聊天机器人
随机对照试验
医学
初级保健
临床终点
电子健康
经济短缺
家庭医学
替代医学
护理部
公共卫生
医疗保健
初级卫生保健
临床试验
基线(sea)
农村卫生
社区卫生
远程医疗
物理疗法
医学教育
治疗组和对照组
社区参与研究
研究设计
梅德林
心理学
通俗的语言
作者
Sairan Li,Yaneng Li,Shuya Zhou,Xinge Tao,Changjie Yu,Muzi Shen,Wangyue Chen,En Meng,Boyou Wu,Qirui Huang,Frances S Mair,Jinchao Zhang,Jie Zhou,Lei Zou,Shasha Han
标识
DOI:10.1038/s44360-025-00021-w
摘要
Abstract With a global shortage of primary healthcare physicians—particularly in resource-limited settings—large language models (LLMs) have the potential to support and enhance patients’ health awareness. Here we developed P&P Care (Population Medicine and Public Health), an LLM-powered primary care chatbot using a dual-track role-play codesign framework where community stakeholders and researchers simulated each another’s perspectives across four phases: contextual understanding; cocreation; testing and refinement; and implementation and evolution. The codesigned chatbot was integrated with e-learning modules and tested in a randomized controlled trial. The trial included 2,113 participants (1,052 women and 1,061 men) from urban and rural areas across 11 Chinese provinces who were randomly assigned to receive a consultation either with preparatory e-learning via the P&P Care or without. The study met its primary endpoint with the e-learning group showing significantly higher objective health awareness (mean score 2.95 ± 1.22) compared with the consultation-only group (mean score 2.34 ± 1.02; P < 0.001). Codesign offers a scalable solution for deploying LLMs in resource-limited settings. Chinese Clinical Trial Registry identifier: ChiCTR2500098101 .
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