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The factor structure of executive function in childhood and adolescence

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  • Laureys, Felien
  • De Waelle, Silke
  • Barendse, Maria T.
  • Lenoir, Matthieu
  • Deconinck, Frederik J.A.

Abstract

Executive functioning (EF) plays a major role in many domains of human behaviour, including self-regulation, academic achievement, and even sports expertise. While a significant proportion of cross-sectional research has focused on the developmental pathways of EF, the existing literature is fractionated due to a wide range of methodologies applied to narrow age ranges, impeding comparison across a broad range of age groups. The current study used a cross-sectional design to investigate the factor structure of EF within late childhood and adolescence. A total of 2166 Flemish children and adolescents completed seven tasks of the Cambridge Brain Sciences test battery. Based on the existing literature, a Confirmatory Factor Analysis was performed, which indicated that a unitary factor model provides the best fit for the youngest age group (7–12 years). For the adolescents (12–18 years), the factor structure consists of four different components, including working memory, shifting, inhibition and planning. With regard to differences between early (12–15 years) and late (15–18 years) adolescents, working memory, inhibition and planning show higher scores for the late adolescents, while there was no difference on shifting. The current study is one of the first to administer the same seven EF tests in a considerably large sample of children and adolescents, and as such contributes to the understanding of the developmental trends in EF. Future studies, especially with longitudinal designs, are encouraged to further increase the knowledge concerning the factor structure of EF, and the development of the different EF components.

Suggested Citation

  • Laureys, Felien & De Waelle, Silke & Barendse, Maria T. & Lenoir, Matthieu & Deconinck, Frederik J.A., 2022. "The factor structure of executive function in childhood and adolescence," Intelligence, Elsevier, vol. 90(C).
  • Handle: RePEc:eee:intell:v:90:y:2022:i:c:s0160289621000842
    DOI: 10.1016/j.intell.2021.101600
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    References listed on IDEAS

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    1. Fen Xu & Yan Han & Mark A Sabbagh & Tengfei Wang & Xuezhu Ren & Chunhua Li, 2013. "Developmental Differences in the Structure of Executive Function in Middle Childhood and Adolescence," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    2. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    3. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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    1. Arendasy, Martin E. & Sommer, Markus & Tschiesner, Reinhard & Feldhammer-Kahr, Martina & Umdasch, Konstantin, 2024. "Using automatic item generation to construct scheduling problems measuring planning ability," Intelligence, Elsevier, vol. 106(C).
    2. Elena Escolano-Perez & José Luis Losada, 2024. "Using artificial intelligence in education: decision tree learning results in secondary school students based on cold and hot executive functions," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    3. Fatima Wasif & Tara McAuley, 2024. "Exploring Close Relationships and Executive Functions as Unique and Joint Predictors of Adolescent Subjective Well-Being Across the Transition to High School," Journal of Happiness Studies, Springer, vol. 25(6), pages 1-21, August.
    4. Feraco, Tommaso & Cona, Giorgia, 2022. "Differentiation of general and specific abilities in intelligence. A bifactor study of age and gender differentiation in 8- to 19-year-olds," Intelligence, Elsevier, vol. 94(C).

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