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Record W1494373589 · doi:10.36834/cmej.36570

Defining Content for a Competency-based (CanMEDS) Postgraduate Curriculum in Ambulatory Care: A Delphi Study

2012· article· en· W1494373589 on OpenAlexaffvenueabout
René Wong

Bibliographic record

VenueCanadian Medical Education Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCompendiumDelphi methodCurriculumMedical educationSet (abstract data type)MedicineAmbulatoryHealth careInclusion (mineral)DelphiAmbulatory carePsychologyNursingPedagogyComputer sciencePolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Ambulatory training in internal medicine has been noted to be dysfunctional and inadequate. In this study, we developed a set of competency-based outcomes specific to ambulatory care to guide the design, implementation and evaluation of instructional events to ensure that societal needs are addressed. METHODS: In 2007 a Delphi technique was used to reach consensus and define the priorities for competency-based training in ambulatory care for internal medicine residents. Four groups of stakeholders in Canada participated: program directors, members of the Canadian Society of Internal Medicine, recent graduates, and residents. RESULTS: Two rounds of the Delphi process were required to reach consensus on a set of sixty competency-based educational objectives in ambulatory care that were classified under the CanMEDS roles. The inclusion of recent graduates in this study resulted in the addition of non-clinical topics that would have otherwise been missed, falling under roles historically viewed as being challenging to teach and evaluate (Manager, Health Advocate). CONCLUSION: This study is the first time a Delphi-process has been used to define the priorities for ambulatory care training in internal medicine under a competency-based framework. The resulting compendium of competency-based objectives provides a foundation from which educators can design, evaluate and modify existing training experiences.

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)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.335
Teacher spread0.313 · 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

Citations6
Published2012
Admission routes3
Has abstractyes

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