Comparative Analysis of Nurse Burnout Across Hospital Specialties

Thesis Abstract

Nurse burnout poses a critical threat to patient safety, quality of care, and workforce sustainability across hospital settings, yet comparative patterns across specialties remain inadequately understood, hindering targeted interventions. This study addresses the problem by examining differential burnout levels and their correlates among nurses in medical-surgical, critical care, and emergency departments, with the aim of informing specialty-specific workforce strategies. The specific objectives are (1) to quantify and compare the prevalence of burnout across hospital specialties using the Maslach Burnout Inventory (MBI); (2) to identify how job demands, control, social support, and organizational justice relate to burnout within each specialty; (3) to examine the moderating role of resilience and coping strategies on the relationship between work stressors and burnout; and (4) to determine the extent to which burnout mediates the relationship between workplace characteristics and intention to leave among nurses in different departments. The theoretical framework integrates the Job Demands-Resources (JD-R) model and the Conservation of Resources (COR) theory to account for how resource depletion and recovery dynamics influence burnout trajectories across specialties. Methodologically, a cross-sectional design will be employed, targeting registered nurses working in three hospital specialties (medical-surgical, critical care, and emergency) within a large urban hospital network. A stratified random sample of 600 nurses (200 per specialty) will be recruited, with inclusion criteria of at least one year of clinical experience and active patient-care duties. Data will be collected using a structured survey comprising the Maslach Burnout Inventory (MBI-HSS) to assess emotional exhaustion, depersonalization, and personal accomplishment; the Karasek Job Content Questionnaire to capture job demands and control; the Utrecht Work Engagement Scale for social support indicators; the Organizational Justice Scale; the Brief Resilience Scale; and a customized items set on coping strategies and intention to leave. Instrument validity will be established through prior psychometric testing in healthcare populations, with reliability checks (Cronbach’s alpha) targeting a minimum of 0.70 across scales. Demographic and work-related covariates (age, gender, shift pattern, tenure, supervisory status) will be collected to control for potential confounding. Data analysis will proceed in three stages. Descriptive statistics will characterize sample demographics and scale scores across specialties. Inferential analyses will compare burnout dimensions across specialties using one-way ANOVA with post hoc Tukey tests, and multivariate analysis of covariance (MANCOVA) controlling for covariates. Structural equation modeling (SEM) will test the JD-R-based hypothesized pathways, including direct effects of job demands and control on burnout, moderating effects of resilience and coping, and mediating effects of burnout on intention to leave. Multi-group SEM will assess potential variation of these pathways by specialty. Missing data will be handled via multiple imputation, and model fit will be evaluated with CFI, TLI, RMSEA, and SRMR criteria. Sensitivity analyses will compare results with and without high-exhaustion participants to explore potential floor/ceiling effects. Key expected findings include higher emotional exhaustion in emergency and critical care nurses relative to medical-surgical counterparts, with depersonalization showing a similar pattern and professional self-efficacy contributing to personal accomplishment differentially across specialties. It is anticipated that high job demands and low control will predict greater burnout, while social support and organizational justice will buffer these effects. Resilience and adaptive coping are expected to mitigate burnout susceptibility, particularly in high-intensity settings, and burnout is anticipated to mediate the relationship between workplace stressors and intention to leave, stronger in critical care and emergency departments. The study contributes to knowledge by elucidating specialty-specific burnout profiles and mechanisms, refining the JD-R model in acute care contexts, and informing targeted interventions—such as workload management, team-based support, leadership practices, and resilience-enhancement programs—tailored to the distinct stressors of medical-surgical, critical care, and emergency settings. The final recommendations will emphasize organizational changes, resource allocation, and professional development initiatives to reduce burnout prevalence, improve nurse retention, and enhance patient safety across hospital specialties.