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A preliminary validation of the Arabic version of the “Profile of Emotional Competence” questionnaire among Tunisian adolescent athletes and nonathletes: insights and implications for sports psychology

Authors Aouani H, Slimani M , Bragazzi NL, Hamrouni S, Elloumi M

Received 23 September 2018

Accepted for publication 13 November 2018

Published 13 March 2019 Volume 2019:12 Pages 155—167


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Mei-Chun Cheung

Hajer Aouani,1 Maamer Slimani,1–3 Nicola Luigi Bragazzi,2–4 Sabeur Hamrouni,1 Mohamed Elloumi1

1High Institute of Sport and Physical Education of Ksar Said, Manouba University, Manouba, Tunisia; 2Department of Health Sciences (DISSAL), Postgraduate School of Public Health, Genoa University, Genoa, Italy; 3Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Section of Psychiatry, Genoa University, Genoa, Italy; 4UNESCO Chair “Anthropology of Health – Biosphere and Healing System”, University of Genoa, Genoa, Italy

Background: Emotional intelligence refers to how individuals deal with intrapersonal or interpersonal emotional information and how a subject identifies, expresses, understands, regulates, and uses his/her own emotions or those of others. The purpose of the present study was to validate the Arabic version of the “Profile of Emotional Competence” (PEC) questionnaire.
Methods: A sample of 285 Tunisian participants (153 men and 132 women) was recruited, age range: 12–18 years (15.2±2.4 years). The participants were prospectively classified into the following two groups: athletes (n=101) and nonathletes (n=184).
Results: Findings of the present study indicated that the Arabic version of the PEC questionnaire has good psychometric properties. The Cronbach’s α suggested that all subscales had adequate internal consistency. Test–retest reliability was excellent. The correlations between interpersonal and intrapersonal subscales were low to moderate (from 0.37 to 0.59), except for the regulation interpersonal, utilization interpersonal, and utilization intrapersonal subscales, which showed negligible correlations with the other subscales. The two-factor solution (interpersonal and intrapersonal competence models) accounted for 62.1% of variance. All subscales loaded on the expected factor, except for the utilization intrapersonal and regulation interpersonal subscales, which did not yield a satisfactory loading. Age and athletes’ status impacted on all the PEC dimensions, except for some subscales.
Conclusion: Finally, psychologists and practitioners in the Arab world could use the PEC questionnaire as a valid and reliable instrument for planning ad hoc interventions.

Keywords: emotion, gender, age, sport exercise, validation



In the last 2 decades, emotional intelligence (EI) has attracted considerable interest among psychologists and sports scientists. This concept refers to how individuals deal with intrapersonal or interpersonal emotional data1 and how a subject identifies, expresses, understands, regulates, and/or uses his/her own emotions or those of others.2,3 Theoretical paradigms subdivide EI into the following three perspectives: 1) ability, 2) trait, and 3) mixed model. In this article, we decided to focus on EI mainly as a trait.

More in detail, the ability perspective takes as a starting point the working hypothesis that EI is a cognitive ability, which is not measured by standard intelligence tests and which relates to reasoning and problem solving within the emotional domain. EI, as an ability, is defined as “the ability to perceive accurately, appraise, and express emotion; the ability to access and/or generate feelings when they facilitate thought; the ability to understand emotion and emotional knowledge; and the ability to regulate emotions to promote emotional and intellectual growth”.2 Mayer et al4 further defined this concept as “the ability to process and reason about emotional information”. EI, as trait, can be defined as “a constellation of emotion-related dispositions capturing the extent to which people attend to, identify, understand, regulate, and utilize their emotions and those of others”.3

Demographic variables such as age and gender have been widely studied with respect to EI,5 leading sometimes to conflicting results, with some studies reporting higher EI scores among females and other investigations finding no clear differences between males and females.6 Concerning age, the “Six Seconds’ Emotional Intelligence Assessment” (SEI) study, which has recruited a sample of 405 American people, has shown that EI tends to increase slightly but significantly with age.7

Several psychometric tools have been developed to assess EI. For instance, different questionnaires measure EI as ability, such as the “Multi Factor Emotional Intelligence Scale” (MEIS) and the “Mayer-Salovey-Caruso Emotional Intelligence Test” (MSCEIT).8,9 There are some other questionnaires, namely the “Trait Emotional Intelligence Questionnaire” (TEIQue),10 the TEIQue-short form (TEIQue-SF),11 and the TEIQue-child form,12 that measure EI as a trait. However, when the objective is to obtain a global picture, the “Profile of Emotional Competence” (PEC)13 represents an added value.

