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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1803) Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (394) Depression and Mood Disorders; Suicide Prevention (1515) mHealth for Wellness, Behavior Change and Prevention (3098) Web-based and Mobile Health Interventions (3629) Mobile Health (mhealth) (3155) Digital Health Reviews (1519) Mobile Health in Psychiatry (478) Anxiety and Stress Disorders (1179)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29412, first published .
Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review

Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review

Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review

Authors of this article:

Gisbert W Teepe1 Author Orcid Image ;   Ashish Da Fonseca2 Author Orcid Image ;   Birgit Kleim3, 4 Author Orcid Image ;   Nicholas C Jacobson5 Author Orcid Image ;   Alicia Salamanca Sanabria6 Author Orcid Image ;   Lorainne Tudor Car7, 8 Author Orcid Image ;   Elgar Fleisch1, 2 Author Orcid Image ;   Tobias Kowatsch1, 2, 6 Author Orcid Image
Article Authors Cited by (27) Tweetations (22) Metrics

Journals

  1. Currey D, Torous J. Digital Phenotyping Data to Predict Symptom Improvement and App Personalization: Protocol for a Prospective Study. JMIR Research Protocols 2022;11(11):e37954 View
  2. Owens A, Krebs C, Kuruppu S, Brem A, Kowatsch T, Aarsland D, Klöppel S. Broadened assessments, health education and cognitive aids in the remote memory clinic. Frontiers in Public Health 2022;10 View
  3. Keller R, Hartmann S, Teepe G, Lohse K, Alattas A, Tudor Car L, Müller-Riemenschneider F, von Wangenheim F, Mair J, Kowatsch T. Digital Behavior Change Interventions for the Prevention and Management of Type 2 Diabetes: Systematic Market Analysis. Journal of Medical Internet Research 2022;24(1):e33348 View
  4. Oikonomidi T, Ravaud P, LeBeau J, Tran V. A systematic scoping review of just-in-time, adaptive interventions finds limited automation and incomplete reporting. Journal of Clinical Epidemiology 2023;154:108 View
  5. Stamatis C, Meyerhoff J, Liu T, Sherman G, Wang H, Liu T, Curtis B, Ungar L, Mohr D. Prospective associations of text‐message‐based sentiment with symptoms of depression, generalized anxiety, and social anxiety. Depression and Anxiety 2022;39(12):794 View
  6. Zielasek J, Reinhardt I, Schmidt L, Gouzoulis-Mayfrank E. Adapting and Implementing Apps for Mental Healthcare. Current Psychiatry Reports 2022;24(9):407 View
  7. Currey D, Torous J. Digital Phenotyping Data to Predict Symptom Improvement and Mental Health App Personalization in College Students: Prospective Validation of a Predictive Model. Journal of Medical Internet Research 2023;25:e39258 View
  8. Kleiman E, Glenn C, Liu R. The use of advanced technology and statistical methods to predict and prevent suicide. Nature Reviews Psychology 2023;2(6):347 View
  9. Teepe G, Glase E, Reips U, Santangelo O. Increasing digitalization is associated with anxiety and depression: A Google Ngram analysis. PLOS ONE 2023;18(4):e0284091 View
  10. ROSS V, BRIJS K, DIRIX H, WETS G, NEVEN A, VANROMPAY Y, CLAES N, JACOBS N. Early Client Involvement In The Design Of A Blended Smartphone Application And Dashboard For Depression (Totem). Journal of Evidence-Based Psychotherapies 2023;22(1):97 View
  11. Castro O, Mair J, Salamanca-Sanabria A, Alattas A, Keller R, Zheng S, Jabir A, Lin X, Frese B, Lim C, Santhanam P, van Dam R, Car J, Lee J, Tai E, Fleisch E, von Wangenheim F, Tudor Car L, Müller-Riemenschneider F, Kowatsch T. Development of “LvL UP 1.0”: a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders. Frontiers in Digital Health 2023;5 View
