Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/4478, first published .
A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial

A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial

A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial

Journals

  1. Wang J, Chu C, Li C, Hayes L, Siminerio L. Diabetes Educators’ Insights Regarding Connecting Mobile Phone– and Wearable Tracker–Collected Self-Monitoring Information to a Nationally-Used Electronic Health Record System for Diabetes Education: Descriptive Qualitative Study. JMIR mHealth and uHealth 2018;6(7):e10206 View
  2. Chawla R, Madhu S, Makkar B, Ghosh S, Saboo B, Kalra S. RSSDI-ESI Clinical Practice Recommendations for the Management of Type 2 Diabetes Mellitus 2020. International Journal of Diabetes in Developing Countries 2020;40(S1):1 View
  3. Yin Z, Lesser J, Paiva K, Zapata Jr J, Moreno-Vasquez A, Grigsby T, Ryan-Pettes S, Parra-Medina D, Estrada V, Li S, Wang J. Using Mobile Health Tools to Engage Rural Underserved Individuals in a Diabetes Education Program in South Texas: Feasibility Study. JMIR mHealth and uHealth 2020;8(3):e16683 View
  4. Chawla R, Madhu S, Makkar B, Ghosh S, Saboo B, Kalra S. RSSDI-ESI clinical practice recommendations for the management of type 2 diabetes mellitus 2020. Indian Journal of Endocrinology and Metabolism 2020;24(1):1 View
  5. Du Y, Dennis B, Rhodes S, Sia M, Ko J, Jiwani R, Wang J. Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study. JMIR Diabetes 2020;5(3):e21183 View
  6. Asbjørnsen R, Wentzel J, Smedsrød M, Hjelmesæth J, Clark M, Solberg Nes L, Van Gemert-Pijnen J. Identifying Persuasive Design Principles and Behavior Change Techniques Supporting End User Values and Needs in eHealth Interventions for Long-Term Weight Loss Maintenance: Qualitative Study. Journal of Medical Internet Research 2020;22(11):e22598 View
  7. Guthrie N, Carpenter J, Edwards K, Appelbaum K, Dey S, Eisenberg D, Katz D, Berman M. Emergence of digital biomarkers to predict and modify treatment efficacy: machine learning study. BMJ Open 2019;9(7):e030710 View
  8. 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
  9. Faruqui S, Du Y, Meka R, Alaeddini A, Li C, Shirinkam S, Wang J. Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial. JMIR mHealth and uHealth 2019;7(11):e14452 View
  10. Alkawaldeh M, Jacelon C, Choi J. Older adults' experiences with a tablet-based self-management intervention for diabetes mellitus type II: A qualitative study. Geriatric Nursing 2020;41(3):305 View
  11. Sittig S, McGowan A, Iyengar S. Extensive Review of Persuasive System Design Categories and Principles: Behavioral Obesity Interventions. Journal of Medical Systems 2020;44(7) View
  12. Halse R, Shoneye C, Pollard C, Jancey J, Scott J, Pratt I, Dhaliwal S, Norman R, Straker L, Boushey C, Delp E, Zhu F, Harray A, Szybiak M, Finch A, McVeigh J, Mullan B, Collins C, Mukhtar S, Edwards K, Healy J, Kerr D. Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial. JMIR Research Protocols 2019;8(2):e12782 View
  13. Huh U, Tak Y, Song S, Chung S, Sung S, Lee C, Bae M, Ahn H. Feedback on Physical Activity Through a Wearable Device Connected to a Mobile Phone App in Patients With Metabolic Syndrome: Pilot Study. JMIR mHealth and uHealth 2019;7(6):e13381 View
  14. Karampela M, Isomursu M, Porat T, Maramis C, Mountford N, Giunti G, Chouvarda I, Lehocki F. The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study. Journal of Medical Internet Research 2019;21(9):e14394 View
  15. Jiwani R, Wang J, Berndt A, Ramaswamy P, Mathew Joseph N, Du Y, Ko J, Espinoza S. Changes in Patient-Reported Outcome Measures With a Technology-Supported Behavioral Lifestyle Intervention Among Patients With Type 2 Diabetes: Pilot Randomized Controlled Clinical Trial. JMIR Diabetes 2020;5(3):e19268 View
  16. Suen L, Wang W, Cheng K, Chua M, Yeung J, Koh W, Yeung S, Ho J. Self-Administered Auricular Acupressure Integrated With a Smartphone App for Weight Reduction: Randomized Feasibility Trial. JMIR mHealth and uHealth 2019;7(5):e14386 View
