This paper is in the following e-collection/theme issue:

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (491) Apps, Mobile, Wearables for Diabetes (298)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22212, 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

Authors of this article:

Anna-Katharina Böhm1 Author Orcid Image ;   Morten Lind Jensen2 Author Orcid Image ;   Mads Reinholdt Sørensen2 Author Orcid Image ;   Tom Stargardt1 Author Orcid Image
Article Authors Cited by (33) Tweetations (6) Metrics

Journals

  1. Akturk H, Dowd R, Shankar K, Derdzinski M. Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features. Diabetes Technology & Therapeutics 2021;23(S1):S-21 View
  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
  9. Burda V, Mráz M, Schneider J, Novák D. Managing Diabetes Using Mobiab: Long-Term Case Study of the Impact of a Mobile App on Self-management. JMIR Diabetes 2022;7(2):e36675 View
  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
  11. Oakley-Girvan I, Docherty J. A New Approach to Enhancing Engagement in eHealth Apps. Interactive Journal of Medical Research 2022;11(2):e38886 View
  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
  15. Stephen D, Nordin A, Nilsson J, Persenius M. Using mHealth applications for self-care – An integrative review on perceptions among adults with type 1 diabetes. BMC Endocrine Disorders 2022;22(1) View
  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
  17. Jakob R, Harperink S, Rudolf A, Fleisch E, Haug S, Mair J, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. Journal of Medical Internet Research 2022;24(5):e35371 View
  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
  19. Doyle J, Murphy E, Gavin S, Pascale A, Deparis S, Tommasi P, Smith S, Hannigan C, Sillevis Smitt M, van Leeuwen C, Lastra J, Galvin M, McAleer P, Tompkins L, Jacobs A, M Marques M, Medina Maestro J, Boyle G, Dinsmore J. A Digital Platform to Support Self-management of Multiple Chronic Conditions (ProACT): Findings in Relation to Engagement During a One-Year Proof-of-Concept Trial. Journal of Medical Internet Research 2021;23(12):e22672 View
  20. Blythin A, Elkes J, van Lindholm T, Bhogal A, Wilkinson T, Saville C, Kirk A. Can digital health apps provide patients with support to promote structured diabetes education and ongoing self-management? A real-world evaluation of myDiabetes usage. DIGITAL HEALTH 2023;9 View
  21. Collier A, Hagemann S, Trinidad S, Vigil-Hayes M. Human-to-Computer Interactivity Features Incorporated Into Behavioral Health mHealth Apps: Systematic Search. JMIR Formative Research 2023;7:e44926 View
  22. Wang R, Rouleau G, Booth G, Brazeau A, El-Dassouki N, Taylor M, Cafazzo J, Greenberg M, Nakhla M, Shulman R, Desveaux L. Understanding Whether and How a Digital Health Intervention Improves Transition Care for Emerging Adults Living With Type 1 Diabetes: Protocol for a Mixed Methods Realist Evaluation. JMIR Research Protocols 2023;12:e46115 View
  23. Hamideh Kerdar S, Gwiasda M, Berger B, Rathjens L, Schwarz S, Jenetzky E, Martin D. Predictors of sustained use of mobile health applications: Content analysis of user perspectives from a fever management app. DIGITAL HEALTH 2023;9 View
  24. Kytö M, Koivusalo S, Tuomonen H, Strömberg L, Ruonala A, Marttinen P, Heinonen S, Jacucci G. Supporting the Management of Gestational Diabetes Mellitus With Comprehensive Self-Tracking: Mixed Methods Study of Wearable Sensors. JMIR Diabetes 2023;8:e43979 View
  25. Brown C, Roucoux G, Rousset-Torrente O, Ali S, Yombo-Kokule L, Chaplin J, Chassany O, Duracinsky M. Fostering Patient-Clinician Communication to Promote Rapid HIV, Hepatitis B Virus, and Hepatitis C Virus Diagnostic Testing: Conceptual Development of a Multilingual App. JMIR Formative Research 2023;7:e49251 View
  26. Tripathi D, Vikram N, Chaturvedi S, Bhatia N. Development of “DiabetesSutra” a mobile application for lifestyle management of Type 2 Diabetes in India. Journal of Diabetes & Metabolic Disorders 2023;23(1):709 View
  27. Sheng Y, Bond R, Jaiswal R, Dinsmore J, Doyle J. Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial. Journal of Medical Internet Research 2024;26:e46287 View
  28. Tarricone R, Petracca F, Svae L, Cucciniello M, Ciani O. Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials. eBioMedicine 2024;103:105091 View
  29. Kytö M, Hotta S, Niinistö S, Marttinen P, Korhonen T, Markussen L, Jacucci G, Sievänen H, Vähä-Ypyä H, Korhonen I, Virtanen S, Heinonen S, Koivusalo S. Periodic mobile application (eMOM) with self-tracking of glucose and lifestyle improves treatment of diet-controlled gestational diabetes without human guidance: a randomized controlled trial. American Journal of Obstetrics and Gynecology 2024;231(5):541.e1 View
  30. Piette J, Lee K, Bosworth H, Isaacs D, Cerrada C, Kainkaryam R, Liska J, Lee F, Kennedy A, Kerr D. Behavioral Engagement and Activation Model Study (BEAMS): A latent class analysis of adopters and non-adopters of digital health technologies among people with Type 2 diabetes. Translational Behavioral Medicine 2024;14(8):491 View

Books/Policy Documents

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