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

Digital Health Reviews (1724) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) mHealth for Patient Education (292) Chatbots and Conversational Agents (740) Diabetes Self-Management (588) Artificial Intelligence (2129) Formative Evaluation of Digital Health Interventions (3229)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60380, first published .
Application of Chatbots to Help Patients Self-Manage Diabetes: Systematic Review and Meta-Analysis

Application of Chatbots to Help Patients Self-Manage Diabetes: Systematic Review and Meta-Analysis

Application of Chatbots to Help Patients Self-Manage Diabetes: Systematic Review and Meta-Analysis

Authors of this article:

Yibo Wu1 Author Orcid Image ;   Jinzi Zhang2, 3 Author Orcid Image ;   Pu Ge4 Author Orcid Image ;   Tingyu Duan5 Author Orcid Image ;   Junyu Zhou6 Author Orcid Image ;   Yiwei Wu7 Author Orcid Image ;   Yuening Zhang8 Author Orcid Image ;   Siyu Liu9 Author Orcid Image ;   Xinyi Liu10 Author Orcid Image ;   Erya Wan11 Author Orcid Image ;   Xinying Sun1 Author Orcid Image
Article Authors Cited by (13) Tweetations (1) Metrics

Journals

  1. Wu Y, Yu Z, Yin X, Li Y, Jiang Y, Liu G, Sun X. Explain the behavior change and maintenance in diabetic patients using MTM-HAPA framework. Frontiers in Psychiatry 2024;15 View
  2. Zugasti Murillo A, Gorgojo Martínez J. De la teleconsulta de la COVID-19 a la teleconsulta de la inteligencia artificial. Endocrinología, Diabetes y Nutrición 2025;72(9):501595 View
  3. Mo Y, Zhao F, Yuan L, Xing Q, Zhou Y, Wu Q, Li C, Lin J, Wu H, Deng S, Zhang M. Healthcare providers’ perceptions of artificial intelligence in diabetes care: A cross-sectional study in China. International Journal of Nursing Sciences 2025;12(3):218 View
  4. Ali S, Bhattacharya S, Chanda A, Dhar B. South Asia’s diabetes crisis needs families: how can we advance from informal care to integrated engagement?. The Lancet Regional Health - Southeast Asia 2025;38:100607 View
  5. Jiang X, Yuan X, Zhao H, Peng J. The Effectiveness and Feasibility of Conversational Agents in Supporting Care for Patients With Cancer: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2025;27:e76968 View
  6. Li C, Li W, Shao Y, Xu Z, Song J, Wang Y. A Scoping Review of Artificial Intelligence-Based Health Education Interventions for Patients with Type 2 Diabetes. Diabetes, Metabolic Syndrome and Obesity 2025;Volume 18:3539 View
  7. Jeon S, Lee S, Kim E, Eun J, Lee K, Lim H, Lee J. Generative AI Chatbot for Diabetes Management: Formative 2-Part Qualitative Study Using DTalksBot Involving Patients and Clinicians. JMIR Formative Research 2025;9:e72553 View
  8. Mohammad talebi H, Safarabadi M, Mousivand M, Zarei A, Fakhari M. Role of artificial intelligence powered chatbots in diabetes self-management: A narrative review. Proceedings of Singapore Healthcare 2025;34 View
  9. Zugasti Murillo A, Gorgojo Martínez J. From COVID-19 telemedicine to artificial intelligence telemedicine. Endocrinología, Diabetes y Nutrición (English ed.) 2025;72(9):501595 View
  10. Furtado V, Araujo J, Furtado E, Bomfim R, Silva V, Mororó N, Vasconcelos L, Carvalho C, Severo M, Torres J, Oliveira J, Freitas A. Assessing the User Experience of an LLM-Based Conversational Assistant in Diabetes Mellitus Care. Journal of Healthcare Informatics Research 2025 View
  11. Begum T, Devi R, Haridas D, Bacanin N, Jovicic M, Nikolic B. My diabetes care: an AI-based mobile app with conversational agent for type 2 diabetes self-management. Scientific Reports 2025;15(1) View

Books/Policy Documents

  1. Tseng Y, Chen S, Mah K, Chen Y. Cross-Cultural Design. View

Conference Proceedings

  1. Mangai S, Supriya A, Kavitha V, Viveka S, Maheswari S, Govindaraj S. 2025 Eleventh International Conference on Bio Signals, Images, and Instrumentation (ICBSII). A Medical Chatbot for Diabetic Patients Using Artificial Intelligence View