Brasseur et al13 have developed the PEC because the other inventories were not deemed able to measure the different competences, separately in terms of self and others (intrapersonal vs interpersonal skills). Brasseur et al13 argued that the PEC is more theoretically aligned with its item content, overall briefer, and more effective to administer than the other tools. As such, authors encouraged researchers or practitioners to use the PEC as an alternative to the other existing inventories and questionnaires. They also suggested that future research is warranted to further examine or confirm the reliability and validity of the PEC among diverse populations from different countries and settings. Of note, the PEC was administered to either healthy individuals or patients. However, its reliability for athletic and Arabic populations has not been assessed yet. This information would help sports practitioners to use the PEC also for these populations.

Various studies have explored the viability of the EI construct in predicting different outcomes, and for example, EI has been linked with performance under stress.14 It is worth noting that practicing sport requires the effective management of stress, tolerance of frustration, regulation of mood, and exercise of emotional restraint, within public purview and scrutiny.15 As such, sports psychologist and scientists could benefit from adopting an easy and comprehensive questionnaire to assess the level of EI among athlete populations.

Generally, EI has been found to be associated with positive performance and outcomes, in a variety of environments, including the academic setting.14 In the field of sports science, the construct of EI has been linked with sports performance. For instance, Perlini and Halverson15 evaluated the level of EI in a sample of 79 National Hockey League (NHL) players across 24 teams. They found that EI intrapersonal competence and general mood were good predictors of hockey performance (in terms of NHL points and games played). Zizzi et al16 explored the relationships between EI and global measures of baseball performance in a sample of 61 college baseball players recruited across 10 teams. Significant correlation between EI and pitching and hitting statistics was detected. Crombie et al17 studied team EI in cricketers and found it positively associated with sports performance of the cricket teams. Furthermore, team EI was shown to be a significant predictor of sports performance. Also, Ghezelsefloo et al18 reported that, in a sample of 95 handball players recruited across nine teams, EI was associated with performance. Mohammad et al19 found that EI varied significantly between state and national volleyball players and was influenced by practice and expertise. Ghazili et al20 reported a positive association between EI and goal orientation among male athletes, whereas Gáspár et al21 described a correlation between exercise volume, defined as weekly hours of exercise, and EI. Vaughan et al22 investigated a sample of 269 participants aged between 18 and 26 years with a range of athletic experience and found that trait EI was positively associated with the quality of decision making and negatively associated with deliberation time and risk taking.

From a trans-cultural standpoint, psychometric properties of the English version of PEC have been so far examined in Belgian,13 Tunisian,23 and Japanese24 populations.

However, concerning the point of view of applied sports psychology, very few studies have explored the theoretical differences between athletes and nonathletes regarding emotional competences, reporting conflicting or mixed evidence. Pasand,25 for example, was not able to find any difference between athletes and nonathletes in terms of EI, whereas Sohrabi et al26 found statistically significant differences. Therefore, the aims of the present study were 1) to validate the Arabic version of the PEC and 2) to investigate potential EI-related differences between athletes and nonathletes.

Participants and methods


Participants were asked to provide demographic information, such as age, gender, if they practiced any sport, and in which sports discipline they were primarily involved. A sample of 285 Tunisian participants (153 men and 132 women, 53.7 and 46.3% of the sample, respectively) was recruited. Age was from 12 to 18 years (15.2±2.4 years) and was categorized in the following two ranges: 12–15 and 16–18 years. Participants were prospectively classified into the following two groups: athletes (n=101, 35.4% of the sample; they participated in a variety of sports, such as taekwondo, kickboxing, athletics, soccer, and trained about three times per week) and nonathletes (n=184, 64.6% of the sample; they were students with no sports background).


Participants attended a total of three data collection sessions, separated by 1 week. During the control session (week 1), participants were familiarized with the psychological inventory. This session was devised as a control day in which the psychological inventory used in the present study was presented and explained to the participants (no data were collected from measurement point 1). The questionnaires of emotional competence were distributed to the participants through their teachers. On measurement point 2, participants completed the questionnaire during class time with a member of the research team available to respond to enquiries. A total of 20–30 minutes were given for each participant to properly answer the questionnaire in a comfortable environment. On measurement point 3, participants completed the questionnaire for the second time, in order to verify their comprehension of items (test–retest reliability analysis).

