Brief Emotional Intelligence Scale- 10 (BEIS-10)

1. Abstract

The Brief Emotional Intelligence Scale-10 (BEIS-10) is an abbreviated, psychometrically validated self-report instrument engineered to assess trait emotional intelligence across five distinct, conceptually grounded dimensions. Developed by Davies, Lane, Devonport, and Scott (2010), the measure represents an empirical refinement and reduction of the 33-item Schutte Self-Report Emotional Intelligence Test (SSEIT; Schutte et al., 1998), which itself was mapped onto the foundational theoretical framework of emotional intelligence originally conceptualized by Peter Salovey and John D. Mayer (1990). The BEIS-10 comprises exactly 10 items organized symmetrically into five primary subscales (two items per dimension): Appraisal of own emotions, Appraisal of others’ emotions, Regulation of own emotions, Regulation of others’ emotions, and Utilization of emotions. Participants rate each item on a 5-point Likert scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”).

Extensive psychometric investigations utilizing exploratory and confirmatory factor analysis demonstrate that the hypothesized five-factor oblique structure exhibits superior fit compared to unidimensional or alternative multi-factor formulations. Despite the brevity of its two-item subscales, the instrument demonstrates robust psychometric properties, including satisfactory inter-item correlations, adequate composite reliability, invariant measurement properties across demographic cohorts, and substantial convergent validity when evaluated alongside established emotional intelligence batteries, positive affectivity, resilient coping, and adaptive performance metrics. Because it circumvents the administrative burden and participant fatigue inherent to lengthy psychometric inventories, the BEIS-10 has attained widespread utility in sports psychology, occupational testing, health psychology, and high-stakes field environments where rapid, ecologically valid assessments of emotional competencies are paramount.

2. Keywords

Brief Emotional Intelligence Scale-10, BEIS-10, emotional intelligence, trait emotional intelligence, emotion regulation, emotion appraisal, emotion utilization, psychometrics, confirmatory factor analysis, scale validation.

3. Authors

The Brief Emotional Intelligence Scale-10 was conceptualized, constructed, and empirically validated by an interdisciplinary research team specializing in sport psychology, emotion research, and behavioral measurement:

• Katharine A. Davies — School of Sport, Performing Arts and Leisure, University of Wolverhampton, Walsall, West Midlands, United Kingdom.
• Andrew M. Lane — Professor of Sport Psychology, Research Centre for Sport, Exercise and Performance, University of Wolverhampton, Gorway Road, Walsall, WS1 3BD, United Kingdom. Corresponding author email: [email protected].
• Tracey J. Devonport — Reader in Sport and Exercise Psychology, Faculty of Education, Health and Wellbeing, University of Wolverhampton, United Kingdom.
• Jennifer A. Scott — Department of Sport and Physical Activity, University of Wolverhampton, United Kingdom.

4. Purpose

The primary purpose of the Brief Emotional Intelligence Scale-10 (BEIS-10) is to provide behavioral scientists, clinical practitioners, applied sports psychologists, and organizational researchers with a concise, theoretically coherent, and psychometrically sound assessment of self-perceived emotional intelligence. For decades, the psychometric operationalization of emotional intelligence has been bifurcated into ability-based maximum performance paradigms (e.g., Mayer-Salovey-Caruso Emotional Intelligence Test; MSCEIT) and self-report trait-based paradigms (e.g., Trait Emotional Intelligence Questionnaire; TEIQue; Bar-On Emotional Quotient Inventory; EQ-i). While comprehensive inventories provide granular behavioral diagnostic profiles, their substantial length (often exceeding 130 to 150 items) introduces severe practical liabilities, including survey attrition, cognitive fatigue, satisficing response behavior, and substantial administrative overhead.

Although briefer alternatives like the 33-item Schutte Self-Report Emotional Intelligence Test (SSEIT) offered a more practical footprint, structural validation investigations repeatedly revealed persistent psychometric anomalies within the 33-item inventory. Different factor analyses of the SSEIT extracted anywhere from one to six disparate dimensions, and several items exhibited unacceptable cross-loadings, weak factor determinacy, or unstable factor configurations across diverse respondent samples. Davies, Lane, Devonport, and Scott (2010) resolved this theoretical and methodological impasse by systematically reducing the item pool to its psychometrically purest core, retaining precisely two high-loading, conceptually unambiguous marker items for each of the five theoretical domains posited by Salovey and Mayer’s (1990) seminal architecture.

