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dc.contributor.authorMelloh, Markus
dc.contributor.authorElfering, A.
dc.contributor.authorSalathé, C.
dc.contributor.authorKäser, A.
dc.contributor.authorBarz, T.
dc.contributor.authorRöder, C.
dc.contributor.authorTheis, J.
dc.date.accessioned2017-01-30T11:51:16Z
dc.date.available2017-01-30T11:51:16Z
dc.date.created2015-12-10T04:26:11Z
dc.date.issued2012
dc.identifier.citationMelloh, M. and Elfering, A. and Salathé, C. and Käser, A. and Barz, T. and Röder, C. and Theis, J. 2012. Predictors of sickness absence in patients with a new episode of low back pain in primary care. Industrial Health. 50 (4): pp. 288-298.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/15674
dc.identifier.doi10.2486/indhealth.MS1335
dc.description.abstract

This study examines predictors of sickness absence in patients presenting to a health practitioner with acute/ subacute low back pain (LBP). Aims of this study were to identify baseline-variables that detect patients with a new LBP episode at risk of sickness absence and to identify prognostic models for sickness absence at different time points after initial presentation. Prospective cohort study investigating 310 patients presenting to a health practitioner with a new episode of LBP at baseline, three-, six-, twelve-week and six-month follow-up, addressing work-related, psychological and biomedical factors. Multivariate logistic regression analysis was performed to identify baseline-predictors of sickness absence at different time points. Prognostic models comprised 'job control', 'depression' and 'functional limitation' as predictive baseline-factors of sickness absence at three and six-week follow-up with 'job control' being the best single predictor (OR 0.47; 95%CI 0.26-0.87). The six-week model explained 47% of variance of sickness absence at six-week follow-up (p<0.001). The prediction of sickness absence beyond six-weeks is limited, and health practitioners should re-assess patients at six weeks, especially if they have previously been identified as at risk of sickness absence. This would allow timely intervention with measures designed to reduce the likelihood of prolonged sickness absence. © 2012 National Institute of Occupational Safety and Health.

dc.titlePredictors of sickness absence in patients with a new episode of low back pain in primary care
dc.typeJournal Article
dcterms.source.volume50
dcterms.source.number4
dcterms.source.startPage288
dcterms.source.endPage298
dcterms.source.issn0019-8366
dcterms.source.titleIndustrial Health
curtin.departmentCurtin Medical School
curtin.accessStatusOpen access via publisher


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