The present study was carried out according to the 1964 Declaration of Helsinki and its subsequent amendments. Participants were informed of their rights during the study, and anonymity of results was ensured. No information about the purposes of the study was provided to the participants until they had completed the protocol, which was approved by the Ethics Committee of the “High Institute of Sport and Physical Education” of Ksar Said, Manouba University, Tunisia, before the commencement of the assessment.

Each participant (or if the subject was under age, his/her parent/guardian) signed a written, informed consent before taking part in the study.

Psychometric tool: the PEC questionnaire

In the present investigation, the PEC13 was used to assess EI. Participants responded to the 50 items using a 5-point Likert scale (ranging from “strongly disagree” to “strongly agree”). The inventory was designed to evaluate the five core competences of EI – namely, identification (I), comprehension (C), expression (E), regulation (R), and utilization (U) of emotions – separately, distinctly for one’s own and others’ emotions. More in detail, the assessing tool was devised in order to quantitatively investigate intrapersonal emotional competence (that is, competence related to one’s own emotions) and interpersonal emotional competence (or competence related to other people’s emotions) separately. Furthermore, the PEC produces a global score related to the overall emotional competence level. The PEC has displayed satisfactory discriminant and convergent validity.13

Translation and validation of the questionnaire

From a methodological standpoint, the linguistic validation of the instrument included all the steps proposed by Vallerand.27 The first step concerned the development of a preliminary version of the inventory, which consisted in a draft approved by an expert evaluation committee. Moreover, a pretest assessment of the clarity of items was performed on a target population (a small sample of 20–30 subjects). During the next step, two translators worked independently to compose a consensus version of the PEC from English to the Arabic language (forward/backward translation). The last step was the back-translation from Arabic to English. The Arabic version of the PEC is reported in Table S1.

The second phase of the validation of the PEC involved assessing the accuracy, reliability, and validity of the instrument. More in detail, this phase consisted of the factor structure analysis known as “exploratory” (exploratory factor analysis [EFA]) and the comprehensive evaluation of the internal consistency.

As a first step, descriptive statistics was performed in order to characterize the collected data, which, before any statistical handling and processing, were visually inspected for potential outliers. More in detail, continuous data were computed as mean and SD, while categorical data were expressed as percentage, where appropriate. Asymmetry/skewness and kurtosis were also computed for each item score. In particular, asymmetry/skewness and kurtosis values were deemed acceptable if they ranged from –2 to +2, in case of normal univariate data distribution.28

Previous validation studies of the PEC provided evidence that a two-correlated factor structure adequately fits the observed data. As such, we could have tested the factor structure of the Arabic PEC through confirmatory factor analysis (CFA). However, the psychometric properties of psychological measures are not automatically warranted when the measures are adapted in other languages.29 Therefore, we chose to use an exploratory approach, rather than a confirmatory one. CFA requires each indicator to load on only one factor, but, as shown by recent studies,30 this assumption might be too restrictive for questionnaires related to the field of personality research, because indicators may have secondary loadings significantly different from zero. The presence of these secondary loadings is, indeed, a critical and crucial issue: it would imply that the items have a weak discriminant validity, since an item that is considered as an indicator of a specific construct can also be an indicator of another construct. In CFA, the more the secondary loadings departs from zero, the more the correlations among the factors will be inflated to account for nonzero secondary loadings restricted to zero, thus yielding biased loadings, overestimated factor correlations, distorted structural relations, and lack of fit, among others.30

For these reasons, the factor structure of the Arabic PEC was tested using EFA. More in detail, different EFA runs were conducted. First, an exploratory run was performed to control for the factorability of the correlation matrix using the Bartlett’s test of sphericity. In case of statistical significance, this test enables scholars to reject the null hypothesis (that is, all the correlations in the correlation matrix are zero and the matrix is an identity matrix).

The Kaiser-Meyer-Olkin (KMO) measure was calculated in order to quantitatively assess the sampling adequacy. Ideally, the KMO should be greater than 0.60 and is considered excellent if greater than 0.90. The likely number of factors was determined both 1) by computing the number of factors with eigenvalues greater than 1 and 2) by visually inspecting the scree plot. The optimal number of factors to extract was confirmed through parallel analysis (PA).31,32 PA compares the observed eigenvalues of factors (if factor analysis is performed) or components (if principal component analysis is performed) extracted from the correlation matrix to be analyzed with those obtained from the simulation of independent correlation matrices of normal pseudo-random samples (in this case, 1,000),32 having the same sample size and number of variables. We retained those factors whose observed eigenvalues were larger than the 95th percentile of the distribution of the corresponding simulated eigenvalues.

