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Can emotional intelligence be improved? A randomized experimental study of a business-oriented EI training program for senior managers

Raquel gilar-corbi, teresa pozo-rico, bárbara sánchez, juan-luís castejón.

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Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected] (RGC); [email protected] (TPR)

Received 2018 Sep 11; Accepted 2019 Oct 9; Collection date 2019.

This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Purpose: This article presents the results of a training program in emotional intelligence. Design/methodology/approach: Emotional Intelligence (EI) involves two important competencies: (1) the ability to recognize feelings and emotions in oneself and others, and (2) the ability to use that information to resolve conflicts and problems to improve interactions with others. We provided a 30-hour Training Course on Emotional Intelligence (TCEI) for 54 senior managers of a private company. A pretest-posttest design with a control group was adopted. Findings: EI assessed using mixed and ability-based measures can be improved after training. Originality/value: The study’s results revealed that EI can be improved within business environments. Results and implications of including EI training in professional development plans for private organizations are discussed.

Introduction

This research study focused on EI training in business environments. Accordingly, the aim of the study was to examine the effectiveness of an original EI training program in improving the EI of senior managers. In this article, we delineate the principles and methodology of an EI training program that was conducted to improve the EI of senior managers of a private company The article begins with a brief introduction to the main models of EI that are embedded with the existing scientific literature. This is followed by a description of the EI training program that was conducted in the present study and presentation of results about its effectiveness in improving EI. Finally, the present findings are discussed in relation to the existing empirical literature, and the limitations and conclusions of the present study are articulated.

Defining EI

Various models of emotional intelligence (EI) have been proposed. The existing scientific literature offers three main models of EI: mixed, ability, and trait models. First, mixed models conceptualize EI as a combination of emotional skills and personality dimensions such as assertiveness and optimism [ 1 , 2 ]. Thus, according to the Bar-On model [ 3 ], emotional-social intelligence (ESI) is a multifactorial set of competencies, skills, and facilitators that determine how people express and understand themselves, understand and relate to others, and respond to daily situations The construct of ESI consists of 10 key components (i.e., self-regard, interpersonal relationships, impulse control, problem solving, emotional self-awareness, flexibility, reality-testing, stress tolerance, assertiveness, and empathy) and five facilitators (optimism, self-actualization, happiness, independence, and social responsibility). Emotionally and socially intelligent people accept and understand their emotions; they are also capable of expressing themselves assertively, being empathetic, cooperating with and relating to others in an appropriate manner, managing stressful situations and changes successfully, solving personal and interpersonal problems effectively, and having an optimistic perspective toward life. Second, ability models of EI focus on the processing of information and related abilities [ 3 ]. Accordingly, Mayer and Salovey [ 4 ] have conceptualized EI as a type of social intelligence that entails the ability to manage and understand one’s own and others’ emotions. Indeed, this implies that EI also entails the ability to use emotional information to manage thoughts and actions in an adaptive manner [ 5 ]. Third, the trait EI approach understands EI as emotion-related information [ 6 ]. According to trait models, EI refers to self-perceptions and dispositions that can be incorporated into fundamental taxonomies of personality. Therefore, according to Petrides and Furnham [ 7 ], trait EI is partially determined by several dimensions of personality and can be situated within the lower levels of personality hierarchies. However, it is a distinct construct that can be differentiated from other personality constructs. In addition, the construct of trait EI includes various personality dispositions as well as the self-perceived aspects of social intelligence, personal intelligence, and ability EI. The following facets are subsumed by the construct of trait EI: adaptability, assertiveness, emotion perception (self and others), emotion expression, management (others), and regulation, impulsiveness (low), relationships, self-esteem, self-motivation, social awareness, stress management, trait empathy, happiness, and optimism [ 7 ]. Finally, as Hodzic et al. [ 8 ] have indicated, most existing definitions of EI permit us to draw the conclusion that EI is a measurable individual characteristic that refers to a way of experiencing and processing emotions and emotional information. It is noteworthy that these models are not mutually exclusive [ 7 ].

Effects of EI on different outcomes

EI has been found to be related to workplace performance in highly demanding work environments (see e.g. [ 9 ]). Consequently, companies, entities, and organizations tend to recognize the importance of EI, promote it on a daily basis to facilitate career growth, and recruit those who possess this ability. [ 10 ].

With regard to research that has examined the EI-performance link, Van Rooy and Viswesvaran [ 11 ] conducted a metanalytic study to examine the predictive power of EI in the workplace. They found that approximately 5% of the variance in workplace performance was explained by EI, and this percentage is adequately significant to increase savings and promote improvements within organizations. In addition, the authors concluded that further in-depth investigations are needed to comprehensively understand the construct of EI.

However, the EI-performance link must be interpreted with caution. Specifically, Joseph and Newman [ 12 ] examined emotional competence in the workplace and found that EI predicts performance among those with high emotional labor jobs but not their counterparts with low emotional labor jobs. In addition, they indicated that further research is required to delineate the relationship between EI and actual job performance, gender and race differences in EI, and the utility of different types of EI measures that are based on ability or mixed models in training and selection. Accordingly, Pérez-González and Qualter [ 13 ] have underscored the need for emotional education. Further, Brasseur et al. [ 14 ] found that better job performance is related to EI, especially among those with jobs for which interpersonal contact is very important.

It is noteworthy that EI is positively related to job satisfaction. Accordingly, Chiva and Alegre [ 15 ] found that there was an indirect positive relationship between self-reported EI (i.e., as per mixed models) and job satisfaction. A total of 157 workers from several companies participated in this study. These findings suggest that people with higher levels of EI are more satisfied with their jobs and demonstrate a greater capacity for learning than their counterparts with lower levels of EI.

Similarly, Sener, Demirel, and Sarlak [ 16 ] adopted a mixed model of EI and examine its effect on job satisfaction. They found that individuals with strong emotional and social competencies demonstrated greater self-control. A total of 80 workers participated in this study. They were able to manage and understand their own and others’ emotions in an intelligent and adaptive manner in their personal and professional lives.

In addition, EI (i.e., as per mixed models) predicts job success because it influences one’s ability to deal with environmental demands and pressures [ 17 ]. Therefore, it has been contended that several components of EI (i.e., as per mixed models) contribute to success and productivity in the workplace [ 18 ]; future research studies should extend this line of inquiry. Several studies have shown that people with high levels of ability EI communicate in an interesting and assertive manner, which in turn makes others feel more comfortable in the workplace [ 19 ]. In addition, it has been contended that EI (i.e., as per mixed models) plays a valuable role in group development because effective teamwork occurs when team members possess knowledge about the strengths and weaknesses of others and the ability to use these strengths when necessary [ 15 , 20 ]. It is especially important for senior managers to demonstrate high levels of EI because they play a predominant role in team management, leadership, and organizational development.

Finally, studies that have examined the relationship between EI and wellbeing have found that ability EI is a predictor of professional success, wellbeing, and socially relevant outcomes [ 21 – 23 ]. Extending this line of inquiry, Slaski and Cartwright [ 24 ] investigated the relationship between EI and the quality of working life among middle managers and found that higher levels of EI is related to better performance, health, and wellbeing.

EI and leadership

The actions of organizational leaders play a crucial role in modulating the emotional experiences of employees [ 25 ]. Accordingly, Thiel, Connelly, and Griffith [ 26 ] found that, within the workplace, emotions affect critical cognitive tasks including information processing and decision making. In addition, the authors have contended that leadership plays a key role in helping subordinates manage their emotions. In another study, Batool [ 27 ] found that the EI of leaders have a positive impact on the stress management, motivation, and productivity of employees.

Gardner and Stough [ 28 ] further investigated the relationship between leadership and EI among senior managers and found that leaders’ management of positive and negative emotions had a beneficial impact on motivation, optimism, innovation, and problem resolution in the workplace. Therefore, the EI of directors and managers is expected to be positively correlated with employees’ work motivation and achievement.

Additionally, EI competencies are involved in the following activities: choosing organizational objectives, planning and organizing work activities, maintaining cooperative interpersonal relationships, and receiving the support that is necessary to achieve organizational goals [ 29 ]. In this regard, some authors have provided compelling theoretical arguments in favor of the existence of a relationship between EI and leadership [ 30 – 34 ]. In this way, several researches [ 30 – 34 ] show that EI is a core and key variable positively related to effective and transformational leadership and this is important for positive effects on job performance and attitudes that are desirable in the organization.

Further, people with high levels of EI are more capable of regulating their emotions to reduce work stress [ 35 ]; thus, it is necessary to emphasize the importance of EI in order to meet the workplace challenges of the 21st century.

In conclusion, EI competencies are considered to be key qualities that individuals who occupy management positions must possess [ 36 ]. Further, EI transcends managerial hierarchies when an organization flourishes [ 37 ]. Finally, emotionally intelligent managers tend to create a positive work environment that improves the job satisfaction of employees [ 38 ].

EI trainings

Past studies have shown that training improves the EI of students [ 22 , 39 , 40 – 44 ], employees [ 45 – 47 ], and managers [ 48 – 52 ]. More specifically, within the academic context, Nelis et al. [ 22 ] found that group-based EI training significantly improved emotion identification and management skills. In another study, Nelis et al. [ 39 ] found that EI training significantly improved emotion regulation and comprehension and general emotional skills. It also had a positive impact on psychological wellbeing, subjective perceptions of health, quality of social relations, and employability. Similarly, several studies that have been conducted within the workplace have shown that EI can be improved through training [ 45 – 52 ] and have underscored the key role that it plays in effective performance [ 53 , 54 ].

In addition, two relevant metanalyses [ 8 , 55 ] concluded that there has been an increase in research interest in EI, recognition of its influence on various aspects of people’s lives, and the number of interventions that aim to improve EI. Relatedly, Kotsou et al. [ 55 ] and Hodzic et al. [ 8 ] reviewed the findings of past studies that have examined the effects of EI training to explore whether such training programs do indeed improve EI.

First, Hodzic et al. [ 8 ] concluded that EI training has a moderate effect on EI and that interventions that are based on ability models of EI have the largest effects. In addition, the improvements that had resulted from these interventions were found to have been temporally sustained.

Second, the conclusions of Kotsou et al.’s [ 55 ] systematic review of the literature on the effectiveness of EI training make it evident that more rigorous and controlled studies are needed to permit one to draw concrete conclusions about whether training improves ability EI. Studies that had adopted mixed models of EI tended to more consistently find that training improves EI. Accordingly, the results of Kotsou et al.’s [ 55 ] metanalytic study revealed that EI training enhances teamwork, conflict management, employability, job satisfaction, and work performance.

Finally, it is necessary to identify and address the limitations of past interventions in future studies to improve their quality and effectiveness.

Purpose of the study

In the systematic review conducted by Kotsou et al. [ 55 ] regarding research published on interventions to improve EI in adults, one out of five studies with managers, was performed on a sample of middle managers, without randomization, with an inactive control group, no immediate measures after the training, and only one evaluation was performed six months after the training. In the other four studies collected in Kotsou et al.’s systematic review [ 55 ], only one study utilized a control group (inactive control group), one employed randomizations, and two studies performed follow-up measures six months after the intervention.

The two metanalyses confirmed and identified some problems or gaps we have tried to overcome in the present study. For this reason, in our study, we propose to deepen the assessment of EI training for senior managers, aiming to overcome most of the limitations mentioned in the studies of Kotsou et al. [ 55 ] and Hodzic et al. [ 8 ] by implementing the following: 1) Include a control group (waiting list group); 2) Conduct follow-up measurements (12 months later); 3) Employ an experimental design; 3) Include a workshop approach with group discussions and interactive participation; 4) Identify specific individual differences (i.e., age, gender) that might determine the effects of interventions; and 5) Use self-report and ability measures. For these reasons, two different ways of evaluating EI have been selected in this study to assess the emotional competencies applied within the labor and business world to solve practical problems: the EQ-i questionnaire [ 2 ], based on mixed models to provide a self-perceived index of EI, and the Situational Test of Emotional Management (STEM) and the Situational Test of Emotional Understanding (STEU) [ 56 ] based on the ability model. Thus, including two different EI measure we aim at obtaining a more reliable validation of the intervention used.

Therefore, the objective of our study was to investigate whether EI can be improved among employees who occupy senior management positions in a private company. Thus, the research hypothesis was that participation in the designed program would improve EI among senior managers.

EI training development

The Course on Emotional Intelligence (TCEI) was created to provide senior managers with emotional knowledge and practical emotional skills so that they can apply and transfer their new understanding to teamwork and find solutions to real company problems and challenges. In this way, TCEI prepares workers to use the emotional learning resources appropriate to each work situation. In addition, TCEI combines face-to-face work sessions with a cross-sectional training through an e-learning platform. For more details, see S1 Appendix 1.

According to Mikolajczak [ 57 ], three interrelated levels of emotional intelligence can be differentiated: a) conceptual-declarative emotion knowledge, b) emotion-related abilities, and c) emotion-related dispositions. The TCEI aims at developing emotional skills, which are included on the second level of Mikolajczak’s model. Moreover, the present study uses the mixed model and the ability model measures to assess the level of EI. In using these measures, it is possible to assess the second level of Mikolajczak’s model. Pérez-González and Qualter [ 13 ] also suggest that activities related to ability EI should be included in emotional education programs.

Thus, this EI program was designed to allow senior managers to make use of their understanding and management of emotions as a strategy to assist them in facing the challenges within their work environment and managing their workgroups. Following the recommendation of Pérez-Gonzáles and Qualter, the training intervention methodology is founded in DAPHnE key practices [ 13 ]. It is important to emphasize that this training is grounded in practicality since it works based on the resolution of real cases, utilizing participative teaching-learning techniques and cooperative learning, while promoting the transfer of all aspects of EI and applied to various situations that can occur in the workplace. The e-learning system in the Moodle platform also provides an added value since it allows the creation of an environment providing exposure to professional experiences and continuous training. This type of pedagogical approach based on skills training and mediated through e-learning is a methodology that emerged in the 1990s when business organizations sought to create environments better suited to improving the management of large groups of employees. After its success, it began to be used in other contexts, including higher education and organizational development [ 58 – 60 ].

Finally, in order to justify the chosen training, it is important to note that the following official competencies for senior managers have been designated by the company:

Supervise the staff and guarantee optimum employee performance by fostering a motivational working environment where employees receive the appropriate support and respect and their initiatives are given the consideration they deserve.

Make decisions and promote clear goals, efficient leadership, competitive compensation, and acknowledgment of the employees’ achievements.

Justify their decisions to executives and directors, explaining how they have ensured training by creating opportunities for appropriate professional development for all employees and how they have facilitated conditions for a better balance in achieving the company’s objectives.

In conclusion, considering the above-mentioned professional competencies required, senior managers were selected as participants in this study since they need to possess and apply aspects related to EI in order to accomplish their leadership and staff management responsibilities.

Participants

The company participating in this study was an international company with almost 175 years of history that occupies a select position in a branch of industry in the natural gas value chain, from the source of supply to market, including supply, liquefaction, shipping, regasification, and distribution. The company is present in over 30 countries around the world.

