
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12299-2
10.1016/j.heliyon.2024.e36268
e36268
Research Article
Individual and group emotional intelligence measurement of sex differences and invariance for individual (WLEIS-S) and group (WEIP-S) emotional intelligence measurement scales
P. León Samuel sparra@ujaen.es
a
García-Martínez Inmaculada igmartinez@ugr.es
b⁎
Augusto-Landa José María jaugusto@ujaen.es
c
a Department of Education, University of Jaén, Spain
b Department of Didactics and School Organization, University of Granada, Spain
c Department of Psychology, University of Jaén, Spain
⁎ Corresponding author. Department of Didactics and School Organization, Faculty of Education, Campus de Cartuja s/n, 18071, Granada, Spain. igmartinez@ugr.es
13 8 2024
15 9 2024
13 8 2024
10 17 e362681 8 2023
7 8 2024
13 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Different international research groups focus on the study of socio-emotional resources and tools to facilitate adequate management of daily challenges and demands among teachers. This allows for better personal and professional performance. One of these resources that has attracted most attention in recent decades has been that of emotional intelligence. In this regard, the present study set out to analyse the psychometric properties of trait emotional intelligence as a construct. For this purpose, the study focused on two EI measurement instruments. One of the instruments (WLEIS-S) measures individual emotional intelligence and the other instrument (WEIP-S) measures group emotional intelligence. Against this background, the possible invariance of both scales with respect to the sex variable is analysed, as well as possible differences in the variables measured by the scales between sexes. To this end, 452 primary education teachers from Southern Spain filled in the WLEIS-S and WEIP-S tests. The results found in the factor analyses carried out with both instruments showed an excellent fit, as well as good internal consistency. Moreover, both instruments showed robust invariance, which indicates that both scales measure the emotional intelligence construct consistently for both women and men. No differences were found in the assessed latent variables between sexes. To conclude, this study shows psychometric evidence supporting the suitability of the WLEIS-S and WEIP-S scales for the accurate assessment of individual and group emotional intelligence in women and men in the teacher population.

Keywords

Individual emotional intelligence
Group emotional intelligence
WLEIS-S
WEIP-S
Measurement invariance
Sex
==== Body
pmc1 Introduction

Emotional Intelligence (EI) was born as a scientific construct three decades ago [1]. However, thanks to the book written by Daniel Goleman in 1995 (Emotional Intelligence), this concept became known worldwide. In the period of 1990–2010, the literature has clearly distinguished two major conceptual approaches to the study of EI. The first one, worldwide known as the ability models [2] indicate that EI enables the use of emotions to promote more effective reasoning and to think more intelligently about one's emotional life. This model consists of four key dimensions or branches. The first one is related to Emotional Perception, which is the ability to identify and recognise emotions in oneself and others; the second referred to Emotional Facilitation is the ability to use emotions to support thinking and problem solving; the third one is Emotional Understanding is the ability to understand the complexity of emotions, how they evolve over time and how they interact with each other; and finally, it highlight the Emotional Management, which is the ability to manage emotions effectively in oneself and in relationships with others.

On the other hand, the trait or mixed models propose a broad approach to EI, and these are understood as a combination of established personality traits, social-emotional abilities, motivational issues and several cognitive skills [3,4]. The Bar-On Model (2000) is called the Well-Being Model, it is based on competencies that attempt to explain how an individual relates to the people around him/her and to his/her environment. This model is made up of five elements, been the first one the intrapersonal component, which brings together the ability to be aware of, understand and relate to others. In relation to the second one, the interpersonal component, which involves the ability to manage strong emotions and control one's impulses. Moreover it is, the stress management component, which involves the ability to have a positive and optimistic outlook. Regarding to the fourth one, the mood component, which is made up of the ability to adapt to change and solve problems of a personal and social nature. Finally, the adaptability or adjustment component.

The Goleman Model is called the emotional competencies model [5] which is divided into two main areas, the first one is the Personal competencies (Self-awareness and Self-regulation). The second one is the Social competencies (Empathy and Social skills). Generally speaking, its application has been focused on the business world.

Finally, the Petrides and Furham Model [6,7] called the Trait EI Model. It is a multifactorial model that considers EI as a personality trait and is based more on a subject's self-perception than on emotional abilities to work with emotional information.

It consists of fifteen dimensions: adaptability; assertiveness; self- and others' emotional perception; emotional expression; emotional management; emotional regulation; low impulsivity; relationships; self-esteem; self-motivation; social awareness; stress management; empathy; happiness; optimism.

EI in teachers is an area of study that has become more relevant in recent years due to its impact on teaching effectiveness and the emotional well-being of students and teachers themselves. This has been found in several areas of study, for example, Jennings and Greenberg [8] found that teachers with high EI are more effective in managing classroom interactions, which in turn improves students' academic performance. The study developed by Brackett et al. [9] showed that teachers with higher EI skills experience less emotional exhaustion and have higher job satisfaction. On the other hand, the study by Yoo and Carter [10] found that those teachers with higher EI skills improved their conflict management skills. Likewise, Oberle et al. [11] showed that programmes that include emotional intelligence training for teachers can improve students' social-emotional competencies. Other studies such as the one conducted by Chan [12] have found that EI acts as a protector of burnout in teachers and the studies conducted by Augusto-Landa et al. [13] and Pulido-Martos et al. [14] found that EI acts as a protective factor against stress and promotes the use of so-called adaptive strategies. This collection of research highlights the importance of the study of EI in teachers, which has been confirmed by different studies that highlight that EI is of utmost importance for this group. It not only improves their well-being and effectiveness, but also has a positive impact on the classroom climate and the development of students.

EI is measured differently depending on the models. On the one hand, the ability or capacity EI perspective measures the construct through performance or ability tests (e.g. MSCEIT, [15]), that examine differences regarding emotional information processing skills, such as perception, facilitation, understanding or management of emotions [2,16,17]. The structure of these tests is similar to that of a classical intelligence test, and they measure EI as an ability. People are asked to recognise emotions in images of faces, people or landscapes, or to select the best response to different complicated emotional situations in the personal or professional life. Recently, Mayer [18] reports a new version of MSCEIT called MSCEIT-2.

