Mengelkoch Summer, Moriarity Daniel P, Novak Anne Marie, Snyder Michael P, Slavich George M, Lev-Ari Shahar
Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA 90095, USA.
Department of Health Promotion, School of Medicine, Tel-Aviv University, Tel-Aviv 6997801, Israel.
J Clin Med. 2023 Dec 19;13(1):24. doi: 10.3390/jcm13010024.
Despite great interest in how dynamic fluctuations in psychological states such as mood, social safety, energy, present-focused attention, and burnout impact stress, well-being, and health, most studies examining these constructs use retrospective assessments with relatively long time-lags. Here, we discuss how ecological momentary assessments (EMAs) address methodological issues associated with retrospective reports to help reveal dynamic associations between psychological states at small timescales that are often missed in stress and health research. In addition to helping researchers characterize daily and within-day fluctuations and temporal dynamics between different health-relevant processes, EMAs can elucidate mechanisms through which interventions reduce stress and enhance well-being. EMAs can also be used to identify changes that precede critical health events, which can in turn be used to deliver ecological momentary interventions, or just-in-time interventions, to help prevent such events from occurring. To enable this work, we provide examples of scales and single-item questions used in EMA studies, recommend study designs and statistical approaches that capitalize on EMA data, and discuss limitations of EMA methods. In doing so, we aim to demonstrate how, when used carefully, EMA methods are well poised to greatly advance our understanding of how intrapersonal dynamics affect stress levels, well-being, and human health.
尽管人们对情绪、社会安全感、能量、当下注意力和倦怠等心理状态的动态波动如何影响压力、幸福感和健康非常感兴趣，但大多数研究这些构念的研究都采用了具有相对较长时间滞后的回顾性评估。在这里，我们讨论生态瞬时评估（EMA）如何解决与回顾性报告相关的方法学问题，以帮助揭示压力和健康研究中经常被忽视的小时间尺度上心理状态之间的动态关联。除了帮助研究人员描述日常和日内波动以及不同健康相关过程之间的时间动态外，EMA还可以阐明干预措施减轻压力和增强幸福感的机制。EMA还可用于识别关键健康事件之前的变化，这些变化反过来可用于提供生态瞬时干预或即时干预，以帮助预防此类事件的发生。为了推动这项工作，我们提供了EMA研究中使用的量表和单项问题的示例，推荐了利用EMA数据的研究设计和统计方法，并讨论了EMA方法的局限性。通过这样做，我们旨在展示如何在谨慎使用时，EMA方法能够极大地推进我们对人际动态如何影响压力水平、幸福感和人类健康的理解。
