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

SCH：INT：合作研究：FITTLE：智能手机生态瞬时干预理论与模型

• 批准号: 1757520
• 负责人: Peter Pirolli
• 金额: $ 16.02万
• 依托单位: Florida Institute for Human and Machine Cognition, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-18 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1757520&HistoricalAwards=false
• 关键词: SCH; INT; Collaborative; Research; FITTLE+

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.

许多健康状况是由不健康的生活方式造成的，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）在为大量人群提供长期个性化的专家日常支持方面存在瓶颈。在饮食和健身等领域，迫切需要扩大现有成功的健康行为改变方法的范围和强度。智能手机平台提供了一个极好的机会，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。智能手机还为收集丰富、精细的数据提供了绝佳的机会，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，当前的理论不具有同样的细粒度和预测性。这个跨学科项目研究理论和方法，以支持通过智能手机将细粒度的行为改变建模和干预整合到个人和群体的日常生活中。Fittle+开发了一种新的革命性的智能手机生态瞬时干预（EMI），用于改善饮食和身体活动。这种方法将提供社会支持、自主计划和个性化指导，这些指导建立在移动传感、认知辅导和基于证据的社会设计的方法之上。这种新方法的基础将需要新的健康行为改变的预测计算理论。目前关于个人健康行为改变的粗粒度概念理论将被细化为细粒度预测计算模型。这些计算模型将能够基于移动传感和交互数据实时跟踪人类环境、活动和社会模式。利用这些监控功能，Fittle+的计算模型将基于潜在的动机、认知和社会机制，支持对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教练行动，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。研究人员的合作团队与夏威夷最大的医疗机构之一的减肥干预专家一起工作。该团队包括移动传感、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方面的专业知识。