This study was conducted involving a sample of 54 senior managers selected from a company in a European country. The sample was extracted from the entire population of senior managers within this company following a stratified random sampling procedure, taking into account the gender of the population in order to select 50% of each gender.

The mean age of participants was 37.61 years (standard deviation = 8.55) and the percentage of female senior managers was 50%. For evaluation purposes, these employees were randomly divided into two groups: the experimental group ( n = 26; mean age = 35.57 (7.54); 50% women) and the control group ( n = 28; mean age = 39.50 (9.11); 50% women). The control group received EI training after the last data collection.

Initially, a group of senior managers from the company was selected to participate in the study, as they are employees who need a special domain of EI due to the competencies assigned to their professional category. In all cases, informed consent was requested for their participation in the study.

Assignment of participants to each condition, experimental or control, was performed using a random-number program. In addition, to avoid the Hawthorne effect, participants were not told if they were assigned to the experimental or control group; only their consent to participate in research on the development of EI was asked. Participants from the control group completed the same evaluations as the training group but were not exposed to the training.

The scales were administered during the pretest phase (Time 1) on an online platform for the experimental and control groups. On average, approximately 90 minutes were needed to complete the tests.

After the data were collected in the pre-test phase, only the experimental group participated in the TCEI over seven weeks, and they received a diploma.

Later, the scales were administered during the posttest phase (Time 2). Similarly, we collected the same data one year later (Time 3). A lapse of one year was allowed to pass because all training programs carried out in this company are re-evaluated one year later to determine whether improvements in employees’ skills were maintained over time. In fact, this demonstrates a clear commitment to monitoring the results achieved. Other studies have also used reevaluations of their results. For example, according to Nelis et al. [ 22 ] and Nelis et al. [ 39 ], the purpose of their studies was to evaluate whether trait EI could be improved and if these changes remained. To accomplish this, the authors performed three assessments: prior to the intervention, at the end of the intervention, and six months later. Therefore, as recommended by Kirkpatrick [ 61 ], research on the effectiveness of training should also include a long-term assessment of skills transfer.

Finally, is important to remark that all participants were properly informed of the investigation, and their written consent was obtained. All methods were performed in accordance with the relevant guidelines and regulations and the study was approved by University of Alicante Ethics Committee (UA-2015-07-06) and carried out in accordance with the relevant guidelines and regulations.

As mentioned before, two different ways of defining and evaluating EI were selected for this study: (1) EQ-i, based on mixed models, and (2) the STEM/STEU questionnaires, based on the ability model of EI.

The Emotional Quotient Inventory [ 2 ]

To measure EI based on the mixed models, the short version of the EQ-i was used, which comprises 51 self-referencing statements and requires subjects to rate the extent to which they agree or disagree with each statement on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). An example item is the following; “In handling situations that arise, I try to think of as many approaches as I can.” The EQ-i comprises five factors: Intrapersonal EI and Self-Perception, Interpersonal EI, Adaptability and Decision Making, General Mood and Self-Expression, Stress Management, and a Total EQ-i score, which serves as a global EI measure. The author of this instrument reports a Cronbach’s alpha ranging from .69 to .86 for the 5 subscales [ 2 , 62 ] and the Cronbach’s alpha of the Emotional Quotient Inventory was .80 for the present sample of senior manager.

Situational Test of Emotional Understanding (STEU) and Situational Test of Emotion Management (STEM) [ 63 ]

Two tests were used to measure EI based on the ability model. Emotion understanding was evaluated by the short version of the Situational Test of Emotional Understanding (STEU) [ 63 ]. This test is composed of 25 items that present an emotional situation (decontextualized, workplace-related, or private-life-related). For each item, participants have to choose which emotion will most likely elicit the described situation. Cronbach’s alpha of STEU is .83 [ 63 ] and the Cronbach’s alpha of the Situational Test of Emotional Understanding was .86 for the present sample of senior manager. An example item is the following: “An unwanted situation becomes less likely or stops altogether. The person involved is most likely to feel: (a) regret, (b) hope, (c) joy, (d) sadness, (e) relief” (in this case, the correct answer is “relief”).

On the other hand, emotion management was evaluated by the short version of the Situational Test of Emotion Management (STEM) [ 63 ]. This test is composed of a 20-item situational judgment test (SJT) that uses hypothetical behavioral scenarios followed by a set of possible responses to the situation. Respondents must choose which option they would most likely select in a “real” situation. Cronbach’s alpha of STEM is .68 [ 63 ] and the Cronbach’s alpha of the Situational Test of Emotion Management was .84 for the present sample of senior manager. An example item is the following: “Pete has specific skills that his workmates do not, and he feels that his workload is higher because of it. What action would be the most effective for Pete? (a) Speak to his boss about this; (b) Start looking for a new job; (c) Be very proud of his unique skills; (d) Speak to his workmates about this.”

TCEI content and organization

The program schedule spanned seven weeks with a face-to-face session of 95 minutes each week, which was delivered by one of the researchers specifically trained for this purpose. All the experimental group participants were taught together in these sessions. The content of each session was the following:

1st Session : Introduction. The objectives and methodology of the training were explained to participants.

2nd Session : Intrapersonal EI and self-perception. Trainees learned to identify their own emotions.

3rd Session : Interpersonal EI. Participants learned to identify others’ emotions.

4th Session : Adaptability and decision making. The objective was to improve trainees’ ability to identify and understand the impact that their own feelings can have on thoughts, decisions, behavior, and work performance resulting in better decisions and workplace adaptability.

5th Session : General mood and self-expression. Trainees worked on expressing their emotions and improving their skills to effectively control their mood.

6th Session : Stress management. Participants learned EI skills to manage stress effectively.

7th Session : Emotional understanding and emotion management. Trainees learned skills to effectively manage their emotions as well as skills that influence the moods and emotions of others.

In addition, access to the virtual environment (Moodle platform) was required after each face-to-face session. The time spent in the platform was registered, with a minimum of five hours required per week.

The virtual environment allowed the researcher to review all the content completed in each face-to-face session.

All of the EI abilities included in the virtual part of the training have been previously used in the face-to-face part; thus, virtual training is simply a method used to consolidate EI knowledge. In fact, the virtual environment has the same function as completing a workbook about the information presented during the face-to-face session. However, the added advantage of working in an e-learning environment is that all of the trainers are connected and can share their tasks and progress with others. At times, in addition to reviewing the contents of the previous session, the e-learning environment also introduces some important terms for the next session utilizing the principles of the well-known flipped classroom methodology. In short, the following activities were carried out through the Moodle platform to consolidate the participants’ knowledge:

1st Session: Participants were informed that e-learning would be part of the training in order to consolidate EI knowledge.

2nd Session: Participants explored the skills of Intrapersonal EI and self-perception in the virtual environment through discussion forums.

3rd Session: Participants learned the skills of identifying others’ emotions and utilizing this emotional information for decision-making. This information was summarized in the virtual environment through discussion forums.

4th Session: Participants sharpened their skills of adaptability and decision-making through the production of innovative ideas and the utilization of critical thinking skills in assessing the impact that their own feelings can have on others’ work performance. Trainees learned how to express their own emotions, as well as the skill of effectively controlling their mood, through the resolution of practical cases in the virtual environment; in these cases, innovative ideas and critical thinking skills were required in order to make better decisions during emotionally impactful; situations. In addition, trainees utilized the forum to reflect on why their own emotional regulation is important for ensuring long-term workplace adaptability.

5th Session: Verbal quiz, discussion, and forum contribution. Trainees participated in an online debate about key emotional skills in order to understand how to apply them in a real work environment. In particular, the debate focused on regulating the self-expression skill and equilibrating the general mood when there are difficult situations within the company. In this way, the participants identified the skills required to effectively manage the stress experienced in order to maintain a positive mood A discussion about common stressful situations at work was carried out in the virtual environment, and strategies for regulating the mood during critical work situations were shared.

6th Session: Discussion of ideas related to EI. Trainees participated in an online debate about key emotional skills in order to understand how to apply stress management skills to the real work environment. It was necessary to share previous work experiences where stress was a significant challenge and reevaluate the emotionally intelligent way to deter stress and maintain a balanced senior manager life.

7th Session: Participants concluded the training on target strategies to effectively manage their emotions as well as skills that influence the moods and emotions of others. This session, therefore, was a period for feedback where brief answers to specific doubts were provided. In addition, the outcomes of the training were established by the participants. Finally, senior managers were encouraged to stay connected through the Moodle platform in order to resolve future challenges together using the EI skills learned and internalized during the training period.

Data analysis

An experimental pretest-posttest with a control group design was adopted. Under this design, multivariate variance analysis (MANOVA) and univariate variance analysis (ANOVA) of repeated measures were performed, in which the measures of dependent variables were treated as variables evaluated within the same subjects, and groups operated as variables between subjects. Finally, all statistical analyses were conducted using SPSS statistical software, version 21.0 (IBM, Armonk, USA).

First, sample normality analysis indicated that the population followed a normal distribution. The results of Box’s M test did not show homogeneity in the variance-covariance matrix on the EQ-i Total Scale (M = 59.29; F = 9.26, p ≥ 0.00) or on the STEM/STEU (M = 231.01; F = 36.07, p ≥0.00). However, Hair et al. [ 64 ] have stated that if the control and the experimental groups are of equal size, which was the case in this study, then that factor tends to mitigate the effects of violations of the normality assumption.

Second, to test whether there was any significant difference between the experimental group and control group at the time of pretest, Student’s t -test was performed to determine the differences in means of all the variables measured ( Table 1 ). Table 1 shows that there were no significant differences at the time of pretest. This finding suggests that both groups began in analogous situations.

Table 1. Student’s t-test of differences in means (t1, t2, t3).

Note. t1 = pretest; t2 = posttest; t3 = follow-up.

1 = direct score

Therefore, we came to the conclusion that the two groups of workers could not be distinguished by EI level before the TCEI program. In addition, the mean age of each group was analyzed and no baseline differences were found between the two groups.

To assess the impact of the program on EI, the scores obtained by both groups were compared before its implementation (pretest–Time 1) and shortly after the program was delivered (posttest–Time 2), as well as one year later (follow-up–Time 3). Group membership was the independent factor or variable, and the scores obtained by the subjects regarding EI were the criteria or dependent variables.

Two control variables, gender and age, were included in the analysis because they could affect the results. However, none of these variables showed a statistically significant effect in any of the variables assessed (p≥ .50 in all cases).

Regarding the implementation of the program, Table 2 presents the test results for intra-subject effects, which showed significant Group x Time interaction for all variables except for Adaptability.

Table 2. Summary of intra- and inter-subject univariate ANOVA.

The observed power was highest in the key scales: 1.00 for the STEU/STEM and Total EQ-i. Regarding the subscales, the observed power was also 1.00 for the Intrapersonal, Stress Management, and General Mood subscales; on the other hand, the observed power for the Interpersonal and the Adaptability subscales was .66 and .55, respectively.

Similarly, the effect size (η 2 ), the proportion of total variability attributable to a factor, and the magnitude of the difference between one time and another resulting from the interaction between the time of assessment and implementation of the program, was high for the key scales: ≥.71 for the STEU/STEM, and .82 for the Total EQ-i. With regards to the subscales, the effect size (η 2 ) was the following: .44 for Intrapersonal, .07 for Interpersonal, .32 for Stress Management, .05 for Adaptability, and .26 for General Mood.

To further explain these results, complementary analyses were performed. On the one hand, as shown in Table 1 , we carried out an average comparison between the experimental and control groups at the measurement moments T2 and T3. Results revealed significant differences between the experimental group and the control group regarding all variables and in both moments (T2 and T3), except for the Interpersonal variable, in which the experimental group obtained higher scores in these two moments but without being statistically significant these differences. This could explain the small effect size obtained for this variable.

In addition, the Adaptability variable showed statistically significant differences between the experimental group and the control group at time T2, with the control group scoring higher, while at time T3, the experimental group also obtains higher scores regarding Adaptability; however, this score difference with regards to the control group was not statistically significant. This could explain why the interaction was not significant and the small effect size obtained for this variable.

In order to compare differences between moments T1, T2, and T3, the marginal means were analyzed for both groups (experimental and control) per moment and variable ( Table 3 ).

Table 3. Marginal means comparing t1-t2, t1-t3, and t2-t3.

Note. EG = experimental group; CG = control group; t1 = pretest; t2 = posttest; t3 = follow-up.

In general, in the experimental group, there was a significant improvement between moments T1 and T2 in all variables, except Interpersonal and Adaptability, which did not present changes at any of the three moments (T1, T2, T3). On the other hand, scores remained without significant changes regarding all variables between moments T2 and T3, except in the case of STEU and STEM, in which the scores continued to improve between moments T2 and T3.

In the control group, the results were the same as in the experimental group concerning the Interpersonal and Adaptability variables. However, with regards to other variables, the trend was inverse to the experimental group between moments T1 and T2; in this case, there was a significant decrease in the scores between these two moments in the rest of the variables. Between moments T2 and T3, the scores remained without significant changes in all the variables measured with the EQ-i. In the case of variables measured with the ability test, there was a significant decrease in the STEU scores between moments T2 and T3, whereas the STEM scores remained without significant changes.

Figs 1 – 3 show the scores obtained in the EQ-i total scale and STEM/STEU total scales by both groups at Times 1, 2, and 3. At Times 2 and 3, the experimental group, which had received the EI training, had an increase in its scores, whereas the control group did not present any substantial change in scores.

Fig 1. Total EQi performance of the groups at pre-test (Time 1), post-test (Time 2), and one year after (Time 3).

Fig 3. STEM performance of the groups at pre-test (Time 1), post-test (Time 2), and one year after (Time 3).

Fig 2. STEU performance of the groups at pre-test (Time 1), post-test (Time 2), and one year after (Time 3).

The objective of this study was to examine the effectiveness of an EI training program among the senior managers (N = 54) of a private company. Consistent with Pérez-González and Qualter [ 13 ], Hodznik et al. [ 8 ], and Kotsou et al.’s [ 55 ] recommendations, we aimed to contribute new research findings and extend the existing literature on the effectiveness of EI training in the workplace. The main findings of this study revealed that intrapersonal EI, self-perception, general mood, self-expression, and stress management were maintained after the completion of the training. On the other hand, improvements in emotional understanding and emotion management had strengthened over time. However, the results also revealed that training did not result in similar improvements across all variables. Specifically, training had a nonsignificant impact on interpersonal and adaptability skills.

Theoretical implications of the study

With regard to the theoretical implications of the present findings, the observed effectiveness of the TCEI, which was conducted using an innovative methodology that entailed face-to-face training and a virtual campus support system among senior managers, extends the existing literature on the development of EI training programs.

