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

RCTs - Protocols/Proposals (eHealth) (667) Electronic Health Records (1319) Apps, Mobile, Wearables for Diabetes (363) Fitness Trackers and Smart Pedometers/Accelerometers (665)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10009, first published .
Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Authors of this article:

Jing Wang1 Author Orcid Image ;   Deidra Carroll Coleman1 Author Orcid Image ;   Justin Kanter2 Author Orcid Image ;   Brad Ummer3 Author Orcid Image ;   Linda Siminerio4 Author Orcid Image
Article Authors Cited by (22) Tweetations (9) Metrics

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  12. 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
  13. Bardram J, Cramer-Petersen C, Maxhuni A, Christensen M, Bækgaard P, Persson D, Lind N, Christensen M, Nørgaard K, Khakurel J, Skinner T, Kownatka D, Jones A. DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. ACM Transactions on Computing for Healthcare 2023;4(2):1 View
  14. Mitchaï P, Mapinduzi J, Verbrugghe J, Michiels S, Janssens L, Kossi O, Bonnechère B, Timmermans A. Mobile technologies for rehabilitation in non-specific spinal disorders: a systematic review of the efficacy and potential for implementation in low- and middle-income countries. European Spine Journal 2023;32(12):4077 View
  15. Chato L, Regentova E. Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data. Journal of Personalized Medicine 2023;13(12):1703 View
  16. 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
  17. Zhao F, Balthazaar S, Hiremath S, Nightingale T, Panza G. Enhancing Spinal Cord Injury Care: Using Wearable Technologies for Physical Activity, Sleep, and Cardiovascular Health. Archives of Physical Medicine and Rehabilitation 2024;105(10):1997 View
  18. Bhargava Y, Kumar Kattupalli K, Baths V. CogTrack: A Proof of Concept for Cognition Tracker. IEEE Access 2024;12:194609 View
  19. Wang Y, Park J, Zhang C, Jukic A, Baird D, Coull B, Hauser R, Mahalingaiah S, Zhang S, Curry C. Performance of algorithms using wrist temperature for retrospective ovulation day estimate and next menses start day prediction: a prospective cohort study. Human Reproduction 2025;40(3):469 View
  20. Du Z, Zhang F, Ge Y, Liu Y, Yu H, Wang Y, Dalan R, Shen X. Application of Wearable Devices in Diabetes Management. Health and Metabolism 2025:7 View

Books/Policy Documents

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