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


Autoři: Yuki Nozaki aff001;  Alicia Puente-Martínez aff002;  Moïra Mikolajczak aff003
Působiště autorů: Department of Human Science, Faculty of Letters, Konan University, Kobe, Japan aff001;  Department of Social Psychology and Methodology of Behavior Sciences, University of the Basque Country, Lejona, Spain aff002;  Department of Psychology, Université catholique de Louvain, Louvain-la-Neuve, Belgium aff003
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0225070

Souhrn

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.

Klíčová slova:

Behavior – Mental health and psychiatry – Emotions – Factor analysis – Research validity – Personality – Personality traits – Maximum likelihood estimation


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