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Record W3208866417 · doi:10.1093/pch/pxab061.095

117 Formal Leadership Teaching in Canadian Pediatric Residency Programs

2021· article· en· W3208866417 on OpenAlexaffabout
David D’Arienzo, Mylène Dandavino

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMontreal Children's Hospital
Fundersnot available
KeywordsMedical educationCurriculumThematic analysisCompetence (human resources)DemographicsGraduate medical educationLeadership developmentEducational leadershipPsychologyMedicineQualitative researchPedagogyAccreditationPolitical science

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Medical Education Background Effective clinical leadership is known to improve clinical outcomes, health service delivery, effective resource allocation, and patient and staff satisfaction rates. Although it is well known that leadership skills can be taught and are necessary for all physicians, there are very few described residency-level structured leadership-training curricula. Yet, pediatric residency programs' Competence-By-Design (CBD) includes 19 stage-specific, leadership-focused Milestones, spanning 10 Entrustable Professional Activities (EPAs) that will need to be assessed. Objectives The purpose of this study was to map how leadership is formally taught in Canadian pediatric residency programs and to explore how leader-specific milestones and EPA are incorporated into programs’ training. Design/Methods Program Directors from all Canadian pediatric residency programs were invited to complete an online, anonymous survey, which was developed using the AMEE Seven-Step Survey Development guidelines. The survey explored demographics, teaching structure, teaching content and methods, assessment, and participants’ perspectives. Descriptive and thematic analyses were performed. Results Ten of the 17 pediatric programs directors responded to the survey. All program directors (n=10), stated that there is a need for mandatory, formal leadership teaching and formal leadership skills assessment for pediatric residents. Yet, half of respondents (n=5) reported no formal leadership teaching and residents' leadership skills are not formally assessed in three (of 10) pediatric residency programs. Additionally, none of the programs offers stage-specific leadership teaching. Of the programs that offer formal leadership teaching, four programs’ teachings are stand-alone courses, while one program has a longitudinal leadership curriculum. Only one program offers formal teachings on leader-related CBD EPAs and/ or Milestones. Seven programs formally assess residents’ leadership skills. Of these, four programs use a formal assessment tool, while three programs do not use any assessment tool. None of the programs utilizes a validated or published leadership skills assessment tool. Thematic analyses revealed that the common barriers to introducing a formal leadership curriculum include limited available time in residents’ teaching curriculum, lack of expertise and resources to teach leadership, and difficulty in assessing leadership skills. Conclusion Although residency programs identify leadership teaching and assessment as necessary, most pediatric residency programs lack formal leadership teaching and assessment. Additionally, no such teaching is stage-specific. Understanding the current state of programs’ leadership teaching will help better prepare programs for the integration of leadership milestones/ EPAs in the curriculum.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.870
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.336
Teacher spread0.293 · 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 routes2
Has abstractyes

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