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开发和评估一个大型语言模型集成的聊天机器人干预,用于在患有高血压前期的成年人中形成身体活动习惯

Haoming Ma¹, Hongzhen Cui², Hongyu Yu³

¹School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

|February 16, 2026

概括

使用大型语言模型 (LLM) 的新聊天机器人HabitBot帮助高血压前的成年人建立体力活动 (PA) 习惯. 这种可扩展的工具在预防慢性疾病方面具有很高的可用性.

科学领域:

数字健康数字健康
行为科学行为科学
预防慢性疾病预防慢性疾病

背景情况:

前高血压构成全球健康风险,增加了对高血压的易感性.
持续的体力活动 (PA) 对于血压管理至关重要,但长期坚持是具有挑战性的.
现有的PA习惯形成干预措施在可扩展性和可访问性方面扎,突出需要创新的解决方案.

研究的目的:

介绍HabitBot,一个与LLM集成的聊天机器人,旨在促进成人高血压前期患者的PA习惯.
利用LLM来增强用户交互,并整合多学科证据,以有效地改变行为.
解决慢性疾病管理当前数字健康干预措施的局限性.

主要方法:

采用了五个阶段的系统开发过程,包括需求评估,文献审查和干预映射.
关键的行为改变理论和技术被合成并集成到聊天机器人的设计中.
用户反通过可用性测试和重点小组进行代改进而被纳入.

主要成果:

确定了八个核心用户需求,并将健康行动过程方法与习惯形成理论相结合.
为干预选择了十二种基于证据的行为改变技术 (BCT).
HabitBot原型显示出高可用性,平均得分为3.84 (SD 0.82).

结论:

哈比特机器人 (HabitBot) 是一种新的整合行为改变策略和用于预防慢性疾病的LLM技术.
聊天机器人提供了一个有希望的,可扩展的,可访问的方法来培养体育活动的习惯.
需要进一步的研究来评估HabitBot的长期疗效和通用性.

关键词:

在高血压前,聊天机器人聊天机器人改变健康行为改变健康行为.大型语言模型.移动健康移动健康移动健康移动健康身体活动身体活动

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