The training program that was conducted as a part of this study failed to improve two dimensions of EI: interpersonal and adaptability skills. There are two possible explanations for why these variables did not demonstrate improvement. First, high-quality training that addresses all the dimensions of EI is necessary to produce large effects. Therefore, the time and exercises that are devoted to these two dimensions of EI may need to be redefined. Accordingly, the second and fourth sessions of this training (i.e., interpersonal and adaptability skills, respectively) can be enriched by adding new activities and including long-term evaluation of the transfer of skills to real workplace situations in which these abilities are required to resolve challenges. Indeed, allocating more time and exercises to these topics may have offered participants greater experience in practicing these interpersonal and adaptability skills in regular and virtual classroom settings before applying them in the workplace.

On the other hand, changes in these two dimensions of EI may not be detectable immediately after the completion of the training or soon after a year has elapsed. Similarly, the studies that Kotsou et al. reviewed [ 55 ] also indicated that improvements in EI may not be detectable immediately or shortly after the completion of an intervention. Further, the conclusions of this review appear to suggest that shorter training programs do not improve some dimensions of EI. Therefore, a more intensive training and longer time gap between completion of training and assessment (i.e., after more than a year has elapsed) may yield significant results for these two dimensions of EI. Indeed, other studies have used longer time gaps such as more than two years [ 40 ] and yearly evaluations across three years [ 47 ].

In any case, the present findings suggest that the proposed training intervention is effective in improving some dimensions of EI. In particular, senior managers who received EI training demonstrated significant improvements in their ability to perceive, understand, and accept their own and others’ emotions in an effective way, be self-reliant, achieve personal goals, manage stress, have a positive attitude, and control and manage emotions; these findings are consistent with those of past studies that have aimed to improve EI by providing training in workplaces [ 45 – 52 ].

The largest effects emerged for the total scores for EI (as per mixed models; total EQ-i), followed by emotion management (STEM) and understanding (STEU), intrapersonal aspects, stress management, and finally, general mood. Moreover, improvements in emotional understanding and emotion management that had resulted from the training intervention had strengthened over time.

Similarly, several researchers have indicated that EI plays a key role in leadership development and success in the workplace [ 65 , 66 ]. The behaviors of managers shape critical stages of their subordinates’ careers as well as the provision of optimal training and promotion [ 67 , 68 ]. Given the unique significance that EI and optimal leadership bears to this group of professionals, the present study aimed to improve the EI of senior managers.

In sum, the proposed program is a training intervention that can be used to enhance the EI of senior managers because, as the previously articulated extensive literature review has demonstrated, EI plays a key role within work environments. Therefore, the present findings suggest that the TCEI is an effective training program that can improve the ability to identify one’s own and others’ emotions as well as identify and understand the impact of one’s feelings on thoughts, decisions, behaviors, and performance at work.

Practical implications

The present findings serve as empirical evidence of the effectiveness of the training program that was conducted in the present study in improving key dimensions of EI that foster the emotional skills that are both necessary and desirable in the workplace. Accordingly, the present findings have practical implications because they support the future use of the EI training program that was used in the present study. In this regard, the present findings revealed that EI training can promote the emotional development of senior managers.

In addition, the methodology of the training program is noteworthy because it required participants to use communication and work as a group to solve real practical problems that necessitate the application of EI skills in the workplace. Similarly, the use of face-to-face training alongside an e-learning platform helped participants acquire the ability to learn independently as well as synergically (i.e., with other senior managers). This encouraged the group to reflect on their knowledge about EI and apply their EI skills to handle workplace challenges.

It is important to emphasize that there were significant temporal changes in the scores of measures of emotional understanding and emotion management; in other words, the scores continued to improve a year after the completion of training. It is interesting to note that the methodology of the last training session was unique because it involved the creation of a “life and career roadmap” and “commitment to growth and development. We believe that these exercises were responsible for the continued improvement in important EI skills over time that was observed in the present study.

This finding has important practical implications because it underscores the importance of requiring senior managers to indicate their commitment to the transfer of knowledge. Indeed, the roadmap defines the results that are expected to follow the implementation of the learned emotional strategies and verifies the achievement of these results. In addition, all managers signed an online contract to indicate their commitment to remain connected through the virtual campus support system to resolve any conflicts that may arise within the company in an emotionally intelligent manner.

We believe that the method of learning that our intervention entailed is more effective than conventionally used methods. Further, the uniqueness of this method may have contributed to the observed change in scores because it allowed frustrated senior managers to share their unresolved issues. Finally, by practicing emotional understanding and emotional management during the training, the created a plan of action and implemented their solutions using EI strategies.

In addition, we believe that signing the online contract helped them understand their responsibilities and the impact that their emotional understanding and emotion management can have on the organization. The fact that their scores on measures of emotional understanding and emotion management continued to increase over time indicates that the subjects had acquired these skills and that, once they had acquired them, they continued to develop them. Similarly, Kotsou et al. [ 55 ] also found that training resulted in stable improvements in EI. In addition to providing their participants with EI tools and skills as a part of their training, they also motivated them to apply these skills and use these tools in the future.

Taken together, the present findings have promising practical implications. Specifically, the findings suggest that a training methodology that facilitates knowledge transfer (i.e., application of knowledge about EI in the management of workplace challenges) can enhance the following dimensions of EI: emotional understanding, emotion management, self-perception (through training activities that pertain to self-regard, self-actualization, and emotional self-awareness), decision making (through training activities that pertain to problem solving, reality testing, and impulse control), self-expression (through training activities that pertain to emotional expression, assertiveness, and independence), and stress management (through training activities that pertain to flexibility, stress tolerance, and optimism).

Limitations and future studies

The present study has several limitations that require explication. First, we included only age and gender as control variables and omitted other individual differences that could have influenced the results. However, it is important for future researchers to define and examine the role of individual differences in the effects of EI training in greater detail. In addition, in accordance with Kotsou et al. [ 55 ] and Hodzic et al.’s [ 8 ] suggestions, detailed behavioral indicators must be examined because they may play a crucial role in the effectiveness of EI training. Another limitation of the present study is that the intervention program was conducted in only one company. Therefore, future studies must implement this program in different companies and across varied business contexts. The present results make it apparent that further refinements are needed in order to address the aforementioned limitations of this intervention.

Another limitation of the present study is that it did not assess the effect that improvements in EI can have on other variables. Accordingly, recommendations for further research include the determination of whether improvements in EI that result from training lead to improvements in other variables such as job satisfaction and performance and successful leadership, in accordance with the results of other research studies [ 69 – 72 ]. Thus, future research studies must consider these possibilities when they examine whether the TCEI has the potential to produce all the aforementioned outcomes at an organizational level. Furthermore, the intervention can be redesigned in such a manner that it yields specific performance outcomes. Further, longitudinal studies on the effectiveness of EI training must be conducted across several sectors and countries.

Finally, senior managers define and direct the careers of the rest of a company’s personnel; Therefore, future research studies must examine how EI training can be used to promote its previously observed desirable effects such as the demonstration of good leadership behaviors, effective cooperation, and teamwork [ 29 , 31 , 34 – 38 , 69 ]. In fact, this is an interesting line of inquiry for future researchers.

Conclusions

In conclusion, the present findings contribute to the existing knowledge on the development of EI because they indicate that the training program resulted in improvements in many dimensions of the EI of senior managers. More specifically, the longitudinal effects of EI training on senior managers’ emotional skills had maintained over time, whereas the corresponding effects on emotional understanding and emotion management had strengthened at one-year follow up. Finally, the implementation of this intervention in organizational settings can nurture and promote a sense of fulfillment among employees.

Supporting information

Data underlying the findings described.

TCEI planning schedule.

Acknowledgments

This research was supported by the Spanish Ministry of Economy and Competitiveness (EDU2015-64562-R)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This research was supported by the Spanish Ministry of Economy and Competitiveness (EDU2015-64562-R) to R.G-C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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REVIEW article

The measurement of emotional intelligence: a critical review of the literature and recommendations for researchers and practitioners.

• 1 School of Management, QUT Business School, Queensland University of Technology, Brisbane, QLD, Australia
• 2 Clinical Skills Development Service, Metro North Hospital and Health Service, Queensland Health, Brisbane, QLD, Australia
• 3 School of Psychology, Faculty of Health and Behavioural Sciences, The University of Queensland, St. Lucia, QLD, Australia
• 4 School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology, Brisbane, QLD, Australia

Emotional Intelligence (EI) emerged in the 1990s as an ability based construct analogous to general Intelligence. However, over the past 3 decades two further, conceptually distinct forms of EI have emerged (often termed “trait EI” and “mixed model EI”) along with a large number of psychometric tools designed to measure these forms. Currently more than 30 different widely-used measures of EI have been developed. Although there is some clarity within the EI field regarding the types of EI and their respective measures, those external to the field are faced with a seemingly complex EI literature, overlapping terminology, and multiple published measures. In this paper we seek to provide guidance to researchers and practitioners seeking to utilize EI in their work. We first provide an overview of the different conceptualizations of EI. We then provide a set of recommendations for practitioners and researchers regarding the most appropriate measures of EI for a range of different purposes. We provide guidance both on how to select and use different measures of EI. We conclude with a comprehensive review of the major measures of EI in terms of factor structure, reliability, and validity.

Overview and Purpose

The purpose of this article is to review major, widely-used measures of Emotional Intelligence (EI) and make recommendations regarding their appropriate use. This article is written primarily for academics and practitioners who are not currently experts on EI but who are considering utilizing EI in their research and/or practice. For ease of reading therefore, we begin this article with an introduction to the different types of EI, followed by a brief summary of different measures of EI and their respective facets. We then provide a detailed set of recommendations for researchers and practitioners. Recommendations focus primarily on choosing between EI constructs (ability EI, trait EI, mixed models) as well as choosing between specific tests. We take into account such factors as test length, number of facets measured and whether tests are freely available. Consequently we also provide recommendations both for users willing to purchase tests and those preferring to utilize freely available measures.

In our detailed literature review, we focus on a set of widely used measures and summarize evidence for their validity, reliability, and conceptual basis. Our review includes studies that focus purely on psychometric properties of EI measures as well as studies conducted within applied settings, particularly health care settings. We include comprehensive tables summarizing key empirical studies on each measure, in terms of their research design and main findings. Our review includes measures that are academic and/or commercial as well as those that are freely available or require payment. To assist users with accessing measures, we include web links to complete EI questionaries for freely available measures and to websites and/or example items for copyrighted measures. For readers interested in reviews relating primarily to EI constructs, theory and outcomes rather than specifically measures of EI, we recommend a number of recent high quality publications (e.g., Kun and Demetrovics, 2010 ; Gutiérrez-Cobo et al., 2016 ). Additionally, for readers interested in a review of measures without the extensive recommendations we provide here, we recommend the chapter by Siegling et al. (2015) .

Early Research on Emotional Intelligence

EI emerged as a major psychological construct in the early 1990s, where it was conceptualized as a set of abilities largely analogous to general intelligence. Early influential work on EI was conducted by Salovey and Mayer (1990) , who defined EI as the “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” (p. 189). They argued that individuals high in EI had certain emotional abilities and skills related to appraising and regulating emotions in the self and others. Accordingly, it was argued that individuals high in EI could accurately perceive certain emotions in themselves and others (e.g., anger, sadness) and also regulate emotions in themselves and others in order to achieve a range of adaptive outcomes or emotional states (e.g., motivation, creative thinking).

However, despite having a clear definition and conceptual basis, early research on EI was characterized by the development of multiple measures (e.g., Bar-On, 1997a , b ; Schutte et al., 1998 ; Mayer et al., 1999 ) with varying degrees of similarity (see Van Rooy et al., 2005 ). One cause of this proliferation was the commercial opportunities such tests offered to developers and the difficulties faced by researchers seeking to obtain copyrighted measures (see section Mixed EI for a summary of commercial measures). A further cause of this proliferation was the difficulty researchers faced in developing measures with good psychometric properties. A comprehensive discussion of this issue is beyond the scope of this article (see Petrides, 2011 for more details) however one clear challenge faced by early EI test developers was constructing emotion-focused questions that could be scored with objective criteria. In comparison to measures of cognitive ability that have objectively right/wrong answers (e.g., mathematical problems), items designed to measure emotional abilities often rely on expert judgment to define correct answers which is problematic for multiple reasons ( Roberts et al., 2001 ; Maul, 2012 ).

A further characteristic of many early measures was their failure to discriminate between measures of typical and maximal performance. In particular, some test developers moved away from pure ability based questions and utilized self-report questions (i.e., questions asking participants to rate behavioral tendencies and/or abilities rather than objectively assessing their abilities; e.g., Schutte et al., 1998 ). Other measures utilized broader definitions of EI that included social effectiveness in addition to typical EI facets (see Ashkanasy and Daus, 2005 ) (e.g., Boyatzis et al., 2000 ; Boyatzis and Goleman, 2007 ). Over time it became clear that these different measures were tapping into related, yet distinct underlying constructs. Currently, there are two popular methods of classifying EI measures. First is the distinction between trait and ability EI proposed initially by Petrides and Furnham (2000) and further clarified by Pérez et al. (2005) . Second is in terms of the three EI “streams” as proposed by Ashkanasy and Daus (2005) . Fortunately there is overlap between these two methods of classification as we discuss below.

Methods of Classifying EI

The distinction between ability EI and trait EI first proposed by Petrides and Furnham (2000) was based purely on whether the measure was a test of maximal performance (ability EI) or a self-report questionnaire (trait EI) ( Petrides and Furnham, 2000 ; Pérez et al., 2005 ). According to this method of classification, Ability EI tests measure constructs related to an individual's theoretical understanding of emotions and emotional functioning, whereas trait EI questionnaires measure typical behaviors in emotion-relevant situations (e.g., when an individual is confronted with stress or an upset friend) as well as self-rated abilities. Importantly, the key aspect of this method of classification is that EI type is best defined by method of measurement: all EI measures that are based on self-report items are termed “trait EI” whereas all measures that are based on maximal performance items are termed “ability EI”.

The second popular method of classifying EI measures refers the three EI “streams” ( Ashkanasy and Daus, 2005 ). According to this method of classification, stream 1 includes ability measures based on Mayer and Salovey's model; stream 2 includes self-report measures based on Mayer and Salovey's model and stream 3 includes “expanded models of emotional intelligence that encompass components not included in Salovey and Mayer's definition” (p. 443). Ashkanasy and Daus (2005) noted that stream 3 had also been referred to as “mixed” models in that they comprise a mixture of personality and behavioral items. The term “mixed EI” is now frequently used in the literature to refer to EI measures that measure a combination of traits, social skills and competencies and overlaps with other personality measures ( O'Boyle et al., 2011 ).

