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

mHealth for Wellness, Behavior Change and Prevention (2728) Mobile Health (mhealth) (2748)

Published on in Vol 3, No 4 (2015): Oct-Dec

Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey

Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey

Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey

Authors of this article:

Laura S. Belmon1 Author Orcid Image ;   Anouk Middelweerd1 Author Orcid Image ;   Saskia J te Velde1 Author Orcid Image ;   Johannes Brug1 Author Orcid Image
Article Authors Cited by (30) Tweetations (23) Metrics

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  7. Cushing C, Fedele D, Brannon E, Kichline T. Parents’ Perspectives on the Theoretical Domains Framework Elements Needed in a Pediatric Health Behavior App: A Crowdsourced Social Validity Study. JMIR mHealth and uHealth 2018;6(12):e192 View
  8. Middelweerd A, te Velde S, Mollee J, Klein M, Brug J. App-Based Intervention Combining Evidence-Based Behavior Change Techniques With a Model-Based Reasoning System to Promote Physical Activity Among Young Adults (Active2Gether): Descriptive Study of the Development and Content. JMIR Research Protocols 2018;7(12):e185 View
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  10. Huang G, Zhou E. Time to Work Out! Examining the Behavior Change Techniques and Relevant Theoretical Mechanisms that Predict the Popularity of Fitness Mobile Apps with Chinese-Language User Interfaces. Health Communication 2019;34(12):1502 View
  11. de Korte E, Wiezer N, Bakhuys Roozeboom M, Vink P, Kraaij W. Behavior Change Techniques in mHealth Apps for the Mental and Physical Health of Employees: Systematic Assessment. JMIR mHealth and uHealth 2018;6(10):e167 View
  12. Direito A, Tooley M, Hinbarji M, Albatal R, Jiang Y, Whittaker R, Maddison R. Tailored Daily Activity: An Adaptive Physical Activity Smartphone Intervention. Telemedicine and e-Health 2020;26(4):426 View
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  14. Anderson K, Burford O, Emmerton L. App Chronic Disease Checklist: Protocol to Evaluate Mobile Apps for Chronic Disease Self-Management. JMIR Research Protocols 2016;5(4):e204 View
  15. Fu Y, Wu W. Predicting household water use behaviour for improved hygiene practices in internet of things environment via dynamic behaviour intervention model. IET Networks 2016;5(5):143 View
  16. D'Addario M, Baretta D, Zanatta F, Greco A, Steca P. Engagement Features in Physical Activity Smartphone Apps: Focus Group Study With Sedentary People. JMIR mHealth and uHealth 2020;8(11):e20460 View
  17. Domin A, Spruijt-Metz D, Theisen D, Ouzzahra Y, Vögele C. Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years. JMIR mHealth and uHealth 2021;9(7):e24308 View
  18. Gosetto L, Pittavino M, Falquet G, Ehrler F. Personalization of Mobile Apps for Health Behavior Change: Protocol for a Cross-sectional Study. JMIR Research Protocols 2023;12:e38603 View
  19. Caille P, Stephan Y, Sutin A, Luchetti M, Canada B, Heraud N, Terracciano A. Personality and change in physical activity across 3–10 years. Psychology & Health 2024;39(5):670 View
  20. Kim E, Han S. Determinants of Continuance Intention to Use Health Apps among Users over 60: A Test of Social Cognitive Model. International Journal of Environmental Research and Public Health 2021;18(19):10367 View
  21. Mähs M, Pithan J, Bergmann I, Gabrys L, Graf J, Hölzemann A, Van Laerhoven K, Otto-Hagemann S, Popescu M, Schwermann L, Wenz B, Pahmeier I, Teti A. Activity tracker-based intervention to increase physical activity in patients with type 2 diabetes and healthy individuals: study protocol for a randomized controlled trial. Trials 2022;23(1) View
  22. Huang G, Sun M, Jiang L. Core social network size is associated with physical activity participation for fitness app users: The role of social comparison and social support. Computers in Human Behavior 2022;129:107169 View
  23. Sun M, Jiang L. Linking social features of fitness apps with physical activity among Chinese users: Evidence from self-reported and self-tracked behavioral data. Information Processing & Management 2022;59(6):103096 View
  24. Vos A, de Bruijn G, Klein M, Lakerveld J, Boerman S, Smit E. SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study. JMIR Formative Research 2023;7:e40851 View
  25. Kuru H. Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App: A Content Analysis. Health Education & Behavior 2024;51(4):636 View
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Books/Policy Documents

  1. Huimei W, Yadi L. Frontier Computing. View
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