Evidence map›Paper›PMID 39694882›Full record

ArticleMusculoskeletal care2024

An Analysis of Publicly Available National Health Service Information Leaflets for Patients With Shoulder Osteoarthritis.

Stacey Lalande, Maria Moffatt, Toby Smith, Vrinda Aggarwal, Chris Littlewood

Abstract read
In one paragraph

Article in Musculoskeletal care, 2024. 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

5 authors.

Stacey LalandeAiredale NHS Foundation Trust, Keighley, UK.
Maria MoffattUniversity of Liverpool, Liverpool, UK.
Toby SmithUniversity of Warwick, Coventry, UK.
Vrinda AggarwalEdge Hill University, Ormskirk, UK.
Chris LittlewoodUniversity of Salford, Salford, UK.

Funding

Health Education England NIHR303345National Institute for Health and Care Research NMSIDI-2023-007
6 · The paper itself

Abstract

backgroundShoulder osteoarthritis is a common cause of pain, disability and difficulty sleeping. Patient information leaflets are produced by NHS Trusts with the aim of informing patients about their diagnosis and available treatment options.

objectivesThe aim of this study was to identify and describe the non-surgical management of people with shoulder osteoarthritis according to publicly available information leaflets produced by NHS Trusts.

methodsOne reviewer undertook an electronic search using Google to identify publicly available patient-facing information leaflets (PIL) produced by NHS Trusts which detailed non-surgical management strategies for people with shoulder osteoarthritis. Relevant data were extracted by one reviewer and verified by two reviewers.

resultsSeventeen PILs from 17 different UK NHS Trusts were identified ranging from December 2016 to February 2024. Information provided in the PIL varied, with topics including general osteoarthritis management, exercise, analgesia, injections, and surgical indications. No PIL covered all areas recommended in the NICE Osteoarthritis Management guidelines.

conclusionPILs developed and published by NHS Trusts are variable in content and do not fully reflect current clinical guidelines. High-quality research to inform consistent, clinically, and cost-effective treatment pathways, including information provision, for patients with shoulder osteoarthritis is needed.

Indexed as

OsteoarthritisPamphletsPatient Education as TopicState MedicineHumansShoulder JointUnited Kingdommanagementpatient informationphysiotherapyshoulder osteoarthritis

Identifiers

PMID39694882
PMCPMC11655428

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.