Les soins infirmiers sont une profession stressante avec un taux élevé d’absentéisme pour cause de maladie. À ce jour, il n’existe pas de méta-analyses permettant de déterminer statistiquement les corrélats d’absence pour maladie dans cette population. Cette méta-analyse a examiné les prédicteurs organisationnels et psychosociaux de l’absence de maladie chez le personnel infirmier.
Background Nursing is a stressful occupation with high rates of sickness absence. To date, there are no meta-analyses that statistically determined the correlates of sickness absence in this population. Aims This meta-analysis examined organizational and psychosocial predictors of sickness absence among nursing staff. Methods As a registered systematic review (PROSPERO: CRD42017071040), which followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, five databases (CINAHL, PROQuest Allied, PROQuest database theses, PsycINFO, PubMed) were reviewed to examine predictors of sickness absence in nurses and nursing assistants between 1990 and 2019. The Population/Intervention/Comparison/Outcome tool was used to support our searches. Effect sizes were analysed using random-effects model. Results Following critical appraisals using (i) National Institutes of Health’s Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and (ii) Strengthening the Reporting of Observational Studies in Epidemiology, 21 studies were included. Nursing assistants had greater odds of sickness absence than nurses. Working night shifts, in paediatrics or psychiatric units, experiencing poor mental health, and fatigue, also increased the odds of sickness absence. There was no evidence that job satisfaction or job strain influenced sickness absence; however, job demand increased the likelihood. Finally, work support reduced the odds of lost-time. Conclusions We synthesized three decades of research where several factors influenced sickness absence. Due to limited recent research, the results should be interpreted with caution as some practices may have changed overtime or between countries. Nevertheless, these findings could help in applying preventative strategies to mitigate lost-time in a vulnerable working population.