Wickwire Emerson M, Verceles Avelino C, Chen Shuo, Zhao Zhiwei, Rogers Valerie E, Wilckens Kristine A, Buysse Daniel J
Sleep Disorders Center, Division of Pulmonary and Critical Care Medicine, Department of Medicine (EMW, ACV), University of Maryland, Baltimore, MD; Department of Psychiatry (EMW, SC), University of Maryland, Baltimore, MD.
Sleep Disorders Center, Division of Pulmonary and Critical Care Medicine, Department of Medicine (EMW, ACV), University of Maryland, Baltimore, MD.
Am J Geriatr Psychiatry. 2023 May;31(5):372-378. doi: 10.1016/j.jagp.2023.01.020. Epub 2023 Feb 1.
To employ smart phone/ecological momentary assessment (EMA) methods to evaluate the impact of insomnia on daytime symptoms among older adults.
Prospective cohort study SETTING: Academic medical center PARTICIPANTS: Twenty-nine older adults with insomnia (M age = 67.5 ± 6.6 years, 69% women) and 34 healthy sleepers (M age = 70.4 ± 5.6 years, 65% women).
Participants wore an actigraph, completed daily sleep diaries, and completed the Daytime Insomnia Symptoms Scale (DISS) via smart phone 4x/day for 2 weeks (i.e., 56 survey administrations across 14 days).
Relative to healthy sleepers, older adults with insomnia demonstrated more severe insomnia symptoms in all DISS domains (alert cognition, positive mood, negative mood, and fatigue/sleepiness). A series of mixed model analyses were performed using the Benjamini-Hochberg procedure for correcting false discovery rate (BH-FDR) and an adjusted p-value <0.05. Among older adults with insomnia, all five prior-night sleep diary variables (sleep onset latency, wake after sleep onset, sleep efficiency, total sleep time, and sleep quality) were significantly associated with next-day insomnia symptoms (i.e., all four DISS domains). The median, first and third quintiles of the effect sizes (R2) of the association analyses were 0.031 (95% confidence interval (CI: [0.011,0.432]), 0.042(CI: [0.014,0.270]), 0.091 (CI:[0.014,0.324]).
Results support the utility of smart phone/EMA assessment among older adults with insomnia. Clinical trials incorporating smart phone/EMA methods, including EMA as an outcome measure, are warranted.
采用智能手机/生态瞬时评估(EMA)方法评估失眠对老年人日间症状的影响。
前瞻性队列研究
学术医疗中心
29名失眠的老年人(平均年龄 = 67.5 ± 6.6岁,69%为女性)和34名睡眠正常者(平均年龄 = 70.4 ± 5.6岁,65%为女性)。
参与者佩戴活动记录仪,每天完成睡眠日记,并通过智能手机每天4次、持续2周(即14天内进行56次调查)完成日间失眠症状量表(DISS)。
与睡眠正常者相比,失眠的老年人在DISS所有领域(警觉认知、积极情绪、消极情绪和疲劳/困倦)表现出更严重的失眠症状。使用Benjamini-Hochberg程序进行了一系列混合模型分析,以校正错误发现率(BH-FDR),调整后的p值 < 0.05。在失眠的老年人中,前一晚睡眠日记的所有五个变量(入睡潜伏期、睡眠中觉醒、睡眠效率、总睡眠时间和睡眠质量)均与次日失眠症状(即DISS所有四个领域)显著相关。关联分析效应大小(R2)的中位数、第一和第三五分位数分别为0.031(95%置信区间(CI):[0.011,0.432])、0.042(CI:[0.014,0.270])、0.091(CI:[0.014,0.324])。
结果支持智能手机/EMA评估在失眠老年人中的实用性。有必要开展纳入智能手机/EMA方法(包括将EMA作为一项结果指标)的临床试验。