient-centered care and promote engagement in self-management, particularly for patients of lower socioeconomic status. Thus, mHealth may be a cost-effective way to deliver self-management education and support. Objective: This feasibility study aimed to build a population management program by identifying patients with diabetes and poorly controlled hypertension who were at risk for adverse renal outcomes and evaluate a multifactorial intervention to address medication self-management. We recruited patients from a federally qualified health center (FQHC) in an underserved, diverse county in the southeastern United States. Methods: Patients were identified via electronic health record. Inclusion criteria were age between 18 and 75 years, diagnosis of type 2 diabetes, poorly controlled hypertension over the last 12 months (mean clinic systolic blood pressure [SBP] ≥140 mm Hg and/or diastolic blood pressure [DBP] ≥90 mm Hg), access to a mobile phone, and ability to receive text messages and emails. The intervention consisted of monthly telephone calls for 6 months by a case manager and weekly, one-way informational text messages. Engagement was defined as the number of phone calls completed during the intervention; individuals who completed 4 or more calls were considered engaged. The primary outcome was change in SBP at the conclusion of the intervention. Results: Of the 141 patients enrolled, 84.0% (118/141) of patients completed 1 or more phone calls and had follow-up SBP measurements for analysis. These patients were on average 56.9 years of age, predominately female (73/118, 61.9%), and nonwhite by self-report (103/118, 87.3%). The proportion of participants with poor baseline SBP control (50/118, 42.4%) did not change significantly at study completion (53/118, 44.9%) (P=.64). Participants who completed 4 or more phone calls (98/118, 83.1%) did not experience a statistically significant decrease in SBP when compared to those who completed fewer calls. Conclusion: We did not reduce uncontrolled hypertension even among the more highly engaged. However, 83% of a predominately minority and low-income population completed at least 67% of the multimodal mHealth intervention. Findings suggest that combining an automated electronic health record system to identify at-risk patients with a tailored mHealth protocol can provide education to this population. While this intervention was insufficient to effect behavioral change resulting in better hypertension control, it does suggest that this FQHC population will engage in low-cost population health applications with a potentially promising impact. Trial Registration: ClinicalTrials.gov NCT02418091; https://clinicaltrials.gov/ct2/show/NCT02418091 (Archived by WebCite at http://www.webcitation.org/76RBvacVU) %M 30964439 %R 10.2196/12541 %U https://www.jmir.org/2019/4/e12541/ %U https://doi.org/10.2196/12541 %U http://www.ncbi.nlm.nih.gov/pubmed/30964439 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 1 %P e10271 %T Appropriation of Mobile Health for Diabetes Self-Management: Lessons From Two Qualitative Studies %A Rossmann,Constanze %A Riesmeyer,Claudia %A Brew-Sam,Nicola %A Karnowski,Veronika %A Joeckel,Sven %A Chib,Arul %A Ling,Rich %+ Department of Media and Communication Science, University of Erfurt, Nordhaeuser Str 63, Erfurt, 99089, Germany, 49 3617374171, constanze.rossmann@uni-erfurt.de %K diabetes %K Germany %K mHealth %K mobile phone %K self-management %K Singapore %D 2019 %7 29.03.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: To achieve clarity on mobile health’s (mHealth’s) potential in the diabetes context, it is necessary to understand potential users’ needs and expectations, as well as the factors determining their mHealth use. Recently, a few studies have examined the user perspective in the mHealth context, but their explanatory value is constrained because of their limitation to adoption factors. Objective: This paper uses the mobile phone appropriation model to examine how individuals with type 1 or type 2 diabetes integrate mobile technology into their everyday self-management. The study advances the field beyond mere usage metrics or the simple dichotomy of adoption versus rejection. Methods: Data were gathered in 2 qualitative studies in Singapore and Germany, with 21 and 16 respondents, respectively. Conducting semistructured interviews, we asked respondents about their explicit use of diabetes-related apps, their general use of varied mobile technologies to manage their disease, and their daily practices of self-management. Results: The analysis revealed that although some individuals with diabetes used dedicated diabetes apps, most used tools across the entire mobile-media spectrum, including lifestyle and messaging apps, traditional health information websites and forums. The material indicated general barriers to usage, including financial, technical, and temporal restrictions. Conclusions: In sum, we find that use patterns differ regarding users’ evaluations, expectancies, and appropriation styles, which might explain the inconclusive picture of effects studies in the diabetes mHealth context. %M 30924786 %R 10.2196/10271 %U http://diabetes.jmir.org/2019/1/e10271/ %U https://doi.org/10.2196/10271 %U http://www.ncbi.nlm.nih.gov/pubmed/30924786 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 3 %P e12179 %T Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey %A Ernsting,Clemens %A Stühmann,Lena Mareike %A Dombrowski,Stephan U %A Voigt-Antons,Jan-Niklas %A Kuhlmey,Adelheid %A Gellert,Paul %+ Charité - Universitätsmedizin Berlin, Institute of Medical Sociology, Charitéplatz 1, Berlin,, Germany, 49 30450529215, paul.gellert@charite.de %K mHealth %K eHealth %K smartphone %K telemedicine %K health literacy %K chronic disease %K comorbidity %K multimorbidity %D 2019 %7 28.03.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health apps can help to change health-related behaviors and manage chronic conditions in patients with cardiovascular diseases (CVDs) and diabetes mellitus, but a certain level of health literacy and electronic health (eHealth) literacy may be needed. Objective: The aim of this study was to identify factors associated with mobile health app use in individuals with CVD or diabetes and detect relations with the perceived effectiveness of health apps among app users. Methods: The study used population-based Web-based survey (N=1500) among Germans, aged 35 years and older, with CVD, diabetes, or both. A total of 3 subgroups were examined: (1) Individuals with CVD (n=1325), (2) Individuals with diabetes (n=681), and (3) Individuals with CVD and diabetes (n=524). Sociodemographics, health behaviors, CVD, diabetes, health and eHealth literacy, characteristics of health app use, and characteristics of apps themselves were assessed by questionnaires. Linear and logistic regression models were applied. Results: Overall, patterns of factors associated with health app use were comparable in individuals with CVD or diabetes or both. Across subgroups, about every fourth patient reported using apps for health-related purposes, with physical activity and weight loss being the most prominent target behaviors. Health app users were younger, more likely to be female (except in those with CVD and diabetes combined), better educated, and reported more physical activity. App users had higher eHealth literacy than nonusers. Those users who perceived the app to have a greater effectiveness on their health behaviors tended to be more health and eHealth literate and rated the app to use more behavior change techniques (BCTs). Conclusions: There are health- and literacy-related disparities in the access to health app use among patients with CVD, diabetes, or both, which are relevant to specific health care professionals such as endocrinologists, dieticians, cardiologists, or general practitioners. Apps containing more BCTs had a higher perceived effect on people’s health, and app developers should take the complexity of needs into account. Furthermore, eHealth literacy appears to be a requirement to use health apps successfully, which should be considered in health education strategies to improve health in patients with CVD and diabetes. %M 30920383 %R 10.2196/12179 %U http://mhealth.jmir.org/2019/3/e12179/ %U https://doi.org/10.2196/12179 %U http://www.ncbi.nlm.nih.gov/pubmed/30920383 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 8 %N 3 %P e12413 %T A Self-Regulation–Based eHealth and mHealth Intervention for an Active Lifestyle in Adults With Type 2 Diabetes: Protocol for a Randomized Controlled Trial %A Poppe,Louise %A De Bourdeaudhuij,Ilse %A Verloigne,Maïté %A Degroote,Laurent %A Shadid,Samyah %A Crombez,Geert %+ Physical Activity and Health Research Group, Department of Movement and Sports Sciences, Ghent University, Watersportlaan 2, Ghent, 9000, Belgium, 32 9 264 63 63, louise.poppe@ugent.be %K protocol %K randomized controlled trial %K eHealth %K mHealth %K type 2 diabetes %K self-regulation %K physical activity %K sedentary behaviour %K mobile phone %D 2019 %7 22.03.2019 %9 Protocol %J JMIR Res Protoc %G English %X Background: Adoption of an active lifestyle plays an important role in the management of type 2 diabetes. Online interventions targeting lifestyle changes in adults with type 2 diabetes have provided mixed results. Previous research highlights the importance of creating theory-based interventions adapted to the population’s specific needs. The online intervention “MyPlan 2.0” targets physical activity and sedentary behavior in adults with type 2 diabetes. This intervention is grounded in the self-regulation framework and, by incorporating the feedback of users with type 2 diabetes, iteratively adapted to its target population. Objective: The aim of this paper is to thoroughly describe “MyPlan 2.0” and the study protocol that will be used to test the effectiveness of this intervention to alter patients’ levels of physical activity and sedentary behavior. Methods: A two-arm superiority randomized controlled trial will be performed. Physical activity and sedentary behavior will be measured using accelerometers and questionnaires. Furthermore, using questionnaires and diaries, patients’ stressors and personal determinants for change will be explored in depth. To evaluate the primary outcomes of the intervention, multilevel analyses will be conducted. Results: The randomized controlled trial started in January 2018. As participants can start at different moments, we aim to finish all testing by July 2019. Conclusions: This study will increase our understanding about whether and how a theory-based online intervention can help adults with type 2 diabetes increase their level of physical activity and decrease their sedentary time. International Registered Report Identifier (IRRID): DERR1-10.2196/12413 %M 30901002 %R 10.2196/12413 %U http://www.researchprotocols.org/2019/3/e12413/ %U https://doi.org/10.2196/12413 %U http://www.ncbi.nlm.nih.gov/pubmed/30901002 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 4 %N 1 %P e10350 %T Perceptions and Acceptability of Text Messaging for Diabetes Care in Primary Care in Argentina: Exploratory Study %A Moyano,Daniela %A Morelli,Daniela %A Santero,Marilina %A Belizan,Maria %A Irazola,Vilma %A Beratarrechea,Andrea %+ Institute for Clinical Effectiveness and Health Policy (IECS), Dr Emilio Ravignani 2024, Buenos Aires, C1414CPV, Argentina, 54 114777 8767, dmoyano@iecs.org.ar %K mobile phones %K short message service %K diabetes mellitus %K public health %K qualitative research %D 2019 %7 18.03.2019 %9 Original Paper %J JMIR Diabetes %G English %X Background: Engagement in self-care behaviors that are essential to optimize diabetes care is challenging for many patients with diabetes. mHealth interventions have been shown to be effective in improving health care outcomes in diabetes. However, more research is needed on patient perceptions to support these interventions, especially in resource settings in low- and middle-income countries. Objective: The goal of the research was to explore perceptions and acceptability of a short message service (SMS) text messaging intervention for diabetes care in underserved people with diabetes in Argentina. Methods: A qualitative exploratory methodology was adopted as part of the evaluation of a program to strengthen diabetes services in primary care clinics located in low-resource settings. The diabetes program included a text messaging intervention for people with diabetes. A total of 24 semistructured telephone interviews were conducted with people with diabetes. Results: Twenty-four middle-aged persons with diabetes were interviewed. Acceptability was considered adequate in terms of its actual use, frequency, and the role of texts as a reminder. We found that text messages could be a mediating device in the patient’s learning processes. Also, being exposed to the texts seemed to help bring about changes in risk perception and care practices and to function as psychosocial support. Another relevant finding was the role of text messaging as a potential facilitator in diabetes care. In this sense, we observed a strong association between receiving text messages and having a better patient-physician relationship. Additionally, social barriers that affect diabetes care such as socioeconomic and psychosocial vulnerability were identified. Conclusions: Our findings show positive contributions of a text messaging intervention for the care of people with diabetes. We consider that an SMS strategy has potential to be replicated in other contexts. However, further studies are needed to explore its sustainability and long-term impact from the perspective of patients. %M 30882362 %R 10.2196/10350 %U http://diabetes.jmir.org/2019/1/e10350/ %U https://doi.org/10.2196/10350 %U http://www.ncbi.nlm.nih.gov/pubmed/30882362 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 3 %P e11933 %T Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study %A Vehi,Josep %A Regincós Isern,Jordi %A Parcerisas,Adrià %A Calm,Remei %A Contreras,Ivan %+ Institut d'Informatica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, Girona, 17003, Spain, 34 620131826, josep.vehi@gmail.com %K diabetes mellitus %K mHealth %K self-management %K blood glucose self-monitoring %K evaluation studies %D 2019 %7 07.03.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Technology has long been used to carry out self-management as well as to improve adherence to treatment in people with diabetes. However, most technology-based apps do not meet the basic requirements for engaging patients. Objective: This study aimed to evaluate the effect of use frequency of a diabetes management app on glycemic control. Methods: Overall, 2 analyses were performed. The first consisted of an examination of the reduction of blood glucose (BG) mean, using a randomly selected group of 211 users of the SocialDiabetes app (SDA). BG levels at baseline, month 3, and month 6 were calculated using the intercept of a regression model based on data from months 1, 4, and 7, respectively. In the second analysis, the impact of low and high BG risk was examined. A total of 2692 users logging SDA ≥5 days/month for ≥6 months were analyzed. The highest quartile regarding low blood glucose index (LBGI) and high blood glucose index (HBGI) at baseline (t1) was selected (n=74 for group A; n=440 for group B). Changes in HBGI and LBGI at month 6 (t2) were analyzed. Results: For analysis 1, baseline BG results for type 1 diabetes mellitus (T1DM) groups A and B were 213.61 (SD 31.57) mg/dL and 206.43 (SD 18.65) mg/dL, respectively, which decreased at month 6 to 175.15 (SD 37.88) mg/dL and 180.6 (SD 40.47) mg/dL, respectively. For type 2 diabetes mellitus (T2DM), baseline BG was 218.77 (SD 40.18) mg/dL and 232.55 (SD 46.78) mg/dL, respectively, which decreased at month 6 to 160.51 (SD 39.32) mg/dL and 173.14 (SD 52.81) mg/dL for groups A and B, respectively. This represents a reduction of estimated A1c (eA1c) of approximately 1.3% (P<.001) and 0.9% (P=.001) for T1DM groups A and B, respectively, and 2% (P<.001) for both A and B T2DM groups, respectively. For analysis 2, T1DM baseline LBGI values for groups A and B were 5.2 (SD 3.9) and 4.4 (SD 2.3), respectively, which decreased at t2 to 3.4 (SD 3.3) and 3.4 (SD 1.9), respectively; this was a reduction of 34.6% (P=.005) and 22.7% (P=.02), respectively. Baseline HBGI values for groups A and B were 12.6 (SD 4.3) and 10.6 (SD 4.03), respectively, which decreased at t2 to 9.0 (SD 6.5) and 8.6 (SD 4.7), respectively; this was a reduction of 30% (P=.001) and 22% (P=.003), respectively. Conclusions: A significant reduction in BG was found in all groups, independent of the use frequency of the app. Better outcomes were found for T2DM patients. A significant reduction in LBGI and HBGI was found in all groups, regardless of the use frequency of the app. LBGI and HBGI indices of both groups tend to have similar values after 6 months of app use. %M 30843865 %R 10.2196/11933 %U http://mhealth.jmir.org/2019/3/e11933/ %U https://doi.org/10.2196/11933 %U http://www.ncbi.nlm.nih.gov/pubmed/30843865 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 2 %P e12658 %T Use, Perspectives, and Attitudes Regarding Diabetes Management Mobile Apps Among Diabetes Patients and Diabetologists in China: National Web-Based Survey %A Zhang,Yiyu %A Li,Xia %A Luo,Shuoming %A Liu,Chaoyuan %A Xie,Yuting %A Guo,Jia %A Liu,Fang %A Zhou,Zhiguang %+ Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No 139, Renmin Road, Changsha, 410011, China, 86 073185292154, zhouzhiguang@csu.edu.cn %K diabetes mellitus %K mobile applications %K surveys and questionnaires %D 2019 %7 08.02.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The diabetes disease burden in China is heavy, and mobile apps have a great potential for diabetes management. However, there is a lack of investigation of diabetes app use among Chinese diabetes patients and diabetologists. The perspectives and attitudes of diabetes patients and diabetologists regarding diabetes apps are also unclear. Objective: Our objectives were to investigate diabetes patients’ and diabetologists’ use, attitudes, and perspectives, as well as patients’ needs, with respect to diabetes apps to provide information regarding the optimal design of diabetes apps and the best strategies to promote their use. Methods: Diabetes patients and diabetologists across China were surveyed on the WeChat (Tencent Corp) network using Sojump (Changsha ran Xing InfoTech Ltd) from January 23, 2018, to July 30, 2018. In total, 2 survey links were initially sent to doctors from 46 Latent Autoimmune Diabetes of Adults Study collaborative hospitals in China in 25 major cities and were spread on their WeChat contacts network. We also published the patient survey link on 3 WeChat public accounts and requested diabetes patients to fill out questionnaires. A multivariate regression analysis was used to identify associations of demographic and basic disease information with app usage among adult patients. Results: Overall, 1276 individuals from 30 provincial regions responded to the patient survey; among them, the overall app awareness rate was 29.94% (382/1276) and usage was 15.44% (197/1276). The usage was higher among patients with type 1 diabetes (T1DM) than among patients with type 2 diabetes (T2DM; 108/473, 22.8% vs 79/733, 10.8%; P<.001). The multivariate regression analysis showed that diabetes type, age, education, family income, and location were associated with app use in adult patients (P<.05). The need for and selection of diabetes apps differed slightly between patients with T1DM and patients with T2DM. The reasons why patients discontinued the use of an app included limited time (59/197, 29.9%), complicated operations (50/197, 25.4%), ineffectiveness for glycemic control (48/197, 24.4%), and cost (38/197, 19.3%). Of the 608 responders to the diabetologist survey, 40.5% (246/608) recommended diabetes apps to patients and 25.2% (153/608) used diabetes apps to manage patients. The greatest obstacles to the diabetologists’ use of apps to manage diabetes patients include limited time (280/608, 46.1%), legal issues (129/608, 21.2%), patients’ distrust (108/608, 17.8%), and billing issues (66/608, 10.9%). Conclusions: The awareness and use of diabetes apps in Chinese people with diabetes and the proportion of diabetologists using diabetes apps to manage patients are low. Designing apps targeting different patient needs and conducting high-quality randomized controlled trials will improve the effectiveness of the apps, provide evidence for patients to choose suitable apps, and be conducive to the promotion of app use. %M 30735147 %R 10.2196/12658 %U http://mhealth.jmir.org/2019/2/e12658/ %U https://doi.org/10.2196/12658 %U http://www.ncbi.nlm.nih.gov/pubmed/30735147 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e11041 %T Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study %A Sarda,Archana %A Munuswamy,Suresh %A Sarda,Shubhankar %A Subramanian,Vinod %+ Touchkin eServices Private Limited, 1st Floor, Manjusha, No 532, 16th Cross, 2nd Main Road, 2nd Stage, Indira Nagar, Bangalore, 560038, India, 91 9762665119, shubhankar@touchkin.com %K depression %K diabetes %K mental health %K comorbidity %K passive sensing %K smartphone %K classification %K machine learning %K mHealth %K risk assessment %D 2019 %7 29.01.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Research studies are establishing the use of smartphone sensing to measure mental well-being. Smartphone sensor information captures behavioral patterns, and its analysis helps reveal well-being changes. Depression in diabetes goes highly underdiagnosed and underreported. The comorbidity has been associated with increased mortality and worse clinical outcomes, including poor glycemic control and self-management. Clinical-only intervention has been found to have a very modest effect on diabetes management among people with depression. Smartphone technologies could play a significant role in complementing comorbid care. Objective: This study aimed to analyze the association between smartphone-sensing parameters and symptoms of depression and to explore an approach to risk-stratify people with diabetes. Methods: A cross-sectional observational study (Project SHADO—Analyzing Social and Health Attributes through Daily Digital Observation) was conducted on 47 participants with diabetes. The study’s smartphone-sensing app passively collected data regarding activity, mobility, sleep, and communication from each participant. Self-reported symptoms of depression using a validated Patient Health Questionnaire-9 (PHQ-9) were collected once every 2 weeks from all participants. A descriptive analysis was performed to understand the representation of the participants. A univariate analysis was performed on each derived sensing variable to compare behavioral changes between depression states—those with self-reported major depression (PHQ-9>9) and those with none (PHQ-9≤9). A classification predictive modeling, using supervised machine-learning methods, was explored using derived sensing variables as input to construct and compare classifiers that could risk-stratify people with diabetes based on symptoms of depression. Results: A noticeably high prevalence of self-reported depression (30 out of 47 participants, 63%) was found among the participants. Between depression states, a significant difference was found for average activity rates (daytime) between participant-day instances with symptoms of major depression (mean 16.06 [SD 14.90]) and those with none (mean 18.79 [SD 16.72]), P=.005. For average number of people called (calls made and received), a significant difference was found between participant-day instances with symptoms of major depression (mean 5.08 [SD 3.83]) and those with none (mean 8.59 [SD 7.05]), P<.001. These results suggest that participants with diabetes and symptoms of major depression exhibited lower activity through the day and maintained contact with fewer people. Using all the derived sensing variables, the extreme gradient boosting machine-learning classifier provided the best performance with an average cross-validation accuracy of 79.07% (95% CI 74%-84%) and test accuracy of 81.05% to classify symptoms of depression. Conclusions: Participants with diabetes and self-reported symptoms of major depression were observed to show lower levels of social contact and lower activity levels during the day. Although findings must be reproduced in a broader randomized controlled study, this study shows promise in the use of predictive modeling for early detection of symptoms of depression in people with diabetes using smartphone-sensing information. %M 30694197 %R 10.2196/11041 %U http://mhealth.jmir.org/2019/1/e11041/ %U https://doi.org/10.2196/11041 %U http://www.ncbi.nlm.nih.gov/pubmed/30694197 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e11885 %T Factors for Supporting Primary Care Physician Engagement With Patient Apps for Type 2 Diabetes Self-Management That Link to Primary Care: Interview Study %A Ayre,Julie %A Bonner,Carissa %A Bramwell,Sian %A McClelland,Sharon %A Jayaballa,Rajini %A Maberly,Glen %A McCaffery,Kirsten %+ Sydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Edward Ford Building (A27), The University of Sydney, Sydney,, Australia, 61 293517220, kirsten.mccaffery@sydney.edu.au %K diabetes mellitus, type 2 %K electronic health records %K telemedicine %K mobile apps %K general practitioners %K physicians, primary care %K self-management %K qualitative research %K translational medical research %D 2019 %7 16.01.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The health burden of type 2 diabetes can be mitigated by engaging patients in two key aspects of diabetes care: self-management and regular contact with health professionals. There is a clear benefit to integrating these aspects of care into a single clinical tool, and as mobile phone ownership increases, apps become a more feasible platform. However, the effectiveness of online health interventions is contingent on uptake by health care providers, which is typically low. There has been little research that focuses specifically on barriers and facilitators to health care provider uptake for interventions that link self-management apps to the user’s primary care physician (PCP). Objective: This study aimed to explore PCP perspectives on proposed features for a self-management app for patients with diabetes that would link to primary care services. Methods: Researchers conducted 25 semistructured interviews. The interviewer discussed potential features that would link in with the patient’s primary care services. Interviews were audio-recorded, transcribed, and coded. Framework analysis and the Consolidated Criteria for Reporting Qualitative Research checklist were employed to ensure rigor. Results: Our analysis indicated that PCP attitudes toward proposed features for an app were underpinned by perceived roles of (1) diabetes self-management, (2) face-to-face care, and (3) the anticipated burden of new technologies on their practice. Theme 1 explored PCP perceptions about how an app could foster patient independence for self-management behaviors but could also increase responsibility and liability for the PCP. Theme 2 identified beliefs underpinning a commonly expressed preference for face-to-face care. PCPs perceived information was more motivating, better understood, and presented with greater empathy when delivered face to face rather than online. Theme 3 described how most PCPs anticipated an initial increase in workload while they learned to use a new clinical tool. Some PCPs accepted this burden on the basis that the change was inevitable as health care became more integrated. Others reported potential benefits were outweighed by effort to implement an app. This study also identified how app features can be positively framed, highlighting potential benefits for PCPs to maximize PCP engagement, buy-in, and uptake. For example, PCPs were more positive when they perceived that an app could facilitate communication and motivation between consultations, focus on building capacity for patient independence, and reinforce rather than replace in-person care. They were also more positive about app features that were automated, integrated with existing software, flexible for different patients, and included secondary benefits such as improved documentation. Conclusions: This study provided insight into PCP perspectives on a diabetes app integrated with primary care services. This was observed as more than a technological change; PCPs were concerned about changes in workload, their role in self-management, and the nature of consultations. Our research highlighted potential facilitators and barriers to engaging PCPs in the implementation process. %M 30664468 %R 10.2196/11885 %U http://mhealth.jmir.org/2019/1/e11885/ %U https://doi.org/10.2196/11885 %U http://www.ncbi.nlm.nih.gov/pubmed/30664468 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e11848 %T Examining Diabetes Management Apps Recommended From a Google Search: Content Analysis %A Jimenez,Geronimo %A Lum,Elaine %A Car,Josip %+ Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Level 18, Clinical Sciences Building, LKC Medicine, Singapore, 308232, Singapore, 65 69047027, geronimo.jimenez@ntu.edu.sg %K chronic diseases %K diabetes %K Google %K health apps %K mobile phone %D 2019 %7 16.1.2019 %9 Viewpoint %J JMIR Mhealth Uhealth %G English %X Background: The availability of smartphone health apps empowers people to manage their own health. Currently, there are over 300,000 health apps available in the market targeting a variety of user needs from weight loss to management of chronic conditions, with diabetes being the most commonly targeted condition. To date, health apps largely fall outside government regulation, and there are no official guidelines to help clinicians and patients in app selection. Patients commonly resort to the internet for suggestions on which diabetes app to use. Objective: The objective of this study was to investigate apps identified through a Google search and characterize these apps in terms of features that support diabetes management. Methods: We performed a Google search for the “best diabetes apps 2017” and explored the first 4 search results. We identified and compiled a list of the apps recommended in the returned search results, which were Web articles. Information about each app was extracted from the papers and corresponding app store descriptions. We examined the apps for the following diabetes management features: medication management, blood glucose