After checking the factor loadings, items were deleted in cases of unsatisfactory loading (that is, values less than 0.45) or loading conflicting with a sound and clear theoretical explanation. Different runs were, therefore, carried out iteratively until convergence was attained and a satisfactory, clearly interpretable solution was finally achieved.

Furthermore, cases of cross-loading were interpreted according to the criteria of salience and total amount of explained variance, with theoretical considerations also being taken into account.31

Reliability analysis of the questionnaire

Reliability of the questionnaire administered was computed by calculating the Cronbach’s a (both unadjusted and adjusted according to the number of items). The following rule of thumb33,34 was used for interpreting the coefficient: excellent psychometric properties with a equal to or greater than 0.9, good with a in the range of 0.8–0.9, acceptable with a in the range of 0.7–0.8, questionable with a in the range of 0.6–0.7, poor with a in the range of 0.5–0.6, and unacceptable with a less than 0.5.

Test–retest reliability analysis of the questionnaire

Test–retest reliability analysis was computed calculating the intraclass correlation coefficient (ICC) (ICC(3,k) according to the Shrout and Fleiss35 convention, two-way mixed model, average measure, consistency, according to the McGraw and Wong36 convention), computed together with its 95% CI.37,38 The following rule of thumb was used to interpret the reliability coefficient: perfect reliability with coefficient equal to 1, excellent if greater than or equal to 0.9, good reliability in the range of 0.8–0.9, acceptable reliability in the range of 0.7–0.8, questionable reliability in the range of 0.6–0.7, poor reliability in the range 0.5–0.6, unacceptable reliability with coefficient less than 0.5, and no reliability with coefficient equal to 0.

Statistical analyses

Student’s t-test was performed to explore gender-related differences. Multivariate ANOVA (MANOVA)39 and multivariate regression analyses were carried out in order to investigate the impact of athlete status, age, and gender on the questionnaire scores. Pearson’s correlations were conducted to determine the relationship between EI dimensions. The strength of correlation was measured using the rule of thumb proposed by Hinkle and collaborators40: the correlation was deemed negligible with r coefficient in the range of 0.00–0.30, low with r in the range of 0.30–0.50, moderate with r in the range of 0.50–0.70, high with r in the range of 0.70–0.90, and very high with r in the range of 0.90–1.00.

All statistical analyses were performed using the commercial software “Statistical Package for Social Sciences” (SPSS for Windows, Version 24.0, released in 2016; IBM Corporation, Armonk, NY, USA). PA was performed with Factor software (which is freely available at

For all analyses, statistical significance was set at P<0.05.


Internal consistency of study items

We tested the dataset for a preliminary assessment, searching for potential multivariate outliers, that is, participants with unusual patterns of answers on questionnaire items. Skewness and kurtosis values were acceptable (Table 1). Then, we computed the reliability statistics for the questionnaire. The Cronbach’s a coefficient for all the questionnaires yielded a value of 0.859 (adjusted 0.858). The Cronbach’s a coefficient for the interpersonal competence dimension resulted 0.688 (adjusted 0.686), while the coefficient for intrapersonal competence dimension was 0.750 (adjusted 0.752). Further details are shown in Table 2.

Table 1 Descriptive statistics for each item of the Arabic version of the PEC questionnaire

Abbreviation: PEC, Profile of Emotional Competence.

Table 2 Descriptive statistics for each subscale of the Arabic version of the PEC questionnaire

Abbreviations: C, comprehension; E, expression; I, identification; PEC, Profile of Emotional Competence; R, regulation; U, utilization.

Test–retest reliability analysis

ICCs ranged from 0.94 (R interpersonal competence) to 0.99 (E interpersonal competence), demonstrating excellent test–retest reliability, with all coefficients greater than 0.9. ICC for the interpersonal domain was 0.9823 (95% CI 0.9776–0.9860), whereas for the intrapersonal domain was 0.9843 (95% CI 0.9802–0.9876). ICC for the overall questionnaire resulted in 0.9866 (95% CI 0.9830–0.9893). Further details are reported in Table 3.

Table 3 ICCs for each subscale

Abbreviations: C, comprehension; E, expression; I, identification; ICCs, intra-class correlation coefficients; R, regulation; U, utilization; CI, confidence interval.

Factor structure of the questionnaire

The KMO measure resulted good (0.868), and the Bartlett’s test statistically was statistically significant.

