A single group follow-up study of non-surgical patients seen by physiotherapists working in expanded roles in orthopaedic departments: recall of recommendations, change in exercise and self-efficacy
Bibliographic record
Abstract
BACKGROUND: Specially trained physiotherapists (advanced practice physiotherapists (APP)) are working in orthopaedic clinics to improve access to orthopaedic services and support chronic disease management. Little attention has been paid to the impact APPs may have on non-surgical patients. In non-surgical patients with hip or knee arthritis consulting an APP in an orthopaedic clinic, the objectives were to: 1) describe patients' recall of APP recommendations, use of self-management strategies, and barriers to management six weeks following consultation; and, 2) compare exercise behaviour and self-efficacy at baseline and six weeks. FINDINGS: This was a single group pre-and post-intervention study of patients who saw an APP when consulting the orthopaedic departments of two hospitals. At baseline and six weeks participants completed the adapted Stanford Exercise Behaviour Scale (response options: none, < 60 minutes/week, 1-3 hours/week or > 3 hours/week), and the Chronic Disease Self-efficacy Scale (range 1-10; higher scores indicate higher self-efficacy). At follow-up participants completed questions on recall of APP recommendations, use of self-management strategies and barriers to management. Seventy three non-surgical patients with hip or knee arthritis participated, a response rate of 89% at follow-up. Seventy one percent of patients reported that the APP recommended exercise, of whom 83% reported exercising to manage their arthritis since the visit. Almost 50% reported an increase in time spent stretching; over 40% reported an increase in time spent walking or doing strengthening exercises at follow-up. Common barriers to arthritis management were time, cost and other health problems. Mean chronic disease self-efficacy scores significantly improved from 6.3 to 7.2 (p < 0.001). The mean difference was 0.95 (95% CI 0.43, 1.62); the effect size was 0.51. CONCLUSIONS: This pilot study of an APP intervention for non-surgical patients referred for orthopaedic consultation showed promising results, particularly for enhancing use of conservative management strategies such as exercise.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".