Does Trait Emotional Intelligence Predict Unique Variance in Early Career Success Beyond IQ and Personality?

Abstract

In order to determine the contribution of emotional intelligence (EI) to career success, in this study, we analyzed the relationship between trait EI (TEI), general mental ability (GMA), the big five personality traits, and career success indicators, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that TEI, and especially its dimension “repair,” has incremental validity in predicting one of the career success indicators (salary) after controlling for GMA and personality. These findings provide support for the use of TEI measures as predictors of career success in the early stage.

Keywords

trait emotional intelligence personality IQ career success

Introduction

The predictive capacity of emotional intelligence (EI) has been amply demonstrated with different job performance, professional success or job satisfaction criteria (e.g., Brackett, Rivers, & Salovey, 2011; Carmeli, 2003; Lopes, Grewal, Kadis, Gall, & Salovey, 2006; Van Rooy & Viswesvaran, 2004), both in studies based on ability models of EI (Daus & Ashkanasy, 2005) and in studies based on Trait EI (TEI; Bar-On, Handley, & Fund, 2006) and mixed models of EI (Boyatzis, Goleman, & Rhee, 2000).

There are also findings that show incremental validity of EI over general mental ability (GMA) and personality traits in predicting work outcomes or indicators of professional success (e.g., Iliescu, Ilie, Ispas, & Ion, 2012; Lyons & Schneider, 2005; O’Boyle, Humphrey, Pollack, Hawver, & Story, 2011).

However, other findings have led some authors to conclude that EI measures fail to add incrementally to the prediction of work outcomes or extrinsic and intrinsic indicators of professional success above and beyond established measures of cognitive intelligence and personality (e.g., Amelang & Steinmayer, 2006; Bastian, Burns, & Nettelbeck, 2005).

The disparity in the results obtained in different studies attempting to determine the predictive power of EI over variables such as IQ and personality traits, and thus respond with any certainty to the question of whether EI predicts significant and unique variance in job performance or career success, has in part been due to factors such as the EI Measures, EI dimensions, scoring methods, criteria, or types of sample used (Van Rooy & Viswesvaran, 2004).

This inconsistency in the results is perhaps most evident when different types of EI measures have been used. As the meta-analysis conducted by O’Boyle, Humphrey, Pollack, Hawver, and Story (2011) demonstrated, the incremental validity of EI depends on the type of measure used, differentiating three streams: (1) ability-based models that use objective test items; (2) self-report or peer-report measures based on the four-branch model of EI; and (3) “mixed models” of emotional competences. While it is to be expected that different measures will yield different results, it is striking that these differences occur when the same measure has been used. Thus, for example, in the case of using ability-based EI measures, some authors have found positive and significant relationships between EI and job performance measures (Iliescu et al., 2012; Lyons & Schneider, 2005) while others have reported the opposite (Amelang & Steinmayer, 2006; Joseph & Newman, 2010).

With respect to the other factors, these have also contributed to a greater or lesser extent to this wide variability in the results obtained, a phenomenon that has greatly impeded their generalization. In the case of the dimensions of EI, the validity of EI for predicting various criteria differs according to the dimension of EI analyzed. Its validity also differs according to the scoring method used (i.e., expert ratings vs. self-reports, or consensus scored self-reports vs. expert scored self-reports).

The most important differences as regards the criteria are between the results obtained using job performance as the criterion and those obtained using indicators of career success as the criteria. In the latter case, the results are not as positive as in the former, indicating that these are different aspects of professional success. Another contrast occurs between life skills criteria and achievement criteria. As Amelang and Steinmayr (2006) reported, recent studies have shown that EI has an incremental validity regarding life outcome criteria, but inconsistent results have been found for achievement criteria.

Finally, the type of sample used has also produced disparate results, so that in some cases the use of different samples (students vs. workers) has not yielded any significant results, for example, in the study by Amelang and Steinmayr (2006), where EI could not explain any variance in the criteria beyond psychometric intelligence and conscientiousness. In other cases, the variability of the results and their interpretation can be attributed to the type of sample, as for example in the study by Bastian, Burns, and Nettelbeck (2005), who argued that it was also possible that the markedly uniform sample assessed (primarily university students) affected the results.

In summary, as noted by Antonakis (2004), contradictions and inconsistencies highlight the importance of using methodologically defensible scientific criteria for conducting or evaluating research. Therefore, given that the results on the incremental validity of EI are ambiguous and require further research, it is necessary to continue seeking more data (Amelang & Steinmay, 2006).

