A cross-sectional evaluation of the Medical Student Symposium at the Canadian Ophthalmological Society Annual Meeting: a quality improvement survey
Bibliographic record
Abstract
Background: Canadian medical school curricula have traditionally been limited in their exposure to ophthalmology. A Medical Student Symposium (MSS) was developed to introduce students to the specialty, teach clinical skills, and help students to seek future opportunities within ophthalmology. Our aim is to provide a model for other specialties to meet the evolving and diverse educational needs of medical trainees. Methods: Medical students were invited to participate in a 3-hour free in-person symposium held at the Canadian Ophthalmological Society (COS) Annual Meeting in June 2023. The symposium was divided into three sections: a 30-minute keynote speaking session, hands-on workshops, and resident mentoring sessions. A cross-sectional quality improvement survey was administered to medical students who attended. Descriptive statistics were used to analyze the survey responses. Results: In total, 70 participants attended the symposium. Of these, 61 participants (87.1%) responded to the survey. The majority of attendees (67.8%) of participants expressed that attending the COS MSS would enhance their applications to ophthalmology residency. With regards to knowledge acquisition, 85.3% and 75.4% of students noted that the MSS improved their didactic and procedural knowledge of ophthalmology, respectively. An overwhelming majority of attendees (95.1%) stated they would recommend the COS MSS to medical students interested in ophthalmology, and 91.6% noted they would attend again. Conclusions: Our study demonstrated that a MSS is a valuable platform to enhance medical students’ exposure and knowledge of the field of ophthalmology. The MSS model can be applied as a novel medical education opportunity to increase exposure to medical specialties and inclusion of junior trainees at national conferences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.079 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".