PA and the preliminary EFAs with visual inspection of the scree plot and the computation of factors with eigenvalues greater than 1 suggested that the optimal number of factors was two. We, thus, performed EFAs, setting the predefined number of factors to be extracted. The two-factor solution accounted for 62.1% of variance. The best loading factors are shown in Table 4. All subscales loaded on the expected factor, except for U intrapersonal and R interpersonal subscales, which did not yield a satisfactory loading, and therefore, could not be retained.

Table 4 Factor loadings for each subscale of the Arabic version of the PEC questionnaire

Abbreviations: C, comprehension; E, expression; I, identification; PEC, Profile of Emotional Competence; R, regulation; U, utilization.

Correlation between all EI dimensions

Inter-item correlations were moderate to high, and corrected item-total correlation was higher than 0.20 for most items.41,42 Further details are reported in Table 5.

Table 5 Correlation between the different subscales of the Arabic version of the PEC questionnaire

Notes: *Statistically significant with P-value <0.05. ***Statistically significant with P-value <0.001.

Abbreviations: C, comprehension; E, expression; I, identification; PEC, Profile of Emotional Competence; R, regulation; U, utilization.

Correlations between the subscales and I interpersonal were all low, except for the moderate correlation with E interpersonal and the negligible correlations with R interpersonal and U intrapersonal. Similarly, correlations between the subscales and I intrapersonal were low, apart from the moderate correlations with E intrapersonal and C intrapersonal and the negligible correlations with R interpersonal, U interpersonal, and U intrapersonal. Correlations with C interpersonal resulted low, except for those with R interpersonal, R intrapersonal, and U interpersonal, which resulted negligible. The correlation with U intrapersonal was not significant. Correlations between C intrapersonal, E interpersonal, and E intrapersonal resulted moderate, whereas the correlation with R intrapersonal was low and the correlations with R interpersonal and U interpersonal were negligible. Finally, the correlation between C intrapersonal and U intrapersonal was not significant. Correlations between the subscales and E interpersonal were in part low and in part negligible. Correlations between E intrapersonal and R interpersonal and U interpersonal resulted negligible, whereas the correlation with R intrapersonal was low. The correlation with U intrapersonal was not significant. Correlations between the subscales and R interpersonal subscale were negligible, except for the correlation with U interpersonal (not significant). Correlations between the subscales and R intrapersonal subscale were low. Finally, correlation between U interpersonal and U intrapersonal resulted negligible.

The correlation between the two factors individuated by EFA yielded a value of 0.737 (P<0.001). Correlations between the subscales and the overall score were low to high and ranged from 0.36 (P<0.001) for U intrapersonal to 0.75 (P<0.001) for C intrapersonal. Correlation between the interpersonal domain and the overall score was very high (0.91, P<0.001) as well as between the overall score and the intrapersonal domain (0.92, P<0.001).

ET between athletes and nonathletes, genders, and age group

At the MANOVA, gender had a statistically significant impact on C intrapersonal (F=10.33, P=0.002) and E intrapersonal (F=7.88, P=0.005) and had a borderline effect on I interpersonal (F=3.18, P=0.076). Being an athlete had an impact on I intrapersonal (F=9.34, P=0.003) and E intrapersonal (F=9.37, P=0.002) and had a borderline effect on intrapersonal (F=3.33, P=0.070). Age had an effect on I interpersonal (F=5.89, P=0.016), C interpersonal (F=11.01, P=0.001), E interpersonal (F=11.24, P=0.001), E intrapersonal (F=7.29, P=0.007), U intrapersonal (F=7.14, P=0.008), interpersonal (F=11.62, P=0.001), and global (F=7.38, P=0.007). No other statistically significant effects could be detected.

At the multivariate regression analysis, age impacted on all subscales, except for R interpersonal (P=0.667). Similarly, athlete status influenced all the subscales apart from R interpersonal (P=0.529) and U intrapersonal (P=0.328). Gender did not impact significantly on any of the PEC subscales. The interaction age × athlete status did not yield statistical significance for C interpersonal (P=0.715), E interpersonal (P=0.255), E intrapersonal (P=0.152), and R interpersonal (P=0.841), whereas the interaction age × gender did not impact on I interpersonal (P=0.190), I intrapersonal (P=0.083), E interpersonal (P=0.359), R interpersonal (P=0.490), R intrapersonal (P=0.672), and U interpersonal (P=0.988). The interaction athlete status × gender did not influence the scores of R interpersonal (P=0.056), R intrapersonal (P=0.668), U interpersonal (P=0.917), and U intrapersonal (P=0.947). Finally, the interaction age × athlete status × gender impacted only on E intrapersonal (P=0.027). For further details, the reader is referred to Tables 68.