The present study was designed in response to this need. We wished to determine whether EI had incremental validity above and beyond well-known general mental abilities and personality traits in predicting career success in the early stage. Our focus on these criteria in the early career stage was motivated by the paucity of research on this stage of a professional career (Rode, Arthaud-Day, Mooney, Near, & Baldwin, 2008) and the importance of including other success criteria beyond the traditional one of job performance, if we were to investigate the relationship between EI and job performance across different type of jobs, as indicated by Amelang and Steinmayr (2006).

Selection of the EI instrument was based on the differentiation established by Petrides, Pita, and Kokkinaki (2007) between trait EI and ability EI, which refers more to the type of measurement rather than the theoretical approach.

Given the evidence demonstrating that EI studies based on self-report measures have a higher predictive power than studies that have assessed EI using EI ability tests (O’Boyle et al., 2011; Van Rooy & Viwesvaran, 2004), in this study, it was decided to use a self-report measure: the Trait Meta-Mood Scale (TMMS). This scale, based on Salovey and Mayer’s model (1990), is one of the most valid and widely used self-report measures developed to assess relevant aspects of individuals’ perceptions of their emotional competences. Unlike ability-based measures, TMMS evaluates the knowledge individuals have about their own emotional abilities rather than their actual capacity. Specifically, it is a measure of three key EI dimensions: attention (perceived attention paid to one’s own emotional states), clarity (perceived ability to understand and discriminate between moods and emotions), and repair (perceived ability to regulate one’s own emotional states).

Several studies have shown that TMMS EI dimensions, such as “clarity” and repair, are important predictors and have incremental validity over intelligence and personality for criteria such as life satisfaction (e.g., Extremera & Fernández-Berrocal, 2005; Palmer, Donaldson, & Stough, 2002; Salovey, Mayer, Goldman, Turvey, & Palfai, 1995).

To determine whether TEI predicts early career success after controlling for the influence of cognitive abilities and personality, we proposed the following hypotheses:

Hypothesis 1: Self-report measures of TEI will show significant effects after controlling for the effects of GMA and personality and will significantly predict career success (salary and career satisfaction) in the early stage.

Hypothesis 2: Of the TEI dimensions assessed, TMMS repair and TMMS clarity will be positively associated with career success and will predict most of the variance in career success when IQ and personality traits are controlled statistically.

Method

Participants

The study was conducted on a sample of 130 university graduates who were in employment at the time of the study. Of these, 64% were women and 36% men, with a mean age of 26.4 years (standard deviation [SD] = 4.38). These percentages are similar to the sex distribution of the student population at this university. The sample consisted of graduates participating in a survey conducted of 339 university graduates from the University of Alicante (Spain) 3 years after completion of their studies. These 339 students had participated 3 years earlier in a study that assessed their personal and socioemotional competences, having been selected through a stratified random sampling system proportional to the number of students enrolled in each of the fields of science and technology (25.7%), social sciences (18.9%), education (24.5%), biohealth (15.9%), and humanities (6.5%).

Measures

Test of “g,” Scale 3

To measure GMA, we used the test of “g,” Scale 3 by Cattell and Cattell (1994; adapted to Spanish by Cordero, De la Cruz, González, & Seisdedos, 1997). Cattell’s test of g is one of the most widely used intelligence tests. This collectively applied scale consists of four subtests that assess fluid intelligence: series, classification, matrices, and conditions, enabling us to obtain the IQ of the sample. Split-half reliability in the validation sample was .78. The internal consistency coefficient, Cronbach’s α, was .83, obtained in the initial sample (n = 339) used in this study.

Big Five Inventory (NEO Five Factor Inventory [NEO-FFI])

The 60 items forming the Spanish version of the NEO-FFI (Costa & McCrae, 1992) was administered to measure personality traits. This is a self-report measure of five personality dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness. Participants indicate their level of agreement with each item on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). The internal consistency reliability coefficient, Cronbach’s α, of the Spanish version of the NEO-FFI, adapted by Cordero, Pamos, and Seisdedos (2008), ranges between 0.82 for agreeableness and 0.90 for neuroticism, similar to the English version. Internal consistency coefficients, Cronbach’s αs, obtained in the initial sample (n = 339) used in this study, were .86, .83, .76, .75 and .82 for Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness, respectively.

Evidence of construct validity obtained in the initial sample used in this study (n = 339) showed the adequacy of exploratory factor analysis (Kaiser-Meyer-Olkin [KMO] = .867; χ² = 1687.33, p < .000). The exploratory factor analysis (principal components with varimax rotation) evidenced a five-factor solution in which all 60 items loaded adequately (>.30) on their intended factor, as theoretically expected.

