Analyzing the Impact of Practice Environment on Nurse Burnout Using Conventional and Multilevel Logistic Regression Models.

Abstract

Background: Most of the previous studies on nursing practice environment and job burnout employed conventional analyses ignoring the impact of unit-level data clusters. This study addressed this gap by examining the effects of the nursing practice environments on dimensions of occupational burnout among a sample of Chinese nurses using multilevel logistic regression models and demonstrating the superiority of employing multilevel models over conventional models within this context. Methods: A proportionate stratified sampling method was applied in this cross-sectional study that invited 1,300 registered nurses (RNs) from nine clinical units of a large, academic hospital in urban China to complete the questionnaire. Nurse-reported information was obtained using the Practice Environment Scale of the Nursing Work Index (PES-NWI) and the Maslach Burnout Inventory (MBI). Findings: A total of 1,178 valid questionnaires were returned for a response rate of 90.62%. RNs generally perceived their nursing practice environment as favorable as measured by the PES-NWI. Approximately 40% of the respondents reported experiencing emotional exhaustion and depersonalization. The multivariate models indicated that nurse burnout was significantly associated with nurse participation in hospital affairs, nursing foundations for quality of care, and adequate staffing. In addition, our results illustrated the advantage of multilevel modeling over the conventional modeling for handling hierarchical data in terms of the accuracy of the estimates and the goodness-of-fit of the model. Conclusions/Application to Practice: These findings underscore the importance of measures aimed at enhancing nursing practice environments to prevent RNs from experiencing feelings of burnout and of considering multilevel analysis in future nursing research.