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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 9, 2024
Date Accepted: Oct 14, 2024

The final, peer-reviewed published version of this preprint can be found here:

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

Wu Y, Zhang J, Ge P, Duan T, Zhou J, Wu Y, Zhang Y, Liu S, Liu X, Wan E, Sun X

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

J Med Internet Res 2024;26:e60380

DOI: 10.2196/60380

PMID: 39626235

PMCID: 11653048

Application of Chatbots in the Patients Self-manage Diabetes: A Systematic Review and Meta-analysis

  • Yibo Wu; 
  • Jinzi Zhang; 
  • Pu Ge; 
  • Tingyu Duan; 
  • Junyu Zhou; 
  • Yiwei Wu; 
  • Yuening Zhang; 
  • Siyu Liu; 
  • Xinyi Liu; 
  • Erya Wan; 
  • Xinying Sun

ABSTRACT

Background:

Diabetes patients need personalized health education for better diabetes control, and chatbots can provide personalized health education functions.

Objective:

This study systematically reviews the current research status and effectiveness of chatbots in the field of diabetes self-management education to support the development of diabetes chatbots.

Methods:

A systematic review and Meta-analysis of studies compliant with chatbots related to self-health education for diabetes patients. The AHRQ assessment tool was adopted for article quality assessment. Research articles in English that fit the study topic were selected, and articles that did not fit the study topic and were not available in full text were excluded. Information sources PubMed and Web of Science databases Retrieved until January 1, 2023.

Results:

A total of 25 studies were included in the review. Chatbots provide services involving both physical and psychological aspects. The criteria for assessing the effectiveness of chatbots can be categorized into technical performance assessment, user experience assessment and user health assessment. Overall, the results of the technical evaluation of the chatbot model were good, and the overall acceptance of chatbots by users was high. In terms of study design, most of the articles in the intervention studies were before-and-after trials, and only one article used a randomized controlled trial (RCT). The meta-analysis found that the chatbot intervention was effective in lowering blood glucose [MD=0.30, 95% CI (0.04, 0.55), P=0.02] and had no significant effect in reducing weight [MD=1.41, 95% CI (-2.29, 5.11), P=0.46] compared with baseline.

Conclusions:

Chatbots have the potential for development in self-management education for people with diabetes. However, the current level of research evidence is low and further high-level studies (e.g., RCTs) are needed to strengthen the evidence base. In addition, researchers should focus on the personalized and user-friendly interactive features of chatbots, as well as improvements in study design.


 Citation

Please cite as:

Wu Y, Zhang J, Ge P, Duan T, Zhou J, Wu Y, Zhang Y, Liu S, Liu X, Wan E, Sun X

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

J Med Internet Res 2024;26:e60380

DOI: 10.2196/60380

PMID: 39626235

PMCID: 11653048

Per the author's request the PDF is not available.

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