TMMS-24

The Spanish short version (24 items; Fernández-Berrocal, Extremera, & Ramos, 2004) of the TMMS-48 by Salovey, Mayer, Goldman, Turvey, and Palfai (1995) measures three factors: (a) attention to feelings, (b) clarity of feelings, defined as understanding one’s feelings, and (c) mood repair, defined as attempts to maintain pleasant moods or repair unpleasant ones. Participants indicate their level of agreement with each statement on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). The scale has acceptable psychometric characteristics. For example, Salovey et al. reported adequate internal consistency (attention, α = .86; clarity, α = .87; and repair, α = .82), and good convergent and discriminant validity for the subscales. The Spanish short version (24 items) of the TMMS (Fernández-Berrocal et al., 2004) was administered to a sample of 292 Spanish undergraduates, aged between 18 and 57 years, and the data were subjected to a principal component factor analysis with varimax rotation. The analysis showed a three-factor solution with attention, clarity, and repair as dimensions, in agreement with the findings reported by Salovey et al.. The internal consistency of the subscales was high (attention, α = .90; clarity, α = .90; and repair, α = .86). Test–retest reliability after 4 weeks ranged from .60 (attention) to .83 (repair). The internal consistency coefficients, Cronbach’s α, obtained in the sample used in this study (n = 339**) were as follows: attention (α = .89), clarity (α = .86), and repair (α = .85). The exploratory factor analysis (principal components with varimax rotation) carried out on the data obtained in the sample used in this study (n = 339***) showed a three-factor solution, corresponding to the dimensions of attention (19.48% explained variance), clarity (17.39%), and repair (16.55%). The rotated factor matrix was examined to interpret the loadings of each item on the factor on which it was hypothesized to load. The range of item loadings by factor were as follows: attention, .64 to .79; clarity, .60 to .78; and repair, .57 to .85. These results are in agreement with findings for the English version (Salovey et al., 1995), and findings for the Spanish version of the TMMS (Fernández-Berrocal et al., 2004).

Career Success Criteria

To assess extrinsic career success, we used the items corresponding to salary from a specific questionnaire based on the employment questionnaires developed as part of the CHEERS (Schomburg & Teichler, 2006) and REFLEX studies (Agencia Nacional de Evaluación de la Calidad y Acreditación, 2007), which collect detailed information on aspects such as the degree course studied, transition from education to employment, first job following graduation, employment history, current post, and the competences considered essential for entry to the labor market. The questionnaire consisted of 43 questions organized into seven sections covering various aspects related to training received, transition to employment, competences, and satisfaction, among others. Salary level was measured as gross monthly income, divided into seven categories: (1) less than 600 Euros (US$787); (2) between 600 and 1,000 Euros (US$787 to 1,312); (3) between 1,000 and 1,200 Euros (US$1,312 to 1,575); (4) between 1,200 and 1,500 Euros (US$1,575 to 1,969 dollars); (5) between 1,500 and 1,800 Euros (US$1,969 to 2,362); (6) between 1,800 and 2,000 Euros (US$2,362 to 2,625 dollars) and (7) more than 2,000 Euros (US$2,625). Due to the sensitive nature of income data, we used income levels rather than real euro/dollar values for each participant. A similar scale was used by Judge, Higgins, Thoreson, and Barrick (1999).

The intrinsic criterion of success (career satisfaction) was obtained from the sum of responses to items 30, 37, and 39, which assessed the degree of satisfaction with their careers on a 5-point scale where 1 = low and 5 = high. Cronbach’s α of internal consistency was .79.

Procedure

The participants were enrolled in a 3-year longitudinal study. In the first phase, conducted in the academic year 2008–2009 when students were enrolled in the final year of their degree course, the NEO-FFI questionnaire was administered together with the Test of factor g and the TMMS-24 scale, to an initial sample of 906 subjects. In the second phase, which took place in the academic year 2011–2012, the initial sample was reduced to 339 graduates, comprising subjects who had participated in the first phase of the study, could be contacted 3.5 years after graduation and who were willing to continue participating. These completed a questionnaire designed to collect information about the employment status of the graduates studied previously and their entry into the workforce. The questionnaire, which required no more than 30 min to fill in, was administered online to be completed within a maximum period of 3 months from receipt.

Results

The correlations between all measures, with means and SDs, are shown in Table 1. As can be seen in this table, IQ was significantly and negatively correlated with neuroticism (−.23) and positively with extraversion (.29), but not with either salary or career satisfaction. Only one of the personality factors, neuroticism, was associated, negatively, with one of the success criteria, salary (−.24). Regarding TEI, only TMMS repair was positively associated with both criteria, salary (.26) and career satisfaction (.21). Finally, correlations between TEI dimensions and personality traits were generally significant, with coefficients that ranged between −.47 and .42.

