Evidence map›Paper›PMID 42625163›Full record

ArticleBMC musculoskeletal disorders2026

What clusters exist among the health care personnel screened for upper extremity musculoskeletal conditions?

Mahla Daliri, Farideh Khosravi, Jamshid Jamali, Mohammadtaghi Shakeri, Mehdi Ataei, Mohammad Hadi Nejat, Ali Moradi

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Mahla DaliriOrthopaedics Research Center, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID http://orcid.org/0000-0001-8722-1129
Farideh KhosraviStudent Research Committee, School of health, Mashhad University of medical sciences, Mashhad, Iran.
Jamshid JamaliDepartment of Biostatistics, Mashhad University of Medical Sciences, Mashhad, Iran.
Mohammadtaghi ShakeriDepartment of Biostatistics, Mashhad University of Medical Sciences, Mashhad, Iran.
Mehdi AtaeiOrthopaedics Research Center, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID http://orcid.org/0009-0008-4458-186X
Mohammad Hadi NejatOrthopaedics Research Center, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID http://orcid.org/0000-0002-6965-6177
Ali MoradiOrthopaedics Research Center, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran. MoradiAL@mums.ac.ir.ORCID http://orcid.org/0000-0001-5796-8774

Funding

Mashhad University of Medical Sciences 4010744
6 · The paper itself

Abstract

backgroundSelf-limiting or degenerative upper extremity musculoskeletal conditions (UEMSCs) are common and often managed without medical intervention. This study aims to identify latent subgroups of these conditions in individuals who do not seek care, by examining a range of biopsychosocial factors. Understanding these patterns, can provide insights to inform personalized and comprehensive care strategies for individuals who do seek medical attention for musculoskeletal illnesses.

methodsA total of 4,635 healthcare staff who provided consent were included in a within cohort-cross-sectional study. We conducted interviews and physical examinations to screen participants for common UEMSCs. Two latent class analyses (LCA) identified statistical groupings of the following upper extremity conditions diagnosed based on symptoms and signs: carpal tunnel syndrome (CTS), lateral epicondylitis (LE), trapeziometacarpal osteoarthritis (TMC OA), DeQuervain tendinopathy (DEQ), trigger digit (TD), ganglion cyst (GAN), and rotator cuff tendinopathy (RCT). One LCA among the 4635 people screened and the other LCA among the 713 people with at least one UEMSC. We then analyzed the association of several biopsychosocial factors with the specific classes identified.

resultsAmong the 4635 workers, 3 latent classes were identified: (1) All UEMSCs except GAN, high distress, lower socioeconomic status, and limited strength (0.4%; 18 workers), (2) Varied UEMSCs, high distress, lower socioeconomic status, and average strength (3.6%, 168 workers), and (3) Limited prevalence of UEMSCs, average distress, average socioeconomic status, and average strength (96%, 4449 workers). Among the 713 people with at least one UE diagnosis 4 latent classes were identified: (1) Isolated RCT (30%, 223 people), (2) Isolated CTS (16%, 127 people) (3) Isolated GAN (7%, 47 people), and (4) varied other specific UEMSCs (47%, 316 people). The people in the GAN class were younger and both mentally and physically healthier.

conclusionThe finding that upper extremity musculoskeletal symptoms and signs are classified with psychological distress and lower socio-economic status among people not seeking care (population cohort), particularly when there is more than one focus of musculoskeletal symptoms, suggests that mental and social health may be key aspects of musculoskeletal illness. TYPE OF STUDY/LOE: Differential Diagnosis / Symptom Prevalence Study. LEVEL OF EVIDENCE: Level II.

Indexed as

Health PersonnelMass ScreeningMusculoskeletal DiseasesUpper ExtremityAdultCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedBiopsychosocialClassification, iranLatent class analysisMusculoskeletalOrthopedicUpper extremity

Identifiers

PMID42625163
PMCPMC13491856

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LicenceCC BY-NC-ND
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Registered trials

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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.