In applied settings, the BEIS-10 is widely utilized across multiple domains:

• Sports and Human Performance Psychology: Athletic performance environments involve rapid fluctuations in acute emotional states (e.g., pre-competitive anxiety, anger, dejection, euphoria). Practitioners utilize the BEIS-10 to evaluate how athletes appraise competitive arousal, regulate dysfunctional emotional states under psychological stress, and harness positive emotional energy (utilization) to sustain task-focused attention and physical stamina.
• Occupational and Organizational Research: In corporate organizational behavior, the BEIS-10 serves as an efficient diagnostic screener to evaluate emotional labor, transformational leadership capacities, occupational burnout, and interpersonal teamwork dynamics. Its minimal administrative footprint renders it ideal for multi-wave diary studies, longitudinal experience-sampling methods (ESM), and large-scale organizational climate surveys.
• Clinical and Counseling Assessment: Clinicians deploy the BEIS-10 as a preliminary screening mechanism to identify deficits in emotional clarity or emotional regulation strategies, frequently observed in depressive disorders, generalized anxiety, borderline personality traits, and alexithymia.
• Large-Scale Epidemiological Surveys: When psychological batteries require the concurrent administration of multiple psychometric constructs (e.g., personality inventories, cognitive tests, quality-of-life scales), the 10-item composition of the BEIS-10 minimizes participant burden while maintaining psychometric fidelity.

5. Psychological Construct

The construct assessed by the BEIS-10 is multidimensional trait emotional intelligence, defined as a constellation of self-perceptions, behavioral dispositions, and self-reported competencies concerning the recognition, expression, regulation, and functional utilization of emotional information in oneself and others. Rooted in the pioneering operationalization articulated by Salovey and Mayer (1990), the BEIS-10 divides emotional functioning into five distinct psychological dimensions:

1. Appraisal of Own Emotions

This subscale assesses an individual’s subjective capacity to identify, label, and comprehend their internal emotional states as they unfold in real time. It reflects emotional granularity and emotional awareness. Individuals scoring high on this dimension display high interoceptive awareness and metacognitive clarity regarding affective shifts. They understand not merely what they feel, but why their mood has altered. Conversely, low scorers manifest varying degrees of subclinical alexithymia, experiencing affective states as diffuse, confusing physiological sensations without clear cognitive labels.

2. Appraisal of Others’ Emotions

This dimension operationalizes affective perception and nonverbal decodification within interpersonal interactions. It reflects an individual’s sensitivity to the subtle nonverbal cues displayed by social counterparts, specifically prosodic vocal markers (e.g., pitch, cadence, tonal inflection) and morphological facial expressions. Conceptually aligned with cognitive empathy and social perception, this dimension enables individuals to accurately interpret social dynamics, detect hidden emotional distress in others, and anticipate interpersonal friction before it escalates into overt conflict.

3. Regulation of Own Emotions

Emotion self-regulation represents the strategic deployment of psychological operations aimed at modulating the trajectory, duration, magnitude, and expressive qualities of personal affective responses. High scorers intentionally enact proactive coping mechanisms—such as cognitive reappraisal, behavioral activation, and the deliberate pursuit of hedonic and eudaimonic activities—to attenuate debilitating negative mood states (such as acute frustration, despair, or panic) while maintaining an optimal emotional equilibrium under conditions of adversity.

4. Regulation of Others’ Emotions

Distinct from personal emotion management, this subscale reflects interpersonal emotion regulation (often termed social management or socio-affective regulation). It evaluates an individual’s capacity and disposition to alter the affective trajectories of other individuals within their immediate environment. This competence includes behavioral interventions designed to elevate another person’s valence when they are experiencing distress (e.g., providing emotional support, reassurance, or humor) and orchestrating pro-social collective environments that foster positive emotional contagion and group cohesion.

5. Utilization of Emotions

The utilization dimension measures the functional integration of emotional experiences with cognitive processes, creative problem-solving, and goal-directed behavioral perseverance. Drawing heavily upon Barbara Fredrickson’s broaden-and-build theory of positive emotions, this subscale reflects an individual’s capacity to channel positive affective states into divergence in cognitive ideation, resilience, and persistent behavioral effort when encountering systemic barriers or physical exhaustion.

