SCH: INT: The Virtual Assistant Health Coach: Learning to Autonomously Improve Health Behaviors

健康指导是一种改善健康行为的有效过程，方法是提供健康相关主题的教育，设定个性化和可实现的健康相关目标，监测和鼓励实现这些目标的进展，以及随着时间的推移对健康目标的进展进行排序或细化。虽然有用，但其高度个性化和劳动密集型的性质使得有效的健康指导的成本对于许多服务不足的人群来说是令人望而却步的，他们可能会从中受益匪浅。该项目将开发一个虚拟健康教练系统，该系统将学习人类健康教练演示，通过智能消息系统(SMS)与患者互动，以制定具体、可衡量、可实现、相关和及时(智能)的适当健康目标。虚拟教练将逐渐变得更加独立，但不会完全自主，原因有两个：第一，在现阶段的研究阶段，人们不能相信系统在遇到独特情况时总是会发送适当的消息；第二，虚拟教练不会替补，而是补充/与人类教练合作。这些功能的成功开发代表着朝着更具可扩展性的健康教练系统迈出了重要的一步，该系统不会牺牲人类健康教练实现的有效性。该项目开发了虚拟健康教练系统的两个关键组件：对话管理和情绪分析组件，用于指导和分析与用户的交流；以及模仿学习组件，用于从人类健康教练与用户的交互中学习高级智能目标设置和教练策略。需要取得重大的技术进步，以解决这些分领域的根本问题，以实现人类水平的健康指导效力和积极的健康结果率。这些方法包括：新的自然语言处理方法，用于处理非正式、简洁的短消息，包括它们所传达的情感和情绪；通过诸如主动性等语言代理表达越来越多的自主性；以及使观察到的行为合理化的逆最优控制方法。在初步可行性研究的基础上，该项目将评估开发的虚拟健康教练的好处，该虚拟健康教练具有不同程度的智能目标设置自主权，并通过短信和健身跟踪设备为不同范围的用户提供额外的健康教练。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Health coaching is an effective process for improving health behaviors by providing education on health-related topics, setting personalized and realizable health-related goals, monitoring and encouraging progress towards those goals, and sequencing or refining a progression of health goals over time. Though useful, its highly personalized and labor-intensive nature makes the cost of effective health coaching prohibitive for many underserved populations that could benefit significantly from it. This project will develop a virtual health coaching system that learns from human health coach demonstrations to interact with patients via the smart message system (SMS) to set appropriate health goals that are Specific, Measurable, Attainable, Relevant, and Timely (SMART). The virtual coach will become progressively more independent, but will not be fully autonomous for two reasons: first, at this stage of research, one cannot trust the system to always send appropriate messages when it encounters unique situations; second, the virtual coach would not substitute, but supplement/collaborate with a human coach. Successful development of these capabilities represents an important step towards more scalable health coaching systems that do not sacrifice the effectiveness realized by a human health coach.This project develops the two key components of a virtual health coaching system: a dialogue management and sentiment analysis component that guides and analyzes communication with users; and an imitation learning component for learning high-level SMART goal-setting and coaching strategies from the human health coach's interactions with users. Significant technical advances that address the underlying problems from these sub-areas are needed to achieve human-level health coaching efficacy and positive health outcome rates. These include: novel natural language processing methods to process informal, concise SMS including the emotion and mood they convey; expression of increasing autonomy via linguistic proxies such as initiative; and inverse optimal control methods for rationalizing observed behavior. Building on an initial feasibility study, this project will assess the benefits of a developed virtual health coach with varying degrees of autonomy for SMART goal setting and additional health coaching for a diverse range of users through SMS and fitness tracking devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.