Latent profile analysis of sleep quality among newly employed nurses: a cross-sectional study

<title>Abstract</title> Background Newly employed nurses face unique challenges during role transition, making them particularly vulnerable to sleep disturbances. However, traditional assessments overlook the heterogeneity of sleep problems in this population. This study employed latent profile analysis (LPA) to identify distinct sleep quality subgroups and explore factors influencing profile membership. Methods A cross-sectional study was conducted from July to September 2024, recruiting 398 newly employed nurses from a tertiary hospital in China. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and psychological status was evaluated with the Depression Anxiety Stress Scales-21 (DASS-21). LPA was performed based on seven PSQI dimensions, followed by chi-square tests, ANOVA, and multinomial logistic regression to identify influencing factors. Results Three latent profiles were identified: healthy sleep (19.6%), suboptimal sleep (48.5%), and sleep disorder (31.9%) groups. The suboptimal sleep group was characterized by prolonged sleep latency and insufficient duration, while the sleep disorder group exhibited elevated scores across all dimensions. Regular physical activity was protective for both suboptimal (OR = 0.528, 95%CI: 0.295–0.945) and sleep disorder groups (OR = 0.432, 95%CI: 0.222–0.843). Anxiety was a risk factor for both groups (OR = 1.141–1.169). Neurotic personality (OR = 11.837, 95%CI: 1.398–100.236) and avoidant coping style (OR = 4.995, 95%CI: 1.026–24.313) were significant risk factors specifically for the sleep disorder group. Conclusion Sleep quality among newly employed nurses demonstrates significant heterogeneity, with over 80% experiencing sleep problems. Targeted interventions focusing on physical activity promotion, anxiety management, and adaptive coping strategies are recommended.