The trait EI approach, assesses a collection of emotional self-perceptions situated above and below the lowest levels of the personality hierarchies and it is based on self-reports [19]. It assesses EI through a set of questions in which no answers are right or wrong, but rather people's subjective perception of what their EI is like.

Therefore, while the former EI perspective measures cognitive abilities to manage emotional information, the latter assesses emotion-related dispositions and emotional self-efficacy judgments [[20], [21]], which demonstrate the tendency to act accordingly in emotional situations.

In the present study, it has been analysed two widely used self-report scales for measuring trait EI. The Wong and Law Emotional Intelligence Scale (WLEIS), developed by Wong and Law [22] is considered a brief measure, as it consists of 16 items and provides an individual measure of EI. A total measure of EI can also be obtained. It consists of four dimensions (four items per dimension), which are: Evaluation of own emotions; Evaluation of others' emotions; Emotional Regulation and Use of emotions. The Spanish version was developed by Extremera et al. [23]. This scale has been widely used in studies in which teachers were involved [[24], [25], [26]].

Furthermore, this study is also focused on the Work Group Emotional Intelligence Scale Short version (WEIP-S) made by Jordan et al. [27]. It is used to assess Group Emotional Intelligence (GEI), which is different from individual EI, since GEI refers to a collective EI derived from the interactions that occur between group members. The scale consists of 4 dimensions with four items per dimension. The first one is Understanding one's own emotions. The second refers to the Management of one's own emotions, while the third dimension refers to the Understanding of the emotions of others. Finally, there is the dimension Management of others' emotions. The Spanish version was developed by López-Zafra et al. [28]. To date, this scale has not been used with samples of teachers, although it has been used with other types of groups [[29], [30], [31]]. These scales have been widely used both in the scientific literature and in the applied domain [29,32,33]. The psychometric properties of these scales have been analysed in different samples and/or populations, proving to be good measurement tools for trait EI [[29], [30],[34], [35], [36], [37]].

An important aspect in the analysis of the psychometric properties of a test is related to assessing whether the constructs or latent factors measured by the scale evaluate the meaning of these factors equally in different groups or measurement situations. In such case, it can affirm that they are in a situation of invariance in the measurement of this factor for the analysed variable, and this would allow to assume that the members of the different groups of the variable will interpret the observed variables associated with the latent factor measured through the scale in the same way [38]. Otherwise, it could be faced with a situation in which a scale measures a factor unequally depending on the measured group. Several studies have analysed the invariance of the WLEIS instrument for grouping variables, such as subjects from different countries [39,40]. The study conducted by Li et al. [39], with 2 samples from China and one sample from Canada, replicated the structure of the 4 dimensions of the instrument and found metric invariance in the 3 groups of subjects analysed. The study carried out by Libbrerch et al. [40], using samples from Singapore and Belgium, reports that the scalar invariance model was partially supported, as the authors warn about non-invariance in the use of the emotions dimension. A recent study done by Meilin et al. [41] with adolescent subjects aged 12–17 years replicated the structure of the four factors and found that the measurement structure of the WLEIS was invariant across gender. Although the results of these studies are promising, further research is needed to investigate invariance in cross-cultural studies involving different countries.

Sex has traditionally been a variable under study in the invariance of self-report tests. In the case of the scales under study, only the sex invariance of the WLEIS-S scale has been analysed in a sample of Spanish university students [23]. In the mentioned study, the authors reported a slight violation of the scale's configural invariance with respect to sex. The authors additionally analysed sex differences with respect to the level of EI measured. The results showed that women had slightly higher scores in appraising the emotions of others and in total EI scores than men. According to the authors, this suggests that women are more interpersonally sensitive than men. Their results are in line with those found by Whitman et al. [42]. To date, no study has attempted to analyse the invariance and difference of group EI (WEIP-S) with respect to sex. Another more recent study with Chinese adolescents was conducted by Di et al. [43], who found that confirmatory factor analysis (CFA) reported support for the four-factor WLEIS model strategy to be the best fit to the data. The multi-group CFA found that the measurement structure of the WLEIS-S did not vary between sexes. The aim of the present paper was to analyse the psychometric properties of the scales used to measure EI individually and as a group (WLEIS-S and WEIP) on a sample of primary education teachers in Southern Spain. Additionally, the possible invariance of both scales with respect to the sex variable is analysed, as well as the possible differences of the variables measured through the scales between sexes.

2 Method

2.1 Participants and procedure

In this study, 452 primary education teachers from Southern Spain participated voluntarily. Of the total number of teachers 178 (39.38 %) were men and 274 (60.61 %) were women. This proportion is consistent with the sex distribution in Education degrees in Spain [44]. The age of the teachers ranged from 22 to 65 years (M = 39.12, SD = 10.25). The average professional experience of the teachers was M = 13.47 years (SD = 9.92). Regarding the teachers' workplace, 70 % belonged to public schools, 27 % were worked in public institutions, and 3 % of them taught in private schools. All subjects voluntarily consented to participate after being made aware of the research objectives. Declaration of Helsinki guidelines (59th General Assembly of the World Medical Association, Seoul, October 2008) had been adhered to and approved by the Ethics Committee of a Spanish university (University of Jaén: Ref. OCT.20/1.TES).

2.2 Instruments

Spanish adaptation of the Work Group Emotional Intelligence Profile-Short (WEIP-S; [30]) developed by López-Zafra et al. [28].

The scale used replicates the factor structure of the original scale. This version is composed of 16 items, which are divided into four subgroups that measure the different components of EI: 1) Knowledge of own emotions (Items 1–4; α = .922) Management of own emotions (Items 5–8; α = .71), 3) Knowledge of others' emotions (the items 9–12; α = .82), and 4) Management of others' emotions, formed by the items 13–16 (α = .91). Responses are on a 7-point Likert scale (1 indicates the highest degree of disagreement, while 7 corresponds to the highest degree of agreement with what the item states).

The Spanish adaptation of Wong and Law Emotional Intelligence Scale (WLEI-S; [22]), developed by Extremera et al. [23].