6. Theoretical Framework

The conceptual architecture of the BEIS-10 is deeply rooted in the historical evolution of emotional intelligence theory over the past four decades. The scale reflects the structural synthesis of two major paradigms: the original cognitive-affective ability framework proposed by Salovey and Mayer (1990) and the psychometric trait-based self-report operationalization subsequently pioneered by Schutte and colleagues (1998).

The Salovey and Mayer (1990) Foundational Model

In their seminal 1990 treatise, Peter Salovey and John D. Mayer proposed the first formal psychological model of emotional intelligence, delineating it as a subset of social intelligence that involves the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them, and to use this information to guide one’s thinking and actions. In this original framework, emotional intelligence was structurally partitioned into three overarching mental processes:

1. Appraisal and Expression of Emotion: Divided across the self (verbal and non-verbal perception) and others (non-verbal perception and empathy).
2. Regulation of Emotion: Divided into the regulation of emotion in the self and the regulation of emotion in others.
3. Utilization of Emotion: Divided into flexible planning, creative thinking, redirected attention, and motivating performance.

Although Mayer and Salovey later refined their conceptualization in 1997 into a four-branch developmental ability model (Perceiving, Facilitating, Understanding, and Managing emotions; Mayer & Salovey, 1997) that favored performance-based maximal testing, the tripartite 1990 model remained the structural blueprint for self-report instrumentation.

Schutte et al. (1998) and the Emergence of the SSEIT

To measure the 1990 Salovey-Mayer construct via self-report, Schutte et al. (1998) compiled an initial pool of 62 items, which was psychometrically refined into the 33-item Schutte Self-Report Emotional Intelligence Test. While Schutte et al. originally posited that the 33 items could be collapsed into a single overarching global EI score, numerous independent psychometric evaluations demonstrated that a unidimensional solution failed to meet contemporary standards of structural fit. Successive factor-analytic studies (e.g., Petrides & Furnham, 2000; Ciarrochi et al., 2001; Saklofske et al., 2003) revealed that the 33 items empirically coalesced into multiple distinct factors, reflecting the multi-branch structure originally posited by Salovey and Mayer.

The Rational and Empirical Synthesis: Davies et al. (2010)

Davies, Lane, Devonport, and Scott (2010) addressed the factor-instability and item redundancy of the SSEIT by conducting rigorous structural equation modeling and confirmatory factor analyses. They recognized that while the theoretical integrity of the five primary dimensions (Appraisal of Own, Appraisal of Others, Regulation of Own, Regulation of Others, and Utilization) was robust, the 33-item instrument contained items with significant residual covariances, complex cross-loadings, and ambiguous conceptual referents. By systematically isolating the two most representative, pure, and psychometrically invariant items per dimension, Davies et al. constructed a 10-item scale that perfectly mapped onto the five-factor theoretical model while minimizing measurement error. This brief architecture aligns cleanly with modern trait emotional intelligence theory (Petrides et al., 2007), which conceptualizes self-reported emotional capabilities as personality traits situated within lower levels of established personality hierarchies.

7. Validity

The construct, convergent, discriminant, and predictive validity of the BEIS-10 have been extensively substantiated across diverse international populations, academic environments, clinical cohorts, and athletic disciplines.

Construct and Factorial Validity

In the original validation studies conducted by Davies et al. (2010), confirmatory factor analysis supported the five-factor oblique structure over alternative configurations. In a heterogeneous sample of athletes and university students, the five-factor model produced fit indices demonstrating structural adequacy:

• Comparative Fit Index (CFI) > 0.95
• Tucker-Lewis Index (TLI) > 0.93
• Root Mean Square Error of Approximation (RMSEA) < 0.05
• Standardized Root Mean Square Residual (SRMR) < 0.04

Competing models, including a unidimensional global EI model and a hierarchical second-order model, demonstrated markedly poorer empirical fit, confirming that the five dimensions capture distinct behavioral and psychological processes that cannot be collapsed without sacrificing construct clarity.

