Network Analysis of Sleep Quality and Psychiatric Symptoms Among ICU Nursing Staff

Intensive care unit (ICU) nurses are at high risk for sleep problems and psychological symptoms. This study aimed to construct a network model to explore the interrelationships between sleep quality and psychiatric symptoms among ICU nurses and to identify central and bridge symptoms for precise intervention.

A multicenter cross-sectional study was conducted from January to March 2025 among registered nurses working in ICUs. Psychiatric symptoms were assessed using the Symptom Checklist-90 (SCL-90), and sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). A Gaussian Graphical Model was estimated using the EBICglasso algorithm. Centrality indices (strength, closeness, betweenness, and expected influence) and bridge centrality were calculated to identify key symptoms. The stability of the network was assessed using nonparametric and case-dropping bootstrap analyses.

A total of 5560 nurses were included in the analysis. The network model revealed a well-connected structure. Centrality analysis indicated that "subjective sleep quality", "anxiety", and "sleep and eating problems" were the most central symptoms in the entire network. Bridge centrality analysis identified "sleep and eating problems" as the most critical bridge symptoms, forming the strongest connections between the sleep and psychiatric symptom communities. The network demonstrated excellent stability, with a correlation stability coefficient of 0.75 for both strength and bridge strength.

The findings highlight the pivotal roles of subjective sleep quality, sleep and eating problems, and anxiety as potential targets for precise interventions. Focusing on these symptoms may effectively disrupt the vicious cycle between poor sleep and psychological distress, thereby improving overall well-being.