Sleep and affect: A conceptual review.
Sleep and affect: A conceptual review.
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DOI：
10.1016/j.smrv.2022.101670
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发表时间：
2022-10
影响因子：
10.5
通讯作者：
Manber, Rachel
中科院分区：
文献类型：
--
作者：
ten Brink, Maia;Dietch, Jessica R.;Tutek, Joshua;Suh, Sooyeon A.;Gross, James J.;Manber, Rachel
日常经验表明，睡眠与情绪密切相关，日间情绪会影响我们的睡眠状况，而睡眠又会影响后续的情绪。然而，针对非临床成年样本中睡眠与情绪这种双向关系的实证证据却并不统一，这可能是由于概念定义和测量方式的多样性所致。这篇概念综述提出了一个细化框架，该框架依据三个子维度对睡眠与情绪的研究结果进行解构，即领域（睡眠和情绪各有不同领域）、方法（即自我报告法与行为/生理测量法）以及时间尺度（即较短与较长时间尺度）。我们通过对PubMed上发表的实证研究（共80篇文章）进行系统回顾，阐释了这一细化框架的价值。我们发现，在某些情况下，尤其是睡眠障碍和睡眠时间方面，我们的框架识别出了睡眠与情绪之间存在关联的有力证据，且这些证据可按领域、方法和时间尺度加以区分。然而，在大多数其他情况下，证据要么尚无定论，要么过于稀少，因而未呈现出清晰的模式。我们的综述未发现睡眠与情绪之间存在细化双向关系的依据。基于综述所发现的空白，我们提出了未来研究的路线图，并探讨了这一细化维度框架的优缺点。
Everyday experience suggests that sleep and affect are closely linked, with daytime affect influencing how we sleep, and sleep influencing subsequent affect. Yet empirical evidence for this bidirectional relationship between sleep and affect in non-clinical adult samples remains mixed, which may be due to heterogeneity in both construct definitions and measurement. This conceptual review proposes a granular framework that deconstructs sleep and affect findings according to three subordinate dimensions, namely domains (which are distinct for sleep and affect), methods (i.e., self-report vs. behavioral/physiological measures), and timescale (i.e., shorter vs. longer). We illustrate the value of our granular framework through a systematic review of empirical studies published in PubMed (N = 80 articles). We found that in some cases, particularly for sleep disturbances and sleep duration, our framework identified robust evidence for associations with affect that are separable by domain, method, and timescale. However, in most other cases, evidence was either inconclusive or too sparse, resulting in no clear patterns. Our review did not find support for granular bidirectionality between sleep and affect. We suggest a roadmap for future studies based on gaps identified by our review and discuss advantages and disadvantages of our granular dimensional framework.
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