Work Fatigue Profiles: Nature, Implications, and Associations With Psychological Empowerment.

Ann-Renée Blais,Caitlin A Comeau,Simon A Houle,Nicolas Gillet,Alexandre J S Morin

doi:10.3389/fpsyg.2020.596206

Abstract

The present study examined the distinct configurations, or profiles, taken by work fatigue dimensions among samples of military (n = 1,436) and civilian (n = 2,477) employees. We also tested profile similarity across these two samples of employees. In addition, this research documented the relations between the identified work fatigue profiles, one predictor variable (psychological empowerment), and a series of attitudinal outcomes (job satisfaction, career satisfaction, and turnover intentions) among military employees. Six profiles of employees characterized by different levels of global and specific (emotional, physical, and mental) work fatigue were identified using latent profile analyses: Low Fatigue, Physically and Emotionally Depleted, Emotionally Depleted, Globally and Mentally Depleted, Globally and Emotionally Depleted, and Balanced. In both samples, employees corresponding to the Balanced profile displayed average levels of global and specific work fatigue. However, this profile slightly differed across sample, as indicated by the observation of work fatigue levels that were slightly higher among the military than among civilians. Militaries’ perceptions of psychological empowerment were significantly related to their likelihood of belonging to all profiles. In turn, militaries’ career satisfaction, job satisfaction, and turnover intentions were also found to differ as a function of profile membership.

Highlights

Work fatigue is typically defined as a reduction of one’s functional capacity due to extreme tiredness (Frone and Tidwell, 2015) and has long been recognized as a precursor of a wide variety of undesirable outcomes for the organization and the employee. Frone and Tidwell (2015) showed that employees presenting high levelsWork Fatigue Profiles of work fatigue displayed lower job satisfaction, psychological health, physical health, and organizational commitment, coupled with accrued turnover intentions and difficulties to relax after work
We focus on the role of psychological empowerment in the prediction of profile membership, and on career satisfaction, job satisfaction, and turnover intentions as outcomes of profile membership
Outcomes we examine the associations between the work fatigue profiles and attitudinal outcome variables previously shown to share variable-centered significant associations with work fatigue (Frone and Tidwell, 2015)

Summary

Introduction

Work fatigue is typically defined as a reduction of one’s functional capacity due to extreme tiredness (Frone and Tidwell, 2015) and has long been recognized as a precursor of a wide variety of undesirable outcomes for the organization (e.g., higher levels of turnover intentions; Cai et al, 2018) and the employee (e.g., lower sleep quality and quantity; Frone and Blais, 2019). Frone and Tidwell (2015) showed that employees presenting high levelsWork Fatigue Profiles of work fatigue displayed lower job satisfaction, psychological health, physical health, and organizational commitment, coupled with accrued turnover intentions and difficulties to relax after work. Despite abundant research (Frone, 2016; Barling and Frone, 2017) supporting the negative consequences associated with the various components of work fatigue (physical, mental, and emotional; Frone and Tidwell, 2015), their combined impact remains understudied. To better understand this combined impact, two complementary approaches can be used. Variablecentered analyses, designed to assess how variables (such as fatigue components) relate to other variables, are able to test for interactions among these variables (i.e., to verify if the effects of a predictor differ as a function of a moderator variable). Variable-centered analyses assume that the observed associations generalize to all members of the sample, and tests of variable-centered interactions are almost impossible to interpret meaningfully when they involve multiple predictors (i.e., more than 2 or 3) and/or nonlinearity

Methods

Results

Conclusion