A97 INTERNAL MEDICINE RESIDENT AND STAFF PERCEPTIONS OF GASTROENTEROLOGY ROTATION
Bibliographic record
Abstract
Abstract Background The choice of subspecialty by internal medicine residents is partially influenced by their experience with that service. Challenges exist between internal medicine and the high acuity, procedurally-heavy, gastroenterology (GI) service. Negative perceptions may limit the number of residents rotating through a gastroenterology elective, impacting knowledge and comfort managing common GI conditions. Aims To identify misperceptions of the GI service at a tertiary hospital, and evaluate resident and new staff comfort in managing common GI conditions. Methods Twenty-question survey sent to internal medicine residents during 2022-2023 and 13-question survey sent to staff that completed training from 2020-2022; both anonymous, and using Qualtrics software. Results The survey was completed by 18% (30/166) of residents and 20% (13/65) of staff. Most staff (62%) practiced in a community setting. Both cohorts cited overnight cross-coverage consults during (56%) and negative word-of mouth (38%), as reasons they avoided a GI elective. Most participants reported a little (33%) or moderate (47%) amount of GI teaching on medicine service and were unaware of formal lectures (79%) during a GI rotation. Residents and staff were most comfortable managing pancreatitis (98%) and ALF (74%). Staff wished for more experience managing pancreatic and liver masses and outpatient IBD flares; however both groups (86%) were unaware of the ambulatory week during the GI rotation. Conclusions Misperception and unawareness of a GI elective persist amongst internal medicine residents and has implications for new staff managing GI conditions. This study has led to action items that address these concerns. Table 1: Resident & staff awareness, perceptions & knowledge of GI Funding Agencies None
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".