Published on in Vol 6, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10123, first published .
To Prompt or Not to Prompt? A Microrandomized Trial of Time-Varying Push Notifications to Increase Proximal Engagement With a Mobile Health App

To Prompt or Not to Prompt? A Microrandomized Trial of Time-Varying Push Notifications to Increase Proximal Engagement With a Mobile Health App

To Prompt or Not to Prompt? A Microrandomized Trial of Time-Varying Push Notifications to Increase Proximal Engagement With a Mobile Health App

Journals

  1. Yang X, Ma L, Zhao X, Kankanhalli A. Factors influencing user’s adherence to physical activity applications: A scoping literature review and future directions. International Journal of Medical Informatics 2020;134:104039 View
  2. Szinay D, Jones A, Chadborn T, Brown J, Naughton F. Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review. Journal of Medical Internet Research 2020;22(5):e17572 View
  3. 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
  4. Güreş N, Arslan S, Yüksel C, Yılmaz H. MOBİL UYGULAMAYA SAHİP HAVAYOLU İŞLETMELERİNİN YOLCULARA YÖNELİK HİZMETLERİNİN ARAŞTIRILMASI. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 2019 View
  5. Issom D, Henriksen A, Woldaregay A, Rochat J, Lovis C, Hartvigsen G. Factors Influencing Motivation and Engagement in Mobile Health Among Patients With Sickle Cell Disease in Low-Prevalence, High-Income Countries: Qualitative Exploration of Patient Requirements. JMIR Human Factors 2020;7(1):e14599 View
  6. Røed M, Vik F, Hillesund E, Van Lippevelde W, Medin A, Øverby N. Process Evaluation of an eHealth Intervention (Food4toddlers) to Improve Toddlers' Diet: Randomized Controlled Trial. JMIR Human Factors 2020;7(3):e18171 View
  7. Nordstoga A, Bach K, Sani S, Wiratunga N, Mork P, Villumsen M, Cooper K. Usability and Acceptability of an App (SELFBACK) to Support Self-Management of Low Back Pain: Mixed Methods Study. JMIR Rehabilitation and Assistive Technologies 2020;7(2):e18729 View
  8. Li S, Psihogios A, McKelvey E, Ahmed A, Rabbi M, Murphy S. Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example. Current Opinion in Systems Biology 2020;21:1 View
  9. Bidargaddi N, Schrader G, Klasnja P, Licinio J, Murphy S. Designing m-Health interventions for precision mental health support. Translational Psychiatry 2020;10(1) View
  10. Güreş N, Arslan S, Yüksel C, Yılmaz H. MOBİL UYGULAMAYA SAHİP HAVAYOLU İŞLETMELERİNİN YOLCULARA YÖNELİK HİZMETLERİNİN ARAŞTIRILMASI. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 2019 View
  11. Carleton K, Patel U, Stein D, Mou D, Mallow A, Blackmore M. Enhancing the scalability of the collaborative care model for depression using mobile technology. Translational Behavioral Medicine 2020;10(3):573 View
  12. Quinn C, Hides L, de Andrade D, Pocuca N, Wilson M, Kavanagh D. Impact of a brief psychoeducational intervention for reducing alcohol use and related harm in school leavers. Drug and Alcohol Review 2019;38(4):339 View
  13. NeCamp T, Sen S, Frank E, Walton M, Ionides E, Fang Y, Tewari A, Wu Z. Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial. Journal of Medical Internet Research 2020;22(3):e15033 View
  14. White B, Giglia R, White J, Dhaliwal S, Burns S, Scott J. Gamifying Breastfeeding for Fathers: Process Evaluation of the Milk Man Mobile App. JMIR Pediatrics and Parenting 2019;2(1):e12157 View
  15. Ziesemer K, König L, Boushey C, Villinger K, Wahl D, Butscher S, Müller J, Reiterer H, Schupp H, Renner B. Occurrence of and Reasons for “Missing Events” in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies. JMIR mHealth and uHealth 2020;8(10):e15430 View
  16. Psihogios A, Li Y, Butler E, Hamilton J, Daniel L, Barakat L, Bonafide C, Schwartz L. Text Message Responsivity in a 2-Way Short Message Service Pilot Intervention With Adolescent and Young Adult Survivors of Cancer. JMIR mHealth and uHealth 2019;7(4):e12547 View
  17. Bell L, Garnett C, Qian T, Perski O, Potts H, Williamson E. Notifications to Improve Engagement With an Alcohol Reduction App: Protocol for a Micro-Randomized Trial. JMIR Research Protocols 2020;9(8):e18690 View
  18. Hanghøj S, Boisen K, Hjerming M, Pappot H. Adolescents’ and young adults’ experiences of a prototype cancer smartphone app. DIGITAL HEALTH 2021;7:205520762199725 View
  19. Qian T, Yoo H, Klasnja P, Almirall D, Murphy S. Estimating time-varying causal excursion effects in mobile health with binary outcomes. Biometrika 2021;108(3):507 View
  20. Venning A, Herd M, Oswald T, Razmi S, Glover F, Hawke T, Quartermain V, Redpath P. Exploring the acceptability of a digital mental health platform incorporating a virtual coach: The good, the bad, and the opportunities. Health Informatics Journal 2021;27(1):146045822199487 View
  21. Bell L, Garnett C, Qian T, Perski O, Williamson E, Potts H. Engagement With a Behavior Change App for Alcohol Reduction: Data Visualization for Longitudinal Observational Study. Journal of Medical Internet Research 2020;22(12):e23369 View
  22. Valle C, Nezami B, Tate D. Designing in-app messages to nudge behavior change: Lessons learned from a weight management app for young adults. Organizational Behavior and Human Decision Processes 2020;161:95 View
  23. Dempsey W, Liao P, Kumar S, Murphy S. The stratified micro-randomized trial design: Sample size considerations for testing nested causal effects of time-varying treatments. The Annals of Applied Statistics 2020;14(2) View
  24. Wei Y, Zheng P, Deng H, Wang X, Li X, Fu H. Design Features for Improving Mobile Health Intervention User Engagement: Systematic Review and Thematic Analysis. Journal of Medical Internet Research 2020;22(12):e21687 View
  25. Baumel A, Fleming T, Schueller S. Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care. Journal of Medical Internet Research 2020;22(10):e20631 View
  26. Wang C, Qi H. Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review. Healthcare 2021;9(3):357 View
  27. Zhang Z, Miehle J, Matsuda Y, Fujimoto M, Arakawa Y, Yasumoto K, Minker W. Exploring the Impacts of Elaborateness and Indirectness in a Behavior Change Support System. IEEE Access 2021;9:74778 View
  28. Muijs L, de Wit M, Knoop H, Snoek F. Feasibility and user experience of the unguided web-based self-help app ‘MyDiaMate’ aimed to prevent and reduce psychological distress and fatigue in adults with diabetes. Internet Interventions 2021;25:100414 View
  29. Dinkel D, Harsh Caspari J, Fok L, Notice M, Johnson D, Watanabe-Galloway S, Emerson M. A qualitative exploration of the feasibility of incorporating depression apps into integrated primary care clinics. Translational Behavioral Medicine 2021 View
  30. Rüther D, Sebode M, Lohse A, Wernicke S, Böttinger E, Casar C, Braun F, Schramm C. Mobile app requirements for patients with rare liver diseases: A single center survey for the ERN RARE-LIVER‬‬‬. Clinics and Research in Hepatology and Gastroenterology 2021;45(6):101760 View

Books/Policy Documents

  1. El‐Toukhy S, Nahum‐Shani I. Wiley StatsRef: Statistics Reference Online. View