A latent profile analysis of sleep disturbance in relation to mental health among college students in China

Abstract

AimsThis 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.MethodsThe 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.ResultsThree 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.ConclusionThe 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.

Psychotic-Like Experiences and Suicidal Ideation Among Adolescents: The Chain Mediating Role of Insomnia Symptoms and Resilience

“…Data on the characteristics of the sample were collected with a questionnaire developed for the study at T1, including sex (female/male), grade (freshman/sophomore/junior/senior), age, ethnicity (Han/others), single-child status (yes/no), parental marital status (good/poor), boarding status (yes/no), parents’ education (primary school or less/junior high school/senior high school), and family income status (<3000 RMB/3000-5000 RMB/>5000 RMB). 53 …”

Study on the Profiles of Sleep Disorders, Associated Factors, and Pathways Among Gynecological Cancer Patients – A Latent Profile Analysis

“…Latent profile analysis (LPA) was a person-focused analytical technique used to identify individuals based on similar features and classify similar individuals into latent discrete populations, which was an ideal method. 31 , 32 LPA can identify different characteristics among individuals through different responses to scale entries, classify samples based on these characteristics, determine the subgroups included in the sample population, and test the relationships between variables in different populations. LPA is widely used in psychology to study the qualitative differences between individual psychology.…”

“…LPA is widely used in psychology to study the qualitative differences between individual psychology. 31 , 32 Individual psychology not only varies horizontally, but may also have structural differences, so latent profile analysis can be used to diagnose and classify psychological and behavioral problems. Previous studies on sleep disorders often used variable focus analysis techniques, which assumed a uniform distribution of patients’ psychological states.…”