Published on in Vol 16, No 4 (2014): April

Factors Related to Sustained Use of a Free Mobile App for Dietary Self-Monitoring With Photography and Peer Feedback: Retrospective Cohort Study

Factors Related to Sustained Use of a Free Mobile App for Dietary Self-Monitoring With Photography and Peer Feedback: Retrospective Cohort Study

Factors Related to Sustained Use of a Free Mobile App for Dietary Self-Monitoring With Photography and Peer Feedback: Retrospective Cohort Study

Journals

  1. Direito A, Jiang Y, Whittaker R, Maddison R. Apps for IMproving FITness and Increasing Physical Activity Among Young People: The AIMFIT Pragmatic Randomized Controlled Trial. Journal of Medical Internet Research 2015;17(8):e210 View
  2. Kuang J, Argo L, Stoddard G, Bray B, Zeng-Treitler Q. Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches. Journal of Medical Internet Research 2015;17(12):e281 View
  3. Hilliard M, Hahn A, Ridge A, Eakin M, Riekert K. User Preferences and Design Recommendations for an mHealth App to Promote Cystic Fibrosis Self-Management. JMIR mHealth and uHealth 2014;2(4):e44 View
  4. Ben Neriah D, Geliebter A. Weight Loss Following Use of a Smartphone Food Photo Feature: Retrospective Cohort Study. JMIR mHealth and uHealth 2019;7(6):e11917 View
  5. Steinhubl S, Muse E, Topol E. The emerging field of mobile health. Science Translational Medicine 2015;7(283):283rv3 View
  6. Rubanovich C, Mohr D, Schueller S. Health App Use Among Individuals With Symptoms of Depression and Anxiety: A Survey Study With Thematic Coding. JMIR Mental Health 2017;4(2):e22 View
  7. Leung L, Chen C. E-health/m-health adoption and lifestyle improvements: Exploring the roles of technology readiness, the expectation-confirmation model, and health-related information activities. Telecommunications Policy 2019;43(6):563 View
  8. Lee H, Cho J. What Motivates Users to Continue Using Diet and Fitness Apps? Application of the Uses and Gratifications Approach. Health Communication 2017;32(12):1445 View
  9. Perski O, Blandford A, West R, Michie S. Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis. Translational Behavioral Medicine 2017;7(2):254 View
  10. Oser M, Wallace M, Solano F, Szigethy E. Guided Digital Cognitive Behavioral Program for Anxiety in Primary Care: Propensity-Matched Controlled Trial. JMIR Mental Health 2019;6(4):e11981 View
  11. Kankanhalli A, Shin J, Oh H. Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review. JMIR mHealth and uHealth 2019;7(1):e11312 View
  12. Sanders J, Loveday A, Pearson N, Edwardson C, Yates T, Biddle S, Esliger D. Devices for Self-Monitoring Sedentary Time or Physical Activity: A Scoping Review. Journal of Medical Internet Research 2016;18(5):e90 View
  13. Elaheebocus S, Weal M, Morrison L, Yardley L. Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review. Journal of Medical Internet Research 2018;20(2):e20 View
  14. Mummah S, Robinson T, Mathur M, Farzinkhou S, Sutton S, Gardner C. Effect of a mobile app intervention on vegetable consumption in overweight adults: a randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity 2017;14(1) View
  15. Holdener M, Gut A, Angerer A. Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study. JMIR mHealth and uHealth 2020;8(1):e13244 View
  16. Khamzina M, Parab K, An R, Bullard T, Grigsby-Toussaint D. Impact of Pokémon Go on Physical Activity: A Systematic Review and Meta-Analysis. American Journal of Preventive Medicine 2020;58(2):270 View
  17. Xiaofei Z, Guo X, Ho S, Lai K, Vogel D. Effects of emotional attachment on mobile health-monitoring service usage: An affect transfer perspective. Information & Management 2021;58(2):103312 View