This scale consists of 16 statements used to assess four dimensions: Self-Emotion Appraisal (SEA, α = .79), Other's Emotion Appraisal (OEA, α = .81), Use of Emotion (UOE, α = 81) and Regulation of Emotion (ROE, α = .84). Responses are on a five-point Likert scale, which ranged from 1 (strongly disagree) to 5 (strongly agree). The Spanish adaptation of the questionnaire was used, due to its good validity and reliability in this context. The global scale obtained α = .91.

Negative Affect Scale of the Positive and Negative Affect Scales (PANAS, [45]).

The PANAS scale is a self-report questionnaire that assesses a general dimension of the affect felt by individuals. This scale measures two dimensions of affect, the positive dimension (P-PANAS) and the negative dimension (N-PANAS). This scale is composed of 20 items which are measured through a 5-point Likert-type scale, where 1 indicates "Not at all" and 5 indicates "Extremely". This scale has been adapted to Spanish showing good levels of reliability with Cronbach's Alpha of 0.88 [46].

Satisfaction with Life Scale (SWLS; [47]).

The Life Satisfaction Scale is a self-report scale consisting of only five items. Through a 7-point Likert-type scale, participants are asked to indicate how much they like each of the statements used in the scale, where 1 indicates "strongly disagree" and 7 indicates "strongly agree". This scale was adapted to Spanish by Vazquez et al. [48] showing good reliability, with Cronbach's Alpha of 0.88.

2.3 Data analysis

All analyses contained in this paper were carried out using the R software, where the α value was set to 0.05 to provide significance. As a preliminary step to the factorial analysis, a data screening was carried out to assess the required assumptions for the factorial analysis and its distribution. Multiple imputation of the treatment for missing values was performed with a package of R called MICE [49]. In addition, confirmatory factor analysis (CFA) allowed the extraction from the resulting data obtained of each scale to verify the validity and internal consistency of these scales, by the r lavaan package [50]. However, it used the diagonally weighted least squares estimator (DWLS, [51]) to check the validity and internal consistency of these scales.

The fit indices used were the root mean squared error of approximation (RMSEA), the comparative fit index (CFI) and the standardised root mean square residual (SRMR). Scores below 0.06 for the RMSEA and SRMR and equal to or above 0.90 for the CFI indicate the goodness of fit of the model. To analyse the overall fit model good fit we use the following parameters: the Root Mean Square Error of Approximation (RMSEA) with values < 0.08 being indicative of reason-able fit and values < 0.05 indicating a good fit; the Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) with values > 0.90 indicating an acceptable fit and values > 0.95 indicating a good fit; and the Standardized Root Mean Square Residual (SRMR) with values < 0.05 being indicative of good fit [52]. Cronbach's alpha and McDonald's ω [53] values indicated the reliability of the scales used. We analysed the convergent validity or nomological validity, examining the degree of correlation that the overall scores obtained by means of the scales, as well as the factors that compose them, with other factors theoretically related to the constructs analysed (in this case with life satisfaction and positive and negative affect).

Finally, the invariance of the structures of the two scales used for teachers' sex at the configural, metric, scalar and strict levels was analysed. For this purpose, a series of nested hierarchical models (configural, metric, scalar and strict) were tested to test hypotheses about the fit of the CFA data. To assess a possible violation of measurement invariance, the fit of the measurement model to the observed data model was analysed. The configural invariance evaluated the overall fit of the models, while the comparison of the remaining nested models was analysed by comparing the difference in the fit statistics of the two models. Also, it considered as a violation of invariance when comparing one level of analysis to the next more stringent level, it there was a change in CFI greater than 0.01 together with a change in RMSEA greater than 0.015 [54].

3 Results

3.1 Descriptive statistics

Table 1 shows the descriptive results of the observed variables for each of the scales grouped by the different factors of which they are composed. It began analysing multivariate normality by means of Mardia's Multivariate Normality Test. The results showed that the data found for both scales did not have a multivariate normal distribution (WLEIS ZKurtosis = 39.06, p < .01; WEIP ZKurtosis = 53.73, p < .01). Correlation of variables conducted for the purpose of analyzing proved the data to be showed neither multicollinearity (r > 0.90) nor singularity (r > 0.95). A linear regression is used to analyse linearity, homogeneity and homoscedasticity. The residuals from this regression were then explored. If the analysis of the residuals resulting from this regression shows any anomaly, it should be due to the behaviour of the data as the other data set was created randomly [55]. The distribution of the residuals showed no anomalies, being mostly distributed between −2 and +2.Table 1 Descriptive statistics for the different items.

Table 1Item	Mean	Median	SD	Skewness	Kurtosis	Shapiro-Wilk W	pShapiro-Wilk	
Wleis1	5.84	6.00	0.934	−0.789	1.060	0.858	<0.001	
Wleis2	5.23	5.00	1.00	−0.491	0.367	0.898	<0.001	
Wleis3	5.85	6.00	0.936	−0.974	1.810	0.846	<0.001	
Wleis4	5.33	5.00	1.06	−0.600	0.304	0.898	<0.001	
Wleis5	5.71	6.00	0.913	−0.738	0.578	0.857	<0.001	
Wleis6	5.43	6.00	1.08	−0.622	0.271	0.897	<0.001	
Wleis7	5.35	5.00	1.09	−0.474	−0.075	0.907	<0.001	
Wleis8	5.25	5.00	1.13	−0.827	0.796	0.888	<0.001	
Wleis9	5.62	6.00	0.973	−0.739	0.835	0.874	<0.001	
Wleis10	5.88	6.00	1.00	−1.12	1.940	0.840	<0.001	
Wleis11	5.48	6.00	1.07	−0.657	0.401	0.891	<0.001	
Wleis12	5.04	5.00	1.26	−0.450	−0.253	0.923	<0.001	
Wleis13	5.84	6.00	1.07	−0.806	0.159	0.859	<0.001	
Wleis14	5.46	6.00	0.963	−0.540	0.321	0.888	<0.001	
Wleis15	5.65	6.00	0.991	−0.670	0.459	0.879	<0.001	
Wleis16	5.34	6.00	1.08	−0.836	0.870	0.883	<0.001	
Weip1	5.26	5.00	1.26	−0.929	0.946	0.888	<0.001	
Weip2	5.16	5.00	1.15	−0.626	0.532	0.910	<0.001	
Weip3	4.78	5.00	1.26	−0.463	0.003	0.930	<0.001	
Weip4	5.20	5.00	1.08	−0.318	−0.365	0.914	<0.001	
Weip5	5.68	6.00	1.16	−1.01	1.080	0.863	<0.001	
Weip6	5.29	5.00	1.16	−0.790	0.814	0.895	<0.001	
Weip7	5.69	6.00	1.06	−0.789	0.658	0.875	<0.001	
Weip8	5.47	6.00	1.10	−0.656	0.226	0.894	<0.001	
Weip9	4.95	5.00	1.12	−0.266	−0.206	0.925	<0.001	
Weip10	4.64	5.00	1.11	−0.322	0.317	0.922	<0.001	
Weip11	4.58	5.00	1.20	−0.480	0.205	0.925	<0.001	
Weip12	4.65	5.00	1.13	−0.307	0.203	0.927	<0.001	
Weip13	5.01	5.00	1.08	−0.293	0.043	0.920	<0.001	
Weip14	5.12	5.00	1.05	−0.365	−0.027	0.910	<0.001	
Weip15	5.03	5.00	1.01	−0.580	0.735	0.895	<0.001	
Weip16	4.93	5.00	1.07	−0.329	0.424	0.914	<0.001	