Table 1.

Correlation Matrix of all Measures and Descriptive Statistics.

	M	SD	1	2	3	4	5	6	7	8	9	10
1. IQ	102.4	15.5	1
2. Neuroticism	31.9	8.3	−.23*	1
3. Extraversion	45.6	6.7	.29**	−31**	1
4. Openness	43.22	7.0	−.01	−.05	.22*	1
5. Agreeableness	41.45	6.9	−.08	−.18	.21*	.35**	1
6. Conscientiousness	46.2	6.3	.01	−.26**	.23*	.23*	.30**	1
7. TMMS attention	26.34	5.63	.09	.27**	.16	.20*	.13	.10	1
8. TMMS clarity	26.47	5.74	.07	−.45**	.42**	.19	.21*	.35**	.26**	1
9. TMMS repair	28.53	6.08	.14	−.47**	.33**	.38*	.21*	.33**	.14	.52**	1
10. Salary	1372	536	.01	−.24*	.06	−.17	−.00	.12	.01	−.09	.26*	1
11. Career satisfaction	9.49	2.6	.00	−.12	.11	−.15	.07	.14	−.04	.08	.21*	.57**	1

Note. TMMS = Trait Meta-Mood Scale.

*p < .05, **p <. 01.

To examine the predictive and incremental validity of TEI dimensions over IQ and the Big Five personality traits for “salary” and “occupational level,” we carried out hierarchical regression analyses (Table 2). For each regression model, a career success criterion (salary or career satisfaction) was the dependent variable, with general intelligence, personality, and TEI dimensions as independent variables (Step 1 = IQ; Step 2 = personality; and Step 3 = TEI dimensions).¹

Table 2.

Results of Hierarchical Multiple Regression Analyses of Initial Career Success.

	Salary		Career satisfaction
	β	▵R ²	β	▵R ²
Step 1: Mental ability		.00 (p = .89)		.00 (p = .93)
IQ	.01		.01
Step 2: Personality traits		.11 (p = .06)		.08 (p =.17)
IQ	−.05		−.03
Neuroticism	−.23*		−.06
Extraversion	.04		.11
Openness	−.21*		−.24*
Agreeableness	−.01		.08
Conscientiousness	.11		.13
Step 3: Trait emotional intelligence		.09* (p = .03)		.06 (p = .11)
IQ	−.02		−.03
Neuroticism	.00		.07
Extraversion	−.03		.11
Openness	−.30**		−.33**
Agreeableness	.01		.10
Conscientiousness	.04		.11
TMMS attention	−.12		−.06
TMMS clarity	.18		−.09
TMMS repair	.30*		.33**
Total adjusted R ²		.20		.14

Note. TMMS = Trait Meta-Mood Scale; N = 103. Change in R ² is based on adjusted R ².

*p < .05, **p < .01.

As shown in Table 2, TEI added significant variance (9%) to the prediction of salary above and beyond transient IQ and the Big Five personality traits as predictors. In the final step, “openness” (β = −.30; p = .00), and TMMS repair (β = .30; p = .02) appeared as significant factors.

With respect to career satisfaction, the model was not significant, although in the case of salary, openness (β = −.33; p = .00) and TMMS repair appeared as significant factors in the last step (β = .33; p = .02).

Discussion

In the present study, an analysis was conducted of the effects of TEI on extrinsic and intrinsic indicators of professional success in the early career stage, after controlling for the effects of GMA and personality traits. The results show that the increase in explained variance provided by TEI dimensions (especially TMMS repair) was only significant for salary (9%) and was slightly above that obtained in other studies (Bastian et al., 2005; Law, Wong, & Song, 2004). In the case of career satisfaction, TEI dimensions did not contribute significantly, although this criterion was positively predicted by TMMS repair and negatively by Openness.

Thus, only the trait emotional dimension of TMMS repair contributed beyond GMA and personality traits to salary level in the early career stage, while this contribution was not significant for level of career satisfaction. Our results in the case of salary are consistent with those obtained in studies that support the incremental validity of TEI over cognitive abilities and personality traits, but in disagreement with others reporting unclear results (Rode et al., 2008).

