Self-reported outcomes from a focus of attention workshop for Canadian physiotherapists
Bibliographic record
Abstract
Research has shown that Canadian physiotherapists’ external focus of attention (EFOA) promotion is low, despite research supporting its benefit for individuals with musculoskeletal dysfunction. In an effort to translate the focus of attention (FOA) knowledge into physiotherapy, an educational workshop was designed and delivered virtually to fifteen Canadian physiotherapists (Mage = 44.5 ± 11.4 years; Mexperience = 18.9 ± 12.7 years). Previous analyses revealed physiotherapists reacted positively to the workshop and significantly improved their knowledge and skill from pre- to post-workshop. The current analyses focus on the self-reported workshop outcomes which utilized a scale ranging from 0 = not at all to 100 = extremely. Comparing pre- to immediately post-workshop, physiotherapists significantly improved their attitudes towards learning and applying FOA content (pre M = 88.25, SD = 11.00; post M = 92.83, SD = 6.59; p = .024, d = 0.56) and self-efficacy in promoting an EFOA (pre M = 59.50, SD = 22.36; post M = 85.72, SD = 7.95, p < .001, r = 0.86). One-week post-workshop, all physiotherapists reported an increase to their EFOA use (M = 79.00, SD = 15.14) and thirteen claimed it improved their clients’ rehabilitation outcomes (M = 68.08, SD = 22.13), which resulted in them reporting a high intention to continue to promote an EFOA in their practice (M = 87.31, SD = 15.09). These results extend the chain of evidence supporting the positive impact of the workshop and serves as an important step in bridging the FOA knowledge-physiotherapy practice gap.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".