Which executive components are most common in preschool and school-age populations?

Updating/working memory, inhibition and cognitive flexibility are the executive processes most frequently identified in factorial models for children aged 0–12 years.

How do exploratory and confirmatory factor analysis differ in studying executive functions?

Exploratory factor analysis uncovers structure without prior hypotheses; confirmatory factor analysis tests specified models, compares alternatives, and assesses model fit and subgroup invariance to clarify latent executive constructs.

What is the task impurity problem in executive function assessment?

Task impurity occurs when executive tests also tap non-executive skills (verbal, visuospatial, motor). Using multiple tasks per construct and latent variable methods helps isolate shared executive variance.

How does the structure of executive functions change with age in children?

Executive structure becomes more differentiated across development; multidimensional (three-factor) models and the prominence of flexibility increase with age, reflecting maturation of frontal systems.

What did the review of factor analysis studies in 0–12 year-olds find?

A review of 35 studies found three-factor models were 1.44 times more likely and flexibility 1.45 times more likely in 0–12 year samples; associations with age were significant (three factors tau=0.29, p=0.044; flexibility tau=0.37, p=0.012).

Executive Function Model Based on Factor Analysis in Child and School-Age Populations: Meta-Analysis

Q: What is the executive functions model based on factor analyses?

A statistical framework using factor analysis to identify latent cognitive factors that explain performance across executive function tasks, aiming to reveal underlying components and reduce the influence of task-specific variance.

Javier Tirapu, Esperanza Bausela-Herreras and Patricia Cordero-Andrés analyze the executive functions model based on factor analyses in child and school-age populations in the neurology journal Neurología.com

Introduction

Executive functions are defined as a set of skills involved in various activities that are novel to the individual and require a creative solution. Their conceptualization and the identification of the factors that configure them in child and school-age populations are not easy.

Objective

To analyze the structure and components of executive function in preschool and school-age populations.

Development

Thirty-five articles were reviewed that use different factorial analysis approaches for factor extraction. The probability of occurrence of a study with three factors in the 0 to 12 years stage is 1.44 times higher than that of studies focusing on another structure. The probability of occurrence of a study that focuses on the flexibility dimension in the 0 to 12 years stage is 1.45 times higher than the presence of a study that focuses on any other dimension. The association between the different structures and dimensions analyzed with age with Kendall’s tau-b indicates a statistically significant association between studies with three factors and age (tau = 0.29; p = 0.044) and flexibility with age (tau = 0.37; p = 0.012).

Conclusions

The diversity of results obtained can be attributed to and is consistent with the plurality of theoretical conceptualizations, tests used and statistical analyses performed. It can be concluded that updating/working memory, inhibition and flexibility are the executive processes most commonly found in factorial models of executive control in preschool and school-age children.

Subscribe
to our
Newsletter

Introduction ‘Executive functions model based on factor analyses in child and school-age populations’

Executive functions are defined as a set of skills that are involved in the generation, monitoring, regulation, execution and readjustment of behaviors appropriate to achieve complex goals, especially those that are novel to the individual and require a creative solution [1]. However, despite multiple definitions and theoretical models [2,3] that attempt to clarify their nature, the concept of executive functions remains vague [4] and even
one of the ‘unsolved mysteries of the mind’ [5]. If we consider the nature of the construct executive functions, two positions can be distinguished.

On the one hand, those who defend the existence of a single construct adaptable to changing environmental demands, comparable to the concept of general intelligence factor or g [6].

On the other hand, there is the view of executive functions as a system composed of multiple independent but closely interrelated processes [7,8].

One of the fundamental problems in the assessment of executive functioning is known as the ‘problem of impure measures‘ [9], as it involves the participation of other non-executive cognitive functions, such as verbal and visuospatial abilities or motor speed.

Miyake et al [10] presented an approach to the task impurity problem consisting of using multiple tasks to measure each component of executive functioning and adopting a latent variable approach to extract the variance common to those tasks.

Factor analysis of the ‘Executive functions model based on factor analyses in child and school-age populations’

Factor analysis is a statistical model that represents the relationships among a set of variables, and posits that such relationships can be explained by a series of unobserved (latent) variables called factors, with a number of factors substantially smaller than that of the variables [11].

Exploratory factor analysis

In exploratory factor analysis (EFA), the researcher analyzes a dataset without any prior hypothesis about its structure, so the results of the analysis will provide information in this regard. However, EFA does not shed light on important conceptual and measurement issues relating to executive functions, because it cannot determine the degree of improvement in model fit that could result from the inclusion of an additional factor.

Confirmatory factor analysis

In confirmatory factor analysis (CFA), well-specified hypotheses are posed (regarding the number of factors, pattern of relationships between variables and factors, and relationships among factors) that will be tested by evaluating the fit of a model [12]. The latter has become one of the most employed tools to try to solve the task impurity problem, as it allows identifying the latent structure underlying observed performance on a cognitive test [13]. Among the advantages of this approach is the possibility of comparing several factorial models (for example, single-factor versus multidimensional) and developing an a priori model about the executive demands required by different tests that will later be subjected to analysis, as well as analyzing whether the same factorial model is applicable to different subgroups, for example, by sex, age or socioeconomic level [14].

The structure or configuration of executive functions changes across the life cycle [15, 16]. De Luca and Leventer [17] analyze the development of executive functions in parallel with the neurological development of the central nervous system, and differentiate between hot executive functions (working memory and inhibition, for example) and cool executive functions (affective decision-making or delay of gratification) [18]. In general terms, O’Toole et al [19] conclude that performance on cold executive tasks shows significant increases in early childhood, but that increase does not occur in the same way in hot executive tasks. Table I shows the structural and functional development of the frontal lobes from 0 to 12 years according to the model proposed by Zelazo et al [3].

Read the full article