The emotional intelligence of pediatric residents – a descriptive cross-sectional study
Bibliographic record
Abstract
Background: Emotional Intelligence (EI) is a type of social intelligence. Excellent scores are achieved by displaying high levels of empathy in interpersonal relationships, strong skills in managing stressful situations as well as other personal competencies. Many of the social competencies that EI describes may have a direct impact on patient care. The objective of this study was to describe EI of pediatric residents and to identify if there are EI skills that should be selected for targeted intervention.Methods: This was a cross-sectional study administering the EQ-i 2.0© psychometric instrument to pediatric residents at the University of Alberta.Results: Thirty-five residents completed the EQ-i 2.0© (100% response rate). Their overall EI score was not significantly different than a normative group of college-educated professionals. Residents had relative strengths in the subcategories of Emotional expression, Interpersonal Relationships, Empathy, and Impulse Control (all p<0.05). Areas of relative weakness were in the subcategories of Stress Tolerance, Assertiveness, Independence, and Problem Solving (all p<0.05). Conclusion: The EI of pediatric residents is consistent with that of other professionals. Educational interventions may be useful in the areas of weakness to enhance the physician-patient relationship.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".