Early Clinical Exposure to Geriatric Medicine in Second‐Year Medical School Students—The McGill Experience
Bibliographic record
Abstract
This study examined the effect of a curriculum change on early clinical exposure to geriatrics for second-year medical students at McGill University and its effects on learning and students' appreciation of geriatrics as a subspecialty. Second-year medical students (N = 200) were exposed to a change in the curriculum involving the integration of 10 weekly sessions into one integrated week in geriatric medicine. Students participating in 10 weekly sessions were Group 1 and students participating in one integrated week were Group 2. Students rated their rotation using two different scales. The students completed 12-item questionnaires during their feedback sessions at the end of the 10-week session experience or the integrated week. The first six items assessed the students' appreciation of their improvement of knowledge in the subject of geriatrics and aging. The second and third part of the survey (questions 7 and 8) included the students' opinions about the quality of the instruction (teaching feedback) and evaluation. Students in Group 2 found their rotation more effective as a learning experience and expressed greater satisfaction with interaction with the tutors, community settings, and multidisciplinary team sessions. Grades obtained on final examinations showed a better and more-effective acquisition of knowledge by Group 2. The integrated week is a more-effective learning tool in the early clinical experience for medical students in geriatric medicine than 10 weekly sessions as the first introductory experience to the field of geriatric medicine.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".