International Workshop on Dynamic Modeling of Health Behavior Change and Maintenance: Moving the Field Forward

健康行为改变和维持动态建模国际研讨会：推动该领域向前发展

• 批准号: 1539846
• 负责人: Donna Spruijt-Metz
• 金额: $ 2.5万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1539846&HistoricalAwards=false
• 关键词: International; Workshop; Dynamic; Modeling; Health

Poor health-related behaviors and habits are responsible for approximately 40% of preventable deaths and the majority of the chronic disease burden. However, our current understanding of health-related behavior is largely based on static snapshots of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social and personal environmental states. Rich streams of continuous data are becoming increasingly available through emerging technologies, including wearable and deployable sensors and mobile phones. This data, combined with sophisticated modeling techniques emanating primarily from engineering fields, can provide unprecedented opportunities to understand behavior in context and in real time. However, to take advantage of these opportunities, dedicated collaborations between behavioral/health scientists and data modelers, as well as across different schools of complex data modeling techniques, are required. The proposed workshop focuses on developing new concepts for modeling the temporally dense, contextually rich and personalized data increasingly afforded by emerging technologies. The major goals of this proposed workshop are to 1) amalgamate techniques from sub-disciplines across different computational modeling approaches, 2) facilitate development of a shared vocabulary/ontology to facilitate communication between modelers, behavioral and health scientists and 3) advance the rigor of dynamic behavioral theories to the next level towards causal and predictive dynamic models.The challenge to 21st century data modeling and health behavior research is to move toward computational, dynamic modeling of behavior that can capture complex and rapid changes in behavioral state and related influencing factors. These new models will pave the way for Just-In-Time, Adaptive Interventions (JITAI) that provide feedback in context, in the moment, when people are most receptive and most likely to benefit. To accomplish this, the workshop proposed here will bring together experts in various types of modeling, for example (but not limited) to systems dynamics, social networks, agent-based modeling, machine learning, and Bayesian inference to work together with behavioral scientists and health care professionals to move this endeavor to the next level. The proposed workshop will follow the International Workshop on Methodologies for Developing and Evaluating Digital Health Interventions, which will be held in London UK, 10-11 September 2015, led by Dr. Susan Michie and Dr. Jeremy Wyatt, sponsored by the Medical Research Council (MRC), UK. The workshop proposed here brings the international leaders in health behavior and mobile interventions together with leaders in big data modeling. This workshop will facilitate an unprecedented collaboration between different streams of "big data" modelers and behaviorists to develop new paradigms for modeling temporally dense, contextualized behavioral data that can guide future JITIAs across health and wellness domains.

与健康相关的不良行为和习惯造成了约40%的可预防死亡和大部分慢性病负担。然而，我们目前对健康相关行为的理解主要基于人类行为的静态快照，而不是响应不断变化的生物，社会和个人环境状态的行为的持续，动态反馈回路。通过新兴技术，包括可穿戴和可部署的传感器以及移动的电话，丰富的连续数据流变得越来越可用。这些数据与主要来自工程领域的复杂建模技术相结合，可以提供前所未有的机会来理解上下文和真实的时间行为。然而，为了利用这些机会，行为/健康科学家和数据建模师之间以及不同的复杂数据建模技术学校之间需要专门的合作。拟议的研讨会侧重于开发新的概念，用于对新兴技术日益提供的时间密集、上下文丰富和个性化的数据进行建模。这个拟议的研讨会的主要目标是：1）融合来自不同计算建模方法的子学科的技术，2）促进共享词汇表/本体的开发，以促进建模者之间的交流，行为和健康科学家; 3）将动态行为理论的严谨性推进到因果和预测动态模型的下一个水平。21世纪世纪数据建模和健康行为研究正朝着计算的、动态的行为建模方向发展，以捕捉行为状态和相关影响因素的复杂和快速变化。这些新模型将为即时适应性干预（JITAI）铺平道路，在人们最容易接受和最有可能受益的时刻提供反馈。为了实现这一目标，这里提出的研讨会将汇集各种类型的建模专家，例如（但不限于）系统动力学，社交网络，基于代理的建模，机器学习和贝叶斯推理，与行为科学家和医疗保健专业人员一起工作，将这一奋进提升到一个新的水平。拟议的研讨会将遵循数字健康干预措施开发和评估方法国际研讨会，该研讨会将于2015年9月10日至11日在英国伦敦举行，由Susan米吉博士和Jeremy Wyatt博士领导，由英国医学研究理事会（MRC）赞助。这里提议的研讨会将健康行为和移动的干预领域的国际领导者与大数据建模领域的领导者聚集在一起。本次研讨会将促进不同的“大数据”建模者和行为学家之间前所未有的合作，为建模时间密集，情境化的行为数据开发新的范式，这些数据可以指导未来的JITIA跨健康和健康领域。