Evidence map›Paper›PMID 23765088›Full record

ArticleJournal of occupational rehabilitation2014

Are the predictors of work absence following a work-related injury similar for musculoskeletal and mental health claims?

Peter M Smith, Oliver Black, Tessa Keegel, Alex Collie

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Article in Journal of occupational rehabilitation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
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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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

4 authors.

Peter M SmithSchool of Public Health and Preventive Medicine, Monash University, Level 6, Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia, peter.smith@monash.edu.
Oliver Black
Tessa Keegel
Alex Collie

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine if the factors associated with days of absence following a work-related injury are similar for mental health versus musculoskeletal (MSK) conditions.

methodsA secondary analysis of wage replacement workers' compensation claims in the state of Victoria, Australia. We examined the relationship between individual, injury, occupational and workplace variables with days of wage replacement over the 2-year period following first day of absence from work separately for mental health claims and MSK claims using negative binomial regression models.

resultsMental health conditions were associated with a greater number of days of absence over the 2 years following first incapacity compared to MSK conditions. Differences were observed in employment, injury and industry variables on absence from work for mental claims compared to MSK claims. Working in the agriculture, forestry, fishing and mining industries and employment with a small organisation were more strongly associated with the number of days of wage-replacement among MSK compared to mental health claims, and working in the public administration and safety, or education and training industries or being employed in a position with high time pressure were associated with greater days of wage-replacement among mental health compared to MSK claims.

conclusionsPredictors of days away from work in the 2 years following an injury differ for mental health versus MSK claims. Given the increasing number of mental health claims in Australia more research is required to understand differences in return-to-work for this group of claimants compared to those with physical injuries.

Indexed as

EmploymentFemaleHumansInsurance Claim ReviewLogistic ModelsMaleMental DisordersMental HealthMiddle AgedMusculoskeletal DiseasesOccupational InjuriesPredictive Value of TestsReturn to WorkRisk FactorsSick LeaveVictoria

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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.