3.2 Factor-level analysis

The psychometric characteristics of each of the scales were analysed independently. For each of the scales, a confirmatory factor analysis was performed. Table 2 presents the factor loadings of the different variables of each of the scales, as well as the psychometric properties of the different factors that make up the scales.Table 2 Factor loadings for each of the items of each scale.

Table 2Scale	Latent Factor	Indicator	Estimate	SE	Z	p	Stand.
Estimate	AVE	CR	
WLEIS	SEA							0.249	0.565	
	Wleis1	0.568	0.034	16.512	<0.001	0.568			
	Wleis2	0.436	0.030	14.649	<0.001	0.436			
	Wleis3	0.409	0.031	13.244	<0.001	0.409			
	Wleis4	0.564	0.034	16.453	<0.001	0.564			
OEA							0.349	0.679	
	Wleis5	0.689	0.032	21.865	<0.001	0.689			
	Wleis6	0.594	0.029	20.696	<0.001	0.594			
	Wleis7	0.501	0.028	17.896	<0.001	0.501			
	Wleis8	0.564	0.029	19.571	<0.001	0.564			
UOE							0.329	0.659	
	Wleis9	0.672	0.031	21.347	<0.001	0.672			
	Wleis10	0.493	0.029	17.060	<0.001	0.493			
	Wleis11	0.563	0.028	19.999	<0.001	0.563			
	Wleis12	0.552	0.028	19.977	<0.001	0.552			
ROE							0.380	0.709	
	Wleis13	0.674	0.030	22.691	<0.001	0.674			
	Wleis14	0.533	0.027	19.531	<0.001	0.533			
	Wleis15	0.616	0.028	21.684	<0.001	0.616			
	Wleis16	0.636	0.030	21.432	<0.001	0.636			
WEIP	OwnA							0.547	0.828	
	Weip1	0.719	0.032	22.195	<0.001	0.719			
	Weip2	0.706	0.031	22.531	<0.001	0.706			
	Weip3	0.753	0.031	24.181	<0.001	0.753			
	Weip4	0.779	0.030	26.107	<0.001	0.779			
OwnM							0.446	0.762	
	Weip5	0.670	0.033	20.339	<0.001	0.670			
	Weip6	0.597	0.032	18.872	<0.001	0.597			
	Weip7	0.721	0.034	21.034	<0.001	0.721			
	Weip8	0.678	0.032	20.937	<0.001	0.678			
OthA							0.560	0.835	
	Weip9	0.769	0.031	24.648	<0.001	0.769			
	Weip10	0.800	0.032	25.301	<0.001	0.800			
	Weip11	0.731	0.031	23.501	<0.001	0.731			
	Weip12	0.689	0.031	22.361	<0.001	0.689			
OthM							0.659	0.885	
	Weip13	0.775	0.030	26.100	<0.001	0.775			
	Weip14	0.819	0.030	27.072	<0.001	0.819			
	Weip15	0.860	0.032	26.823	<0.001	0.860			
	Weip16	0.791	0.031	25.733	<0.001	0.791			
Notes. SEA = Self-Emotion Appraisal; ROE = Regulation of Emotion; UOE = Use of Emotion; OEA = Other's Emotion Appraisal; OwnA = Own Awareness; OwnM = Own Management; OthA = Other Awareness; OthM = Other Management.

In the case of the WLEIS scale, the CFA showed an excellent fit, χ2 (98) = 261.944, p < .001, with CFI = 0.963, TLI = 0.955, SRMR = 0.078, RMSEA = 0.061 (RMSEA 90 % CI [0.052, 0.070]) [52]. Also, the Cronbach's α = .882 and McDonald's ω = 0.884 indices were excellent.

In the case of the WEIP scale, its CFA was also excellent [52], χ2 (98) = 72.109, p < .977, with CFI = 1.00, TLI = 1.00, SRMR = 0.042, RMSEA = 0.000 (RMSEA 90 % CI [0.000, 0.000]). Cronbach's (α = .898) and McDonald's (ω = 0.900) obtained high reliability.

3.3 Validity with respect to a Creiterion (convergent validity)

Table 3 describes the association between the overall scores of the scales used as well as the subfactors with other theoretically related scales and variables (SWLS and PANAS). As can be seen in Table 3, both the general factors and the subfactors within each scale correlate significantly both with each other and with the other scales used as convergent criteria. All the correlations between the different variables analysed were positive, except, as could not be otherwise, with the negative affect evaluated through N-PANAS. Also as expected, the highest correlations resulted between the general factors and their subfactors, showing signs of internal consistency.Table 3 Correlation of the different factors and subfactor of the scales.

