Published on in Vol 4, No 1 (2016): Jan-Mar

Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion

Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion

Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion

Journals

  1. Höchsmann C, Dorling J, Martin C, Newton R, Apolzan J, Myers C, Denstel K, Mire E, Johnson W, Zhang D, Arnold C, Davis T, Fonseca V, Lavie C, Price-Haywood E, Katzmarzyk P. Effects of a 2-Year Primary Care Lifestyle Intervention on Cardiometabolic Risk Factors. Circulation 2021;143(12):1202 View
  2. Oshima S, Tait S, Thomas S, Fayanju O, Ingraham K, Barrett N, Hwang E. Association of Smartphone Ownership and Internet Use With Markers of Health Literacy and Access: Cross-sectional Survey Study of Perspectives From Project PLACE (Population Level Approaches to Cancer Elimination). Journal of Medical Internet Research 2021;23(6):e24947 View
  3. Huang C, Yang M. Empirical Investigation of Factors Influencing Consumer Intention to Use an Artificial Intelligence-Powered Mobile Application for Weight Loss and Health Management. Telemedicine and e-Health 2020;26(10):1240 View
  4. Zhou M, Bian B, Zhu W, Huang L. The Impact of Parental Migration on Multidimensional Health of Children in Rural China: The Moderating Effect of Mobile Phone Addiction. Children 2022;10(1):44 View
  5. Thomas D, Paynter J, Peterson C, Heymsfield S, Nduati A, Apolzan J, Martin C. A new universal dynamic model to describe eating rate and cumulative intake curves. The American Journal of Clinical Nutrition 2017;105(2):323 View
  6. Gilmore L, Redman L. Application of mathematical models in the management of obesity during pregnancy and the postpartum period in reproductive age women. Nutrition Research 2019;70:7 View
  7. Gerving C, Lasater R, Starling J, Ostendorf D, Redman L, Estabrooks C, Cummiskey K, Antonetti V, Thomas D. Predicting energy intake in adults who are dieting and exercising. International Journal of Obesity 2022;46(12):2095 View
  8. Martin C, Höchsmann C, Dorling J, Bhapkar M, Pieper C, Racette S, Das S, Redman L, Kraus W, Ravussin E. Challenges in defining successful adherence to calorie restriction goals in humans: Results from CALERIE™ 2. Experimental Gerontology 2022;162:111757 View
  9. Kwon O, Choi J, Jang Y. The Effectiveness of eHealth Interventions on Lifestyle Modification in Patients With Nonalcoholic Fatty Liver Disease: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2023;25:e37487 View
  10. Blundell J. The contribution of behavioural science to nutrition: Appetite control. Nutrition Bulletin 2017;42(3):236 View
  11. Boratto L, Carta S, Iguider W, Mulas F, Pilloni P. Fair performance-based user recommendation in eCoaching systems. User Modeling and User-Adapted Interaction 2022;32(5):839 View
  12. Hall K, Kahan S. Maintenance of Lost Weight and Long-Term Management of Obesity. Medical Clinics of North America 2018;102(1):183 View
  13. El-Sherif D, Abouzid M. Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak. Globalization and Health 2022;18(1) View
  14. Berthoud H, Morrison C, Münzberg H. The obesity epidemic in the face of homeostatic body weight regulation: What went wrong and how can it be fixed?. Physiology & Behavior 2020;222:112959 View
  15. Gilmore L, Klempel M, Martin C, Myers C, Burton J, Sutton E, Redman L. Personalized Mobile Health Intervention for Health and Weight Loss in Postpartum Women Receiving Women, Infants, and Children Benefit: A Randomized Controlled Pilot Study. Journal of Women's Health 2017;26(7):719 View
  16. Roe B, Qi D, Beyl R, Neubig K, Apolzan J, Martin C. A Randomized Controlled Trial to Address Consumer Food Waste with a Technology-aided Tailored Sustainability Intervention. Resources, Conservation and Recycling 2022;179:106121 View
