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Record W7067064510

Leading from Behind: An Educational Intervention to Address Faculty and Learner Preparedness for Competence By Design in Psychiatry

2021· article· en· W7067064510 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)PreparednessMental healthSession (web analytics)Liaison psychiatryIntervention (counseling)
DOInot available

Abstract

fetched live from OpenAlex

Bryce Bogie,1– 3 Sarah Payne,4 Sheila Harms,4 Meghan McConnell,5,6 Zainab Samaan4,7,8 1Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada; 2Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada; 3The Royal’s Institute of Mental Health Research, Ottawa, Ontario, Canada; 4Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada; 5Department of Innovation in Medical Education, University of Ottawa, Ottawa, Ontario, Canada; 6Department of Anesthesiology and Pain Medicine, University of Ottawa, Ottawa, Ontario, Canada; 7Department of Health Research Methods, Evidence and Impact (HEI), McMaster University, Hamilton, Ontario, Canada; 8Clinician Investigator Program, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, CanadaCorrespondence: Bryce Bogie Email bryce.bogie@uottawa.caPurpose: Residency training programs across Canada are beginning to implement the Royal College of Physicians and Surgeons of Canada’s new Competence By Design (CBD) framework in medical education. The objective of the current research was to assess faculty members’ and learners’ understanding of, and preparedness for, the national shift to CBD in psychiatry before and after an educational intervention.Methods: The current research implemented a pre-test/post-test design to investigate faculty members’ and learners’ perceptions and attitudes towards competency-based medical education (CBME) and CBD before and after a one-hour educational session delivered by an expert on CBME.Results: Of the 104 session attendees, 83 (79.8%) completed the pre-survey and 80 (76.9%) completed the post-survey. Both groups reported a moderate level of baseline knowledge of CBME and CBD. Knowledge of CBME improved significantly for both faculty members (p = 0.03) and learners (p < 0.01) after the education session; however, only learners showed a significant increase in knowledge of the CBD framework following the education session (p < 0.01). Further, only learners demonstrated a significant increase in perceived preparedness for CBD following the session (p = 0.02).Conclusion: Overall, a brief, one-hour education session was at least somewhat effective at improving knowledge and preparedness for psychiatry’s transition to CBD. In order to facilitate the transition to CBD and to assist in the rollout of future policy changes, psychiatry departments should provide both faculty members and learners with educational sessions and resources prior to the policy implementation.Keywords: competency-based medical education, Competence By Design, faculty development, feedback, implementation, policy change

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)0.008
metaresearch head score (Gemma)0.027
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.227
GPT teacher head0.566
Teacher spread0.339 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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