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Cited by 282

The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.

Shoulder disorders and occupation

Open access
Linaker, Catherine H., Walker-Bone, Karen·2015·Best Practice & Research Clinical Rheumatology
DOI 10.1016/j.berh.2015.04.001
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Abstract

Shoulder pain is very common and causes substantial morbidity. Standardised classification systems based upon presumed patho-anatomical origins have proved poorly reproducible and hampered epidemiological research. Despite this, there is evidence that exposure to combinations of physical workplace strains such as overhead working, heavy lifting and forceful work as well as working in an awkward posture increase the risk of shoulder disorders. Psychosocial risk factors are also associated. There is currently little evidence to suggest that either primary prevention or treatment strategies in the workplace are very effective and more research is required, particularly around the cost-effectiveness of different strategies.

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Registry

Crossref · 10.1016/j.berh.2015.04.001

Cites

77 of 77 references verified0 citation errors · 0 not checkable

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Citations

Cites

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Metadata

Authors
Linaker, C. H., & Walker-Bone, K.
Venue
Best Practice & Research Clinical Rheumatology
Publisher
Elsevier BV
Published
2015-06
Volume
29
Issue
3
Pages
405-423
ISSN
1521-6942 (ISSN-L)
DOI
10.1016/j.berh.2015.04.001
OpenAlex
W305151308
Cited by
282
References
77
FWCI
8.48
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Shoulder disorders and occupation. https://app.cochat.ai/papers/10.1016/j.berh.2015.04.001
The paper
Linaker, C. H., & Walker-Bone, K. (2015). Shoulder disorders and occupation. Best Practice & Research Clinical Rheumatology. https://doi.org/10.1016/j.berh.2015.04.001

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.