  17. Ifejika N, Bhadane M, Cai C, Noser E, Grotta J, Savitz S. Use of a Smartphone-Based Mobile App for Weight Management in Obese Minority Stroke Survivors: Pilot Randomized Controlled Trial With Open Blinded End Point. JMIR mHealth and uHealth 2020;8(4):e17816 View
  18. Cavero-Redondo I, Martinez-Vizcaino V, Fernandez-Rodriguez R, Saz-Lara A, Pascual-Morena C, Álvarez-Bueno C. Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis. Nutrients 2020;12(7):1977 View
  19. Jiwani R, Dennis B, Bess C, Monk S, Meyer K, Wang J, Espinoza S. Assessing acceptability and patient experience of a behavioral lifestyle intervention using fitbit technology in older adults to manage type 2 diabetes amid COVID-19 pandemic: A focus group study. Geriatric Nursing 2021;42(1):57 View
  20. De Groot J, Wu D, Flynn D, Robertson D, Grant G, Sun J. Efficacy of telemedicine on glycaemic control in patients with type 2 diabetes: A meta-analysis. World Journal of Diabetes 2021;12(2):170 View
  21. Mehraeen E, Noori T, Nazeri Z, Heydari M, Mehranfar A, Moghaddam H, Aghamohammadi V. Identifying features of a mobile-based application for self-care of people living with T2DM. Diabetes Research and Clinical Practice 2021;171:108544 View
  22. Brewer L, Kumbamu A, Smith C, Jenkins S, Jones C, Hayes S, Burke L, Cooper L, Patten C. A Cardiovascular Health and Wellness Mobile Health Intervention Among Church-Going African Americans: Formative Evaluation of the FAITH! App. JMIR Formative Research 2020;4(11):e21450 View
  23. Krishnakumar A, Verma R, Chawla R, Sosale A, Saboo B, Joshi S, Shaikh M, Shah A, Kolwankar S, Mattoo V. Evaluating Glycemic Control in Patients of South Asian Origin With Type 2 Diabetes Using a Digital Therapeutic Platform: Analysis of Real-World Data. Journal of Medical Internet Research 2021;23(3):e17908 View
  24. McLeod A, Schiffer L, Castellanos K, DeMott A, Olender S, Fitzgibbon M, Hughes S, Fantuzzi G, Tussing-Humphreys L. Impact of Physical Activity and Weight Loss on Fat Mass, Glucose Metabolism, and Inflammation in Older African Americans with Osteoarthritis. Nutrients 2020;12(11):3299 View
  25. Hwang N, Park J, Chang M. Telehealth Interventions to Support Self-Management in Stroke Survivors: A Systematic Review. Healthcare 2021;9(4):472 View
  26. Tamilselvi S, Saravana Kumar N, Lavanya S, Bindhu J, Kaviyavarshini N. RETRACTED ARTICLE: Artificial intelligence for a bio-sensored detection of tuberculosis. Network Modeling Analysis in Health Informatics and Bioinformatics 2021;10(1) View
  27. Ko J, Wang J, Du Y, Jiwani R, Li C. Personalized Behavioral Nutrition Among Older Asian Americans. Nursing Research 2021;70(4):317 View
  28. Hamasaki H. Efficacy of Wearable Devices to Measure and Promote Physical Activity in the Management of Diabetes. EMJ Diabetes 2018:62 View
  29. Su Z, Meyer K, Li Y, McDonnell D, Joseph N, Li X, Du Y, Advani S, Cheshmehzangi A, Ahmad J, da Veiga C, Chung R, Wang J, Hao X. Technology-based interventions for nursing home residents: a systematic review protocol. BMJ Open 2021;11(12):e056142 View
  30. Li S, Yin Z, Lesser J, Li C, Choi B, Parra-Medina D, Flores B, Dennis B, Wang J. Community Health Worker-Led mHealth-Enabled Diabetes Self-management Education and Support Intervention in Rural Latino Adults: Single-Arm Feasibility Trial. JMIR Diabetes 2022;7(2):e37534 View
  31. Kamstra R, Boorsma A, Krone T, van Stokkum R, Eggink H, Peters T, Pasman W. Validation of the Mobile App Version of the EQ-5D-5L Quality of Life Questionnaire Against the Gold Standard Paper-Based Version: Randomized Crossover Study. JMIR Formative Research 2022;6(8):e37303 View
  32. Khani Jeihooni A, Sobhani A, Afzali Harsini P, Amirkhani M. Effect of educational intervention based on PRECEDE model on lifestyle modification, self-management behaviors, and hypertension in diabetic patients. BMC Endocrine Disorders 2023;23(1) View
  33. Karimi N, Opie R, Crawford D, O’Connell S, Hamblin P, Steele C, Ball K. Participants’ and Health Care Providers’ Insights Regarding a Web-Based and Mobile-Delivered Healthy Eating Program for Disadvantaged People With Type 2 Diabetes: Descriptive Qualitative Study. JMIR Formative Research 2023;7:e37429 View