Table 6 Mean ± SD of the PEC subscales and factors for male and female participants

Abbreviations: C, comprehension; E, expression; I, identification; PEC, Profile of Emotional Competence; R, regulation; U, utilization.

Table 7 Multivariate regression analysis for each variable

Abbreviations: C, comprehension; E, expression; I, identification; R, regulation; U, utilization.

Table 8 Predictors for each subscale

Abbreviations: C, comprehension; E, expression; I, identification; R, regulation; U, utilization.


This study effectively validated the metrological qualities of our Arabic translation of the PEC, which can henceforth be proposed to an Arabic-speaking public. Indeed, the reliability of this version, which was assessed in terms of internal consistency and repeatability, has been deemed good. The questionnaire’s Cronbach’s a coefficient was equal to 0.68 and 0.75 for interpersonal and intrapersonal dimensions, respectively, whereas the coefficient for the global questionnaire was 0.86.

According to the English version of the PEC,13 the internal consistency of the Arabic version of PEC subscales was generally good. The Cronbach’s a for the interpersonal and intrapersonal dimensions of Arabic version of PEC was questionable and acceptable, respectively. Moreover, the range of the Cronbach’s a coefficients for the 10 subscales was lower than the original English version (ranging from 0.72 to 0.83). On the basis of the current reliability results, the Arabic PEC showed sufficient reliability.

The construct validity was examined through a series of correlations between different subscales and different determinants and expected outcomes. For instance, the correlations between interpersonal and intrapersonal subscales were low to moderate (from 0.37 to 0.59), except for the R interpersonal, U interpersonal, and U intrapersonal, which showed negligible correlations with other scales. More specifically, there were no significant correlations between U intrapersonal and C interpersonal, U intrapersonal and C intrapersonal, and U intrapersonal and E intrapersonal. At the theoretical level, these results confirm both the relationship between the intrapersonal and interpersonal dimensions of EI, as well as their relative independence. Data, indeed, supported the relevance of assessing both dimensions, separately. This also suggests that participants who have difficulties in identifying and utilization their emotions were not particularly good at comprehension and expression of their and others’ emotions. Overall, the findings of present study provide good support for the validity and the reliability of the questionnaire and they suggest that the psychometric properties of the Arabic PEC are similar to the psychometric properties of the original English version.

However, some differences between our and the original questionnaires should be discussed. For instance, it has already been demonstrated that there was a significant difference between men and women in regard to emotional abilities4345 and this finding was not replicated in our sample. It would nonetheless appear that women’s EI abilities tend to be greater than men’s;4345 unfortunately, the different ages and populations sampled in our study do not allow us to offer further interpretation of this tendency, which would require targeted analysis in a dedicated study. Furthermore, there was significant difference in all the subscales of the PEC apart from R interpersonal and U intrapersonal according to the athletes’ status. In this respect, however, it is interesting to note that Li et al46 found that university students whose time involvement in exercise reached the recommended level needed for health and well-being were found to have better total EI score and composite subscale scores for intrapersonal, interpersonal, stress management, general mood, and adaptability, compared to the students in the insufficient physical activity and inactive groups. This suggests that regular sports practice and experience in practicing seem to constitute elements favoring enhanced emotional abilities. In addition, the current study showed significant age differences on all of EC subscales, except for R interpersonal. Similar results have been reported in previous studies.4750

Implications of the findings

Our findings confirm the importance of assessing EI among athletes. These results have practical implications in that EI training can improve EI level among athletes and, therefore, enhance and optimize their performance. For instance, Campo et al51 have demonstrated the effectiveness of an EI training intervention (four face-to-face sessions over a 5-month period, with homework and follow-up procedures) to improve EI at the trait level in a sample of 67 rugby players.

Strengths and limitations

To the best of our knowledge, the current study is the first validation of the PEC in Arabic language. Aouani et al23 administered the PEC in a Tunisian sample but utilized the French version of the inventory.

The present study is not without limitations, which should be properly acknowledged. The major limitation is given by the fact that the Arabic version of the PEC did not undergo a cross-validation with other scales/questionnaires investigating other psychological parameters and constructs. As such, further research in the field is warranted: future studies should explore the correlation/association of the translated version of the PEC with other questionnaires (for instance, investigating happiness, quality of life, or mental and physical health, as well as other psychological measures of emotional competences) and with variables related to sports performance. Another shortcoming is represented by the cross-sectional study design and the sample size selection/recruitment (convenience sample). As such, further investigations should be conducted, utilizing randomized samples and exploiting a longitudinal study design. Furthermore, all of the study participants were adolescents aged 15.2±2.4 years (range 12–18 years), whereas Brasseur et al13 only tested gifted adolescents who were on average older (mean age 16.5±1.3 years). As such, to the best of our knowledge, this is a first article evaluating the PEC in an average teen population and, therefore, warrants further replication of our findings.