self-management, physical activity, diet and nutrition, and weight management. Results: Overall, 26 apps were recommended in 4 papers. One app was listed in all 4 papers, and 3 apps appeared on 3 of the 4 lists. Apart from one paper, there were no explicit criteria to justify or explain the selection of apps. We found a wide variation in the type and the number of diabetes management features in the recommended apps. Five apps required payment to be used. Two-thirds of the apps had blood glucose management features, and less than half had medication management features. The most prevalent app features were nutrition or diet-related (19/24, 79%) and physical activity tracking (14/24, 58%). Conclusions: The ambiguity of app selection and the wide variability in key features of the apps recommended for diabetes management may pose difficulties for patients when selecting the most appropriate app. It is critical to involve patients, clinicians, relevant professional bodies, and policy makers to define the key features an app should have for it to be classified as a “diabetes management” app. The lessons learned here may be extrapolated for the development and recommendation of apps for the management of other chronic conditions. %R 10.2196/11848 %U http://mhealth.jmir.org/2019/1/e11848/ %U https://doi.org/10.2196/11848 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e12297 %T The Efficacy of Mobile Phone Apps for Lifestyle Modification in Diabetes: Systematic Review and Meta-Analysis %A Wu,Xinghan %A Guo,Xitong %A Zhang,Zhiwei %+ eHealth Research Institute, School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, Harbin,, China, 86 451 86414022, xitongguo@gmail.com %K smartphone %K mobile applications %K diabetes mellitus %K lifestyle %K physical activity %K diet %K behavior therapy %D 2019 %7 15.01.2019 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Diabetes and related complications are estimated to cost US $727 billion worldwide annually. Type 1 diabetes, type 2 diabetes, and gestational diabetes are three subtypes of diabetes that share the same behavioral risk factors. Efforts in lifestyle modification, such as daily physical activity and healthy diets, can reduce the risk of prediabetes, improve the health levels of people with diabetes, and prevent complications. Lifestyle modification is commonly performed in a face-to-face interaction, which can prove costly. Mobile phone apps provide a more accessible platform for lifestyle modification in diabetes. Objective: This review aimed to summarize and synthesize the clinical evidence of the efficacy of mobile phone apps for lifestyle modification in different subtypes of diabetes. Methods: In June 2018, we conducted a literature search in 5 databases (Cochrane Central Register of Controlled Trials, MEDLINE, Embase, CINAHL, and PsycINFO). We evaluated the studies that passed screening using The Cochrane Collaboration’s risk of bias tool. We conducted a meta-analysis for each subtype on the mean difference (between intervention and control groups) at the posttreatment glycated hemoglobin (HbA1c) level. Where possible, we analyzed subgroups for short-term (3-6 months) and long-term (9-12 months) studies. Heterogeneity was assessed using the I2 statistic. Results: We identified total of 2669 articles through database searching. After the screening, we included 26 articles (23 studies) in the systematic review, of which 18 studies (5 type 1 diabetes, 11 type 2 diabetes, and 2 prediabetes studies) were eligible for meta-analysis. For type 1 diabetes, the overall effect on HbA1c was statistically insignificant (P=.46) with acceptable heterogeneity (I2=39%) in the short-term subgroup (4 studies) and significant heterogeneity between the short-term and long-term subgroups (I2=64%). Regarding type 2 diabetes, the overall effect on HbA1c was statistically significant (P<.01) in both subgroups, and when the 2 subgroups were combined, there was virtually no heterogeneity within and between the subgroups (I2 range 0%-2%). The effect remained statistically significant (P<.01) after adjusting for publication bias using the trim and fill method. For the prediabetes condition, the overall effect on HbA1c was statistically insignificant (P=.67) with a large heterogeneity (I2=65%) between the 2 studies. Conclusions: There is strong evidence for the efficacy of mobile phone apps for lifestyle modification in type 2 diabetes. The evidence is inconclusive for the other diabetes subtypes. %M 30664494 %R 10.2196/12297 %U http://mhealth.jmir.org/2019/1/e12297/ %U https://doi.org/10.2196/12297 %U http://www.ncbi.nlm.nih.gov/pubmed/30664494 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e10321 %T Mobile App for Improved Self-Management of Type 2 Diabetes: Multicenter Pragmatic Randomized Controlled Trial %A Agarwal,Payal %A Mukerji,Geetha %A Desveaux,Laura %A Ivers,Noah M %A Bhattacharyya,Onil %A Hensel,Jennifer M %A Shaw,James %A Bouck,Zachary %A Jamieson,Trevor %A Onabajo,Nike %A Cooper,Madeline %A Marani,Husayn %A Jeffs,Lianne %A Bhatia,R Sacha %+ Women’s College Hospital Institute for Health System Solutions and Virtual Care, Women’s College Hospital, 76 Grenville Street, Toronto, ON, M5S 1B2, Canada, 1 416 323 6400, payal.agarwal@wchospital.ca %K mobile apps %K diabetes mellitus, type 2 %K self-management %K blood glucose self-monitoring %K randomized controlled trial %K pragmatic clinical trial %D 2019 %7 10.01.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: As the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A1c (HbA1c) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear. Objective: The primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA1c levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA1c levels compared with controls. Methods: The study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA1c levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app. Results: The results of an analysis of covariance controlling for baseline HbA1c levels did not show evidence of intervention impact on HbA1c levels at 3 months (mean difference [ITG−WLC] −0.42, 95% CI −1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA1c levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants’ 3-month HbA1c levels (95% CI −0.03 to −0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51). Conclusions: The results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA1c levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed. Trial Registration: Clinicaltrials.gov NCT02813343; https://clinicaltrials.gov/ct2/show/NCT02813343 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02813343) %M 30632972 %R 10.2196/10321 %U https://mhealth.jmir.org/2019/1/e10321/ %U https://doi.org/10.2196/10321 %U http://www.ncbi.nlm.nih.gov/pubmed/30632972 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 1 %P e10421 %T Identifying Brief Message Content for Interventions Delivered via Mobile Devices to Improve Medication Adherence in People With Type 2 Diabetes Mellitus: A Rapid Systematic Review %A Long,Hannah %A Bartlett,Yvonne K %A Farmer,Andrew J %A French,David P %+ Manchester Centre for Health Psychology, School of Health Sciences, University of Manchester, Coupland 1 Building, Coupland Street, Manchester, M13 9PL, United Kingdom, 44 161 275 2605, david.french@manchester.ac.uk %K medication adherence %K diabetes mellitus %K systematic review %K text messaging %K mHealth %K self-management %D 2019 %7 09.01.2019 %9 Review %J J Med Internet Res %G English %X Background: Current interventions to support medication adherence in people with type 2 diabetes are generally resource-intensive and ineffective. Brief messages, such as those delivered via short message service (SMS) systems, are increasingly used in digital health interventions to support adherence because they can be delivered on a wide scale and at low cost. The content of SMS text messages is a crucial intervention feature for promoting behavior change, but it is often unclear what the rationale is for chosen wording or any underlying mechanisms targeted for behavioral change. There is little guidance for developing and optimizing brief message content for use in mobile device–delivered interventions. Objective: This review aimed to (1) identify theoretical constructs (ie, the targets that interventions aim to change) and behavioral strategies (ie, features of intervention content) found to be associated with medication adherence in patients with type 2 diabetes and (2) map these onto a standard taxonomy for behavior change techniques (BCTs, that is, active ingredients of interventions used to promote behavioral change, to produce an evidence-based set of approaches that have shown promise of improving adherence in previous studies and which could be further tested in digital health interventions. Methods: A rapid systematic review of existing relevant systematic reviews was conducted. MEDLINE and PsycINFO databases were searched from inception to April 10, 2017. Inclusion criteria were (1) systematic reviews of quantitative data if the studies reviewed identified predictors of or correlates with medication adherence or evaluated medication adherence–enhancing interventions and included adult participants taking medication to manage a chronic physical health condition, and (2) systematic reviews of qualitative studies of experiences of medication adherence for adult participants with type 2 diabetes. Data were extracted on review characteristics and BCTs, theoretical constructs, or behavioral strategies associated with improved adherence. Constructs and strategies were mapped onto the BCT version 1 taxonomy. Results: A total of 1701 references were identified; 25 systematic reviews (19 quantitative reviews, 3 qualitative reviews, and 3 mixed-method reviews) were included. Moreover, 20 theoretical constructs (eg, self-efficacy) and 19 behavioral strategies (eg, habit analysis) were identified in the included reviews. In total, 46 BCTs were identified as being related to medication adherence in type 2 diabetes (eg, habit formation, prompts or cues, and information about health consequences). Conclusions: We identified 46 promising BCTs related to medication adherence in type 2 diabetes on which the content of brief messages delivered through mobile devices to improve adherence could be based. By using explicit systematic review methods and linking our findings to a standardized taxonomy of BCTs, we have described a novel approach for the development of digital message content. Future brief message interventions that aim to support medication adherence could incorporate the identified BCTs. %M 30626562 %R 10.2196/10421 %U https://www.jmir.org/2019/1/e10421/ %U https://doi.org/10.2196/10421 %U http://www.ncbi.nlm.nih.gov/pubmed/30626562 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 7 %N 1 %P e10664 %T Mobile Phone–Based Telemedicine Practice in Older Chinese Patients with Type 2 Diabetes Mellitus: Randomized Controlled Trial %A Sun,Chenglin %A Sun,Lin %A Xi,Shugang %A Zhang,Hong %A Wang,Huan %A Feng,Yakun %A Deng,Yufeng %A Wang,Haimin %A Xiao,Xianchao %A Wang,Gang %A Gao,Yuan %A Wang,Guixia %+ Department of Endocrinology, First Hospital of Jilin University, 71 Xinmin Street, Changchun,, China, 86 0431 88783212, clsun213@163.com %K telemedicine %K type 2 diabetes %K health management %D 2019 %7 04.01.2019 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Previous studies on telemedicine interventions have shown that older diabetic patients experience difficulty in using computers, which is a barrier to remote communication between medical teams and older diabetic patients. However, older people in China tend to find it easy to use mobile phones and personal messaging apps that have a user-friendly interface. Therefore, we designed a mobile health (mHealth) system for older people with diabetes that is based on mobile phones, has a streamlined operation interface, and incorporates maximum automation. Objective: The goal of the research was to investigate the use of mobile phone–based telemedicine apps for management of older Chinese patients with type 2 diabetes mellitus (T2DM). Variables of interest included efficacy and safety. Methods: A total of 91 older (aged over 65 years) patients with T2DM who presented to our department were randomly assigned to one of two groups. Patients in the intervention group (n=44) were provided glucometers capable of data transmission and received advice pertaining to medication, diet, and exercise via the mHealth telemedicine system. Patients assigned to the control group (n=47) received routine outpatient care with no additional intervention. Patients in both groups were followed up at regular 3-month intervals. Results: After 3 months, patients in the intervention group showed significant (P<.05) improvement in postprandial plasma glucose level. After 6 months, patients in the intervention group exhibited a decreasing trend in postprandial plasma glucose and glycated hemoglobin levels compared with the baseline and those in the control group (P<.05). Conclusions: Mobile phone–based telemedicine apps help improve glycemic control in older Chinese patients with T2DM. Trial Registration: China Clinical Trial Registration Center ChiCTR 1800015214; http://www.chictr.org.cn/showprojen.aspx?proj=25949 (Archived by WebCite at http://www.webcitation.org/73wKj1GMq). %M 30609983 %R 10.2196/10664 %U https://mhealth.jmir.org/2019/1/e10664/ %U https://doi.org/10.2196/10664 %U http://www.ncbi.nlm.nih.gov/pubmed/30609983 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 12 %P e12460 %T Continuous Temperature-Monitoring Socks for Home Use in Patients With Diabetes: Observational Study %A Reyzelman,Alexander M %A Koelewyn,Kristopher %A Murphy,Maryam %A Shen,Xuening %A Yu,E %A Pillai,Raji %A Fu,Jie %A Scholten,Henk Jan %A Ma,Ran %+ California School of Podiatric Medicine, Samuel Merritt University, 2299 Post Street, San Francisco, CA, 94115, United States, 1 415 345 1195, areyzelman@samuelmerritt.edu %K diabetes %K diabetic foot ulcer %K continuous temperature monitoring %K Charcot arthropathy %K digital health %K wearable %K neurofabric %K mobile phone %K wireless %K Bluetooth %K neuropathy %K home use %D 2018 %7 17.12.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Over 30 million people in the United States (over 9%) have been diagnosed with diabetes. About 25% of people with diabetes will experience a diabetic foot ulcer (DFU) in their lifetime. Unresolved DFUs may lead to sepsis and are the leading cause of lower-limb amputations. DFU rates can be reduced by screening patients with diabetes to enable risk-based interventions. Skin temperature assessment has been shown to reduce the risk of foot ulceration. While several tools have been developed to measure plantar temperatures, they only measure temperature once a day or are designed for clinic use only. In this report, wireless sensor-embedded socks designed for daily wear are introduced, which perform continuous temperature monitoring of the feet of persons with diabetes in the home environment. Combined with a mobile app, this wearable device informs the wearer about temperature increases in one foot relative to the other, to facilitate early detection of ulcers and timely intervention. Objective: A pilot study was conducted to assess the accuracy of sensors used in daily wear socks, obtain user feedback on how comfortable sensor-embedded socks were for home use, and examine whether observed temperatures correlated with clinical observations. Methods: Temperature accuracy of sensors was assessed both prior to incorporation in the socks, as well as in the completed design. The measured temperatures were compared to the reference standard, a high-precision thermostatic water bath in the range 20°C-40°C. A total of 35 patients, 18 years of age and older, with diabetic peripheral neuropathy were enrolled in a single-site study conducted under an Institutional Review Board–approved protocol. This study evaluated the usability of the sensor-embedded socks and correlated the observed temperatures with clinical findings. Results: The temperatures measured by the stand-alone sensors were within 0.2°C of the reference standard. In the sensor-embedded socks, across multiple measurements for each of the six sensors, a high agreement (R2=1) between temperatures measured and the reference standard was observed. Patients reported that the socks were easy to use and comfortable, ranking them at a median score of 9 or 10 for comfort and ease of use on a 10-point scale. Case studies are presented showing that the temperature differences observed between the feet were consistent with clinical observations. Conclusions: We report the first use of wireless continuous temperature monitoring for daily wear and home use in patients with diabetes and neuropathy. The wearers found the socks to be no different from standard socks. The temperature studies conducted show that the sensors used in the socks are reliable and accurate at detecting temperature and the findings matched clinical observations. Continuous temperature monitoring is a promising approach as an early warning system for foot ulcers, Charcot foot, and reulceration. %M 30559091 %R 10.2196/12460 %U http://www.jmir.org/2018/12/e12460/ %U https://doi.org/10.2196/12460 %U http://www.ncbi.nlm.nih.gov/pubmed/30559091 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 4 %P e17 %T Glucose Control, Disease Burden, and Educational Gaps in People With Type 1 Diabetes: Exploratory Study of an Integrated Mobile Diabetes App %A Tack,Cornelis J %A Lancee,Gerardus J %A Heeren,Barend %A Engelen,Lucien JLPG %A Hendriks,Sandra %A Zimmerman,Lisa %A De Massari,Daniele %A van Gelder,Marleen MHJ %A van de Belt,Tom H %+ Radboud REshape Innovation Center, Radboud University Medical Center, IR 911, Geert Grooteplein Zuid 10, Nijmegen, 6525 GA, Netherlands, 31 0243668911, tom.vandebelt@radboudumc.nl %K diabetes %K app %K self-care %K medication suggestion %K disease management %K diabetes mellitus, type 1 %K mobile applications %D 2018 %7 23.11.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Self-monitoring and self-management, crucial for optimal glucose control in type 1 diabetes, requires many disease-related decisions per day and imposes a substantial disease burden on people with diabetes. Innovative technologies that integrate relevant measurements may offer solutions that support self-management, decrease disease burden, and benefit diabetes control. Objective: The objective of our study was to evaluate a prototype integrated mobile phone diabetes app in people with type 1 diabetes. Methods: In this exploratory study, we developed an app that contained cloud-stored log functions for glucose, carbohydrates (including a library), insulin, planned exercise, and mood, combined with a bolus calculator and communication functions. Adults with diabetes tested the app for 6 weeks. We assessed the feasibility of app use, user experiences, perceived disease burden (through questionnaires), insulin dose and basal to bolus ratio, mean glucose level, hemoglobin A1c, and number of hypoglycemic events. Results: A total of 19 participants completed the study, resulting in 5782 data entries. The most frequently used feature was logging blood glucose, insulin, and carbohydrates. Mean diabetes-related emotional problems (measured with the Problem Areas in Diabetes scale) scores decreased from 14.4 (SD 10.0) to 12.2 (SD 10.3; P=.04), and glucose control improved, with hemoglobin A1c decreasing from 7.9% (mean 62.3, SD 8 mmol/mol) to 7.6% (mean 59.8, SD 7 mmol/mol; P=.047). The incidence of hypoglycemic events did not change. Participants were generally positive about the app, rating it as “refreshing,” and as providing structure by reinforcing insulin-dosing principles. The app revealed substantial knowledge gaps. Logged data enabled additional detailed analyses. Conclusions: An integrated mobile diabetes app has the potential to improve diabetes self-management and provide tailored educational support, which may decrease disease burden and benefit diabetes control. %M 30470680 %R 10.2196/diabetes.9531 %U http://diabetes.jmir.org/2018/4/e17/ %U https://doi.org/10.2196/diabetes.9531 %U http://www.ncbi.nlm.nih.gov/pubmed/30470680 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 11 %P e12237 %T App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison %A Martinez-Millana,Antonio %A Jarones,Elena %A Fernandez-Llatas,Carlos %A Hartvigsen,Gunnar %A Traver,Vicente %+ ITACA, Universitat Politècnica de València, Camino de Vera s/n, Valencia, 46022, Spain, 34 963877606, anmarmil@itaca.upv.es %K mHealth %K type 1 diabetes mellitus %K patient empowerment %K apps %K diabetes self-management %D 2018 %7 21.11.2018 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: Research in type 1 diabetes management has increased exponentially since the irruption of mobile health apps for its remote and self-management. Despite this fact, the features affect in the disease management and patient empowerment are adopted by app makers and provided to the general population remain unexplored. Objective: To study the gap between literature and available apps for type 1 diabetes self-management and patient empowerment and to discover the features that an ideal app should provide to people with diabetes. Methods: The methodology comprises systematic reviews in the scientific literature and app marketplaces. We included articles describing interventions that demonstrated an effect on diabetes management with particular clinical endpoints through the use of mobile technologies. The features of these apps were gathered in a taxonomy of what an ideal app should look like to then assess which of these features are available in the market. Results: The literature search resulted in 231 matches. Of these, 55 met the inclusion criteria. A taxonomy featuring 3 levels of characteristics was designed based on 5 papers which were selected for the synthesis. Level 1 includes 10 general features (Personalization, Family support, Agenda, Data record, Insulin bolus calculator, Data management, Interaction, Tips and support, Reminders, and Rewards) Level 2 and Level 3 included features providing a descriptive detail of Level 1 features. Eighty apps matching the inclusion criteria were analyzed. None of the assessed apps fulfilled the features of the taxonomy of an ideal app. Personalization (70/80, 87.5%) and Data record (64/80, 80.0%) were the 2 top prevalent features, whereas Agenda (5/80, 6.3%) and Rewards (3/80, 3.8%) where the less predominant. The operating system was not associated with the number of features (P=.42, F=.81) nor the type of feature (P=.20, χ2=11.7). Apps were classified according to the number of level 1 features and sorted into quartiles. First quartile apps had a regular distribution of the ten features in the taxonomy whereas the other 3 quartiles had an irregular distribution. Conclusions: There are significant gaps between research and the market in mobile health for type 1 diabetes management. While the literature focuses on aspects related to gamification, rewarding, and social communities, the available apps are focused on disease management aspects such as data record and appointments. Personalized and tailored empowerment features should be included in commercial apps for large-scale assessment of potential in the self-management of the disease. %M 30463839 %R 10.2196/12237 %U http://mhealth.jmir.org/2018/11/e12237/ %U https://doi.org/10.2196/12237 %U http://www.ncbi.nlm.nih.gov/pubmed/30463839 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 4 %P e10105 %T Promoting Self-Care of Diabetic Foot Ulcers Through a Mobile Phone App: User-Centered Design and Evaluation %A Ploderer,Bernd %A Brown,Ross %A Seng,Leonard Si Da %A Lazzarini,Peter A %A van Netten,Jaap J %+ School of Electrical Engineering and Computer Science, Queensland University of Technology, Gardens Point 2 George Street, Brisbane, QLD, 4001, Australia, 61 73138 ext 4927, b.ploderer@qut.edu.au %K mobile apps %K foot ulcer, diabetic %K self-care (rehabilitation) %K therapeutic adherence and compliance %K patient engagement %K podiatry %D 2018 %7 10.10.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Without effective self-care, people with diabetic foot ulcers (DFUs) are at risk of prolonged healing times, hospitalization, amputation, and reduced quality of life. Despite these consequences, adherence to DFU self-care remains low. New strategies are needed to engage people in the self-care of their DFUs. Objective: This study aimed to evaluate the usability and potential usefulness of a new mobile phone app to engage people with DFUs in self-care. Methods: We developed a new mobile phone app, MyFootCare, to engage people with DFUs through goals, progress monitoring, and reminders in self-care. Key features included novel visual analytics that automatically extract and monitor DFU size information from mobile phone photos of the foot. A functional prototype of MyFootCare was created and evaluated through a user-centered design process with 11 participants with DFUs. Data were collected through semistructured interviews discussing existing self-care practices and observations of MyFootCare with participants. Data were analyzed qualitatively through thematic analysis. Results: Key themes were as follows: (1) participants already used mobile phone photos to monitor their DFU progress; (2) participants had limited experience with using mobile phone apps; (3) participants desired the objective DFU size data provided by the tracking feature of MyFootCare to monitor their DFU progress; (4) participants were ambivalent about the MyFootCare goal image and diary features, commenting that these features were useful but also that it was unlikely that they would use them; and (5) participants desired to share their MyFootCare data with their clinicians to demonstrate engagement in self-care and to reflect on their progress. Conclusions: MyFootCare shows promising features to engage people in DFU self-care. Most notably, ulcer size data are useful to monitor progress and engage people. However, more work is needed to improve the usability and accuracy of MyFootCare, that is, by refining the process of taking and analyzing photos of DFUs and removing unnecessary features. These findings open the door for further work to develop a system that is easy to use and functions in everyday life conditions and to test it with people with DFUs and their carers. %M 30305266 %R 10.2196/10105 %U https://diabetes.jmir.org/2018/4/e10105/ %U https://doi.org/10.2196/10105 %U http://www.ncbi.nlm.nih.gov/pubmed/30305266 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 9 %P e11400 %T Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study %A Zhang,Yiyu %A Li,Xia %A Luo,Shuoming %A Liu,Chaoyuan %A Liu,Fang %A Zhou,Zhiguang %+ Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, No 139, Renmin Road, Changsha, 410011, China, 86 073185292154, zhouzhiguang@csu.edu.cn %K diabetes mellitus, type 1 %K mobile applications %K qualitative research %K surveys and questionnaires %D 2018 %7 21.9.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: With the popularity of mobile phones, mobile apps have great potential for the management of diabetes, but the effectiveness of current diabetes apps for type 1 diabetes mellitus (T1DM) is poor. No study has explored the reasons for this deficiency from the users’ perspective. Objective: The aims of this study were to explore the perspectives and needs of T1DM patients and diabetes experts concerning a diabetes app and to design a new T1DM management mobile app. Methods: A mixed-methods design combining quantitative surveys and qualitative interviews was used to explore users’ needs and perspectives. Experts were surveyed at 2 diabetes conferences using paper questionnaires. T1DM patients were surveyed using Sojump (Changsha ran Xing InfoTech Ltd) on a network. We conducted semistructured, in-depth interviews with adult T1DM patients or parents of child patients who had ever used diabetes apps. The interviews were audio-recorded, transcribed, and coded for theme identification. Results: The expert response rate was 63.5% (127/200). The respondents thought that the reasons for app invalidity were that patients did not continue using the app (76.4%, 97/127), little guidance was received from health care professionals (HCPs; 73.2%, 93/127), diabetes education knowledge was unsystematic (52.8%, 67/127), and the app functions were incomplete (44.1%, 56/127). A total of 245 T1DM patient questionnaires were collected, of which 21.2% (52/245) of the respondents had used diabetes apps. The reasons for their reluctance to use an app were limited time (39%, 20/52), complicated operations (25%, 13/52), uselessness (25%, 13/52), and cost (25%, 13/52). Both the experts and patients thought that the most important functions of the app were patient-doctor communication and the availability of a diabetes diary. Two themes that were useful for app design were identified from the interviews: (1) problems with patients’ diabetes self-management and (2) problems with current apps. In addition, needs and suggestions for a diabetes app were obtained. Patient-doctor communication, diabetes diary, diabetes education, and peer support were all considered important by the patients, which informed the development of a prototype multifunctional app. Conclusions: Patient-doctor communication is the most important function of a diabetes app. Apps should be integrated with HCPs rather than stand-alone. We advocate that doctors follow up with their patients using a diabetes app. Our user-centered method explored comprehensively and deeply why the effectiveness of current diabetes apps for T1DM was poor and what T1DM patients needed for a diabetes app and provided meaningful guidance for app design. %M 30249580 %R 10.2196/11400 %U http://mhealth.jmir.org/2018/9/e11400/ %U https://doi.org/10.2196/11400 %U http://www.ncbi.nlm.nih.gov/pubmed/30249580 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 7 %P e158 %T The Complexity of Mental Health App Privacy Policies: A Potential Barrier to Privacy %A Powell,Adam C %A Singh,Preeti %A Torous,John %+ Payer+Provider Syndicate, 111 Beach Street Suite 4e, Boston, MA 02111, United States, 1 617 939 9168, powell@payerprovider.com %K apps %K privacy %K ethics %K mobile phone %D 2018 %7 30.7.