  34. Cyriac J, Jenkins S, Patten C, Hayes S, Jones C, Cooper L, Brewer L. Improvements in Diet and Physical Activity–Related Psychosocial Factors Among African Americans Using a Mobile Health Lifestyle Intervention to Promote Cardiovascular Health: The FAITH! (Fostering African American Improvement in Total Health) App Pilot Study. JMIR mHealth and uHealth 2021;9(11):e28024 View
  35. Cucciniello M, Petracca F, Ciani O, Tarricone R. Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials. npj Digital Medicine 2021;4(1) View
  36. Bonn S, Licitra G, Bellocco R, Trolle Lagerros Y. Clinical Outcomes Among Working Adults Using the Health Integrator Smartphone App: Analyses of Prespecified Secondary Outcomes in a Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(3):e24725 View
  37. Geurts K, Ozcan B, van Hoek M, van de Laar R, van Teeffelen J, van Rosmalen J, van Rossum E, Berk K. The (cost) effectiveness of a very low-energy diet intervention with the use of eHealth in patients with type 2 diabetes and obesity: study protocol for a randomised controlled non-inferiority trial (E-diet trial). Trials 2023;24(1) View
  38. Karimi N, Opie R, Crawford D, O’Connell S, Ball K. Digitally Delivered Interventions to Improve Nutrition Behaviors Among Resource-Poor and Ethnic Minority Groups With Type 2 Diabetes: Systematic Review. Journal of Medical Internet Research 2024;26:e42595 View
  39. Geurts K, Woodcock-Nekeman S, Hummel M, Dietvorst C, van Rossum E, Berk K. The Effect of Including eHealth in Dietary Interventions for Patients with Type 2 Diabetes with Overweight or Obesity: A Systematic Review. Nutrients 2023;15(17):3776 View
  40. Hodgson W, Kirk A, Lennon M, Janssen X, Russell E, Wani C, Eskandarani D. RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) Evaluation of the Use of Activity Trackers in the Clinical Care of Adults Diagnosed With a Chronic Disease: Integrative Systematic Review. Journal of Medical Internet Research 2023;25:e44919 View
  41. Okpako T, Woodward A, Walters K, Davies N, Stevenson F, Nimmons D, Chew-Graham C, Protheroe J, Armstrong M. Effectiveness of self-management interventions for long-term conditions in people experiencing socio-economic deprivation in high-income countries: a systematic review and meta-analysis. Journal of Public Health 2023;45(4):970 View
  42. Ma X, Fan W, Zhang X, Zhang S, Feng X, Song S, Wang H. The urban-rural disparities and factors associated with the utilization of public health services among diabetes patients in China. BMC Public Health 2023;23(1) View
  43. Jin T, Kang G, Song S, Lee H, Chen Y, Kim S, Shin M, Park Y, Lee J. The effects of dietary self-monitoring intervention on anthropometric and metabolic changes via a mobile application or paper-based diary: a randomized trial. Nutrition Research and Practice 2023;17(6):1238 View
  44. Shaw Jr G, Castro B, Gunn L, Norris K, Thorpe Jr R. The Association of eHealth Literacy Skills and mHealth Application Use Among US Adults With Obesity: Analysis of Health Information National Trends Survey Data. JMIR mHealth and uHealth 2024;12:e46656 View
  45. Kumar N, Lavanya S, Kaviyavarshini N. Clarans & birch datamining techniques for disease diagnosis. Multimedia Tools and Applications 2024 View
  46. Gostoli S, Raimondi G, Popa A, Giovannini M, Benasi G, Rafanelli C. Behavioral Lifestyle Interventions for Weight Loss in Overweight or Obese Patients with Type 2 Diabetes: A Systematic Review of the Literature. Current Obesity Reports 2024 View
  47. Ko J, Wang J, Mbue N, Schembre S, Cron S. Effect of the Implementation of A Multiple-Behavior Self-Monitoring Intervention on Dietary Intake in Type 2 Diabetes (Preprint). JMIR Formative Research 2023 View
  48. Tarricone R, Petracca F, Svae L, Cucciniello M, Ciani O. Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials. eBioMedicine 2024;103:105091 View
  49. Heine M, Lupton-Smith A, Pakosh M, Grace S, Derman W, Hanekom S. Exercise-based rehabilitation for major non-communicable diseases in low-resource settings: a scoping review. BMJ Global Health 2019;4(6):e001833 View

Books/Policy Documents

  1. Olaleye S, Gutiérrez-Leefmans M. Design, Operation and Evaluation of Mobile Communications. View