This study investigated the psychometric properties of the PEC in Arabic. Despite the abovementioned limitations, this study represents the first attempt of validating the PEC in Arabic language. However, further studies should overcome the shortcomings of the present study and should test the factorial structure of the questionnaire using randomized samples and CFA. Sports psychologists and practitioners in the Arab world could use the PEC as a valid and reliable instrument for planning ad hoc interventions.


The authors are grateful to the participants and their coaches for their kind cooperation during experimentation sessions.


The authors report no conflicts of interest in this work.



Petrides KV, Furnham A. Trait emotional intelligence: behavioural validation in two studies of emotion recognition and reactivity to mood induction. Eur J Pers. 2003;17(1):39–57.


Mayer JD, Salovey P. What is emotional intelligence? In: Salovey P, Sluyter D, editors. Emotional Development and Emotional Intelligence: Educational Implications. New York: Basic Books; 1997:3–31.


Mikolajczak M. Moving beyond the ability-trait debate: a three level model of emotional intelligence. E J Appl Psychol. 2009;5:25–32.


Mayer JD, Roberts RD, Barsade SG. Human abilities: emotional intelligence. Annu Rev Psychol. 2008;59:507–536.


Pooja P, Kumar P. Demographic variables and its effect on emotional intelligence: a study on Indian service sector employees. Ann Neurosci. 2016;23(1):18–24.


Meshkat M, Nejati R. Does emotional intelligence depend on gender? a study on undergraduate English majors of three Iranian universities. SAGE Open. 2017:1–8.


Fariselli L, Ghini M, Freedman J. Age and Emotional Intelligence. White Paper. 2006. Available from: Accessed December 4, 2018.


Mayer JD, Salovey P, Caruso DR. Emotional intelligence: theory, findings, and implications. Psychol Inq. 2004;60:197–215.


Salovey P, Grewal D. The science of emotional intelligence. Curr Dir Psychol Sci. 2005;14(6):281–285.


Schutte NS, Malouff JM, Hall LE, et al. Development and validation of a measure of emotional intelligence. Pers Individ Dif. 1998;25(2):167–177.


Cooper A, Petrides KV. A psychometric analysis of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) using item response theory. J Pers Assess. 2010;92(5):449–457.


Joseph DL, Newman DA. Emotional intelligence: an integrative meta-analysis and cascading model. J Appl Psychol. 2010;95(1):54–78.


Brasseur S, Grégoire J, Bourdu R, Mikolajczak M. The Profile of Emotional Competence (PEC): development and validation of a self-reported measure that fits dimensions of emotional competence theory. PLoS One. 2013;8(5):e62635.


Lyons JB, Schneider TR. The influence of emotional intelligence on performance. Pers Individ Dif. 2005;39(4):693–703.


Perlini AH, Halverson TR. Emotional intelligence in the National Hockey League. Can J Behav Sci. 2006;38(2):109–119.


Zizzi S, Deaner H, Hirschhorn D. The relationship between emotional intelligence and performance among college basketball players. J Appl Sport Psychol. 2003;15(3):262–269.


Crombie D, Lombard C, Noakes T. Increasing emotional intelligence in cricketers: an intervention study. Int J Sports Sci Coach. 2011;6(1):69–86.


Ghezelsefloo H, Hemmatinezhad M, Hemmatinezhad M, Ramazaninezhad R. Relationship between emotional intelligence and athlete’s mood with team- efficiency and performance in elite - handball players. Int J Sport Stud. 2012;2(3):155–162.


Mohammad G, Khan S, Singh J. Emotional intelligence between state and national level volleyball players. J Phys Educ Res. 2015;2(2):53–59.


Ghazili Z, Makvandi B, Naderi F. Relationship between emotional intelligence’s components and goal-orientated attitude in athletes. MAGNT Res Rep. 2015;3:1550–1507.


Gáspár Z, Soós I, Szabo A. Is there a link between the volume of physical exercise and emotional intelligence (EQ)? Pol Psychol Bull. 2017;48(1):105–110.


Vaughan R, Laborde S, Mcconville C. The effect of athletic expertise and trait emotional intelligence on decision-making. Eur J Sport Sci. 2018:1–9.


