STUDY PROTOCOL article

Front. Psychiatry

Sec. Public Mental Health

Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1585702

This article is part of the Research TopicThe Intersection of Psychology, Healthy Behaviors, and its OutcomesView all 105 articles

The effect of Artificial Intelligence Health Education Accurately Linkage System on childhood asthma: study protocol for a pilot randomized controlled trial

Provisionally accepted
Huan-Fang  WangHuan-Fang Wang1Yun-Hua  LiYun-Hua Li2Qiaoling  ZhangQiaoling Zhang1Lihong  HanLihong Han1Lirong  WangLirong Wang1Lifang  ZhangLifang Zhang1Xue  BaiXue Bai1Mingyue  ChengMingyue Cheng1Ting  ZhangTing Zhang1Fang  ZhaoFang Zhao1Hui  LiHui Li3Xiaoyun  WangXiaoyun Wang1*
  • 1Inner Mongolia Maternal and Child Health Care Hospital, Huhhot, China
  • 2Chengdu College of Arts and Sciences, Chengdu, Sichuan, China
  • 3Shandong Provincial Hospital, Jinan, Shandong Province, China

The final, formatted version of the article will be published soon.

Background: Childhood asthma is a prevalent chronic disease that affects millions of children worldwide. Managing this disease demands not only medical treatment but also the long-term selfmanagement efforts of both children and their parents. Conventional self-management education typically depends on face-to-face approaches, often failing to take into account the personalized requirements and ongoing support needed. Nevertheless, with the evolution of artificial intelligence (AI) technology, fresh prospects have emerged to boost the effectiveness of self-management for childhood asthma. Based on it, we have designed an AI Health Education Accurately Linkage System (AI-HEALS) to explore whether AI-driven interventions can improve self-management capabilities of families with asthmatic children, thereby helping them control the disease and reduce medical costs.Methods: This research is a pilot single-blind randomized controlled trial (RCT) intended to gauge the efficacy of the AI-HEALS intervention delivered via the WeChat platform in enhancing the selfmanagement abilities of families with asthmatic children. Participants will be recruited from eligible families whose children have been diagnosed with asthma and randomly allocated to either the intervention group or the control group. The control group will receive standard treatment, whereas the intervention group will receive both standard treatment and the AI-HEALS intervention. The intervention includes an AI-enabled, voice-activated interactive question-and-answer system, as well as monitoring and recording of physiological indicators, regular reminders, and customized educational articles. All components of the intervention will mainly be provided through a WeChat official account named "Children's Asthma Health Management Expert." AI-HEALS will construct its knowledge base according to pediatric asthma treatment guidelines to enhance the accuracy and reliability of the information it offers. The primary outcome measure is the alteration in asthma symptom control levels, while secondary outcomes comprise a variety of other physiological indicators related to asthma, parents' self-management behaviors, and mental health conditions.Discussion: This study combines AI and mobile health technology to develop the AI-HEALS system, with the aim of assisting families of children with asthma in controlling the disease symptoms. The primary objective is to evaluate whether the intervention can improve asthma symptom control.

Keywords: artificial intelligence, Large Language Model, Childhood asthma, Chronic Disease, mobile health, rct

Received: 01 Mar 2025; Accepted: 06 May 2025.

Copyright: © 2025 Wang, Li, Zhang, Han, Wang, Zhang, Bai, Cheng, Zhang, Zhao, Li and Wang. 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: Xiaoyun Wang, Inner Mongolia Maternal and Child Health Care Hospital, Huhhot, China

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