Abstract：
Prehypertension, an early stage in the development of hypertension, impacts a substantial segment of the adult population worldwide. Addressing this issue, our study introduces HabitBot, an AI-driven chatbot tailored to encourage physical activity (PA) habits among individuals with prehypertension. HabitBot combines natural language processing with multidisciplinary approaches, drawing from both theoretical frameworks and empirical studies. The chatbot development followed a systematic, five-phase process: comprehensive needs assessment, literature review on behavior change theories, analysis for selecting effective behavior change techniques (BCTs), prototype design through intervention mapping, and refining the intervention based on user feedback. The outcome includes a prototype that integrates the Health Action Process Approach and Habit Formation Theory, utilizing twelve identified BCTs effective in fostering PA habits. User feedback further refined the chatbot across multiple dimensions such as user interface, content accessibility, and privacy. HabitBot exemplifies an innovative integration of behavior change strategies with advanced language model technology, paving the way for digital health interventions in chronic disease prevention. Future studies should assess its long-term efficacy in habit formation and explore its applicability to various demographic groups.
摘要：
高血压前期,高血压发展的早期阶段，影响了全世界很大一部分成年人。解决这个问题，我们的研究介绍了HabitBot,一种人工智能驱动的聊天机器人，旨在鼓励高血压前期患者的体育锻炼(PA)习惯。HabitBot将自然语言处理与多学科方法相结合，借鉴理论框架和实证研究。聊天机器人的开发遵循了一个系统的，五阶段过程：全面需求评估，关于行为改变理论的文献综述，选择有效的行为改变技术(BCT)的分析，通过干预映射进行原型设计，并根据用户反馈改进干预。结果包括一个原型，集成了健康行动过程方法和习惯形成理论，利用12个确定的BCT有效培养PA习惯。用户反馈进一步完善了跨多个维度的聊天机器人，例如用户界面，内容可访问性,和隐私。HabitBot体现了行为改变策略与高级语言模型技术的创新集成，为慢性病预防中的数字健康干预措施铺平了道路。未来的研究应评估其在习惯形成中的长期功效，并探索其对各种人口统计学群体的适用性。
