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Record W4407778782 · doi:10.1136/bmjopen-2024-094220

Online physical activity resources for individuals with rheumatoid arthritis: an environmental scan and quality appraisal

2025· review· en· W4407778782 on OpenAlexafffund
Manuel Ester, Saania Zafar, Kiran Dhiman, Christine Graveline, Annette McKinnon, Alison M. Hoens, Claire Barber

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of British ColumbiaResearch CanadaArthritis Research Centre of CanadaAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersMitacs
KeywordsMedicineRheumatoid arthritisQuality (philosophy)Physical therapyFamily medicineEnvironmental healthIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To review publicly available physical activity (PA) resources for individuals with rheumatoid arthritis (RA). Aims were to find online print and audiovisual resources, review their characteristics and critically examine their quality from medical, exercise and behavioural science perspectives. DESIGN: An environmental scan was completed using the Google search engine, following a pragmatic approach to reviewing patient-facing self-care resources. DATA SOURCES: We used combinations of common search terms for RA and PA. The first five pages of results were reviewed for patient-facing resources. ELIGIBILITY CRITERIA: Resources were included if they were (1) included RA-specific content, (2) provided specific PA recommendations, (3) written in English and (4) freely available. DATA EXTRACTION AND SYNTHESIS: Two independent experts completed a medical review of resources to ensure appropriateness for RA. Data were then extracted by two reviewers using a standardised template to record resource characteristics. Two research team members and two patient partners independently evaluated resources for readability, understandability and actionability. Finally, the quality of exercise recommendations and behaviour change technique use was evaluated by an expert reviewer. RESULTS: The search yielded 23 RA-specific PA resources, 17 of which passed the medical review. All 10 print resources and 7 audiovisual resources were created in English-speaking countries. The mean reading grade was 9.0±1.5. Print resources had mean understandability of 80.0±9.8% and actionability of 60.0±27.7%. Audiovisual materials had mean understandability of 86.0±9.2% and actionability of 86.9±22.9%. The quality of exercise recommendations was low. Only one resource provided comprehensive cardiovascular exercise advice, and two resources provided comprehensive strength exercise advice. 3-14 behaviour change technique groups were featured in each resource. The most common groups were 'shaping knowledge' and 'natural consequences'. CONCLUSIONS: The quality of RA-specific PA resources is variable. Some high-quality resources exist that provide actionable PA behaviour change advice. Healthcare teams may refer patients to these resources. However, more work is needed to improve the overall quality of resources. Codevelopment with patients, providers and exercise behaviour change experts is recommended, ensuring resources are actionable, contain clear exercise recommendations and promote behaviour change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.100
metaresearch head score (Gemma)0.305
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.100
Threshold uncertainty score0.527

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.305
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0390.034
Science and technology studies0.0020.002
Scholarly communication0.0060.008
Open science0.0030.006
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.094
GPT teacher head0.463
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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