Our findings reinforce the importance of the emotional regulation dimension of TMMS repair, represented by aspects such as “having a mostly optimistic outlook, trying to think about pleasant things, trying to think positively or trying to maintain a good mood,” which was more closely related to salary than to career satisfaction, so that individuals who show a greater capacity to overcome negative events achieve higher levels of salary early in their career. The fact that this dimension of emotional regulation adds significant variance to the prediction of salary over and above the other factors reinforces the importance of this dimension in the prediction not only of this type of criteria but also of others such as entrepreneurial self-efficacy (Salvador, 2008), the quality of one’s interpersonal relationships (Lopes, Salovey, & Strauss, 2002) and life satisfaction (Extremera & Fernández-Berrocal, 2005).

Meanwhile, the TEI dimension of TMMS clarity, described by indicators such as “being clear about feelings, being able to define them, knowing how one feels or understanding one's emotions,” did not seem to be associated with any of the criteria, in contrast to associations found for the other criteria (Extremera & Fernández-Berrocal, 2005; Salovey et al., 1995).

Therefore, these results partially confirm the first hypothesis (for salary rather than for career satisfaction) and also provide partial support for the second hypothesis, since TMMS clarity did not appear for any of the criteria.

As regards GMA, our results show that IQ does not predict either salary or career satisfaction in the early career stages, in contrast to results reported by other authors who have found positive relationships between general intelligence and career success (Dreher & Bretz, 1991; Judge, Higgins, Thoreson, & Barrick, 1999; O’Reilly & Chatman, 1994), but consistent with other studies that found no relationship between the constructs (Rode et al., 2008) or found that this relationship was moderate (Ng, Eby, Sorensen, & Feldman, 2005) or negative (Ganzach, 1998).

The negligible direct contribution of general intelligence as a predictor of the criteria may have been due to (a) the type of sample studied (graduates whom it would be reasonable to assume have a high IQ), (b) the interaction between IQ and EI, in such a way that the correlation between variables and criteria varied depending on the IQ level (Coté & Miners, 2006), (c) the distal nature of IQ compared to EI in determining success (Spurk & Abele, 2011), or (d) the type of criteria on which the prediction equations were based (job performance compared to extrinsic career success).

On the other hand, the absence of a correlation in this study between general intelligence and EI is consistent with the results obtained in other studies (Davies, Stankov, & Roberts, 1998; Derksen, Kramer, & Katzko, 2002; Fox & Spector, 2000) and supports the differential validity of EI.

The results also show the importance of the personality trait openness as a negative predictor of career success, consistent with some previous studies (Bozionelos, 2004; Gelissen & De Graaf, 2006; Seibert & Kraimer, 2001) but in disagreement with others, which found a weak to positive relationship with salary, promotion, or job performance (Furnham, Taylor, & Chamorro-Premuzic, 2008; Ng et al., 2005; Palifka, 2009; Van der Linden, Te Nijenhuis, & Bakker, 2010). It therefore appears that in the early stages of a career, diffuse or wide-ranging interests may have a negative effect on achieving a higher salary.

As regards the other personality traits, the only significant relationship identified in our study was for neuroticism, which was associated negatively with salary, consistent with other studies (Salgado, 1998). This might be explained by the barrier that could arise as a result of focusing too much on one’s own emotions rather than on employment goals that lead to professional achievement. Thus, subjects who worry too much achieve lower levels of career satisfaction, which would clarify the positive significant correlation between TMMS attention and neuroticism. The fact that only this criterion, and not salary, was affected indicates that these criteria have differential characteristics that render it difficult to generalize the relationship between TEI and general criteria.

When evaluating results, it is important to consider the study’s strengths and limitations. The main limitation of this study concerns sample size. The present study may have lacked sufficient power to corroborate the statistical significance of the relationships that have been found using larger samples.

Besides this, one of the study’s strengths is that the present research was based on longitudinal data; thus, conclusions regarding possible causal relationships can be made. Its importance also resides in indicating for the first time the relationship between TEI and career success criteria in the early stage. We also believe that this study has made a 2-fold contribution. On one hand, the results recommend the use of EI trait measures as a predictor of professional success indicators, and one practical implication of the present study is that the results can be used in the screening and selection process, as well as for guidance and orientation. On the other hand, it serves as a basis for the development of training actions related to socioemotional competences and aimed at University students. In considering the theoretical implications of our findings, these have important consequences as regards understanding the influence of individual differences on career success.

Recommendations for future studies include the use of emotion-related cognitive measures via performance-based tests. In addition, variables that may moderate the impact of IE, such as cognitive and personality variables, as well as external variables such as job characteristics, should also be considered. Furthermore, in order to more fully understand the complex issue of career success, the results obtained in samples of professionals in the early stages of their careers are compared with those obtained for samples of professionals with more experience.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study formed part of research project ref. PSI2009-12696, funded by the Spanish Ministry of Science and Innovation.

Note

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