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KMID : 1141220210120040536
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Safety and Health at Work
2021 Volume.12 No. 4 p.536 ~ p.543
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Demographic, Lifestyle, and Physical Health Predictors of Sickness Absenteeism in Nursing: A Meta-Analysis
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Gohar Basem
Lariviere Michel
Lightfoot Nancy
Lariviere Celine
Wenghofer Elizabeth
Nowrouzi-Kia Behdin
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Abstract
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Background: Sickness absenteeism is an area of concern in nursing and is more concerning given the recent impacts of the COVID-19 pandemic on healthcare. This study is one of two meta-analyses that examined sickness absenteeism in nursing. In this study, we examined demographic, lifestyle, and physical health predictors.
Methods: We reviewed five databases (CINAHL, ProQuest Allied, ProQuest database theses, PsycINFO, and PubMed) for our search. We registered the systematic review (CRD de-identified) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Additionally, we used the Population/Intervention/Comparison/Outcome Tool to improve our searches.
Results: Following quality testing, 17 articles were used for quantitative synthesis. Female employees were at higher risks of sickness absenteeism than their male counterparts (OR = 1.73; 95% CI: 1.33?2.25). Nursing staff who rated their health as poor had a greater likelihood of experiencing sickness absence (OR = 1.38; 95% CI: 1.19-1.60). Also, previous sick leave predicted future leaves (OR = 3.35; 95% CI: 1.37?8.19). Moreover, experiencing musculoskeletal pain (OR = 2.41 95% CI: 1.77?3.27) increased the likelihood of sickness absence with greater odds when it is a back pain (OR = 3.05; 95% CI: 1.66?5.62). Increased age, physical activity, and sleep were not associated with sick leave.
Conclusion: Several variables were statistically associated with the occurrence of sickness absenteeism. One primary concern is the limited research in this area despite alarming rates of sick leave in healthcare. More research is required to identify predictors of sickness absence, and thereby, implement preventative measures.
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KEYWORD
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Meta-analysis, Nursing, Predictors, Sickness Absenteeism
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