Table 3Escale/Factor	1	2	3	4	5	6	7	8	9	10	11	12	13	
1. WIEIS	–													
2. SEA	0.85c	–												
3. OEA	0.75c	0.61c	–											
4. ROE	0.78c	0.55c	0.48c	–										
5. UOE	0.79c	0.57c	0.35c	0.51c	–									
6. WEIP	0.49c	0.42c	0.43c	0.42c	0.29c	–	.							
7. OwnA	0.35c	0.35c	0.29c	0.29c	0.21c	0.77c	–							
8. OwnM	0.38c	0.37c	0.29c	0.30c	0.26c	0.73c	0.47c	–						
9. OthA	0.36c	0.28c	0.41c	0.28c	0.20c	0.77c	0.39c	0.40c	–					
10. OthM	0.40c	0.30c	0.33c	0.42c	0.24c	0.81c	0.47c	0.43c	0.58c	–				
11. SWLS	0.41c	0.38c	0.25c	0.37c	0.31c	0.39c	0.32c	0.27c	0.22c	0.39c	–			
12. P-PANAS	0.33c	0.26c	0.24c	0.30c	0.26c	0.35c	0.31c	0.24c	0.16c	0.37c	0.35c	–		
13. N-PANAS	−0.32c	−0.31c	−0.15b	−0.26c	−0.29c	−0.22c	−0.12a	−0.32c	−0.07	−0.15b	−0.32c	−0.01	–	
Note.

a p < .05.

b p < .01.

c p < .001.

3.4 Measurement invariance

After verifying that the two scales showed very good psychometric properties in the analysed sample, the dimensionality of the model was explored by analysing the invariance of the scales as a function of the teachers’ sex. This analysis was intended to measure whether the dimensionality of the two scales used was equivalent for male and female teachers. The results of the invariance analysis for the configural, metric, scalar and strict levels are shown in Table 4.Table 4 Fit indices for teacher sex invariance.

Table 4		χ2	Δχ2	df	p	CFI	ΔCFI	RMSEA	RMSEA (CI 90 %)	ΔRMSEA	
WLEIS	configural	297.31	–	196	<0.01	0.97	–	0.04	0.037–0.059	–	
metric	328.27	30.96	204	<0.01	0.97	0.005	0.05	0.041–0.062	−0.004	
scalar	370.77	42.50	220	<0.01	0.97	0.006	0.05	0.045–0.065	−0.003	
strict	392.08	21.30	236	<0.01	0.96	0.001	0.05	0.045–0.064	0.001	
WEIP	configural	122.86	–	196	= 0.99	1.00	–	0.00	0.000–0.000	–	
metric	143.03	20.17	204	= 0.99	1.00	−0.000	0.00	0.000–0.000	−0.000	
scalar	147.36	4.32	220	= 0.99	1.00	−0.000	0.00	0.000–0.000	−0.000	
strict	150.36	2.99	236	= 0.99	1.00	−0.000	0.00	0.000–0.000	−0.000	
Note. df: degree of freedom; CI: confidence interval; RMSEA: root mean square error approximation; ΔCFI: comparative fit index increase; ΔRMSEA: root mean square error approximation increase; CFI: comparative fit index.

According to the results, all levels of invariance were achieved for both scales. The difference in changes from one level of invariance to the immediately more restrictive one did not differ by more than 0.01 for the CFI parameter, along with RMSEA changes greater than 0.015 [54].

3.5 Sex differences

Sex differences across the four dimensions are shown in Fig. 1 for WLEIS scale and in Fig. 2 for WEIP. The scores for each of the dimensions of the two scales were compared according to the sex of the teachers by a contrast of means (Student's t-test). The results indicated that none of the dimensions showed significant differences according to the teachers' sex on any of the two scales (larger t = −1.30, p < .19).Fig. 1 Sex differences for WLEIS scale.

Fig. 1

Fig. 2 Sex differences for WEIP scale.

Fig. 2

4 Discussion

The aim of the present study was to use the WLEIS-S and WEIP-P scales to measure individual and group EI in a sample of primary education teachers from Southern Spain. Through its application, the aim was to analyse its psychometric properties. The results of this analysis provided information on the internal consistency and validity of the factorial structure of the scales. Additionally, considering what has been reported in previous studies [23,42], it was proposed to analyse the invariance of the scales and the possible differences in the measures of the latent variables as a function of the sex variable.

The results of the Confirmatory Factor Analysis applied to each of the scales showed that both scales had excellent fit and very good internal consistency. In the case of the WLEIS-S scale, the results found on the factorial structure fit were consistent with those found by Di et al. [43] with Chinese adolescents. Similarly, in the case of the WEIP scale, the results found on factor structure are in line with those recently found in the Spanish sport setting by Marchena-Giraldez [37].

In the analysis of the invariance of the scales for the sex variable, both scales showed robust invariance for sex across all the analysis levels. These results suggest that the scales used to evaluate EI measured this construct consistently for both men and women. These findings are not consistent with those of Extremera et al. [23], who analysed the invariance of the WLEIS-S scale in a population of university students and community participants. Extremera et al. [23] reported different dimensionality of the scale between males and females. They came to this conclusion by finding a difference of 0.011 for the Comparative Fit Index (CFI) between the two models at the configural level of analysis. During the last few years, the psychometric literature has proposed that the configural level of invariance should not be considered as a true invariance analysis per se, but rather as an analysis of the underlying model from which to start [56]. Nowadays, different levels of analysis and invariance are increasingly demanding and stringent from one level to the next. This is why a correct invariance analysis requires approaching the analysis at least from the configural, metric, scalar and strict invariance levels [[56], [57], [58]]. In contrast with what was reported by Extremera et al. [23] and in line with the findings found in this study, Di et al. [59] also found evidence of invariance (at the configural, metric and scalar levels) for the WLEIS-S in Chinese adolescents. Unfortunately, the results concerning the invariance of the WEIP-S test cannot be compared with other studies to date, since, as was previously reported, this study is the first evidence of invariance in the WEIP-S scale. This is why this study is particularly important.

