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

被引:0
作者
Martin Inge Standal
Lene Aasdahl
Chris Jensen
Vegard Stolsmo Foldal
Roger Hagen
Egil Andreas Fors
Marit Solbjør
Odin Hjemdal
Margreth Grotle
Ingebrigt Meisingset
机构
[1] Norwegian University of Science and Technology,Department of Psychology, Faculty of Social and Educational Sciences
[2] Norwegian University of Science and Technology,Department of Public Health and Nursing, Faculty of Medicine and Health Sciences
[3] Unicare Helsefort Rehabilitation Centre,General Practice Research Unit, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences
[4] National Center for Occupational Rehabilitation,Department of Physiotherapy, Faculty of Health Sciences
[5] Norwegian University of Science and Technology,Department for Research of Musculoskeletal Disorders (FORMI)
[6] Oslo Metropolitan University,undefined
[7] Oslo University Hospital,undefined
来源
Journal of Occupational Rehabilitation | 2021年 / 31卷
关键词
Sick leave; Return to work; Vocational rehabilitation; Common mental disorder; Pain;
D O I
暂无
中图分类号
学科分类号
摘要
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.
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页码:383 / 392
页数:9
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共 299 条
[1]  
Hoefsmit N(2012)Intervention characteristics that facilitate return to work after sickness absence: a systematic literature review J Occup Rehabil 22 462-477
[2]  
Houkes I(2018)Effectiveness of workplace interventions in return-to-work for musculoskeletal, pain-related and mental health conditions: an update of the evidence and messages for practitioners J Occup Rehabil 28 1-15
[3]  
Nijhuis FJ(2017)Return-to-work coordination programmes for improving return to work in workers on sick leave Cochrane Database Syst Rev. 3 CD011618-179
[4]  
Cullen K(2018)Effect of inpatient multicomponent occupational rehabilitation versus less comprehensive outpatient rehabilitation on sickness absence in persons with musculoskeletal- or mental health disorders: a randomized clinical trial J Occup Rehabil 28 170-8
[5]  
Irvin E(2011)Subgrouping patients with low back pain in primary care: are we getting any better at it? Man Ther 16 3-203
[6]  
Collie A(2015)The science of clinical practice: disease diagnosis or patient prognosis? Evidence about “what is likely to happen” should shape clinical practice BMC Med 13 20-1602
[7]  
Clay F(2008)Against diagnosis Ann Intern Med 149 200-43
[8]  
Gensby U(2016)Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 Lancet 388 1545-231
[9]  
Jennings P(2012)Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study Lancet 380 37-29
[10]  
Vogel N(2018)Common psychosocial factors predicting return to work after common mental disorders, cardiovascular diseases, and cancers: a review of reviews supporting a cross-disease approach J Occup Rehabil 28 215-27