Screening for the risk on long-term sickness absence

被引:7
|
作者
Goorts, Kaat [1 ]
Vandenbroeck, Sofie [1 ,2 ]
Rusu, Dorina [3 ,4 ]
Du Bois, Marc [1 ]
Godderisu, Lode [1 ,2 ]
机构
[1] Univ Leuven, Ctr Environm & Hlth, Kapucijnenvoer 35-5, B-3000 Leuven, Belgium
[2] IDEWE, External Serv Prevent & Protect Work, Leuven, Belgium
[3] Univ Liege, Dept Publ Hlth Sci, Occupat & Environm Med, Liege, Belgium
[4] SPMT ARISTA, External Serv Prevent & Protect Work, Leuven, Belgium
关键词
Long-term sickness absence; validation study; screening instrument;
D O I
10.4081/jphr.2018.1419
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Long-term sickness absence is a growing concern in Belgium and other European countries. Since 2017, Belgian physicians of the sickness funding organisations are required to assess the re-integration possibilities within the first two months of sickness absence. Given the shortage of physicians in the assessment of work disability and the growing number of people in sickness absence, there is a need for a triage tool, allowing to assign return-to work support to patients having a high-risk profile not to resume work. Methods/design: The current study comprises a comprehensive validation process of a screening tool that supports Belgian physicians in guiding people back to work. The study consists of a theoretical construct validation (face validity and content validity), and an empirical construct validation (concurrence validity, factorial validity, predictive validity, hypothesis testing validity and known-group validity). Expected impact of the study for Public Health: The screening instrument assessing the risk for long-term sickness absence is a tool developed to support physicians who work for sickness funds and for occupational health and safety organisations. Both professionals play an important role in the return to work process and the prevention of long-term sickness absence. The screening tool aims at making a distinction between people who will resume their work independently and people who will need support to do so. Generation of this prediction model will help physicians to focus effort and resources in the high-risk group. Results may also help understand the relationship between the biopsychosocial model and long-term sick-leave.
引用
收藏
页码:81 / 86
页数:6
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