Development and Validation of a New Competency Framework for Athletic Therapy in Canada
Bibliographic record
Abstract
Context Competency-based education (CBE) is entrenched in educating health professionals in Canada. CBE is a framework that identifies desired performance characteristics in training competent, entry-level health professionals. Objective To update, develop, and validate a new Canadian Athletic Therapists Association (CATA) framework for athletic therapy education. Design Framework development occurred in 4 phases and was developed through a multistage process that involved a scoping review (phase 1) and consensus methodology (ie, a blending of modified Ebel and modified Delphi consensus methods; phases 2–4). Patients or Other Participants Phase 2: a total of 7 experts (program directors) from each Canadian accredited institution. Phase 3: a total of 14 experts (1 program director and educational expert from each accredited institution). Phase 4: a total of 7 experts (program directors) and 246 certified members of the CATA. Main Outcome Measure(s) Each phase consisted of a systematic process with 80% consensus agreement set a priori. In phase 1, a scoping review was conducted to identify common terminology that could be used to guide the framework development process and to identify competency frameworks used by other health professional organizations. Phase 2 consisted of adopting a common language that would serve to keep the expert group on the task at hand and avoid confusion. In phase 3, frameworks used by other health professional organizations were evaluated and used to determine the validity of the old CATA framework. In phase 4, the old CATA framework was updated and a new framework was developed and validated. Results In phase 1, the result of the scoping review yielded 368 papers, of which 5 were used to propose a common language for phase 2 and 9 highlighted competency frameworks used by other health professions for comparison in phase 3. In phase 3, the expert group voted unanimously to adopt and adapt the CanMEDS framework (ie, roles). In phase 4, the new CATA competency framework was validated, and most competencies achieved consensus. Competencies that did not achieve consensus in the first round of voting underwent face-to-face discussions via videoconferencing. After discussions, the remaining competencies were revised, and all newly worded competencies achieved consensus. Conclusions The resultant framework was validated, and most competencies achieved consensus. The new athletic therapy competency framework outlines the 165 competencies resulting from this methodical process and will hopefully facilitate interdisciplinary communication and practice.
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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 | 0.149 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".