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Record W4228996691 · doi:10.1097/acm.0000000000004731

Intrinsic or Invisible? An Audit of CanMEDS Roles in Entrustable Professional Activities

2022· article· en· W4228996691 on OpenAlexaffabout
Andrew B. LoGiudice, Matthew Sibbald, Sandra Monteiro, Jonathan Sherbino, Amy Keuhl, Geoffrey R. Norman, Teresa M. Chan

Bibliographic record

VenueAcademic Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsAuditPsychologyMedical educationMedicineBusinessAccounting

Abstract

fetched live from OpenAlex

PURPOSE: Postgraduate medical education in Canada has quickly transformed to a competency-based model featuring new entrustable professional activities (EPAs) and associated milestones. It remains unclear, however, how these milestones are distributed between the central medical expert role and 6 intrinsic roles of the larger CanMEDS competency framework. A document review was thus conducted to measure how many EPA milestones are classified under each CanMEDS role, focusing on the overall balance between representation of intrinsic roles and that of medical expert. METHOD: Data were extracted from the EPA guides of 40 Canadian specialties in 2021 to measure the percentage of milestones formally linked to each role. Subsequent analyses explored for differences when milestones were separated by stage of postgraduate training, weighted by an EPA's minimum number of observations, or sorted by surgical and medical specialties. RESULTS: Approximately half of all EPA milestones (mean = 48.6%; 95% confidence interval [CI] = 45.9, 51.3) were classified under intrinsic roles overall. However, representation of the health advocate role was consistently low (mean = 2.95%; 95% CI = 2.49, 3.41), and some intrinsic roles-mainly leader, scholar, and professional-were more heavily concentrated in the final stage of postgraduate training. These findings held true under all conditions examined. CONCLUSIONS: The observed distribution of roles in EPA milestones fits with high-level descriptions of CanMEDS in that intrinsic roles are viewed as inextricably linked to medical expertise, implying both are equally important to cultivate through curricula. Yet a fine-grained analysis suggests that a low prevalence or late emphasis of some intrinsic roles may hinder how they are taught or assessed. Future work must explore whether the quantity or timing of milestones shapes the perceived value of each role, and other factors determining the optimal distribution of roles throughout training.

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)0.029
metaresearch head score (Gemma)0.122
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.871

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.122
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.010
Science and technology studies0.0030.003
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.371
Teacher spread0.342 · 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

Citations11
Published2022
Admission routes2
Has abstractyes

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