College of Education, Hebei University, Baoding, China.
College of Education, Hebei University, Baoding, China.
J Affect Disord. 2023 Oct 15;339:877-886. doi: 10.1016/j.jad.2023.07.108. Epub 2023 Jul 26.
Sleep problems are highly prevalent during COVID-19 pandemic. However, only very limited studies have examined the changing patterns of insomnia symptom before and during the COVID-19 pandemic, and most of these studies were limited to two-wave designs and the variable-centered approach.
The data was taken from a large-scale health-related cohort among Chinese college students. This cohort was a five-wave design and 3834 participants who completed at least two waves were included in the present study. Growth mixture modeling (GMM) was used to estimate trajectory classes for insomnia symptoms, followed by binary logistic regression to explore the association between trajectory classes and subsequent mental health problems.
GMM analyses extracted four distinct trajectories of insomnia symptoms: stable-low pattern (n = 2897, 75.6 %), increasing pattern (n = 405, 10.6 %), decreasing pattern (n = 182, 4.7 %), and stable-high pattern (n = 350, 9.1 %). Additionally, we found that individuals in stable-high and increasing patterns were more likely to experience mental health problems after the COVID-19 pandemic even after adjusting significant covariates and outcomes at baseline.
Appreciable heterogeneity in insomnia symptoms among college students was revealed before and during the COVID-19 pandemic. About 20 % of college students were classified as high-risk patterns of insomnia symptoms. Psychological interventions should target such vulnerable groups to reduce the rates of mental health problems.
在 COVID-19 大流行期间,睡眠问题非常普遍。然而,只有非常有限的研究检查了 COVID-19 大流行前后失眠症状的变化模式,而且大多数这些研究都限于两波设计和变量中心方法。
该数据来自中国大学生大规模健康相关队列。该队列是一个五波设计,有 3834 名至少完成了两波的参与者被纳入本研究。增长混合模型(GMM)用于估计失眠症状的轨迹类别,然后使用二项逻辑回归来探讨轨迹类别与随后的心理健康问题之间的关联。
GMM 分析提取了失眠症状的四个不同轨迹:稳定低模式(n=2897,75.6%)、增加模式(n=405,10.6%)、减少模式(n=182,4.7%)和稳定高模式(n=350,9.1%)。此外,我们发现,即使在调整了重要的协变量和基线结果后,处于稳定高和增加模式的个体在 COVID-19 大流行后更有可能出现心理健康问题。
在 COVID-19 大流行前后,大学生的失眠症状表现出相当大的异质性。约 20%的大学生被归类为失眠症状的高危模式。心理干预应针对这些脆弱群体,以降低心理健康问题的发生率。