The Interaction Between Leadership, the Patient-to-Nurse Ratio and Nurses’ Work-Life Balance in the Psychiatric Inpatient Setting in Switzerland: A Secondary Data Analysis of Cross-Sectional Data

Abstract

Psychiatric nurses’ work environment factors, including long hours, heavy workloads and leadership issues, can serve as barriers to achieving a healthy work-life balance. However, for both individuals and organizations, that balance is crucial as it is a key determinant of job satisfaction and leaving intentions. To address the limiting evidence to that topic, this study had two objectives: (1) to describe the work-life balance of nurses working in psychiatric inpatient settings; and (2) to examine those nurses’ work-life balance and its associations with individual (i.e., age, gender), psychosocial (i.e., leadership) and structural factors (i.e., employment percentage). To analyze these factors and their impacts, we conducted a cross-sectional study in a sample of 1209 nurses from 116 units in 13 psychiatric hospitals of the German-speaking part of Switzerland and analyzed the resulting data via multilevel analysis. This led to three main results. First, nurses reported a high mean value regarding their work-life balance. Second, multivariable regression results indicated that their work-life balance ratings correlated directly with certain psychosocial work environment factors (leadership and support of nurses, perceived staffing resources) and inversely with structural factors (employment percentage, overtime). And third, we found an interaction between leadership and support of nurses and the patient-to-nurse ratio: the lower the leadership level, the stronger the inverse association between patient load and work-life balance. No individual factors were significantly associated with work-life balance. Overall, though, we found that organizational factors are vital to nurses’ work-life balance. Therefore, interventions to improve nurses’ work-life balance should be institution-level, and should focus on improving either leadership or structural factors, e.g., employment percentage, overtime, and patient-to-nurse ratios.