Voices from the clinic: a qualitative analysis of physiotherapy strategies in musculoskeletal care for knee osteoarthritis patients
Bibliographic record
Abstract
BACKGROUND: Physiotherapy has emerged as an important health strategy to deliver lifestyle, exercise and physical activity for people with knee osteoarthritis. However, little is known about the extent to which physiotherapists adhere to clinical practice guidelines. This study aimed to explore the perspectives and care patterns of physiotherapists in Sydney, Australia on their delivery of knee osteoarthritis care and how this aligns with the 2019 Osteoarthritis Research Society International (OARSI) guidelines. METHODS: We invited thirty-three physiotherapists from nine private practices in metropolitan Sydney to partake in a semi-structured interview. The interviews were digitally recorded and transcribed verbatim. The data collected were analysed deductively using content analysis, comparing guidelines to current care patterns, while their perspectives were inductively analysed through thematic analysis. RESULTS: Thirty physiotherapists participated (age range 22-63 years, 17 male and 13 female). Interview responses indicated that most physiotherapists were satisfied with their care of knee osteoarthritis patients. Most physiotherapists delivered "core" guideline-based care of education and land-based exercise. Recommendations of modalities of exercise, including hydrotherapy and manual therapy, were discussed and were perceived to be beneficial despite not being "core" clinical guideline recommendations. Current treatment strategies focussed on disease severity, symptom presentation and/or patient exercise history with little emphasis on education about osteoarthritis pathophysiology and drug-based pain relief. The thematic analysis identified two over-arching themes; (1) capacity to deliver and awareness of evidence-based care and (2) perceived recommendations for future physiotherapy management. Participants identified notable areas of potential service improvement including developing stronger and more effective reimbursement models, increased consult times and improved patient access. CONCLUSION: The study provided unique insights towards physiotherapists' current usual knee osteoarthritis care and their perceived barriers to delivering guideline-based care. Thus, informing a need for future studies to focus on developing specific and detailed guidelines if physiotherapists are to align more closely to the core guideline-based recommendations. TRIAL REGISTRATION: This study was part of a larger study, with the full protocol published and registered at ClinicalTrials (ACTRN12620000188932, ACTRN12620000218998) 19/02/2020).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".