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

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  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
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  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
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  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
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  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
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  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;11(9):1708 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
  31. Workman A, Johnston F, Campbell S, Williamson G, Lucani C, Bowman D, Cooling N, Jones P. Evaluating User Preferences, Comprehension, and Trust in Apps for Environmental Health Hazards: Qualitative Case Study. JMIR Formative Research 2022;6(12):e38471 View
  32. Li S, Halabi R, Selvarajan R, Woerner M, Fillipo I, Banerjee S, Mosser B, Jain F, Areán P, Pratap A. Recruitment and Retention in Remote Research: Learnings From a Large, Decentralized Real-world Study. JMIR Formative Research 2022;6(11):e40765 View
  33. Nahum-Shani I, Dziak J, Wetter D. MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions. Frontiers in Digital Health 2022;4 View
  34. Lindsay N, Baker T, Calder-Dawe O. Mental coaching through crisis: digital technologies and psychological governance during COVID-19. Critical Public Health 2022;32(1):104 View
  35. Burke L, Sereika S, Bizhanova Z, Parmanto B, Kariuki J, Cheng J, Beatrice B, Cedillo M, Pulantara I, Wang Y, Loar I, Conroy M. The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial. Journal of Medical Internet Research 2022;24(7):e38243 View
  36. Stewart C, Ranjan Y, Conde P, Rashid Z, Sankesara H, Bai X, Dobson R, Folarin A. Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study). JMIR Research Protocols 2021;10(12):e32587 View
  37. Moon K, Sobolev M, Grella M, Alvarado G, Sapra M, Ball T. An mHealth Platform for Augmenting Behavioral Health in Primary Care: Longitudinal Feasibility Study. JMIR Formative Research 2022;6(7):e36021 View
  38. Gan D, McGillivray L, Larsen M, Christensen H, Torok M. Technology-supported strategies for promoting user engagement with digital mental health interventions: A systematic review. DIGITAL HEALTH 2022;8:205520762210982 View
  39. Phatsoane Gaven M, Quaife M, Majam M, Singh L, Rhagnath N, Wonderlik T, Gumede S. HIV self-test reporting using mHealth platforms: A pilot study in Johannesburg, South Africa. Frontiers in Reproductive Health 2023;5 View
  40. Domin A, Uslu A, Schulz A, Ouzzahra Y, Vögele C. A Theory-Informed, Personalized mHealth Intervention for Adolescents (Mobile App for Physical Activity): Development and Pilot Study. JMIR Formative Research 2022;6(6):e35118 View
  41. Trinquart L, Liu C, McManus D, Nowak C, Lin H, Spartano N, Borrelli B, Benjamin E, Murabito J. Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial. Journal of Medical Internet Research 2023;25:e40784 View
  42. Carvalho C, Prando B, Dantas L, Serrão P. Mobile health technologies for the management of spine disorders: A systematic review of mHealth applications in Brazil. Musculoskeletal Science and Practice 2022;60:102562 View
  43. Kaye L, Gondalia R, Thompson A, Stempel D, Barrett M. The relationship between objective app engagement and medication adherence in asthma and COPD: a retrospective analysis. Scientific Reports 2021;11(1) View
  44. Fronczek L, Mende M, Scott M, Nenkov G, Gustafsson A. Friend or foe? Can anthropomorphizing self-tracking devices backfire on marketers and consumers?. Journal of the Academy of Marketing Science 2022 View
  45. Ding M, Wang W. Analysis of Factors Influencing We-Intention in Healthcare Applications Based on the AISAS Model. International Journal of Human–Computer Interaction 2023:1 View
  46. De la Rosa-Gómez A, Waldherr K. Editorial: Highlights in digital mental health 2021/22. Frontiers in Digital Health 2023;4 View
  47. Oakley-Girvan I, Yunis R, Longmire M, Ouillon J. What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review. Telemedicine and e-Health 2021 View
  48. He Z, Tian S, Singh A, Chakraborty S, Zhang S, Lustria M, Charness N, Roque N, Harrell E, Boot W. A Machine-Learning Based Approach for Predicting Older Adults’ Adherence to Technology-Based Cognitive Training. Information Processing & Management 2022;59(5):103034 View
  49. Hoepper B, Siegel K, Carlon H, Kahler C, Park E, Taylor S, Simpson H, Hoeppner S. Feature-Level Analysis of a Smoking Cessation Smartphone App Based on a Positive Psychology Approach: Prospective Observational Study. JMIR Formative Research 2022;6(7):e38234 View
  50. Bührmann L, Van Daele T, Rinn A, De Witte N, Lehr D, Aardoom J, Loheide-Niesmann L, Smit J, Riper H. The feasibility of using Apple's ResearchKit for recruitment and data collection: Considerations for mental health research. Frontiers in Digital Health 2022;4 View
  51. Amagai S, Pila S, Kaat A, Nowinski C, Gershon R. Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review. Journal of Medical Internet Research 2022;24(4):e35120 View
  52. Militello L, Sobolev M, Okeke F, Adler D, Nahum-Shani I. Digital Prompts to Increase Engagement With the Headspace App and for Stress Regulation Among Parents: Feasibility Study. JMIR Formative Research 2022;6(3):e30606 View
  53. Broffman L, Harrison S, Zhao M, Goldman A, Patnaik I, Zhou M. The Relationship Between Broadband Speeds, Device Type, Demographic Characteristics, and Care-Seeking Via Telehealth. Telemedicine and e-Health 2023;29(3):425 View
  54. Gan D, McGillivray L, Han J, Christensen H, Torok M. Effect of Engagement With Digital Interventions on Mental Health Outcomes: A Systematic Review and Meta-Analysis. Frontiers in Digital Health 2021;3 View
  55. Wlasak W, Zwanenburg S, Paton C. Supporting Autonomous Motivation for Physical Activity With Chatbots During the COVID-19 Pandemic: Factorial Experiment. JMIR Formative Research 2023;7:e38500 View
  56. Chatterjee P, Beck A, Brager J, Durand D, D'Adamo C. The Effect of an Automated Mobile Patient Engagement Application on Emergency Department Revisits: Prospective Observational Study. JMIR Formative Research 2021;5(12):e17839 View
  57. Kloos N, Austin J, van ‘t Klooster J, Drossaert C, Bohlmeijer E. Appreciating the Good Things in Life During the Covid-19 Pandemic: A Randomized Controlled Trial and Evaluation of a Gratitude App. Journal of Happiness Studies 2022;23(8):4001 View
  58. White K, Matcham F, Leightley D, Carr E, Conde P, Dawe-Lane E, Ranjan Y, Simblett S, Henderson C, Hotopf M. Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial. JMIR Research Protocols 2021;10(12):e32653 View
  59. Coughlin J, Martin L, Zhao D, Goheer A, Woolf T, Holzhauer K, Lehmann H, Lent M, McTigue K, Clark J, Bennett W. Electronic Health Record–Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study. Journal of Medical Internet Research 2022;24(6):e34191 View
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  62. Moon K, Sobolev M, Kane J. Digital and Mobile Health Technology in Collaborative Behavioral Health Care: Scoping Review. JMIR Mental Health 2022;9(2):e30810 View
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Books/Policy Documents

  1. El‐Toukhy S, Nahum‐Shani I. Wiley StatsRef: Statistics Reference Online. View
  2. Martinho D, Carneiro J, Neves J, Novais P, Corchado J, Marreiros G. Progress in Artificial Intelligence. View
  3. Xu W, Legaspi R, Ishikawa Y. Persuasive Technology. View
  4. Sobolev M, Okeke F, Plonsky O. Persuasive Technology. View