Schmickler Johanna M, Blaschke Simon, Mess Filip, Olson Nils, Reiner Barbara, Schulz Thorsten, Friedrich Julian
Associate Professorship of Didactics in Sport and Health, Department Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, Am Olympiacampus 11, 80809, Munich, Germany.
Chair of Preventive Pediatrics, Department Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.
BMC Psychol. 2025 Aug 12;13(1):907. doi: 10.1186/s40359-025-03280-0.
Poor sleep quality is a prevalent issue among university students, raising concerns for both individual well-being and public health. While the heterogeneity of sleep quality has been recognized, research examining distinct sleep quality subtypes and their influencing factors is still developing. This study aimed to explore sleep quality profiles among German university students and identify socio-demographic, health-related, and academic factors associated with profile membership.
A total of 1,526 university students from various academic disciplines participated in the study. Data were collected via an online questionnaire, including the Pittsburgh Sleep Quality Index, Perceived Stress Scale, Utrecht Work Engagement Scale for Students, and questions on socio-demographic, health-related, and academic factors. Latent profile analysis and multinomial logistic regression were used to analyze the data.
We identified four distinct sleep quality profiles among our participants: the Average Sleep Profile (78.5%), the Insomnia Risk Profile (8.2%), the Above Average Profile (7.2%), and the Medicated Sleepiness Profile (6.1%). Prolonged sleep onset latency and daytime sleepiness were common across most profiles, indicating that these are widespread sleep-related issues among students. Female students (OR = 2.75, p < 0.001) and those with higher stress levels (OR = 1.09, p < 0.001) were more likely to belong to the Insomnia Risk Profile. Older students (aged 23 years or above) (OR = 1.88, p = 0.030), those enrolled in State examination programs (OR = 5.73, p = 0.016) as well as students experiencing higher stress (OR = 1.08, p < 0.001) and academic workload (OR = 1.01, p = 0.022), had an increased likelihood of belonging to the Medicated Sleepiness Profile. Students reporting better subjective health status were less likely to be assigned to profiles characterized by maladaptive sleep patterns.
These findings underscore the variability in sleep quality among university students, offering insights for the development of tailored preventive interventions. Future sleep promotion programs should consider individual differences when designing strategies to address the diverse sleep challenges faced by students.
睡眠质量差是大学生中普遍存在的问题，引起了对个人幸福和公众健康的关注。虽然人们已经认识到睡眠质量的异质性，但研究不同睡眠质量亚型及其影响因素的工作仍在不断发展。本研究旨在探讨德国大学生的睡眠质量概况，并确定与概况归属相关的社会人口学、健康相关和学业因素。
共有1526名来自不同学科的大学生参与了本研究。通过在线问卷收集数据，包括匹兹堡睡眠质量指数、感知压力量表、乌得勒支学生工作投入量表，以及关于社会人口学、健康相关和学业因素的问题。采用潜在概况分析和多项逻辑回归对数据进行分析。
我们在参与者中确定了四种不同的睡眠质量概况：平均睡眠概况（78.5%）、失眠风险概况（8.2%）、高于平均水平概况（7.2%）和药物性嗜睡概况（6.1%）。大多数概况中普遍存在入睡潜伏期延长和日间嗜睡的情况，这表明这些是学生中普遍存在的与睡眠相关的问题。女学生（比值比=2.75，p<0.001）和压力水平较高者（比值比=1.09，p<0.001）更有可能属于失眠风险概况。年龄较大的学生（23岁及以上）（比值比=1.88，p=0.030）、参加国家考试项目的学生（比值比=5.73，p=0.016）以及压力较大（比值比=1.08，p<0.001）和学业负担较重（比值比=1.01，p=0.022）的学生，属于药物性嗜睡概况的可能性增加。报告主观健康状况较好的学生被分配到以适应不良睡眠模式为特征的概况的可能性较小。
这些发现强调了大学生睡眠质量的变异性，为制定针对性的预防干预措施提供了见解。未来的睡眠促进计划在设计应对学生面临的各种睡眠挑战的策略时应考虑个体差异。
