Volume 46, Issue 4 p. 292-301
HEALTH POLICY AND SYSTEMS

Job-Related Stress and Sickness Absence Among Belgian Nurses: A Prospective Study

Jeroen Trybou PhD

Corresponding Author

Jeroen Trybou PhD

Post-doctoral research fellow, Department of Public Health, Ghent University, Belgium

Correspondence

Jeroen Trybou, De Pintelaan 185, 9000 Ghent, Belgium. E-mail: [email protected]

Search for more papers by this author
Sofie Germonpre MSc

Sofie Germonpre MSc

Lecturer, Department of Healthcare, HU Brussel, Brussels, Belgium

Search for more papers by this author
Heidi Janssens MSc

Heidi Janssens MSc

Doctoral researcher, Department of Public Health, Ghent University, Ghent, Belgium

Search for more papers by this author
Annalisa Casini PhD

Annalisa Casini PhD

Post-doctoral researcher, Department of Epidemiology and Health Promotion, School of Public Health, Free University of Brussels, Brussels, Belgium

Search for more papers by this author
Lutgart Braeckman PhD

Lutgart Braeckman PhD

Professor, Department of Public Health, Ghent University, Ghent, Belgium

Search for more papers by this author
Dirk De Bacquer PhD

Dirk De Bacquer PhD

Professor, Department of Public Health, Ghent University, Ghent, Belgium

Search for more papers by this author
Els Clays PhD

Els Clays PhD

Assistant professor, Department of Public Health, Ghent University, Ghent, Belgium

Search for more papers by this author
First published: 22 April 2014
Citations: 39

Abstract

Purpose

The purpose of this study was to investigate the influence of job stress on sickness absence of nurses and determine the predictive power of the Demand-Control-Support (DCS) model, the Effort-Reward Imbalance-Overcommitment (ERI-OC) model, and a combination of both.

Design

A survey was conducted to measure job stress in a sample of 527 Belgian nurses, followed by prospective data collection of sickness absence (long-term, short-term, and multiple episodes).

Findings

Perceptions of job strain and ERI increased the odds for long-term (adjusted odds ratio [OR] = 2.26; 99% confidence interval [CI; 1.27–4.04]) and multiple episodes of sickness absence (adjusted OR = 1.64; 95% CI [1.01–2.65]). Iso-strain and ERI-OC increased the odds for long-term (OR = 1.75; 95% CI [0.98–3.11]), multiple episode (adjusted OR = 1.93; 95% CI [1.14–3.26]), and short-term (adjusted OR = 1.69; 95% CI [1.03–2.76]) sickness absence.

Conclusions

The combined model of DCS and ERI-OC predicts the odds for long-term and short-term sickness absence and multiple episodes.

Clinical Relevance

This study has implications for human resources management in nursing organizations. Nursing administrators are advised to monitor and balance nurses’ job demands and efforts. They should recognize the importance of social support, job control, job rewards, and overcommitment in order to reduce the job stress of nurses.