Prior to moving on, we note that Petrides and Furnham's (2000 ) trait vs. ability distinction is sufficient to categorize the vast majority of EI tests. Utilizing this system, both stream 2 (self-report) and stream 3 (self-report mixed) are simply classified as “trait” measures. Indeed as argued by Pérez et al. (2005) , this method of classification is probably sufficient given that self-report measures of EI tend to correlate strongly regardless of whether they are stream 2 or stream 3 measures. However, given that the terms “stream 3” and “mixed” are so extensively used in the EI literature, we will also use them here. We are not proposing that these terms are ideal or even useful when classifying EI, but rather we wish to adopt language that is most representative of the existing literature on EI. In the following section therefore, we refer to ability EI (stream 1), trait EI (steam 2), and mixed EI (stream 3). As outlined later, decisions regarding which measure of EI to use should be based on what form of EI is relevant to a particular research project or professional application.

For the purposes of this review, we refer to “ability” based measures as tests that utilize questions/items comparable to those found in IQ tests (see Austin, 2010 ). These include all tests containing ability-type items and not only those based directly on Mayer and Salovey's model. In contrast to trait based measures, ability measures do not require that participants self-report on various statements, but rather require that participants solve emotion-related problems that have answers that are deemed to be correct or incorrect (e.g., what emotion might someone feel prior to a job interview? (a) sadness, (b) excitement, (c) nervousness, (d) all of the above). Ability based measures give a good indication of individuals' ability to understand emotions and how they work. However since they are tests of maximal ability, they do not tend to predict typical behavior as well as trait based measures (see O'Connor et al., 2017 ). Nevertheless, ability-based measures are valid, albeit weak, predictors of a range of outcomes including work related attitudes such as job satisfaction ( Miao et al., 2017 ), and job performance ( O'Boyle et al., 2011 ).

In this review, we define trait based measures as those that utilize self-report items to measure overall EI and its sub dimensions. We utilize this term for measures that are self-report, and have not explicitly been termed as “mixed” or “stream 3” by others. Individuals high in various measures of trait EI have been found to have high levels of self-efficacy regarding emotion-related behaviors and tend to be competent at managing and regulating emotions in themselves and others. Also, since trait EI measures tend to measure typical behavior rather than maximal performance, they tend to provide a good prediction of actual behaviors in a range of situations ( Petrides and Furnham, 2000 ). Recent meta-analyses have linked trait EI to a range of work attitudes such as job satisfaction and organization commitment ( Miao et al., 2017 ), Job Performance ( O'Boyle et al., 2011 ).

As noted earlier, although the majority of EI measures can be categorized using the terms “ability EI” and “trait EI”, we adopt the term “mixed EI” in this review when this term has been explicitly used in our source articles. The term mixed EI is predominately used to refer to questionnaires that measure a combination of traits, social skills and competencies that overlap with other personality measures. Generally these measures are self-report, however a number also utilize 360 degree forms of assessment (self-report combined with multiple peer reports from supervisors, colleagues and subordinates) (e.g., Bar-On, 1997a , b ) This is particularly true for commercial measures designed to predict and improve performance in the workplace. A common aspect in many of these measures is the focus on emotional “competencies” which can theoretically be developed in individuals to enhance their professional success (See Goleman, 1995 ). Research on mixed measures have found them to be valid predictors of multiple emotion-related outcomes including job satisfaction, organizational commitment ( Miao et al., 2017 ), and job performance ( O'Boyle et al., 2011 ). Effect sizes of these relationships tend to be moderate and on par with trait-based measures.

We note that although different forms of EI have emerged (trait, ability, mixed) there are nevertheless a number of conceptual similarities in the majority of measures. In particular, the majority of EI measures are regarded as hierarchical meaning that they produce a total “EI score” for test takers along with scores on multiple facets/subscales. Additionally, the facets in ability, trait and mixed measures of EI have numerous conceptual overlaps. This is largely due to the early influential work of Mayer and Salovey. In particular, the majority of measures include facets relating to (1) perceiving emotions (in self and others), (2) regulating emotions in self, (3) regulating emotions in others, and (4) strategically utilizing emotions. Where relevant therefore, this article will compare how well different measures of EI assess the various facets common to multiple EI measures.

Emotional Intelligence Scales

The following emotional intelligence scales were selected to be reviewed in this article because they are all widely researched general measures of EI that also measure several of the major facets common to EI measures (perceiving emotions, regulating emotions, utilizing emotions).

1. Mayer-Salovey-Caruso Emotional Intelligence Tests (MSCEIT) ( Mayer et al., 2002a , b ).

2. Self-report Emotional Intelligence Test (SREIT) ( Schutte et al., 1998 )

3. Trait Emotional Intelligence Questionnaire (TEIQue) ( Petrides and Furnham, 2001 )

4. Bar-On Emotional Quotient Inventory (EQ-i) ( Bar-On, 1997a , b )

5. i) The Situational Test of Emotional Management (STEM) ( MacCann and Roberts, 2008 )

ii) The Situational Test of Emotional Understanding (STEU) ( MacCann and Roberts, 2008 )

6. Emotional and Social competence Inventory (ESCI) ( Boyatzis and Goleman, 2007 )

The complete literature review of these measures is included in the Literature Review section of this article. The following section provides a set of recommendations regarding which of these measures is appropriate to use across various research and applied scenarios.

Recommendations Regarding the Appropriate Use of Measures

Deciding between measuring trait ei, ability ei and mixed ei.

A key decision researchers/practitioners need to make prior to incorporating EI measures into their work is whether they should utilize a trait, ability or mixed measure of EI. In general, we suggest that when researchers/practitioners are interested in emotional abilities and competencies then they should utilize measures of ability EI. In particular ability EI is important in situations where a good theoretical understanding of emotions is required. For example a manager high in ability EI is more likely to make good decisions regarding team composition. Indeed numerous studies on ability EI and decision making in professionals indicates that those high in EI tend to be competent decision makers, problem solvers and negotiators due primarily to their enhanced abilities at perceiving and understanding emotions (see Mayer et al., 2008 ). More generally, ability EI research also has demonstrated associations between ability EI and social competence in children ( Schultz et al., 2004 ) and adults ( Brackett et al., 2006 ).

We suggest that researchers/practitioners should select trait measures of EI when they are interested in measuring behavioral tendencies and/or emotional self-efficacy. This should be when ongoing, typical behavior is likely to lead to positive outcomes, rather than intermittent, maximal performance. For example, research on task-induced stress (i.e., temporary states of negative affect evoked by short term, challenging tasks) has shown trait EI to have incremental validity over other predictors ( O'Connor et al., 2017 ). More generally, research tends to show that trait EI is a good predictor of effective coping styles in response to life stressors (e.g., Austin et al., 2010 ). Overall, trait EI is associated with a broad set of emotion and social related outcomes adults and children ( Mavroveli and Sánchez-Ruiz, 2011 ; Petrides et al., 2016 ) Therefore in situations characterized by ongoing stressors such as educational contexts and employment, we suggest that trait measures be used.

When both abilities and traits are important, researchers/practitioners might choose to use both ability and trait measures. Indeed some research demonstrates that both forms of EI are important stress buffers and that they exert their protective effects at different stages of the coping process: ability EI aids in the selection of coping strategies whereas trait EI predicts the implementation of such strategies once selected ( Davis and Humphrey, 2014 ).

Finally, when researchers/practitioners are interested in a broader set of emotion-related and social-related dispositions and competencies we recommend a mixed measure. Mixed measures are particularly appropriate in the context of the workplace. This seems to be the case for two reasons: first, the tendency to frame EI as a set of competencies that can be trained (e.g., Goleman, 1995 ; Boyatzis and Goleman, 2007 ) is likely to equip workers with a positive growth mindset regarding their EI. Second, the emphasis on 360 degree forms of assessment in mixed measures provides individuals with information not only on their self-perceptions, but on how others perceive them which is also particularly useful in training situations.

Advantages and Disadvantages of Trait and Ability EI

There are numerous advantages and disadvantages of the different forms of EI that test users should factor into their decision. One disadvantage of self-report measures is that people are not always good judges of their emotion-related abilities and tendencies ( Brackett et al., 2006 ; Sheldon et al., 2014 ; Boyatzis, 2018 ). A further disadvantage of self-report, trait based measures is their susceptibility to faking. Participants can easily come across as high in EI by answering questions in a strategic, socially desirable way. However, this is usually only an issue when test-takers believe that someone of importance (e.g., a supervisor or potential employer) will have access to their results. When it is for self-development or research, individuals are less likely to fake their answers to trait EI measures (see Tett et al., 2012 ). We also note that the theoretical bases of trait and mixed measures have also been questioned. Some have argued for example that self-report measures of EI measure nothing fundamentally different from the Big Five (e.g., Davies et al., 1998 ). We will not address this issue here as it has been extensively discussed elsewhere (e.g., Bucich and MacCann, 2019 ) however we emphasize that regardless of the statistical distinctiveness of self-report measures of EI, there is little question regarding their utility and predictive validity ( O'Boyle et al., 2011 ; Miao et al., 2017 ).

One advantage of ability based measures is that they cannot be faked. Test-takers are told to give the answer they believe is correct, and consequently should try to obtain a score as high as possible. A further advantage is that they are often more engaging tests. Rather than simply rating agreement with statements as in trait based measures, test-takers attempt to solve emotion-related problems, solve puzzles, and rate emotions in pictures.

Overall however, there are a number of fundamental problems with ability based measures. First, many personality and intelligence theorists question the very existence of ability EI, and suggest it is nothing more than intelligence. This claim is supported by high correlations between ability EI and IQ, although some have provided evidence to the contrary (e.g., MacCann et al., 2014 ). Additionally, the common measures of ability EI tend to have relatively poor psychometric properties in terms of reliability and validity. Ability EI measures do not tend to strongly predict outcomes that they theoretically should predict (e.g., O'Boyle et al., 2011 ; Miao et al., 2017 ). Maul (2012) also outlines a comprehensive set of problems with the most widely used ability measure, the MSCEIT, related to consensus-based scoring, reliability, and underrepresentation of the EI construct. Also see Petrides (2011) for a comprehensive critique of ability measures.

General Recommendation for Non-experts Choosing Between Ability and Trait EI

While the distinction between trait, ability and mixed EI is important, we acknowledge that many readers will simply be looking for an overall measure of emotional functioning that can predict personal and professional effectiveness. Therefore, when potential users have no overt preference for trait or ability measures but need to decide, we strongly recommend researchers/ practitioners begin with a trait-based measure of EI . Compared to ability based measures, trait based measures tend to have very good psychometric properties, do not have questionable theoretical bases and correlate moderately and meaningfully with a broad set of outcome variables. In general, we believe that trait based measures are more appropriate for most purposes than ability based measures. That being said, several adequate measures of ability EI exist and these have been reviewed in the Literature Review section. If there is a strong preference to use ability measures of EI then several good options exist as outlined later.

Choosing a Specific Measure of Trait EI

Based on our literature review we suggest that a very good, comprehensive measure of trait EI is the Trait Emotional Intelligence Questionnaire, or TEIQue ( Petrides and Furnham, 2001 ). If users are not restricted by time or costs (commercial users need to pay, researchers do not) then the TEIQue is a very good option. The TEIQue is a widely used questionnaire that measures 4 factors and 15 facets of trait EI. It has been cited in more than 2,000 academic studies. It is regarded as a “trait” measure of EI because it is based entirely on self-report responses, and facet scores represent typical behavior rather than maximal performance. There is extensive evidence in support of its reliability and validity ( Andrei et al., 2016 ). The four factors of the TEIQue map on to the broad EI facets present in multiple measures of EI as follows: emotionality = perceiving emotions, self-control = regulating emotions in self, sociability = regulating emotions in others, well-being = strategically utilizing emotions.

One disadvantage of the TEIQue however is that it is not freely available for commercial use. The website states that commercial or quasi-commercial use without permission is prohibited. The test can nevertheless be commercially used for a relatively small fee. The relevant webpage can be found here ( http://psychometriclab.com/ ). A second disadvantage is that the test can be fairly easily faked due to its use of a self-report response scale. However, this is generally only an issue when individuals have a reason for faking (e.g., their score will be seen by someone else and might impact their prospects of being selected for a job) (see Tett et al., 2012 ). Consequently, we do not recommend the TEIQue to be used for personnel selection, but it is relevant for other professional purposes such as in EI training and executive coaching.

There are very few free measures of trait EI that have been adequately investigated. One exception is the widely used, freely available measure termed the Self-Report Emotional Intelligence Test (SREIT, Schutte et al., 1998 ). The SREIT has been cited more than 3,000 times. The full paper which includes all test items can be accessed here ( https://www.researchgate.net/publication/247166550_Development_and_Validation_of_a_Measure_of_Emotional_Intelligence ). Although it was designed to measure overall EI, subsequent research indicates that it performs better as a multidimensional scale measuring 4 distinct factors including: optimism/mood regulation, appraisal of emotions, social skills and utilization of emotions. These four scales again map closely to the broad facets present in many EI instruments as follows: optimism/mood regulation = regulating emotions in self, appraisal of emotions = perceiving emotions in self, social skills = regulating emotions in others, and utilization of emotions = strategically utilizing emotions. Please note that although one study has comprehensively critiqued the SREIT ( Petrides and Furnham, 2000 ), it actually works well as a multidimensional measure. This was acknowledged by the authors of the critique and has been subsequently confirmed (e.g., by O'Connor and Athota, 2013 ).

Long vs. Short Measures of Trait EI

The TEIQue is available in long form (153 items, 15 facets, 4 factors) and short form (30 items, 4 factors/subscales). A complete description of all factors and facets can be found here ( http://www.psychometriclab.com/adminsdata/files/TEIQue%20interpretations.pdf ). We recommend using the short form when users are interested in measuring only the 4 broad EI factors measured by this questionnaire (self-control, well-being, sociability, emotionality). Additionally, there is much more research on the short form of the questionnaire (e.g., Cooper and Petrides, 2010 ) (see Table 5 ), and the scoring instructions for the short form are freely available for researchers. If the short form is used, it is recommended that all factors/subscales are utilized because they predict outcomes in different ways (e.g., O'Connor and Brown, 2016 ). The SREIT is available only as a short, 33 item measure. All subscales are regarded as equally important and should be included if possible. Again it is noted that this test is freely available and the article publishing the items specifically states “Note: the authors permit free use of the scale for research and clinical purposes.”

When users require a comprehensive measure of trait EI, the long form of the TEIQue is also a good option (see Table 5 ). Although not as widely researched as the short version, the long version nevertheless has strong empirical support for reliability and validity. The long form is likely to be particularly useful for coaching and training purposes, because the use of 15 narrow facets allows for more focused training and intervention than measures with fewer broad facets/factors.

Choosing Between Measures of Ability EI

The most researched and supported measure of ability EI is the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT) (see Tables 2 , 3 ). It has been cited in more than 1,500 academic studies. It uses a 4 branch approach to ability EI and measures ability dimensions of perceiving emotions, facilitating thought, understanding emotions and managing emotions. These scales broadly map onto the broad constructs present in many measures of EI as follows: facilitating thought = strategically utilizing emotions, perceiving emotions = perceiving emotions in self and others, understanding emotions = understanding emotions, and managing emotions = regulating emotions in self and others. However, this is a highly commercialized test and relatively expensive to use. The test is also relatively long (141 items) and time consuming to complete (30–45 min).