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In 2017, the Supreme Court of India ruled that privacy is a fundamental right of every citizen. Although mobile phone apps have the potential to help people with noncommunicable diseases, such as diabetes and mental illness, they often contain complex privacy policies, which consumers may not understand. This complexity may impede the ability of consumers to make decisions regarding privacy, a critical issue due to the stigma of mental illness. Objective: Our objective is to determine whether mental health apps have more complex privacy policies than diabetes apps. Methods: The study used privacy policies extracted from apps. The apps pertained to diabetes or mental health, and were all of Indian origin. Privacy policy reading complexity was compared between the two types of apps using a series of 15 readability measures. The universe of applicable apps on the Google Play store, as viewed between May and June 2017, was considered. The measures of readability were compared using chi-square tests. Results: No significant difference was found between the privacy policy readability of the diabetes apps versus the mental health apps for each of the measures considered. The mean Flesch-Kincaid Grade Level was 13.9 for diabetes apps and 13.6 for mental health apps; therefore, the mean policy grade level for both types of apps was written at a college level. Privacy policies in the 25th percentile of complexity were also written at a college level for both types of apps. Conclusions: Privacy policy complexity may be a barrier for informed decision making. %M 30061090 %R 10.2196/mhealth.9871 %U http://mhealth.jmir.org/2018/7/e158/ %U https://doi.org/10.2196/mhealth.9871 %U http://www.ncbi.nlm.nih.gov/pubmed/30061090 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 7 %P e10206 %T Diabetes Educators’ Insights Regarding Connecting Mobile Phone– and Wearable Tracker–Collected Self-Monitoring Information to a Nationally-Used Electronic Health Record System for Diabetes Education: Descriptive Qualitative Study %A Wang,Jing %A Chu,Chin-Fun %A Li,Chengdong %A Hayes,Laura %A Siminerio,Linda %+ School of Nursing, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, MSC 7851, San Antonio, TX, 78229-3900, United States, 1 210 450 8561, jwang10@uthscsa.edu %K wearable %K connected health %K mHealth %K diabetes %K self-management %K lifestyle intervention %K electronic health record %K self-monitoring %K behavior modification %K usability %D 2018 %7 26.07.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes educators are integral to a clinical team in providing diabetes self-management education and support; however, current mobile and Web-based self-management tools are not integrated into clinical diabetes care to support diabetes educators’ education efforts. Objective: The objective of our study was to seek diabetes educators’ insights regarding the development of an interface within the Chronicle Diabetes system, a nationally used electronic health record (EHR) system for diabetes education documentation with behavioral goal-setting functions, to transfer mobile phone- and wearable tracker-collected self-monitoring information from patients to diabetes educators to facilitate behavioral goal monitoring. Methods: A descriptive qualitative study was conducted to seek educators’ perspectives on usability and interface development preferences in developing a connected system. Educators can use the Chronicle Diabetes system to set behavioral goals with their patients. Individual and group interviews were used to seek educators’ preferences for viewing mobile phone- and wearable tracker-collected information on diet, physical activity, and sleep in the Chronicle Diabetes system using open-ended questions. Interview data were transcribed verbatim and analyzed for common themes. Results: Five common themes emerged from the discussion. First, educators expressed enthusiasm for and concerns about viewing diet and physical activity data in Chronicle Diabetes system. Second, educators valued viewing detailed dietary macronutrients and activity data; however, they preferred different kinds of details depending on patients’ needs, conditions, and behavioral goals and educators’ training background. Third, all educators liked the integration of mobile phone-collected data into Chronicle Diabetes system and preferably with current EHR systems. Fourth, a need for a health care team and a central EHR system to be formed was realized for educators to share summaries of self-monitoring data with other providers. Fifth, educators desired advanced features for the mobile app and the connected interface that can show self-monitoring data. Conclusions: Flexibility is needed for educators to track the details of mobile phone- and wearable tracker-collected diet and activity information, and the integration of such data into Chronicle Diabetes and EHR systems is valuable for educators to track patients’ behavioral goals, provide diabetes self-management education and support, and share data with other health care team members to faciliate team-based care in clinical practice. %M 30049667 %R 10.2196/10206 %U http://mhealth.jmir.org/2018/7/e10206/ %U https://doi.org/10.2196/10206 %U http://www.ncbi.nlm.nih.gov/pubmed/30049667 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 2 %P e10 %T New-Onset Diabetes Educator to Educate Children and Their Caregivers About Diabetes at the Time of Diagnosis: Usability Study %A Bernier,Angelina %A Fedele,David %A Guo,Yi %A Chavez,Sarah %A Smith,Megan D %A Warnick,Jennifer %A Lieberman,Leora %A Modave,François %+ Department of Health Outcomes and Biomedical Informatics, University of Florida, 2004 Mowry Road, CTRB 3217, Gainesville, FL, 32610, United States, 1 3522945984, modavefp@ufl.edu %K mHealth %K information technology %K diabetes education %K pediatrics %D 2018 %7 06.06.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Diabetes self-management education is essential at the time of diagnosis. We developed the New-Onset Diabetes Educator (NODE), an animation-based educational web application for type 1 diabetes mellitus patients. Objective: Our hypothesis is that NODE is a feasible, effective and user-friendly intervention in improving diabetes self-management education delivery to child/caregiver-dyads at the time of diagnosis. Methods: We used a pragmatic parallel randomized trial design. Dyads were recruited within 48 hours of diagnosis and randomized into a NODE-enhanced diabetes self-management education or a standard diabetes self-management education group. Dyads randomized in the NODE group received the intervention on an iPad before receiving the standard diabetes self-management education with a nurse educator. The Diabetes Knowledge Test 2 assessed disease-specific knowledge pre- and postintervention in both groups, and was compared using t tests. Usability of the NODE mobile health intervention was assessed in the NODE group. Results: We recruited 16 dyads (mean child age 10.75, SD 3.44). Mean Diabetes Knowledge Test 2 scores were 14.25 (SD 4.17) and 18.13 (SD 2.17) pre- and postintervention in the NODE group, and 15.50 (SD 2.67) and 17.38 (SD 2.26) in the standard diabetes self-management education group. The effect size was medium (Δ=0.56). Usability ratings of NODE were excellent. Conclusions: NODE is a feasible mobile health strategy for type 1 diabetes education. It has the potential to be an effective and scalable tool to enhance diabetes self-management education at time of diagnosis, and consequently, could lead to improved long-term clinical outcomes for patients living with the disease. %M 30291069 %R 10.2196/diabetes.9202 %U http://diabetes.jmir.org/2018/2/e10/ %U https://doi.org/10.2196/diabetes.9202 %U http://www.ncbi.nlm.nih.gov/pubmed/30291069 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 6 %P e131 %T Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes %A Weatherall,James %A Paprocki,Yurek %A Meyer,Theresa M %A Kudel,Ian %A Witt,Edward A %+ Kantar Health, 700 Dresher Road, Suite 200, Horsham, PA, 19044, United States, 1 484 442 1415, Theresa.Meyer@kantarhealth.com %K Fitbit charge HR %K type 2 diabetes mellitus %K sleep %K health outcomes %K health behaviors %D 2018 %7 05.06.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist. Objective: The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM). Methods: This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating. Results: The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=−.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02). Conclusions: Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes. %R 10.2196/mhealth.8122 %U http://mhealth.jmir.org/2018/6/e131/ %U https://doi.org/10.2196/mhealth.8122 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 5 %P e10662 %T A Mobile App for Identifying Individuals With Undiagnosed Diabetes and Prediabetes and for Promoting Behavior Change: 2-Year Prospective Study %A Leung,Angela YM %A Xu,Xin Yi %A Chau,Pui Hing %A Yu,Yee Tak Esther %A Cheung,Mike KT %A Wong,Carlos KH %A Fong,Daniel YT %A Wong,Janet YH %A Lam,Cindy LK %+ Centre for Gerontological Nursing, School of Nursing, The Hong Kong Polytechnic University, GH528, 5th Floor, Core G, School of Nursing, Hung Hom, Kowloon, Hong Kong SAR,, China (Hong Kong), 852 27665587, angela.ym.leung@polyu.edu.hk %K diabetes mellitus %K prediabetes %K prediabetic state %K mobile apps %K lifestyle %D 2018 %7 24.05.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: To decrease the burden of diabetes in society, early screening of undiagnosed diabetes and prediabetes is needed. Integrating a diabetes risk score into a mobile app would provide a useful platform to enable people to self-assess their risk of diabetes with ease. Objective: The objectives of this study were to (1) assess the profile of Diabetes Risk Score mobile app users, (2) determine the optimal cutoff value of the Finnish Diabetes Risk Score to identify undiagnosed diabetes and prediabetes in the Chinese population, (3) estimate users’ chance of developing diabetes within 2 years of using the app, and (4) investigate high-risk app users’ lifestyle behavior changes after ascertaining their risk level from the app. Methods: We conducted this 2-phase study among adults via mobile app and online survey from August 2014 to December 2016. Phase 1 adopted a cross-sectional design, with a descriptive analysis of the app users’ profile. We used a Cohen kappa score to show the agreement between the risk level (as shown in the app) and glycated hemoglobin test results. We used sensitivity, specificity, and area under the curve to determine the optimal cutoff value of the diabetes risk score in this population. Phase 2 was a prospective cohort study. We used a logistic regression model to estimate the chance of developing diabetes after using the app. Paired t tests compared high-risk app users’ lifestyle changes. Results: A total of 13,289 people used the app in phase 1a. After data cleaning, we considered 4549 of these as valid data. Most users were male, and 1811 (39.81%) had tertiary education or above. Among them, 188 (10.4%) users agreed to attend the health assessment in phase 1b. We recommend the optimal value of the diabetes risk score for identifying persons with undiagnosed diabetes and prediabetes to be 9, with an area under the receiver operating characteristic curve of 0.67 (95% CI 0.60-0.74), sensitivity of 0.70 (95% CI 0.58-0.80), and specificity of 0.57 (95% CI 0.47-0.66). At the 2-year follow-up, people in the high-risk group had a higher chance of developing diabetes (odds ratio 4.59, P=.048) than the low-risk group. The high-risk app users improved their daily intake of vegetables (baseline: mean 0.76, SD 0.43; follow-up: mean 0.93, SD 0.26; t81=–3.77, P<.001) and daily exercise (baseline: mean 0.40, SD 0.49; follow-up: mean 0.54, SD 0.50; t81=–2.08, P=.04). Conclusions: The Diabetes Risk Score app has been shown to be a feasible and reliable tool to identify persons with undiagnosed diabetes and prediabetes and to predict diabetes incidence in 2 years. The app can also encourage high-risk people to modify dietary habits and reduce sedentary lifestyle. %M 29793901 %R 10.2196/10662 %U http://mhealth.jmir.org/2018/5/e10662/ %U https://doi.org/10.2196/10662 %U http://www.ncbi.nlm.nih.gov/pubmed/29793901 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 5 %P e162 %T The Effectiveness of Smartphone Apps for Lifestyle Improvement in Noncommunicable Diseases: Systematic Review and Meta-Analyses %A Lunde,Pernille %A Nilsson,Birgitta Blakstad %A Bergland,Astrid %A Kværner,Kari Jorunn %A Bye,Asta %+ Department of Physiotherapy, Faculty of Health Sciences, OsloMet—Oslo Metropolitan University, 1st Floor, Pilestredet 50, Oslo, 0130, Norway, 47 48063537, plunde@oslomet.no %K smartphone %K telemedicine %K noncommunicable diseases %K lifestyle %K diet %K exercise %D 2018 %7 04.05.2018 %9 Review %J J Med Internet Res %G English %X Background: Noncommunicable diseases (NCDs) account for 70% of all deaths in a year globally. The four main NCDs are cardiovascular diseases, cancers, chronic pulmonary diseases, and diabetes mellitus. Fifty percent of persons with NCD do not adhere to prescribed treatment; in fact, adherence to lifestyle interventions is especially considered as a major challenge. Smartphone apps permit structured monitoring of health parameters, as well as the opportunity to receive feedback. Objective: The aim of this study was to review and assess the effectiveness of app-based interventions, lasting at least 3 months, to promote lifestyle changes in patients with NCDs. Methods: In February 2017, a literature search in five databases (EMBASE, MEDLINE, CINAHL, Academic Research Premier, and Cochrane Reviews and Trials) was conducted. Inclusion criteria was quantitative study designs including randomized and nonrandomized controlled trials that included patients aged 18 years and older diagnosed with any of the four main NCDs. Lifestyle outcomes were physical activity, physical fitness, modification of dietary habits, and quality of life. All included studies were assessed for risk of bias using the Cochrane Collaboration`s risk of bias tool. Meta-analyses were conducted for one of the outcomes (glycated hemoglobin, HbA1c) by using the estimate of effect of mean post treatment with SD or CI. Heterogeneity was tested using the I2 test. All studies included in the meta-analyses were graded. Results: Of the 1588 records examined, 9 met the predefined criteria. Seven studies included diabetes patients only, one study included heart patients only, and another study included both diabetes and heart patients. Statistical significant effect was shown in HbA1c in 5 of 8 studies, as well in body weight in one of 5 studies and in waist circumference in one of 3 studies evaluating these outcomes. Seven of the included studies were included in the meta-analyses and demonstrated significantly overall effect on HbA1c on a short term (3-6 months; P=.02) with low heterogeneity (I2=41%). In the long term (10-12 months), the overall effect on HbA1c was statistical significant (P=.009) and without heterogeneity (I2=0%). The quality of evidence according to Grading of Recommendations Assessment, Development and Evaluation was low for short term and moderate for long term. Conclusions: Our review demonstrated limited research of the use of smartphone apps for NCDs other than diabetes with a follow-up of at least 3 months. For diabetes, the use of apps seems to improve lifestyle factors, especially to decrease HbA1c. More research with long-term follow-up should be performed to assess the effect of smartphone apps for NCDs other than diabetes. %M 29728346 %R 10.2196/jmir.9751 %U http://www.jmir.org/2018/5/e162/ %U https://doi.org/10.2196/jmir.9751 %U http://www.ncbi.nlm.nih.gov/pubmed/29728346 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 5 %P e93 %T Usefulness of a Novel Mobile Diabetes Prevention Program Delivery Platform With Human Coaching: 65-Week Observational Follow-Up %A Michaelides,Andreas %A Major,Jennifer %A Pienkosz Jr,Edmund %A Wood,Meghan %A Kim,Youngin %A Toro-Ramos,Tatiana %+ Clinical Research Department, Noom Inc, 229 West 28th Street, 9th Floor, New York, NY,, United States, 1 347 480 8871, tatiana@noom.com %K prediabetes %K body weight %K behavioral interventions %K mHealth %K mobile app %K diabetes prevention %D 2018 %7 03.05.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: It is widely recognized that the prevalence of obesity and comorbidities including prediabetes and type 2 diabetes continue to increase worldwide. Results from a 24-week Diabetes Prevention Program (DPP) fully mobile pilot intervention were previously published showing promising evidence of the usefulness of DPP-based eHealth interventions on weight loss. Objective: This pilot study extends previous findings to evaluate weight loss results of core (up to week 16) and maintenance (postcore weeks) DPP interventions at 65 weeks from baseline. Methods: Originally, 140 participants were invited and 43 overweight or obese adult participants with a diagnosis of prediabetes signed up to receive a 24-week virtual DPP with human coaching through a mobile platform. At 65 weeks, this pilot study evaluates weight loss and engagement in maintenance participants by means of repeated measures analysis of variances and backward multiple linear regression to examine predictors of weight loss. Last observation carried forward was used for endpoint measurements. Results: At 65 weeks, mean weight loss was 6.15% in starters who read 1 or more lessons per week on 4 or more core weeks, 7.36% in completers who read 9 or more lessons per week on core weeks, and 8.98% in maintenance completers who did any action in postcore weeks (all P<.001). Participants were highly engaged, with 80% (47/59) of the sample completing 9 lessons or more and 69% (32/47) of those completing the maintenance phase. In-app actions related to self-monitoring significantly predicted weight loss. Conclusions: In comparison to eHealth programs, this pilot study shows that a fully mobile DPP can produce transformative weight loss. A fully mobile DPP intervention resulted in significant weight loss and high engagement during the maintenance phase, providing evidence for long-term potential as an alternative to in-person DPP by removing many of the barriers associated with in-person and other forms of virtual DPP. %M 29724709 %R 10.2196/mhealth.9161 %U http://mhealth.jmir.org/2018/5/e93/ %U https://doi.org/10.2196/mhealth.9161 %U http://www.ncbi.nlm.nih.gov/pubmed/29724709 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 4 %P e92 %T A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial %A Wang,Jing %A Cai,Chunyan %A Padhye,Nikhil %A Orlander,Philip %A Zare,Mohammad %+ Cizik School of Nursing, The University of Texas Health Science Center at Houston, 6901 Bertner Avenue, SON 580C, Houston, TX, 77030, United States, 1 7135009022, jing.wang@uth.tmc.edu %K self-monitoring %K diabetes %K obesity %K mobile health %K behavior change %K connected health %K patient-generated health data %K lifestyle %K patient engagement %K comparative effectiveness trial %D 2018 %7 10.04.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Self-monitoring is a cornerstone of behavioral lifestyle interventions for obesity and type 2 diabetes mellitus. Mobile technology has the potential to improve adherence to self-monitoring and patient outcomes. However, no study has tested the use of a smartphone to facilitate self-monitoring in overweight or obese adults with type 2 diabetes mellitus living in the underserved community. Objective: The aim of this study was to examine the feasibility of and compare preliminary efficacy of a behavioral lifestyle intervention using smartphone- or paper-based self-monitoring of multiple behaviors on weight loss and glycemic control in a sample of overweight or obese adults with type 2 diabetes mellitus living in underserved communities. Methods: We conducted a randomized controlled trial to examine the feasibility and preliminary efficacy of a behavioral lifestyle intervention. Overweight or obese patients with type 2 diabetes mellitus were recruited from an underserved minority community health center in Houston, Texas. They were randomly assigned to one of the three groups: (1) behavior intervention with smartphone-based self-monitoring, (2) behavior intervention with paper diary-based self-monitoring, and (3) usual care group. Both the mobile and paper groups received a total of 11 face-to-face group sessions in a 6-month intervention. The mobile group received an Android-based smartphone with 2 apps loaded to help them record their diet, physical activity, weight, and blood glucose, along with a connected glucometer, whereas the paper group used paper diaries for these recordings. Primary outcomes of the study included percentage weight loss and glycated hemoglobin (HbA1c) changes over 6 months. Results: A total of 26 patients were enrolled: 11 in the mobile group, 9 in the paper group, and 6 in the control group. We had 92% (24/26) retention rate at 6 months. The sample is predominantly African Americans with an average age of 56.4 years and body mass index of 38.1. Participants lost an average of 2.73% (mobile group) and 0.13% (paper group) weight at 6 months, whereas the control group had an average 0.49% weight gain. Their HbA1c changed from 8% to 7 % in mobile group, 10% to 9% in paper group, and maintained at 9% for the control group. We found a significant difference on HbA1c at 6 months among the 3 groups (P=.01). We did not find statistical group significance on percentage weight loss (P=.20) and HbA1c changes (P=.44) overtime; however, we found a large effect size of 0.40 for weight loss and a medium effect size of 0.28 for glycemic control. Conclusions: Delivering a simplified behavioral lifestyle intervention using mobile health–based self-monitoring in an underserved community is feasible and acceptable and shows higher preliminary efficacy, as compared with paper-based self-monitoring. A full-scale randomized controlled trial is needed to confirm the findings in this pilot study. Trial Registration: ClinicalTrials.gov NCT02858648; https://clinicaltrials.gov/ct2/show/NCT02858648 (Archived by WebCite at http://www.webcitation.org/6ySidjmT7) %M 29636320 %R 10.2196/mhealth.4478 %U http://mhealth.jmir.org/2018/4/e92/ %U https://doi.org/10.2196/mhealth.4478 %U http://www.ncbi.nlm.nih.gov/pubmed/29636320 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 7 %N 4 %P e10009 %T Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial %A Wang,Jing %A Coleman,Deidra Carroll %A Kanter,Justin %A Ummer,Brad %A Siminerio,Linda %+ Cizik School of Nursing, The University of Texas Health Science Center at Houston, 6901 Bertner Avenue, SON 580C, Houston, TX, 77030, United States, 1 7135009022, jing.wang@uth.tmc.edu %K wearable devices %K connected health %K mobile health %K diabetes %K randomized clinical trial %K goal setting %K lifestyle intervention %K electronic health record %K self-monitoring %K behavior modification %D 2018 %7 02.04.2018 %9 Protocol %J JMIR Res Protoc %G English %X Background: Mobile and wearable technology have been shown to be effective in improving diabetes self-management; however, integrating data from these technologies into clinical diabetes care to facilitate behavioral goal monitoring has not been explored. Objective: The objective of this paper is to report on a study protocol for a pragmatic multi-site trial along with the intervention components, including the detailed connected health interface. This interface was developed to integrate patient self-monitoring data collected from a wearable fitness tracker and its companion smartphone app to an electronic health record system for diabetes self-management education and support (DSMES) to facilitate behavioral goal monitoring. Methods: A 3-month multi-site pragmatic clinical trial was conducted with eligible patients with diabetes mellitus from DSMES programs. The Chronicle Diabetes system is currently freely available to diabetes educators through American Diabetes Association–recognized DSMES programs to set patient nutrition and physical activity goals. To integrate the goal-setting and self-monitoring intervention into the DSMES process, a connected interface in the Chronicle Diabetes system was developed. With the connected interface, patient self-monitoring information collected from smartphones and wearable fitness trackers can facilitate educators’ monitoring of patients’ adherence to their goals. Feasibility outcomes of the 3-month trial included hemoglobin A1c levels, weight, and the usability of the connected system. Results: An interface designed to connect data from a wearable fitness tracker with a companion smartphone app for nutrition and physical activity self-monitoring into a diabetes education electronic health record system was successfully developed to enable diabetes educators to facilitate goal setting and monitoring. A total of 60 eligible patients with type 2 diabetes mellitus were randomized into either group 1) standard diabetes education or 2) standard education enhanced with the connected system. Data collection for the 3-month pragmatic trial is completed. Data analysis is in progress. Conclusions: If results of the pragmatic multi-site clinical trial show preliminary efficacy and usability of the connected system, a large-scale implementation trial will be conducted. Trial Registration: ClinicalTrials.gov NCT02664233; https://clinicaltrials.gov/ct2/show/NCT02664233 (Archived by WebCite at http://www.webcitation.org/6yDEwXHo5) %M 29610111 %R 10.2196/10009 %U http://www.researchprotocols.org/2018/4/e10009/ %U https://doi.org/10.2196/10009 %U http://www.ncbi.nlm.nih.gov/pubmed/29610111 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 7 %N 3 %P e77 %T Strengths-Based Behavioral Intervention for Parents of Adolescents With Type 1 Diabetes Using an mHealth App (Type 1 Doing Well): Protocol for a Pilot Randomized Controlled Trial %A Hilliard,Marisa E %A Eshtehardi,Sahar S %A Minard,Charles G %A Saber,Rana %A Thompson,Debbe %A Karaviti,Lefkothea P %A Rojas,Yuliana %A Anderson,Barbara J %+ Section of Psychology, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, 1102 Bates Avenue, Suite 940, Houston, TX, 770030, United States, 1 832 824 7209, marisa.hilliard@bcm.edu %K adolescence %K type 1 diabetes %K parenting %D 2018 %7 13.03.2018 %9 Protocol %J JMIR Res Protoc %G English %X Background: Supportive parent involvement for adolescents’ type 1 diabetes (T1D) self-management promotes optimal diabetes outcomes. However, family conflict is common and can interfere with collaborative family teamwork. Few interventions have used explicitly strengths-based approaches to help reinforce desired management behaviors and promote positive family interactions around diabetes care. Objective: The aim of this protocol was to describe the development of a new, strengths-based behavioral intervention for parents of adolescents with T1D delivered via a mobile-friendly Web app called Type 1 Doing Well. Methods: Ten adolescent-parent dyads and 5 diabetes care providers participated in a series of qualitative interviews to inform the design of the app. The 3- to 4-month pilot intervention will involve 82 parents receiving daily prompts to use the app, in which they will mark the diabetes-related strength behaviors (ie, positive attitudes or behaviors related to living with or managing T1D) their teen engaged in that day. Parents will also receive training on how to observe diabetes strengths and how to offer teen-friendly praise via the app. Each week, the app will generate a summary of the teen’s most frequent strengths from the previous week based on parent reports, and parents will be encouraged to praise their teen either in person or from a library of reinforcing text messages (short message service, SMS). Results: The major outcomes of this pilot study will include intervention feasibility and satisfaction data. Clinical and behavioral outcomes will include glycemic control, regimen adherence, family relationships and conflict, diabetes burden, and health-related quality of life. Conclusions: This strengths-based, mobile health (mHealth) intervention aims to help parents increase their awareness of and efforts to support their adolescents’ engagement in positive diabetes-related behaviors. If efficacious, this intervention has the potential to reduce the risk of family conflict, enhance collaborative family teamwork, and ultimately improve diabetes outcomes. Trial Registration: ClinicalTrials.gov NCT02877680; https://clinicaltrials.gov/ct2/show/NCT02877680 (Archived by WebCite at http://www.webcitation.org/6xTAMN5k2) %M 29535081 %R 10.2196/resprot.9147 %U http://www.researchprotocols.org/2018/3/e77/ %U https://doi.org/10.2196/resprot.9147 %U http://www.ncbi.nlm.nih.gov/pubmed/29535081 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 1 %P e6 %T Mobile App for Simplifying Life With Diabetes: Technical Description and Usability Study of GlucoMan %A Schmocker,Kaspar S %A Zwahlen,Fabian S %A Denecke,Kerstin %+ Institute for Medical Informatics, Bern University of Applied Sciences, Quellgasse 21, Biel,, Switzerland, 41 32 321 67 94, kerstin.denecke@bfh.ch %K diabetes management %K patient empowerment %K mobile health %K self-care %K chronic disease management %K diabetes mellitus %K mobile apps %D 2018 %7 26.02.