Convergent Validity

Convergent validity has been established by correlating BEIS-10 subscales with longer validated emotional intelligence measures, psychological resilience scales, and subjective well-being indices:

• Longer Emotional Intelligence Scales: Strong, statistically significant correlations (ranging from r = 0.62 to r = 0.84) are observed between the BEIS-10 subscale scores and their corresponding parent dimensions on the full 33-item SSEIT (Schutte et al., 1998) and the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF; Petrides & Furnham, 2006).
• Affective States and Psychological Well-Being: The Regulation of Own Emotions and Utilization of Emotions subscales exhibit robust positive correlations with positive affect (as assessed by the PANAS; r = 0.41 to 0.52, p < 0.001) and subjective happiness (Subjective Happiness Scale; Lyubomirsky & Lepper, 1999), while showing significant inverse correlations with negative affect (r = -0.38, p < 0.01) and perceived stress.
• Empathy and Social Functioning: The Appraisal of Others’ Emotions and Regulation of Others’ Emotions subscales correlate positively with the Interpersonal Reactivity Index (IRI; Davis, 1983) subscales of Empathic Concern (r = 0.46) and Perspective Taking (r = 0.49).

Discriminant and Criterion Validity

Discriminant validity has been demonstrated by showing that the BEIS-10 accounts for unique variance in behavioral outcomes beyond that accounted for by the Big Five personality traits (Neuroticism, Extraversion, Openness, Agreeableness, Conscientiousness). In multiple hierarchical regression analyses, BEIS-10 subscales accounted for significant incremental variance in performance under acute competitive stress, academic self-efficacy, and team cohesion after controlling for Big Five variance. Furthermore, discriminant validity from general cognitive ability (IQ) is well documented; correlations between BEIS-10 dimensions and fluid intelligence matrices typically hover near zero (r = -0.05 to 0.12, non-significant), reinforcing the independence of trait emotional self-efficacy from cognitive aptitude.

8. Reliability

The evaluation of internal consistency and temporal stability for brief scales presents unique psychometric considerations. Because Cronbach’s alpha is mathematically sensitive to the total number of items within a scale, two-item subscales frequently display artificially attenuated alpha coefficients even when the underlying inter-item correlations are high.

Internal Consistency Metrics

In the original normative sample analyzed by Davies et al. (2010), the internal consistency indices (Cronbach’s α) for the five two-item subscales demonstrated satisfactory reliability for micro-scales:

• Appraisal of Own Emotions: α = 0.73; Inter-item correlation r = 0.58
• Appraisal of Others’ Emotions: α = 0.71; Inter-item correlation r = 0.55
• Regulation of Own Emotions: α = 0.68; Inter-item correlation r = 0.52
• Regulation of Others’ Emotions: α = 0.69; Inter-item correlation r = 0.53
• Utilization of Emotions: α = 0.66; Inter-item correlation r = 0.49

Contemporary psychometric standards (e.g., Clark & Watson, 1995; Eisinga, te Grotenhuis, & Pelzer, 2013) recommend that for two-item instruments, the mean inter-item correlation and the Spearman-Brown prophecy coefficient provide more accurate estimates of reliability than Cronbach’s alpha. Across subsequent independent replications (e.g., Lane et al., 2011; Vaughan et al., 2019), all inter-item correlations for the BEIS-10 fell comfortably within the recommended optimal range of 0.40 to 0.65, demonstrating high internal consistency without item redundancy. Composite reliability (ρ_c) calculated via structural equation modeling typically yields values exceeding 0.70 across all five latent factors.

Test-Retest Stability

Temporal stability assessments have demonstrated strong test-retest reliability across diverse intervals. Davies et al. (2010) reported a two-week test-retest correlation coefficient ranging from r = 0.76 to r = 0.85 across the five subscales in a stable student cohort. Longitudinal assessments administered across six-month intervals in athletic tracking programs have revealed stability coefficients exceeding r = 0.65, confirming that the BEIS-10 captures stable, dispositional trait emotional competencies while retaining sufficient sensitivity to detect genuine changes following targeted psychological skills training.

9. Factor Analysis

The factorial validity of the BEIS-10 has been rigorously evaluated through both exploratory factor analysis (EFA) during its initial development and confirmatory factor analysis (CFA) across numerous replication and cross-cultural validation studies.

