Predicting long-term sickness absence among employees with frequent sickness absence.
Adult
Burnout, Professional
Cohort Studies
Educational Status
Female
Humans
Male
Marital Status
Middle Aged
Models, Statistical
Netherlands
Occupational Health
/ statistics & numerical data
ROC Curve
Risk Factors
Sick Leave
/ statistics & numerical data
Surveys and Questionnaires
Work Engagement
Workload
Absenteeism
Health surveillance
Occupational health
Prediction model
ROC analysis
Sick leave
Journal
International archives of occupational and environmental health
ISSN: 1432-1246
Titre abrégé: Int Arch Occup Environ Health
Pays: Germany
ID NLM: 7512134
Informations de publication
Date de publication:
May 2019
May 2019
Historique:
received:
14
05
2018
accepted:
04
11
2018
pubmed:
27
11
2018
medline:
31
10
2019
entrez:
27
11
2018
Statut:
ppublish
Résumé
Frequent absentees are at risk of long-term sickness absence (SA). The aim of the study is to develop prediction models for long-term SA among frequent absentees. Data were obtained from 53,833 workers who participated in occupational health surveys in the period 2010-2013; 4204 of them were frequent absentees (i.e., employees with ≥ 3 SA spells in the year prior to the survey). The survey data of the frequent absentees were used to develop two prediction models: model 1 including job demands and job resources and model 2 including burnout and work engagement. Discrimination between frequent absentees with and without long-term SA during follow-up was assessed with the area under the receiver operating characteristic curve (AUC); (AUC) ≥ 0.75 was considered useful for practice. A total of 3563 employees had complete data for analyses and 685 (19%) of them had long-term SA during 1-year follow-up. The final model 1 included age, gender, education, marital status, prior long-term SA, work pace, role clarity and learning opportunities. Discrimination between frequent absentees with and without long-term SA was significant (AUC 0.623; 95% CI 0.601-0.646), but not useful for practice. Model 2 showed comparable discrimination (AUC 0.624; 95% CI 0.596-0.651) with age, gender, education, marital status, prior long-term SA, burnout and work engagement as predictor variables. Differentiating by gender or sickness absence cause did not result in better discrimination. Both prediction models discriminated significantly between frequent absentees with and without long-term SA during 1-year follow-up, but have to be further developed for use in healthcare practice.
Identifiants
pubmed: 30474733
doi: 10.1007/s00420-018-1384-6
pii: 10.1007/s00420-018-1384-6
pmc: PMC6435617
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
501-511Références
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