STUDY PROTOCOL article

Front. Med.

Sec. Pulmonary Medicine

Study Protocol: Artificial Intelligence Health Education Accurately Linking System for Enhancing Self-Management in Chronic Obstructive Pulmonary Disease Patients via WeChat

    JW

    Ju Wu 1

    YL

    Yun-Hua Li 2

    TH

    Tingting He 1

    YG

    Yan Guo 1

    JZ

    Jing Zhong 1

    LW

    Lifen Wang 1

    ZX

    Zhen Xiao 1

    PW

    Ping Wang 1

    PL

    Ping Li 1

    XS

    Xia Shu 1

    QG

    Qiuhong Guo 1

    QY

    Qing Yuan 1

    LQ

    Lijuan Qiu 1

    NY

    Ni Yang 3

    LL

    Liping Liao 1

  • 1. Zigong First People's Hospital, Zigong, China

  • 2. Chengdu University of Arts and Sciences, Chengdu, China

  • 3. Henan University of Science and Technology, Luoyang, China

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Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a widespread chronic illness that affects millions of people around the world. Its management not only necessitates medical intervention but also long-term patient self-management. Most traditional self-management education fails to address individualized needs and ongoing support. With improvements in information technology, especially in the application of artificial intelligence (AI) for health management, new avenues have emerged that can improve COPD patients' self-management capacity, ultimately leading to better disease control and improved quality of life. Thus, we have developed an AI Health Education Accurately Linking System (AI-HEALS) to examine if AI-HEALS-based intervention is effective in enhancing COPD patients' ability for self-management, ultimately leading to better disease management and improved quality of life. Methods and Analysis: This randomized controlled trial (RCT) aims to evaluate the efficacy of AI-HEALS intervention implemented through WeChat platform in improving self-management ability of COPD patients. Eligible COPD patients meeting the inclusion criteria will be randomly assigned to either an intervention group or a control group. The control group will receive standard treatment, while the intervention group will receive the AI-HEALS program in addition to standard treatment. The AI-HEALS system is an AI driven question and answer platform with integrated voice interaction capabilities, designed to facilitate easier interaction between patients and the system. It provides real-time physiological monitoring, medication and behavior reminders, and personalized health education through the "COPD Health Management Expert" WeChat platform. The system is supported by a self-developed knowledge base based on established clinical guidelines and evidence for COPD, ensuring the accuracy and reliability of the information provided. Outcome measurements will be conducted at multiple time points, including baseline (upon enrollment), hospital discharge, the end of the intervention, and at 3, 6, and 9 months after the completion of the intervention. Ethics and Dissemination: Ethical approval for the study was obtained from the Medical Ethics Committee of Zigong First People's Hospital (Ethics No. Ethics (Research) 2024, Issue 152, 31/10/2024). The clinical trial is registered under ChiCTR2400092829, with registration completed on 25/11/2024.

Summary

Keywords

artificial intelligence, Chronic Disease, chronic obstructive pulmonary disease, Large Language Model, mobile health, rct

Received

06 January 2026

Accepted

20 February 2026

Copyright

© 2026 Wu, Li, He, Guo, Zhong, Wang, Xiao, Wang, Li, Shu, Guo, Yuan, Qiu, Yang and Liao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Liping Liao

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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