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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Sep 22, 2025
Open Peer Review Period: Sep 22, 2025 - Nov 17, 2025
Date Accepted: Mar 31, 2026
(closed for review but you can still tweet)

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

Experiences and Perceived Influence of the Artificial Intelligence–Based Health Education Accurately Linking System (AI-HEALS) on Health Behaviors Among Patients With Type 2 Diabetes: Qualitative Study

Wang J, Wu Y, Jiang Y, Bao R, Gu X, Kong B, Sun X

Experiences and Perceived Influence of the Artificial Intelligence–Based Health Education Accurately Linking System (AI-HEALS) on Health Behaviors Among Patients With Type 2 Diabetes: Qualitative Study

J Med Internet Res 2026;28:e84605

DOI: 10.2196/84605

PMID: 42118150

Experiences and Perceived Influence of the Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) on Health Behaviors among Patients with Type 2 Diabetes: A Qualitative Study

  • Jing Wang; 
  • Yibo Wu; 
  • Yang Jiang; 
  • Rantong Bao; 
  • Xinbao Gu; 
  • Bingyang Kong; 
  • Xinying Sun

ABSTRACT

Background:

The management of type 2 diabetes requires comprehensive self-management strategies that include diet, physical activity, medication adherence, and blood-glucose monitoring. In recent years, Artificial Intelligence-based intervention have shown promise in supporting these behaviors. However, evidence on user experience remains limited.

Objective:

This study aims to explore patients' experiences with Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) and their perceived influence on self-management behaviors among patients with type 2 diabetes.

Methods:

This qualitative study employed purposive maximum-variation sampling to conduct semistructured interviews with 17 patients with type 2 diabetes who had used the AI-HEALS. Interviews were conducted three months after the intervention (August–December 2023) with participants recruited from 45 communities in the Daxing and Shunyi Districts of Beijing. The interview guide focused on behavior change (diet, activity, medication, glucose monitoring) and interaction with the AI-HEALS system. Transcripts were coded in NVivo 12 and analyzed thematically by two independent researchers with consensus procedures and member checking.

Results:

Participants’ experiences with AI-HEALS were reflected in the following themes: (1) Catalyzing Health Awareness and Concern; (2) Empowering Self-Management Practices; (3) Navigating Usability and Engagement; and (4) Enhancing Psychological Adaptation. Participants perceived that AI-HEALS enhanced their health knowledge, improved self-management behaviors and self-efficacy, and alleviated diabetes-related psychological stress and largely through personalized advice.

Conclusions:

This study suggests that patients perceive AI-HEALS as potentially supporting self-management behaviors and self-efficacy among patients with type 2 diabetes. Clinical Trial: This study has been registered at Chinese Clinical Trial Registry: ChiCTR2300068952, 02/03/2023, https://www.chictr.org.cn/index.html.


 Citation

Please cite as:

Wang J, Wu Y, Jiang Y, Bao R, Gu X, Kong B, Sun X

Experiences and Perceived Influence of the Artificial Intelligence–Based Health Education Accurately Linking System (AI-HEALS) on Health Behaviors Among Patients With Type 2 Diabetes: Qualitative Study

J Med Internet Res 2026;28:e84605

DOI: 10.2196/84605

PMID: 42118150

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