  12. Smith K, Blease C, Faurholt-Jepsen M, Firth J, Van Daele T, Moreno C, Carlbring P, Ebner-Priemer U, Koutsouleris N, Riper H, Mouchabac S, Torous J, Cipriani A. Digital mental health: challenges and next steps. BMJ Mental Health 2023;26(1):e300670 View
  13. Rohaj A, Bulaj G. Digital Therapeutics (DTx) Expand Multimodal Treatment Options for Chronic Low Back Pain: The Nexus of Precision Medicine, Patient Education, and Public Health. Healthcare 2023;11(10):1469 View
  14. Wang J, Wu Z, Choi S, Sen S, Yan X, Miner J, Sander A, Lyden A, Troost J, Carlozzi N. The Dosing of Mobile-Based Just-in-Time Adaptive Self-Management Prompts for Caregivers: Preliminary Findings From a Pilot Microrandomized Study. JMIR Formative Research 2023;7:e43099 View
  15. Teepe G, Lukic Y, Kleim B, Jacobson N, Schneider F, Santhanam P, Fleisch E, Kowatsch T. Development of a digital biomarker and intervention for subclinical depression: study protocol for a longitudinal waitlist control study. BMC Psychology 2023;11(1) View
  16. Lipschitz J, Pike C, Hogan T, Murphy S, Burdick K. The Engagement Problem: a Review of Engagement with Digital Mental Health Interventions and Recommendations for a Path Forward. Current Treatment Options in Psychiatry 2023;10(3):119 View
  17. Muench F, Madden S, Oommen S, Forthal S, Srinagesh A, Stadler G, Kuerbis A, Leeman R, Suffoletto B, Baumel A, Haslip C, Vadhan N, Morgenstern J. Automated, tailored adaptive mobile messaging to reduce alcohol consumption in help‐seeking adults: A randomized controlled trial. Addiction 2024;119(3):530 View
  18. Kaya R, Kaplan V, Solmaz F, Yılmaz Y, Düken M. Just-in-Time Adaptive Interventions for Depression. Psikiyatride Güncel Yaklaşımlar 2024;16(4):585 View
  19. Gray L, Marcynikola N, Barnett I, Torous J. The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study. Journal of Integrative and Complementary Medicine 2024;30(11):1108 View
  20. Slade C, Benzo R, Washington P. Design Guidelines for Improving Mobile Sensing Data Collection: Prospective Mixed Methods Study. Journal of Medical Internet Research 2024;26:e55694 View
  21. Henry L, Blay-Tofey M, Haeffner C, Raymond C, Tandilashvili E, Terry N, Kiderman M, Metcalf O, Brotman M, Lopez-Guzman S. Just-In-Time Adaptive Interventions to Promote Behavioral Health: Protocol for a Systematic Review. JMIR Research Protocols 2025;14:e58917 View
  22. Castro O, Salamanca-Sanabria A, Alattas A, Teepe G, Leidenberger K, Fleisch E, Tudor Car L, Muller-Riemenschneider F, Kowatsch T. Top-funded companies offering digital health interventions for the prevention and treatment of depression: a systematic market analysis. Archives of Public Health 2024;82(1) View
  23. Tang T, Klein G, Görges M, Yip A, Fisher L, Polonsky W, Hessler D, Taylor D. Evaluating a mental health support mobile app for adults with type 1 diabetes living in rural and remote communities: The REACHOUT pilot study. Diabetic Medicine 2025;42(3) View
  24. van Genugten C, Thong M, van Ballegooijen W, Kleiboer A, Spruijt-Metz D, Smit A, Sprangers M, Terhorst Y, Riper H. Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review. Frontiers in Digital Health 2025;7 View
  25. Metcalf O, Forbes D, Henry L, Qian T, Varker T, Brotman M, Cowlishaw S, Lamb K, O'Donnell M. A just-in-time adaptive intervention (Shift) to manage problem anger after trauma: Co-design and development (Preprint). JMIR Human Factors 2024 View

Books/Policy Documents

  1. Keller R, Wangenheim F, Mair J, Kowatsch T. Digital Therapeutics for Mental Health and Addiction. View

Conference Proceedings

  1. Lee J, Lee B, Choe E. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. Decorative, Evocative, and Uncanny: Reactions on Ambient-to-Disruptive Health Notifications via Plant-Mimicking Shape-Changing Interfaces View