Executive Function Model Basí on Factorial Analysis in Children and School-Age Populations: Meta-analysis

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

Introduction

Executive functions are definí as a set of skills involví in various activities that are novel to the individual and require a creative solution. Their conceptualization and the identification of the úctors that configure them in inúnt and school-age populations is not easy.

Objective

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

Development

Thirty-five articles using different approaches to úctor analysis for úctor extraction were reviewí. The probability of occurrence of a study with three úctors 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 focusing on the flexibility dimension in the 0 to 12 years stage is 1.45 times higher than the presence of a study focusing on any other dimension. The association between the different structures and dimensions analyzí with age using Kendall’s tau-b indicates a statistically significant association between studies with three úctors and age (tau = 0.29; p = 0.044) and flexibility with age (tau = 0.37; p = 0.012).

Conclusions

The diversity of obtainí results can be attributí to and is consistent with the plurality of theoretical conceptualizations, tests usí, and statistical analyses performí. It can be concludí that updating/working memory, inhibition, and flexibility are the executive processes most commonly found in úctorial models of executive control in preschool and school-age children.

Introduction ‘Model of executive functions basí on úctor analyses in inúnt and school-age populations’

Executive functions are definí as a set of skills that are involví 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 ‘unsolví mysteries of the mind’ [5]. If we consider the nature of the executive functions construct, two positions can be differentiatí.

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

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

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

Miyake et al [10] presentí one way to address 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 ‘Model of executive functions basí on úctor analyses in inúnt 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 explainí by a series of unobserví (latent) variables callí úctors, with a number of úctors substantially smaller than that of the variables [11].

Exploratory úctor analysis

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

Confirmatory úctor analysis

In confirmatory úctor analysis (CFA) well-specifií hypotheses are posí (regarding the number of úctors, the pattern of relationships between the variables and the úctors, and relationships among the úctors) that will be testí by evaluating the fit of a model [12]. The latter has become one of the most usí tools to try to solve the problem of impure measures, since it allows identifying the latent structure underlying the performance observí in a cognitive test [13]. Among the advantages of this approach is the possibility of comparing several úctorial models (for example, unidimensional versus multidimensional) and developing an a priori model about the executive demands requirí by different tests that will later be subjectí to analysis, as well as analyzing whether the same úctorial model is applicable to different subgroups, for example, by sex, age, or socioeconomic level [14].

The structure or configuration of executive functions changes throughout 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 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 cool executive tasks shows significant increases in early childhood, but that increase does not occur in the same way in hot executive tasks. Table I presents the structural and functional development of the frontal lobes from 0 to 12 years according to the model proposí by Zelazo et al [3].

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Modelo de funciones ejecutivas basado en análisis factoriales en población infantil y escolar: metaanálisis