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.

与健康相关的行为和习惯差不良，约有40％的可预防死亡和大多数慢性病负担。但是，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学，社会和个人环境状态而进行的持续动态反馈行为循环。通过新兴技术（包括可穿戴和可部署的传感器以及手机），丰富的连续数据流越来越多。这些数据与主要来自工程领域发出的复杂建模技术相结合，可以提供前所未有的机会，可以实时理解行为。但是，为了利用这些机会，需要行为/健康科学家与数据建模者以及各个复杂数据建模技术之间的专门合作。拟议的研讨会着重于开发新的概念，以建模新兴技术越来越多地提供了时间密集，上下文丰富和个性化的数据。该提议的研讨会的主要目标是1）跨不同计算建模方法的子学科的融合技术，2）促进共享词汇/本体论的发展，以促进建模者，行为和健康科学家之间的交流，3）动态行为理论朝着因果关系和预测动态模型的一个新层面。对21世纪数据建模和健康行为研究的挑战是朝着行为的计算，动态建模迈进，可以捕捉行为状态的复杂而快速变化的行为状态和相关影响因素。这些新模型将为及时的自适应干预措施（Jitai）铺平道路，这些干预措施（Jitai）在上下文中，当时人们最容易受益，最有可能受益。为此，这里提出的研讨会将汇集各种类型的建模的专家，例如（但不限）到系统动态，社交网络，基于代理的建模，机器学习和贝叶斯推断，以与行为科学家和行为科学家和医疗保健专业人员将这项努力转移到新的水平。拟议的研讨会将遵循有关开发和评估数字健康干预方法的国际研讨会，该研讨会将于2015年9月10日至11日在伦敦英国举行，由苏珊·米歇尔（Susan Michie）博士和杰里米·怀亚特（Jeremy Wyatt）博士领导，由医学研究委员会赞助。 （MRC），英国。这里提出的研讨会将健康行为和移动干预方面的国际领导者与大数据建模的领导者一起。该研讨会将促进不同的“大数据”建模者和行为主义者之间的前所未有的合作，以开发新的范式来建模时间密集的，上下文化的行为数据，这些数据可以指导跨健康和健康领域的未来Jitias。