Frontiers in Psychology (May 2020)

The Moderating Role of Regulatory Institutional Environment in the Relationship Between Emotional Job Demands and Employee Absenteeism Likelihood of Healthcare Workers. Evidence From the Low-Income Country Context

  • Benson Munyenyembe,
  • Ying-Yu Chen,
  • Wen-Chiung Chou

DOI
https://doi.org/10.3389/fpsyg.2020.01052
Journal volume & issue
Vol. 11

Abstract

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Previous research has not clearly studied how the effects of emotional job demands on absenteeism likelihood are moderated by the contingent absenteeism-related regulatory institutional environments of low-income countries. In this regard, we surveyed 487 healthcare workers in a low-income country in order to test for the effect of emotional job demands on healthcare workers’ absenteeism likelihood. We also explored the mediating role of work engagement and the contingent role of context-specific regulatory institutional environments on the link between emotional job demands and absenteeism likelihood. The main findings of this study are as follows: (1) emotional job demands have a direct positive effect on healthcare workers’ absenteeism likelihood, (2) work engagement plays a mediating role on the link between emotional job demands and healthcare workers’ absenteeism likelihood, and (3) the regulatory institutional environment related to absenteeism moderates the negative link between work engagement and absenteeism likelihood. Results in this study demonstrate the crucial role that the context-specific regulatory institutional environment related to absenteeism plays in suppressing the effect of emotional job demands on absenteeism likelihood when considered through the work-engagement pathway. The study’s findings clarify the mechanism through which emotional job demands affect absenteeism likelihood in a low-income country context. The study thus offers a new refined theoretical perspective on how emotional job demands, work engagement, and context-specific regulatory institutional environments interact in ways that predict absenteeism likelihood.

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