Development and Validation of the Emotional Self‐Awareness Questionnaire: A Measure of Emotional Intelligence
Bibliographic record
Abstract
This study examined the psychometric characteristics of the Emotional Self-Awareness Questionnaire (ESQ), a self-report measure of emotional intelligence. The ESQ, Emotional Intelligence Scale, and measures of alexithymia, positive negative affect, personality, cognitive ability, life satisfaction, and leadership aspirations were administered to 1,406 undergraduate psychology students. The ESQ was reduced from 118 to 60 items via factor and reliability analyses, retaining 11 subscales and a normal score distribution with a reliability of .92. The ESQ had significant positive correlations with the Emotional Intelligence Test and positive affect, significant negative correlations with alexithymia and negative affect, and an insignificant correlation with cognitive ability. The ESQ accounted for 35% of the variance in life satisfaction over and above the Big Five, cognitive ability, and self-esteem, and demonstrated incremental validity in explaining GPA and leadership aspirations. The significance of emotional intelligence as a unique contributor to psychological well-being and performance, and applications for the ESQ in assessment and outcome research in couple and family therapy are discussed.
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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 | 0.006 | 0.012 |
| 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 | 0.000 | 0.001 |
| 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".