Abstract
Purpose The objective of the present study was to validate an existing prediction rule (including age, education, depressive/anxiety symptoms, and recovery expectations) for predictions of the duration of sickness absence due to common mental disorders (CMDs) and investigate the added value of work-related factors. Methods A prospective cohort study including 596 employees who reported sick with CMDs in the period from September 2013 to April 2014. Work-related factors were measured at baseline with the Questionnaire on the Experience and Evaluation of Work. During 1-year follow-up, sickness absence data were retrieved from an occupational health register. The outcome variables of the study were sickness absence (no = 0, yes = 1) at 3 and 6 months after reporting sick with CMDs. Discrimination between workers with and without sickness absence was investigated at 3 and 6 months with the area under the receiver operating characteristic curve (AUC). Results A total of 220 (37 %) employees agreed to participate and 211 (35 %) had complete data for analysis. Discrimination was poor with AUC = 0.69 and AUC = 0.55 at 3 and 6 months, respectively. When 'variety in work' was added as predictor variable, discrimination between employees with and without CMD sickness absence improved to AUC = 0.74 (at 3 months) and AUC = 0.62 (at 6 months). Conclusions The original prediction rule poorly predicted CMD sickness absence duration. After adding 'variety in work', the prediction rule discriminated between employees with and without CMD sickness absence 3 months after reporting sick. This new prediction rule remains to be validated in other populations.
Original language | English |
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Pages (from-to) | 202-209 |
Number of pages | 8 |
Journal | Journal of Occupational Rehabilitation |
Volume | 27 |
Issue number | 2 |
Early online date | 3-Jun-2016 |
DOIs | |
Publication status | Published - Jun-2017 |
Keywords
- Mental disorders
- Prognosis
- Return to work
- Sick leave
- Validation studies
- SYMPTOM QUESTIONNAIRE 4DSQ
- DISABILITY PENSION
- PROGNOSTIC MODELS
- RISK-FACTORS
- WORK
- HEALTH
- POPULATION
- RETURN
- RECLASSIFICATION
- ENVIRONMENT