Student Perceptions of the Ophthalmology Curriculum in Medical School
Bibliographic record
Abstract
Purpose There is no national standard for ophthalmology curricula in U.S. and Canadian medical schools. We aim to evaluate medical students' perceptions of the current ophthalmology curriculum without mandatory rotation at New York University School of Medicine (NYUSOM). Design A cross-sectional Internet survey. Methods A cross-sectional Internet survey was distributed to all NYUSOM students in March to May 2017. The main parameters measured in the study were students' self-reported confidence with ophthalmology skills and satisfaction with curriculum. Results Response rate was 27.5% (166 of 604) of NYUSOM students. Many students reported they were not comfortable diagnosing eye emergencies (64%), using a direct ophthalmoscope (71%), or testing visual acuity (50%). The majority of students did not want ophthalmology to become a mandatory rotation, but reported additional in-person training would be most helpful, compared with videos, web-based didactics, lectures, or virtual training. Completion of an ophthalmology elective and more hours of ophthalmology training were associated with increased confidence with eye examination and greater satisfaction with the curriculum. Conclusions It is critical for all physicians-in-training to have adequate skills in eye examination. Identifying areas of improvement and determining the best teaching modality will be important in updating the ophthalmology curriculum for medical students. The majority of medical students are not at all or only slightly confident with eye examinations. Increasing the amount of in-person ophthalmology training in medical school improves confidence with eye examination.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".