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Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study

BACKGROUND: Long-term sickness absence results in increased risks of permanent disability and a compromised quality of life. Return to work is an important factor in reducing these risks. Little is known about return to work factors for long-term sick-listed workers with subjective health complaints...

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Autores principales: Weerdesteijn, Kristel H. N., Schaafsma, Frederieke, Bonefaas-Groenewoud, Karin, Heymans, Martijn, Van der Beek, Allard, Anema, Johannes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354686/
https://www.ncbi.nlm.nih.gov/pubmed/32652981
http://dx.doi.org/10.1186/s12889-020-09203-5
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author Weerdesteijn, Kristel H. N.
Schaafsma, Frederieke
Bonefaas-Groenewoud, Karin
Heymans, Martijn
Van der Beek, Allard
Anema, Johannes
author_facet Weerdesteijn, Kristel H. N.
Schaafsma, Frederieke
Bonefaas-Groenewoud, Karin
Heymans, Martijn
Van der Beek, Allard
Anema, Johannes
author_sort Weerdesteijn, Kristel H. N.
collection PubMed
description BACKGROUND: Long-term sickness absence results in increased risks of permanent disability and a compromised quality of life. Return to work is an important factor in reducing these risks. Little is known about return to work factors for long-term sick-listed workers with subjective health complaints. The aim of this study was to evaluate prognostic factors for partial or full return to a paid job for at least 28 days for long-term sick-listed workers with subjective health complaints, and to compare these factors with those of workers with other disorders. METHODS: Data from a prospective cohort study of 213 participants with subjective health complaints and 1.037 reference participants were used. The participants answered a questionnaire after 84 weeks of sickness absence. Return to work was measured after one and two years. Univariable logistic regression analyses were performed (P ≤ 0.157) for variables per domain with return to work (i.e. demographic, socio-economic and work-related, health-related, and self-perceived ability). Subsequently, multivariable logistic regression analyses with backward selection (P ≤ 0.157) were performed. Remaining factors were combined in a multivariable and final model (P ≤ 0.05). RESULTS: Both for workers with subjective health complaints and for the reference group, non-health-related factors remained statistically significant in the final model. This included receiving a partial or complete work disability benefit (partial: OR 0.62, 95% CI 0.26–1.47 and OR 0.69, 95% CI 0.43–1.12; complete: OR 0.24, 95% CI 0.10–0.58 and OR 0.12, 95% CI 0.07–0.20) and having a positive self-perceived possibility for return to work (OR 1.06, 95% CI 1.01–1.11 and OR 1.08, 95% CI 1.05–1.11). CONCLUSIONS: Non-health-related factors seem to be more important than health-related factors in predicting return to work after long-term sickness absence. Receiving a work disability benefit and having negative expectations for return to work seem to complicate return to work most for workers with subjective health complaints. With respect to return to work predictors, workers with subjective health complaints do not differ from the reference group.
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spelling pubmed-73546862020-07-15 Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study Weerdesteijn, Kristel H. N. Schaafsma, Frederieke Bonefaas-Groenewoud, Karin Heymans, Martijn Van der Beek, Allard Anema, Johannes BMC Public Health Research Article BACKGROUND: Long-term sickness absence results in increased risks of permanent disability and a compromised quality of life. Return to work is an important factor in reducing these risks. Little is known about return to work factors for long-term sick-listed workers with subjective health complaints. The aim of this study was to evaluate prognostic factors for partial or full return to a paid job for at least 28 days for long-term sick-listed workers with subjective health complaints, and to compare these factors with those of workers with other disorders. METHODS: Data from a prospective cohort study of 213 participants with subjective health complaints and 1.037 reference participants were used. The participants answered a questionnaire after 84 weeks of sickness absence. Return to work was measured after one and two years. Univariable logistic regression analyses were performed (P ≤ 0.157) for variables per domain with return to work (i.e. demographic, socio-economic and work-related, health-related, and self-perceived ability). Subsequently, multivariable logistic regression analyses with backward selection (P ≤ 0.157) were performed. Remaining factors were combined in a multivariable and final model (P ≤ 0.05). RESULTS: Both for workers with subjective health complaints and for the reference group, non-health-related factors remained statistically significant in the final model. This included receiving a partial or complete work disability benefit (partial: OR 0.62, 95% CI 0.26–1.47 and OR 0.69, 95% CI 0.43–1.12; complete: OR 0.24, 95% CI 0.10–0.58 and OR 0.12, 95% CI 0.07–0.20) and having a positive self-perceived possibility for return to work (OR 1.06, 95% CI 1.01–1.11 and OR 1.08, 95% CI 1.05–1.11). CONCLUSIONS: Non-health-related factors seem to be more important than health-related factors in predicting return to work after long-term sickness absence. Receiving a work disability benefit and having negative expectations for return to work seem to complicate return to work most for workers with subjective health complaints. With respect to return to work predictors, workers with subjective health complaints do not differ from the reference group. BioMed Central 2020-07-11 /pmc/articles/PMC7354686/ /pubmed/32652981 http://dx.doi.org/10.1186/s12889-020-09203-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Weerdesteijn, Kristel H. N.
Schaafsma, Frederieke
Bonefaas-Groenewoud, Karin
Heymans, Martijn
Van der Beek, Allard
Anema, Johannes
Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title_full Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title_fullStr Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title_full_unstemmed Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title_short Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
title_sort predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354686/
https://www.ncbi.nlm.nih.gov/pubmed/32652981
http://dx.doi.org/10.1186/s12889-020-09203-5
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