Sleep profiles as a longitudinal predictor for depression magnitude and variability following the onset of COVID-19.

Sleep profiles as a longitudinal predictor for depression magnitude and variability following the onset of COVID-19.
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DOI:
10.1016/j.jpsychires.2022.01.024
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发表时间:
2022-03
影响因子:
4.8
通讯作者:
Chen S
Chen S
中科院分区:
医学2区
文献类型:
--
作者:
Bi K;Chen S

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2019冠状病毒病(COVID-19)扰乱了包括睡眠在内的多个生活领域。本研究使用纵向数据集(N = 671)和以人为中心的分析方法-潜在剖面分析(LPA) -来阐明睡眠和抑郁之间的关系。在研究开始时,我们使用LPA识别匹兹堡睡眠质量指数(PSQI)评估的睡眠模式概况。然后,这些资料被用作抑郁程度和随时间变化的预测指标。确定了三种潜在特征(药物失眠症睡眠者[MIS]、无效睡眠者[IS]和健康睡眠者[HS])。随着时间的推移,MIS的抑郁程度最高,IS次之,HS次之。抑郁症的可变性模式略有不同:虽然MIS比IS和HS表现出更大的抑郁症可变性,但IS和HS在抑郁症的可变性方面没有随时间变化的差异。药物失眠症患者的抑郁程度和可变性均高于低效率睡眠者和健康睡眠者,而后两者在抑郁变异性方面没有差异,尽管低效率睡眠者的抑郁程度高于健康睡眠者。讨论了临床意义和局限性。
The coronavirus disease 2019 (COVID-19) has disrupted multiple domains of life including sleep. The present study used a longitudinal dataset (N = 671) and a person-centered analytic approach – latent profile analysis (LPA) – to elucidate the relationship between sleep and depression. We used LPA to identify profiles of sleep patterns assessed by Pittsburg Sleep Quality Index (PSQI) at the beginning of the study. The profiles were then used as a predictor of depression magnitude and variability over time. Three latent profiles were identified (medicated insomnia sleepers [MIS], inefficient sleepers [IS], and healthy sleepers [HS]). MIS exhibited the highest level of depression magnitude over time, followed by IS, followed by HS. A slightly different pattern emerged for the variability of depression: While MIS demonstrated significantly greater depression variability than both IS and HS, IS and HS did not differ in their variability of depression over time. Medicated insomnia sleepers exhibited both the greatest depression magnitude and variability than inefficient sleepers and healthy sleepers, while the latter two showed no difference in depression variability despite inefficient sleepers’ greater depression magnitude than healthy sleepers. Clinical implications and limitations are discussed.
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