IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0225070.html

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

Author

Listed:
  • Yuki Nozaki
  • Alicia Puente-Martínez
  • Moïra Mikolajczak

Abstract

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.

Suggested Citation

  • Yuki Nozaki & Alicia Puente-Martínez & Moïra Mikolajczak, 2019. "Evaluating the higher-order structure of the Profile of Emotional Competence (PEC): Confirmatory factor analysis and Bayesian structural equation modeling," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-17, November.
    • Handle: RePEc:plo:pone00:0225070
    DOI: 10.1371/journal.pone.0225070
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225070
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0225070&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0225070?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. David Rindskopf, 1983. "Parameterizing inequality constraints on unique variances in linear structural models," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 73-83, March.
    2. Golino, Hudson F. & Demetriou, Andreas, 2017. "Estimating the dimensionality of intelligence like data using Exploratory Graph Analysis," Intelligence, Elsevier, vol. 62(C), pages 54-70.
    3. Hudson F Golino & Sacha Epskamp, 2017. "Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-26, June.
    4. Sophie Brasseur & Jacques Grégoire & Romain Bourdu & Moïra Mikolajczak, 2013. "The Profile of Emotional Competence (PEC): Development and Validation of a Self-Reported Measure that Fits Dimensions of Emotional Competence Theory," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-8, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Boris Forthmann & Mark A. Runco, 2020. "An Empirical Test of the Inter-Relationships between Various Bibliometric Creative Scholarship Indicators," Publications, MDPI, vol. 8(2), pages 1-16, June.
    2. Hudson Golino & Alexander P. Christensen & Robert Moulder & Seohyun Kim & Steven M. Boker, 2022. "Modeling Latent Topics in Social Media using Dynamic Exploratory Graph Analysis: The Case of the Right-wing and Left-wing Trolls in the 2016 US Elections," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 156-187, March.
    3. Wafa Mohammed Aldighrir, 2024. "Development and validation of the educational leadership scale for mental health providers: A network analysis approach," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    4. Chien-Fan Chen & Cherng G. Ding, 2026. "An improvement in the detection of common method biases," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 791-815, February.
    5. Javier Cejudo & Débora Rodrigo-Ruiz & Maria Luz López-Delgado & Lidia Losada, 2018. "Emotional Intelligence and Its Relationship with Levels of Social Anxiety and Stress in Adolescents," IJERPH, MDPI, vol. 15(6), pages 1-11, May.
    6. François Bogacz & Thierry Pun & Olga M. Klimecki, 2020. "Improved conflict resolution in romantic couples in mediation compared to negotiation," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 7(1), pages 1-14, December.
    7. Lukáš Copuš & Peter Madzík & Helena Šajgalíková & Karol Čarnogurský, 2023. "Is There a Possibility to Characterize an Organizational Culture by Its Selected Cultural Dimensions?," SAGE Open, , vol. 13(4), pages 21582440231, October.
    8. Andrey Nasledov & Sergey Miroshnikov & Liubov Tkacheva & Kirill Miroshnik & Meriam Uld Semeta, 2021. "Application of Psychometric Approach for ASD Evaluation in Russian 3–4-Year-Olds," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    9. Tsonaka, R. & Moustaki, I., 2007. "Parameter constraints in generalized linear latent variable models," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4164-4177, May.
    10. Kan, Kees-Jan & van der Maas, Han L.J. & Levine, Stephen Z., 2019. "Extending psychometric network analysis: Empirical evidence against g in favor of mutualism?," Intelligence, Elsevier, vol. 73(C), pages 52-62.
    11. Raveenajit Kaur A. P. & Kalvant Singh & Alberto Luis August, 2021. "Exploring the Factor Structure of the Constructs of Technological, Pedagogical, and Content Knowledge (TPACK): An Exploratory Factor Analysis Based on the Perceptions of TESOL Pre-Service Teachers at a British Private University in Malaysia," Research Journal of Education, Academic Research Publishing Group, vol. 7(2), pages 103-115, 06-2021.
    12. Sacha Epskamp, 2020. "Psychometric network models from time-series and panel data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 206-231, March.
    13. Lap Sum Chan & Gen Li & Eric B. Fauman & Xianyong Yin & Markku Laakso & Michael Boehnke & Peter X. K. Song, 2025. "DrFARM: identification of pleiotropic genetic variants in genome-wide association studies," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    14. Bing Li & Cody Ding & Huiying Shi & Fenghui Fan & Liya Guo, 2023. "Assessment of Psychological Zone of Optimal Performance among Professional Athletes: EGA and Item Response Theory Analysis," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    15. Anne Boomsma, 1985. "Nonconvergence, improper solutions, and starting values in lisrel maximum likelihood estimation," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 229-242, June.
    16. Virginia Fernández-Pérez & Ana Montes-Merino & Lázaro Rodríguez-Ariza & Patricia Esther Alonso Galicia, 2019. "Emotional competencies and cognitive antecedents in shaping student’s entrepreneurial intention: the moderating role of entrepreneurship education," International Entrepreneurship and Management Journal, Springer, vol. 15(1), pages 281-305, March.
    17. Stefano Vicentin & Umberto Granziol & Daniele Romano & Michele Scandola & Giorgia Cona, 2026. "The effect of age on the architecture of psychological and cognitive dimensions: a network perspective," European Journal of Ageing, Springer, vol. 23(1), pages 1-11, December.
    18. Annalina Sarra & Lara Fontanella & Maila Pentucci & Giovanna Cioci & Ida Esposito, 2025. "Proposing the use of psychometric network analysis to investigate the relationship between teachers and technology," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(5), pages 4703-4724, October.
    19. Imen Krifa & Llewellyn Ellardus van Zyl & Amel Braham & Selma Ben Nasr & Rebecca Shankland, 2022. "Mental Health during COVID-19 Pandemic: The Role of Optimism and Emotional Regulation," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    20. Nadja Bodner & Laura Bringmann & Francis Tuerlinckx & Peter Jonge & Eva Ceulemans, 2022. "ConNEcT: A Novel Network Approach for Investigating the Co-occurrence of Binary Psychopathological Symptoms Over Time," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 107-132, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0225070. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.