Advancing the Science and Practice of Ecological Momentary Assessment

推进生态瞬时评价的科学性与实践性 项目摘要 本提案是根据PAR-16-260“方法和测量”项目公告提交的。 社会和行为科学”，具体目标是改善实时数据采集的测量， 经验生态瞬时评估（EMA）是一系列用于重复捕获自我报告的技术 而人们在日常生活中，并且对于评估主观状态特别有用。旨在实现 对症状、幸福感、情感、信念以及社会和物理环境进行准确和精细的测量 随着时间的推移，在自然环境中。虽然EMA方法广泛用于行为，社会和医学研究，但 是我们理解中的关键差距，必须解决EMA方法的最佳理解和应用。 本提案审查了五个问题，以提供有关EMA的必要概念信息和实用工具， 进行严格的，高质量的，可复制的EMA研究;它采用了几种新的方法来实现这些 目标.调查的主要问题包括：了解受访者如何解读和回答瞬间 通过进行实时定性访谈提出问题;确定各种EMA方案因素（例如，长度 评估，评估天数）影响受访者的选择偏差，并影响暂时的遵守情况， 以及开发有效评估特定设计影响的工具;测试新设计的模型， 使用现代心理测量学原理（项目反应理论）生成EMA测量工具，并评估 EMA计算机化自适应测试的可能性;检查EMA的核心特征-EMA报告较少 比回忆报告有偏见-通过比较两种类型的自我报告与客观标准;最后， 实验性地检查了假设会使EMA报告产生偏差的因素，其基础是， 自我监控和报告可以影响报告的性质（即，测量反应性）。

Advancing the Science and Practice of Ecological Momentary Assessment PROJECT SUMMARY This proposal is submitted in response to the program announcement PAR-16-260, “Methodology and Measurement in the Social and Behavioral Sciences,” with the specific goal of improving measurement in real-time data capture of experiences. Ecological Momentary Assessment (EMA) is a family of techniques for repeatedly capturing self-reports while people go about their everyday lives, and is particularly useful for assessing subjective states. It aims to achieve accurate and granular measurement of symptoms, well-being, affect, beliefs, and the social and physical environment over time in natural contexts. Although EMA methods are widely used in behavioral, social, and medical research, there are critical gaps in our understanding that must be resolved for EMA methods to be optimally understood and applied. This proposal examines five issues to provide necessary conceptual information about EMA and practical tools for conducting rigorous, high-quality, and replicable EMA studies; it employs several novel approaches for achieving these goals. The main issues to be investigated include: understanding how respondents interpret and answer momentary questions by conducting real-time, qualitative interviews; determining how various EMA protocol factors (e.g., length of assessment, number of days of assessments) impact selection bias of respondents and influence momentary compliance, and the development of a tool for efficiently evaluating the impact of particular designs; testing a model for a new generation of EMA measurement tools using modern psychometric principles (Item Response Theory), and evaluating the possibility of computerized adaptive tests for EMA; examining a core feature of EMA – that EMA reports are less biased than recall reports – by comparing both types of self-reports with an objective standard; and, finally, experimentally examining factors that have been hypothesized to bias EMA reporting, based on the idea that the act of self-monitoring and reporting may influence the nature of reports (i.e., measurement reactivity).