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Patients with diabetes can be affected by several comorbidities that require immediate action when occurring as they may otherwise cause fatal or consequential damage. For this reason, patients must closely monitor their metabolism and inject insulin when necessary. The documentation of glucose values and other relevant measurements is often still on paper in a diabetes diary. Objective: The goal of this work is to develop and implement a novel mobile health system for the secure collection of relevant data referring to a person’s metabolis and to digitize the diabetes diary to enable continuous monitoring for both patients and treating physicians. One specific subgoal is to enable data transmission of health parameters to secure data storage. Methods: The process of implementing the system consists of (1) requirements analysis with patients and physicians to identify patient needs and specify relevant functionalities, (2) design and development of the app and the data transmission, and (3) usability study. Results: We developed and implemented the mobile app GlucoMan to support data collection pertaining to a person’s metabolism. An automated transfer of measured values from a glucometer was implemented. Medication and nutrition data could be entered using product barcodes. Relevant background knowledge such as information on carbohydrates was collected from existing databases. The recorded data was transmitted using international interoperability standards to the MIDATA.coop storage platform. The usability study revealed some design issues that needs to be solved, but in principle, the study results show that the app is easy to use and provides useful features. Conclusions: Data collection on a patient’s metabolism can be supported with a multifunctional app such as GlucoMan. Besides monitoring, continuous data can be documented and made available to the treating physician. GlucoMan allows patients to monitor disease-relevant parameters and decide who accesses their health data. In this way, patients are empowered not only to manage diabetes but also manage their health data. %M 30291070 %R 10.2196/diabetes.8160 %U http://diabetes.jmir.org/2018/1/e6/ %U https://doi.org/10.2196/diabetes.8160 %U http://www.ncbi.nlm.nih.gov/pubmed/30291070 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 1 %P e4 %T Change in Glycemic Control With Use of a Digital Therapeutic in Adults With Type 2 Diabetes: Cohort Study %A Berman,Mark A %A Guthrie,Nicole L %A Edwards,Katherine L %A Appelbaum,Kevin J %A Njike,Valentine Y %A Eisenberg,David M %A Katz,David L %+ Better Therapeutics LLC, 445 Bush Street, Suite 300, San Francisco, CA,, United States, 1 617 877 0327, mark@bettertherapeutics.io %K type 2 diabetes %K mobile health %K mHealth %K lifestyle medicine %K mobile apps %K digital therapeutics %D 2018 %7 14.02.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Intensive lifestyle change can treat and even reverse type 2 diabetes. Digital therapeutics have the potential to deliver lifestyle as medicine for diabetes at scale. Objective: This 12-week study investigates the effects of a novel digital therapeutic, FareWell, on hemoglobin A1c (HbA1c) and diabetes medication use. Methods: Adults with type 2 diabetes and a mobile phone were recruited throughout the United States using Facebook advertisements. The intervention aim was to effect a sustainable shift to a plant-based dietary pattern and regular exercise by advancing culinary literacy and lifestyle skill acquisition. The intervention was delivered by an app paired with specialized human support, also delivered digitally. Health coaching was provided every 2 weeks by telephone, and a clinical team was available for participants requiring additional support. Participants self-reported current medications and HbA1c at the beginning and end of the 12-week program. Self-efficacy related to managing diabetes and maintaining dietary changes was assessed via survey. Engagement was recorded automatically through the app. Results: We enrolled 118 participants with a baseline HbA1c >6.5%. Participants were 81.4% female (96/118) and resided in 38 US states with a mean age of 50.7 (SD 9.4) years, baseline body mass index of 38.1 (SD 8.8) kg/m2, and baseline HbA1c of 8.1% (SD 1.6). At 12 weeks, 86.2% (94/109) of participants were still using the app. Mean change in HbA1c was –0.8% (97/101, SD 1.3, P<.001) for those reporting end-study data. For participants with a baseline HbA1c >7.0% who did not change medications midstudy, HbA1c change was –1.1% (67/69, SD 1.4, P<.001). The proportion of participants with an end-study HbA1c <6.5% was 28% (22/97). After completion of the intervention, 17% (16/97) of participants reported a decrease in diabetic medication while 8% (8/97) reported an increase. A total of 57% (55/97) of participants achieved a composite outcome of reducing HbA1c, reducing diabetic medication use, or both; 92% (90/98) reported greater confidence in their ability to manage their diabetes compared to before the program, and 91% (89/98) reported greater confidence in their ability to maintain a healthy dietary pattern. Participants engaged with the app an average of 4.3 times per day. We observed a significantly greater decrease in HbA1c among participants in the highest tertile of app engagement compared to those in the lowest tertile of app engagement (P=.03). Conclusions: Clinically meaningful reductions in HbA1c were observed with use of the FareWell digital therapeutic. Greater glycemic control was observed with increasing app engagement. Engagement and retention were both high in this widely distributed sample. %M 30291074 %R 10.2196/diabetes.9591 %U http://diabetes.jmir.org/2018/1/e4/ %U https://doi.org/10.2196/diabetes.9591 %U http://www.ncbi.nlm.nih.gov/pubmed/30291074 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 3 %N 1 %P e3 %T Use of a Mobile App to Facilitate Blood Glucose Monitoring in Adolescents With Type 1 Diabetes: Single-Subject Nonrandomized Clinical Trial %A Bellfield,Edward J %A Sharp,Lisa K %A Xia,Yinglin %A Gerber,Ben S %+ Department of Pediatrics, University of Illinois at Chicago, 840 South Wood Street, Chicago, IL, 60612, United States, 1 312 996 1795, ejbellfieldmd@gmail.com %K type 1 diabetes %K adolescence %K mobile health %K mHealth %K mobile phone %D 2018 %7 07.02.2018 %9 Original Paper %J JMIR Diabetes %G English %X Background: Cloud-based glucose monitoring programs allow users with diabetes to wirelessly synchronize their glucometers to their mobile phones. They also provide visualization and remote access of their data through its mobile app. There have been very few studies evaluating their effectiveness in managing diabetes among adolescents with type 1 diabetes (T1D). Objective: The purpose of this study was to assess the feasibility of using a mobile app to improve daily average blood glucose (BG) levels and increase BG monitoring frequency. Methods: We used an ABA single-subject prospective study design. We recruited five participants aged 13 to 17 years with uncontrolled T1D, glycated hemoglobin A1c 9.0%-10.7%, self-monitoring behavior of ≤5 checks/day, and on multiple daily insulin injections. The study consisted of 4-week intervals of three phases: (1) phase A: usual glucose monitoring log (fax); (2) phase B: mobile app; and (3) phase A': second phase A. A certified diabetes educator and endocrinologist reviewed logs and provided recommendations weekly. Data were analyzed using a quasi-Poisson model to adjust for overdispersion among individual participants, and a generalized estimating equation model for overall intervention effect in aggregate. Results: For mean daily BG (mg/dL) levels, participant 1 had decreased values on the mobile app (298 to 281, P=.03) and maintained in phase A'. Participant 4 had an increase in mean daily BG in phase A' (175 to 185, P=.01), whereas participant 5 had a decrease in mean daily BG in phase A' (314 to 211, P=.04). For daily monitoring (checks/day), participant 3 increased in phase B (4.6 to 8.3, P=.01) and maintained in phase A'. Participant 5 also had increased daily monitoring at each phase (2.1 to 2.4, P=.01; 2.4 to 3.4, P=.02). For the five participants combined, the overall mean BG and BG checks per day in phase A were mean 254.8 (SD 99.2) and mean 3.6 (SD 2.0), respectively, mean 223.1 (SD 95.7) and mean 4.5 (SD 3.0) in phase B, and mean 197.5 (SD 81.3) and mean 3.7 (SD 2.1) in phase A'. Compared to phase A, mean glucose levels declined during phase B and remained lower during phase A' (P=.002). There was no overall change in BG checks by phase (P=.25). However, mean BG levels negatively correlated with daily BG checks (r=–.47, P<.001). Although all participants had positive opinions about the app, its utilization was highly variable. Conclusions: We demonstrated modest feasibility of adolescents with uncontrolled T1D utilizing a glucose monitoring mobile app. Further study is needed to better determine its effects on BG level and monitoring frequency. Psychosocial factors and motivational barriers likely influence adoption and continuous use of technology for diabetes management. %M 30291085 %R 10.2196/diabetes.8357 %U http://diabetes.jmir.org/2018/1/e3/ %U https://doi.org/10.2196/diabetes.8357 %U http://www.ncbi.nlm.nih.gov/pubmed/30291085 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 6 %N 1 %P e6 %T Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus %A Pustozerov,Evgenii %A Popova,Polina %A Tkachuk,Aleksandra %A Bolotko,Yana %A Yuldashev,Zafar %A Grineva,Elena %+ Department of Biomedical Engineering, Saint Petersburg State Electrotechnical University, Professora Popova, 5, Saint Petersburg, 197376, Russian Federation, 7 812 234 01 33, pustozerov.e@gmail.com %K blood glucose prediction %K mHealth %K gestational diabetes mellitus %K recommender system %K personalized medicine %K mobile app %D 2018 %7 09.01.2018 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Personalized blood glucose (BG) prediction for diabetes patients is an important goal that is pursued by many researchers worldwide. Despite many proposals, only a few projects are dedicated to the development of complete recommender system infrastructures that incorporate BG prediction algorithms for diabetes patients. The development and implementation of such a system aided by mobile technology is of particular interest to patients with gestational diabetes mellitus (GDM), especially considering the significant importance of quickly achieving adequate BG control for these patients in a short period (ie, during pregnancy) and a typically higher acceptance rate for mobile health (mHealth) solutions for short- to midterm usage. Objective: This study was conducted with the objective of developing infrastructure comprising data processing algorithms, BG prediction models, and an appropriate mobile app for patients’ electronic record management to guide BG prediction-based personalized recommendations for patients with GDM. Methods: A mobile app for electronic diary management was developed along with data exchange and continuous BG signal processing software. Both components were coupled to obtain the necessary data for use in the personalized BG prediction system. Necessary data on meals, BG measurements, and other events were collected via the implemented mobile app and continuous glucose monitoring (CGM) system processing software. These data were used to tune and evaluate the BG prediction model, which included an algorithm for dynamic coefficients tuning. In the clinical study, 62 participants (GDM: n=49; control: n=13) took part in a 1-week monitoring trial during which they used the mobile app to track their meals and self-measurements of BG and CGM system for continuous BG monitoring. The data on 909 food intakes and corresponding postprandial BG curves as well as the set of patients’ characteristics (eg, glycated hemoglobin, body mass index [BMI], age, and lifestyle parameters) were selected as inputs for the BG prediction models. Results: The prediction results by the models for BG levels 1 hour after food intake were root mean square error=0.87 mmol/L, mean absolute error=0.69 mmol/L, and mean absolute percentage error=12.8%, which correspond to an adequate prediction accuracy for BG control decisions. Conclusions: The mobile app for the collection and processing of relevant data, appropriate software for CGM system signals processing, and BG prediction models were developed for a recommender system. The developed system may help improve BG control in patients with GDM; this will be the subject of evaluation in a subsequent study. %M 29317385 %R 10.2196/mhealth.9236 %U http://mhealth.jmir.org/2018/1/e6/ %U https://doi.org/10.2196/mhealth.9236 %U http://www.ncbi.nlm.nih.gov/pubmed/29317385 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 6 %N 12 %P e242 %T Mobile Health Technology (mDiab) for the Prevention of Type 2 Diabetes: Protocol for a Randomized Controlled Trial %A Muralidharan,Shruti %A Mohan,Viswanathan %A Anjana,Ranjit Mohan %A Jena,Sidhant %A Tandon,Nikhil %A Allender,Steven %A Ranjani,Harish %+ Translational Research Department, Madras Diabetes Research Foundation, Dr. Mohan's Diabetes Specialities Centre, No 4, Conron Smith Road,, Gopalapuram, Chennai, 600086, India, 91 4443968888, ranjani@mdrf.in %K prevention %K diabetes mellitus, type 2 %K mHealth %D 2017 %7 12.12.2017 %9 Protocol %J JMIR Res Protoc %G English %X Background: The prevalence of type 2 diabetes is increasing in epidemic proportions in low- and middle-income countries. There is an urgent need for novel methods to tackle the increasing incidence of diabetes. The ubiquity of mobile phone use and access to Internet makes mobile health (mHealth) technology a viable tool to prevent and manage diabetes. Objective: The objective of this randomized controlled trial is to implement and evaluate the feasibility, cost-effectiveness, and sustainability of a reality television–based lifestyle intervention program. This intervention program is delivered via a mobile phone app (mDiab) to approximately 1500 Android smartphone users who are adults at a high risk for type 2 diabetes from three cities in India, namely, Chennai, Bengaluru, and New Delhi. Methods: The mDiab intervention would be delivered via a mobile phone app along with weekly coach calls for 12 weeks. Each participant will go through a maintenance phase of 6 to 8 months post intervention. Overall, there would be 3 testing time points in the study: baseline, post intervention, and the end of follow-up. The app will enable individuals to track their weight, physical activity, and diet alongside weekly video lessons on type 2 diabetes prevention. Results: The study outcomes are weight loss (primary measure of effectiveness); improvement in cardiometabolic risk factors (ie, waist circumference, blood pressure, glucose, insulin, and lipids); and improvement in physical activity, quality of life, and dietary habits. Sustainability will be assessed through focus group discussions. Conclusions: If successful, mDiab can be used as a model for translational and implementation research in the use of mHealth technology for diabetes prevention and may be further expanded for the prevention of other noncommunicable diseases such as hypertension and cardiovascular diseases. Trial Registration: Clinical Trials Registry of India CTRI/2015/07/006011 http://ctri.nic.in/Clinicaltrials/pdf_generate.php? trialid=11841 (Archived by WebCite at http://www.webcitation.org/6urCS5kMB) %M 29233806 %R 10.2196/resprot.8644 %U http://www.researchprotocols.org/2017/12/e242/ %U https://doi.org/10.2196/resprot.8644 %U http://www.ncbi.nlm.nih.gov/pubmed/29233806 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e30 %T A Feasible and Efficacious Mobile-Phone Based Lifestyle Intervention for Filipino Americans with Type 2 Diabetes: Randomized Controlled Trial %A Bender,Melinda S %A Cooper,Bruce A %A Park,Linda G %A Padash,Sara %A Arai,Shoshana %+ Family Health Care Nursing Department, School of Nursing, University of California San Francisco, 2 Koret Way, N431C, Box 0606, San Francisco, CA, 94143, United States, 1 415 502 5668, melinda.bender@ucsf.edu %K randomized controlled trial %K mobile health %K Filipino American %K type 2 diabetes %K weight loss %K physical activity %K diet %D 2017 %7 12.12.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Filipino Americans have a high prevalence of obesity, type 2 diabetes (T2D), and cardiovascular disease compared with other Asian American subgroups and non-Hispanic whites. Mobile health (mHealth) weight loss interventions can reduce chronic disease risks, but these are untested in Filipino Americans with T2D. Objective: The objective of this study was to assess feasibility and potential efficacy of a pilot, randomized controlled trial (RCT) of a culturally adapted mHealth weight loss lifestyle intervention (Pilipino Americans Go4Health [PilAm Go4Health]) for overweight Filipino Americans with T2D. Methods: This was a 2-arm pilot RCT of the 3-month PilAm Go4Health intervention (phase 1) with an active waitlist control and 3-month follow-up (phase 2). The waitlist control received the PilAm Go4Health in phase 2, whereas the intervention group transitioned to the 3-month follow-up. PilAm Go4Health incorporated a Fitbit accelerometer, mobile app with diary for health behavior tracking (steps, food/calories, and weight), and social media (Facebook) for virtual social support, including 7 in-person monthly meetings. Filipino American adults ≥18 years with T2D were recruited from Northern California. Feasibility was measured by rates of recruitment, engagement, and retention. Multilevel regression analyses assessed within and between group differences for the secondary outcome of percent weight change and other outcomes of weight (kg), body mass index (BMI), waist circumference, fasting plasma glucose, HbA1c, and steps. Results: A total of 45 Filipino American adults were enrolled and randomized. Mean age was 58 (SD 10) years, 62% (28/45) were women, and mean BMI was 30.1 (SD 4.6). Participant retention and study completion were 100%, with both the intervention and waitlist group achieving near-perfect attendance at all 7 intervention office visits. Groups receiving the PilAm Go4Health in phase 1 (intervention group) and phase 2 (waitlist group) had significantly greater weight loss, −2.6% (−3.9 to −1.4) and −3.3% (−1.8 to −4.8), respectively, compared with the nonintervention group, resulting in a moderate to small effect sizes (d=0.53 and 0.37, respectively). In phase 1, 18% (4/22) of the intervention group achieved a 5% weight loss, whereas 82% (18/22) maintained or lost 2% to 5% of their weight and continued to maintain this weight loss in the 3-month follow-up. Other health outcomes, including waist circumference, BMI, and step counts, improved when each arm received the PilAm Go4Health, but the fasting glucose and HbA1c outcomes were mixed. Conclusions: The PilAm Go4Health was feasible and demonstrated potential efficacy in reducing diabetes risks in overweight Filipino Americans with T2D. This study supports the use of mHealth and other promising intervention strategies to reduce obesity and diabetes risks in Filipino Americans. Further testing in a full-scale RCT is warranted. These findings may support intervention translation to reduce diabetes risks in other at-risk diverse populations. Trial Registration: Clinicaltrials.gov NCT02290184; https://clinicaltrials.gov/ct2/show/NCT02290184 (Archived by WebCite at http://www.webcitation.org/6vDfrvIPp) %M 30291068 %R 10.2196/diabetes.8156 %U http://diabetes.jmir.org/2017/2/e30/ %U https://doi.org/10.2196/diabetes.8156 %U http://www.ncbi.nlm.nih.gov/pubmed/30291068 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 12 %P e183 %T The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial %A Quinn,Charlene C %A Swasey,Krystal K %A Crabbe,J Christopher F %A Shardell,Michelle D %A Terrin,Michael L %A Barr,Erik A %A Gruber-Baldini,Ann L %+ Department of Epidemiology and Public Health, School of Medicine, University of Maryland, 660 W Redwood Street, Howard Hall Suite 200, Baltimore, MD, 21201, United States, 1 410 706 2406, cquinn@som.umaryland.edu %K diabetes distress %K mobile health %K depression %K diabetes %K Diabetes Distress Scale %K Patient Health Questionnaire %K women %K emotional well-being %D 2017 %7 07.12.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes is a complex, demanding disease that requires the constant attention of patients. The burden of self-management, including different medication regimens, routine self-care activities, and provider visits, has an impact on patients’ emotional well-being. Diabetes distress and depression are two important components of emotional well-being that may negatively affect diabetes outcomes. Objective: The aim was to determine the impact of the 1-year Mobile Diabetes Intervention Study cluster randomized clinical trial on emotional well-being measured by diabetes distress and depression among adults with type 2 diabetes (T2D). Methods: A total of 163 adults with not-well-managed T2D were enrolled from community primary care practices. Primary care practices were cluster randomized into either a usual care control group or intervention group. Intervention participants were given a mobile phone with coaching software including a Web portal to communicate with providers. A priori established secondary outcomes included distress measured by the Diabetes Distress Scale (DDS), with subscales measuring emotional burden, interpersonal distress, physician-related distress, and regimen-related distress, as well as depression measured by the Patient Health Questionnaire (PHQ-9). Linear mixed models were used to calculate the effect of the intervention on diabetes distress levels over time, both overall and separately by sex, and to determine if the intervention affected distress or depression. The impact of total DDS on changes in HbA1c was also studied. Results: There were no significant treatment group effects for DDS total (baseline: P=.07; differences over time: P=.38) or for depression (P=.06 over time). Significant declines in total DDS were observed over the 12-month intervention period (P=.01). Regimen-related distress significantly decreased for all study participants (P<.001), but no significant change over time was observed for emotional burden (P=.83), interpersonal distress (P=.64), or physician-related distress (P=.73). Women in both the usual care and intervention groups were more likely to have higher overall DDS, emotional burden, physician-related distress, and regimen-related distress, but not interpersonal distress. Women also reported higher baseline depression compared to men (P=.006). Overall, depression decreased over the treatment period (P=.007), but remained unaffected by group assignment (P=.06) or by sex (P=.97). Diabetes distress had no effect on the change in HbA1c (P=.91) over the treatment period. Conclusions: Although we found no definitive overall or sex-specific effect of the intervention on diabetes distress or depression, this study makes an important contribution to the understanding of mobile health interventions and the impact on emotional health. Our study verified previous work that although diabetes distress and depression are highly correlated, these measures are not evaluating the same construct. Design of future mobile technology provides an opportunity to personalize, contextualize, and intervene in the emotional well-being of persons with diabetes. Trial Registration: Clinicaltrials.gov NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6vVgRCLAF) %M 29217502 %R 10.2196/mhealth.8910 %U http://mhealth.jmir.org/2017/12/e183/ %U https://doi.org/10.2196/mhealth.8910 %U http://www.ncbi.nlm.nih.gov/pubmed/29217502 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 11 %P e179 %T One Drop | Mobile on iPhone and Apple Watch: An Evaluation of HbA1c Improvement Associated With Tracking Self-Care %A Osborn,Chandra Y %A van Ginkel,Joost R %A Marrero,David G %A Rodbard,David %A Huddleston,Brian %A Dachis,Jeff %+ Informed Data Systems Inc, 85 Delancey St, Ste 71, New York, NY, 10002, United States, 1 8604242858, chandra@onedrop.today %K type 1 diabetes %K type 2 diabetes %K mobile health %K mobile phone %K smartwatch %K glycated hemoglobin A1c %K HbA1c %K glycemic control %K self-care behavior %D 2017 %7 29.11.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The One Drop | Mobile app supports manual and passive (via HealthKit and One Drop’s glucose meter) tracking of self-care and glycated hemoglobin A1c (HbA1c). Objective: We assessed the HbA1c change of a sample of people with type 1 diabetes (T1D) or type 2 diabetes (T2D) using the One Drop | Mobile app on iPhone and Apple Watch, and tested relationships between self-care tracking with the app and HbA1c change. Methods: In June 2017, we identified people with diabetes using the One Drop | Mobile app on iPhone and Apple Watch who entered two HbA1c measurements in the app 60 to 365 days apart. We assessed the relationship between using the app and HbA1c change. Results: Users had T1D (n=65) or T2D (n=191), were 22.7% (58/219) female, with diabetes for a mean 8.34 (SD 8.79) years, and tracked a mean 2176.35 (SD 3430.23) self-care activities between HbA1c entries. There was a significant 1.36% or 14.9 mmol/mol HbA1c reduction (F=62.60, P<.001) from the first (8.72%, 71.8 mmol/mol) to second HbA1c (7.36%, 56.9 mmol/mol) measurement. Tracking carbohydrates was independently associated with greater HbA1c improvement (all P<.01). Conclusions: Using One Drop | Mobile on iPhone and Apple Watch may favorably impact glycemic control. %M 29187344 %R 10.2196/mhealth.8781 %U http://mhealth.jmir.org/2017/11/e179/ %U https://doi.org/10.2196/mhealth.8781 %U http://www.ncbi.nlm.nih.gov/pubmed/29187344 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 11 %P e170 %T Diabetes Data Management System to Improve Glycemic Control in People With Type 1 Diabetes: Prospective Cohort Study %A Irace,Concetta %A Schweitzer,Matthias Axel %A Tripolino,Cesare %A Scavelli,Faustina Barbara %A Gnasso,Agostino %+ Metabolic Diseases Unit, Department of Clinical and Experimental Medicine, University of Catanzaro, University Campus, Catanzaro, 88100, Italy, 39 09613697039, gnasso@unicz.it %K diabetes mellitus %K blood glucose self-monitoring %K smartphone %K internet %D 2017 %7 21.11.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Smartphone and Web technology can improve the health care process, especially in chronic diseases. Objective: The aim of this study was to investigate whether the use of blood glucose (BG) data management system, which enables connection to smartphones, the Web, the cloud, and downloading, can improve glycemic control in subjects with type 1 diabetes mellitus (T1DM). Methods: This study was a prospective, single-arm, cohort feasibility study with 6 months of duration. T1DM subjects enrolled had experience in self-monitoring blood glucose, but were download data naïve. Fasting BG and glycated hemoglobin (HbA1c) were collected at the enrollment and at follow-up. Subjects were divided into Downloader (DL) and No-downloader (NDL). Results: A total of 63 subjects were analyzed, of which 30 were classified as DL and 33 as NDL. At the end of the study, DL had significantly lower HbA1c, mean daily glucose, standard deviation, percentage of BG values above target, and pre- and postprandial (lunch and dinner) values compared with NDL (all P<.05). The percentage of BG values within treatment target was significantly higher in DL compared with NDL (47% [SD 9] vs 37% [SD 13]; P=.001). Conclusions: The findings suggest that, in T1DM, downloading of BG from data management system, which enables connection to smartphones, the Web, and the cloud, might be a valuable contributor to improved glycemic control. %M 29162560 %R 10.2196/mhealth.8532 %U http://mhealth.jmir.org/2017/11/e170/ %U https://doi.org/10.2196/mhealth.8532 %U http://www.ncbi.nlm.nih.gov/pubmed/29162560 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 10 %P e124 %T Designing a Self-Management App for Young People With Type 1 Diabetes: Methodological Challenges, Experiences, and Recommendations %A Castensøe-Seidenfaden,Pernille %A Reventlov Husted,Gitte %A Teilmann,Grete %A Hommel,Eva %A Olsen,Birthe Susanne %A Kensing,Finn %+ Pediatric and Adolescent Department, Nordsjællands Hospital, Hillerød, University of Copenhagen, Dyrehavevej 29, 1521, Hillerød, 3400, Denmark, 45 29824322, pernille.castensoee-seidenfaden@regionh.dk %K adolescents %K mHealth %K diabetes %K chronic condition %K self-management %K transition %K participatory design %K usability %K feasibility %K methodological recommendations %D 2017 %7 23.10.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Young people with type 1 diabetes often struggle to self-manage their disease. Mobile health (mHealth) apps show promise in supporting self-management of chronic conditions such as type 1 diabetes. Many health care providers become involved in app development. Unfortunately, limited information is available to guide their selection of appropriate methods, techniques, and tools for a participatory design (PD) project in health care. Objective: The aim of our study was to develop an mHealth app to support young people in self-managing type 1 diabetes. This paper presents our methodological recommendations based on experiences and reflections from a 2-year research study. Methods: A mixed methods design was used to identify user needs before designing the app and testing it in a randomized controlled trial. App design was based on qualitative, explorative, interventional, and experimental activities within an overall iterative PD approach. Several techniques and tools were used, including workshops, a mail panel, think-aloud tests, and a feasibility study. Results: The final mHealth solution was “Young with Diabetes” (YWD). The iterative PD approach supported researchers and designers in understanding the needs of end users (ie, young people, parents, and health care providers) and their assessment of YWD, as well as how to improve app usability and feasibility. It is critical to include all end user groups during all phases of a PD project and to establish a multidisciplinary team to provide the wide range of expertise required to build a usable and useful mHealth app. Conclusions: Future research is needed to develop and evaluate more efficient PD techniques. Health care providers need guidance on what tools and techniques to choose for which subgroups of users and guidance on how to introduce an app to colleagues to successfully implement an mHealth app in health care organizations. These steps are important for anyone who wants to design an mHealth app for any illness. %M 29061552 %R 10.2196/mhealth.8137 %U http://mhealth.jmir.org/2017/10/e124/ %U https://doi.org/10.2196/mhealth.8137 %U http://www.ncbi.nlm.nih.gov/pubmed/29061552 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 10 %P e158 %T Guidelines and mHealth to Improve Quality of Hypertension and Type 2 Diabetes Care for Vulnerable Populations in Lebanon: Longitudinal Cohort Study %A Doocy,Shannon %A Paik,Kenneth E %A Lyles,Emily %A Hei Tam,Hok %A Fahed,Zeina %A Winkler,Eric %A Kontunen,Kaisa %A Mkanna,Abdalla %A Burnham,Gilbert %+ Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, United States, 1 4105022628, doocy1@jhu.edu %K mHealth %K hypertension %K diabetes mellitus %K chronic disease %K Lebanon, Syria %K refugees %D 2017 %7 18.10.