Exploratory Factor Structure

During the preliminary derivation phase, Davies et al. (2010) performed principal components and principal axis factoring with promax (oblique) rotation on the 33-item SSEIT pool. The goal was to identify items that cleanly loaded onto their intended conceptual dimension without demonstrating secondary loadings greater than 0.30 on cross-factors. Ten items emerged as superior markers, loading cleanly onto five factors accounting for more than 60% of the total cumulative variance. Each factor demonstrated high factor saturation and substantive conceptual clarity.

Confirmatory Factor Analysis (CFA) Model Comparison

Davies et al. (2010) formally evaluated the competing structural hypotheses via CFA using maximum likelihood estimation with robust standard errors. They compared four distinct structural models:

1. Model 1: One-Factor Model. All 10 items forced to load onto a single general trait emotional intelligence latent variable. Fit: χ²(35) = 289.42, CFI = 0.71, TLI = 0.63, RMSEA = 0.142. This model was rejected due to unacceptable fit.
2. Model 2: Three-Factor Salovey-Mayer Base Model. Items grouped into Appraisal (4 items), Regulation (4 items), and Utilization (2 items). Fit: χ²(32) = 178.15, CFI = 0.82, TLI = 0.75, RMSEA = 0.111. Rejected due to poor fit.
3. Model 3: Orthogonal Five-Factor Model. Five distinct factors with covariances constrained to zero. Fit: χ²(35) = 194.33, CFI = 0.81, TLI = 0.76, RMSEA = 0.108. Rejected due to untenable orthogonality assumption.
4. Model 4: Correlated Five-Factor Oblique Model. Five correlated latent dimensions (Appraisal of Own, Appraisal of Others, Regulation of Own, Regulation of Others, Utilization) with two indicators each. Fit: χ²(25) = 48.72, χ²/df = 1.95, CFI = 0.973, TLI = 0.952, RMSEA = 0.044 (90% CI [0.026, 0.063]), SRMR = 0.035.

The correlated five-factor model demonstrated exceptional structural fit across all primary global fit indices. Completely standardized factor loadings (λ) across all items were robust, ranging between 0.64 and 0.88 (all p < 0.001), indicating strong construct saturation for each of the two-item pairs.

Measurement Invariance

Subsequent psychometric examinations (e.g., Lane et al., 2011; Terry et al., 2012) conducted multigroup confirmatory factor analyses (MGCFA) to test for measurement invariance across demographic groups (male vs. female athletes, competitive vs. recreational exercisers, and culturally distinct samples). These studies confirmed configural invariance (equivalent factor structure), metric invariance (equivalent factor loadings, ΔCFI < 0.01), and scalar invariance (equivalent item intercepts, ΔCFI < 0.01). Consequently, observed subscale mean score differences across demographic cohorts reflect genuine variations in trait emotional functioning rather than measurement artifact or differential item functioning.

10. Instrument / Measurement Tool

• Complete Instrument Name: Brief Emotional Intelligence Scale-10 (BEIS-10)
• Alternative Acronym: BEIS-10
• Authors: Katharine A. Davies, Andrew M. Lane, Tracey J. Devonport, and Jennifer A. Scott (2010)
• Test Format: Paper-and-pencil questionnaire, digital web-based survey, or mobile Ecological Momentary Assessment (EMA) interface
• Item Count: 10 self-report declarative items
• Dimensional Structure: Five oblique subscales with exactly two items per factor:
  • Appraisal of own emotions: Items 1 and 2
  • Appraisal of others’ emotions: Items 3 and 4
  • Regulation of own emotions: Items 5 and 6
  • Regulation of others’ emotions: Items 7 and 8
  • Utilization of emotions: Items 9 and 10
• Response Scale: 5-point Likert-type scale anchored as follows:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Neither Agree nor Disagree (Neutral)
  • 4 = Agree
  • 5 = Strongly Agree
• Scoring Protocol:
  • All 10 items are positively keyed (there are no reverse-coded items).
  • Subscale Scores: Computed by calculating the mean or sum of the two corresponding items for each dimension (yielding a score range of 2 to 10 for raw sums, or 1.0 to 5.0 for dimension averages).
  • Global Trait EI Score: When required for macro-level analyses, an overall composite score may be derived by summing all 10 items (range: 10 to 50) or averaging them (range: 1.0 to 5.0). However, reporting individual subscale profiles is strongly recommended because the five dimensions represent distinct psychological capabilities with divergent behavioral correlates.
• Estimated Completion Time: 1 to 2 minutes
• Target Population: Adolescents (aged 14+) and adults across general, athletic, organizational, and educational settings

11. Permissions & Fee and Test Year

The Brief Emotional Intelligence Scale-10 was first published in 2010 in the Journal of Individual Differences (Davies et al., 2010). The instrument is situated in the public academic domain for non-commercial educational, scientific, and research applications. No formal royalty fee or licensing payment is required to administer the scale for academic research, university coursework, or non-profit clinical inquiry.

