Evidence map›Paper›PMID 27807731›Full record

ArticleJournal of occupational rehabilitation2017

Who will have Sustainable Employment After a Back Injury? The Development of a Clinical Prediction Model in a Cohort of Injured Workers.

Heather M Shearer, Pierre Côté, Eleanor Boyle, Jill A Hayden, John Frank, William G Johnson

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Article in Journal of occupational rehabilitation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Heather M ShearerUOIT-CMCC Center for the Study of Disability Prevention and Rehabilitation, University of Ontario Institute of Technology, 2000 Simcoe St. North, Oshawa, ON, L1H 7K4, Canada. heather.shearer@uoit.ca.
Pierre CôtéUOIT-CMCC Center for the Study of Disability Prevention and Rehabilitation, University of Ontario Institute of Technology, 2000 Simcoe St. North, Oshawa, ON, L1H 7K4, Canada.
Eleanor BoyleDivision of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Jill A HaydenDepartment of Community Health and Epidemiology, Dalhousie University, 5790 University Avenue, Room 403, Halifax, NS, B3H 1V7, Canada.
John FrankChair, Public Health Research and Policy, Usher Institute of Population Health Sciences, University of Edinburgh, Scottish Collaboration for Public Health Research and Policy, First Floor, 20 West Richmond St., Edinburgh, EH4 6AQ, UK.
William G JohnsonDepartment of Biomedical Informatics, Arizona State University, Samuel C. Johnson Research Bldg., 13212 Shea Blvd., Scottsdale, AZ, 85259, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose Our objective was to develop a clinical prediction model to identify workers with sustainable employment following an episode of work-related low back pain (LBP). Methods We used data from a cohort study of injured workers with incident LBP claims in the USA to predict employment patterns 1 and 6 months following a workers' compensation claim. We developed three sequential models to determine the contribution of three domains of variables: (1) basic demographic/clinical variables; (2) health-related variables; and (3) work-related factors. Multivariable logistic regression was used to develop the predictive models. We constructed receiver operator curves and used the c-index to measure predictive accuracy. Results Seventy-nine percent and 77 % of workers had sustainable employment at 1 and 6 months, respectively. Sustainable employment at 1 month was predicted by initial back pain intensity, mental health-related quality of life, claim litigation and employer type (c-index = 0.77). At 6 months, sustainable employment was predicted by physical and mental health-related quality of life, claim litigation and employer type (c-index = 0.77). Adding health-related and work-related variables to models improved predictive accuracy by 8.5 and 10 % at 1 and 6 months respectively. Conclusion We developed clinically-relevant models to predict sustainable employment in injured workers who made a workers' compensation claim for LBP. Inquiring about back pain intensity, physical and mental health-related quality of life, claim litigation and employer type may be beneficial in developing programs of care. Our models need to be validated in other populations.

Indexed as

Disability EvaluationAdultChi-Square DistributionFemaleHumansJob SatisfactionLow Back PainMaleOccupational InjuriesOutcome Assessment, Health CareProportional Hazards ModelsProspective StudiesReturn to WorkTime FactorsWorkers' CompensationBack injuriesEmploymentReturn to work

Identifiers

PMID27807731

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.