TH-P01-006-interactive - Are intelligent employees less exhausted? The mediating role of job resources

Burnout and fatigue
Interactive Poster Presentation
1 hour 30 minutes
O'Brien Foyer
Employee stress and burnout
Burnout and fatigue
Are intelligent employees less exhausted? The mediating role of job resources
K. Kulikowski*
Cognitive capacities are one of the best predictors of job performance, however, still little is known of their relationships with employee well-being. To fill this gap, based on the Job Demands-Resources theory (JD-R), we propose that cognitive capacities: working memory capacity (WMC) and fluid intelligence (Gf) might positively predict job resources and job resources in turn might negatively predict exhaustion. WMC as reflecting information storage and processing ability and Gf as reasoning and problem solving in face of an uncertainty might help employees to shape work environment into more resourceful place, job resources in turn, according to JD-R, might reduce level of exhaustion.
Multi-occupational sample of 167 employees completed a set of two WMC and three Gf computerized tests along with three job resources surveys and The Oldenburg Burnout Inventory.
Structural equation modelling with latent variable and bootstrapping procedure revealed that, as predicted by JD-R, job resources negatively predict exhaustion. Surprisingly, Gf indirectly increased exhaustion through decrease in job resources, whereas WMC indirectly decreased exhaustion through increase in job resources.
As cross sectional study our findings need to be replicate in further longitudinal study.
Research Implications
Our results suggest that WMC and Gf are significant predictors of exhaustion and could not be further ignored in models of employee well-being, like JD-R.
 For the first time, we propose and empirically tested the possible role of WMC and Gf for predicting exhaustion via job resources.  We have shown that two closely related cognitive capacities predict exhaustion in different ways.

Jagiellonian University in Kraków
PhD Candidate

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