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老年人睡眠质量的潜在类别及其相关预测因素:一种以个体为中心的方法。

Latent classes of sleep quality and related predictors in older adults: A person-centered approach.

机构信息

School of Psychology, Shaanxi Normal University, 199 South Chang'an Road, Xi'an 710062, China.

School of Psychology, Shaanxi Normal University, 199 South Chang'an Road, Xi'an 710062, China.

出版信息

Arch Gerontol Geriatr. 2022 Sep-Oct;102:104736. doi: 10.1016/j.archger.2022.104736. Epub 2022 May 21.

Abstract

OBJECTIVES

This research identified latent classes of sleep quality on the basis of the Pittsburgh Sleep Quality Index (PSQI) among older Chinese adults and investigated whether some influencing factors are associated with these classes.

METHODS

A total of 1047 older adults were involved in this study. Self-reported questionnaires were used to measure the levels of sleep quality, background variables (demographic factors, socioeconomic status, and life satisfaction), health status (self-rated health, depressive symptoms, and anxiety), social resources (perceived friends' support and family affective involvement), and psychological resources (sense of coherence and hope).

RESULTS

Latent class analysis revealed four latent classes, namely, poor sleep quality (17.6%), inadequate sleep (13.8%), disturbed sleep (18.2%), and good sleep quality (50.4%) in older adults. Multinomial logistic regression analyses suggested that some of the background variables, all three health-related factors, and all four personal resources predicted group membership. Specifically, age, gender, self-rated health, and hope were significant factors that could predict the membership of all classes.

CONCLUSION

This study revealed four groups of sleep quality and its related predictors in older adults. Our results provided information for tailored interventions that can promote older adults' sleep quality and prevent a worsened sleep quality unprecedented situation.

摘要

目的

本研究基于匹兹堡睡眠质量指数(PSQI)识别了老年中国成年人的睡眠质量潜在类别,并探讨了一些影响因素是否与这些类别相关。

方法

共有 1047 名老年人参与了这项研究。使用自报问卷来衡量睡眠质量、背景变量(人口统计学因素、社会经济地位和生活满意度)、健康状况(自我评估的健康状况、抑郁症状和焦虑)、社会资源(感知到的朋友支持和家庭情感投入)和心理资源(心理一致感和希望)的水平。

结果

潜在类别分析显示,老年人的睡眠质量存在四种潜在类别,即睡眠质量差(17.6%)、睡眠不足(13.8%)、睡眠紊乱(18.2%)和睡眠质量好(50.4%)。多项逻辑回归分析表明,一些背景变量、所有三个与健康相关的因素以及所有四个个人资源都可以预测群体归属。具体来说,年龄、性别、自我评估的健康状况和希望是可以预测所有类别的成员的重要因素。

结论

本研究揭示了老年人群中睡眠质量及其相关预测因素的四个组别。我们的研究结果为有针对性的干预措施提供了信息,这些干预措施可以促进老年人的睡眠质量,防止睡眠质量出现前所未有的恶化。

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