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Record W4405441448 · doi:10.1093/ptj/pzae176

Fostering Adherence to Evidence-Based Care in the Management of Musculoskeletal Shoulder Pain: A Mixed-Methods Study

2024· article· en· W4405441448 on OpenAlexaff
Christina R. Maxwell, Jon Salsberg, Katie Robinson, F. Desmeules, Véronique Lowry, Christie Tetreault, Karen McCreesh

Bibliographic record

VenuePhysical Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of SaskatchewanUniversité de SherbrookeUniversité de Montréal
FundersIrish Research Council
KeywordsThematic analysisMedicineTimelineLikert scaleStakeholderHealth careFamily medicinePatient educationNursingPsychologyQualitative researchPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective was to identify the priorities of individuals with musculoskeletal shoulder pain and their health care providers (HCPs) that are perceived to foster multistakeholder adherence to evidence-based recommendations. METHODS: The study used a mixed-methods design, informed by concept mapping. Patients with shoulder pain (ie, ≥6 weeks) and HCPs involved in their care (recruited via social media, email, etc) were invited to complete an initial survey to identify perceived priorities to foster adherence to evidence-based recommendations. Preliminary data sorting resulted in a final priority list, with a subset (n = 20) of respondents rating their importance using a Likert scale. A public and patient involvement (PPI) panel (N = 8) assisted in this rating phase, further sorting of priorities based on thematic similarities (ie, into categories and then domains), analysis, interpretation, and developing a concept map illustrating relationships between them. RESULTS: One hundred and fifty-four participants (HCPs = 133; patients = 21) responded to the initial survey, generating 77 priorities, grouped into 13 categories, and then into 3 domains: (1) Education, (2) Patient-centered care, and (3) Health care communication. Patients prioritized categories relating to the provision of a specific diagnosis, the establishment of a strong therapeutic relationship, and the need for education on progress and recovery timelines, as well as treatment options. HCPs prioritized these same educational categories, also prioritizing the need for tailoring exercise therapy and providing a unified message on best management. PPI panelists identified education on treatment options coupled with a strong therapeutic alliance and a unified message on best management to be of pivotal importance in fostering adherence. Panelists also stressed that future knowledge translation resources must provide tailored education. CONCLUSION: HCPs and patients agree on the need to prioritize education related to progress and recovery timelines as well as treatment options, with a strong therapeutic alliance and a unified message on best management also considered of pivotal importance for adherence to evidence-based recommendations. IMPACT: To the knowledge of the authors, this is the first study, including a broad range of stakeholder groups spanning across 11 different countries, to explore the priorities that stakeholders perceived to support stricter adherence to evidence-based recommendations for musculoskeletal shoulder pain, with the relationship between these priorities visually illustrated using a concept map. Patients and HCPs were united in their prioritization of education relating to expected progress and recovery timelines, as well as treatment options and supporting evidence. Stakeholders also identified the need for greater emphasis to be placed on establishing a therapeutic relationship and on integrating shared decision-making into clinical practice to further facilitate adherence. Education relating to treatment options and supporting evidence, a strong therapeutic relationship, and a unified message on best management were perceived by the PPI panel as being pivotal in facilitating adherence to evidence-based treatment. The findings of this study highlight the need for improved tailoring of educational resources for shoulder pain, as well as more cohesive messaging from health care providers, both assisting in supporting first-line treatments, such as exercise therapy, for musculoskeletal shoulder pain.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.118
GPT teacher head0.474
Teacher spread0.356 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations3
Published2024
Admission routes1
Has abstractyes

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