Evidence map›Paper›PMID 37672733›Full record

ArticleScandinavian journal of work, environment & health2023

Development and validation of a work-related risk score for upper-extremity musculoskeletal disorders in a French working population.

Clémence Rapicault, Yves Roquelaure, Julie Bodin, Natacha Fouquet, Sandrine Bertrais

Abstract read
In one paragraph

Article in Scandinavian journal of work, environment & health, 2023. 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

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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

5 authors.

Clémence RapicaultINSERM UMR 1085 - IRSET, Equipe Epidémiologie en Santé au Travail et Ergonomie (ESTER), Faculté de Santé - Département Médecine, 28 rue Roger Amsler, CS 74521, F-49045 Angers Cedex 1, France. clemence.rapicault@univ-angers.fr.
Yves Roquelaure
Julie Bodin
Natacha Fouquet
Sandrine Bertrais

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim was to develop an easy-to-use risk score based on occupational factors and to validate its performance to identify workers either having (diagnostic setting) or developing (prognostic setting) upper-extremity musculoskeletal disorders (UEMSD).

methodsThis study relied on data from the Cosali prospective cohort conducted in a French working population. Diagnostic status for six UEMSD at inclusion and at follow-up was assessed by a standardized clinical examination. Data on occupational factors were collected through a self-administered questionnaire completed before the clinical examination at inclusion. The risk score was derived from a prediction model developed on data of 2,468 workers included in 2002-2003, and the validation sample is composed of 1,051 workers included later in 2004-2005. The prognostic performance of the risk score was assessed in workers without UEMSD at baseline.

resultsA total of 13% and 12% of workers had a UEMSD at inclusion in the development and validation sample. The developed risk score includes physical, organizational and psychosocial factors at work. In the validation sample, this score had acceptable performance for identifying workers having or not UEMSD at baseline (AUC: 0.60 [95% CI 0.57 to 0.63]), in particular the negative predictive value was high (89%-90%). The baseline risk score showed similar performance for predicting incident UEMSD at follow-up examination.

conclusionThis score can be useful as a first-line risk assessment tool, especially for excluding the low-risk work situations from further intervention by an ergonomist. Further validation studies are needed to determine its performance among various working populations.

Indexed as

Musculoskeletal DiseasesOccupational DiseasesHumansProspective StudiesRisk FactorsUpper Extremity

Identifiers

PMID37672733
PMCPMC10858731

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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.