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Record W2789771711 · doi:10.1093/jcag/gwy008.062

A61 AN ASSESSMENT OF THE EDUCATIONAL EXPERIENCE OF MEDICAL STUDENTS AND RESIDENTS AFTER THEIR GASTROENTEROLOGY AND HEPATOLOGY ROTATIONS

2018· article· en· W2789771711 on OpenAlexaffabout
Noor Jawaid, Zane Gallinger, Kyle J. Fortinsky

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHepatologyMedicineLikert scaleInternal medicineDemographicsFamily medicineMedical educationGastroenterologyPsychology

Abstract

fetched live from OpenAlex

Trainee educational experience on gastroenterology (GI) and hepatology rotations can vary between hospitals. Routine practice in GI takes place predominantly in an ambulatory setting, while core rotations are known to expose trainees to mainly inpatient medicine in the form of a consult service. As a result, obtaining knowledge across a wide variety of gastrointestinal disorders during a 1 month rotation may not be feasible. To assess the education experience of medical students and residents after their gastroenterology and hepatology rotation in order to identify key topics which may not be adequately covered. A web-based survey was sent to 130 medical students and residents who completed a rotation in GI and hepatology within the University of Toronto hospital network. The survey included demographics and questions regarding frequency of teaching, quality of teaching, and breadth of topics covered during their rotation. There were additional questions pertaining to the utility of novel resources as a learning supplement. Data was analyzed using descriptive statistics. The survey response rate was 50% (65/130) with medical students accounting for 29% while residents (PGY 1–3) accounted for 71% of the respondents. Most (72%) do not plan on pursuing a career in GI and had completed only 1 rotation. The vast majority (98%) reported spending 75% or more of their rotation managing inpatients rather than outpatients. Most learners (79%) felt their learning experience could have been improved, as the overall educational experience was rated a 5 on a 10-point likert scale. Many (80%) felt the amount of teaching differed significantly between the staff on service, and only 23% reported receiving daily formal teaching. The most pronounced deficits in clinical exposure and formal teaching topics included viral hepatitis, irritable bowel syndrome, gastrointestinal malignancies, and pregnancy-related gastrointestinal disorders. Only 49% of respondents received resources to supplement their learning. The vast majority (91%) agreed that receiving a daily question-and-answer resource spanning a variety of topics could improve their learning during the rotation. Current rotations are not addressing many core topics within gastroenterology and hepatology. There is wide variation in teaching between different hospital sites and staff. Most learners are not reporting high levels of satisfaction with their rotations, which can be partly explained by the lack of clinical exposure or teaching around common gastrointestinal disorders. Additional resources are not routinely being provided leading to significant gaps in knowledge. This study lends support towards creating a novel question-and-answer based resource to supplement learning and ensure core topics are being addressed during each rotation. None

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.355
Teacher spread0.344 · 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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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