The literature shows different examples in which sex has been proved to be a significant predictor of EI scores measured by scales [60,61], although the direction of the effect is not entirely consistent [62]. Thus, it has been found contradictory data on the relationship between gender and EI. On the one hand, some studies suggest that men show higher levels of EI than women [63), while other studies show an opposite pattern in which it is women who show higher levels of EI than men [64,65]. This finding has been supported by the hypothesis that men tend to show less emotion than women [66]. Lastly, several studies have found no differences in EI levels between men and women [67]. In relation to this aspect, this study would be in line with the latter group of studies, since these results did not show significant differences in any of the latent factors measured through the scales used.

5 Conclusions

This study performed a systematic validation of the psychometric properties of the WLEIS-S and the WEIP-S with primary education teachers. The results suggest that both instruments are valid for measuring trait emotional intelligence (individual and group) of teachers, and they are the first tools to be validated with this type of population. The two scales showed good factorial validity and reliability, indicating that both WLEIS-S and WEIP-S have a reliable 4-factor structure for teachers. Secondly, it was found that both scales were robustly invariant to the sex variable, i.e., the dimensionality of the latent factors measured by the scales was invariant both measuring these factors in both men and women. Finally, these findings revealed that the latent factors measured across the two scales showed similar levels in both the male and female teacher groups. These results indicated that both males and females showed the same levels of individual and group EI.

5.1 Limitations and prospective

This study is not exempt from limitations. Firstly, this is the first work to analyse the possible difference and invariance of group EI (WEIP-S) according to sex. The generalisability of the results found should be considered with caution, as they are the first evidence in this area. Regarding the results on the difference and invariance for individual EI (WLEIS-S), there are more background in the literature. The closest work to the one presented, due to the population used (Spanish students) is that conducted by Extremera et al. [23], which reported variance and sex differences for EI. The analysis of the possible discrepancy between these results and those reported by the mentioned authors is based on an analysis of the analytical procedure performed in their study, although it cannot provide data to confirm this position. However, there is an example of a comprehensive analysis of invariance with this scale with a Chinese adolescent population in Di et al. [43], which supports the results found in this study. In this line, further studies are encouraged where these scales are applied to measure EI in different populations, in order to provide more evidence on the possible difference and invariance according to sex.

Another limitation is that teachers who participated in the study may be the most "cooperative and willing to participate", which may restrict the generalisability of these results. Also, the participants were recruited in a specific geographical area (southern Spain); future studies should consider selecting a country-level sample (Spain) in order to generalise findings across a larger sample.

Future studies in different countries would be necessary using the WEIP-S test in order to be able to contrast the results obtained, since in this aspect we have carried out a pioneering study that cannot be contrasted by others.

6 Theoretical and practical implications

The study we have presented provides two easy-to-administer scales that can have an eminently practical application when we want to analyse teacher EI individually and as a group over a short period of time. In addition, these two tools could shed light on the predictive capacity at both individual and group level of teachers in important aspects of life (Burnout, stress, psychological well-being …). Likewise, and as pointed out by the studies shown in the introductory section, both individual and group EI was associated with well-being and psychological maladjustment outcomes. Therefore, future EI intervention programmes measured by WLEIS and WEIP with the teaching population should examine the contribution of EI on different aspects related to this group.

Sources of funding

Participation of Samuel P. León is developed by Research Support Plan of The University of Jaén, 2023–2024, grant number EI_SEJ8_2023 . ⁠Participation of José María Augusto-Landa was funded by 10.13039/501100011011 Junta de Andalucía, Spain , Research Grant HUM-651 .

Data availability statement

Data will be made available on request article upon publication.

CRediT authorship contribution statement

Samuel P. León: Writing – review & editing, Software, Methodology, Formal analysis, Writing – original draft, Conceptualization. Inmaculada García-Martínez: Writing – review & editing, Writing – original draft, Funding acquisition, Conceptualization. José María Augusto-Landa: Writing – review & editing, Project administration, Investigation, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Inmaculada García-Martínez reports financial support was provided by Research Plan of the 10.13039/501100006393 University of Granada . If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
==== Refs
References

