To Be or Not to Be a Cardiorespiratory Physiotherapist: Factors That Influence Career Choice in a Sample of Canadian Physiotherapists
Bibliographic record
Abstract
Purpose: This study explored the factors that influence choosing or not choosing a career in cardiorespiratory physiotherapy (CRP) from the perspective of a group of currently practising, experienced physiotherapists in Canada. Methods: A modified Dillman approach was used to distribute a cross-sectional, self-administered, online questionnaire to all eligible members of the cardiorespiratory and orthopaedic divisions of the Canadian Physiotherapy Association. A total of 438 participants—21 CRP and 417 non-CRP therapists—completed the survey. The survey response rate was 9.4%. Results: A narrow scope of practice (61.9%) and a lack of interest in CRP subject matter (50.1%) were the most influential factors deterring the respondents from making CRP their career choice. Interest in CRP (81.0%), mentorship (76.2%), access to physical resources (76.2%), and inter-professional practice (71.4%) were the most influential factors in pursuing a career in CRP. Conclusion: Increasing the awareness of the scope of practice for CRP, exposure to positive mentors, and rich practice settings are key factors in promoting physiotherapists' specialisation in CRP.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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".