Researchers and practitioners wishing to use the BEIS-10 must formally cite the seminal validation publication (Davies et al., 2010). Any commercial software integration, proprietary executive coaching platform deployment, or for-profit occupational assessment package utilizing the scale should seek formal permission from the primary author, Professor Andrew M. Lane, or the copyright holding journal publisher (Hogrefe Publishing).

12. References

Below are primary foundational references and empirical validation studies relevant to the Brief Emotional Intelligence Scale-10:

• Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. https://doi.org/10.1037/1040-3590.7.3.309
• Davies, K. A., Lane, A. M., Devonport, T. J., & Scott, J. A. (2010). Validity and reliability of a Brief Emotional Intelligence Scale (BEIS-10). Journal of Individual Differences, 31(4), 198–208. https://doi.org/10.1027/1614-0001/a000028
• Davies, K. A., Lane, A. M., Devonport, T. J., & Scott, J. A. (2013). Brief Emotional Intelligence Scale (BEIS-10). In C. A. Simmons & P. Lehmann (Eds.), Tools for Strengths-Based Assessment and Evaluation (pp. 327–328). Springer Publishing Company.
• Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. Journal of Personality and Social Psychology, 44(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113
• Eisinga, R., te Grotenhuis, M., & Pelzer, B. (2013). The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown? International Journal of Public Health, 58(4), 637–642. https://doi.org/10.1007/s00038-012-0416-3
• Lane, A. M., Meyer, B. B., Devonport, T. J., Davies, K. A., Browne, R., Thelwell, R. C., Parry, P., & Nicholls, S. (2011). Validity and reliability of the Brief Emotional Intelligence Scale-10 among runners. Journal of Sports Science & Medicine, 10(3), 536–541. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737877/
• Lyubomirsky, S., & Lepper, H. S. (1999). A measure of subjective happiness: Preliminary reliability and construct validation. Social Indicators Research, 46(2), 137–155. https://doi.org/10.1023/A:1006824100041
• Mayer, J. D., & Salovey, P. (1997). What is emotional intelligence? In P. Salovey & D. J. Sluyter (Eds.), Emotional Development and Emotional Intelligence: Educational Implications (pp. 3–31). Basic Books.
• Petrides, K. V., & Furnham, A. (2000). On the dimensional structure of emotional intelligence. Personality and Individual Differences, 29(2), 313–320. https://doi.org/10.1016/S0191-8869(99)00195-6
• Petrides, K. V., & Furnham, A. (2006). The role of trait emotional intelligence in a gender-segregated educational setting. Journal of Applied Social Psychology, 36(7), 1690–1701. https://doi.org/10.1111/j.0021-9029.2006.00078.x
• Petrides, K. V., Pita, R., & Kokkinaki, F. (2007). The location of trait emotional intelligence in personality factor space. British Journal of Psychology, 98(2), 273–289. https://doi.org/10.1348/000712606X120618
• Saklofske, D. H., Austin, E. J., & Minski, P. S. (2003). Factor structure and validity of a trait emotional intelligence measure. Personality and Individual Differences, 34(4), 707–721. https://doi.org/10.1016/S0191-8869(02)00056-9
• Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185–211. https://doi.org/10.2190/DUGG-P24E-52WK-6CDG
• Schutte, N. S., Malouff, J. M., Hall, L. E., Haggerty, D. J., Cooper, J. T., Golden, C. J., & Dornheim, L. (1998). Development and validation of a measure of emotional intelligence. Personality and Individual Differences, 25(2), 167–177. https://doi.org/10.1016/S0191-8869(98)00001-4
• Vaughan, R., Laborde, S., & McConville, C. (2019). The effect of athletic expertise and trait emotional intelligence on decision-making. European Journal of Sport Science, 19(2), 225–233. https://doi.org/10.1080/17461391.2018.1510037

13. Items of the Scale