  18. Lattie E, Schueller S, Sargent E, Stiles-Shields C, Tomasino K, Corden M, Begale M, Karr C, Mohr D. Uptake and usage of IntelliCare: A publicly available suite of mental health and well-being apps. Internet Interventions 2016;4:152 View
  19. Naslund J, Aschbrenner K, Barre L, Bartels S. Feasibility of Popular m-Health Technologies for Activity Tracking Among Individuals with Serious Mental Illness. Telemedicine and e-Health 2015;21(3):213 View
  20. Kim J, Wineinger N, Taitel M, Radin J, Akinbosoye O, Jiang J, Nikzad N, Orr G, Topol E, Steinhubl S. Self-Monitoring Utilization Patterns Among Individuals in an Incentivized Program for Healthy Behaviors. Journal of Medical Internet Research 2016;18(11):e292 View
  21. König L, Sproesser G, Schupp H, Renner B. Describing the Process of Adopting Nutrition and Fitness Apps: Behavior Stage Model Approach. JMIR mHealth and uHealth 2018;6(3):e55 View
  22. Wessels N, Hulshof L, Loohuis A, van Gemert-Pijnen L, Jellema P, van der Worp H, Blanker M. User Experiences and Preferences Regarding an App for the Treatment of Urinary Incontinence in Adult Women: Qualitative Study. JMIR mHealth and uHealth 2020;8(6):e17114 View
  23. 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
  24. Turner-McGrievy G, Wilcox S, Kaczynski A, Spruijt-Metz D, Hutto B, Muth E, Hoover A. Crowdsourcing for self-monitoring: Using the Traffic Light Diet and crowdsourcing to provide dietary feedback. DIGITAL HEALTH 2016;2:205520761665721 View
  25. Chib A, Lin S. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909 View
  26. Yu Z, Sealey-Potts C, Rodriguez J. Dietary Self-Monitoring in Weight Management: Current Evidence on Efficacy and Adherence. Journal of the Academy of Nutrition and Dietetics 2015;115(12):1931 View
  27. D’Ambrosio A, Agricola E, Russo L, Gesualdo F, Pandolfi E, Bortolus R, Castellani C, Lalatta F, Mastroiacovo P, Tozzi A, Cai T. Web-Based Surveillance of Public Information Needs for Informing Preconception Interventions. PLOS ONE 2015;10(4):e0122551 View
  28. Patrick K, Hekler E, Estrin D, Mohr D, Riper H, Crane D, Godino J, Riley W. The Pace of Technologic Change. American Journal of Preventive Medicine 2016;51(5):816 View
  29. Turner-McGrievy G, Dunn C, Wilcox S, Boutté A, Hutto B, Hoover A, Muth E. Defining Adherence to Mobile Dietary Self-Monitoring and Assessing Tracking Over Time: Tracking at Least Two Eating Occasions per Day Is Best Marker of Adherence within Two Different Mobile Health Randomized Weight Loss Interventions. Journal of the Academy of Nutrition and Dietetics 2019;119(9):1516 View
  30. Fritz M, Armenta C, Walsh L, Lyubomirsky S. Gratitude facilitates healthy eating behavior in adolescents and young adults. Journal of Experimental Social Psychology 2019;81:4 View
  31. Crane D, Garnett C, Brown J, West R, Michie S. Factors Influencing Usability of a Smartphone App to Reduce Excessive Alcohol Consumption: Think Aloud and Interview Studies. Frontiers in Public Health 2017;5 View
  32. Tonkin E, Jeffs L, Wycherley T, Maher C, Smith R, Hart J, Cubillo B, Brimblecombe J. A Smartphone App to Reduce Sugar-Sweetened Beverage Consumption Among Young Adults in Australian Remote Indigenous Communities: Design, Formative Evaluation and User-Testing. JMIR mHealth and uHealth 2017;5(12):e192 View
  33. Sawesi S, Rashrash M, Phalakornkule K, Carpenter J, Jones J. The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature. JMIR Medical Informatics 2016;4(1):e1 View
  34. Rasche P, Schlomann A, Mertens A. Who Is Still Playing Pokémon Go? A Web-Based Survey. JMIR Serious Games 2017;5(2):e7 View
