Network Structure of Sleep Quality and Emotional State Among ICU Nurses: A Cross-Sectional Analysis

The high-stress ICU environment impairs nurses' sleep and emotional health, creating a bidirectional cycle that adversely affects both well-being and patient safety-a dynamic not fully examined in traditional research.

To identify core and bridge symptoms within the interconnected network of sleep disturbances and emotional dysregulation among ICU nurses.

A multicentre cross-sectional study was conducted from February to March 2025, involving ICU nurses from 18 tertiary hospitals in Jiangsu, Zhejiang and Shanghai. The survey utilised the Profile of Mood States-Short Form (POMS-SF) and the Pittsburgh Sleep Quality Index (PSQI) to assess the mood states and sleep quality of the participating ICU nurses. Network analysis was conducted using R version 4.3.3, with centrality measures employed to pinpoint the key symptoms within the network.

In total, 498 ICU nurses participated. The symptom network revealed POMS1 (Tension-Anxiety) and PSQI1 (Subjective Sleep Quality) as central nodes (EI = 1.231 and 0.956, respectively). Key bridge symptoms included POMS3 (Fatigue-Inertia) (BEI = 0.161) and PSQI5 (Sleep Disturbance) (BEI = 0.095). The strongest edge linked POMS5 (Vigour-Activity) and POMS7 (Esteem-Related Affect) (partial correlation = 0.761). Network predictability was highest for POMS4 (Depression-Dejection).

This study reveals a bidirectional network linking sleep and emotional symptoms in ICU nurses, identifying anxiety and subjective sleep quality as central nodes, with fatigue and sleep disturbances as key bridges. These findings call for integrated, precision interventions that target both core and bridge symptoms.

The results prioritise targeting anxiety and sleep quality through cognitive interventions and sleep monitoring, while disrupting the fatigue-sleep bridge via circadian-aligned scheduling and fatigue management. This network-based approach offers a structured framework for implementing integrated support systems to enhance nurse resilience and patient safety in ICUs.