Executive Functions (EFs) comprise a set of mental skills that enable university students to consciously regulate their academic performance and learning behaviors. Research has identified several EFs as critical determinants of academic success, including emotion regulation, responsibility monitoring, working memory, cognitive flexibility, metacognitive learning, study planning, and decision-making. This protocol article presents an enhanced version of a scale designed to assess EF in the university context. The principal innovation of this revised instrument lies in its incorporation of five additional EFs, thereby providing a more comprehensive evaluation of these cognitively demanding skills essential for academic achievement. Our proposed methodology follows a psychometric validation process to examine the scale’s reliability, validity, and practical utility. Through this protocol, we anticipate establishing robust measurement properties for the new scale, advancing our understanding of university students’ cognitive processes. Furthermore, we expect the findings to facilitate the development of improved assessment tools and targeted interventions to enhance executive functioning in higher education settings. This research contributes to the growing literature seeking to optimize academic outcomes through evidence-based cognitive evaluation and support.
propiedades psicométricas
Executive Functions Scale for University Students: Protocol for the Second Version (UEF-2)
Propiedades Psicométricas del Inventario CABI Para la Determinación del TDAH. Psychometric Properties Of The Cabi Inventory In The Determination Of ADHD.
Attention Deficit Hyperactivity Disorder (ADHD) is one of the most frequent mental health issues among children and adolescents
worldwide. Current literature shows that ADHD could affect both academic and work performances of those who present it. The aim of the present study was to analyze the psychometric properties of the Child and Adolescence Behavior Inventory (CABI) through an exploratory study, based on the report of 350 Chilean parents. Results indicated a three-dimensional model (sluggish cognitive tempo, inattention and hyperactivity) with adequate fit of the data (RMSEA=0.065; CFI= 0.954; TLI=0.941; PL=207) that explained 61.76% of the total variance with an Alpha of 0.961. Results show that the subscales analyzed have acceptable psychometric properties, an adequate internal consistency and that their indicators have a correct discriminatory power.
Therefore, according to these preliminary results, CABI can be considered a useful assessment tool for the diagnosis of ADHD. Implications for practice, policy and future research are discussed.
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Psychometric Properties Of ADHD Rating Scale In School Context. Propiedades Psicométricas de la Escala ADHD en el Contexto Escolar
Background: The ADHD Rating Scale IV (ADHD RS IV) is one of the most commonly used scales in attention deficit hyperactivity disorder (ADHD) assessment. Its psychometric properties have been studied in contexts including Europe and North America, however, in Latin America, there is shortage of empirical evidence about validity or reliability reported by teachers on a scholar context. The aim of the research was to analyze the psychometric properties of the ADHD RS IV based on the behavior of students reported by teachers. Material/methods: Three hundred and forty-five students voluntarily participated in this study (162 men and 183 women), aged between 5 and 15 years (Mage = 10.43, SD = 3.61). As instruments of measurement ADHD RS IV, Perception of Differences Test and Go / No-Go experiment were used. Cronbach’s alpha, Pearson correlation and confirmatory factor analysis were applied and analyzed. Results: In the results it was found that internal consistency coefficient of RS IV ADHD is between .93 and .97. There is a significant statistically correlation between the scale and the number of successes points in the Perception of Differences Test (r = -.55, p = < .001) and mistakes to stimuli no-go (r = .34, p = .002). The classic ADHD model of two factors had good indicators of goodness of fit x2(101) = 321.40, p < .001; CFI = .96; RMSEA = .08 (.07 to .09) and SRMR = .04. Conclusions: The article is finalized highlighting the ADHD RS IV has adequate psychometric properties in order to be applied in the school context.