Aouani H, Slimani M, Hamrouni S, Bragazzi NL, Elloumi M. Data concerning the psychometric properties of the “Profile of Emotional Competence” questionnaire administered to a sample of athletes and non-athletes. Data Brief. 2018;18:769–775.


Nozaki Y, Koyasu M. Can we apply an emotional competence measure to an eastern population? psychometric properties of the profile of emotional competence in a Japanese population. Assessment. 2016;23(1):112–123.


Pasand F. Emotional intelligence in athletes and non-athletes and its relationship with demographic variables. Br J Sports Med. 2010;44(Suppl_1):i56–i82.


Sohrabi R, Garajeh PA, Mohammadi A. Comparative study of emotional intelligence of athlete and non- athlete female students of Tabriz islamic Azad university. Procedia Soc Behav Sci. 2011;30:1846–1848.


Vallerand RJ. Towards transcultural validation methodology of psychological questionnaires: implications for french research. Can Psychol. 1989;30:662–689.


George D, Mallery P. SPSS for Windows Step by Step: A Simple Guide and Reference 17.0 Update. 10th ed. Boston, MA: Pearson; 2010.


Hambleton RK. Issues, designs, and technical guidelines for adapting tests into multiple languages and cultures. In: Hambleton RK, Merenda PF, Spielberger CD, editors. Adapting Educational and Psychological Tests for Cross-cultural Assessment. Mahwah, NJ: Lawrence Erlbaum; 2005:3–38.


Asparouhov T, Muthén B. Exploratory structural equation modeling. Struct Equ Modeling. 2009;16(3):397–438.


Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30:179–185.


Buja A, Eyuboglu N. Remarks on parallel analysis. Multivariate Behav Res. 1992;27(4):509–540.


Kline P. The Handbook of Psychological Testing. 2nd ed. London: Routledge; 2000.


DeVellis RF. Scale Development: Theory and Applications. Los Angeles: Sage; 2012.


Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 1979;86(2):420–428.


Mcgraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Methods. 1996;1(1):30–46.


Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231–240.


Berchtold A. Test–retest: agreement or reliability? Method Innov. 2016;9:1–7.


Warne RT. A primer on multivariate analysis of variance (MANOVA) for behavioral scientists. Pract Assess Res Eval. 2014;19(17):1–10.


Hinkle DE, Wiersma W, Jurs SG. Applied Statistics for the Behavioral Sciences. 5th ed. Boston: Houghton Mifflin; 2003.


Nunnally JC, Bernstein IH. Psychometric Theory. 3rd ed. New York: McGraw-Hill; 1994.


Brackett MA, Mayer JD. Convergent, discriminant, and incremental validity of competing measures of emotional intelligence. Pers Soc Psychol Bull. 2003;29(9):1147–1158.


Extremera N, Fernández-Berrocal P, Salovey P. Spanish version of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). Version 2.0: reliabilities, age and gender differences. Psicothema. 2006;18(Suppl):42–48.


Kafetsios K. Attachment and emotional intelligence abilities across the life course. Pers Individ Dif. 2004;37(1):129–145.


Palmer BR, Gignac G, Manocha R, Stough C. A psychometric evaluation of the Mayer–Salovey–Caruso Emotional Intelligence Test Version 2.0. Intelligence. 2005;33(3):285–305.


Li Gsf LFJH, Wang AHH. Exploring the relationships of physical activity, emotional intelligence and health in Taiwan college students. J Exerc Sci Fit. 2009;7:55–63.


Cabello R, Navarro Bravo B, Latorre Josã© Miguel, Fernã¡ndez-Berrocal P. Ability of university-level education to prevent age-related decline in emotional intelligence. Front Aging Neurosci. 2014; 6(141):7.


Austin EJ, Saklofske DH, Huang SHS, Mckenney D. Measurement of trait emotional intelligence: testing and cross-validating a modified version of Schutte et al.’s (1998) measure. Pers Individ Dif. 2004;36(3):555–562.


Fernández-Berrocal P, Cabello R, Castillo R, Extremera N. Gender differences in emotional intelligence: the mediating effect of age. Psychol Behav. 2012;20:77–89.


Laborde S, Dosseville F, Allen MS. Emotional intelligence in sport and exercise: a systematic review. Scand J Med Sci Sports. 2016;26(8):862–874.


Campo M, Laborde S, Mosley E. Emotional intelligence training in team sports: the influence of a season long intervention program on trait emotional intelligence. J Indiv Diff. 2016;37(3):152–158.

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