A pain science education and walking program to increase physical activity in people with symptomatic knee osteoarthritis: a feasibility study
Bibliographic record
Abstract
Abstract: Introduction: Nine of 10 people with knee osteoarthritis are inactive. Unhelpful pain beliefs may negatively influence physical activity levels. Targeting these unhelpful pain beliefs, through contemporary pain science education (PSE), may provide benefit. Objectives: To evaluate the feasibility of conducting a clinical trial to determine the effect of adding PSE (vs adding sham ultrasound) to an individualised, physiotherapist-led education and walking program in people with painful knee osteoarthritis. Methods: Twenty participants were randomised (1:1) into the PSE group or Control group, each receiving 4 in-person weekly treatments, then 4 weeks of at-home activities (weekly telephone check-in). Clinical outcomes and physical activity (7 days of wrist-worn accelerometry) were assessed at baseline, 4 (clinical outcomes only), 8, and 26 weeks. A priori feasibility criteria for recruitment, intervention adherence, viability of wrist-based accelerometry, and follow-up retention were set. Perceived intervention credibility, acceptability, and usefulness from participants and clinicians were assessed (ratings, written/verbal feedback). Results: Most feasibility criteria were met. On average, 7 adults/wk were eligible, with 70% recruited. Treatment compliance was high (in-person: 80% PSE; 100% Control; at-home: 78% PSE; 75% Control). Wrist-based accelerometry had >75% valid wear-time. Sufficient follow-up rates were not achieved (26 weeks: 65%). Participant and clinician feedback highlighted that PSE was too complex and did not match patient expectations of “physiotherapy”, that sham ultrasound was problematic (clinician), but that both treatments had high credibility, acceptability, and usefulness. Conclusions: Progression to a full trial is warranted. Strategies to increase participant retention, refine the PSE content/delivery, and replace/remove the sham intervention are required.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".