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Record W3139827616 · doi:10.4085/1947-380x-20-080

Development and Validation of a New Competency Framework for Athletic Therapy in Canada

2021· article· en· W3139827616 on OpenAlexaffabout
Mark R. Lafave, Jeffrey Michael Owen, Breda Eubank, Richard DeMont

Bibliographic record

VenueAthletic Training Education Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsConcordia UniversityMount Royal University
Fundersnot available
KeywordsContext (archaeology)AccreditationDelphi methodMedical educationCertificationTerminologyPhase (matter)PsychologyMedicinePolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.149
metaresearch head score (Gemma)0.130
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.211
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1490.130
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0150.010
Science and technology studies0.0130.006
Scholarly communication0.0100.004
Open science0.0060.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.049
GPT teacher head0.337
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes2
Has abstractyes

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