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

Exercise and Diet Tracking for Diabetes Patients (86) mHealth for Treatment Adherence (404)

Published on in Vol 5, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18363, first published .
Relationship Between Age and Weight Loss in Noom: Quasi-Experimental Study

Relationship Between Age and Weight Loss in Noom: Quasi-Experimental Study

Relationship Between Age and Weight Loss in Noom: Quasi-Experimental Study

Authors of this article:

Laura DeLuca1 Author Orcid Image ;   Tatiana Toro-Ramos2 Author Orcid Image ;   Andreas Michaelides2 Author Orcid Image ;   Elizabeth Seng1 Author Orcid Image ;   Charles Swencionis1 Author Orcid Image
Article Authors Cited by (26) Tweetations (2) Metrics

Journals

  1. Toro-Ramos T, Heaner M, Yang Q, DeLuca L, Behr H, Reynolds K, Kim Y, Michaelides A. Postpartum Weight Retention: A Retrospective Data Analysis Measuring Weight Loss and Program Engagement with a Mobile Health Program. Journal of Women's Health 2021;30(11):1645 View
  2. Fundoiano-Hershcovitz Y, Hirsch A, Dar S, Feniger E, Goldstein P. Role of Digital Engagement in Diabetes Care Beyond Measurement: Retrospective Cohort Study. JMIR Diabetes 2021;6(1):e24030 View
  3. Mitchell E, Yang Q, Behr H, Ho A, DeLuca L, May C, Michaelides A. Psychosocial Characteristics by Weight Loss and Engagement in a Digital Intervention Supporting Self-Management of Weight. International Journal of Environmental Research and Public Health 2021;18(4):1712 View
  4. Mitchell E, Yang Q, Ho A, Behr H, May C, DeLuca L, Michaelides A. Self-Reported Nutritional Factors Are Associated with Weight Loss at 18 Months in a Self-Managed Commercial Program with Food Categorization System: Observational Study. Nutrients 2021;13(5):1733 View
  5. Yang Q, Mitchell E, Ho A, DeLuca L, Behr H, Michaelides A. Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis. Frontiers in Public Health 2021;9 View
  6. Behr H, Ho A, Mitchell E, Yang Q, DeLuca L, Michealides A. How Do Emotions during Goal Pursuit in Weight Change over Time? Retrospective Computational Text Analysis of Goal Setting and Striving Conversations with a Coach during a Mobile Weight Loss Program. International Journal of Environmental Research and Public Health 2021;18(12):6600 View
  7. Chen X, Giles J, Yao Y, Yip W, Meng Q, Berkman L, Chen H, Chen X, Feng J, Feng Z, Glinskaya E, Gong J, Hu P, Kan H, Lei X, Liu X, Steptoe A, Wang G, Wang H, Wang H, Wang X, Wang Y, Yang L, Zhang L, Zhang Q, Wu J, Wu Z, Strauss J, Smith J, Zhao Y. The path to healthy ageing in China: a Peking University–Lancet Commission. The Lancet 2022;400(10367):1967 View
  8. Auster-Gussman L, Lockwood K, Graham S, Pitter V, Branch O. Engagement in Digital Health App-Based Prevention Programs Is Associated With Weight Loss Among Adults Age 65+. Frontiers in Digital Health 2022;4 View
  9. Garner N, Smith J, Sampson M, Greaves C. Quantity and specificity of action-plans as predictors of weight loss: analysis of data from the Norfolk Diabetes Prevention Study (NDPS). Psychology & Health 2024;39(1):42 View
  10. Nazare J, Woolf A, Sysoev I, Ballinger S, Saveski M, Walker M, Roy D. Technology-assisted coaching can increase engagement with learning technology at home and caregivers’ awareness of it. Computers & Education 2022;188:104565 View
  11. Ho A, Behr H, Mitchell E, Yang Q, Lee J, May C, Michaelides A, König L. Goal language is associated with attrition and weight loss on a digital program: Observational study. PLOS Digital Health 2022;1(6):e0000050 View
