Study protocol for a randomized controlled trial to evaluate the effectiveness of an artificial intelligence-based health education accurately linking system based on traditional Chinese medicine body constitution in patients with chronic disease multimorbidity.
中国成年人慢性病共病患病率较高，构成了严重的公共卫生挑战。个性化且可及的生活方式干预是改善长期结局的关键。现有的移动健康技术通常提供通用化内容，可及性高，但忽视了基于中医体质开展个体化干预的潜力。中医强调辨识体质类型，以制定更具针对性和全面性的个性化生活方式指导。因此，我们开发了基于中医体质的人工智能健康教育与生活方式支持系统（AI-HEALS），以探索其可行性并评估其在改善临床结局、增强慢性病共病患者自我管理行为方面的初步疗效。本研究采用三臂平行随机对照试验设计。计划招募207名高血压、2型糖尿病和/或高脂血症患者，按1：1：1比例随机分配至常规慢性病管理组、通用型AI-HEALS干预组或基于中医体质的AI-HEALS干预组。常规管理组仅接受标准化慢性病照护。AI-HEALS通过微信小程序部署，具有自动化健康教育内容推送、数字化日记数据记录和智能问答功能。后台知识库涵盖慢性病共病和基于中医体质的养生内容。通用型AI-HEALS组将接受针对慢性病共病的健康教育内容。基于中医体质的AI-HEALS组将首先通过小程序完成体质评估，随后系统将根据其体质类型，从慢性病共病与中医体质养生的联合知识库中推送量身定制的健康管理内容。干预持续3个月，随访至第6个月。主要结局为从基线至干预结束时收缩压的变化。次要结局包括血糖和血脂水平、慢性病自我管理行为等。中医体质分类的变化将作为探索性结局。本研究将中医体质理论与AI-HEALS系统相结合，为慢性病共病提供了一种创新、个性化且可及的管理策略，并力图探索传统医学理论与现代信息技术相结合的价值。本方案描述了一项旨在产生初步疗效证据的随机对照试验。https://www.chictr.org.cn/index.html，标识号ChiCTR2600118267。
The prevalence of chronic disease multimorbidity among Chinese adults is high and presents a serious public health challenge. Personalized and accessible lifestyle interventions are key to improving long-term outcomes. Existing mobile health technologies often deliver generalized content, offering high accessibility but overlooking the potential of individualized interventions informed by Traditional Chinese Medicine (TCM) body constitution. TCM emphasizes identification of constitution types to develop more targeted and comprehensive personalized lifestyle guidance. Therefore, we developed the Artificial Intelligence-Health Education and Lifestyle Support system based on TCM body constitution (AI-HEALS) to explore its feasibility and assess its preliminary efficacy in improving clinical outcomes, enhancing self-management behaviors among patients with chronic disease multimorbidity. This study adopts a three-arm parallel randomized controlled trial design. A total of 207 patients with hypertension, type 2 diabetes, and/or hyperlipidemia will be recruited and randomized in a 1:1:1 ratio into a routine chronic disease management group, a generalized AI-HEALS intervention group, or a TCM-based AI-HEALS intervention group. The routine management group will receive standard chronic disease care only. AI-HEALS is deployed via a WeChat Mini Program and features automated health-education content delivery, digital diaries for data logging, and intelligent Q&A functions. The backend houses a knowledge base covering chronic disease multimorbidity and TCM constitution-based wellness. The generalized AI-HEALS group will receive health-education content targeting chronic disease multimorbidity. The TCM-based AI-HEALS group will first complete a constitution assessment through the Mini Program, after which the system will deliver personalized health-management content tailored to their constitution type, drawing from the combined knowledge base of chronic disease multimorbidity and TCM constitution wellness. The intervention will last 3 months with follow-ups to month 6. The primary outcome is the change in systolic blood pressure from baseline to the end of intervention. Secondary outcomes include blood glucose and lipid levels, chronic-disease self-management behaviors, among others. Changes in TCM constitution classification will be treated as an exploratory outcome. This study integrates TCM constitution theory with the AI-HEALS system to provide an innovative, personalized, and accessible management strategy for chronic disease multimorbidity, and seeks to explore the value of combining traditional medical theory with modern information technology. This protocol describes a randomized controlled trial designed to generate preliminary evidence on effectiveness. https://www.chictr.org.cn/index.html, identifier ChiCTR2600118267.
Qingqing Liu, Yuqi Yang, Yi Hu, Xiaohua Yang, Suxiang Liu, Rantong Bao, et al. Study protocol for a randomized controlled trial to evaluate the effectiveness of an artificial intelligence-based health education accurately linking system based on traditional Chinese medicine body constitution in patients with chronic disease multimorbidity.. Frontiers in public health. 2026; doi:10.3389/fpubh.2026.1773974.
Qingqing Liu, Yuqi Yang, Yi Hu, Xiaohua Yang, Suxiang Liu, Rantong Bao, et al (2026). Study protocol for a randomized controlled trial to evaluate the effectiveness of an artificial intelligence-based health education accurately linking system based on traditional Chinese medicine body constitution in patients with chronic disease multimorbidity.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1773974
Qingqing Liu, Yuqi Yang, Yi Hu, Xiaohua Yang, Suxiang Liu, Rantong Bao, et al. Study protocol for a randomized controlled trial to evaluate the effectiveness of an artificial intelligence-based health education accurately linking system based on traditional Chinese medicine body constitution in patients with chronic disease multimorbidity.[J]. Frontiers in public health, 2026 doi:10.3389/fpubh.2026.1773974.
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