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

mHealth for Wellness, Behavior Change and Prevention (2743) Mobile Health (mhealth) (2765) Behavior Change (653)

Published on in Vol 6, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9801, first published .
Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study

Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study

Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study

Authors of this article:

Sherry Pagoto1 Author Orcid Image ;   Bengisu Tulu2 Author Orcid Image ;   Emmanuel Agu3 Author Orcid Image ;   Molly E Waring1 Author Orcid Image ;   Jessica L Oleski1 Author Orcid Image ;   Danielle E Jake-Schoffman4 Author Orcid Image
Article Authors Cited by (19) Tweetations (49) Metrics

Journals

  1. Yu Y, Sereika S, Finegold D, Burke L. Problem-solving, Adherence to Lifestyle Goals, and Weight Loss Among Individuals Participating in a Weight Loss Study. International Journal of Behavioral Medicine 2021;28(3):328 View
  2. Arigo D, Jake-Schoffman D, Wolin K, Beckjord E, Hekler E, Pagoto S. The history and future of digital health in the field of behavioral medicine. Journal of Behavioral Medicine 2019;42(1):67 View
  3. Asbjørnsen R, Smedsrød M, Solberg Nes L, Wentzel J, Varsi C, Hjelmesæth J, van Gemert-Pijnen J. Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review. Journal of Medical Internet Research 2019;21(6):e14265 View
  4. Poss-Doering R, Kuehn L, Kamradt M, Glassen K, Wensing M. Applying Digital Information Delivery to Convert Habits of Antibiotic Use in Primary Care in Germany: Mixed-Methods Study. Journal of Medical Internet Research 2020;22(10):e18200 View
  5. Ogden J, Maxwell H, Wong A. Development and feasibility study of an app (Ladle) for weight loss and behaviour change. PeerJ 2019;7:e6907 View
  6. Kliemann N, Croker H, Johnson F, Beeken R. Development of the Top Tips Habit-Based Weight Loss App and Preliminary Indications of Its Usage, Effectiveness, and Acceptability: Mixed-Methods Pilot Study. JMIR mHealth and uHealth 2019;7(5):e12326 View
  7. Turner-McGrievy G, Yang C, Monroe C, Pellegrini C, West D. Is Burden Always Bad? Emerging Low-Burden Approaches to Mobile Dietary Self-monitoring and the Role Burden Plays with Engagement. Journal of Technology in Behavioral Science 2021;6(3):447 View
  8. Gardner B, Richards R, Lally P, Rebar A, Thwaite T, Beeken R. Breaking habits or breaking habitual behaviours? Old habits as a neglected factor in weight loss maintenance. Appetite 2021;162:105183 View
  9. Skoda E, Steinbach J, Robitzsch A, Pfeiffer C, Schüren L, Tomaszewski J, Niedergethman M, Schweda A, Bäuerle A, Teufel M. Metabolic Surgery Supporting Aftercare via Group-Intervention (MeSSAGES): study protocol of a randomised controlled trial. BMJ Open 2021;11(12):e053839 View
  10. Wang T, Zheng X, Liang J, An K, He Y, Nuo M, Wang W, Lei J. Use of Machine Learning to Mine User-Generated Content From Mobile Health Apps for Weight Loss to Assess Factors Correlated With User Satisfaction. JAMA Network Open 2022;5(5):e2215014 View
  11. Sysko R, Bibeau J, Boyar A, Costello K, Michaelides A, Mitchell E, Susanin A, Hildebrandt T. A 2.5-Year Weight Management Program Using Noom Health: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2022;11(8):e37541 View
  12. 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
  13. Elnaggar A, von Oppenfeld J, Whooley M, Merek S, Park L. Applying Mobile Technology to Sustain Physical Activity After Completion of Cardiac Rehabilitation: Acceptability Study. JMIR Human Factors 2021;8(3):e25356 View
  14. Singh A, Schooley B, Patel N. Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study. JMIR mHealth and uHealth 2023;11:e43105 View
  15. Chew H, Achananuparp P, Dalakoti M, Chew N, Chin Y, Gao Y, So B, Shabbir A, Peng L, Ngiam K. Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study. Frontiers in Nutrition 2024;11 View
  16. Reading J, Crane M, Guan J, Jackman R, Thomson M, LaRose J. Acceptability of a Self-Guided Lifestyle Intervention Among Young Men: Mixed Methods Analysis of Pilot Findings. JMIR Formative Research 2024;8:e53841 View
  17. Pfledderer C, von Klinggraeff L, Burkart S, da Silva Bandeira A, Lubans D, Jago R, Okely A, van Sluijs E, Ioannidis J, Thrasher J, Li X, Beets M. Consolidated guidance for behavioral intervention pilot and feasibility studies. Pilot and Feasibility Studies 2024;10(1) View
  18. Zhu Y, Zhang R, Yin S, Sun Y, Womer F, Liu R, Zeng S, Zhang X, Wang F. Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation. JMIR Public Health and Surveillance 2024;10:e47428 View

Books/Policy Documents

  1. Nezu A, Nezu C, Gerber H, Damico J. Comprehensive Clinical Psychology. View