  17. Alhasani M, Mulchandani D, Oyebode O, Baghaei N, Orji R. A Systematic and Comparative Review of Behavior Change Strategies in Stress Management Apps: Opportunities for Improvement. Frontiers in Public Health 2022;10 View
  18. Chen J, Lieffers J, Bauman A, Hanning R, Allman‐Farinelli M. The use of smartphone health apps and other mobile health (mHealth) technologies in dietetic practice: a three country study. Journal of Human Nutrition and Dietetics 2017;30(4):439 View
  19. Daryabeygi-Khotbehsara R, Shariful Islam S, Dunstan D, McVicar J, Abdelrazek M, Maddison R. Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review. Journal of Medical Internet Research 2021;23(9):e26315 View
  20. Joseph-Shehu E, Ncama B, Irinoye O. Developing and Pilot Testing an Integrated Technology–Moderated Institutional Health Promotion Model Using Operational Research Approach. CIN: Computers, Informatics, Nursing 2019;37(10):532 View
  21. Hales S, Smith C, Turner T, Sword D, DuBose-Morris R, Blackburn D, Malcolm R, O’Neil P. Development and Pilot Testing of a Telehealth Weight Loss Program. Translational Journal of the American College of Sports Medicine 2023;8(2) View
  22. Rivera-Romero O, Gabarron E, Ropero J, Denecke K. Designing personalised mHealth solutions: An overview. Journal of Biomedical Informatics 2023;146:104500 View
  23. Höchsmann C, Martin C, Apolzan J, Dorling J, Newton R, Denstel K, Mire E, Johnson W, Zhang D, Arnold C, Davis T, Fonseca V, Thethi T, Lavie C, Springgate B, Katzmarzyk P. Initial weight loss and early intervention adherence predict long‐term weight loss during the Promoting Successful Weight Loss in Primary Care in Louisiana lifestyle intervention. Obesity 2023;31(9):2272 View
  24. Valdez Gonzalez N, Kee J, Palma M, Pruitt J. The relationship between monetary incentives, social status, and physical activity. Journal of Behavioral and Experimental Economics 2024;108:102155 View
  25. Felfernig A, Wundara M, Tran T, Le V, Lubos S, Polat-Erdeniz S. Sports recommender systems: overview and research directions. Journal of Intelligent Information Systems 2024;62(4):1125 View
  26. Kwon S, Wan N, Burns R, Brusseau T, Kim Y, Kumar S, Ertin E, Wetter D, Lam C, Wen M, Byun W. The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings. Sensors 2021;21(4):1411 View
  27. Johnson K, Gutierrez E, Dionicio P, McConnell J, Sauls R, Alencar M. Telehealth-Based Health Coaching Produces Significant Weight Loss over 12 Months in a Usual Care Setting. International Medical Education 2022;1(2):79 View
  28. Li X, Yin A, Choi H, Chan V, Allman-Farinelli M, Chen J. Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care. Nutrients 2024;16(15):2573 View
  29. Helminski D, Sussman J, Pfeiffer P, Kokaly A, Ranusch A, Renji A, Damschroder L, Landis-Lewis Z, Kurlander J. Development, implementation, and evaluation methods for dashboards in health care: Scoping Review (Preprint). JMIR Medical Informatics 2024 View
  30. Lavoie H, Scotti K, Christou D, Jake-Schoffman D. A look into the cancer continuum for the development of a physical activity intervention: qualitative investigation of the physical activity experiences and preferences of female cancer survivors. Supportive Care in Cancer 2024;32(11) View
  31. Ivezić D, Keppel J, Horneber D, Becker C, Laumer S, Walle H, Schneegass S, Amft O. EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study. F1000Research 2024;13:1347 View

Books/Policy Documents

  1. Iyawa G, Ondiek C, Osakwe J. Smart Medical Data Sensing and IoT Systems Design in Healthcare. View
  2. Wen T, Hsu C, Sun C, Jiang J, Juang J. Human Dynamics Research in Smart and Connected Communities. View
  3. Ryan D, Anton S. Present Knowledge in Nutrition. View