A second, potentially more practical option includes two related tests of ability EI designed by MacCann and Roberts (2008) (see Tables 2 , 7 ). These tests are called the Situational Test of Emotion Management (STEM) and the Situational Test of Emotional Understanding (the STEU). These tests are becoming increasingly used in academic articles; the original paper has now been cited more than 250 times. The two aspects of ability EI measured in these tests map neatly onto two of the broad EI constructs present in multiple measures of EI. Specifically, the STEM can be regarded as a measure of emotional regulation in oneself and the STEU can be regarded as a measure of emotional understanding. As indicated in Table 7 , there is strong psychometric support for these tests (although the alpha for STEU is sometimes borderline/low). A further advantage of STEU is that it contains several items regarding workplace behavior, making it highly applicable for use in professional contexts.

If researchers/practitioners decide to use the STEM and STEU, additional measures might be required to measure the remaining broad EI constructs present in other tests. Although these measures could all come from relevant scales of tests reviewed in this article (see Table 1 ), there is a further option. Users should consider the Diagnostic Analysis of Non-verbal Accuracy scale (DANVA) which is a widely used, validated measure of perceiving emotion in others (see Nowicki and Duke, 1994 for an introduction to the DANVA). Alternatively, for those open to using a combination of ability and trait measures, users might wish to use Schutte et al.'s (1998) SREIT to assess remaining facets of EI (see Table 4 ). This is because it is free and captures aspects of EI not measured by STEM/STEU. These include appraisal of emotions (for perceiving emotions) and utilization of emotions (for strategically utilizing emotions), respectively.

Table 1 . Summary of recommended emotional intelligence assessment measures for each broad EI construct.

Therefore, if there is a strong preference to utilize ability based measures, the STEM, STEU, and DANVA represent some very good options worth considering. The advantage of using these over the MSCEIT is the lower cost of these measures and the reduced test time. Although the STEM, STEU, and DANVA do not seem to be freely available for commercial use, they are nevertheless appropriate for commercial use and likely to be cheaper than alternative options at this point in time.

Deciding Between Using a Single Measure or Multiple Measures

When seeking to measure EI, researchers/practitioners could choose to use (1) a single EI tool that measures overall EI along with common EI facets (i.e., perceiving emotions in self and others, regulating emotions in self and others and strategically utilizing emotions) or (2) some combination of existing scales from EI tool/s to cumulatively measure the four constructs.

The first option represents the most pragmatic and generally optimal solution because all information about the relevant facets and related measures would usually be located in a single document (e.g., test manual, journal article) or website. Additionally, if a paid test is used it would only require a single payment to a single author/institution. Furthermore, single EI tools are generally based on theoretical models of EI that have implications for training and development. For example EI facets in Goleman's (1995 ) model (as measured using the ESCI, Boyatzis and Goleman, 2007 ) are regarded as characteristics that can be trained. Therefore, if a single EI tool is selected, the theory underlying the tool could be used to model the interventions.

However, a disadvantage of the first option is that some EI measures will not contain the specific set of EI constructs researchers/practitioners are interested in assessing. This will often be the case when practitioners are seeking a comprehensive measure of EI but prefer a freely available measure. The second option specified above would solve this problem. However, the trade-off would be increased complexity and the absence of a single underlying theory that relates to the selected measures. Tables 2 – 8 describe facets within each measure as well as reliability and validity evidence for each facet and can be used to assist the selection of multiple measures if users choose to do this.

Table 2 . Summary of major emotional Intelligence assessment measures.

Table 3 . Review of selected studies detailing psychometric properties of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT).

Table 4 . Review of selected studies detailing psychometric properties of the Self-report Emotional Intelligence Test (SREIT).

Table 5 . Review of selected studies on psychometric properties of the Trait Emotional Intelligence Questionnaire (TEIQue).

Table 6 . Review of selected studies on psychometric properties of the Emotional Quotient Inventory (EQ-i) ( Bar-On, 1997a , b ).

Table 7 . Review of selected studies on psychometric properties of the STEU and STEM.

Table 8 . Review of selected studies on psychometric properties of the Emotional and Social competence Inventory (ESCI).

The Best Measure of Each Broad EI Construct (Evaluated Across all Reviewed Tests)

In some cases, researchers/practitioners will not need to measure overall EI, but instead seek to measure a single dimension of EI (e.g., emotion perception, emotion management etc.). In general, we caution the selective use of individual EI scales and recommend that users habitually measure and control for EI facets they are not directly interested in. Nevertheless, we acknowledge that in some cases users will have to select a single measure and consequently, this section specifies a selection of what we consider the “best” measures for each construct. We do this for both free measures and those requiring payment. In order to determine which measure constitutes the “best” measure for each construct, the following criteria were applied:

1. The measure should have been used in multiple research studies published in high quality journals.

2. There should be good evidence for the reliability of the measure in multiple academic studies incorporating the measure.

3. The measure should have obtained adequate validity evidence in multiple academic studies. Most importantly, evidence of construct validity should have been established, including findings demonstrating that the measure correlates meaningfully with measures of related constructs.

4. The measure should be based on a strong and well-supported theory of EI.

5. The measure should be practical (i.e., easy to administer, quickly completed and scored).

Where multiple measures met the above criteria, they were compared on their performance on each criterion (i.e., a measure with a lot of research scored higher on the first criteria than a measure with a medium level of research). Table 1 summarizes these results.

Please note that the Emotional and Social Intelligence Inventory (ESCI) by Boyatzis and Goleman (2007) has subscales that are also closely related to the ones listed in Table 1 (see full technical manual here ( http://www.eiconsortium.org/pdf/ESCI_user_guide.pdf ). The measure was developed primarily to predict and enhance performance at work and items are generally written to reflect workplace scenarios. Subscales from this test were not consistently chosen as the “best” measures because it has not had as extensive published research as the other tests. Most research using this measure has also used peer-ratings rather than self-ratings which makes it difficult to compare with the majority of measures (this is not a weakness though). Nevertheless, it should be considered if cost is not an issue and there is a strong desire to utilize a test specifically developed for the workplace.

Qualifications and Training

Although our purpose in this paper is not to outline the necessary training or qualifications required to administer the set of tests/questionnaires reviewed, we feel it is important to make some comments on this. First, we recommend that all researchers and practitioners considering using one more of these tests have a good understanding of the principles of psychological assessment. Users should understand the concepts of reliability, validity and the role of norms in psychological testing. There are many good introductory texts in this area (e.g., Kaplan and Saccuzzo, 2017 ). Furthermore, we recommend users have a good understanding of the limitations of psychological testing and assessment. When using EI measures to evaluate suitability of job applicants, these measures should form only part of the assessment process and should not be regarded as comprehensive information about applicants. Finally, some of the tests outlined in this review require specific certification and/or qualifications. Certification and/or qualification is required for administrators of the ESCI, MSCEIT, and EQi 2.0).

Literature Review

The final section of this article is a literature review of the 6 popular measures we have covered. We have included our review at the end of this article because we regard it as optional reading. We suggest that this section will be useful primarily for those seeking a more in depth understanding of the key studies underlying the various measures we have presented in earlier sections.

This literature review had two related aims; first to identify prominent EI measures used in the literature, as well as specifically in applied (e.g., health care) contexts. The emotional intelligence measures we included were those that measured both overall EI as well as more specific EI constructs common to multiple measures (e.g., those related to perceiving emotions in self and others, regulating emotions in self and others and strategically utilizing emotions). The second aim was to identify individual studies that have explored the validity and reliability of the specific emotional intelligence measures identified.

Inclusion Criteria

Four main inclusion criteria were applied to select literature: (a) focus on adult samples, (b) use of reputable, peer-reviewed journal articles, (c) use of an EI scale, and (d) where possible, use of a professional sample (e.g., health care professionals) rather than primarily student samples. The literature search therefore focused on empirical, quantitative investigations published in peer-reviewed journals. The articles reviewed therefore were generally methodologically sound and enabled a thorough analysis of some aspect of reliability or validity. We only reviewed articles published after 1990. Additionally, only papers in English were reviewed.

Papers were identified by conducting searches in the following electronic databases: PsycINFO, Medline, PubMED, CINAHL (Cumulative Index for Nursing and Allied Health Literature), EBSCO host and Google Scholar. Individual journals were also scanned such as The Journal of Nursing Measurement and Psychological Assessment.

Search Terms

When searching for emotional intelligence scales and related literature, search terms included: trait emotional intelligence, ability emotional intelligence, emotional intelligence scales, mixed emotional intelligence and emotional intelligence measures. Some common EI facet titles (e.g., self-awareness, self-regulation/self-management, social awareness, and relationship management) were also entered as search terms however this revealed far less relevant literature than searches based on EI terms. To access studies using professionals we also used terms such as workplace, healthcare, and nursing, along with emotional intelligence.

When searching for literature on the identified scales, the name of the respective scale was included in the search term (such as TEIQue scale) and the authors' names, along with terms such as workplace, organization, health care, nurses, health care professionals, to identify specific studies with a professional employee sample that utilized the specific scale. The terms validity and reliability were also used. Additionally, a similar search was conducted on articles that had cited the original papers. This search was done conducted utilizing Google Scholar. Table 2 summarizes the result of the first part of the literature review. It provides an overview of major Emotional Intelligence assessment measures, in terms of when they were developed, who developed them, what form of EI they measure, theoretical basis, test length and details regarding cost.

Tables 3 – 8 summarize research on the validity and reliability of the 6 tests included in Table 2 . In these tables we summarize the methodology used in major studies assessing reliability and validity as well as the results from these studies.

Collectively, these tables indicate that all 6 of the measures we reviewed have received some support for their reliability and validity. Measures with extensive research include the MSCEIT, SREIT, and TEIQue, and EQ-I and those with less total research are the STEU/STEM and ESCI. Existing research does not indicate that these latter measures are any less valid or reliable that the others; on the contrary they are promising measures but require further tests of reliability and validity. As noted previously, this table confirms that the tests with the strongest current evidence for construct and predictive validity are the self-report/trait EI measures (TEIQue, EQ-I, and SREIT). We note that although there is evidence for construct validity of the SREIT based on associations with theoretically related constructs (e.g., alexithymia, optimism; see Table 4 ), some have suggested the measure is problematic due to its use of self-report questions that primarily measure ability based constructs (see Petrides and Furnham, 2000 ).

In this article we have reviewed six widely used measures of EI and made recommendations regarding their appropriate use. This article was written primarily for researchers and practitioners who are not currently experts on EI and therefore we also clarified the difference between ability EI, trait EI and mixed EI. Overall, we recommend that users should use single, complete tests where possible and choose measures of EI most suitable for their purpose (i.e., choose ability EI when maximal performance is important and trait EI when typical performance is important). We also point out that, across the majority of emotion-related outcomes, trait EI tends to be a stronger predictor and consequently we suggest that new users of EI consider using a trait-based measure before assessing alternatives. The exception is in employment contexts where tests utilizing 360 degree assessment (primarily mixed measures) can also be very useful.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

The QUT library funded the article processing charges for this paper.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: emotional intelligence, measures, questionnaires, trait, ability, mixed, recommendations

Citation: O'Connor PJ, Hill A, Kaya M and Martin B (2019) The Measurement of Emotional Intelligence: A Critical Review of the Literature and Recommendations for Researchers and Practitioners. Front. Psychol. 10:1116. doi: 10.3389/fpsyg.2019.01116

Received: 05 October 2018; Accepted: 29 April 2019; Published: 28 May 2019.

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Copyright © 2019 O'Connor, Hill, Kaya and Martin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Peter J. O'Connor, peter.oconnor@qut.edu.au

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Emotional Intelligence as an Ability: Theory, Challenges, and New Directions

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About 25 years ago emotional intelligence (EI) was first introduced to the scientific community. In this chapter, we provide a general framework for understanding EI conceptualized as an ability. We start by identifying the origins of the construct rooted in the intelligence literature and the foundational four-branch model of ability EI, then describe the most commonly employed measures of EI as ability, and critically review predictive validity evidence. We further approach current challenges, including the difficulties of scoring answers as “correct” in the emotional sphere, and open a discussion on how to increase the incremental validity of ability EI. We finally suggest new directions by introducing a distinction between a crystallized component of EI, based on knowledge of emotions, and a fluid component, based on the processing of emotion information.

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• Emotional intelligence
• Crystallized EI
• Emotion information processing
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Research in the domains of psychology, education, and organizational behavior in the past 30 years has been characterized by a resurgence of interest for emotions, opening the door to new conceptualizations of intelligence that point to the role of emotions in guiding intelligent thinking (e.g., Bower, 1981 ; Zajonc, 1980 ). Earlier work often raised concern surrounding the compatibility between logic and emotion, and the potential interference of emotion in rational behavior, as they were considered to be in “opposition” (e.g., Lloyd, 1979 ). Research shifted into the study of how cognition and emotional processes could interact to enhance thinking, in which context Salovey and Mayer first introduced the construct of emotional intelligence (EI). Their initial definition described EI as the “ability to monitor one’s own and other’s feelings and emotions, to discriminate among them, and to use this information to guide one’s thinking and actions” (Salovey & Mayer, 1990 , p. 189).

The definition of EI was heavily influenced by early work focused on describing, defining, and assessing socially competent behavior such as social intelligence (Thorndike, 1920 ). The attempt to understand social intelligence led to further inquiries by theorists such as Gardner ( 1983 ) and Sternberg ( 1988 ), who proposed more inclusive approaches to understanding general intelligence. Gardner’s concepts of intrapersonal intelligence , namely, the ability to know one’s emotions, and interpersonal intelligence, which is the ability to understand other individuals’ emotions and intentions, aided in the development of later models in which EI was originally introduced as a subset of social intelligence (Salovey & Mayer, 1990 ). Further prehistory to EI involved the investigation of the relation of social intelligence to alexithymia , a clinical construct defined by difficulties recognizing, understanding, and describing emotions (e.g., MacLean, 1949 ; Nemiah, Freyberger, & Sifneos, 1976 ), as well as research examining the ability to recognize facial emotions and expressions (Ekman, Friesen, & Ancoli, 1980 ).

EI was popularized in the 1990s by Daniel Goleman’s ( 1995 ) best-selling book, Emotional Intelligence: Why It Can Matter More Than IQ , as well as through a number of other popular books (e.g., Cooper & Sawaf, 1997 ). However, the lack of empirical evidence available at the time to support the “exciting” statements and claims about the importance of EI in understanding human behavior and individual differences (Davies, Stankov, & Roberts, 1998 ) prompted critiques and further investigation into the construct. Major psychological factors such as intelligence, temperament, personality, information processing, and emotional self-regulation have been considered in the conceptualization of EI, leading to a general consensus that EI may be multifaceted and could be studied from different perspectives (Austin, Saklofske, & Egan, 2005 ; Stough, Saklofske, & Parker, 2009 ; Zeidner, Roberts, & Matthews, 2008 ).

