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Record W3135563584 · doi:10.1093/jcag/gwab002.093

A95 HOW ENDOSCOPY TEACHERS MAKE POLYPECTOMY ENTRUSTMENT DECISIONS IN CLINICAL AND SIMULATION-BASED SETTINGS

2021· article· en· W3135563584 on OpenAlexaffabout
Thurarshen Jeyalingam, Catharine M. Walsh, Walter Tavares, Maria Mylopoulos, Kathryn Hodwitz, L W Liu

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity Health NetworkSt. Michael's HospitalSickKids FoundationHospital for Sick ChildrenThe Wilson Centre
Fundersnot available
KeywordsPolypectomyMedical educationGrounded theoryNarrativeEndoscopyTask (project management)MedicineConstruct (python library)PsychologyNursingQualitative researchRadiologyInternal medicineComputer scienceColonoscopy

Abstract

fetched live from OpenAlex

Abstract Background Entrustment, a central construct in competency-based medical education (CBME), represents the point at which clinical supervisors trust a trainee to perform a task independently. Many implementations of CBME involve assessing entrustment through observation of entrustable professional activities (EPAs). While EPAs are frequently assessed in both clinical and simulation-based settings, research has yet to clarify how faculty who teach endoscopy form judgments of entrustment across these two contexts. Aims We aimed to explore the features that endoscopy teachers report as influencing their entrustment decisions regarding polypectomy across clinical and simulation-based assessment settings. Methods We designed an interview-based, constructivist grounded theory-informed study involving endoscopy teachers and trainees in the University of Toronto gastroenterology residency program. Teachers completed separate EPA assessments of each trainee’s performance of an endoscopic polypectomy (colonic polyps < 1cm, Paris 0-Is or 0-Ip in morphology) in both settings. Teachers were interviewed after each assessment to explore how they made their entrustment decision within and across settings. Transcribed interview data were coded iteratively using constant comparison to generate themes. Results Based on 14 interviews with 7 endoscopy teachers, we found that they: (1) held multiple meanings of entrustment for polypectomy, both within and across participants, (2) expressed variability in how they justified their entrustment decisions, the related narrative, and numerical scoring, (3) held unique personal criteria for making decisions ‘comfortably,’ including authenticity of the task, variability in terms of polyp shape, location, and morphology, as well as the ability to assess trainee response to procedural complications (e.g., post-polypectomy bleeding), and (4) perceived a relative freedom when using simulation to make entrustment decisions due to the absence of a real patient. Conclusions We found that faculty who teach endoscopy defined polypectomy entrustment in a variety of ways, leading to variability in how they judged entrustment within and across trainees and assessment settings. The observed idiosyncrasies suggest gastroenterology competence committees cannot assume equivalence of EPA data obtained from different settings. Furthermore, educators designing faculty development for CBME will need to attend to the criteria that endoscopy teachers report they need to comfortably make entrustment decisions. Funding Agencies Royal College of Physicians and Surgeons of Canada

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)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.014
GPT teacher head0.318
Teacher spread0.303 · 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 designQualitative
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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