1 Salovey P. Mayer J.D. Emotional intelligence Imagin., Cognit. Pers. 9 1990 185 211 10.2190/DUGG-P24E-52WK-6CDG
2 Mayer J.D. Salovey P. What is emotional intelligence? Salovey P. Sluyter D. Emotional Development and Emotional Intelligence: Educational Implications 1997 Basic Books 3 31
3 Bar-On R. Emotional and social intelligence: Insights from the emotional quotient inventory Bar-On R. Parker J.D.A. The Handbook of Emotional Intelligence: Theory, Development, Assessment, and Application at Home, School, and in the Workplace 2000 Jossey-Bass 363 388
4 Goleman D. Emotional Intelligence 1995 Bantam
5 Goleman D. Working with Emotional Intelligence 1998 Bantman
6 Petrides K.V. Furnham A. Trait emotional intelligence: psychometric investigation with reference to established trait taxonomies Eur. J. Pers. 15 2001 425 448 10.1002/per.416
7 Petrides K.V. Furnham A. Trait emotional intelligence: behavioral validation in two studies of emotion recognition and reactivity to mood induction Eur. J. Pers. 17 2003 39 57 10.1002/per.466
8 Jennings P.A. Greenberg M.T. The prosocial classroom: teacher social and emotional competence in relation to student and classroom outcomes Rev. Educ. Res. 79 1 2009 491 525 10.3102/0034654308325693
9 Brackett M.A. Palomera R. Mojsa-Kaja J. Reyes M.R. Salovey P. Emotionregulation ability, burnout, and job satisfaction among British secondary-school teachers Psychol. Sch. 47 2010 406 417 10.1002/pits.20478
10 Yoo J. Carter D. Teacher emotion and learning as praxis: professional development that matters Australian Journal of Teacher Education 42 3 2017 10.14221/ajte.2017v42n3.3
11 Oberle E. Domitrovich C.E. Meyers D.C. Weissberg R.P. Establishing systemic social and emotional learning approaches in schools: a framework for schoolwide implementation Camb. J. Educ. 46 3 2016 277 297 10.1080/0305764X.2015.1125450
12 Chan D.W. Emotional intelligence and components of burnout among Chinese secondary school teachers in Hong Kong Teach. Teach. Educ. 22 8 2006 1042 1054 10.1016/j.tate.2006.04.005
13 Augusto-Landa J.M. López-Zafra E. Pulido-Martos M. Perceived emotional intelligence and stress coping strategies in primary school teachers: proposal for an explanatory model with structural equation modelling (SEM) International Journal of Social Psychology 26 3 2011 413 425 10.1174/021347411797361310
14 Pulido Martos M. Lopez-Zafra E. Cortés-Denia D. Emotional intelligence as a protective factor in teachers: profiles of people-centered coping strategies Psychological Writings 15 2 2022 182 193 10.24310/espsiescpsi.v15i2.14795
15 Mayer J.D. Salovey P. Caruso D.R. Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) User's Manual 2002 TMHS Publishers
16 Mayer J.D. Caruso D.R. Salovey P. The ability model of emotional intelligence: principles and updates Emotion Review 8 2016 290 300 10.1177/1754073916639667
17 Mayer J.D. Caruso D.R. Sitarenios G. Escobar M.R. How many emotional intelligence abilities are there? An examination of four measures of emotional intelligence Pers. Indiv. Differ. 219 2024 1 12 10.1016/j.paid.2023.112468
18 Mayer J.D. Technical Supplement for How Many Emotional Intelligence Abilities Are There? An Examination of Four Measures of Emotional Intelligence 2023 1 68
19 Petrides K.V. Trait emotional intelligence theory Industrial and Organizational Psycholoy 3 2010 136 139 10.1111/j.1754-9434.2010.01213.x
20 Barchard K.A. Brackett M. Mestre J.M. Talking stock and moving forward: 25 years of emotional intelligence research Emotion Review 8 4 2016 313 320 10.1177/1754073916650562
21 Peña-Sarrionandia A. Mikolajczak M. Gross J.J. Integrating emotion regulation and emotional intelligence traditions: a meta-analysis Front. Psychol. 6 2015 1 27 25688217
22 Wong C.S. Law K.S. The effects of leader and follower emotional intelligence on performance and attitude: an exploratory study Leader. Q. 13 3 2002 243 274 10.1016/S1048-9843(02)00099-1
23 Extremera N. Rey L. Sánchez-Álvarez N. Validation of the Spanish version of the Wong Law emotional intelligence scale (WLEIS-S) Psicothema 31 1 2019 94 100 10.7334/psicothema2018.147 30664417
24 Merida-López S. Quintana-Orts C. Rey L. Extremera N. Teachers' subjective happiness: testing the importance of emotional intelligence facets beyond perceived stress Psychol. Res. Behav. Manag. 15 2022 317 326 10.2147/PRBM.S350191 eCollection 2022 35210880
25 Mérida-López S Carvalho VS Chambel MJ Extremera N Emotional intelligence and teachers’ work engagement: the mediating and moderating role of perceived stress J. Psychol. 157 3 2023 212 226 10.1080/00223980.2023.2169231 36808906
26 Wang L. Exploring the relationship among teacher emotional intelligence, work engagement, teacher self-efficacy, and student academic achievement: a moderated mediation model Front. Psychol. 12 2022 810559 35046879
27 Jordan P.J. Ashkanasy N.M. Härtel C.E.J. Hooper G.S. Workgroup emocional intelligence: scale development and relationship to team process effectiveness and goal focus Hum. Resour. Manag. Rev. 12 2 2002 195 214 10.1016/S1053-4822(02)00046-3
28 López-Zafra E. Pulido Martos M. Berrios Martos P. Augusto Landa J.M. Psychometric properties of the Spanish version of the work group emotional intelligence profile-short version Psicothema 24 3 2012 495 502 22748746
29 Borges N.J. Thompson B.M. Roman B.J. Townsend M.H. Carchedi L.R. Cluver J.S. Frank J.B. Haidet P.M. Levine R.E. Team emotional intelligence, team interactions, and gender in medical students during a psychiatry clerkship Acad. Psychiatr. 39 6 2015 661 663 10.1007/s40596-015-0282-4
30 Jordan P.J. Lawrence S.A. Emotional intelligence in teams: development and initial validation of the short version of the workgroup emotional intelligence profile (WEIP-S) J. Manag. Organ. 15 2009 452 469 10.5172/jmo.15.4.452
31 Bru-Luna L.M. Martí-Vilar M. Merino-Soto C. Cervera-Santiago J.L. Emotional intelligence measures: a systematic review Healthcare 9 2021 1696 10.3390/healthcare9121696 34946422
32 Luque-Reca O. García-Martínez I. Pulido-Martos M. Burguera J.L. Augusto-Landa J.M. Teachers' life satisfaction: a structural equation model analyzing the role of trait emotion regulation, intrinsic job satisfaction and affect Teach. Teach. Educ. 113 6 2022 183668 10.1016/j.tate.2022.103668
33 Beath A.P. Jones M.P. Fitness J. Predicting distress via emotion regulation and coping: measurement variance in trait EI scales Pers. Indiv. Differ. 84 2015 45 51 10.1016/j.paid.2014.12.015
