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Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

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Abstract

Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models’ risk discrimination was also investigated. Methods 2,562 municipal eldercare workers (95 % women) participated in the Working in Eldercare Survey. Predictor variables were measured by questionnaire at baseline in 2005. Prognostic models were validated for predictions of high (≥30) SA days and high (≥3) SA episodes retrieved from employer records during 1-year follow-up. The accuracy of predictions was assessed by calibration graphs and the ability of the models to discriminate between high- and low-risk workers was investigated by ROC-analysis. The added value of work environment variables was measured with Integrated Discrimination Improvement (IDI). Results 1,930 workers had complete data for analysis. The models underestimated the risk of high SA in eldercare workers and the SA episodes model had to be re-calibrated to the Danish data. Discrimination was practically useful for the re-calibrated SA episodes model, but not the SA days model. Physical workload improved the SA days model (IDI = 0.40; 95 % CI 0.19–0.60) and psychosocial work factors, particularly the quality of leadership (IDI = 0.70; 95 % CI 053–0.86) improved the SA episodes model. Conclusions The prognostic model predicting high SA days showed poor performance even after physical workload was added. The prognostic model predicting high SA episodes could be used to identify high-risk workers, especially when psychosocial work factors are added as predictor variables.

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Conflict of interest

The authors Corné Roelen, Christina Malmose Stapelfeldt, Martijn Heymans, Willem van Rhenen, Merete Labriola, Claus Vinther Nielsen, Ute Bültmann, and Chris Jensen declare that they have no conflict of interest.

Informed consent

Eldercare workers participated in the Working in Eldercare Survey in 2005. For the present study, available survey data were used without collecting new participant data. The Danish Data Protection Agency approved of using the survey data (reference 2012-41-1290). All procedures followed were in accordance with the Helsinki Declaration of 1975 as revised in 2000.

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Authors and Affiliations

  1. ArboNed Occupational Health Service, PO Box 85091, 3508 AB, Utrecht, The Netherlands

    Corné A. M. Roelen & Willem van Rhenen

  2. Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands

    Corné A. M. Roelen & Martijn W. Heymans

  3. Section of Community and Occupational Medicine, Department of Health Sciences, University Medical Center Groningen, University of Groningen, PO Box 196, 9700 AD, Groningen, The Netherlands

    Corné A. M. Roelen & Ute Bültmann

  4. Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, Aarhus, Denmark

    Christina M. Stapelfeldt & Merete Labriola

  5. Section of Clinical Social Medicine and Rehabilitation, Department of Public Health, Aarhus University, Aarhus, Denmark

    Claus V. Nielsen

  6. Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway

    Chris Jensen

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  1. Corné A. M. Roelen
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  2. Christina M. Stapelfeldt
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  3. Martijn W. Heymans
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Correspondence to Corné A. M. Roelen.

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Roelen, C.A.M., Stapelfeldt, C.M., Heymans, M.W. et al. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables. J Occup Rehabil 25, 279–287 (2015). https://doi.org/10.1007/s10926-014-9536-3

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  • DOI: https://doi.org/10.1007/s10926-014-9536-3

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