Published on in Vol 20, No 2 (2018): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9723, first published .
A Novel Approach for Fully Automated, Personalized Health Coaching for Adults with Prediabetes: Pilot Clinical Trial

A Novel Approach for Fully Automated, Personalized Health Coaching for Adults with Prediabetes: Pilot Clinical Trial

A Novel Approach for Fully Automated, Personalized Health Coaching for Adults with Prediabetes: Pilot Clinical Trial

Journals

  1. Monteiro-Guerra F, Rivera-Romero O, Fernandez-Luque L, Caulfield B. Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review. IEEE Journal of Biomedical and Health Informatics 2020;24(6):1738 View
  2. Broome D, Hilton C, Mehta N. Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management. Current Diabetes Reports 2020;20(2) View
  3. Sforzo G, Kaye M, Harenberg S, Costello K, Cobus-Kuo L, Rauff E, Edman J, Frates E, Moore M. Compendium of Health and Wellness Coaching: 2019 Addendum. American Journal of Lifestyle Medicine 2020;14(2):155 View
  4. Van Rhoon L, Byrne M, Morrissey E, Murphy J, McSharry J. A systematic review of the behaviour change techniques and digital features in technology-driven type 2 diabetes prevention interventions. DIGITAL HEALTH 2020;6:205520762091442 View
  5. Sequi-Dominguez I, Alvarez-Bueno C, Martinez-Vizcaino V, Fernandez-Rodriguez R, del Saz Lara A, Cavero-Redondo I. Effectiveness of Mobile Health Interventions Promoting Physical Activity and Lifestyle Interventions to Reduce Cardiovascular Risk Among Individuals With Metabolic Syndrome: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(8):e17790 View
  6. Contreras I, Vehi J. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review. Journal of Medical Internet Research 2018;20(5):e10775 View
  7. Gimbel R, Rennert L, Crawford P, Little J, Truong K, Williams J, Griffin S, Shi L, Chen L, Zhang L, Moss J, Marshall R, Edwards K, Crawford K, Hing M, Schmeltz A, Lumsden B, Ashby M, Haas E, Palazzo K. Enhancing Patient Activation and Self-Management Activities in Patients With Type 2 Diabetes Using the US Department of Defense Mobile Health Care Environment: Feasibility Study. Journal of Medical Internet Research 2020;22(5):e17968 View
  8. Muralidharan S, Ranjani H, Mohan Anjana R, Jena S, Tandon N, Gupta Y, Ambekar S, Koppikar V, Jagannathan N, Allender S, Mohan V. Engagement and Weight Loss: Results from the Mobile Health and Diabetes Trial. Diabetes Technology & Therapeutics 2019;21(9):507 View
  9. Li J, Huang J, Zheng L, Li X. Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect. Frontiers in Public Health 2020;8 View
  10. Bradway M, Pfuhl G, Joakimsen R, Ribu L, Grøttland A, Årsand E, Borsci S. Analysing mHealth usage logs in RCTs: Explaining participants’ interactions with type 2 diabetes self-management tools. PLOS ONE 2018;13(8):e0203202 View
  11. Vehi J, Regincós Isern J, Parcerisas A, Calm R, Contreras I. Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study. JMIR mHealth and uHealth 2019;7(3):e11933 View
  12. Gershkowitz B, Hillert C, Crotty B. Digital Coaching Strategies to Facilitate Behavioral Change in Type 2 Diabetes: A Systematic Review. The Journal of Clinical Endocrinology & Metabolism 2021;106(4):e1513 View
  13. Kaasalainen K, Kalmari J, Ruohonen T. Developing and testing a discrete event simulation model to evaluate budget impacts of diabetes prevention programs. Journal of Biomedical Informatics 2020;111:103577 View
  14. Sieczkowska S, de Lima A, Swinton P, Dolan E, Roschel H, Gualano B. Health Coaching Strategies for Weight Loss: A Systematic Review and Meta-Analysis. Advances in Nutrition 2021;12(4):1449 View
  15. Pham Q, Gamble A, Hearn J, Cafazzo J. The Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations. Journal of Medical Internet Research 2021;23(2):e22320 View
  16. Nelson A, Moses O, Rea B, Morton K, Shih W, Alramadhan F, Singh P. Pilot Feasibility Study of Incorporating Whole Person Care Health Coaching Into an Employee Wellness Program. Frontiers in Public Health 2021;8 View
  17. Chew H, Ang W, Lau Y. The potential of artificial intelligence in enhancing adult weight loss: a scoping review. Public Health Nutrition 2021;24(8):1993 View
  18. Tong H, Quiroz J, Kocaballi A, Fat S, Dao K, Gehringer H, Chow C, Laranjo L. Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression. Preventive Medicine 2021;148:106532 View
  19. Schneider-Kamp A. The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2021;58:004695802110179 View
  20. Thomas Craig K, Morgan L, Chen C, Michie S, Fusco N, Snowdon J, Scheufele E, Gagliardi T, Sill S. Systematic review of context-aware digital behavior change interventions to improve health. Translational Behavioral Medicine 2021;11(5):1037 View