Changing Morning Report: An Educational Intervention to Address Curricular Needs
Bibliographic record
Abstract
Morning report is a case-based teaching session common to many residency programs with varying purposes and focuses. At our institution, physicians and residents felt our Internal Medicine morning report had lost its educational focus. The purpose of this project was to improve morning report using a well-known curriculum development framework for medical education. We conducted a focus group of residents to develop and implement changes to morning report. Themes from our focus group led us to split morning report with the first 30 minutes for postgraduate year 3 (PGY-3) residents to give handover, to receive feedback on diagnosis and management, and to either discuss an interesting case or receive teaching aimed at their final certification examination. The second 30 minutes involved PGY-3 residents leading PGY-1 residents in case-based discussions with an attending physician providing feedback on the content and process of teaching. We measured success based on a follow-up survey and comments from resident evaluations before and after the change. Overall, the changes were well received by both faculty and residents; however comments revealed that the success of morning report is preceptor dependent. In summary, we have successfully implemented a split morning report model to enhance resident education with positive feedback.
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 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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".