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

Journals

  1. Ramirez M, Wu S, Beale E. Designing a Text Messaging Intervention to Improve Physical Activity Behavior Among Low-Income Latino Patients With Diabetes: A Discrete-Choice Experiment, Los Angeles, 2014–2015. Preventing Chronic Disease 2016;13 View
  2. Davis A, Ellis R. A quasi-experimental investigation of college students’ ratings of two physical activity mobile apps with varied behavior change technique quantity. DIGITAL HEALTH 2019;5:205520761989134 View
  3. Sill J, Steenbock B, Helmer S, Zeeb H, Pischke C. Apps zur Förderung von körperlicher Aktivität – Nutzung und Einstellungen bei Erwachsenen im Alter von 50 Jahren und älter. Prävention und Gesundheitsförderung 2019;14(2):109 View
  4. Lentferink A, Oldenhuis H, de Groot M, Polstra L, Velthuijsen H, van Gemert-Pijnen J. Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review. Journal of Medical Internet Research 2017;19(8):e277 View
  5. Wichmann F, Sill J, Hassenstein M, Zeeb H, Pischke C. Apps zur Förderung von körperlicher Aktivität. Prävention und Gesundheitsförderung 2019;14(2):93 View
  6. Dallinga J, Janssen M, van der Werf J, Walravens R, Vos S, Deutekom M. Analysis of the Features Important for the Effectiveness of Physical Activity–Related Apps for Recreational Sports: Expert Panel Approach. JMIR mHealth and uHealth 2018;6(6):e143 View
  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
  9. Simons D, De Bourdeaudhuij I, Clarys P, De Cocker K, Vandelanotte C, Deforche B. A Smartphone App to Promote an Active Lifestyle in Lower-Educated Working Young Adults: Development, Usability, Acceptability, and Feasibility Study. JMIR mHealth and uHealth 2018;6(2):e44 View
  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
  13. Huang G, Ren Y. Linking technological functions of fitness mobile apps with continuance usage among Chinese users: Moderating role of exercise self-efficacy. Computers in Human Behavior 2020;103:151 View
  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 2023 View
  26. Lurz M, Gemesi K, Holzmann S, Kretzschmar B, Wintergerst M, Groh G, Böhm M, Gedrich K, Hauner H, Krcmar H, Holzapfel C. Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey. BMC Public Health 2024;24(1) View

Books/Policy Documents

  1. Huimei W, Yadi L. Frontier Computing. View
  2. Kettunen E, Makkonen M, Kari T, Critchley W. Optimizing Health Monitoring Systems With Wireless Technology. View
  3. Wilson K, Rhodes R. Essentials of exercise and sport psychology: An open access textbook. View