Subgroups of Long-Term Sick-Listed Based on Prognostic Return to Work Factors Across Diagnoses: A Cross-Sectional Latent Class Analysis

Martin Inge Standal,Odin Hjemdal,Lene Aasdahl,Egil Andreas Fors,Margreth Grotle,Marit Solbjør,Vegard Stolsmo Foldal,Chris Jensen,Roger Hagen,Ingebrigt Meisingset

doi:10.1007/s10926-020-09928-5

Abstract

Comorbidity 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.

Highlights

Prolonged sickness absence is costly for society and associated with adverse health outcomes and comorbidity for the individual [1]
In order to help individuals return to work (RTW) effective vocational rehabilitation interventions are required as healthcare treatment alone has little impact on work outcomes [2]
Studies using prognostic factors have found subgroups characterized by Identification of those at risk for prolonged sick leave is important for both social insurance and vocational rehabilitation services in order to create plans for RTW [63]

Summary

Introduction

Prolonged sickness absence is costly for society and associated with adverse health outcomes and comorbidity for the individual [1]. In order to help individuals return to work (RTW) effective vocational rehabilitation interventions are required as healthcare treatment alone has little impact on work outcomes [2]. The variation in effectiveness found in RTW interventions could partly be due to the effects being averaged across heterogeneous samples, meaning some subgroups will have no benefit or possibly even experience negative outcomes of these interventions [7]. Diagnosis is often used as basis for recruitment into such interventions, even though diagnosis provides limited information of the complexity and interrelationship between factors associated with prognosis [8, 9].

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