SCH: INT: Collaborative Research: FITTLE+: Theory and Models for Smartphone Ecological Momentary Intervention

许多健康状况是由不健康的生活方式引起的，可以通过改变行为来改善。传统的行为改变方法（例如，减肥诊所;私人教练）在向大量人口长期提供专家个性化日常支持方面存在瓶颈。迫切需要扩大现有成功的健康行为改变方法在饮食和健身等领域的范围和强度。智能手机平台提供了一个绝佳的机会，可以以巨大的规模经济将最有效的行为改变干预措施投射到日常生活中。智能手机还提供了一个很好的机会，可以收集丰富的、细粒度的数据，这些数据是理解和预测人们日常生活中行为变化动态所必需的。这些详细测量和干预的机会所带来的挑战是，目前的理论不是同样细粒度和预测。这个跨学科项目研究理论和方法，以支持通过智能手机集成到个人和团体的日常生活中的细粒度行为变化建模和干预。 Fittle+开发了一种新的变革形式的智能手机交付的生态瞬时干预（EMI），以改善饮食和身体活动。这种方法将提供社会支持和自主计划和个性化的辅导，建立在移动的传感，认知辅导和基于证据的社会设计的方法。这种新方法的基础将需要新的健康行为变化预测计算理论。目前粗粒度的个人健康行为变化的概念理论将被细化为细粒度的预测计算模型。这些计算模型将能够基于移动的传感和交互数据跟踪每时每刻的人类环境、活动和社交模式。使用这些监控功能，Fittle+的计算模型将支持基于潜在动机，认知和社会机制的个人用户和群体的评估和预测。这些预测模型还将用于规划和优化辅导行动，包括详细的诊断，个性化的目标，以及情境和个人适应的干预措施。研究人员的合作小组与减肥干预者在全国最大的健康组织之一的设施在夏威夷。该团队包括移动的传感，人工智能，计算认知，社会心理学，人机交互，计算机辅导和测量理论的专业知识。

Many health conditions are caused by unhealthy lifestyles and can be improved by behavior change. Traditional behavior-change methods (e.g., weight-loss clinics; personal trainers) have bottlenecks in providing expert personalized day-to-day support to large populations for long periods. There is a pressing need to extend the reach and intensity of existing successful health behavior change approaches in areas such as diet and fitness. Smartphone platforms provide an excellent opportunity for projecting maximally effective interventions for behavior change into everyday life at great economies of scale. Smartphones also provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting behavior-change dynamics in people going about their everyday lives. The challenge posed by these opportunities for detailed measurement and intervention is that current theory is not equally fine-grained and predictive. This interdisciplinary project investigates theory and methods to support fine-grained behavior-change modeling and intervention integrated via smartphone into the daily lives of individuals and groups. Fittle+ develops a new and transformative form of smartphone-delivered Ecological Momentary Intervention (EMI) for improving diet and physical activity. This approach will provide social support and autonomously planned and personalized coaching that builds on methods from mobile sensing, cognitive tutoring, and evidence-based social design. The foundation for this new approach will require new predictive computational theories of health behavior change. Current coarse-grained conceptual theories of individual health behavior change will be refined into fine-grained predictive computational models. These computational models will be capable of tracking moment-by-moment human context, activity, and social patterns based on mobile sensing and interaction data. Using these monitoring capabilities, Fittle+'s computational models will support assessment of, and predictions about, individual users and groups based on underlying motivational, cognitive, and social mechanisms. These predictive models will also be used to plan and optimize coaching actions including detailed diagnostics, individualized goals, and contextually and personally adapted interventions. The collaborative team of researchers works with weight-loss interventionists at one of nation's largest health organization's facility in Hawaii. The team includes expertise in mobile sensing, artificial intelligence, computational cognition, social psychology, human computer interaction, computer tutoring, and measurement theory.