We've Moved!
Visit SDSU’s new digital collections website at https://digitalcollections.sdsu.edu
Description
Burnout and work engagement have been shown to lead to important work outcomes (e.g., burnout: absenteeism, turnover; work engagement: productivity, profitability) and a large body of research has focused on characteristics of the work environment that may impact employee levels of burnout and work engagement. Specifically, researchers have demonstrated that prolonged exposure to job demands leads to burnout, and an emerging body of research suggests job resources lead to work engagement. However, there has been little attention to the role of individual differences as predictors of burnout or work engagement. Knowledge of the predictive role of individual differences would be insightful for researchers, and hiring managers could use results to select for individuals negatively disposed to burnout and positively disposed to work engagement. Therefore, I investigated whether individual differences (i.e., core self-evaluations, affective temperament, and proactive personality) predict burnout and work engagement. In addition, the indirect effect of individual differences was explored to investigate whether the way employees frame and interpret aspects of the work environment influence employees' levels of burnout and work engagement. I also investigated whether individual differences explain variance in burnout over and above perceptions of job demands (i.e., role overload, role conflict) and whether individual differences explain variance in work engagement over and above perceptions of job resources (i.e., autonomy, supervisor support). Lastly, I determined which individual differences are the most important predictors of burnout and work engagement. To address these questions, an online survey was administered to three samples of working employees using (1) Amazon's Mechanical Turk (MTurk), (2) San Diego State University's Psychology Department participant pool, and (3) a "snowball" convenience sample recruited from social media websites, such as LinkedIn. In the current study, (a) bivariate correlations, (b) tests of mediation, (c) hierarchical multiple regression analyses, and (d) dominance analysis were used to assess (a) the direct relationship between individual difference variables and burnout and work engagement, (b) the indirect effect of individual difference variables, (c) the incremental validity of individual difference variables over and above characteristics of the work environment, and (d) which individual difference variable is most predictive relative to the others. It was found all individual differences were significantly related to burnout and work engagement in the direction hypothesized. In addition, individual differences were shown to influence burnout and work engagement by shaping the way employees frame and interpret job demands and resources. Individual differences also predicted, burnout and work engagement over and above aspects of the work environment. Lastly, the results suggest the most parsimonious measure to predict burnout and work engagement is positive affectivity, as the dominance analysis indicated positive affectivity is the second-best predictor of burnout and the best predictor of work engagement. And although the current study may have some limitations, the findings suggest knowledge of individual differences deserve a greater role in research and may be useful in practice as well.