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The long-term prediction of return to work following serious accidental injuries: A follow up study
BACKGROUND: Considerable indirect costs are incurred by time taken off work following accidental injuries. The aim of this study was to predict return to work following serious accidental injuries. METHOD: 121 severely injured patients were included in the study. Complete follow-up data were availab...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3082290/ https://www.ncbi.nlm.nih.gov/pubmed/21470424 http://dx.doi.org/10.1186/1471-244X-11-53 |
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author | Hepp, Urs Moergeli, Hanspeter Buchi, Stefan Bruchhaus-Steinert, Helke Sensky, Tom Schnyder, Ulrich |
author_facet | Hepp, Urs Moergeli, Hanspeter Buchi, Stefan Bruchhaus-Steinert, Helke Sensky, Tom Schnyder, Ulrich |
author_sort | Hepp, Urs |
collection | PubMed |
description | BACKGROUND: Considerable indirect costs are incurred by time taken off work following accidental injuries. The aim of this study was to predict return to work following serious accidental injuries. METHOD: 121 severely injured patients were included in the study. Complete follow-up data were available for 85 patients. Two weeks post trauma (T1), patients rated their appraisal of the injury severity and their ability to cope with the injury and its job-related consequences. Time off work was assessed at one (T2) and three years (T3) post accident. The main outcome was the number of days of sick leave taken due to the accidental injury. RESULTS: The patients' appraisals a) of the injury severity and b) of their coping abilities regarding the accidental injury and its job-related consequences were significant predictors of the number of sick-leave days taken. Injury severity (ISS), type of accident, age and gender did not contribute significantly to the prediction. CONCLUSIONS: Return to work in the long term is best predicted by the patients' own appraisal of both their injury severity and the ability to cope with the accidental injury. |
format | Text |
id | pubmed-3082290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30822902011-04-27 The long-term prediction of return to work following serious accidental injuries: A follow up study Hepp, Urs Moergeli, Hanspeter Buchi, Stefan Bruchhaus-Steinert, Helke Sensky, Tom Schnyder, Ulrich BMC Psychiatry Research Article BACKGROUND: Considerable indirect costs are incurred by time taken off work following accidental injuries. The aim of this study was to predict return to work following serious accidental injuries. METHOD: 121 severely injured patients were included in the study. Complete follow-up data were available for 85 patients. Two weeks post trauma (T1), patients rated their appraisal of the injury severity and their ability to cope with the injury and its job-related consequences. Time off work was assessed at one (T2) and three years (T3) post accident. The main outcome was the number of days of sick leave taken due to the accidental injury. RESULTS: The patients' appraisals a) of the injury severity and b) of their coping abilities regarding the accidental injury and its job-related consequences were significant predictors of the number of sick-leave days taken. Injury severity (ISS), type of accident, age and gender did not contribute significantly to the prediction. CONCLUSIONS: Return to work in the long term is best predicted by the patients' own appraisal of both their injury severity and the ability to cope with the accidental injury. BioMed Central 2011-04-06 /pmc/articles/PMC3082290/ /pubmed/21470424 http://dx.doi.org/10.1186/1471-244X-11-53 Text en Copyright ©2011 Hepp et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hepp, Urs Moergeli, Hanspeter Buchi, Stefan Bruchhaus-Steinert, Helke Sensky, Tom Schnyder, Ulrich The long-term prediction of return to work following serious accidental injuries: A follow up study |
title | The long-term prediction of return to work following serious accidental injuries: A follow up study |
title_full | The long-term prediction of return to work following serious accidental injuries: A follow up study |
title_fullStr | The long-term prediction of return to work following serious accidental injuries: A follow up study |
title_full_unstemmed | The long-term prediction of return to work following serious accidental injuries: A follow up study |
title_short | The long-term prediction of return to work following serious accidental injuries: A follow up study |
title_sort | long-term prediction of return to work following serious accidental injuries: a follow up study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3082290/ https://www.ncbi.nlm.nih.gov/pubmed/21470424 http://dx.doi.org/10.1186/1471-244X-11-53 |
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