Evaluating the higher-order structure of the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling

• Published in: PloS one Vol. 14; no. 11; p. e0225070
• Main Authors: Nozaki, Yuki, Puente-Martínez, Alicia, Mikolajczak, Moïra
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14.11.2019; Public Library of Science (PLoS)
• Subjects: Analysis; Bayes Theorem; Bayesian analysis; Biology and Life Sciences; Discriminant analysis; Domains; Emotional Intelligence; Emotions; Factor analysis; Factor Analysis, Statistical; Female; Humans; Identification; Male; Mathematical models; Medicine and Health Sciences; Middle Aged; Modelling; Models, Theoretical; Multivariate statistical analysis; Personality; Physical Sciences; Research and Analysis Methods; Social Sciences; Social skills; Structural equation modeling; Systematic review; Utilization
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0225070

Emotional competence (EC) reflects individual differences in the identification, comprehension, expression, regulation, and utilization of one's own and others' emotions. EC can be operationalized using the Profile of Emotional Competence (PEC). This scale measures each of the five core emotional competences (identification, comprehension, expression, regulation, and utilization), separately for one's own and others' emotions. However, the higher-order structure of the PEC has not yet been systematically examined. This study aimed to fill this gap using four different samples (French-speaking Belgian, Dutch-speaking Belgian, Spanish, and Japanese). Confirmatory factor analyses and Bayesian structural equation modeling revealed that a structure with two second-order factors (intrapersonal and interpersonal EC) and with residual correlations among the types of competence (identification, comprehension, expression, regulation, and utilization) fitted the data better than alternative models. The findings emphasize the importance of distinguishing between intrapersonal and interpersonal domains in EC, offer a better framework for differentiating among individuals with different EC profiles, and provide exciting perspectives for future research.