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

Diabetes Self-Management (525) Apps, Mobile, Wearables for Diabetes (330) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1544)

Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41501, first published .
Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample

Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample

Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample

Authors of this article:

Karim Zahed1 Author Orcid Image ;   Ranjana Mehta1 Author Orcid Image ;   Madhav Erraguntla1 Author Orcid Image ;   Khalid Qaraqe2 Author Orcid Image ;   Farzan Sasangohar1, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Dave D, Vyas K, Cote G, Erraguntla M. Hypoglycemia and hyperglycemia detection using ECG: A multi-threshold based personalized fusion model. Biomedical Signal Processing and Control 2024;96:106569 View
  2. Alamer A. Predictors of Type-2 Diabetes Self-Screening: The Impact of Health Beliefs Model, Knowledge, and Demographics. International Journal of Statistics in Medical Research 2025;14:45 View
  3. Fan J, Li J, Duan C, Zhao Q, Guo Y. Utilization and Influencing Factors of Mobile Health Applications in Diabetes Management. CIN: Computers, Informatics, Nursing 2025 View