Survey of Medical Student Empathy at a Canadian Medical School: A Cross-Sectional Quantitative Survey
Why this work is in the frame
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Bibliographic record
Abstract
Introduction: Within a medical context, empathy is defined as "an appropriate understanding and communication of a patient's experience." While it has been established that empathy is an important quality to have as a doctor, studies have shown that empathy in medical students declines during their clinical years. However, there are no studies to date that evaluate medical student empathy in Canada. Therefore, we aimed to evaluate medical student empathy at McGill University Medical School using the Jefferson Scale of Empathy (JSE). Methods: We used a cross-sectional study design and invited medical students across all 4 years, in October 2019, to complete the JSE. The JSE is a validated psychometric tool that measures empathy at one point in time. The survey was distributed via email and on social media. Results: A total of 133 students from all 4 years responded, proportionate across each year; 119 responses were included in analysis. Differences in mean questionnaire were not statistically significant for gender, age or specialty interest. The analysis of variance for differences in year of medical school was significant (P=.0104). Between groups analysis revealed a statistically significant decrease between Med-2 empathy scores (average score 117.6) and Med-3 (107.5), P<.01. Multivariable analysis demonstrated the decrease in empathy remained statistically significant (P<.05). Discussion: Our statistical analysis determined that medical students’ empathy declines between the second and third year of medical school in a Canadian context, consistent with global results. This information can help target changes in the medical curriculum to preserve empathy in students, and prevent this decline, which could then be applied to other medical schools internationally.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 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 it