Unveiling the psychological network of work alienation among nursing interns: A resource conservation perspective and...

Clinical internship is critical for nursing students, but heavy workload and emotional demands increase the risk of work alienation. Traditional linear models fail to capture complex interrelationships among psychological factors.

To apply psychological network analysis to explore the associative structure of work alienation in nursing interns, identifying central and bridge nodes to generate hypothesis‑generating intervention priorities.

A cross-sectional survey was employed. Nursing interns from four tertiary hospitals in the Guanzhong region of Shaanxi Province were recruited via convenience sampling from January to August 2025. Data were collected using the Nurse Work Alienation Scale, Compassion Fatigue Scale, Moral Distress Scale, Ethical Sensitivity Questionnaire for Nursing Students, and NASA Task Load Index. A total of 934 valid responses were obtained. A regularized partial correlation network model was estimated using the EBICglasso method (γ = 0.5). Node strength and bridge strength were calculated, and stability was assessed via bootstrap.

Node strength analysis identified personal responsibility (1.19), burnout (1.18), and failure to maintain patient's best interest (1.13) as the three most central nodes. Bridge strength analysis revealed secondary traumatic stress (STS) as the strongest bridge (0.43, 95% CI [0.31, 0.55]), followed by perceived workload (0.38) and self‑evaluation (0.38). Subgroup network comparisons showed no significant structural differences by gender, age, or education (all p > 0.05). Stability analysis confirmed good robustness for centrality estimates.

Psychological network analysis mapped the associative structure of work alienation, identifying personal responsibility, burnout, and STS as key hub and bridge nodes. These findings offer hypothesis‑generating targets for future interventions (e.g., trauma‑informed care, workload management, self‑efficacy enhancement), pending validation in longitudinal studies.