caa a22 4500 606211322 CHVBK 20210128101037.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s10926-014-9536-3 doi (NATIONALLICENCE)springer-10.1007/s10926-014-9536-3 Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables [Elektronische Daten] [Corné Roelen, Christina Stapelfeldt, Martijn Heymans, Willem van Rhenen, Merete Labriola, Claus Nielsen, Ute Bültmann, Chris Jensen] 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. Springer Science+Business Media New York, 2014 Absenteeism nationallicence Decision support techniques nationallicence Health care sector nationallicence Reproducibility of results nationallicence Sick leave nationallicence Workload nationallicence Roelen Corné ArboNed Occupational Health Service, PO Box 85091, 3508 AB, Utrecht, The Netherlands aut Stapelfeldt Christina Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, Aarhus, Denmark aut Heymans Martijn Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands aut van Rhenen Willem ArboNed Occupational Health Service, PO Box 85091, 3508 AB, Utrecht, The Netherlands aut Labriola Merete Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, Aarhus, Denmark aut Nielsen Claus Section of Clinical Social Medicine and Rehabilitation, Department of Public Health, Aarhus University, Aarhus, Denmark aut Bültmann Ute 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 aut Jensen Chris Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway aut Journal of Occupational Rehabilitation Springer US; http://www.springer-ny.com 25/2(2015-06-01), 279-287 1053-0487 25:2<279 2015 25 10926 https://doi.org/10.1007/s10926-014-9536-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10926-014-9536-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Roelen Corné ArboNed Occupational Health Service, PO Box 85091, 3508 AB, Utrecht, The Netherlands aut NATIONALLICENCE 700 1- Stapelfeldt Christina Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, Aarhus, Denmark aut NATIONALLICENCE 700 1- Heymans Martijn Department of Epidemiology and Biostatistics, VU University Medical Center, VU University, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands aut NATIONALLICENCE 700 1- van Rhenen Willem ArboNed Occupational Health Service, PO Box 85091, 3508 AB, Utrecht, The Netherlands aut NATIONALLICENCE 700 1- Labriola Merete Public Health and Quality Improvement, Central Denmark Region, MarselisborgCentret, Aarhus, Denmark aut NATIONALLICENCE 700 1- Nielsen Claus Section of Clinical Social Medicine and Rehabilitation, Department of Public Health, Aarhus University, Aarhus, Denmark aut NATIONALLICENCE 700 1- Bültmann Ute 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 aut NATIONALLICENCE 700 1- Jensen Chris Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway aut NATIONALLICENCE 773 0- Journal of Occupational Rehabilitation Springer US; http://www.springer-ny.com 25/2(2015-06-01), 279-287 1053-0487 25:2<279 2015 25 10926