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Given the protracted nature of the crisis in Syria, the large noncommunicable disease (NCD) caseload of Syrian refugees and host Lebanese, and the high costs of providing NCD care, the implications for Lebanon’s health system are vast. Objective: The aim of this study was to evaluate the effectiveness of treatment guidelines and a mobile health (mHealth) app on quality of care and health outcomes in primary care settings in Lebanon. Methods: A longitudinal cohort study was implemented from January 2015 to August 2016 to evaluate the effectiveness of treatment guidelines and an mHealth app on quality of care and health outcomes for Syrian and Lebanese patients in Lebanese primary health care (PHC) facilities. Results: Compared with baseline record extraction, recording of blood pressure (BP) readings (−11.4%, P<.001) and blood sugar measurements (−6.9%, P=.03) significantly decreased following the implementation of treatment guidelines. Recording of BP readings also decreased after the mHealth phase as compared with baseline (−8.4%, P=.001); however, recording of body mass index (BMI) reporting increased at the end of the mHealth phase from baseline (8.1%, P<.001) and the guidelines phase (7.7%, P<.001). There were a great proportion of patients for whom blood sugar, BP, weight, height, and BMI were recorded using the tablet compared with in paper records; however, only differences in BMI were statistically significant (31.6% higher in app data as compared with paper records; P<.001). Data extracted from the mHealth app showed that a higher proportion of providers offered lifestyle counseling compared with the counseling reported in patients’ paper records (health diet counseling; 77.3% in app data vs 8.8% in paper records, P<.001 and physical activity counseling and 59.7% in app vs 7.1% in paper records, P<.001). There were statistically significant increases in all four measures of patient-provider interaction across study phases. Provider inquiry of medical history increased by 16.6% from baseline following guideline implementation and by 28.2% from baseline to mHealth implementation (P<.001). From baseline, patient report of provider inquiry regarding medication complications increased in the guidelines and mHealth phases by 12.9% and 59.6%, respectively, (P<.001). The proportion of patients reporting that providers asked other questions relevant to their illness increased from baseline through guidelines implementation by 27.8% and to mHealth implementation by 66.3% (P<.001). Follow-up scheduling increased from baseline to the guidelines phase by 20.6% and the mHealth phase by 39.8% (P<.001). Conclusions: Results from this study of an mHealth app in 10 PHC facilities in Lebanon indicate that the app has potential to improve adherence to guidelines and quality of care. Further studies are necessary to determine the effects of patient-controlled health record apps on provider adherence to treatment guidelines, as well as patients’ long-term medication and treatment adherence and disease control. %M 29046266 %R 10.2196/mhealth.7745 %U http://mhealth.jmir.org/2017/10/e158/ %U https://doi.org/10.2196/mhealth.7745 %U http://www.ncbi.nlm.nih.gov/pubmed/29046266 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e25 %T Functionality, Implementation, Impact, and the Role of Health Literacy in Mobile Phone Apps for Gestational Diabetes: Scoping Review %A Chen,Qiong %A Carbone,Elena T %+ Department of Nutrition, School of Public Health and Health Sciences, University of Massachusetts/Amherst, Chenoweth Laboratory, 100 Holdsworth Way, Amherst, MA, 01003-9282, United States, 1 413 545 1071, ecarbone@nutrition.umass.edu %K gestational diabetes %K mobile app %K health literacy %K smartphone %K scoping review %D 2017 %7 04.10.2017 %9 Review %J JMIR Diabetes %G English %X Background: The increasing ownership of mobile phones and advances in hardware and software position these devices as cost-effective personalized tools for health promotion and management among women with gestational diabetes mellitus (GDM). Numerous mobile phone apps are available online; however, to our knowledge, no review has documented how these apps are developed and evaluated in relation to GDM. Objective: The objective of our review was to answer the following 2 research questions: (1) What is known from the existing literature about the availability, functionality, and effectiveness of mobile phone apps on GDM prevention and management? (2) What is the role of health literacy in these apps? Methods: We searched 7 relevant electronic databases for original research documents using terms related to mobile phone apps, GDM, and health literacy. We thematically categorized selected articles using a framework adapted from Arksey and O’Malley. Results: We included 12 articles related to 7 apps or systems in the final analysis. We classified articles around 2 themes: (1) description of the development, feasibility, or usability of the apps or systems, and (2) trial protocols. The degree of personalization varied among the apps for GDM, and decision support systems can be used to generate time-efficient personalized feedback for both patients and health care providers. Health literacy was considered during the development or measured as an outcome by some apps. Conclusions: There is a limited body of research on mobile phone apps in relation to GDM prevention and management. Mobile phone apps can provide time- and cost-efficient personalized interventions for GDM. Several randomized controlled trials have been launched recently to evaluate the effectiveness of the apps. Consideration of health literacy should be improved when developing features of the apps. %M 30291088 %R 10.2196/diabetes.8045 %U http://diabetes.jmir.org/2017/2/e25/ %U https://doi.org/10.2196/diabetes.8045 %U http://www.ncbi.nlm.nih.gov/pubmed/30291088 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 4 %N 4 %P e24 %T Lack of Adoption of a Mobile App to Support Patient Self-Management of Diabetes and Hypertension in a Federally Qualified Health Center: Interview Analysis of Staff and Patients in a Failed Randomized Trial %A Thies,Kathleen %A Anderson,Daren %A Cramer,Benjamin %+ Community Health Center, Inc., Weitzman Institute, 631 Main St, Middletown, CT, 06457, United States, 1 603 661 9113, thiesk@chc1.com %K telehealth %K mobile health %K mHealth %K underserved patients %K HIT %K usability %D 2017 %7 03.10.2017 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Thousands of mobile health (mHealth) apps have been developed to support patients’ management of their health, but the effectiveness of many of the apps remains unclear. While mHealth apps appear to hold promise for improving the self-management of chronic conditions across populations, failure to balance the system demands of the app with the needs, interests, or resources of the end users can undermine consumers’ adoption of these technologies. Objective: The original aim of this study was to evaluate the effectiveness of a commercial mHealth app in improving clinical outcomes for adult patients in a Federally Qualified Health Center (FQHC) with uncontrolled diabetes and/or hypertension. Patients entered clinical data into the app, which also supported messaging between patients and providers. After a 4-month period of vigorous recruitment, the trial was suspended due to low enrollment and inconsistent use of the app by enrolled patients. The project aim was changed to understanding why the trial was unsuccessful. Methods: We used the user-task-context (eUTC) usability framework to develop a set of interview questions for patients and staff who were involved in the trial. All interviews were done by phone and lasted 20 to 30 minutes. Interviews were not recorded. Results: There was a poor fit between the app, end users, and recruitment and treatment approaches in our setting. Usability testing might have revealed this prior to launch but was not an option. There was not sufficient time during routine care for clinical staff to familiarize patients with the app or to check clinical data and messages, which are unreimbursed activities. Some patients did not use the app appropriately. The lack of integration with the electronic health record (EHR) was cited as a problem for both patients and staff who also said the app was just one more thing to attend to. Conclusions: This brief trial underscores the pitfalls in the utilization of mHealth apps. Effective use of mHealth tools requires a good fit between the app, the users’ electronic health (eHealth) literacy, the treatment approach, staff time, and reimbursement for services. The last 3 are contextual factors of the setting that affected the adoption of the app and context is an important factor in implementation science. We recommend that researchers address contextual factors in the trial and adoption of mHealth technologies. %M 28974481 %R 10.2196/humanfactors.7709 %U https://humanfactors.jmir.org/2017/4/e24/ %U https://doi.org/10.2196/humanfactors.7709 %U http://www.ncbi.nlm.nih.gov/pubmed/28974481 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e22 %T Views of Patients on Using mHealth to Monitor and Prevent Diabetic Foot Ulcers: Qualitative Study %A Boodoo,Chris %A Perry,Julie Ann %A Hunter,Paul John %A Duta,Dragos Ioan %A Newhook,Samuel Carl Paul %A Leung,General %A Cross,Karen %+ Department of Medical Imaging, St Michael’s Hospital, 30 Bond Street, Toronto, ON,, Canada, 1 416 864 6060 ext 2871, LeungGe@smh.ca %K mHealth %K telemedicine %K diabetic foot ulcer %K diabetes %K qualitative research %D 2017 %7 15.09.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: People with diabetes are at risk for diabetic foot ulcers (DFUs), which can lead to limb loss and a significant decrease in quality of life. Evidence suggests that mHealth can be an effective tool in diabetes self-management. mHealth presents an opportunity for the prevention and monitoring of DFUs. However, there is a paucity of research that explores its effectiveness in the DFU patient population, as well as the views and attitudes of these patients toward technology and mHealth. Objective: This study aimed to explore the views, attitudes, and experiences of a diabetic patient population with or at risk of DFUs regarding technology, mHealth, and the diabetic foot. Methods: We used a qualitative research approach using in-depth interviews with 8 patients with DFUs. Questions were structured around experience with technology, current health practices related to diabetic foot care, and thoughts on using an mHealth device that prevents and monitors DFUs. We transcribed and thematically analyzed all interviews. Results: All patients had positive responses for an mHealth intervention aimed at preventing and monitoring DFUs. We found 4 themes in the data: diversity in use of technology, feet-checking habits, 2-way communication with health care professionals (HCPs), and functionality. There were varying levels of familiarity with and dependence on technology within this patient population. These relationships correlated with distinct generations found in North America, including baby boomers and Generation X. Furthermore, we found that most patients performed daily feet checks to monitor any changes in health. However, some did not perform feet checks prior to the development of a DFU. Patients expressed interest in 2-way communication with HCPs that would allow for easier appointment scheduling, sharing of medical data, decreased number of visits, and use of alerts for when medical attention is required. Patients also identified conditions of functionality for the mHealth intervention. These included consideration of debilitating complications because of diabetes, such as retinopathy and decreased mobility; ease of use of the intervention; and implementation of virtual communities to support continued use of the intervention. Conclusions: Our patient population expressed an interest in mHealth for preventing and monitoring DFUs, although some participants were not frequent users of technology. mHealth continues to show potential in improving patient outcomes, and this study provides a foundation for designing interventions specific to a DFU population. Further research is needed to confirm these findings. %M 30291089 %R 10.2196/diabetes.8505 %U http://diabetes.jmir.org/2017/2/e22/ %U https://doi.org/10.2196/diabetes.8505 %U http://www.ncbi.nlm.nih.gov/pubmed/30291089 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e21 %T One Drop | Mobile: An Evaluation of Hemoglobin A1c Improvement Linked to App Engagement %A Osborn,Chandra Y %A van Ginkel,Joost R %A Rodbard,David %A Heyman,Mark %A Marrero,David G %A Huddleston,Brian %A Dachis,Jeff %+ Informed Data Systems, Inc, 85 Delancey Street, Suite 71, New York, NY,, United States, 1 860 424 2858, chandra@onedrop.today %K type 1 diabetes %K type 2 diabetes %K mobile app %K tracking %K self-care %K glycemic control %D 2017 %7 24.08.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Three recent reviews evaluated 19 studies testing the hemoglobin A1c (HbA1c) benefit of 16 diabetes apps, including 5 publicly available apps. Most studies relied on small samples and did not link app engagement with outcomes. Objective: This study assessed both HbA1c change in a large sample of people using the One Drop | Mobile app and associations between app engagement and changes in HbA1c. Methods: The One Drop | Mobile app for iOS and Android is designed to manually and passively (via Apple HealthKit, Google Fit, and the One Drop | Chrome blood glucose meter) store, track, and share data. Users can schedule medication reminders, view statistics, set goals, track health outcomes, and get data-driven insights. In June 2017, we queried data on people with diabetes using the app who had entered at least 2 HbA1c values in the app >60 and ≤365 days apart. Multiple imputation corrected for missing data. Unadjusted and adjusted mixed effects repeated measures models tested mean HbA1c change by time, diabetes type, and their interaction. Multiple regression models assessed relationships between using the app to track food, activity, blood glucose, and medications and HbA1c change. Results: The sample (N=1288) included people with type 1 diabetes (T1D) (n=367) or type 2 diabetes (T2D) (n=921) who were 35% female, diagnosed with diabetes for a mean 9.4 (SD 9.9) years, and tracked an average 1646.1 (SD 3621.9) self-care activities in One Drop | Mobile between their first (mean 8.14% [SD 2.06%]) and second HbA1c entry (mean 6.98% [SD 1.1%]). HbA1c values were significantly associated with user-entered average blood glucose 90 days before the second HbA1c entry (rho=.73 to .75, P<.001). HbA1c decreased by an absolute 1.07% (unadjusted and adjusted F=292.03, P<.001) from first to second HbA1c entry. There was a significant interaction between diabetes type and HbA1c. Both groups significantly improved, but users with T2D had a greater HbA1c decrease over time than users with T1D (F=10.54, P<.001). For users with T2D (n=921), HbA1c decreased by an absolute 1.27% (F=364.50, P<.001) from first to second HbA1c entry. Finally, using One Drop | Mobile to record food was associated with greater HbA1c reductions even after adjusting for covariates and after also adjusting for insulin use for users with T2D (all P<.05). Conclusions: People with T1D and T2D reported a 1.07% to 1.27% absolute reduction in HbA1c during a median 4 months of using the One Drop | Mobile app. Using the app to track self-care was associated with improved HbA1c. More research is needed on the health benefits of publicly available diabetes apps, particularly studies associating app engagement with short- and long-term effects. %M 30291059 %R 10.2196/diabetes.8039 %U http://diabetes.jmir.org/2017/2/e21/ %U https://doi.org/10.2196/diabetes.8039 %U http://www.ncbi.nlm.nih.gov/pubmed/30291059 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e19 %T Diabetes App-Related Text Messages From Health Care Professionals in Conjunction With a New Wireless Glucose Meter With a Color Range Indicator Improves Glycemic Control in Patients With Type 1 and Type 2 Diabetes: Randomized Controlled Trial %A Grady,Mike %A Katz,Laurence Barry %A Cameron,Hilary %A Levy,Brian Leonard %+ LifeScan Scotland Ltd, Beechwood Park North, Inverness, IV2 5DL, United Kingdom, 44 01463 ext 721889, mgrady@its.jnj.com %K diabetes app %K text message %K color range indicator %K blood glucose monitor, wireless %D 2017 %7 07.08.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Mobile diabetes apps enable health care professionals (HCPs) to monitor patient progress, offer remote consultations, and allow more effective and informed treatment decisions between patients and HCPs. The OneTouch Reveal app aggregates data from a blood glucose meter and provides analytics to help patients and HCPs visualize glycemic trends and patterns, enabling more informed treatment and lifestyle decisions. The app also allows patients and HCPs to keep connected by exchanging text messages (short message service [SMS]) or progress reports via email. Objective: The primary objective of our study was to assess changes in glycemic control and overall experiences of patients and HCPs using the app in conjunction with the wireless OneTouch Verio Flex blood glucose meter. Methods: We randomly assigned 137 adults with type 1 (T1DM) or type 2 diabetes mellitus (T2DM) and a glycated hemoglobin (HbA1c) level of ≥7.5% and ≤11.0% to use the glucose meter alone or glucose meter plus the app for 24 weeks. The meter + app group were scheduled to receive diabetes-related text messages from their HCP every 2 weeks (total of 12 texts). Clinical measures and self-reported outcomes were assessed during face-to-face clinic visits between the participant and a diabetes nurse at baseline, week 12, and week 24. Results: In 128 completed participants, HbA1c decreased after 12 and 24 weeks in both the meter-only (n=66) (0.56% and 0.55%, respectively) and meter + app groups (n=62) (0.78% and 0.67%, respectively) compared with baseline (each P<.001). The difference in HbA1c reduction between the 2 groups was not statistically significant at 12 or 24 weeks (P=.12 and P=.45, respectively). However, the decrease in HbA1c was greater in T2DM participants using the meter + app after 12 weeks (1.04%) than in T2DM participants using the meter alone (0.58%; P=.09). In addition, decrease in HbA1c in participants using the meter + app who received at least 10 diabetes-related text messages (1.05%) was significantly greater than in meter-only participants (P<.01). Conclusions: Use of the OneTouch Verio Flex glucose meter alone or in combination with the OneTouch Reveal diabetes app was associated with significant improvements in glycemic control after 12 and 24 weeks. Improvements using the app were greatest in participants with T2DM and those participants who received the highest number of HCP text messages. This study suggests that real-time availability of patient data and the ability to send personalized diabetes-related text messages can assist HCPs to improve glycemic control in patients between scheduled visits. Trial Registration: Clinicaltrials.gov NCT02429024; https://clinicaltrials.gov/ct2/show/NCT02429024 (Archived by WebCite at http://www.webcitation.org/6sCTDRa1l) %M 30291092 %R 10.2196/diabetes.7454 %U http://diabetes.jmir.org/2017/2/e19/ %U https://doi.org/10.2196/diabetes.7454 %U http://www.ncbi.nlm.nih.gov/pubmed/30291092 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 2 %P e12 %T iOS Appstore-Based Phone Apps for Diabetes Management: Potential for Use in Medication Adherence %A Martinez,Mark %A Park,Su Bin %A Maison,Isaac %A Mody,Vicky %A Soh,Lewis Sungkon %A Parihar,Harish Singh %+ Philadelphia College of Osteopathic Medicine - GA campus, School of Pharmacy, 625 Old Peachtree Rd NW, School of Pharmacy, Suwanee, GA, 30024, United States, 1 6784077350, harishpa@pcom.edu %K diabetes %K telemedicine %K blood glucose self-monitoring glucose monitoring %K mobile applications %K self-care %K mobile health %D 2017 %7 11.07.2017 %9 Case Report %J JMIR Diabetes %G English %X Background: Currently, various phone apps have been developed to assist patients. Many of these apps are developed to assist patients in the self-management of chronic diseases such as diabetes. It is essential to analyze these various apps to understand the key features that would potentially be instrumental in helping patients successfully achieve goals in disease self-management. Objective: The objective of this study was to conduct a review of all the available diabetes-related apps in the iOS App Store to evaluate which diabetic app is more interactive and offers a wide variety of operations such as monitoring glucose, water, carbohydrate intake, weight, body mass index (BMI), medication, blood pressure (BP) levels, reminders or push notifications, food database, charts, exercise management, email, sync between devices, syncing data directly to the prescribers, and other miscellaneous functions such as (Twitter integration, password protection, retina display, barcode scanner, apple watch functionality, and cloud syncing). Methods: Data was gathered using the iOS App Store on an iPad. The search term “diabetes” resulted in 1209 results. Many of the results obtained were remotely related to diabetes and focused mainly on diet, exercise, emergency services, refill reminders, providing general diabetes information, and other nontherapeutic options. We reviewed each app description and only included apps that were meant for tracking blood glucose levels. All data were obtained in one sitting by one person on the same device, as we found that carrying out the search at different times or on different devices (iPhones) resulted in varying results. Apps that did not have a feature for tracking glucose levels were excluded from the study. Results: The search resulted in 1209 results; 85 apps were retained based on the inclusion criteria mentioned above. All the apps were reviewed for average customer ratings, number of reviews, price, and functions. Of all the apps surveyed, 18 apps with the highest number of user ratings were used for in-depth analysis. Of these 18 apps, 50% (9/18) also had a medication adherence function. Our analysis revealed that the Diabetes logbook used by the mySugr app was one of the best; it differentiated itself by introducing fun as a method of increasing adherence. Conclusions: A large variation was seen in patient ratings of app features. Many patient reviewers desired simplicity of app functions. Glucose level tracking and email features potentially helped patients and health care providers manage the disease more efficiently. However, none of the apps could sync data directly to the prescribers. Additional features such as graph customization, availability of data backup, and recording previous entries were also requested by many users. Thus, the use of apps in disease management and patient and health-care provider involvement in future app refinement and development should be encouraged. %M 30291096 %R 10.2196/diabetes.6468 %U http://diabetes.jmir.org/2017/2/e12/ %U https://doi.org/10.2196/diabetes.6468 %U http://www.ncbi.nlm.nih.gov/pubmed/30291096 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 6 %P e85 %T Use of and Beliefs About Mobile Phone Apps for Diabetes Self-Management: Surveys of People in a Hospital Diabetes Clinic and Diabetes Health Professionals in New Zealand %A Boyle,Leah %A Grainger,Rebecca %A Hall,Rosemary M %A Krebs,Jeremy D %+ Department of Medicine, University of Otago Wellington, Department of Medicine, 23A Mein St, PO Box 7343, Wellington, 6242, New Zealand, 64 43855541, Jeremy.Krebs@ccdhb.org.nz %K mHealth, mobile applications %K telemedicine %K diabetes mellitus %D 2017 %7 30.06.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: People with diabetes mellitus (DM) are using mobile phone apps to support self-management. The numerous apps available to assist with diabetes management have a variety of functions. Some functions, like insulin dose calculators, have significant potential for harm. Objectives: The study aimed to establish (1) whether people with DM in Wellington, New Zealand, use apps for DM self-management and evaluate desirable features of apps and (2) whether health professionals (HPs) in New Zealand treating people with DM recommend apps to patients, the features HPs regard as important, and their confidence with recommending apps. Methods: A survey of patients seen at a hospital diabetes clinic over 12 months (N=539) assessed current app use and desirable features. A second survey of HPs attending a diabetes conference (n=286) assessed their confidence with app recommendations and perceived usefulness. Results: Of the 189 responders (35.0% response rate) to the patient survey, 19.6% (37/189) had used a diabetes app. App users were younger and in comparison to other forms of diabetes mellitus, users prominently had type 1 DM. The most favored feature of the app users was a glucose diary (87%, 32/37), and an insulin calculator was the most desirable function for a future app (46%, 17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.4%, 98/152). Of the 115 responders (40.2% response rate) to the HPs survey, 60.1% (68/113) had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps. Conclusions: The use of apps to record blood glucose was the most favored function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers). %M 28666975 %R 10.2196/mhealth.7263 %U http://mhealth.jmir.org/2017/6/e85/ %U https://doi.org/10.2196/mhealth.7263 %U http://www.ncbi.nlm.nih.gov/pubmed/28666975 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 1 %P e13 %T Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material %A Chen,Xuewei %A Acosta,Sandra %A Barry,Adam E %+ Transdisciplinary Center for Health Equity Research, Department of Health and Kinesiology, Texas A&M University, Blocker 311B, 4243 TAMU, College Station, TX, 77843, United States, 1 979 676 0758, xueweichen@tamu.edu %K health literacy %K health education %K health communication %K language translation %K diabetes %K machine translation %K mobile translation app %K human interpreter %K translator %D 2017 %7 29.06.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Diabetes is a major health crisis for Hispanics and Asian Americans. Moreover, Spanish and Chinese speakers are more likely to have limited English proficiency in the United States. One potential tool for facilitating language communication between diabetes patients and health care providers is technology, specifically mobile phones. Objective: Previous studies have assessed machine translation quality using only writing inputs. To bridge such a research gap, we conducted a pilot study to evaluate the quality of a mobile language translation app (iTranslate) with a voice recognition feature for translating diabetes patient education material. Methods: The pamphlet, “You are the heart of your family…take care of it,” is a health education sheet for diabetes patients that outlines three recommended questions for patients to ask their clinicians. Two professional translators translated the original English sentences into Spanish and Chinese. We recruited six certified medical translators (three Spanish and three Chinese) to conduct blinded evaluations of the following versions: (1) sentences interpreted by iTranslate, and (2) sentences interpreted by the professional human translators. Evaluators rated the sentences (ranging from 1-5) on four scales: Fluency, Adequacy, Meaning, and Severity. We performed descriptive analyses to examine the differences between these two versions. Results: Cronbach alpha values exhibited high degrees of agreement on the rating outcomes of both evaluator groups: .920 for the Spanish raters and .971 for the Chinese raters. The readability scores generated using MS Word’s Flesch-Kincaid Grade Level for these sentences were 0.0, 1.0, and 7.1. We found iTranslate generally provided translation accuracy comparable to human translators on simple sentences. However, iTranslate made more errors when translating difficult sentences. Conclusions: Although the evidence from our study supports iTranslate’s potential for supplementing professional human translators, further evidence is needed. For this reason, mobile language translation apps should be used with caution. %M 30291084 %R 10.2196/diabetes.7446 %U http://diabetes.jmir.org/2017/1/e13/ %U https://doi.org/10.2196/diabetes.7446 %U http://www.ncbi.nlm.nih.gov/pubmed/30291084 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 6 %P e227 %T Tailored Communication Within Mobile Apps for Diabetes Self-Management: A Systematic Review %A Holmen,Heidi %A Wahl,Astrid Klopstad %A Cvancarova Småstuen,Milada %A Ribu,Lis %+ Department of Nursing and Health Promotion, Faculty of Health Sciences, Oslo and Akershus University College of Applied Sciences, PB. 4, St. Olavs plass, Oslo,, Norway, 47 67 23 62 41, heidi.holmen@hioa.no %K diabetes mellitus (MeSH) %K communication (MeSH) %K mobile apps %K self-management %K systematic review %K mHealth %D 2017 %7 23.06.