The Importance of Organizational Justice on Job Burnout Among Midwestern U.S. Social Workers

ABSTRACT

The current research study examined the effects of organizational justice on burnout among U.S. social workers in the northwestern part of the U.S. state of Ohio. Specifically, the effects of perceptions of distributive and procedural justice on the burnout sub-domains of emotional exhaustion and depersonalization were explored (the third dimension of feeling ineffective at work was not measured). Low levels of distributive and/or procedural justice should lead to psychological strain for social workers, which can result in job burnout. Of the 450 distributed surveys, 255 usable ones were returned. Both distributive and procedural justice adversely affected the two burnout sub-domains of emotional exhaustion and depersonalization. Distributive justice had larger sized effects on emotional exhaustion compared to procedural justice. Distributive justice represents outcomes such as pay, benefit, and promotions, which tend to have a significant impact on social workers, who are often paid less than other professional occupations, resulting in psychological strain and emotional burnout. Both distributive and procedural justice had similar sized effects on depersonalization burnout. The current results underscore the need for organizational interventions by improving perceptions of distributive and procedural justice in order to reduce burnout.

KEYWORDS:

• Organizational justice
• social workers
• job burnout

Acknowledgments

The authors thank the reviewers, the Editor, and the editorial team for their comments which improved this article. The authors also thank Janet Lambert for proofreading the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For Griffin et at., (2010), the measures for the three burnout sub-domains of emotional exhaustion, depersonalization, and feeling ineffective at work were based on Wright and Saylor (1991), who used slightly reworded items and fewer items modeled after the Maslach Burnout Inventory (Maslach & Jackson, 1981). Due to space limitations of the questionnaire, we measured emotional exhaustion with five items, while the Maslach Burnout Inventory measures emotional exhaustion with nine items. We elected to use the items listed above based on face validity of measuring emotional exhaustion. The Maslach Burnout Inventory uses five items to measure depersonalization and we used five items to measure depersonalization. Feeling ineffective at work (also referred to as reduced personal accomplishment or reduced sense of accomplishment at work in the literature) is measured with eight items in the Maslach Inventory. As noted earlier, the current study did not include a measure for feeling in effective. This is noted as a limitation of the current study in the Discussion section.:

2 A correlation matrix of the study variables is available upon request.

3 The control variable age had a significant negative association in the multivariate analysis for emotional exhaustion and depersonalization, which means older social worker participants reported lower levels of emotional exhaustion and lower levels of depersonalization of coworkers and clients. In addition, race/ethnicity had a significant association with depersonalization, where Caucasian participants reported higher levels of this dimension of burnout. As the focus of the current study was the association of distributive and procedural justice with emotional exhaustion and depersonalization burnout, and the personal characteristics were included as control variables, the results of these two personal characteristics are not discussed in this article.

4 Even though the two dependent variables of emotional exhaustion and depersonalization were created using ordinal-level measured items, OLS regression was selected because it tends to be robust and is a common estimation method in this type of study. This least squares estimation technique is said to produce the best linear unbiased estimators (BLUE), and OLS regression also produces efficient estimates (i.e., the amount of variance in the sample estimates around the population value) (Berry, 1993). While OLS regression tends to be robust, Ordered Ordinal Regression was estimated as well (not reported in tabular format). Ordered Ordinal regression models can be used for ordered ordinal-level limited dependent variables (Long, 1997). The Ordered Ordinal regression results were the same in terms of the amount of variance explained and the significance of variables as found using OLS regression.