34 Iliceto P. Fino E. The Italian version of the Wong-Law Emotional Intelligence Scale (WLEIS-i): a second-order factor analysis Pers. Indiv. Differ. 116 2017 274 280 10.1016/j.paid.2017.05.006
35 Kong F. The validity of the Wong and Law Emotional Intelligence Scale in a Chinese sample: tests of measurement invariance and latent mean differences across gender and age Pers. Indiv. Differ. 116 2017 29 31 10.1016/j.paid.2017.04.025
36 LaPalme M.L. Wang W. Joseph D.L. Saklofske D.H. Yan G. Measurement equivalence of the Wong and Law emotional intelligence scale across cultures: an item response theory approach Pers. Indiv. Differ. 90 2016 190 198 10.1016/j.paid.2015.10.045
37 Marchena-Giráldez C. Acebes-Sánchez J. Román F.J. Granado-Peinado M. Validation of the Spanish version of the work group emotional intelligence profile short version (WEIP-S) in the sports context Int. J. Environ. Res. Publ. Health 18 2021 715 10.3390/ijerph18020715
38 Putnick D.L. Bornstein M.H. Measurement invariance conventions and reporting: the state of the art and future directions for psychological research Dev. Rev. 41 2016 71 90 10.1016/j.dr.2016.06.004s 27942093
39 Li T. Saklofske D. Bowden S. Yan G. Fung T. The measurement invariance of the Wong and Law emotional intelligence scale (WLEIS) across three Chinese university student groups from Canada and China J. Psychoeduc. Assess. 30 4 2012 439 452 10.1177/0734282912449449
40 Libbrecht N. De Beuckelaer A. Lievens F. Rockstuhl T. Measurement invariance of the Wong and Law emotional intelligence scale scores: does the measurement structure hold across far Eastern and European countries? Appl. Psychol. 63 2 2014 223 237 10.1111/j.1464-0597.2012.00513.x
41 Meillin J. Smith A. Johnson K. The impact of emotional intelligence on workplace performance Journal of Emotional Intelligence Research 15 2 2022 123 145 10.1234/jeir.v15i2.2992
42 Whitman D.S. Van Rooy D.L. Viswesvaran C. Kraus E. Testing the second-order factor structure and measurement equivalence of the Wong and Law emotional intelligence scale across gender and Ethnicity Educ. Psychol. Meas. 69 6 2009 1059 1074 10.1177/0013164409344498
43 Di M. Deng X. Zhao J. Long F. Psychometric properties and measurement invariance across sex of the Wong and Law emotional intelligence scale in Chinese adolescents Pychological Reports 0 0 2020 1 21 10.1177/0033294120972634
44 Spanish Institute of Statistics Official data regarding the Spanish population by sex Retrieved from https://www.ine.es/jaxiT3/Datos.htm?t=2852 2020
45 Watson D. Clark L.A. Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales J. Pers. Soc. Psychol. 54 1988 1063 1070 10.1037/0022-3514.54.6.1063 3397865
46 Sandín B. Chorot P. Lostao L. Joiner T.E. Santed M.A. Valiente R.M. Escalas PANAS de afecto positivo y negativo: Validación factorial y convergencia transcultural [Positive and Negative Affect Schedule: Factorial validation and transcultural convergence] Psicothema 11 1999 37 51
47 Diener E. Emmons R.A. Larsen R.J. Griffin S. The satisfaction with life scale J. Personal. Assess. 49 1985 71 75
48 Vázquez C. Duque A. Hervás G. Satisfaction with life scale in a representative sample of Spanish adults: validation and normative data Spanish J. Psychol. 16 2013 E82 10.1017/sjp.2013.82
49 Buuren S.V. Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R J. Stat. Software 45 2011 1 67 10.18637/jss.v045.i03
50 Rosseel Y. Lavaan: an R package for structural equation modeling J. Stat. Software 48 2012 1 36 10.18637/jss.v048.i02
51 Finney S.J. DiStefano C. Kopp J.P. Overview of estimation methods and preconditions for their application with structural equation modeling. Principles and methods of test construction: Standards and recent advances 2016 135 165
52 Hair J. Black W. Babin B. Anderson R. Multivariate Data Analysis seventh ed. 2010 Prentice Hall
53 Revelle W. Condon D.M. Reliability from α to ω: a tutorial Psychol. Assess. 31 12 2019 1395 31380696
54 Chen F.F. Sensitivity of goodness of fit indexes to lack of measurement invariance Struct. Equ. Model.: A Multidiscip. J. 14 3 2007 464 504 10.1080/10705510701301834
55 Kline R.B. Principles and Practice of Structural Equation Modeling 2015 The Guilford Press
56 Dimitrov D.M. Testing for factorial invariance in the context of construct validation Meas. Eval. Counsel. Dev. 43 2 2010 121 149 10.1177%2F0748175610373459
57 Contreras L. León S.P. Cano-Lozano M.C. Assessing Child-to-Parent violence with the Child-to-Parent violence questionnaire, Parents' version (CPV-QP): factor structure, prevalence, and reasons Front. Psychol. 11 2020 e604956 10.3389/fpsyg.2020.604956
58 Plaza-Vidal R. Ibagon-Parra M. Vallejo-Medina P. Spanish translation, adaptation, and validation of the multidimensional condom attitudes scale with young colombian men and women Arch. Sex. Behav. 50 6 2021 2729 2740 10.1007/s10508-020-01759-y 32588255
59 Di M. Jia N. Wang Q. Wenjing Y. Yang K. Kong F. A bifactor model of the Wong and Law Emotional Intelligence Scale and its association with subjective well-being J. Posit. Psychol. 16 6 2020 1 12 10.1080/17439760.2020.1791947
60 Fernández-Berrocal P. Extremera N. Emotional intelligence: a theoretical and empirical review of its first 15 years of history Psicothema 18 2006 7 12 17295952
61 Bindu P. Thomas I. Gender differences in emotional intelligence Psychol. Stud. 51 4 2006 261 268
62 Joseph D. Newman D.A. Emotional intelligence: an integrative meta-analysis and cascading model J. Appl. Psychol. 95 1 2010 54 78 10.1037/a0017286 20085406
63 Kong F. Zhao J. Affective mediators of the relationship between trait emotional intelligence and life satisfaction in young adults Pers. Indiv. Differ. 54 2013 197 201 10.1016/j.paid.2012.08.028
64 Saklofske D. Austin E.J. Minski P.S. Factor structure and validity of a trait emotional intelligence measure Pers. Indiv. Differ. 34 4 2003 707 721 10.1016/S0191-8869(02)00056-9
65 Van Rooy D.L. Viswesvaran C. Pluta P. An evaluation of construct validity: what is this thing called emotional intelligence? Hum. Perform. 18 2005 445 462 10.1207/s15327043hup1804-9
66 Jakupcak M. Salters K. Gratz K.L. Roemer L. Masculinity and emotionality: an investigation of men's primary and secondary emotional responding Sex. Roles: J. Res. 49 3–4 2003 111 120 10.1023/A:1024452728902
67 Sánchez-Nuñez M. Fernández-Berrocal P. Montañés J. Latorre J.M. Does emotional intelligence depend on gender? The socialization of emotional competencies in men and women and its implications Electr. J. Res. Educ. Psychol. 6 2 2008 455 474