  35. Mummah S, Mathur M, King A, Gardner C, Sutton S. Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults. JMIR mHealth and uHealth 2016;4(2):e51 View
  36. Mohr D, Tomasino K, Lattie E, Palac H, Kwasny M, Weingardt K, Karr C, Kaiser S, Rossom R, Bardsley L, Caccamo L, Stiles-Shields C, Schueller S. IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety. Journal of Medical Internet Research 2017;19(1):e10 View
  37. Jee H. Review of researches on smartphone applications for physical activity promotion in healthy adults. Journal of Exercise Rehabilitation 2017;13(1):3 View
  38. Cheung K, Ling W, Karr C, Weingardt K, Schueller S, Mohr D. Evaluation of a recommender app for apps for the treatment of depression and anxiety: an analysis of longitudinal user engagement. Journal of the American Medical Informatics Association 2018;25(8):955 View
  39. Maringer M, van’t Veer P, Klepacz N, Verain M, Normann A, Ekman S, Timotijevic L, Raats M, Geelen A. User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research. Nutrition Journal 2018;17(1) View
  40. Hu X, Qian M, Cheng B, Cheung Y. Personalized Policy Learning Using Longitudinal Mobile Health Data. Journal of the American Statistical Association 2021;116(533):410 View
  41. Vinnikova A, Lu L, Wei J, Fang G, Yan J. The Use of Smartphone Fitness Applications: The Role of Self-Efficacy and Self-Regulation. International Journal of Environmental Research and Public Health 2020;17(20):7639 View
  42. Yan M, Filieri R, Gorton M. Continuance intention of online technologies: A systematic literature review. International Journal of Information Management 2021;58:102315 View
  43. Berglind D, Yacaman-Mendez D, Lavebratt C, Forsell Y. The Effect of Smartphone Apps Versus Supervised Exercise on Physical Activity, Cardiorespiratory Fitness, and Body Composition Among Individuals With Mild-to-Moderate Mobility Disability: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(2):e14615 View
  44. Jung J, Wellard-Cole L, Cai C, Koprinska I, Yacef K, Allman-Farinelli M, Kay J. Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(2):1 View
  45. Minen M, Jaran J, Boyers T, Corner S. Understanding What People With Migraine Consider to be Important Features of Migraine Tracking: An Analysis of the Utilization of Smartphone‐Based Migraine Tracking With a Free‐Text Feature. Headache: The Journal of Head and Face Pain 2020;60(7):1402 View
  46. Harjumaa M, Absetz P, Ermes M, Mattila E, Männikkö R, Tilles-Tirkkonen T, Lintu N, Schwab U, Umer A, Leppänen J, Pihlajamäki J. Internet-Based Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits: Design and 6-Month Usage Results of Randomized Controlled Trial. JMIR Diabetes 2020;5(3):e15219 View
  47. Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(9):e20283 View
  48. Yan M, Filieri R, Raguseo E, Gorton M. Mobile apps for healthy living: Factors influencing continuance intention for health apps. Technological Forecasting and Social Change 2021;166:120644 View
  49. Zhang P, Burns R, Fu Y, Godin S, Li Z, Zhang X. Efficacy of a 4-Week Smartphone Application Intervention on College Students’ BMI, Physical Activity, and Motivation. International Journal of Kinesiology in Higher Education 2021:1 View

Books/Policy Documents

  1. . M-Health: Fundamentals and Applications. View
  2. Monti J. Reference Module in Biomedical Sciences. View
  3. Ramirez V, Starobin B, Monti J. Encyclopedia of Cardiovascular Research and Medicine. View
  4. Wang L, He D, Ni X, Zou R, Yuan X, Shang Y, Hu X, Geng X, Jiang K, Dong J, Wu H. Smart Health. View