Medical Students' Perceptions of Emergency Medicine Careers
Bibliographic record
Abstract
Introduction Previous studies on specialty choice have investigated specialty characteristics that are appealing to undergraduate students. Little is known about how students' attitudes towards Emergency Medicine (EM) careers evolve over their schooling. Methods An open-ended survey of medical students' career interests was distributed five times over the four-year undergraduate curriculum from 1999 to 2008 at Memorial University. We tested specialty choices across genders, and looked at how likely a student's choice in their first year influenced their final year choice, a metric we termed "endurance". The qualitative data was coded to identify key themes and sentinel quotes. Lastly, we conducted semi-structured interviews with academic emergency physicians at Dalhousie University to assess the relevance of these findings to postgraduate training. Results Males expressed more interest in EM than females. EM had more endurance than internal medicine, but less than family medicine, over the four-year curriculum. The biggest drawbacks for EM included lack of patient follow-up and lack of EM experience; positive perspectives focused on clinical variety and elective experiences. Lifestyle was prominent, seen as both positive and negative. Emergency physicians considered EM lifestyle attractive, and characterized medical students' perceptions as "skewed," highlighting lack of insight into system flaws. Conclusions Medical students' opinions towards EM tended to shift over time, particularly the perception of the work. Medical students' perceptions differ from that of experienced emergency physicians. Medical schools may be able to improve clinical exposure and provide more informed counselling or mentoring with respect to EM.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".