Two conceptually different approaches dominate the current study of EI: the trait and the ability approach (Petrides & Furnham, 2001 ). The trait approach conceives EI as dispositional tendencies, such as personality traits or self-efficacy beliefs (see Petrides, Sanchez-Ruiz, Siegling, Saklofske, & Mavroveli, Chap. 3 , this volume). This approach is often indicated in the literature as also including “mixed” models, although such models are conceptually distinct from conceptions of EI as personality because they consider EI as a mixture of traits, competences, and abilities (e.g., Bar-On, 2006 ; Goleman, 1998 ). Both the trait approach and the “mixed” models share the same measurement methods of EI, namely, self-report questionnaires. In contrast, the ability approach conceptualizes EI as a cognitive ability based on the processing of emotion information and assesses it with performance tests. The current chapter deals with the latter approach, where we first outline Mayer and Salovey’s ( 1997 ) foundational four-branch ability EI model, then describe commonly used and new measures of EI abilities, critically review evidence of EI’s predictive validity, and finally discuss outstanding challenges, suggesting new directions for the measurement and conceptualization of EI as an ability.

Although not the focus of the present contribution, it should be noted that some attempts to integrate both ability and trait EI perspectives exist in the literature, including the multi-level developmental investment model (Zeidner, Matthews, Roberts, & MacCann, 2003 ) and the tripartite model (Mikolajczak, 2009 ). For example, the tripartite model suggests three levels of EI: (1) knowledge about emotions, (2) ability to apply this knowledge in real-world situations, and (3) traits reflecting the propensity to behave in a certain way in emotional situations (typical behavior). Research and applications on this tripartite model are currently underway (e.g., Laborde, Mosley, Ackermann, Mrsic, & Dosseville, Chap. 11 , this volume; Maillefer, Udayar, Fiori, submitted ). More theory and research is needed to elucidate how the different EI approaches are related with each other. What all of these theoretical frameworks share in common is their conceptualization of EI as a distinct construct from traditional IQ and personality, which facilitates the potential for prediction of, and influence on, various real-life outcomes (Ciarrochi, Chan, & Caputi, 2000 ; Mayer, Salovey, & Caruso, 2008 ; Petrides, Perez-Gonzalez, & Furnham, 2007 ).

The Four-Branch Ability EI Model

The main characteristic of the ability approach is that EI is conceived as a form of intelligence. It specifies that cognitive processing is implicated in emotions, is related to general intelligence, and therefore ought to be assessed through performance measures that require respondents to perform discrete tasks and solve specific problems (Freeland, Terry, & Rodgers, 2008 ; Mayer, Caruso, & Salovey, 2016 ; Mayer & Salovey, 1997 ). The mainstream model of EI as an ability is the four-branch model introduced by Mayer and Salovey ( 1997 ), which has received wide acknowledgment and use and has been foundational in the development of other EI models and measures. The four-branch model identifies EI as being comprised of a number of mental abilities that allow for the appraisal, expression, and regulation of emotion, as well the integration of these emotion processes with cognitive processes used to promote growth and achievement (Salovey & Grewal, 2005 ; Salovey & Mayer, 1990 ). The model is comprised of four hierarchically linked ability areas, or branches: perceiving emotions, facilitating thought using emotions, understanding emotions, and managing emotions (see Fig. 2.1 ).

The Mayer and Salovey ( 1997 ) four-branch model of emotional intelligence (EI) abilities

Perceiving emotions (Branch 1) refers to the ability to identify emotions accurately through the attendance, detection, and deciphering of emotional signals in faces, pictures, or voices (Papadogiannis, Logan, & Sitarenios, 2009 ). This ability involves identifying emotions in one’s own physical and psychological states, as well as an awareness of, and sensitivity to, the emotions of others (Mayer, Caruso, & Salovey, 1999 ; Papadogiannis et al., 2009 ).

Facilitating thought using emotions (Branch 2) involves the integration of emotions to facilitate thought. This occurs through the analysis of, attendance to, or reflection on emotional information, which in turn assists higher-order cognitive activities such as reasoning, problem-solving, decision-making, and consideration of the perspectives of others (Mayer & Salovey, 1997 ; Mayer, Salovey, & Caruso, 2002 ; Papadogiannis et al., 2009 ). Individuals with a strong ability to use emotions would be able to select and prioritize cognitive activities that are most conducive to their current mood state, as well as change their mood to fit the given situation in a way that would foster better contextual adaptation.

Understanding emotions (Branch 3) comprises the ability to comprehend the connections between different emotions and how emotions change over time and situations (Rivers, Brackett, Salovey, & Mayer, 2007 ). This would involve knowledge of emotion language and its utilization to identify slight variations in emotion and describe different combinations of feelings. Individuals stronger in this domain understand the complex and transitional relationships between emotions and can recognize emotional cues learned from previous experiences, thus allowing them to predict expressions in others in the future (Papadogiannis et al., 2009 ). For example, an understanding that a colleague is getting frustrated, through subtle changes in tone or expression, can improve individuals’ communication in relationships and their personal and professional performances.

Finally, managing emotions (Branch 4) refers to the ability to regulate one’s own and others’ emotions successfully. Such ability would entail the capacity to maintain, shift, and cater emotional responses, either positive or negative, to a given situation (Rivers et al., 2007 ). This could be reflected in the maintenance of a positive mood in a challenging situation or curbing elation at a time in which an important decision must be made. Recovering quickly from being angry or generating motivation or encouragement for a friend prior to an important activity are illustrations of high-level emotion management (Papadogiannis et al., 2009 ).

The four EI branches are theorized to be hierarchically organized, with the last two abilities (understanding and management), which involve higher-order (strategic) cognitive processes, building on the first two abilities (perception and facilitation), which involve rapid (experiential) processing of emotion information (Mayer & Salovey, 1997 ; Salovey & Grewal, 2005 ). It should be noted that the proposed hierarchical structure of the model, as well as its four distinctive branches, have been contradicted. First, developmental evidence suggests that abilities in different EI domains (e.g., perceiving, managing) are acquired in parallel rather than sequentially, through a complex learning process involving a wide range of biological and environmental influences (Zeidner et al., 2003 ). Though this conceptualization supports the notion that lower-level competencies aid in the development of more sophisticated skills, it also identifies ways in which the four EI branches are sometimes developed simultaneously, with lower-level abilities of perceiving, facilitating, understanding, and managing emotions at the same time leading to their later improvement.

The four-branch model has also been challenged through factor analysis in several cases, which did not support a hierarchical model with one underlying global EI factor (Fiori & Antonakis, 2011 ; Rossen, Kranzler, & Algina, 2008 ). Moreover, facilitating thought using emotions (Branch 2) did not emerge as a separate factor and was found to be empirically redundant with the other branches (Fan, Jackson, Yang, Tang, & Zhang, 2010 ; Fiori et al., 2014 ; Fiori & Antonakis, 2011 ; Gignac, 2005 ; Palmer, Gignac, Manocha, & Stough, 2005 ), leading scholars to adopt a revised three-branch model of ability EI, comprised of emotion recognition, emotion understanding, and emotion management (Joseph & Newman, 2010 ; MacCann, Joseph, Newman, & Roberts, 2014 ). Nevertheless, the four branches remain the foundation for current ability EI models, and their description aids in the theoretical understanding of the content domains covered by ability-based perspectives on EI (Mayer et al., 2016 ).

Measurement of EI Abilities

How ability EI is measured is critically important to how the results are interpreted. The fact that ability EI is measured by maximum-performance tests, as is appropriate for a form of intelligence, instead of self-report questionnaires, as is the case for trait EI (see Petrides et al., Chap. 3 , this volume) can, in itself, lead to different results (Brackett, Rivers, Shiffman, Lerner, & Salovey, 2006 ). This is analogous to asking people to provide evidence of their intelligence by utilizing a performance IQ measure versus asking them how high they think their IQ is. Although most individuals have insight with regard to their own abilities, there are those who do not. There are, of course, others who over- or underestimate their intelligence unintentionally or for social desirability purposes, resulting in different scores depending on the format of measurement. Thus, it would be challenging to determine whether the results are attributable to the construct itself or to the assessment methods that are being used (MacCann & Roberts, 2008 ).

Though this example is referring to empirically acknowledged problems with self-report measures in general, reflected in vulnerability to faking, social desirability, and ecological validity (Grubb & McDaniel, 2007 ; Roberts, Zeidner, & Matthews, 2007 ), problems with performance measures of EI that may alter the response outcome also exist. For instance, typical ability EI items require individuals to demonstrate their “ability” to perceive, use, understand, and manage emotions by responding to a variety of hypothetical scenarios and visual stimuli, thus deeming the incorrect/correct response format as a method of scoring. Although this may correlate with real-life outcomes, it may not be an accurate representation of EI in real-life social interactions (Vesely, 2011 ; Vesely-Maillefer, 2015 ).

With these considerations in mind , we provide below a short description of the most commonly used as well as some newly developed tests to measure EI abilities.

The Mayer-Salovey-Caruso Emotional Intelligence Test

The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer et al., 2002 ; Mayer, Salovey, Caruso, & Sitarenios, 2003 ) is the corresponding measure of the dominant-to-date four-branch theoretical model of ability EI (Mayer & Salovey, 1997 ). This is a performance-based measure that provides a comprehensive coverage of ability EI by assessing how people perform emotion tasks and solve emotional problems. It assesses the four EI branches with 141 items distributed across eight tasks (two tasks per branch). Perceiving emotions (Branch 1) is assessed with two emotion perception tasks: (1) the faces task involves identifying emotions conveyed through expressions in photographs of people’s faces; and (2) the pictures task involves identifying emotions in pictures of landscapes and abstract art. For both tasks, respondents are asked to rate on a 5-point scale the degree to which five different emotions are expressed in each stimulus. Facilitating thought (Branch 2) is assessed with two tasks: (1) the facilitation task involves evaluating how different moods may facilitate specific cognitive activities; and (2) the sensations task involves comparing emotions to other sensations, such as color, light, and temperature. For both tasks, respondents are asked to indicate which of the different emotions best match the target activity/sensation. Understanding emotions (Branch 3) is assessed with two multiple-choice tests: (1) the changes test involves questions about how emotions connect to certain situations and how emotions may change and develop over time; and (2) the blends test involves questions about how different emotions combine and interact to form new emotions. For both tests, respondents are asked to choose the most appropriate of five possible response options. Managing emotions (Branch 4) is assessed with two situational judgment tests (SJTs) using a series of vignettes depicting real-life social and emotional situations: (1) the emotion management test involves judgments about strategies for regulating the protagonist’s own emotions in each situation; and (2) the emotional relations test involves judgments about strategies for managing emotions within the protagonist’s social relationships. For both tests, respondents are asked to rate the level of effectiveness of several different strategies, ranging from 1 = very ineffective to 5 = very effective.

The MSCEIT assessment yields a total EI score, four-branch scores, and two area scores for experiential EI (Branches 1 and 2 combined) and strategic EI (Branches 3 and 4 combined). Consistent with the view of EI as a cognitive ability , the scoring of item responses follows the correct/incorrect format of an ability-based IQ test while also requiring the individual to be attuned to social norms (Salovey & Grewal, 2005 ). The correctness of the MSCEIT responses can be determined in one of two ways: (a) based on congruence with the answers of emotion experts (expert scoring) or (b) based on the proportion of the sample that endorsed the same answer (general consensus scoring) (Mayer et al., 2003 ; Papadogiannis et al., 2009 ; Salovey & Grewal, 2005 ). Mayer et al. ( 2003 ) reported high agreement between the two scoring methods in terms of correct answers ( r  = 0.91) and test scores ( r  = 0.98). The test internal consistency reliability (split half) is r  = 0.91–0.93 for the total EI and r  = 0.76–0.91 for the four-branch scores, with expert scoring producing slightly higher reliability estimates (Mayer et al., 2003 ).

The MSCEIT has been the only test available to measure EI as an ability for a long time, and much of the existing validity evidence on ability EI, which we review in the next section, is based on the MSCEIT, introducing the risk of mono-method bias in research. Although there are other standardized tests that can be used to measure specific EI abilities (described below), the MSCEIT remains the only omnibus test to measure all four branches of the ability EI model in one standardized assessment. Another attractive feature of the MSCEIT is the availability of a matching youth research version (MSCEIT-YRV; Mayer, Salovey, & Caruso, 2005 ; Rivers et al., 2012 ), which assesses the same four EI branches using age-appropriate items for children and adolescents (ages 10–17). However, a major barrier to research uses of the MSCEIT and its derivatives is that these tests are sold commercially and scored off-site by the publisher, Multi-Health Systems Inc. Furthermore, the MSCEIT has several well-documented psychometric limitations (Fiori et al., 2014 ; Fiori & Antonakis, 2011 ; Maul, 2012 ; Rossen et al., 2008 ), which have prompted researchers to develop alternative instruments, to generalize findings across assessments , and to create non-commercial alternatives for research.

Tests of Emotion Understanding and Management

Recently, there has been an important advancement in ability EI measurement: the introduction of a second generation of ability EI tests, notably the Situational Test of Emotional Understanding (STEU) and the Situational Test of Emotion Management (STEM) introduced by MacCann and Roberts ( 2008 ). Both the STEU and the STEM follow the SJT format similar to that used for the managing emotions branch of the MSCEIT, where respondents are presented with short vignettes depicting real-life social and emotional situations (42 on the STEU and 44 on the STEM) and asked to select, among a list of five, which emotion best describes how the protagonist would feel in each situation (STEU) or which course of action would be most effective in managing emotions in each situation (STEM). Correct answers on the STEU are scored according to Roseman’s (2001) appraisal theory (theory-based scoring), and correct answers on the STEM are scored according to the judgments provided by emotion experts (expert scoring). The reliability of the two tests is reported to be between alpha = 0.71 and 0.72 for STEU and between alpha = 0.68 and 0.85 for STEM (Libbrecht & Lievens, 2012 ; MacCann & Roberts, 2008 ). Brief forms of both tests (18–19 items) have also been developed for research contexts where comprehensive assessment of EI is not required (Allen et al., 2015 ). There is also an 11-item youth version of the STEM (STEM-Y; MacCann, Wang, Matthews, & Roberts, 2010 ) adapted for young adolescents. The STEU and STEM items are available free of charge in the American Psychological Association PsycTESTS database (see also https://doi.org/10.1037/a0012746.supp ). These tests look promising, although they have been introduced recently and more research is needed to ascertain their construct and predictive validity (but see Burrus et al., 2012 ; Libbrecht & Lievens, 2012 ; Libbrecht, Lievens, Carette, & Côté, 2014 ).

The text-based format of the SJT items on the STEU, STEM, and MSCEIT raises concerns about their ecological validity, as real-life social encounters require judgments of verbal as well as nonverbal cues . To address this concern, MacCann, Lievens, Libbrecht, and Roberts ( 2016 ) recently developed a multimedia test of emotion management, the 28-item multimedia emotion management assessment (MEMA) , by transforming the original text-based scenarios and response options from the STEM into a video format. MacCann et al.’s ( 2016 ) comparisons of the MEMA with the text-based items from the MSCEIT managing emotions branch produced equivalent evidence of construct and predictive validity for the two tests.

