A latent profile analysis of sleep disturbance in relation to mental health among college students in China - Chen, Chunping; He, Zigeng; Xu, Bingna; Shao, Jianyao; Wang, Dongfang (Frontiers in Public Health, 2023)
Aims This study aimed to examine the subtype classification characteristics of sleep disturbance (SD) in college students and their associations with sample characteristic factors and mental health outcomes. Methods The sample comprised 4,302 college students (Mean age = 19.92 ± 1.42 years, 58.6% females). The Youth Self-Rating Insomnia Scale, Beck Depression Inventory, 8-item Positive Subscale of the Community Assessment of Psychic Experiences, and 10-item Connor-Davidson Resilience Scale were used to assess adolescents’ sleep disturbance, depressive symptoms, psychotic-like experiences (PLEs), and resilience. Latent profile analysis, logistic regression, and liner regression analysis were used to analyze the data. Results Three subtypes of SD in college students were identified: the high SD profile (10.6%), the mild SD profile (37.5%), and the no SD profile (51.9%). Compared with college students in the “no SD” profile, risk factors for “high SD” include being male and poor parental marital status. Sophomores were found to predict the “high SD” profile or “mild SD” profile relative to the “no SD” profile. College students in the “mild SD” profile or “high SD” profile were more likely to have a higher level of depressive symptoms and PLEs, while a lower level of resilience. Conclusion The findings highlighted that target intervention is urgently needed for male college students, sophomores, and those with poor parental marital status in the “mild SD” profile or “high SD” profile.