Explanatory models of executive functioning in university students: Decision tree and structural equations analysis.

Abstract

Executive functions are fundamental to the success of students in higher education. Our objective was to develop an explanatory model based on the interaction of executive functions. This study used a cross-sectional design with a sample of 1,233 Cuban university students. The Cuban adaptation of the University Executive Function Scale, which assesses seven executive function dimensions, was employed. In the first phase, descriptive statistics were used to analyze the scores of these functions in the studied population, identifying those with the lowest performance. The second phase applied a decision tree analysis using the CHAID method, considering risk and accuracy estimators, to determine the main predictors of executive functions. Finally, in the third phase, a structural equation model was developed to examine the relationships between variables and the predictors of the least developed executive functions, assessing model fit using the CFI, TLI, RMSEA, and SRMR indices. The results indicate that the majority of scores in the executive functions of Cuban university students fall within the average range, although below-average scores were observed in Conscious Regulation of Behavior and Conscious Monitoring of Responsibilities. The decision tree analysis identified that the Supervisory Attention System is the main predictor of Conscious Monitoring of Responsibilities, while Conscious Regulation of Emotions emerged as the strongest predictor of Conscious Regulation of Behavior. Structural equation models reveal that the Supervisory Attention System and Verification of Behavior for Learning are key predictors of Conscious Monitoring of Responsibilities, and that the latter also positively influences Emotional and Behavioral Regulation.