Tests of Emotion Perception

There are several long-existing standardized measures of perceptual accuracy in recognizing emotions, many of which were introduced even before the construct of EI. Therefore, these were not presented as EI tests but do capture the perceiving emotions branch of EI and could be considered as viable alternatives to the MSCEIT. Among the most frequently used of these tests are the Diagnostic Analysis of Nonverbal Accuracy (DANVA ; Nowicki & Duke 1994 ), the Profile of Nonverbal Sensitivity (PONS ; Rosenthal, Hall, DiMatteo, Rogers, & Archer, 1979 ), and the Japanese and Caucasian Brief Affect Recognition Test (JACBART ; Matsumoto et al., 2000 ). Like the MSCEIT faces task, these tests involve viewing a series of stimuli portraying another person’s emotion, and the respondent’s task is to correctly identify the emotion expressed. However, unlike the rating-scale format of the MSCEIT faces items, these other tests use a multiple-choice format, where respondents must choose one emotion, from a list of several, that best matches the stimulus. This difference in response format could be one possible reason why performance on the MSCEIT perceiving branch shows weak convergence with these other emotion recognition tests (MacCann et al., 2016 ).

Different emotion recognition tests use different types of stimuli and modalities (e.g., photos of faces, audio recordings) and cover different numbers of target emotions. For example, the DANVA uses 24 photos of male and female facial expressions and 24 audio recordings of male and female vocal expressions of the same neutral sentence (“I am going out of the room now but I’ll be back later”), representing 1 of 4 emotions (happiness, sadness, anger, and fear) in 2 intensities, either weak or strong. The PONS is presented as a test assessing interpersonal sensitivity, or the accuracy in judging other people’s nonverbal cues and affective states. It includes 20 short audio and video segments of a woman for a total length of 47 minutes. The task is to identify which of two emotion situations best describes the woman’s expression. The JACBART uses 56 pictures of Japanese and Caucasian faces expressing 1 of 5 emotions (fear, happiness, sadness, anger, surprise, contempt, and disgust). The interesting feature of this test, in comparison to others, is that it employs a very brief presentation time (200 ms). Each expressive picture is preceded and followed by the neutral version of the same person expressing the emotion in the target picture, so as to reduce post effects of the pictures and get a more spontaneous evaluation of the perceived emotion.

Both the MSCEIT perceiving branch and the earlier emotion recognition tests have been critiqued for their focus on a single modality (i.e., still photos vs. audio recordings), as well as for their restricted range of target emotions (i.e., few basic emotions, only one of them positive), which limits their ecological validity and precludes assessing the ability to differentiate between more nuanced emotion states (Schlegel, Fontaine, & Scherer, 2017 ; Schlegel, Grandjean, & Scherer, 2014 ). The new wave of emotion recognition tests developed at the Swiss Center for Affective Sciences – the Multimodal Emotion Recognition Test (MERT ; Bänziger, Grandjean, & Scherer, 2009 ) and the Geneva Emotion Recognition Test (GERT ; Schlegel et al., 2014 ) – aim to rectify both problems by employing more ecologically valid stimuli, involving dynamic multimodal (vocal plus visual) portrayals of 10 (MERT) to 14 (GERT) different emotions, half of them positive. For example, the GERT consists of 83 videos (1–3 s long) of professional male and female actors expressing 14 emotions (joy, amusement, pride, pleasure, relief, interest, anger, fear, despair, irritation, anxiety, sadness, disgust, and surprise) through facial expressions, nonverbal gestural/postural behavior, and audible pseudo-linguistic phrases that resemble the tone of voice of the spoken language. A short version (GERT-S) is also available with 42 items only (Schlegel & Scherer, 2015 ). The reliability is 0.74 for the long version. The emerging evidence for the construct and predictive validity of the GERT looks promising (Schlegel et al., 2017 ).

Predictive Validity of Ability EI

Among the most researched and debated questions in the ability EI literature is whether ability EI can predict meaningful variance in life outcomes – does ability EI matter? (Antonakis, Ashkanasy, & Dasborough, 2009 ; Brackett, Rivers, & Salovey, 2011 ; Mayer, Salovey, & Caruso, 2008 ). Several studies have shown that ability EI predicts health-related outcomes, including higher satisfaction with life, lower depression, and fewer health issues (Fernández-Berrocal & Extremera, 2016 ; Martins, Ramalho, & Morin, 2010 ). Furthermore, high EI individuals tend to be perceived by others more positively because of their greater social-emotional skills (Fiori, 2015 ; Lopes, Cote, & Salovey, 2006 ) and thus enjoy better interpersonal functioning in the family (Brackett et al., 2005 ), at work (Côte & Miners, 2006 ), and in social relationships (Brackett et al., 2006 ). Ability EI has also been positively implicated in workplace performance and leadership (Côte, Lopes, Salovey, & Miners, 2010 ; O’Boyle, Humphrey, Pollack, Hawver, & Story, 2011 ).

Evidence for ability EI predicting academic success is mixed in post-secondary settings (see Parker, Taylor, Keefer, & Summerfeldt, Chap. 16 , this volume) but more consistent for secondary school outcomes, where ability EI measures have been associated with fewer teacher-rated behavioral and learning problems and higher academic grades (Ivcevic & Brackett, 2014 ; Rivers et al., 2012 ). There is also compelling evidence from over 200 controlled studies of school-based social and emotional learning (SEL) programs, showing that well-executed SEL programs reduce instances of behavioral and emotional problems and produce improvements in students’ academic engagement and grades (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011 ; see also Elias, Nayman, & Duffell, Chap. 12 , this volume). Hoffmann, Ivcevic, and Brackett (Chap. 7 , this volume) describe one notable example of such evidence-based SEL program, the RULER approach , which is directly grounded in the four-branch ability EI model.

Although these results are certainly encouraging regarding the importance of ability EI as a predictor of personal, social, and performance outcomes, there are several important caveats to this conclusion. First, ability EI measures may capture predominantly the knowledge aspects of EI, which can be distinct from the routine application of that knowledge in real-life social-emotional interaction. This disconnect between emotional knowledge and application of knowledge is also supported by the tripartite model of EI mentioned above (Mikolajczak, 2009 ), which separates the ability-based knowledge from trait-based applications within its theory. For example, it posits the possibility that a person with strong cognitive knowledge and verbal ability can describe which emotional expression would be useful in a given situation, but may not be able to select or even display the corresponding emotion in a particular social encounter. Indeed, many other factors, apart from intelligence, contribute to people’s actual behavior, including personality, motives, beliefs, and situational influences.

This leads to the second caveat: whether ability EI is distinct enough from other established constructs, such as personality and IQ, to predict incremental variance in outcomes beyond these well-known variables. Although the overlap of EI measures with known constructs is more evident for trait EI measures (Joseph, Jin, Newman, & O’Boyle, 2015 ), some studies have shown that a substantial amount of variance in ability EI tests, in particular the MSCEIT, was predicted by intelligence, but also by personality traits, especially the trait of agreeableness (Fiori & Antonakis, 2011 ). These results suggest that ability EI, as measured with the MSCEIT, pertains not only to the sphere of emotional abilities, as it was originally envisioned, but depends also on one’s personality characteristics, which conflicts with the idea that ability EI should be conceived (and measured) solely as a form of intelligence. Given these overlaps, the contribution of ability EI lowers once personality and IQ are accounted for. For example, the meta-analysis by Joseph and Newman ( 2010 ) showed that ability EI provided significant but rather limited incremental validity in predicting job performance over personality and IQ.

Of course, one may argue that even a small portion of incremental variance that is not accounted for by known constructs is worth the effort. Further and indeed, a more constructive reflection on the role of ability EI in predicting various outcomes refers to understanding why its contributions may have been limited so far. The outcomes predicted by ability EI should be emotion-specific, given that it is deemed to be a form of intelligence that pertains to the emotional sphere. There is no strong rationale for expecting ability EI to predict generic work outcomes such as job performance; for this type of outcome, we already know that IQ and personality account for the most variance. Instead, work-related outcomes that involve the regulation of emotions, such as emotional labor, would be more appropriate. This idea is corroborated by the meta-analytic evidence showing stronger incremental predictive validity of ability EI for jobs high in emotional labor, such as customer service positions (Joseph & Newman, 2010 ; Newman, Joseph, & MacCann, 2010 ).

Another reason why the incremental validity of ability EI measures appears to be rather small may be related to the limits of current EI measures. For example, the MSCEIT has shown to be best suited to discriminate individuals at the low end of the EI ability distribution (Fiori et al., 2014 ). For the other individuals (medium and high in EI), variation in the MSCEIT scores does not seem to reflect true variation in EI ability. Given that most of the evidence on ability EI to date is based on the MSCEIT, it is likely that some incremental validity of ability EI was “lost” due to the limitations of the test utilized to measure it.

Another caveat concerns making inferences about predictive validity of ability EI from the outcomes of EI and SEL programs. Here, the issue is in part complicated by the fact that terms such as “ability” and “competence” are often used interchangeably, but in fact reflect different characteristics, the latter being a trait-like solidification of the former through practice and experience. Many EI programs are in fact meant to build emotional competence, going beyond the mere acquisition of emotional knowledge and working toward the application of that knowledge across different contexts. As such, other processes and factors, apart from direct teaching and learning of EI abilities, likely contribute to positive program outcomes. For example, the most effective school-based SEL programs are those that also modify school and relational environments in ways that would model, reinforce, and provide opportunities for students to practice the newly acquired EI skills in everyday situations (see also Elias et al., Chap. 12 , this volume; Humphrey, Chap. 8 , this volume). Thus, it would be inappropriate to attribute the outcomes of such programs solely to increases in students’ EI abilities, without acknowledging the supportive social and contextual influences.

It is also important to better understand which processes mediate the role of ability EI in improving individuals’ emotional functioning. Social cognitive theories of self-efficacy (Bandura, 1997 ) and self-concept (Marsh & Craven, 2006 ) can inform which types of processes might be involved in linking ability to behavioral change. Specifically, successful acquisition and repeated practice of EI skills can build individuals’ sense of confidence in using those skills (i.e., higher perceived EI self-efficacy), which would increase the likelihood of drawing upon those skills in future situations, in turn providing further opportunities to hone the skills and reinforce the sense of self-competence (Keefer, 2015 ). Research on self-efficacy beliefs in one’s ability to regulate emotions supports this view (Alessandri, Vecchione, & Caprara, 2015 ).

Mayer et al. ( 2016 ) cogently summarized the ambivalent nature of predictive validity evidence for ability EI: “the prediction from intelligence to individual instances of “smart” behavior is fraught with complications and weak in any single instance. At the same time, more emotionally intelligent people have outcomes that differ in important ways from those who are less emotionally intelligent” (p. 291). We concur with this conclusion but would treat it as tentative, given that there are several unresolved issues with the way ability EI has been measured and conceptualized, as discussed below. This opens the possibility that EI’s predictive validity would improve once these measurement and theoretical issues have been clarified.

Measurement and Conceptual Issues

Scoring of correct responses.

One of the greatest challenges of operationalizing EI as an ability has been (and still is) how to score a correct answer on an ability EI test. Indeed, in contrast to personality questionnaires in which answers depend on the unrestricted choice of the respondent and any answer is a valid one, ability test responses are deemed correct or wrong based on an external criterion of correctness. Among the most problematic aspects is the identification of such criterion; it is difficult to find the one best way across individuals who may differ with respect to how they feel and manage emotions effectively (Fiori et al., 2014 ). After all, the very essence of being intelligent implies finding the best solution to contextual adaptation given the resources one possesses. For example, one may be aware that, in principle, a good way to deal with a relational conflict is to talk with the other person to clarify the sources of conflict and/or misunderstanding. However, if one knows they and/or their partner are not good at managing interpersonal relationships , one may choose to avoid confrontation as a more effective strategy in the moment, given the personal characteristics of the individuals involved (Fiori et al., 2014 ).

This example evokes another issue that has not been addressed in the literature on ability EI, namely, the potential difference between what response would be more “intelligent” personally versus socially. One may argue that the solution should fill both needs; however, these may be in contradiction. For instance, suppression of one’s own feelings may help to avoid an interpersonal conflict, an action seen as socially adaptive ; however, this same strategy maybe personally unhealthy if the person does not manage their suppressed emotion in other constructive ways. In this case, a more socially unacceptable response that releases emotion may have been more “emotionally intelligent” as it relates to the self but less so as it relates to others. The problematic part is that current measurement tools do not take these nuances into account. This relates also to the lack of distinction in the literature on emotion skills related to the “self” versus “others,” a criticism discussed below.

In addition, “correctness” of an emotional reaction may depend on the time frame within which one intends to pursue a goal that has emotional implications. For example, if a person is focused on the short-term goal of getting one’s way after being treated unfairly by his or her supervisor, the most “effective” way to manage the situation would be to defend one’s position in front of the supervisor regardless of possible ramifications . In contrast, if one is aiming at a more long-term goal, such as to preserve a good relationship with the boss, the person may accept what is perceived as an unfair treatment and try to “let it go” (Fiori et al., 2014 ).

Scholars who have introduced ability EI measures have attempted to address these difficulties by implementing one of these three strategies to find a correct answer: (a) judge whether an answer is correct according to the extent to which it overlaps with the answer provided by the majority of respondents, also called the consensus scoring ; (b) identify correctness according to the choice provided by a pool of emotion experts, or expert scoring ; and (c) identify whether an answer is correct according to the principles of emotion theories, or theoretical scoring . The consensus scoring was introduced by Mayer et al. ( 1999 ) as a scoring option for the MSCEIT, based on the idea that emotions are genetically determined and shared by all human beings and that, for this reason, the answer chosen by the majority of people can be taken as the correct way to experience emotions. Unfortunately, this logic appears profoundly faulty once one realizes that answers chosen by the majority of people are by definition easy to endorse and that tests based on this logic are not challenging enough for individuals with average or above average EI (for a thorough explanation of this measurement issue, see Fiori et al., 2014 ).

Furthermore, what the majority of people say about emotions may simply reflect lay theories, which, although shared by most, can still be incorrect. The ability to spot a fake smile is a good example of this effect. This task is challenging for all but a restricted group of emotion experts (Maul, 2012 ). In this case, the “correct” answer should be modeled on the few that can spot fake emotions, not on the modal answer in the general population. In fact, the emotionally intelligent “prototype” should be among the very few that can spot fake emotions, rather than among the vast majority of people that get them wrong. Thus, from a conceptual point of view, it would make better sense to score test takers’ responses with respect to a group of emotion experts (high EI individuals ), as long as items reflect differences between typical individuals and those that are higher than the norm (Fiori et al., 2014 ). Items for which the opinion of experts is very close to that of common people should be discarded in testing EI abilities, because they would not be difficult enough to discriminate among individuals with different levels of EI.

