Job-related burnout is a significant concern for researchers, law enforcement administrators, and government authorities because of its broader effects on officer health, job performance, and service provided to the public. This topic is particularly relevant amidst a variety of complex challenges and heightened scrutiny surrounding law enforcement officers, their decisions, and relations with the public. The current analysis indicates that approximately 19 percent of the total sample were experiencing severe levels of emotional exhaustion and 13 percent had extreme values of depersonalization. In addition, regression analyses suggest that specific measures of workload and values were the strongest predictors of emotional exhaustion, while depersonalization was driven by similar factors in addition to a measure of community that tapped into relations with the public. Furthermore, little empirical support was found for the importance of agency and community-level variables as predictors of either component of burnout. A discussion of how to translate those results into efforts to mitigate burnout is presented. (publisher abstract modified)
Burnout in Blue: An Analysis of the Extent and Primary Predictors of Burnout Among Law Enforcement Officers in the United States
NCJ Number
253943
Journal
Police Quarterly Volume: 22 Issue: 3 Dated: 2019 Pages: 278-304
Date Published
2019
Length
26 pages
Annotation
Although much work has been conducted on burnout among police officers, the aim of this study was to build on the literature by analyzing survey data from approximately 13,000 sworn respondents representing 89 agencies throughout the United States, so as to describe the extent of two components of burnoutemotional exhaustion and depersonalization; then, based on Leiter and Maslach's (2004) six areas of work life, this study used multivariate analysis to identify the primary predictors of those two components of burnout and how they are shaped by the characteristics of the agencies and communities in which these officers work.
Abstract
Date Published: January 1, 2019