  12. Torres L, Lee J, Park S, Di Lorenzo R, Branam J, Fraser S, Salisbury B. Retention, Fasting Patterns, and Weight Loss With an Intermittent Fasting App: Large-Scale, 52-Week Observational Study. JMIR mHealth and uHealth 2022;10(10):e35896 View
  13. Carey A, Yang Q, DeLuca L, Toro-Ramos T, Kim Y, Michaelides A. The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis. JMIR mHealth and uHealth 2021;9(11):e30622 View
  14. Behr H, Ho A, Yang Q, Mitchell E, DeLuca L, Greenstein N, Michaelides A. Men’s Weight Loss Outcomes, Behaviors, and Perceptions in a Self-Directed Commercial Mobile Program: Retrospective Analysis. Health Education & Behavior 2023;50(1):70 View
  15. Rodriguez D, Lawrence K, Luu S, Yu J, Feldthouse D, Gonzalez J, Mann D. Development of a computer-aided text message platform for user engagement with a digital Diabetes Prevention Program: a case study. Journal of the American Medical Informatics Association 2021;29(1):155 View
  16. Ruelas A, Martínez Contreras T, Esparza Romero J, Díaz Zavala R, Candia Plata M, Hingle M, Armenta Guirado B, Haby M. Factors influencing adults to drop out of intensive lifestyle interventions for weight loss. Translational Behavioral Medicine 2023;13(4):245 View
  17. Samoilova Y, Matveeva M, Vachadze T, Tolmachev I, Zakharchuk P. Gamification as a method of preventing childhood obesity. Profilakticheskaya meditsina 2022;25(9):117 View
  18. McCallum M, Ho A, May C, Behr H, Mitchell E, Michealides A. Body Positivity and Self-Compassion on a Publicly Available Behavior Change Weight Management Program. International Journal of Environmental Research and Public Health 2021;18(24):13358 View
  19. Xu M, Li J, Zou Y, Xu Y. The Comparison of the Effects between Continuous and Intermittent Energy Restriction in Short-Term Bodyweight Loss for Sedentary Population: A Randomized, Double-Blind, Controlled Trial. International Journal of Environmental Research and Public Health 2021;18(21):11645 View
  20. May C, Ho A, Yang Q, McCallum M, Iyengar N, Comander A, Mitchell E, Michaelides A. Comparing Outcomes of a Digital Commercial Weight Loss Program in Adult Cancer Survivors and Matched Controls with Overweight or Obesity: Retrospective Analysis. Nutrients 2021;13(9):2908 View
  21. Pigsborg K, Stentoft-Larsen V, Demharter S, Aldubayan M, Trimigno A, Khakimov B, Engelsen S, Astrup A, Hjorth M, Dragsted L, Magkos F. Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach. Frontiers in Nutrition 2023;10 View
  22. Mitchell E, Fabry A, Ho A, May C, Baldwin M, Blanco P, Smith K, Michaelides A, Shokoohi M, West M, Gotera K, El Massad O, Zhou A. The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study. JMIR mHealth and uHealth 2023;11:e47473 View
  23. Pigsborg K, Kalea A, De Dominicis S, Magkos F. Behavioral and Psychological Factors Affecting Weight Loss Success. Current Obesity Reports 2023;12(3):223 View
  24. Chang B, Tam E, Villas Boas P, Tullis L, Lopes F, Li J. Envisioning digital health for older adults: a polychronic disease approach. International Journal of Digital Health 2023 View
  25. Saslow L, O’Brien A, Raymond K, Bayandorian H, Marriott D, Moskowitz J, Daubenmier J, Bridges D, Cousineau C, Griauzde D. Feasibility and acceptability of an online multicomponent very low-carbohydrate intervention in young adult women with obesity: a pilot study. Pilot and Feasibility Studies 2024;10(1) View
  26. Fundoiano-Hershcovitz Y, Breuer Asher I, Kantor H, Rahmon S, Ritholz M, Horwitz D, Manejwala O, Goldstein P. Walking away from depression: the mediating role of walking activity in depression impacting blood glucose levels of people with diabetes or prediabetes. Frontiers in Endocrinology 2024;15 View