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Background: The Work Ability Index (WAI) identifies non-sicklisted workers at risk of future long-term sickness absence (LTSA). The WAI is a complicated instrument and inconvenient for use in large-scale surveys. We investigated whether shortened versions of the WAI identify non-sicklisted workers at risk of LTSA. Methods: Prospective study including two samples of non-sicklisted workers participating in occupational health checks between 2010 and 2012. A heterogeneous development sample (N = 2899) was used to estimate logistic regression coefficients for the complete WAI, a shortened WAI version without the list of diseases, and single-item Work Ability Score (WAS). These three instruments were calibrated for predictions of different (≥2, ≥4 and ≥6 weeks) LTSA durations in a validation sample of non-sicklisted workers (A/ = 3049) employed at a steel mill, differentiating between manual (N =1710) and non-manual (N=1339) workers. The discriminative ability was investigated by receiver operating characteristic analysis. Results: All three instruments under-predicted the LTSA risks in both manual and non-manual workers. The complete WAI discriminated between individuals at high and low risk of LTSA ≥2, ≥4 and ≥6 weeks in manual and non-manual workers. Risk predictions and discrimination by the shortened WAI without the list of diseases were as good as the complete WAI. The WAS showed poorer discrimination in manual and non-manual workers. Conclusions: The WAI without the list of diseases is a good alternative to the complete WAI to identify non-sicklisted workers at risk of future LTSA durations ≥2, ≥4 and ≥6 weeks. [ABSTRACT FROM AUTHOR]

Background: Recently, a three-item screener, derived from the 16-item distress scale of the Four-Dimensional Symptom Checklist (4DSQ), was used to measure psychological distress in sicklisted employees. The aim of the present study was to investigate the ability of the 16-item distress scale and three-item distress screener to identify non-sicklisted employees at risk of sickness absence (SA) due to mental disorders. Methods: Prospective cohort study including 4877 employees working in distribution and transport. The 4DSQ distress scale was distributed at baseline in November 2010. SA diagnosed within the International Classification of Diseases -10 chapter F was defined as mental SA and retrieved from an occupational health register during 2-year follow-up. The area under the receiver operating characteristic curve (AUC) was used to discriminate between workers with ('cases') and without ('non-cases') mental SA during follow-up. Results: A total of 2782 employees (57%) were included in complete cases analysis; 73 employees had mental SA during 2-year follow-up. Discrimination between cases and non-cases was similar for the 16-item distress scale (AUC =0.721; 95% CI, 0.622-0.823) and the three-item screener (AUC = 0.715; 95% CI, 0.615-0.815). Conclusion: Healthcare providers could use the three-item distress screener to identify non-sicklisted employees at risk of future mental SA. [ABSTRACT FROM AUTHOR]

Background: Self-rated health (SRH) has been found to predict sickness absence (SA). The present study investigated the effect of replacing single-item SRH by a multi-item health measure on SA predictions., Methods: Longitudinal study of 2059 Norwegian nurses with assessments in three waves each separated by 1 year. Health was measured by single-item SRH and multi-item SF-12 in waves 1 and 2. SA was self-reported in all three waves and high SA was defined as more than or equal to 31 SA days within the last 12 months. Predictions of high SA by a model including age, prior SA and single-item SRH were compared with predictions by a model including age, prior SA and multi-item SF-12. Both models were bootstrapped to correct for over-optimism and prospectively validated for their predictions in a new time frame., Results: 1253 nurses (61%) had complete data for analysis. The SF-12 model predicted the risk of high SA more accurately (χ(2) = 4.294; df = 8) and was more stable over time than the SRH model (model χ(2) = 14.495; df = 8). Both prediction models correctly discriminated between high-risk and low-risk individuals in 73% of the cases at wave 2 and in 71% of the cases at wave 3., Conclusions: The accuracy of predictions increased when single-item SRH was replaced by multi-item SF-12, but the discriminative ability did not improve. Single-item SRH suffices to identify employees at increased risk of high SA., (© The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.)