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Record W4386744328 · doi:10.1186/s12891-023-06877-x

Identifying strategies that support equitable person-centred osteoarthritis care for diverse women: content analysis of guidelines

2023· article· en· W4386744328 on OpenAlexafffund
Chidinma Abuwa, Angelina Abbaticchio, Madeline Theodorlis, Deborah A. Marshall, Crystal MacKay, Cornelia M. Borkhoff, Glen Hazlewood, Marisa Battistella, Aïsha Lofters, Vandana Ahluwalia, Anna R. Gagliardi

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsWilliam Osler Health SystemPublic Health OntarioUniversity Health NetworkToronto General HospitalUniversity of TorontoWest Park Healthcare CentreUniversity of Calgary
FundersArthritis SocietyCanadian Rheumatology AssociationArthritis Health Professions AssociationBone and Joint Canada
KeywordsMedicinePsychological interventionDisadvantagedGuidelineSocioeconomic statusFamily medicineMEDLINEContent analysisNursingPopulationEnvironmental healthPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Women are disproportionately impacted by osteoarthritis (OA) but less likely than men to access early diagnosis and management, or experience OA care tailored through person-centred approaches to their needs and preferences, particularly racialized women. One way to support clinicians in optimizing OA care is through clinical guidelines. We aimed to examine the content of OA guidelines for guidance on providing equitable, person-centred care to disadvantaged groups including women. METHODS: We searched indexed databases and websites for English-language OA-relevant guidelines published in 2000 or later by non-profit organizations. We used manifest content analysis to extract data, and summary statistics and text to describe guideline characteristics, person-centred care (PCC) using a six-domain PCC framework, OA prevalence or barriers by intersectional factors, and strategies to improve equitable access to OA care. RESULTS: We included 36 OA guidelines published from 2003 to 2021 in 8 regions or countries. Few (39%) development panels included patients. While most (81%) guidelines included at least one PCC domain, guidance was often brief or vague, few addressed exchange information, respond to emotions and manage uncertainty, and none referred to fostering a healing relationship. Few (39%) guidelines acknowledged or described greater prevalence of OA among particular groups; only 3 (8%) noted that socioeconomic status was a barrier to OA care, and only 2 (6%) offered guidance to clinicians on how to improve equitable access to OA care: assess acceptability, availability, accessibility, and affordability of self-management interventions; and employ risk assessment tools to identify patients without means to cope well at home after surgery. CONCLUSIONS: This study revealed that OA guidelines do not support clinicians in caring for diverse persons with OA who face disadvantages due to intersectional factors that influence access to and quality of care. Developers could strengthen OA guidelines by incorporating guidance for PCC and for equity that could be drawn from existing frameworks and tools, and by including diverse persons with OA on guideline development panels. Future research is needed to identify multi-level (patient, clinician, system) strategies that could be implemented via guidelines or in other ways to improve equitable, person-centred OA care. PATIENT OR PUBLIC CONTRIBUTION: This study was informed by a team of researchers, collaborators, and thirteen diverse women with lived experience, who contributed to planning, and data collection, analysis and interpretation by reviewing study materials and providing verbal (during meetings) and written (via email) feedback.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.113
GPT teacher head0.337
Teacher spread0.224 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations8
Published2023
Admission routes2
Has abstractyes

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