Advancing the measurement of emotional well-being with the Day Reconstruction Method

7.项目摘要/摘要 日期重建法(DRM)作为一种调查方法受到了广泛的关注 大规模人群研究中日常情绪幸福感体验的测量。数字版权管理 当情感体验在一天的过程中展开时，收集关于它们的细粒度信息。通常， 总体(“平均”)情绪水平可以作为DRM中一个人的情绪幸福感的指标。 然而，人们情感生活的许多方面并不能通过他们的平均感受来反映。建议数 应用程序寻求利用DRM中固有的丰富信息来构建措施 捕捉情绪幸福感的动态方面，包括强度、频率、变异性、调节、 以及一个人日常情感体验的复杂性。利用现有指标的丰富曲目 在实验室和动态评估研究中开发的个人内部情绪动力学，我们采用 检查这些指标是否可以成功地应用于人口水平研究的方法 通过数字版权管理。新的DRM指标的心理测量学特性将被系统地评估和 在由1000名50岁或以上的受访者组成的基于概率的互联网小组中进行比较，包括他们的 可靠性，它们与从生态瞬时评估得出的平行指数的对应关系，以及 他们对反应风格伪影的敏感性。对DRM受访者的认知访谈将揭示 完成工具的认知策略，可能促进或阻碍内容效度 新的DRM指标。评估新的DRM指标可以在多大程度上增强对 老年人的幸福感和健康差距，我们将检查新的DRM指标的能力 对人口分组(年龄、性别、教育、种族/族裔、残疾)的歧视；我们将进一步 检查哪些指标可以预测健康结果的变化。情绪健康的新指标- 从DRM派生出来可以促进大规模分析情绪健康和 功能障碍，加深对老龄化人口幸福感发展和决定因素的理解， 并增加用于评估政策决策的选项。

7. Project Summary/Abstract The Day Reconstruction Method (DRM) has found widespread attention as a survey method for the measurement of daily emotional well-being experiences in large-scale population-based research. The DRM collects granular information about affective experiences as they unfold over the course of a day. Typically, the overall (“average”) level of emotions serves as an indicator of a person’s emotional well-being from the DRM. However, many aspects of people’s emotional lives are not captured by how they feel on average. The proposed application seeks to utilize the rich information inherent in the DRM for the construction of measures capturing dynamic aspects of emotional well-being, involving the intensity, frequency, variability, regulation, and complexity of a person’s everyday emotional experiences. Drawing on a rich repertoire of existing metrics of intrapersonal emotion dynamics developed in laboratory and ambulatory assessment research, we take the approach of examining whether these metrics can be successfully applied to population-level research afforded by the DRM. The psychometric properties of the new DRM metrics will be systematically evaluated and compared in a probability-based Internet panel of 1000 respondents 50 years or older, including their reliability, their correspondence with parallel indices derived from ecological momentary assessments, and their susceptibility to response style artifacts. Cognitive interviews with DRM respondents will shed light on cognitive strategies for completing the instrument that could either facilitate or impede the content validity of the new DRM metrics. To evaluate the extent to which the new DRM metrics can augment understanding of well-being and health disparities in older ages, we will examine the ability of the new DRM metrics to discriminate between demographic subgroups (age, sex, education, race/ethnicity, disability); we will further examine which of the metrics are predictive of changes in health outcomes. New metrics of emotional well- being derived from the DRM could facilitate large-scale analyses of disparities of emotional health and dysfunction, refine understanding of the development and determinants of well-being in the aging population, and augment options for evaluating policy decisions.