Simulation Experiences in Canadian Physiotherapy Programmes: A Description of Current Practices
Bibliographic record
Abstract
Purpose: Although health care professional education programmes around the world are increasingly using sophisticated simulation technology, the scope of simulation use in Canadian physiotherapy programmes is currently undefined. The current study explores the definitions of simulation, its current use, and the perceived benefits and barriers in Canadian entry-to-practice physiotherapy programmes. Method: Using a qualitative, descriptive study approach, we contacted Canadian physiotherapy programmes to identify faculty members with simulation experience. Using a semi-structured interview format, we asked participants to discuss their perspectives of simulation in their physiotherapy programmes. Interviews were audio recorded, transcribed, and analyzed for themes. Results: Of 13 eligible Canadian physiotherapy programmes, participants from 8 were interviewed. The interviews revealed three major themes: (1) variability in the definition of fidelity in simulation, (2) variability in simulation use, and (3) the benefits of and barriers to the use of simulation. Conclusions: Variability in the definition of fidelity in simulation among Canadian physiotherapy programmes is consistent with the current literature, highlighting a spectrum of complexity from low fidelity to high fidelity. Physiotherapy programmes are using a variety of simulations, with the aim of creating a bridge from theoretical knowledge to clinical practice. This study describes the starting point for characterizing simulation implementation in Canadian physiotherapy programmes and reflects the diversity that exists across the country.
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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) | 0.000 | 0.000 |
| 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".