EAGER: Defining a Dynamical Behavioral Model to Support a Just in Time Adaptive Intervention

EAGER：定义动态行为模型以支持及时自适应干预

• 批准号: 1449751
• 负责人: Eric Hekler
• 金额: $ 28.75万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1449751&HistoricalAwards=false
• 关键词: EAGER; Defining; Dynamical; Behavioral; Model

EAGER: Defining a Dynamical Behavioral Model to Support a Just in Time Adaptive Intervention This EAGER supports exploratory work to develop a novel approach to the creation of a dynamical computational model of human health behavior. The goal of this high risk project is to apply an experimental design that merges methods from multiple disciplines to generate the necessary data to develop a dynamical systems model of human health behavior. In theory, mobile technologies have this capacity to provide health interventions in real-time that are adapted to the individual, but in practice the specific theoretical models and decision rules required to determine exactly when, where, and how to intervene do not exist. Standard health approaches use theoretical frameworks to identify and select target behaviors and approaches or intervention. By creating dynamical models of human behavior, real-time adaptive interventions can be developed and empirically assessed building the foundational science of computational behavior. While this project is concerned with creating dynamic computational models for increasing exercise behavior, the approach may find applications more broadly with a wide range of human health issues.The goal of this EAGER project is to create a mathematical model that will provide the evdience for making decisions about when, where, and how a "just in time" adaptive mHealth physical activity intervention should be implemented. Creating this dynamical behavioral model is a challenging problem that requires insights from different disciplines because behavioral science provides insights regarding what to measure, and behavioral intervention strategies that could be used dynamically; however, current behavioral theories fail to provide any real insights on when, where, and how to intervene at the opportune moment. Control systems engineering provides a methodology for creating dynamic mathematical models and decision-making, but this methodology has only sparsely been applied in a human behavioral context. A key first step for developing a dynamical behavioral model is to gather "informative" empirical data to estimate the model. These data will be generated with an informative system identification "informative" experiment within a human context that builds on lessons from behavioral science about experimental designs and that takes full advantage of the temporally rich data available from mHealth technologies. We will use these data to develop a fundamental yet empirically- supported dynamical behavioral model for understanding our target behavior.

EAGER：定义动态行为模型以支持及时的适应性干预这项EAGER支持探索性工作，以开发一种新的方法来创建人类健康行为的动态计算模型。这一高风险项目的目标是采用一种实验设计，该设计融合了来自多个学科的方法，以产生必要的数据，以开发人类健康行为的动态系统模型。理论上，移动技术有能力提供适合个人的实时卫生干预措施，但在实践中，不存在确定干预的确切时间、地点和方式所需的具体理论模型和决策规则。标准健康方法使用理论框架来识别和选择目标行为和方法或干预措施。通过创建人类行为的动态模型，可以开发和经验评估实时自适应干预措施，建立计算行为的基础科学。虽然这个项目关注的是为增加锻炼行为创建动态计算模型，但这种方法可能会在更广泛的人类健康问题上得到更广泛的应用。这个EAGER项目的目标是创建一个数学模型，该模型将为决定何时、何地以及如何实施“及时”适应性移动健康身体活动干预提供证据。创建这种动态行为模型是一个具有挑战性的问题，需要来自不同学科的见解，因为行为科学提供了关于测量什么的见解，以及可以动态使用的行为干预策略；然而，目前的行为理论未能提供任何关于何时、何地以及如何在适当时机进行干预的真正见解。控制系统工程为创建动态数学模型和决策提供了一种方法，但这种方法仅在人类行为环境中很少应用。开发动态行为模型的关键第一步是收集“信息丰富”的经验数据来估计模型。这些数据将通过在人类背景下进行的信息系统识别“信息”实验生成，该实验建立在有关实验设计的行为科学经验的基础上，并充分利用移动健康技术提供的临时丰富数据。我们将使用这些数据来开发一个基本的但经验支持的动态行为模型来理解我们的目标行为。