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: The prevalence of diabetes is increasing and with the requirements for self-management and risk of late complications, it remains a challenge for the individual and society. Patients can benefit from support from health care personnel in their self-management, and the traditional communication between patients and health care personnel is changing. Smartphones and apps offer a unique platform for communication, but apps with integrated health care personnel communication based on patient data are yet to be investigated to provide evidence of possible effects. Objective: Our goal was to systematically review studies that aimed to evaluate integrated communication within mobile apps for tailored feedback between patients with diabetes and health care personnel in terms of (1) study characteristics, (2) functions, (3) study outcomes, (4) effects, and (5) methodological quality. Methods: A systematic literature search was conducted following our International Prospective Register of Systematic Reviews (PROSPERO) protocol, searching for apps with integrated communication for persons with diabetes tested in a controlled trial in the period 2008 to 2016. We searched the databases PubMed, Medical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Central, Excerpta Medica database (EMBASE), ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform. The search was closed in September 2016. Reference lists of primary articles and review papers were assessed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and we applied the Cochrane risk of bias tool to assess methodological quality. Results: We identified 2822 citations and after duplicate removal, we assessed 1128 citations. A total of 6 papers were included in this systematic review, reporting on data from 431 persons participating in small trials of short duration. The integrated communication features were mostly individualized as written non–real-time feedback. The number of functions varied from 2 to 9, and blood glucose tracking was the most common. HbA1c was the most common primary outcome, but the remaining reported outcomes were not standardized and comparable. Because of both the heterogeneity of the included trials and the poor methodological quality of the studies, a meta-analysis was not possible. A statistically significant improvement in the primary measure of outcome was found in 3 of the 6 included studies, of which 2 were HbA1c and 1 was mean daytime ambulatory blood pressure. Participants in the included trials reported positive usability or feasibility postintervention in 5 out of 6 trials. The overall methodological quality of the trials was, however, scored as an uncertain risk of bias. Conclusions: This systematic review highlights the need for more trials of higher methodological quality. Few studies offer an integrated function for communication and feedback from health care personnel, and the research field represents an area of heterogeneity with few studies of highly rigorous methodological quality. This, in combination with a low number of participants and a short follow-up, is making it difficult to provide reliable evidence of effects for stakeholders. %M 28645890 %R 10.2196/jmir.7045 %U http://www.jmir.org/2017/6/e227/ %U https://doi.org/10.2196/jmir.7045 %U http://www.ncbi.nlm.nih.gov/pubmed/28645890 %0 Journal Article %I %V %N %P %T %D %7 .. %9 %J %G English %X %U %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 5 %P e75 %T Incorporation of a Stress Reducing Mobile App in the Care of Patients With Type 2 Diabetes: A Prospective Study %A Munster-Segev,Maya %A Fuerst,Oren %A Kaplan,Steven A %A Cahn,Avivit %+ Diabetes Unit, Department of Internal Medicine, Hadassah Hebrew University Hospital, PO Box 12000, Jerusalem, 91120, Israel, 972 26778021, avivit@hadassah.org.il %K diabetes mellitus, type 2 %K biofeedback %K physiological stress response %K mobile health %K telemedicine %D 2017 %7 29.05.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Severe and sustained emotional stress creates a physiological burden through increased sympathetic activity and higher energy demand. This may lead to increased oxidative stress and development of the metabolic syndrome. Emotional stress has been shown to contribute to the onset, progression, and control of type 2 diabetes (T2D). Stress management and biofeedback assisted relaxation have been shown to improve glycemic control. Use of a mobile app for stress management may enhance the scalability of such an approach. Objective: The aim of this study was to assess the effect of using a mobile app of biofeedback-assisted relaxation on weight, blood pressure (BP), and glycemic measures of patients with T2D. Methods: Adult patients with T2D and inadequate glycemic control (hemoglobin A1c [HbA1c]>7.5%) were recruited from the outpatient diabetes clinic. Baseline weight, BP, HbA1c, fasting plasma glucose (FPG), triglycerides (TG), and 7-point self-monitoring of blood glucose were measured. Patients were provided with a stress reducing biofeedback mobile app and instructed to use it 3 times a day. The mobile app—Serenita—is an interactive relaxation app based on acquiring a photoplethysmography signal from the mobile phone’s camera lens, where the user places his finger. The app collects information regarding the user’s blood flow, heart rate, and heart rate variability and provides real-time feedback and individualized breathing instructions in order to modulate the stress level. All clinical and biochemical measures were repeated at 8 and 16 weeks of the study. The primary outcome was changes in measures at 8 weeks. Results: Seven patients completed 8 weeks of the study and 4 completed 16 weeks. At week 8, weight dropped by an average of 4.0 Kg (SD 4.3), systolic BP by 8.6 mmHg (SD 18.6), HbA1c by 1.3% (SD 1.6), FPG by 4.3 mmol/l (4.2), and serum TG were unchanged. Conclusions: Stress reduction using a mobile app based on biofeedback may improve glycemic control, weight, and BP. %M 28554881 %R 10.2196/mhealth.7408 %U http://mhealth.jmir.org/2017/5/e75/ %U https://doi.org/10.2196/mhealth.7408 %U http://www.ncbi.nlm.nih.gov/pubmed/28554881 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 5 %P e69 %T Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review %A Kim,Ben YB %A Lee,Joon %+ Health Data Science Lab, School of Public Health and Health Systems, University of Waterloo, Lyle Hallman North, 3rd Floor, 200 University Avenue W, Waterloo, ON, N2L 3G1, Canada, 1 519 888 4567 ext 31567, joon.lee@uwaterloo.ca %K mobile health %K mHealth %K smartphone %K mobile phone %K tablet %K older adults %K seniors %K chronic disease %K chronic disease management %K scoping review %D 2017 %7 23.05.2017 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions. Objective: We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions. Methods: We used the Arksey and O’Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model. Results: A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers. Conclusions: Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies. %M 28536089 %R 10.2196/mhealth.7141 %U http://mhealth.jmir.org/2017/5/e69/ %U https://doi.org/10.2196/mhealth.7141 %U http://www.ncbi.nlm.nih.gov/pubmed/28536089 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 4 %P e54 %T Designing Patient-Centered Text Messaging Interventions for Increasing Physical Activity Among Participants With Type 2 Diabetes: Qualitative Results From the Text to Move Intervention %A Horner,Gabrielle N %A Agboola,Stephen %A Jethwani,Kamal %A Tan-McGrory,Aswita %A Lopez,Lenny %+ Division of Hospital Medicine, University of California San Francisco, 4150 Clement St, 1A-69, San Francisco, CA, 94121, United States, 1 6176276600, lenny.lopez@ucsf.edu %K diabetes mellitus, type 2 %K text messaging %K exercise %K qualitative research %D 2017 %7 24.04.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Type 2 diabetes mellitus (T2DM) is a disease affecting approximately 29.1 million people in the United States, and an additional 86 million adults have prediabetes. Diabetes self-management education, a complex health intervention composed of 7 behaviors, is effective at improving self-care behaviors and glycemic control. Studies have employed text messages for education, reminders, and motivational messaging that can serve as “cues to action,” aiming to improve glucose monitoring, self-care behaviors, appointment attendance, and medication adherence. Objectives: The Text to Move (TTM) study was a 6-month 2-parallel group randomized controlled trial of individuals with T2DM to increase physical activity, measured by a pedometer. The intervention arm received text messages twice daily for 6 months that were tailored to the participant’s stage of behavior change as defined by the transtheoretical model of behavior change. Methods: We assessed participants’ attitudes regarding their experience with text messaging, focusing on perceived barriers and facilitators, through two focus groups and telephone interviews. All interviews were audiorecorded, transcribed verbatim, coded, and analyzed using a grounded theory approach. Results: The response rate was 67% (31/46 participants). The average age was 51.4 years and 61% (19/31 participants) were male. The majority of individuals were English speakers and married, had completed at least 12th grade and approximately half of the participants were employed full-time. Overall, participants were satisfied with the TTM program and recalled the text messages as educational, informational, and motivational. Program involvement increased the sense of connection with their health care center. The wearing of pedometers and daily step count information served as motivational reminders and created a sense of accountability through the sentinel effect. However, there was frustration concerning the automation of the text message program, including the repetitiveness, predictability of text time delivery, and lack of customization and interactivity of text message content. Participants recommended personalization of texting frequency as well as more contact time with personnel for a stronger sense of support, including greater surveillance and feedback based on their own results and comparison to other participants. Conclusions: Participants in a theory-based text messaging intervention identified key facilitators and barriers to program efficacy that should be incorporated into future texting interventions to optimize participant satisfaction and outcomes. Trial Registration: Clinicaltrials.gov NCT01569243; http://clinicaltrials.gov/ct2/show/NCT01569243 (Archived by Webcite at http://www.webcitation.org/6pfH6yXag) %M 28438728 %R 10.2196/mhealth.6666 %U http://mhealth.jmir.org/2017/4/e54/ %U https://doi.org/10.2196/mhealth.6666 %U http://www.ncbi.nlm.nih.gov/pubmed/28438728 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 4 %P e53 %T Developing a Patient-Centered mHealth App: A Tool for Adolescents With Type 1 Diabetes and Their Parents %A Holtz,Bree E %A Murray,Katharine M %A Hershey,Denise D %A Dunneback,Julie K %A Cotten,Shelia R %A Holmstrom,Amanda J %A Vyas,Arpita %A Kaiser,Molly K %A Wood,Michael A %+ Department of Advertising and Public Relations, Michigan State University, 404 Wilson Road, Room 309, East Lansing, MI, 48824, United States, 1 5178844537, bholtz@msu.edu %K mHealth %K qualitative research %K type 1 diabetes %K family %D 2017 %7 19.04.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Type 1 diabetes (T1D) afflicts approximately 154,000 people under 20 years of age. Three-quarters of adolescents are not achieving glycosylated hemoglobin (HbA1c) targets, which leads to negative health outcomes. Mobile health (mHealth), the use of technology in health, has been used successfully to improve health in many chronic conditions, including diabetes. Objective: The purpose of this study was to use patient-centered research methods to inform and improve the design and functionality of our T1D app, MyT1DHero, and to provide insight for others who are designing a health app for adolescents and parents. Methods: This study included data from focus groups with participants recruited from the Juvenile Diabetes Research Foundation (JDRF) southeast Michigan’s family network. All data collected during the sessions were audio-recorded, transcribed, and coded. Results: Four key themes were identified: (1) diabetes is unpredictable, (2) negative and frustrated communication, (3) motivations to use an app, and (4) feedback specific to our app. Conclusions: A patient-centered approach was used to assist in the development of an app for adolescents with T1D. Participants were satisfied with overall app design; customization, interactivity, and tangible rewards were identified as being necessary for continued use. Participants believed the app would help improve the communication between parents and adolescents. Many apps developed in the health context have not used a patient-centered design method or have seen vast improvements in health. This paper offers suggestions to others seeking to develop apps for adolescents and their parents. %M 28428167 %R 10.2196/mhealth.6654 %U http://mhealth.jmir.org/2017/4/e53/ %U https://doi.org/10.2196/mhealth.6654 %U http://www.ncbi.nlm.nih.gov/pubmed/28428167 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 3 %P e35 %T Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy %A Wu,Yuan %A Yao,Xun %A Vespasiani,Giacomo %A Nicolucci,Antonio %A Dong,Yajie %A Kwong,Joey %A Li,Ling %A Sun,Xin %A Tian,Haoming %A Li,Sheyu %+ Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, 37# Guoxue Road, Wuhou District, Chengdu, 610041, China, 86 13194874843, lisheyu@gmail.com %K mobile health %K mHealth %K mobile applications %K mobile apps %K diabetes mellitus %K classification %D 2017 %7 14.03.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile health apps for diabetes self-management have different functions. However, the efficacy and safety of each function are not well studied, and no classification is available for these functions. Objective: The aims of this study were to (1) develop and validate a taxonomy of apps for diabetes self-management, (2) investigate the glycemic efficacy of mobile app-based interventions among adults with diabetes in a systematic review of randomized controlled trials (RCTs), and (3) explore the contribution of different function to the effectiveness of entire app-based interventions using the taxonomy. Methods: We developed a 3-axis taxonomy with columns of clinical modules, rows of functional modules and cells of functions with risk assessments. This taxonomy was validated by reviewing and classifying commercially available diabetes apps. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, the Chinese Biomedical Literature Database, and ClinicalTrials.gov from January 2007 to May 2016. We included RCTs of adult outpatients with diabetes that compared using mobile app-based interventions with usual care alone. The mean differences (MDs) in hemoglobin A1c (HbA1c) concentrations and risk ratios of adverse events were pooled using a random-effects meta-analysis. After taxonomic classification, we performed exploratory subgroup analyses of the presence or absence of each module across the included app-based interventions. Results: Across 12 included trials involving 974 participants, using app-based interventions was associated with a clinically significant reduction of HbA1c (MD 0.48%, 95% CI 0.19%-0.78%) without excess adverse events. Larger HbA1c reductions were noted among patients with type 2 diabetes than those with type 1 diabetes (MD 0.67%, 95% CI 0.30%-1.03% vs MD 0.37%, 95% CI –0.12%-0.86%). Having a complication prevention module in app-based interventions was associated with a greater HbA1c reduction (with complication prevention: MD 1.31%, 95% CI 0.66%-1.96% vs without: MD 0.38%, 95% CI 0.09%-0.67%; intersubgroup P=.01), as was having a structured display (with structured display: MD 0.69%, 95% CI 0.32%-1.06% vs without: MD 0.69%, 95% CI –0.18%-0.53%; intersubgroup P=.03). However, having a clinical decision-making function was not associated with a larger HbA1c reduction (with clinical decision making: MD 0.19%, 95% CI –0.24%-0.63% vs without: MD 0.61%, 95% CI 0.27%-0.95%; intersubgroup P=.14). Conclusions: The use of mobile app-based interventions yields a clinically significant HbA1c reduction among adult outpatients with diabetes, especially among those with type 2 diabetes. Our study suggests that the clinical decision-making function needs further improvement and evaluation before being added to apps. %M 28292740 %R 10.2196/mhealth.6522 %U http://mhealth.jmir.org/2017/3/e35/ %U https://doi.org/10.2196/mhealth.6522 %U http://www.ncbi.nlm.nih.gov/pubmed/28292740 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 1 %P e5 %T A Novel Intervention Including Individualized Nutritional Recommendations Reduces Hemoglobin A1c Level, Medication Use, and Weight in Type 2 Diabetes %A McKenzie,Amy L %A Hallberg,Sarah J %A Creighton,Brent C %A Volk,Brittanie M %A Link,Theresa M %A Abner,Marcy K %A Glon,Roberta M %A McCarter,James P %A Volek,Jeff S %A Phinney,Stephen D %+ Virta Health, 535 Mission St 14th Floor, San Francisco, CA, 94105, United States, 1 9188974301, steve@virtahealth.com %K type 2 diabetes %K ketosis %K Hb A1c %K weight loss %K mobile health %D 2017 %7 07.03.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Type 2 diabetes (T2D) is typically managed with a reduced fat diet plus glucose-lowering medications, the latter often promoting weight gain. Objective: We evaluated whether individuals with T2D could be taught by either on-site group or remote means to sustain adequate carbohydrate restriction to achieve nutritional ketosis as part of a comprehensive intervention, thereby improving glycemic control, decreasing medication use, and allowing clinically relevant weight loss. Methods: This study was a nonrandomized, parallel arm, outpatient intervention. Adults with T2D (N=262; mean age 54, SD 8, years; mean body mass index 41, SD 8, kg·m−2; 66.8% (175/262) women) were enrolled in an outpatient protocol providing intensive nutrition and behavioral counseling, digital coaching and education platform, and physician-guided medication management. A total of 238 participants completed the first 10 weeks. Body weight, capillary blood glucose, and beta-hydroxybutyrate (BOHB) levels were recorded daily using a mobile interface. Hemoglobin A1c (HbA1c) and related biomarkers of T2D were evaluated at baseline and 10-week follow-up. Results: Baseline HbA1c level was 7.6% (SD 1.5%) and only 52/262 (19.8%) participants had an HbA1c level of <6.5%. After 10 weeks, HbA1c level was reduced by 1.0% (SD 1.1%; 95% CI 0.9% to 1.1%, P<.001), and the percentage of individuals with an HbA1c level of <6.5% increased to 56.1% (147/262). The majority of participants (234/262, 89.3%) were taking at least one diabetes medication at baseline. By 10 weeks, 133/234 (56.8%) individuals had one or more diabetes medications reduced or eliminated. At follow-up, 47.7% of participants (125/262) achieved an HbA1c level of <6.5% while taking metformin only (n=86) or no diabetes medications (n=39). Mean body mass reduction was 7.2% (SD 3.7%; 95% CI 5.8% to 7.7%, P<.001) from baseline (117, SD 26, kg). Mean BOHB over 10 weeks was 0.6 (SD 0.6) mmol·L−1 indicating consistent carbohydrate restriction. Post hoc comparison of the remote versus on-site means of education revealed no effect of delivery method on change in HbA1c (F1,260=1.503, P=.22). Conclusions: These initial results indicate that an individualized program delivered and supported remotely that incorporates nutritional ketosis can be highly effective in improving glycemic control and weight loss in adults with T2D while significantly decreasing medication use. %M 30291062 %R 10.2196/diabetes.6981 %U http://diabetes.jmir.org/2017/1/e5/ %U https://doi.org/10.2196/diabetes.6981 %U http://www.ncbi.nlm.nih.gov/pubmed/30291062 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 6 %N 3 %P e38 %T Enhancing mHealth Technology in the Patient-Centered Medical Home Environment to Activate Patients With Type 2 Diabetes: A Multisite Feasibility Study Protocol %A Gimbel,Ronald %A Shi,Lu %A Williams,Joel E %A Dye,Cheryl J %A Chen,Liwei %A Crawford,Paul %A Shry,Eric A %A Griffin,Sarah F %A Jones,Karyn O %A Sherrill,Windsor W %A Truong,Khoa %A Little,Jeanette R %A Edwards,Karen W %A Hing,Marie %A Moss,Jennie B %+ Department of Public Health Sciences, Clemson University, 501 Edwards Hall, Clemson, SC, 29634-0745, United States, 1 864 656 1969, rgimbel@clemson.edu %K mHealth %K diabetes mellitus %K patient activation %K patient-centered medical home %K patient centered care %K eHealth %K health information %D 2017 %7 06.03.2017 %9 Protocol %J JMIR Res Protoc %G English %X Background: The potential of mHealth technologies in the care of patients with diabetes and other chronic conditions has captured the attention of clinicians and researchers. Efforts to date have incorporated a variety of tools and techniques, including Web-based portals, short message service (SMS) text messaging, remote collection of biometric data, electronic coaching, electronic-based health education, secure email communication between visits, and electronic collection of lifestyle and quality-of-life surveys. Each of these tools, used alone or in combination, have demonstrated varying degrees of effectiveness. Some of the more promising results have been demonstrated using regular collection of biometric devices, SMS text messaging, secure email communication with clinical teams, and regular reporting of quality-of-life variables. In this study, we seek to incorporate several of the most promising mHealth capabilities in a patient-centered medical home (PCMH) workflow. Objective: We aim to address underlying technology needs and gaps related to the use of mHealth technology and the activation of patients living with type 2 diabetes. Stated differently, we enable supporting technologies while seeking to influence patient activation and self-care activities. Methods: This is a multisite phased study, conducted within the US Military Health System, that includes a user-centered design phase and a PCMH-based feasibility trial. In phase 1, we will assess both patient and provider preferences regarding the enhancement of the enabling technology capabilities for type 2 diabetes chronic care management. Phase 2 research will be a single-blinded 12-month feasibility study that incorporates randomization principles. Phase 2 research will seek to improve patient activation and self-care activities through the use of the Mobile Health Care Environment with tailored behavioral messaging. The primary outcome measure is the Patient Activation Measure scores. Secondary outcome measures are Summary of Diabetes Self-care Activities Measure scores, clinical measures, comorbid conditions, health services resource consumption, and technology system usage statistics. Results: We have completed phase 1 data collection. Formal analysis of phase 1 data has not been completed. We have obtained institutional review board approval and began phase 1 research in late fall 2016. Conclusions: The study hypotheses suggest that patients can, and will, improve their activation in chronic care management. Improved activation should translate into improved diabetes self-care. Expected benefits of this research to the scientific community and health care services include improved understanding of how to leverage mHealth technology to activate patients living with type 2 diabetes in self-management behaviors. The research will shed light on implementation strategies in integrating mHealth into the clinical workflow of the PCMH setting. Trial Registration: ClinicalTrials.gov NCT02949037. https://clinicaltrials.gov/ct2/show/NCT02949037. (Archived by WebCite at http://www.webcitation.org/6oRyDzqei) %M 28264792 %R 10.2196/resprot.6993 %U http://www.researchprotocols.org/2017/3/e38/ %U https://doi.org/10.2196/resprot.6993 %U http://www.ncbi.nlm.nih.gov/pubmed/28264792 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 3 %P e4 %T Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials %A Bonoto,Bráulio Cezar %A de Araújo,Vânia Eloisa %A Godói,Isabella Piassi %A de Lemos,Lívia Lovato Pires %A Godman,Brian %A Bennie,Marion %A Diniz,Leonardo Mauricio %A Junior,Augusto Afonso Guerra %+ Post Graduate Program in Medicines and Pharmaceutical Assistance, Department of Social Pharmacy, Federal University of Minas Gerais, Av Presidente Antônio Carlos, 6627, Campus Pampulha, Belo Horizonte, 31270-901, Brazil, 55 31 98722 9477, brauliofarma@yahoo.com.br %K diabetes mellitus %K self-care %K mobile applications %K telemedicine %D 2017 %7 01.03.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diabetes Mellitus (DM) is a chronic disease that is considered a global public health problem. Education and self-monitoring by diabetic patients help to optimize and make possible a satisfactory metabolic control enabling improved management and reduced morbidity and mortality. The global growth in the use of mobile phones makes them a powerful platform to help provide tailored health, delivered conveniently to patients through health apps. Objective: The aim of our study was to evaluate the efficacy of mobile apps through a systematic review and meta-analysis to assist DM patients in treatment. Methods: We conducted searches in the electronic databases MEDLINE (Pubmed), Cochrane Register of Controlled Trials (CENTRAL), and LILACS (Latin American and Caribbean Health Sciences Literature), including manual search in references of publications that included systematic reviews, specialized journals, and gray literature. We considered eligible randomized controlled trials (RCTs) conducted after 2008 with participants of all ages, patients with DM, and users of apps to help manage the disease. The meta-analysis of glycated hemoglobin (HbA1c) was performed in Review Manager software version 5.3. Results: The literature search identified 1236 publications. Of these, 13 studies were included that evaluated 1263 patients. In 6 RCTs, there were a statistical significant reduction (P<.05) of HbA1c at the end of studies in the intervention group. The HbA1c data were evaluated by meta-analysis with the following results (mean difference, MD −0.44; CI: −0.59 to −0.29; P<.001; I²=32%).The evaluation favored the treatment in patients who used apps without significant heterogeneity. Conclusions: The use of apps by diabetic patients could help improve the control of HbA1c. In addition, the apps seem to strengthen the perception of self-care by contributing better information and health education to patients. Patients also become more self-confident to deal with their diabetes, mainly by reducing their fear of not knowing how to deal with potential hypoglycemic episodes that may occur. %M 28249834 %R 10.2196/mhealth.6309 %U http://mhealth.jmir.org/2017/3/e4/ %U https://doi.org/10.2196/mhealth.6309 %U http://www.ncbi.nlm.nih.gov/pubmed/28249834 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 1 %P e3 %T Mixed-Methods Research in Diabetes Management via Mobile Health Technologies: A Scoping Review %A Sahin,Cigdem %A Naylor,Patti-Jean %+ Social Dimensions of Health Program, University of Victoria, PO Box 3050, STN CSC, Victoria, BC, V8W 3P5, Canada, 1 250 472 5185, csahin@uvic.ca %K mHealth %K self-management %K methods %K review %D 2017 %7 06.02.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Considering the increasing incidence and prevalence of diabetes worldwide and the high level of patient involvement it requires, diabetes self-management is a serious issue. The use of mobile health (mHealth) in diabetes self-management has increased, but so far research has not provided sufficient information about the uses and effectiveness of mHealth-based interventions. Alternative study designs and more rigorous methodologies are needed. Mixed-methods designs may be particularly useful because both diabetes self-management and mHealth studies require integrating theoretical and methodological approaches. Objective: This scoping review aimed to examine the extent of the use of mixed-methods research in mHealth-based diabetes management studies. The methodological approaches used to conduct mixed-methods studies were analyzed, and implications for future research are provided. Methods: Guided by Arksey and O’Malley’s framework, this scoping review implemented a comprehensive search strategy including reviewing electronic databases, key journal searches, Web-based research and knowledge centers, websites, and handsearching reference lists of the studies. The studies focusing on mHealth technologies and diabetes management were included in the review if they were primary research papers published in academic journals and reported using a combination of qualitative and quantitative methods. The key data extracted from the reviewed studies include purpose of mixing, design type, stage of integration, methods of legitimation, and data collection techniques. Results: The final sample (N=14) included studies focused on the feasibility and usability of mHealth diabetes apps (n=7), behavioral measures related to the mHealth apps (n=6), and challenges of intervention delivery in the mHealth context (n=1). Reviewed studies used advanced forms of mixed-methods designs where integration occurred at multiple points and data were collected using multiple techniques. However, the majority of studies did not identify a specific mixed-methods design or use accepted terminology; nor did they justify using this approach. Conclusions: This review provided important insights into the use of mixed methods in studies focused on diabetes management via mHealth technologies. The prominent role of qualitative methods and tailored measures in diabetes self-management studies was confirmed, and the importance of using multiple techniques and approaches in this field was emphasized. This review suggests defining specific mixed-methods questions, using specific legitimation methods, and developing research designs that overcome sampling and other methodological problems in future studies. %M 30291052 %R 10.2196/diabetes.6667 %U http://diabetes.jmir.org/2017/1/e3/ %U https://doi.org/10.2196/diabetes.6667 %U http://www.ncbi.nlm.nih.gov/pubmed/30291052 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 2 %N 1 %P e2 %T Smartphone App Use for Diabetes Management: Evaluating Patient Perspectives %A Lithgow,Kirstie %A Edwards,Alun %A Rabi,Doreen %+ Department of Medicine, Cumming School of Medicine, University of Calgary, 1820 Richmond Road SW, Calgary, AB, T2T 5C7, Canada, 1 403 605 0811, kclithgo@ucalgary.ca %K type 1 diabetes %K mobile health %K smartphone %D 2017 %7 23.01.2017 %9 Original Paper %J JMIR Diabetes %G English %X Background: Finding novel ways to engage patients in chronic disease management has led to increased interest in the potential of mobile health technologies for the management of diabetes. There is currently a wealth of smartphone apps for diabetes management that are available for free download or purchase. However, the usability and desirability of these apps has not been extensively studied. These are important considerations, as these apps must be accepted by the patient population at a practical level if they are to be utilized. Objective: The purpose of this study was to gain insight into patient experiences related to the use of smartphone apps for the management of type 1 diabetes. Methods: Adults with type 1 diabetes who had previously (or currently) used apps to manage their diabetes were eligible to participate. Participants (n=12) completed a questionnaire in which they were required to list the names of preferred apps and indicate which app functions they had used. Participants were given the opportunity to comment on app functions that they perceived to be missing from the current technology. Participants were also asked whether they had previously paid for an app and whether they would be willing to do so. Results: MyFitnessPal and iBGStar were the apps most commonly listed as the best available on the market. Blood glucose tracking, carbohydrate counting, and activity tracking were the most commonly used features. Ten participants fulfilled all eligibility criteria, and indicated that they had not encountered any one app that included all of the functions that they had used. The ability to synchronize an app with a glucometer or insulin pump was the most common function that participants stated was missing from current app