Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at, first published .
Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study


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  2. Zulj S, Carvalho P, Ribeiro R, Andrade R, Magjarevic R. Data size considerations and hyperparameter choices in case-based reasoning approach to glucose prediction. Biocybernetics and Biomedical Engineering 2021;41(2):733 View
  3. Li J, Yu K, Bao X, Liu X, Yao J. Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study. Journal of Medical Internet Research 2021;23(8):e29299 View
  4. Kwan Y, Ong Z, Choo D, Phang J, Yoon S, Low L. A Mobile Application to Improve Diabetes Self-Management Using Rapid Prototyping: Iterative Co-Design Approach in Asian Settings. Patient Preference and Adherence 2023;Volume 17:1 View
  5. Fu H, Wyman J, Peden-McAlpine C, Draucker C, Schleyer T, Adam T. App Design Features Important for Diabetes Self-management as Determined by the Self-Determination Theory on Motivation: Content Analysis of Survey Responses From Adults Requiring Insulin Therapy. JMIR Diabetes 2023;8:e38592 View
  6. Wiegel J, Seppen B, Nurmohamed M, Bos W, ter Wee M. Who stop telemonitoring disease activity and who adhere: a prospective cohort study of patients with inflammatory arthritis. BMC Rheumatology 2022;6(1) View
  7. Kim S, Stanton K, Park Y, Thomas S. A Mobile App for Children With Asthma to Monitor Indoor Air Quality (AirBuddy): Development and Usability Study. JMIR Formative Research 2022;6(5):e37118 View
  8. Lim S, Tay M, Ong K, Johal J, Yap Q, Chan Y, Yeo G, Khoo C, Yaxley A. Association Between Mobile Health App Engagement and Weight Loss and Glycemic Control in Adults With Type 2 Diabetes and Prediabetes (D’LITE Study): Prospective Cohort Study. JMIR Diabetes 2022;7(3):e35039 View
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  10. Sheng Y, Doyle J, Bond R, Jaiswal R, Gavin S, Dinsmore J. Home-based digital health technologies for older adults to self-manage multiple chronic conditions: A data-informed analysis of user engagement from a longitudinal trial. DIGITAL HEALTH 2022;8:205520762211259 View
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  12. Kruse C, Mileski M, Heinemann K, Huynh H, Leafblad A, Moreno E. Analyzing the Effectiveness of mHealth to Manage Diabetes Mellitus Among Adults Over 50: A Systematic Literature Review. Journal of Multidisciplinary Healthcare 2023;Volume 16:101 View
  13. Kytö M, Markussen L, Marttinen P, Jacucci G, Niinistö S, Virtanen S, Korhonen T, Sievänen H, Vähä-Ypyä H, Korhonen I, Heinonen S, Koivusalo S. Comprehensive self-tracking of blood glucose and lifestyle with a mobile application in the management of gestational diabetes: a study protocol for a randomised controlled trial (eMOM GDM study). BMJ Open 2022;12(11):e066292 View
  14. Clements M, Kaufman N, Mel E. Using Digital Health Technology to Prevent and Treat Disease. Diabetes Technology & Therapeutics 2022;24(S1):S-76 View
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  16. Petracca F, Tempre R, Cucciniello M, Ciani O, Pompeo E, Sannino L, Lovato V, Castaman G, Ghirardini A, Tarricone R. An Electronic Patient-Reported Outcome Mobile App for Data Collection in Type A Hemophilia: Design and Usability Study. JMIR Formative Research 2021;5(12):e25071 View
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  18. Rennie K, Lawlor E, Yassaee A, Booth A, Westgate K, Sharp S, Tyrrell C, Aral M, Wareham N. Engagement With mHealth COVID-19 Digital Biomarker Measurements in a Longitudinal Cohort Study: Mixed Methods Evaluation. Journal of Medical Internet Research 2023;25:e40602 View
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Books/Policy Documents

  1. Ikwunne T, Hederman L, Wall P. Co-creating for Context in the Transfer and Diffusion of IT. View
  2. Ruckau S, Schneider A, Rösch-Lehmann A. Gestaltung des Wandels im Dienstleistungsmanagement. View