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Record W4392260739 · doi:10.1016/j.sopen.2024.02.008

“Doing well”: Intraoperative entrustable professional activity assessments provided limited technical feedback

2024· article· en· W4392260739 on OpenAlex
Riley Brian, Natalie Rodriguez, Connie J. Zhou, Megan Casey, Rosa Mora, Katherine R. Miclau, Vivian E Kwok, Liane S. Feldman, Adnan Alseidi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurgery Open Science · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsFormative assessmentSubspecialtyNarrativeNarrative reviewMedical educationInclusion (mineral)MedicinePsychologyPedagogyFamily medicineSocial psychology

Abstract

fetched live from OpenAlex

Background: Entrustable Professional Activities (EPAs) allow for the assessment of specific, observable, essential tasks in medical education. Since being developed in non-surgical fields, EPA assessments have been implemented in surgery to explore intraoperative entrustment. However, assessment burden is a significant problem for faculty, and it is unknown whether EPA assessments enable formative technical feedback. EPAs' formative utility could inform how surgical programs facilitate technical feedback for trainees. We aimed to assess the extent to which narrative comments provided through the Fellowship Council (FC) EPA assessments contained technical feedback. Methods: The FC previously collected EPA assessments for subspecialty surgical fellows from September 2020 to October 2022. Two raters reviewed assessments' narrative comments for inclusion of each skill area that makes up part of the Objective Structured Assessment of Technical Skills (OSATS). A third rater reconciled discrepant ratings. Results: During the study period, there were 3302 completed EPA assessments, including 1191 fellow self-assessments, 1124 faculty assessments, and 987 assessments without an identified assessor role. We found that assessments' narrative comments related to a median of two of the seven OSATS areas (IQR:1-2). There were no comments relevant to any of the seven OSATS areas in 16.0 % of all assessments. Conclusions: In this review of narrative comments for EPA assessments from the FC, we found that limited technical feedback of the kind included in the OSATS was provided in many assessments. These results suggest benefit to adjusting the EPA form, enhancing faculty development, or continuing additional types of targeted technical assessment intraoperatively. Key message: This analysis of narrative comments from fellowship EPA assessments showed that many assessments included limited technical feedback. To allow for continued technical feedback for fellows, these results highlight the need for further refinements of the EPA assessment form, additional faculty development, or ongoing use of other types of technical assessment.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.424
Teacher spread0.383 · 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