Shift work, sociodemographic factors, and sleep quality among nurses working in rotating and day shifts: a cross-sectional analysis

Background Nurses’ sleep quality is vital for their health and well-being, especially given their demanding, irregular schedules. This study examined associations between work schedule, shift selection, and sociodemographic factors and sleep quality among nurses in Saudi Arabia. Methods A self-reported, descriptive cross-sectional study used a two-part questionnaire comprising sociodemographic data and the Pittsburgh Sleep Quality Index (internal consistency α = .824). Chi-square tests and Cramér’s V assessed bivariate associations between demographic/workplace variables and sleep quality. Because several candidate predictors (education, experience, age) were severely collinear with the shift-exposure variables (variance inflation factors up to 14) and several subgroups showed near-deterministic relationships with the outcome, a parsimonious multivariable logistic regression adjusted for nationality and marital status, estimated using Firth’s penalized (bias-reduced) method, replaced the originally planned partial least squares structural equation modeling mediation analysis, which assumed a temporally implausible causal ordering for cross-sectional data. Results Of 140 nurses analyzed, 60 (42.9%) reported good sleep quality and 80 (57.1%) reported poor sleep quality. Good sleep quality declined with age (70.0% at 20–24 years to 24.5% at >35 years; χ² (3) = 11.85, p = .008). Work schedule, shift selection, education, experience, department, marital status, and nationality were all significantly associated with sleep quality (all p Conclusion Work schedule and shift selection were the strongest correlates of sleep quality in this sample, but these associations, including the direction of the rotating-shift and mandatory-assignment findings, are cross-sectional and adjusted, not causal, and should be interpreted alongside the severe collinearity among education, experience, age, and shift assignment. Prospective research is needed to clarify these relationships before informing scheduling policy.