Disrupted Work-Rest Patterns Linked to Turnover Intention via Depression in Nurses

Nurses in China whose work-rest patterns are more heavily disrupted report a stronger intention to leave their jobs, according to a multilevel study published in BMC Nursing. The study, led by Mengze Zhang and colleagues, applied Bayesian multilevel structural equation modeling to examine how work-rest disruption relates to two persistent occupational problems: burnout and turnover intention. Notably, the model did not show a statistically credible direct association between work-rest disruption and burnout.

Instead, depression emerged as the factor connected to both outcomes, linking disruption to burnout and turnover intention through indirect pathways. The authors frame nursing turnover and burnout as complex issues that challenge the sustainable development of healthcare systems, with consequences that extend beyond the workforce itself. These problems are associated with nurses' physical and mental health concerns as well as patient safety risks.

Against that backdrop, the study set out to identify the associations of work-rest disruption with turnover intention and burnout, and to test whether depression accounts for the connections between them. Methodologically, the analysis operated at two levels. At the individual level, the model estimated associations between work-rest disruption and each of the two outcomes, together with hypothesized indirect paths running through depression.

At the specialty level, the researchers tested whether the aggregated night-shift busyness of a nursing specialty moderated the association between individual work-rest disruption and depression, allowing the psychological impact of disrupted rest to vary by clinical context. The results supported the mediating role of depression. Work-rest disruption was positively associated with turnover intention, and the model identified indirect associations of disruption with both burnout and turnover intention through depression.

The cross-level interaction was also significant, indicating that the strength of the association between work-rest disruption and depression depended on the night-shift busyness aggregated within a nurse's specialty. In practical terms, the same amount of reported disruption carried different psychological weight depending on how busy night shifts were across the specialty group. By identifying depression as the factor linked to both burnout and turnover intention, and by showing that the specialty's night-shift context conditions the disruption-depression association, the study offers a framework for future research on retention in nursing.

The authors note that the findings may inform strategies aimed at maintaining an effective healthcare system by addressing work-rest disruption and its psychological consequences. As an observational study, however, it establishes associations rather than causal effects, and the direction of the relationships between disruption, depression, burnout, and turnover intention cannot be determined from the design.

Subject of Research: Associations of work-rest disruption with burnout and turnover intention among nurses in China, mediated by depression and moderated by specialty-level night-shift busyness.

Article Title: Linking work-rest disruption to occupational burnout and turnover intention: evidence from a multilevel study among nurses in China

Article References: Zhang, M., Zhang, J., Cao, Y., & Fu, X. (2026). Linking work-rest disruption to occupational burnout and turnover intention: evidence from a multilevel study among nurses in China. BMC Nursing. https://doi.org/10.1186/s12912-026-05565-0

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05565-0

Keywords: nurses, work-rest disruption, burnout, turnover intention, depression, night shift, multilevel analysis, Bayesian structural equation modeling, occupational health, China, BMC Nursing, healthcare workforce