Finally, scoring grounded in emotion theories offers a valuable alternative, as it allows setting item difficulties and response options in correspondence with theory-informed emotion processes (Schlegel, 2016 ). Some of the recently developed ability EI tests have utilized this approach. For example, response options on the STEM-B (Allen et al., 2015 ) and MEMA (MacCann et al., 2016 ) map onto the various emotion regulation strategies outlined in Gross’ ( 1998 ) process model of emotion regulation. Based on this theory, certain strategies (e.g., positive reappraisal, direct modification) would be more adaptive than others (e.g., emotion suppression, avoidance), and the correct responses on the ability EI items can be set accordingly. However, this too may appear to be a “subjective” criterion because of the differences among theories regarding what is deemed the adaptive way to experience, label, and regulate emotions. For example, suppression is regarded as a deleterious strategy to manage emotions because of its negative long-term effects (Gross, 1998 ). However, evidence suggests (Bonanno, Papa, Lalande, Westphal, & Coifman, 2004 ; Matsumoto et al., 2008 ) that the damaging effect of suppressing emotions may depend on how this strategy fits with the social and cultural contexts, as also discussed earlier in the example of the relational conflict. Moreover, there are systematic differences across cultures in how emotions are to be expressed, understood, and regulated “intelligently” (see Huynh, Oakes, & Grossman, Chap. 5 , this volume), which poses additional challenges for developing an unbiased scoring system for ability EI tests.

Self- vs. Other-Related EI Abilities

Another issue that has not received much attention in the literature and that might explain why ability EI contributions in predicting outcomes are limited refers to the fact that ability EI theorization, in particular Mayer and Salovey’s ( 1997 ) four-branch model, blurs the distinction between emotional abilities that refer to the self with those that refer to others (e.g., perceiving emotions in oneself vs. in others, understanding what one is feeling vs. someone else is feeling, etc.), as if using the abilities for perceiving/understanding/managing emotions in oneself would automatically entail using these abilities successfully with others. However, being good at understanding one’s own emotional reactions does not automatically entail being able to understand others’ emotional reactions (and vice versa). There is some intuitive evidence: some professionals (e.g., emotion experts, psychologists) may be very good at understanding their patients’ emotional reactions, but not as good at understanding their own emotional reactions. Further, scientific evidence also exists : knowledge about the self seems to be processed in a distinctive way compared to social knowledge. For example, brain imaging studies show that taking the self-perspective or the perspective of someone else activates partially different neural mechanisms and brain regions (David et al., 2006 ; Vogeley et al., 2001 ).

The most important implication of considering the two sets of abilities (e.g., employed for oneself or with respect to others) as distinct rather than equivalent is that each of them might predict different outcomes. Recent evidence comes from a program evaluation study of an EI training program for teachers investigating the mechanisms by which EI skills are learned (described in Vesely-Maillefer & Saklofske, Chap. 14 , this volume). Preliminary results showed differential perceived outcomes in self- versus other-related EI skills , dependent on which ones were taught and practiced. Specifically, practice of self-relevant EI skills was the primary focus of the program, and these were perceived to have increased by the program’s end more than the other-related EI skills (Vesely-Maillefer, 2015 ).

It is worth noting that some recently introduced measures of EI make the explicit distinction between the self- and other-oriented domains of abilities. For instance, the Profile of Emotional Competence (PEC; Brasseur, Grégoire, Bourdu, & Mikolajczak, 2013 ) is a trait EI questionnaire that distinguishes between intrapersonal and interpersonal EI competences, and the Genos emotional intelligence test (Gignac, 2008 ) measures awareness and management of emotions in both self and others separately. Additionally, a new ability EI test currently under development at the University of Geneva, the Geneva Emotional Competence Test (Mortillaro & Schlegel), distinguishes between emotion regulation in oneself (emotion regulation) and in others (emotion management). The adoption of these more precise operationalizations of self- and other-related EI abilities would allow collecting “cleaner” validity data for the ability EI construct.

Conscious vs. Automatic Processes

Among the most compelling theoretical challenges EI researchers need to address is to understand the extent to which ability EI depends on conscious versus automatic processes (Fiori, 2009 ). Most ability EI research, if not all, has dealt with the investigation of how individuals thoughtfully reason about their own and others’ emotional experience by consciously feeling, understanding, regulating, and recognizing emotions. However, a large portion of emotional behavior is, in fact, not conscious (Feldman Barrett, Niedenthal, & Winkielman, 2005 ). For example, individuals may process emotional signals, such as nonverbal emotional behavior, without having any hint of conscious perception (Tamietto & de Gelder, 2010 ). Applied to the domain of ability EI, this implies that individuals may be able to use emotions intelligently even without being aware of how they do it and/or without even realizing that they are doing it. Research on cognitive biases in emotional disorders supports this idea: systematic errors in the automatic processing of emotion information have been causally implicated in vulnerability for mood and anxiety disorders (Mathews & MacLeod, 2005 ).

EI scholars need to acknowledge the automaticity component of ability EI, first, because it is theoretically relevant and second, because it might explain additional variance in emotionally intelligent behavior due to subconscious or unconscious processes that have been ignored to date. Some contributions have provided conceptual models (Fiori, 2009 ) and raised theoretical issues (Ybarra, Kross, & Sanchez-Burks, 2014 ) that would help to move forward in this direction. Evidence-based research is the next step and would require scholars to employ experimental paradigms in which the level of emotional consciousness is manipulated in order to observe its effects on emotionally intelligent behavior.

New Developments and Future Directions

The domain of research on ability EI is in its early developmental stage, and there is still much to explore, both on the theoretical and the measurement side. The seminal four-branch model introduced by Mayer and Salovey ( 1997 ) needs to be further developed and refined on the basis of the most recent research findings. As mentioned above, the model of ability EI as composed of four hierarchically related branches underlying a latent global EI factor does not seem to be supported, at least in its original formulation (e.g., Fiori & Antonakis, 2011 ; Rossen et al., 2008 ). On the measurement side, it seems as if progress has been made in terms of introducing new tests to measure specific EI abilities. A further step is to clarify what exactly scores on these tests are measuring and what mechanisms account for test performance. For instance, in the past the possibility was raised that individuals high in EI might be overly sensitive to emotions felt by themselves and by others in a way that could in certain circumstances compromise their health (e.g., Ciarrochi et al., 2002 ) and social effectiveness (Antonakis et al., 2009 ). Recent empirical evidence (Fiori & Ortony, 2016 ) showed that indeed high EI individuals were more strongly affected by incidental anger in forming impressions of an ambiguous target (study 1) and that they amplified the importance of emotion information, which affected their social perception (study 2). This characteristic associated with being high in EI was called “hypersensitivity ,” and it was deemed to have either positive or negative effects depending on the context (Fiori & Ortony, 2016 ).

Further investigation should also clarify which aspects of ability EI may be missing in current measurement and theorization. Ability EI tests, including the second generation, show moderate correlations with measures of intelligence, a finding that supports the conceptualization of EI as a form of intelligence. Interestingly, the component of intelligence most strongly correlated with measures of EI abilities – particularly the strategic branches of understanding and managing – is crystallized intelligence , or g c (Farrelly & Austin, 2007 ; MacCann, 2010 ; Mayer, Roberts, & Barsade, 2008 ; Roberts et al., 2006 , 2008 ), which suggests that current tests represent especially the acquired knowledge about emotions people possess. Indeed, items of the STEU and the STEM (as well as most items of the MSCEIT) require respondents to identify the best strategy to cope with emotionally involving situations described in a short vignette or to understand the emotion one would feel in a hypothetical scenario. Individuals may correctly answer such items relying on what they know about emotions, leaving open the question of whether they would be able to apply that knowledge in novel situations. For instance, individuals with Asperger’s syndrome undertaking ability EI training improved their EI scores while still lacking fundamental interpersonal skills (Montgomery, McCrimmon, Schwean, & Saklosfke, 2010 ). All in all, it appears that the STEU and the STEM measure performance in hypothetical situations, rather than actual performance, the former being more dependent on the declarative knowledge individuals possess about emotions (Fiori, 2009 ; Fiori & Antonakis, 2012 ). Tests employed to measure emotion recognition ability (e.g., JACBART) are not based on hypothetical scenarios but on pictures or videos of individuals showing emotions. Although these tests require the use of perceptual skills – differently from the tests of strategic EI abilities – they still show a significant association with g c  although to a lesser extent (Roberts et al., 2006 ). Indeed, individuals may rely on the knowledge they possess of how emotions are expressed to correctly identify emotions.

At the same time, ability EI measures show little associations with emotion-processing tasks that are more strongly related to the fluid component of intelligence, or g f , such as inspection time and selective attention to emotional stimuli (Farrelly & Austin, 2007 ; Fiori & Antonakis, 2012 ). For example, Fiori and Antonakis ( 2012 ) examined predictors of performance on a selective attention task requiring participants to ignore distracting emotion information. Results showed that fluid intelligence and the personality trait of openness predicted faster correct answers on the attentional task. Interestingly, none of the ability EI test facets (as measured with the MSCEIT) predicted performance, suggesting that the MSCEIT taps into something different from emotion information processing . Austin ( 2010 ) examined the associations of the STEU and the STEM with inspection time on an emotion perception task and found no relations for the STEM. The STEU scores predicted inspection time only at intermediate and long stimulus durations, but not at very brief exposures requiring rapid processing of the stimuli, suggesting that the STEU captures conscious rather than preconscious emotion information processing. MacCann, Pearce, and Roberts ( 2011 ) looked at the associations of the strategic EI abilities (measured with the STEU and STEM), fluid and crystallized intelligence , and emotion recognition tasks based on processing of visual and auditory emotional stimuli. Their results revealed an ability EI factor distinct from g, but with some subcomponents more strongly related to g f (particularly those involving visual perception of emotional stimuli ) and others to g c (those concerning strategic abilities and the auditory perception of emotional stimuli). This study suggested the presence of potentially distinct subcomponents of fluid and crystallized ability EI, although the authors did not investigate this possibility (MacCann et al., 2011 ).

The association between current ability EI tests and emotion-information processing tasks has not been systematically addressed in the literature and deserves further investigation. In fact, it is expected that high-EI individuals would have wider emotion knowledge but also stronger emotion-processing abilities in dealing with emotional stimuli, both accounting for how individuals perform in emotionally charged situations and each predicting distinct portions of emotionally intelligent behavior. The identification of a component of ability EI that is not (fully) captured by current tests is important because it would reveal an aspect of EI that is not measured (and therefore omitted) in current research. Yet, such a component may be relevant to predicting emotionally intelligent behavior. For example, Ortony, Revelle, and Zinbarg ( 2008 ), in making the case as to why ability EI would need a fluid , experiential component, cite the case of intelligent machines, which, on the basis of algorithmic processes, would be able to perform well on the ability EI test even without being able to experience any emotion. This example highlights the importance of measuring factors associated with emotional experience and the processing of emotion information, beyond emotion knowledge, which would be better captured by bottom-up processes generated by the encoding and treatment of emotion information.

In sum, research suggests that within a broad conceptualization of ability EI as a unique construct, there might be two distinct components : one related to top-down, higher-order reasoning about emotions, depending more strongly on acquired and culture-bound knowledge about emotions, hereafter named the crystallized component of ability EI (EI c , or emotion knowledge ), and another based on bottom-up perceptual responses to emotion information, requiring fast processing and hereafter named the fluid component of ability EI (EI f , or emotion information processing ) (see Fig. 2.2 ).

Conceptualization of ability EI as composed of a fluid (EI f ) and crystallized (EI c ) component, both affected by conscious and automatic emotion processes

An additional way to look at the relationship between the two components underlying ability EI is by considering what might account for such differences, namely, the type of processing (conscious vs. automatic) necessary for ability EI tests. The role automatic processes might play in EI has been approached only recently (Fiori, 2009 ), and it is progressively gaining recognition and interest especially in organizational research (Walter, Cole, & Humphrey, 2011 ; Ybarra et al., 2014 ). With respect to the relationship between a crystallized and a fluid component of ability EI, it is plausible that answers to current ability EI tests strongly rely on conscious reasoning about emotions, whereas performance on emotional tasks, such as inspection time and fast categorization of emotional stimuli, for example, relies more on automatic processing. This may be the case as individuals in the latter tasks provide answers without being fully aware of what drives their responses. Thus, current ability EI tests and emotion information processing tasks may be tapping into different ways of processing emotion information (conscious vs. automatic; see also Fiori, 2009 ). The extent to which current ability EI tests depend on controlled processes and are affected by cognitive load is still unaddressed (Ybarra et al., 2014 ). Given that no task is process pure (Jacoby, 1991 ), both controlled and automatic processes are likely to account for responses in current ability EI tests. However, such tests require great effort and deep reasoning about emotions and thus likely tap mostly into controlled processes.

The most important implication of the engagement of two types of processing in ability EI is that each of them may predict a different type of emotional performance. More specifically, ability EI tests that rely more on emotion knowledge or the crystallized component of EI may be more suited to predict effortful and consciously accessible emotional behavior, whereas tasks meant to “catch the mind in action” (Robinson & Neighbors, 2006 ), such as those based on emotion information processing , may account mostly for spontaneous and unintentional behavior . If this is the case, then current ability EI tests may predict to a greater extent consciously accessible performance and to a lower extent emotionally intelligent behaviors that depend on spontaneous/automatic processing (Fiori, 2009 ; Fiori & Antonakis, 2012 ). The hypothesized relationship is illustrated in Fig. 2.3 .

Hypothesized effects of the fluid (EI f ) and crystallized (EI c ) ability EI components on emotional behavior

The next generation of ability EI tests will hopefully incorporate more recent theoretical advancements related to additional components of EI – such as sub- or unconscious processes or the fluid , emotion-information processing component of EI. Some may ask how the perfect measure would look like. Knowing that EI is a complex construct, it seems unlikely that “one perfect” measure that would capture all the different components of EI is in the near future. It may be more realistic to aim for “several good” measures of EI, each of them capturing key aspects of this construct with satisfactory reliability and validity. Despite some noted theoretical and practical gaps in the current literature on ability EI, the construct of EI is still in its developmental stages. With increasing interest in EI’s potential for real-world applications and its growing literature, this domain of research provides a challenging yet exciting opportunity for innovative researchers.

Change history

31 december 2019.

Chapter 2 of this book has been converted to open access and the copyright holder has been changed to ‘The Author(s)’.The book has also been updated with these changes.

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Acknowledgments

This chapter benefited from the support of the Swiss National Science Foundation (grant no 100014_165605 awarded to Marina Fiori).

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Fiori, M., Vesely-Maillefer, A.K. (2018). Emotional Intelligence as an Ability: Theory, Challenges, and New Directions. In: Keefer, K., Parker, J., Saklofske, D. (eds) Emotional Intelligence in Education. The Springer Series on Human Exceptionality. Springer, Cham. https://doi.org/10.1007/978-3-319-90633-1_2

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