technology. One participant had previously paid for a diabetes-related app and the other 9 participants indicated that they would be willing to pay. Conclusions: Despite dissatisfaction with the currently available apps, there is interest in using these tools for diabetes management. Adapting existing technology to better meet the needs of this patient population may allow these apps to become more widely utilized. %M 30291051 %R 10.2196/diabetes.6643 %U http://diabetes.jmir.org/2017/1/e2/ %U https://doi.org/10.2196/diabetes.6643 %U http://www.ncbi.nlm.nih.gov/pubmed/30291051 %0 Journal Article %@ 2369-6893 %I JMIR Publications %V 2 %N 1 %P e11 %T Developing a Patient-Centered mHealth App for Diabetes %A Murray,Katharine Marie %A Holtz,Bree Elizabeth %A Wood,Michael %A Holmstrom,Amanda %A Cotten,Shelia %A Dunneback,Julie %A Hershey,Denise %A Vyas,Arpita %+ Department of Advertising and Public Relations, Michigan State University, Room 309, 404 Wilson Road, East Lansing, MI, 48824, United States, 1 517 884 8892, murra172@msu.edu %K mHealth %K type 1 diabetes %K diabetes self-management %K adolescent health %D 2016 %7 14.12.2016 %9 Poster %J iproc %G English %X Background: Type 1 diabetes (T1D) afflicts approximately 154,000 people under the age of 20. T1D care is complex, which is why parents often manage their child’s disease. Once the child reaches adolescence, they must begin to transition from parent care to self-care. As a result of the inherent complexity of managing T1D, this transition is often difficult. During this time, adherence to the prescribed treatment regimen drops. Uncontrolled T1D can lead to blindness, nervous system disease, kidney disease, amputations, and premature mortality. mHealth apps have been shown to be successful at monitoring and managing chronic diseases, including diabetes. This project is in the formative stages of developing an app for adolescents with T1D to connect with their parents to bridge the transition of care. Our proposed app, MyT1D_Hero, is unique in that it links the child’s information to their parent’s cell phone and promotes positive communication within families. Research suggests this interaction is imperative for a successful transition in care. Objective: The goal of this study was to determine the perceptions of adolescents with T1D and their parents regarding how best to aid in the transition to diabetes self-management. Methods: We conducted two sets of focus groups to examine perceptions of the proposed app. The first study included focus groups and interviews with adolescents aged 13-22 with T1D (n=12) and parents (n=9). These focus groups and interviews helped inform the development of a second set of focus group protocols conducted with adolescents aged 10-13 with T1D (n=5) and parents (n=7). Using grounded theory, the transcripts were analyzed by generating codes based on an iterative examination of the data. Members of the research team then coded the interviews independently; any discrepancies were discussed and resolved. These codes were applied to the transcripts and a list of key themes emerged. Results: The analysis of the initial focus groups and interviews yielded the following key themes: (1) adolescents were more likely to have a phone because they have diabetes and (2) both groups felt that parents nagged and believed an app might reduce conflict. The second session yielded the following key themes: (1) parents want to feel confident in their child’s ability to manage their diabetes independently, but they want to be engaged in managing their child’s T1D; (2) children want more positive communication from their parents regarding their T1D; and (3) customization of the app was important, including adjusting the level of parent involvement. Both studies revealed that incentives and gamification will encourage long-term use of the mobile app. Conclusions: Taking a patient-centered approach to gain insight into the daily management of T1D supports the development of a T1D mHealth app to aid in the transition toward self-management. The first study established the need for and projected usefulness of an app. The second study demonstrated additional necessities for creating an app that meets the needs of adolescents and their parents. Additionally, both studies demonstrated the importance of supportive patient-centered research to tailor mHealth interventions. %R 10.2196/iproc.6102 %U http://www.iproc.org/2016/1/e11/ %U https://doi.org/10.2196/iproc.6102 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 1 %N 2 %P e5 %T DiaFit: The Development of a Smart App for Patients with Type 2 Diabetes and Obesity %A Modave,François %A Bian,Jiang %A Rosenberg,Eric %A Mendoza,Tonatiuh %A Liang,Zhan %A Bhosale,Ravi %A Maeztu,Carlos %A Rodriguez,Camila %A Cardel,Michelle I %+ Department of Health Outcomes and Policy, University of Florida, 2004 Mowry road, CTRB 3217, Gainesville, FL, 32610, United States, 1 3522945984, modavefp@ufl.edu %K mHealth %K diabetes %K obesity %K apps %D 2016 %7 13.12.2016 %9 Original Paper %J JMIR Diabetes %G English %X Background: Optimal management of chronic diseases, such as type 2 diabetes (T2D) and obesity, requires patient-provider communication and proactive self-management from the patient. Mobile apps could be an effective strategy for improving patient-provider communication and provide resources for self-management to patients themselves. Objective: The objective of this paper is to describe the development of a mobile tool for patients with T2D and obesity that utilizes an integrative approach to facilitate patient-centered app development, with patient and physician interfaces. Our implementation strategy focused on the building of a multidisciplinary team to create a user-friendly and evidence-based app, to be used by patients in a home setting or at the point-of-care. Methods: We present the iterative design, development, and testing of DiaFit, an app designed to improve the self-management of T2D and obesity, using an adapted Agile approach to software implementation. The production team consisted of experts in mobile health, nutrition sciences, and obesity; software engineers; and clinicians. Additionally, the team included citizen scientists and clinicians who acted as the de facto software clients for DiaFit and therefore interacted with the production team throughout the entire app creation, from design to testing. Results: DiaFit (version 1.0) is an open-source, inclusive iOS app that incorporates nutrition data, physical activity data, and medication and glucose values, as well as patient-reported outcomes. DiaFit supports the uploading of data from sensory devices via Bluetooth for physical activity (iOS step counts, FitBit, Apple watch) and glucose monitoring (iHealth glucose meter). The app provides summary statistics and graphics for step counts, dietary information, and glucose values that can be used by patients and their providers to make informed health decisions. The DiaFit iOS app was developed in Swift (version 2.2) with a Web back-end deployed on the Health Insurance Portability and Accountability Act compliant-ready Amazon Web Services cloud computing platform. DiaFit is publicly available on GitHub to the diabetes community at large, under the GNU General Public License agreement. Conclusions: Given the proliferation of health-related apps available to health consumers, it is essential to ensure that apps are evidence-based and user-oriented, with specific health conditions in mind. To this end, we have used a software development approach focusing on community and clinical engagement to create DiaFit, an app that assists patients with T2D and obesity to better manage their health through active communication with their providers and proactive self-management of their diseases. %M 29388609 %R 10.2196/diabetes.6662 %U http://diabetes.jmir.org/2016/2/e5/ %U https://doi.org/10.2196/diabetes.6662 %U http://www.ncbi.nlm.nih.gov/pubmed/29388609 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 11 %P e290 %T Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis %A Ming,Wai-Kit %A Mackillop,Lucy H %A Farmer,Andrew J %A Loerup,Lise %A Bartlett,Katy %A Levy,Jonathan C %A Tarassenko,Lionel %A Velardo,Carmelo %A Kenworthy,Yvonne %A Hirst,Jane E %+ Nuffield Department of Obstetrics & Gynaecology, John Radcliffe Hospital, Level 3, Women's Centre, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom, 44 01865 221019, jane.hirst@obs-gyn.ox.ac.uk %K pregnancy %K diabetes mellitus %K telemedicine %K review %K meta-analysis %K pregnancy in diabetics %D 2016 %7 09.11.2016 %9 Review %J J Med Internet Res %G English %X Background: Diabetes in pregnancy is a global problem. Technological innovations present exciting opportunities for novel approaches to improve clinical care delivery for gestational and other forms of diabetes in pregnancy. Objective: To perform an updated and comprehensive systematic review and meta-analysis of the literature to determine whether telemedicine solutions offer any advantages compared with the standard care for women with diabetes in pregnancy. Methods: The review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Randomized controlled trials (RCT) in women with diabetes in pregnancy that compared telemedicine blood glucose monitoring with the standard care were identified. Searches were performed in SCOPUS and PubMed, limited to English language publications between January 2000 and January 2016. Trials that met the eligibility criteria were scored for risk of bias using the Cochrane Collaborations Risk of Bias Tool. A meta-analysis was performed using Review Manager software version 5.3 (Nordic Cochrane Centre, Cochrane Collaboration). Results: A total of 7 trials were identified. Meta-analysis demonstrated a modest but statistically significant improvement in HbA1c associated with the use of a telemedicine technology. The mean HbA1c of women using telemedicine was 5.33% (SD 0.70) compared with 5.45% (SD 0.58) in the standard care group, representing a mean difference of −0.12% (95% CI −0.23% to −0.02%). When this comparison was limited to women with gestational diabetes mellitus (GDM) only, the mean HbA1c of women using telemedicine was 5.22% (SD 0.70) compared with 5.37% (SD 0.61) in the standard care group, mean difference −0.14% (95% CI −0.25% to −0.04%). There were no differences in other maternal and neonatal outcomes reported. Conclusions: There is currently insufficient evidence that telemedicine technology is superior to standard care for women with diabetes in pregnancy; however, there was no evidence of harm. No trials were identified that assessed patient satisfaction or cost of care delivery, and it may be in these areas where these technologies may be found most valuable. %M 27829574 %R 10.2196/jmir.6556 %U http://www.jmir.org/2016/11/e290/ %U https://doi.org/10.2196/jmir.6556 %U http://www.ncbi.nlm.nih.gov/pubmed/27829574 %0 Journal Article %@ 1929-0748 %I JMIR Publications Inc. %V 5 %N 3 %P e93 %T Design and Usability Evaluation of Social Mobile Diabetes Management System in the Gulf Region %A Alanzi,Turki %A Istepanian,Robert %A Philip,Nada %+ Health Information Management and Technology Department, College of Applied Medical Sciences, University of Dammam, 12345, Dammam,, Saudi Arabia, 966 133331211, talanzi@uod.edu.sa %K mobile health %K mobile diabetes management %K social networking for health care %K diabetes mellitus %K telemedicine %K electronic health %K Kingdom of Saudi Arabia %D 2016 %7 26.09.2016 %9 Original Paper %J JMIR Res Protoc %G English %X Background: The prevalence of diabetes in the Gulf States is one of the highest globally. It is estimated that 20% of the population in the region has been diagnosed with diabetes and according to the International Diabetes Federation (IDF), five of the IDF’s “top 10” countries for diabetes prevalence in 2011 and projected for 2030 are in this region. In recent years, there have been an increasing number of clinical studies advocating the use of mobile phone technology for diabetes self-management with improved clinical outcomes. However, there are few studies to date addressing the application of mobile diabetes management in the Gulf region, particularly in the Kingdom of Saudi Arabia (KSA), where there is exponential increase in mobile phone usage and access to social networking. Objective: The objective of this paper is to present the design and development of a new mobile health system for social behavioral change and management tailored for Saudi patients with diabetes called Saudi Arabia Networking for Aiding Diabetes (SANAD). A usability study for the SANAD system is presented to validate the acceptability of using mobile technologies among patients with diabetes in the KSA and the Gulf region. Methods: The SANAD system was developed using mobile phone technology with diabetes management and social networking modules. For the usability study the Questionnaire for User Interaction Satisfaction was used to evaluate the usability aspect of the SANAD system. A total of 33 users with type 2 diabetes participated in the study. Results: The key modules of the SANAD system consist of (1) a mobile diabetes management module; (2) a social networking module; and (3) a cognitive behavioral therapy module for behavioral change issues. The preliminary results of the usability study indicated general acceptance of the patients in using the system with higher usability rating in patients with type 2 diabetes. Conclusions: We found that the acceptability of the system was high among Saudi patients with diabetes, and ongoing work in this research area is underway to conduct a clinical pilot study in the KSA for patients with type 2 diabetes. The wide deployment of such a system is timely and required in the Gulf region due to the wide use of mobile phones and social networking mediums. %M 27670696 %R 10.2196/resprot.4348 %U http://www.researchprotocols.org/2016/3/e93/ %U https://doi.org/10.2196/resprot.4348 %U http://www.ncbi.nlm.nih.gov/pubmed/27670696 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 5 %N 3 %P e148 %T Telemedicine Versus Standard Follow-Up Care for Diabetes-Related Foot Ulcers: Protocol for a Cluster Randomized Controlled Noninferiority Trial (DiaFOTo) %A Iversen,Marjolein M %A Espehaug,Birgitte %A Hausken,Marie F %A Graue,Marit %A Østbye,Truls %A Skeie,Svein %A Cooper,John G %A Tell,Grethe S %A Günther,Bodo Erhardt %A Dale,Håvard %A Smith-Strøm,Hilde %A Kolltveit,Beate-Christin H %A Kirkevold,Marit %A Rokne,Berit %+ Centre for Evidence-Based Practice, Faculty of Health and Social Sciences, Bergen University College, Pb 7030, Bergen,, Norway, 47 555 87 500 ext 5815, miv@hib.no %K diabetes %K diabetic foot %K foot ulcer %K telemedicine %K randomized controlled trial %K primary care %K delivery of health care, integrated %K complex intervention %K patient-reported outcomes %K Norway %K cluster RCT %D 2016 %7 18.07.2016 %9 Protocol %J JMIR Res Protoc %G English %X Background: This paper presents the protocol for an ongoing study to evaluate a telemedicine follow-up intervention for patients with diabetes-related foot ulcers. Diabetes-related foot ulcers represent challenges for patients and the health services. The large increase in the prevalence of diabetes, combined with the aging population, means that the absolute number of patients with diabetes-related foot ulcers is likely to continue to increase. Health care services therefore need to provide close clinical follow-up care for people with diabetes both in primary and specialist care. Information and communication technologies may enable more integrated treatment and care pathways across organizational boundaries. However, we lack knowledge about the effect of telemedicine follow-up and how such services can be optimally organized. Objective: To present the design and methods of a study evaluating a telemedicine follow-up intervention for patients with diabetes-related foot ulcers. Methods: The study is designed as a cluster randomized controlled trial (noninferiority trial) involving municipalities or municipality districts (clusters) belonging to one clinical site in Western Norway. The study includes patients with type 1 and type 2 diabetes presenting with a new foot ulcer at the initial visit to the clinic. Patients in the intervention group receive telemedicine follow-up care in the community. The key ingredient in the intervention is the close integration between health care levels. The intervention is facilitated by the use of an interactive wound platform consisting of a Web-based ulcer record combined with a mobile phone, enabling counseling and communication between nurses in the community and specialist health care. Patients in the control group receive standard hospital outpatient care. The primary endpoint in the trial is healing time; secondary outcomes include amputation and death, patient-reported outcome measures, and follow-up data on the recurrence of foot ulcers. In addition, qualitative substudies are being performed to provide a more comprehensive evaluation of the ongoing processes during the trial with the patients in the intervention and control groups and those health care professionals either working in primary care or in specialist care delivering the intervention. Results: The project has been funded. The inclusion of patients started in September 2012. Because recruitment goals were not met in the initial period, two more clinical sites have been included to meet sample size requirements. Patient recruitment will continue until June 2016. Data collection in the qualitative substudies has been completed. Conclusions: This telemedicine trial operates in a novel setting and targets patients with diabetes-related foot ulcers during a 12-month follow-up period. The trial addresses whether integrated care using telemedicine between primary and specialist health care can be an equivalent alternative to standard outpatient care. Trial Registration: ClinicalTrials.gov NCT01710774; https://clinicaltrials.gov/ct2/show/NCT01710774 (Archived by WebCite at http://www.webcitation.org/6im6KfFov). %M 27430301 %R 10.2196/resprot.5646 %U http://www.researchprotocols.org/2016/3/e148/ %U https://doi.org/10.2196/resprot.5646 %U http://www.ncbi.nlm.nih.gov/pubmed/27430301 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 3 %N 2 %P e23 %T Mobile Phone and Web-based Cognitive Behavior Therapy for Depressive Symptoms and Mental Health Comorbidities in People Living With Diabetes: Results of a Feasibility Study %A Clarke,Janine %A Proudfoot,Judith %A Ma,Howard %+ Black Dog Institute, Hospital Road, Randwick, 2031, Australia, 61 2 9382 3767, janine.clarke@unsw.edu.au %K diabetes %K depression %K Internet interventions %K eHealth %K CBT %D 2016 %7 31.05.2016 %9 Original Paper %J JMIR Ment Health %G English %X Background: Depression is often comorbid with diabetes; however, undertreatment of depressive symptoms in people affected is common. Objective: We studied preliminary acceptability and effectiveness of a fully automated, mobile phone, and web-based public health intervention, myCompass, for reducing depressive symptoms and improving mental health comorbidities in people with diabetes. Methods: In this single-group feasibility study, 89 volunteers with type 1 (n=34) or type 2 (n=55) diabetes and at least mild depressive symptoms used myCompass for 7 weeks. Web-based measures of depressive and anxious symptoms, functional impairment, diabetes-specific variables, and user satisfaction were completed at baseline, postintervention, and 3-month follow-up. Results: Retention rates were 54% (n=48) at postintervention and 36% (n=32) at follow-up. Depressive symptoms were significantly improved at postintervention (P<.001; within-group effect size d=1.05), with gains persisting at follow-up. Mental health comorbidities, including anxiety (P<.001), functioning (P<.001), and diabetes-specific distress (P<.001), also showed significant and sustained improvement. Satisfaction with myCompass was high, with convenience and ease of program use, and relevance of program content rated positively by participants. Conclusions: The myCompass program shows promise as an acceptable and effective treatment for depression and comorbid mental health problems in people with diabetes. The program is broadly available, free to use, and may benefit patients with diabetes who do not access services and/or wish to manage their mental health themselves. Replication of these findings in a controlled study is warranted. %M 27245948 %R 10.2196/mental.5131 %U http://mental.jmir.org/2016/2/e23/ %U https://doi.org/10.2196/mental.5131 %U http://www.ncbi.nlm.nih.gov/pubmed/27245948 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 18 %N 5 %P e101 %T Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study %A Rhyner,Daniel %A Loher,Hannah %A Dehais,Joachim %A Anthimopoulos,Marios %A Shevchik,Sergey %A Botwey,Ransford Henry %A Duke,David %A Stettler,Christoph %A Diem,Peter %A Mougiakakou,Stavroula %+ ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, Bern, 3008, Switzerland, 41 316327592, stavroula.mougiakakou@artorg.unibe.ch %K diabetes mellitus, type 1 %K carbohydrate counting %K computer vision systems %K food recognition %K meal assessment %K mobile phone %K food volume estimation %D 2016 %7 11.05.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals. %M 27170498 %R 10.2196/jmir.5567 %U http://www.jmir.org/2016/5/e101/ %U https://doi.org/10.2196/jmir.5567 %U http://www.ncbi.nlm.nih.gov/pubmed/27170498 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 18 %N 4 %P e86 %T The Impact of Automated Brief Messages Promoting Lifestyle Changes Delivered Via Mobile Devices to People with Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Controlled Trials %A Arambepola,Carukshi %A Ricci-Cabello,Ignacio %A Manikavasagam,Pavithra %A Roberts,Nia %A French,David P %A Farmer,Andrew %+ University of Oxford, Nuffield Department of Primary Care Health Sciences, Radcliffe Observatory Quarter, Woodstock Road, Oxford., Oxford, OX2 6GG, United Kingdom, 44 01865 617190, ignacio.riccicabello@phc.ox.ac.uk %K Diabetes mellitus, type 2 %K mobile health %K text messaging %K systematic review %K diet %K physical activity %K self-care %D 2016 %7 19.04.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Brief automated messages have the potential to support self-management in people with type 2 diabetes, but their effect compared with usual care is unclear. Objective: To examine the effectiveness of interventions to change lifestyle behavior delivered via automated brief messaging in patients with type 2 diabetes. Methods: A systematic literature review of controlled trials examined the impact of interventions, delivered by brief messaging, and intended to promote lifestyle change in people with type 2 diabetes, on behavioral and clinical outcomes. Bibliographic databases searched included Medline, Embase, CINAHL, PsycINFO, and ISI WoK. Two reviewers independently screened citations. We extracted information on study risk of bias, setting (high versus low- and middle-income countries) and intervention characteristics (including use of theory and behavior-change techniques). Outcome measures included acceptability of the interventions and their impact on 1) determinants of lifestyle behavior (knowledge about diabetes, self-efficacy, attitudes towards self-management), 2) lifestyle behavior (diet, physical activity), and 3) clinical and patient-reported outcomes. Where possible, we pooled data using random-effects meta-analyses to obtain estimates of effect size of intervention compared to usual care. Results: We identified 15 trials (15 interventions) meeting our inclusion criteria. Most interventions were delivered via short message service text messaging (n=12) and simultaneously targeted diet and physical activity (n=11). Nine interventions consisted of unidirectional messages, whereas six consisted of bidirectional messages, with patients receiving automated tailored feedback based on self-reported data. The acceptability of the interventions, and their impact on lifestyle behavior and its determinants, were examined in a low proportion of trials, with heterogeneous results being observed. In 13 trials (1155 patients) where data were available, there was a difference in glycated hemoglobin of -0.53% (95% CI -0.59% to -0.47%) between intervention groups compared to usual care. In five trials (406 patients) there was a non-significant difference in body mass index of -0.25 kg/m2 (95% CI -1.02 to 0.52). Interventions based on unidirectional messages produced similar effects in the outcomes examined, compared to those based on bidirectional messages. Interventions conducted in low- and middle-income countries showed a greater impact than those conducted in high-income countries. In general, trials were not free of bias and did not use explicit theory. Conclusions: Automated brief messages strategies can improve health outcomes in people with type 2 diabetes. Larger, methodologically robust trials are needed to confirm these positive results. %M 27095386 %R 10.2196/jmir.5425 %U http://www.jmir.org/2016/4/e86/ %U https://doi.org/10.2196/jmir.5425 %U http://www.ncbi.nlm.nih.gov/pubmed/27095386 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 1 %N 1 %P e2 %T Information and Communication Technology-Powered Diabetes Self-Management Systems in China: A Study Evaluating the Features and Requirements of Apps and Patents %A Li,Ying %A Tan,Jin %A Shi,Bozhi %A Duan,Xiaolian %A Zhong,Daidi %A Li,Xiaoling %A Qu,Jianning %+ Chongqing Academy of Science & Technology, 2Yangliu Road, Huangshan Avenue, New North Zone, Chongqing, 401123, China, 86 2367300872, dxl@cast.gov.cn %K apps %K diabetes %K information and communication technology %K self-monitoring of blood glucose %K patents %D 2016 %7 06.04.2016 %9 Original Paper %J JMIR Diabetes %G English %X Background: For patients with diabetes, the self-monitoring of blood glucose (SMBG) is a recommended way of controlling the blood glucose level. By leveraging the modern information and communication technology (ICT) and the corresponding infrastructure, engineers nowadays are able to merge the SMBG activities into daily life and to dramatically reduce patient’s burden. Such type of ICT-powered SMBG had already been marketed in the United States and the European Union for a decade, but was introduced into the Chinese market only in recent years. Although there is no doubt about the general need for such type of SMBG in the Chinese market, how it could be adapted to the local technical and operational environment is still an open question. Objective: Our overall goal is to understand the local requirements and the current status of deploying ICT-powered SMBG to the Chinese market. In particular, we aim to analyze existing domestic SMBG mobile apps and relevant domestic patents to identify their various aspects, including the common functionalities, innovative feature, defects, conformance to standards, prospects, etc. In the long run, we hope the outcome of this study could help the decision making on how to properly adapt ICT-powered SMBG to the Chinese market. Methods: We identified 289 apps. After exclusion of irrelevant apps, 78 apps remained. These were downloaded and analyzed. A total of 8070 patents related to glucose were identified from patent database. Irrelevant materials and duplicates were excluded, following which 39 patents were parsed to extract the important features. These apps and patents were further compared with the corresponding requirements derived from relevant clinical guidelines and data standards. Results: The most common features of studied apps were blood health data recording, notification, and decision supporting. The most common features of studied patents included mobile terminal, server, and decision supporting. The main difference between patents and apps is that the patents had 2 specific features, namely, interface to the hospital information system and recording personal information, which were not mentioned in the app. The other major finding is that, in general, in terms of the components of the features, although the features identified in both apps and patents conform to the requirements of the relevant clinical guidelines and data standards, upon looking into the details, gaps exist between the features of the identified apps and patents and the relevant clinical guidelines and data standards. In addition, the social media feature that the apps and patents have is not included in the standard requirements list. Conclusions: The development of Chinese SMBG mobile apps and relevant patents is still in the primitive stage. Although the functionalities of most apps and patents can meet the basic requirements of SMBG, gaps have been identified when comparing the functionalities provided by apps and patents with the requirements necessitated by the standards. One of the most important gaps is that only a small portion of the studied apps provides the automatic data transmission and exchange feature, which may hamper the overall performance. The clinical guidelines can thus be further developed to leverage new features provided by ICT-powered SMBG apps (eg, the social media feature, which may help to improve the social intervention of patients with diabetes). %M 30291083 %R 10.2196/diabetes.4475 %U http://diabetes.jmir.org/2016/1/e2/ %U https://doi.org/10.2196/diabetes.4475 %U http://www.ncbi.nlm.nih.gov/pubmed/30291083 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 1 %N 1 %P e1 %T Data Mining of a Remote Behavioral Tracking System for Type 2 Diabetes Patients: A Prospective Cohort Study %A Wayne,Noah %A Cercone,Nick %A Li,Jiye %A Zohar,Ariel %A Katz,Joel %A Brown,Patrick %A Ritvo,Paul %+ Health Behaviour Change Lab, School of Kinesiology & Health Science, York University, 136 Chemistry Building, 4700 Keele Street, Toronto, ON, M3J1P3, Canada, 1 416 736 2100 ext 22396, pritvo@yorku.ca %K diabetes mellitus, type 2 %K health coaching %K mhealth %K telehealth %K data mining %D 2016 %7 06.04.2016 %9 Original Paper %J JMIR Diabetes %G English %X Background: Complications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software. Objective: Associations were evaluated between the smartphone monitoring of health behaviors and HbA1c reductions in a patient subsample with type 2 diabetes who demonstrated clinically significant benefits after participation in a randomized controlled trial. Methods: A priori association-rule algorithms, implemented in the C language, were applied to app-discretized use data involving three primary health behavior trackers (exercise, diet, and glucose monitoring) from 29 participants who achieved clinically significant HbA1c reductions. Use was evaluated in relation to improved HbA1c outcomes. Results: Analyses indicated that nearly a third (9/29, 31%) of participants used a single tracker, half (14/29, 48%) used two primary trackers, and the remainder (6/29, 21%) of the participants used three primary trackers. Decreases in HbA1c were observed across all groups (0.97-1.95%), but clinically significant reductions were more likely with use of one or two trackers rather than use of three trackers (OR 0.18, P=.04). Conclusions: Data mining techniques can reveal relevant coherent behavior patterns useful in guiding future intervention structure. It appears that focusing on using one or two trackers, in a symbolic function, was more effective (in this sample) than regular use of all three trackers. %M 30291054 %R 10.2196/diabetes.4506 %U http://diabetes.jmir.org/2016/1/e1/ %U https://doi.org/10.2196/diabetes.4506 %U http://www.ncbi.nlm.nih.gov/pubmed/30291054 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 4 %P e108 %T Let Visuals Tell the Story: Medication Adherence in Patients with Type II Diabetes Captured by a Novel Ingestion Sensor Platform %A Browne,Sara H %A Behzadi,Yashar %A Littlewort,Gwen %+ University of California, San Diego, School of Medicine, 9500 Gilman Drive, Mail Code 0640, La Jolla, CA, 92093-0640, United States, 1 858 822 6563, shbrowne@ucsd.edu %K ingestion sensor platform %K data visualization %K time domain methods %K medication adherence %K patient self-management %D 2015 %7 31.12.