Does emotional intelligence change during medical school gross anatomy course? Correlations with students’ performance and team cohesion
Bibliographic record
Abstract
Emotional intelligence (EI) has been associated with increased academic achievement, but its impact on medical education is relatively unexplored. This study sought to evaluate change in EI, performance outcomes, and team cohesion within a team-based medical school anatomy course. Forty-two medical students completed a pre-course and post-course Schutte Self-Report Emotional Intelligence Test (SSEIT). Individual EI scores were then compared with composite course performance grade and team cohesion survey results. Mean pre-course EI score was 140.3 out of a possible 160. During the course, mean individual EI scores did not change significantly (P = 0.17) and no correlation between EI scores and academic performance was noted (P = 0.31). In addition, EI did not correlate with team cohesion (P = 0.16). While business has found significant utility for EI in increasing performance and productivity, its role in medical education is still uncertain.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".