Inclusion of Exercise Prescription in Solid Organ Transplant in Physical Therapy Curricula Across Canadian Universities: A National Survey
Bibliographic record
Abstract
Purpose: This study evaluated the extent of education about exercise prescription for patients with solid organ transplant (SOT) provided in physical therapy (PT) entry-level programmes across Canadian universities. The nature (content being taught), delivery (modes used to disseminate information), time dedicated to the topic, and opinions of educators were explored. Method: A cross-sectional survey was emailed to 36 educators at Canadian universities. The survey questions related to the nature, delivery, and time dedicated to SOT exercise prescription, and the opinions of educators. Results: The response rate was 93%. Educators reported that lung and heart transplantation were taught the most, followed by kidney and liver, with little to no emphasis on pancreas transplants. This material was mainly taught at the graduate level and as part of cardiopulmonary courses with minimal emphasis on practical skills. Aerobic exercise is the main exercise prescription being taught. The main barrier to offering more SOT prescription education experienced by educators was the lack of available class time. Conclusions: SOT exercise prescription is not extensively covered in PT curricula and does not include all organ groups to the same extent. Students have few practical opportunities, which are important to gain the abilities and confidence to treat this population. The development of a continuing education course could promote greater knowledge.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".