Fostering Adherence to Evidence-Based Care in the Management of Musculoskeletal Shoulder Pain: A Mixed-Methods Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.085 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".