ArticleInternational archives of occupational and environmental health2020
External validation of a prediction model and decision tree for sickness absence due to mental disorders.
Article in International archives of occupational and environmental health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A novel model to predict mental distress among medical graduate students in China.BMC psychiatry · 2021Trial
- Variation in mental health-related sickness absence duration: The role of occupational health professionals.PloS one · 2026Article
- Machine learning prediction of long-term sickness absence due to mental disorders using Brief Job Stress Questionnaire data.Scientific reports · 2025Article
- Identifying risk factors of long sickness absences: a registry-based study using explainable AI methods.BMJ open · 2025Article
- External validation of a predictive model for post-treatment persistent disease byEuropean journal of nuclear medicine and molecular imaging · 2025Article
- Association Between Social Capital and Anxiety Among Older Adults in China: A Cross-Sectional Study.Psychology research and behavior management · 2025Article
- Assessment of Performance, Interpretability, and Explainability in Artificial Intelligence-Based Health Technologies: What Healthcare Stakeholders Need to Know.Mayo Clinic proceedings. Digital health · 2023Review
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4 authors.
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Abstract
purposeA previously developed prediction model and decision tree were externally validated for their ability to identify occupational health survey participants at increased risk of long-term sickness absence (LTSA) due to mental disorders.
methodsThe study population consisted of N = 3415 employees in mobility services who were invited in 2016 for an occupational health survey, consisting of an online questionnaire measuring the health status and working conditions, followed by a preventive consultation with an occupational health provider (OHP). The survey variables of the previously developed prediction model and decision tree were used for predicting mental LTSA (no = 0, yes = 1) at 1-year follow-up. Discrimination between survey participants with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC).
resultsA total of n = 1736 (51%) non-sick-listed employees participated in the survey and 51 (3%) of them had mental LTSA during follow-up. The prediction model discriminated (AUC = 0.700; 95% CI 0.628-0.773) between participants with and without mental LTSA during follow-up. Discrimination by the decision tree (AUC = 0.671; 95% CI 0.589-0.753) did not differ significantly (p = 0.62) from discrimination by the prediction model.
conclusionAt external validation, the prediction model and the decision tree both poorly identified occupational health survey participants at increased risk of mental LTSA. OHPs could use the decision tree to determine if mental LTSA risk factors should be explored in the preventive consultation which follows after completing the survey questionnaire.
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