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dc.contributor.authorStandal, Martin Inge
dc.contributor.authorAasdahl, Lene
dc.contributor.authorJensen, Chris
dc.contributor.authorFoldal, Vegard
dc.contributor.authorHagen, Roger
dc.contributor.authorFors, Egil Andreas
dc.contributor.authorSolbjør, Marit
dc.contributor.authorHjemdal, Odin
dc.contributor.authorGrotle, Margreth
dc.contributor.authorMeisingset, Ingebrigt
dc.identifier.citationJournal of occupational rehabilitation. 2020, .en_US
dc.description.abstractComorbidity is common among long-term sick-listed and many prognostic factors for return to work (RTW) are shared across diagnoses. RTW interventions have small effects, possibly due to being averaged across heterogeneous samples. Identifying subgroups based on prognostic RTW factors independent of diagnoses might help stratify interventions. The aim of this study was to identify and describe subgroups of long-term sick-listed workers, independent of diagnoses, based on prognostic factors for RTW. Latent class analysis of 532 workers sick-listed for eight weeks was used to identify subgroups based on seven prognostic RTW factors (self-reported health, anxiety and depressive symptoms, pain, self-efficacy, work ability, RTW expectations) and four covariates (age, gender, education, physical work). Four classes were identified: Class 1 (45% of participants) was characterized by favorable scores on the prognostic factors; Class 2 (22%) by high anxiety and depressive symptoms, younger age and higher education; Class 3 (16%) by overall poor scores including high pain levels; Class 4 (17%) by physical work and lack of workplace adjustments. Class 2 included more individuals with a psychological diagnosis, while diagnoses were distributed more proportionate to the sample in the other classes. The identified classes illustrate common subgroups of RTW prognosis among long-term sick-listed individuals largely independent of diagnosis. These classes could in the future assist RTW services to provide appropriate type and extent of follow-up, however more research is needed to validate the class structure and examine how these classes predict outcomes and respond to interventions.en_US
dc.publisherSpringer Natureen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleSubgroups of long-term sick-listed based on prognostic return to work factors across diagnoses – A cross-sectional latent class analysisen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalJournal of occupational rehabilitationen_US
dc.relation.projectNorges forskningsråd: 256633en_US
dc.description.localcodeOpen Access This 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

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal