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Record W4389627266 · doi:10.36834/cmej.77140

The CanMEDS Competency Framework in laboratory medicine: a phenomenographic study exploring how professional roles are applied outside the clinical environment

2023· article· en· W4389627266 on OpenAlexaffvenueabout
Chloe Bogaty, Janneke Frambach

Bibliographic record

VenueCanadian Medical Education Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsHôtel-Dieu de QuébecCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsBlueprintThematic analysisMedical educationAutonomyContext (archaeology)MedicinePsychologyEngineering ethicsQualitative researchEngineeringSociologyPolitical science

Abstract

fetched live from OpenAlex

Background: The CanMEDS Competency Framework is an internationally recognized model used to outline the proficiencies of a physician. It has predominantly been studied in clinical environments but not all medical specialties take part in direct patient contact. In laboratory medicine, the role of the physician is to promote and enhance patient diagnostics by managing and overseeing the functions of a diagnostic laboratory. Methods: This phenomenographic study explores the lived experiences of biochemistry, microbiology, and pathology residency program directors to better understand how they utilize the CanMEDS competencies. Eight laboratory medicine program directors from across Canada were individually interviewed using a semi-structured interview, and the data was analysed using inductive thematic analysis. Results: The findings show that the current framework is disconnected from the unique context of laboratory medicine with some competencies appearing unrelatable using the current standardized definitions and expectations. Nevertheless, participants considered the framework to be an appropriate blueprint of the competencies necessary for their professional environment, but to make it accessible more autonomy is required to adapt the framework to their needs. Conclusion: Newer renditions of the CanMEDS Competency Framework should better consider the realities of non-clinical disciplines.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.083
GPT teacher head0.398
Teacher spread0.316 · 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 teacher head, not a consensus.

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

Citations5
Published2023
Admission routes3
Has abstractyes

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