Published on in Vol 7, No 9 (2019): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12956, first published .
Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial

Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial

Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial

Journals

  1. Jung M, Locke S, Bourne J, Beauchamp M, Lee T, Singer J, MacPherson M, Barry J, Jones C, Little J. Cardiorespiratory fitness and accelerometer-determined physical activity following one year of free-living high-intensity interval training and moderate-intensity continuous training: a randomized trial. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1) View
  2. Stassen G, Grieben C, Froböse I, Schaller A. Engagement with a Web-Based Health Promotion Intervention among Vocational School Students: A Secondary User and Usage Analysis. International Journal of Environmental Research and Public Health 2020;17(7):2180 View
  3. Aekplakorn W, Suriyawongpaisal P, Srithamrongsawadi S, Kaewkamjonchai P. Assessing a national policy on strengthening chronic care in primary care settings of a middle-income country using patients’ perspectives. BMC Health Services Research 2021;21(1) View
  4. MacPherson M, Merry K, Locke S, Jung M. Developing Mobile Health Interventions With Implementation in Mind: Application of the Multiphase Optimization Strategy (MOST) Preparation Phase to Diabetes Prevention Programming. JMIR Formative Research 2022;6(4):e36143 View
  5. Weber M, Ziolkowski S, Bootwala A, Bienvenida A, Anand S, Lobelo F. Perceptions of physical activity and technology enabled exercise interventions among people with advanced chronic kidney disease: a qualitative study. BMC Nephrology 2021;22(1) View
  6. MacPherson M, Cranston K, Johnston C, Locke S, Jung M. Evaluation and Refinement of a Bank of SMS Text Messages to Promote Behavior Change Adherence Following a Diabetes Prevention Program: Survey Study. JMIR Formative Research 2021;5(8):e28163 View
  7. Agachi E, Bijmolt T, van Ittersum K, Mierau J. The Effect of Periodic Email Prompts on Participant Engagement With a Behavior Change mHealth App: Longitudinal Study. JMIR mHealth and uHealth 2023;11:e43033 View
  8. Hesketh K, Low J, Andrews R, Jones C, Jones H, Jung M, Little J, Mateus C, Pulsford R, Singer J, Sprung V, McManus A, Cocks M. Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): protocol for a feasibility randomised controlled trial. BMJ Open 2021;11(11):e052563 View
  9. Wang H, Ho A, Wiener R, Sambamoorthi U. The Association of Mobile Health Applications with Self-Management Behaviors among Adults with Chronic Conditions in the United States. International Journal of Environmental Research and Public Health 2021;18(19):10351 View
  10. MacPherson M, Merry K, Locke S, Jung M. How Can We Keep People Engaged in the Behavior Change Process? An Exploratory Analysis of Two mHealth Applications. Journal of Technology in Behavioral Science 2022;7(3):337 View
  11. Graham S, Pitter V, Hori J, Stein N, Branch O. Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence. DIGITAL HEALTH 2022;8:205520762211306 View
  12. Yang A, Singh N, Varshney U. Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework. Journal of Medical Systems 2022;46(10) View
  13. Cheng Y, Hsu T, Fried J, Chao P. Are we Ready to be e-Social Service Practitioners for Older Adults? Potential of Taiwanese Social Service College Students. IEEE Access 2022;10:52451 View
  14. Wiegel J, Seppen B, Nurmohamed M, ter Wee M, Bos W. Predictors for response to electronic patient-reported outcomes in routine care in patients with rheumatoid arthritis: a retrospective cohort study. Rheumatology International 2023;43(4):651 View
  15. Stecher C, Cloonan S, Linnemayr S, Huberty J. Combining Behavioral Economics–Based Incentives With the Anchoring Strategy: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2023;12:e39930 View
  16. Shanmugavel A, Shakya P, Shrestha A, Nepal J, Shrestha A, Daneault J, Rawal S. Designing and Developing a Mobile App for Management and Treatment of Gestational Diabetes in Nepal: User-Centered Design Study. JMIR Formative Research 2024;8:e50823 View
  17. Di Martino G, della Valle C, Centorbi M, Buonsenso A, Fiorilli G, Calcagno G, Iuliano E, di Cagno A. Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity. International Journal of Environmental Research and Public Health 2024;21(2):233 View
  18. Smith-Turchyn J, Mukherjee S, Tomasone J, Fong A, Nayiga B, Ball E, Stouth D, Sabiston C. Evaluating Wall-Mounted Prompts to Facilitate Physical Activity-Related Discussion between Individuals with Cancer and Oncology Health Care Providers: A Pre-post Survey Study. Physiotherapy Canada 2024;76(1):34 View
  19. Fundoiano-Hershcovitz ‪, Ritholz M, Horwitz D, Behar E, Manejwala O, Goldstein P. The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study. Journal of Medical Internet Research 2024;26:e54940 View
  20. Ang G, Tan C, Lim N, Tan J, Müller-Riemenschneider F, Cook A, Chen C. Hourly step recommendations to achieve daily goals for working and older adults. Communications Medicine 2024;4(1) View

Books/Policy Documents

  1. Ofori M, El-Gayar O. Optimizing Health Monitoring Systems With Wireless Technology. View