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: Chronic diseases such as diabetes require high levels of medication adherence and patient self-management for optimal health outcomes. A novel sensing platform, Digital Health Feedback System (Proteus Digital Health, Redwood City, CA), can for the first time detect medication ingestion events and physiological measures simultaneously, using an edible sensor, personal monitor patch, and paired mobile device. The Digital Health Feedback System (DHFS) generates a large amount of data. Visual analytics of this rich dataset may provide insights into longitudinal patterns of medication adherence in the natural setting and potential relationships between medication adherence and physiological measures that were previously unknown. Objective: Our aim was to use modern methods of visual analytics to represent continuous and discrete data from the DHFS, plotting multiple different data types simultaneously to evaluate the potential of the DHFS to capture longitudinal patterns of medication-taking behavior and self-management in individual patients with type II diabetes. Methods: Visualizations were generated using time domain methods of oral metformin medication adherence and physiological data obtained by the DHFS use in 5 patients with type II diabetes over 37-42 days. The DHFS captured at-home metformin adherence, heart rate, activity, and sleep/rest. A mobile glucose monitor captured glucose testing and level (mg/dl). Algorithms were developed to analyze data over varying time periods: across the entire study, daily, and weekly. Following visualization analysis, correlations between sleep/rest and medication ingestion were calculated across all subjects. Results: A total of 197 subject days, encompassing 141,840 data events were analyzed. Individual continuous patch use varied between 87-98%. On average, the cohort took 78% (SD 12) of prescribed medication and took 77% (SD 26) within the prescribed ±2-hour time window. Average activity levels per subjects ranged from 4000-12,000 steps per day. The combination of activity level and heart rate indicated different levels of cardiovascular fitness between subjects. Visualizations over the entire study captured the longitudinal pattern of missed doses (the majority of which took place in the evening), the timing of ingestions in individual subjects, and the range of medication ingestion timing, which varied from 1.5-2.4 hours (Subject 3) to 11 hours (Subject 2). Individual morning self-management patterns over the study period were obtained by combining the times of waking, metformin ingestion, and glucose measurement. Visualizations combining multiple data streams over a 24-hour period captured patterns of broad daily events: when subjects rose in the morning, tested their blood glucose, took their medications, went to bed, hours of sleep/rest, and level of activity during the day. Visualizations identified highly consistent daily patterns in Subject 3, the most adherent participant. Erratic daily patterns including sleep/rest were demonstrated in Subject 2, the least adherent subject. Correlation between sleep /rest and medication ingestion in each individual subject was evaluated. Subjects 2 and 4 showed correlation between amount of sleep/rest over a 24-hour period and medication-taking the following day (Subject 2: r=.47, P<.02; Subject 4: r=.35, P<.05). With Subject 2, sleep/rest disruptions during the night were highly correlated (r=.47, P<.009) with missing doses the following day. Conclusions: Visualizations integrating medication ingestion and physiological data from the DHFS over varying time intervals captured detailed individual longitudinal patterns of medication adherence and self-management in the natural setting. Visualizing multiple data streams simultaneously, providing a data-rich representation, revealed information that would not have been shown by plotting data streams individually. Such analyses provided data far beyond traditional adherence summary statistics and may form the foundation of future personalized predictive interventions to drive longitudinal adherence and support optimal self-management in chronic diseases such as diabetes. %M 26721413 %R 10.2196/mhealth.4292 %U http://mhealth.jmir.org/2015/4/e108/ %U https://doi.org/10.2196/mhealth.4292 %U http://www.ncbi.nlm.nih.gov/pubmed/26721413 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 4 %P e105 %T A Text-Messaging and Pedometer Program to Promote Physical Activity in People at High Risk of Type 2 Diabetes: The Development of the PROPELS Follow-On Support Program %A Morton,Katie %A Sutton,Stephen %A Hardeman,Wendy %A Troughton,Jacqui %A Yates,Tom %A Griffin,Simon %A Davies,Melanie %A Khunti,Kamlesh %A Eborall,Helen %+ Social Science Applied to Healthcare Improvement Research Group, Department of Health Sciences, University of Leicester, 22-28 Princess Road West, Leicester, , United Kingdom, 44 116 252 5400, hce3@le.ac.uk %K physical activity %K mHealth %K text messaging %K pedometer %K tailoring %K type 2 diabetes %K intervention development %D 2015 %7 15.12.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: Mobile technologies for health (mHealth) represent a promising strategy for reducing type 2 diabetes (T2DM) risk. The PROPELS trial investigates whether structured group-based education alone or supplemented with a follow-on support program combining self-monitoring with pedometers and tailored text-messaging is effective in promoting and maintaining physical activity among people at high risk of T2DM. Objective: This paper describes the iterative development of the PROPELS follow-on support program and presents evidence on its acceptability and feasibility. Methods: We used a modified mHealth development framework with four phases: (1) conceptualization of the follow-on support program using theory and evidence, (2) formative research including focus groups (n=15, ages 39-79 years), (3) pre-testing focus groups using a think aloud protocol (n=20, ages 52-78 years), and (4) piloting (n=11). Analysis was informed by the constant comparative approach, with findings from each phase informing subsequent phases. Results: The first three phases informed the structure, nature, and content of the follow-on support program, including the frequency of text messages, the need for tailored content and two-way interaction, the importance of motivational messages based on encouragement and reinforcement of affective benefits (eg, enjoyment) with minimal messages about weight and T2DM risk, and the need for appropriate language. The refined program is personalized and tailored to the individual’s perceived confidence, previous activity levels, and physical activity goals. The pilot phase indicated that the program appeared to fit well with everyday routines and was easy to use by older adults. Conclusions: We developed a feasible and innovative text messaging and pedometer program based on evidence and behavior change theory and grounded in the experiences, views, and needs of people at high diabetes risk. A large scale trial is testing the effectiveness of this 4-year program over and above structured group education alone. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 83465245; http://www.controlled-trials.com/ISRCTN83465245/83465245 (Archived by WebCite at http://www.webcitation.org/6dfSmrVAe) %M 26678750 %R 10.2196/mhealth.5026 %U http://mhealth.jmir.org/2015/4/e105/ %U https://doi.org/10.2196/mhealth.5026 %U http://www.ncbi.nlm.nih.gov/pubmed/26678750 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 3 %P e87 %T A Framework to Assist Health Professionals in Recommending High-Quality Apps for Supporting Chronic Disease Self-Management: Illustrative Assessment of Type 2 Diabetes Apps %A Hale,Kelli %A Capra,Sandra %A Bauer,Judith %+ Centre of Dietetics Research, School of Human Movement and Nutrition Sciences, University of Queensland, Building 26B, Cnr Blair & Union Rds, St Lucia, 4072, Australia, 61 7 3346 7703, k.hale@uq.edu.au %K mobile apps %K chronic disease %K patient-centered care %K technology %D 2015 %7 14.09.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: This paper presents an approach to assist health professionals in recommending high quality apps for supporting chronic disease self-management. Most app reviews focus on popularity, aesthetics, functionality, usability, and information quality. There is no doubt these factors are important in selecting trustworthy apps which are appealing to users, but behavioral theory may be also be useful in matching the apps to user needs. Objective: The framework developed aims to be methodologically sound, capable of selecting popular apps which include content covered by evidence-based programs, consistent with behavioral theory, as well as a patient-centered approach for matching apps to patients’ individual needs. Methods: A single disease—type 2 diabetes—was selected to illustrate how the framework can be applied as this was deemed to represent the types of strategies used in many chronic diseases. A systematic approach based on behavioral theory and recommendations from best practice guidelines was developed for matching apps to patients’ needs. In March 2014, a series of search strategies was used to identify top-rated iPhone and Android health apps, representing 29 topics from five categories of type 2 diabetes self-management strategies. The topics were chosen from published international guidelines for the management of diabetes. The senior author (KH) assessed the most popular apps found that addressed these topics using the Behavioral Theory Content Survey (BTS), which is based on traditional behavioral theory. A tool to assist decision making when using apps was developed and trialed with health professionals for ease of use and understanding. Results: A total of 14 apps were assessed representing all five topic categories of self-management. Total theoretical scores (BTS scores) were less than 50 on a 100-point scale for all apps. Each app scored less than 50% of the total possible BTS score for all four behavioral theories and for most of the 20 behavioral strategies; however, apps scored higher than 50% of the total possible BTS score for specific strategies related to their primary focus. Our findings suggest that the apps studied would be more effective when used in conjunction with therapy than as stand-alone apps. Apps were categorized according to topic and core intervention strategies. A framework for matching apps to identified patient needs was developed based on app categorization and principles of patient-centered care. The approach was well accepted and understood by a convenience sample of health practitioners. Conclusions: The framework presented can be used by health practitioners to better match apps with client needs. Some apps incorporate highly interactive strategies of behavioral theory, and when used as an adjunct may increase patient participation and the effectiveness of therapy. %M 26369346 %R 10.2196/mhealth.4532 %U http://mhealth.jmir.org/2015/3/e87/ %U https://doi.org/10.2196/mhealth.4532 %U http://www.ncbi.nlm.nih.gov/pubmed/26369346 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 3 %P e84 %T Popular Glucose Tracking Apps and Use of mHealth by Latinos With Diabetes: Review %A Williams,John Patrick %A Schroeder,Dirk %+ Hubert Department of Global Health, Rollins School of Public Health, Emory University, 4595 LaSalle Court, Marietta, GA, 30062, United States, 1 770 649 0298, dschroeder@holadoctor.net %K diabetes mellitus %K mobile health %K mobile applications %K systematic review %K Hispanic %D 2015 %7 25.08.2015 %9 Review %J JMIR mHealth uHealth %G English %X Background: Diabetes mellitus in the United States is an increasingly common chronic disease, costing hundreds of billions of dollars and contributing to hundreds of thousands of deaths each year. The prevalence of diabetes is over 50% higher in Latinos than in the general population, and this group also suffers from higher rates of complications and diabetes-related mortality than NHWs. mHealth is a promising new treatment modality for diabetes, though few smartphone apps have been designed specifically for Latinos. Objective: The objectives of our study were: (1) to identify the most common features of the most popular diabetes apps and consider how such features may be improved to meet the needs of Latinos; (2) to determine the use of diabetes apps among a sample of online Hispanics in the US. Methods: Our study consisted of two parts. First, 20 of the most popular diabetes apps were reviewed in order to ascertain the most prevalent features and functionalities. Second, an online survey was fielded through a popular health website for Latinos (HolaDoctor) inquiring about respondents’ use of diabetes apps. Results: Approximately one-third of apps reviewed were available in Spanish. The most common features were blood glucose recording/annotation and activity logs. The majority of apps permitted exportation of data via e-mail but only a third enabled uploading to an online account. Twenty percent of apps reviewed could connect directly with a glucometer, and 30% had reminder functionalities prompting patients to take medications or check blood glucose levels. Over 1600 online surveys were completed during the second half of April 2014. More than 90% of respondents were from the United States, including Puerto Rico. The majority of respondents used a device running on an Android platform while only a quarter used an iPhone. Use of diabetes apps was approximately 3% among diabetic respondents and 3.6% among diabetic respondents who also had a smartphone. Among app users, blood glucose and medication diaries were the most frequently used functionalities while hemoglobin A1c and insulin diaries were the least used. A significant majority of app users did not share their progress on social media though many of these were willing to share it with their doctor. Conclusions: Latino diabetics have unique needs and this should be reflected in diabetes apps designed for this population. Existing research as well as our survey results suggest that many Latinos do not possess the prerequisite diabetes knowledge or self-awareness to fully benefit from the most prevalent functionalities offered by the most popular diabetes apps. We recommend developers incorporate more basic features such as diabetes education, reminders to check blood glucose levels or take medications, Spanish language interfaces, and glucometer connectivities, which are relatively underrepresented in the most popular diabetes apps currently available in Spanish. %M 26307533 %R 10.2196/mhealth.3986 %U http://mhealth.jmir.org/2015/3/e84/ %U https://doi.org/10.2196/mhealth.3986 %U http://www.ncbi.nlm.nih.gov/pubmed/26307533 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 3 %N 1 %P e32 %T Diabetes Text-Message Self-Management Support Program (SMS4BG): A Pilot Study %A Dobson,Rosie %A Carter,Karen %A Cutfield,Richard %A Hulme,Ashley %A Hulme,Richard %A McNamara,Catherine %A Maddison,Ralph %A Murphy,Rinki %A Shepherd,Matthew %A Strydom,Johan %A Whittaker,Robyn %+ National Institute for Health Innovation, School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, National Institute for Health Innovation, School of Population Health, University of Auckland, Tamaki Campus,, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand, Auckland, , New Zealand, 64 9 3737599 ext 84766, r.dobson@auckland.ac.nz %K mHealth %K diabetes mellitus %K text message %K mobile phone %K SMS %K self-management %D 2015 %7 25.03.2015 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: The increasing prevalence of diabetes and costly long-term complications associated with poor glycemic control are issues facing health services worldwide. Diabetes self-management, with the support of health care providers, is critical for successful outcomes, however, frequent clinical contact is costly. Text messages via short message service (SMS) have the advantage of instant transmission at low cost and, given the ubiquity of mobile phones, may be the ideal platform for the delivery of diabetes self-management support. A tailored text message-based diabetes support intervention called Self-Management Support for Blood Glucose (SMS4BG) was developed. The intervention incorporates prompts around diabetes education, management, and lifestyle factors (healthy eating, exercise, and stress management), as well as blood glucose monitoring reminders, and is tailored to patient preferences and clinical characteristics. Objective: To determine the usability and acceptability of SMS4BG among adults with poorly controlled diabetes. Methods: Adults (aged 17 to 69 years) with type 1 (n=12) or type 2 diabetes (n=30), a hemoglobin A1c (HbA1c) over 70 mmol/mol (8.6%), and who owned a mobile phone (n=42) were recruited to take part in a 3-month pilot study of SMS4BG. At registration, participants selected the modules they would like to receive and, where appropriate, the frequency and timing of blood glucose monitoring reminders. Patient satisfaction and perceptions of the usability of the program were obtained via semistructured phone interviews conducted at completion of the pilot study. HbA1c was obtained from patient records at baseline and completion of the pilot study. Results: Participants received on average 109 messages during the 3-month program with 2 participants withdrawing early from the study. Follow-up interviews were completed with 93% of participants with all reporting SMS4BG to be useful and appropriate to their age and culture. Participants reported a range of perceived positive impacts of SMS4BG on their diabetes and health behaviors. HbA1c results indicated a positive impact of the program on glycemic control with a significant decrease in HbA1c from baseline to follow-up. Conclusions: A tailored text message-based intervention is both acceptable and useful in supporting self-management in people with poorly controlled diabetes. A randomized controlled trial of longer duration is needed to assess the efficacy and sustainability of SMS4BG. %M 25830952 %R 10.2196/mhealth.3988 %U http://mhealth.jmir.org/2015/1/e32/ %U https://doi.org/10.2196/mhealth.3988 %U http://www.ncbi.nlm.nih.gov/pubmed/25830952 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 2 %N 4 %P e57 %T A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH %A Holmen,Heidi %A Torbjørnsen,Astrid %A Wahl,Astrid Klopstad %A Jenum,Anne Karen %A Småstuen,Milada Cvancarova %A Årsand,Eirik %A Ribu,Lis %+ Department of Nursing, Faculty of Health Sciences, Oslo and Akershus University College of Applied Sciences, PB 4 St.Olavs Plass, Oslo, 0130, Norway, 47 90580017, Heidi.Holmen@hioa.no %K self-care %K mobile applications %K cellular phone %K telemedicine %K counseling %K motivational interviewing %K diabetes mellitus, type 2 %K hemoglobin A1c protein, human %D 2014 %7 11.12.2014 %9 Original Paper %J JMIR mHealth uHealth %G English %X Background: Self-management is crucial in the daily management of type 2 diabetes. It has been suggested that mHealth may be an important method for enhancing self-management when delivered in combination with health counseling. Objective: The objective of this study was to test whether the use of a mobile phone–based self-management system used for 1 year, with or without telephone health counseling by a diabetes specialist nurse for the first 4 months, could improve glycated hemoglobin A1c (HbA1c) level, self-management, and health-related quality of life compared with usual care. Methods: We conducted a 3-arm prospective randomized controlled trial involving 2 intervention groups and 1 control group. Eligible participants were persons with type 2 diabetes with an HbA1c level ≥7.1% (≥54.1 mmol/mol) and aged ≥18 years. Both intervention groups received the mobile phone–based self-management system Few Touch Application (FTA). The FTA consisted of a blood glucose–measuring system with automatic wireless data transfer, diet manual, physical activity registration, and management of personal goals, all recorded and operated using a diabetes diary app on the mobile phone. In addition, one intervention group received health counseling based on behavior change theory and delivered by a diabetes specialist nurse for the first 4 months after randomization. All groups received usual care by their general practitioner. The primary outcome was HbA1c level. Secondary outcomes were self-management (heiQ), health-related quality of life (SF-36), depressive symptoms (CES-D), and lifestyle changes (dietary habits and physical activity). Data were analyzed using univariate methods (t test, ANOVA) and multivariate linear and logistic regression. Results: A total of 151 participants were randomized: 51 to the FTA group, 50 to the FTA-health counseling (FTA-HC) group, and 50 to the control group. Follow-up data after 1 year were available for 120 participants (79%). HbA1c level decreased in all groups, but did not differ between groups after 1 year. The mean change in the heiQ domain skills and technique acquisition was significantly greater in the FTA-HC group after adjusting for age, gender, and education (P=.04). Other secondary outcomes did not differ between groups after 1 year. In the FTA group, 39% were substantial users of the app; 34% of the FTA-HC group were substantial users. Those aged ≥63 years used the app more than their younger counterparts did (OR 2.7; 95% CI 1.02-7.12; P=.045). Conclusions: The change in HbA1c level did not differ between groups after the 1-year intervention. Secondary outcomes did not differ between groups except for an increase in the self-management domain of skill and technique acquisition in the FTA-HC group. Older participants used the app more than the younger participants did. %M 25499872 %R 10.2196/mhealth.3882 %U http://mhealth.jmir.org/2014/4/e57/ %U https://doi.org/10.2196/mhealth.3882 %U http://www.ncbi.nlm.nih.gov/pubmed/25499872 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 1 %N 2 %P e12 %T Ideas and Enhancements Related to Mobile Applications to Support Type 1 Diabetes %A Pulman,Andy %A Taylor,Jacqui %A Galvin,Kathleen %A Masding,Mike %+ The School of Health & Social Care, Bournemouth University, R109, Royal London House, Christchurch Road, Bournemouth, BH1 3LT, United Kingdom, 44 1202 962749, apulman@bournemouth.ac.uk %K patient education %K type 1 diabetes %K mobile %K apps %K sociotechnical design %K lifeworld %K humanising healthcare %K patient voice %K empathy %K ideas %K enhancements %D 2013 %7 25.07.2013 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Mobile devices have become increasingly important to young people who now use them to access a wide variety of health-related information. Research and policy related to the integration of health information and support with this technology do not effectively consider the viewpoint of a younger patient. Views of young people with type 1 diabetes are vital in developing quality services and improving their own health-related quality of life (HRQOL), yet research on their lifestyle and use of Web and mobile technology to support their condition and in non–health-related areas is sparse. Objective: To develop insight into young people with type 1 diabetes and their current use of Web and mobile technology and its potential impact on HRQOL. This can be achieved by constructing an in-depth picture of their day-to-day experiences from qualitative interviewing and exploring how they make use of technology in their lives and in relation to their condition and treatment. The goal was then to build something to help them, using the researcher’s technical expertise and seeking users’ opinions during the design and build, utilizing sociotechnical design principles. Methods: Data were collected by semistructured, in-depth qualitative interviews (N=9) of young people with type 1 diabetes aged 18-21. Interviews were transcribed and loaded onto NVivo for theme identification. Data analysis was undertaken during initial interviews (n=4) to locate potential ideas and enhancements for technical development. Latter interviews (n=5) assisted in the iterative sociotechnical design process of the development and provided additional developmental ideas. Results: Six themes were identified providing an understanding of how participants lived with and experienced their condition and how they used technology. Four technological suggestions for improvement were taken forward for prototyping. One prototype was developed as a clinically approved app. A number of ideas for new mobile apps and enhancements to currently existing apps that did not satisfactorily cater to this age group’s requirements for use in terms of design and functionality were suggested by interviewees but were not prototyped. Conclusions: This paper outlines the nonprototyped suggestions from interviewees and argues that young people with type 1 diabetes have a key role to play in the design and implementation of new technology to support them and improve HRQOL. It is vital to include and reflect on their suggestions as they have a radically different view of technology than either their parents or practitioners. We need to consider the relationship to technology that young people with type 1 diabetes have, and then reflect on how this might make a difference to them and when it might not be a suitable mechanism to use. %M 25100684 %R 10.2196/mhealth.2567 %U http://mhealth.jmir.org/2013/2/e12/ %U https://doi.org/10.2196/mhealth.2567 %U http://www.ncbi.nlm.nih.gov/pubmed/25100684 %0 Journal Article %@ 2291-5222 %I JMIR Publications Inc. %V 1 %N 1 %P e1 %T Long-Term Engagement With a Mobile Self-Management System for People With Type 2 Diabetes %A Tatara,Naoe %A Årsand,Eirik %A Skrøvseth,Stein Olav %A Hartvigsen,Gunnar %+ Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Sykehusveien 23, P.O. Box 35, Tromsø, 9038, Norway, 47 07766, naoe.tatara@telemed.no %K Type 2 diabetes %K self-management %K user-involved design process %K mobile phone %K usage %K usability %K mHealth %D 2013 %7 27.03.2013 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: In a growing number of intervention studies, mobile phones are used to support self-management of people with Type 2 diabetes mellitus (T2DM). However, it is difficult to establish knowledge about factors associated with intervention effects, due to considerable differences in research designs and outcome measures as well as a lack of detailed information about participants’ engagement with the intervention tool. Objective: To contribute toward accumulating knowledge about factors associated with usage and usability of a mobile self-management application over time through a thorough analysis of multiple types of investigation on each participant’s engagement. Methods: The Few Touch application is a mobile-phone–based self-management tool for patients with T2DM. Twelve patients with T2DM who have been actively involved in the system design used the Few Touch application in a real-life setting from September 2008 until October 2009. During this period, questionnaires and semistructured interviews were conducted. Recorded data were analyzed to investigate usage trends and patterns. Transcripts from interviews were thematically analyzed, and the results were further analyzed in relation to the questionnaire answers and the usage trends and patterns. Results: The Few Touch application served as a flexible learning tool for the participants, responsive to their spontaneous needs, as well as supporting regular self-monitoring. A significantly decreasing (P<.05) usage trend was observed among 10 out of the 12 participants, though the magnitude of the decrease varied widely. Having achieved a sense of mastery over diabetes and experiences of problems were identified as reasons for declining motivation to continue using the application. Some of the problems stemmed from difficulties in integrating the use of the application into each participant’s everyday life and needs, although the design concepts were developed in the process where the participants were involved. The following factors were identified as associated with usability and/or usage over time: Integration with everyday life; automation; balance between accuracy and meaningfulness of data with manual entry; intuitive and informative feedback; and rich learning materials, especially about foods. Conclusion: Many grounded design implications were identified through a thorough analysis of results from multiple types of investigations obtained through a year-long field trial of the Few Touch application. The study showed the importance and value of involving patient-users in a long-term trial of a tool to identify factors influencing usage and usability over time. In addition, the study confirmed the importance of detailed analyses of each participant’s usage of the provided tool for better understanding of participants’ engagement over time. %M 25100649 %R 10.2196/mhealth.2432 %U http://mhealth.jmir.org/2013/1/e1/ %U https://doi.org/10.2196/mhealth.2432 %U http://www.ncbi.nlm.nih.gov/pubmed/25100649