En este estudio, el objetivo principal es analizar la validez externa del test AULA y estudiar su efectividad diagnóstica en relación con el TDAH. La muestra seleccionada consistió en 407 niños (272 hombres y 135 mujeres) entre 6 y 16 años del norte de España. De estos, 213 tenían un diagnóstico de TDAH (105 con tipo predominantemente inatento, 108 con tipo combinado) y 194 eran controles. Los resultados obtenidos muestran, por un lado, una convergencia óptima entre las variables comparables de la escala Conners (validada en España con el nombre de EDAH) y las variables estudiadas con AULA. Por otro lado, demuestran la eficacia de AULA para clasificar a los sujetos como patológicos o sanos. Estos resultados proporcionan una mayor validez externa a la herramienta y su especificidad y sensibilidad.
ABSTRACT:
The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) is mainly based on structured scales, such as Conners’ ADHD Rating Scale (EDAH in the Spanish version) and DSM interviews. The use of technologies in neuropsychological assessment, such as the AULA virtual reality based test leads to more accurate diagnosis. The current study presents findings from analyzing the external validity of AULA and its contribution to the diagnosis of ADHD. Four hundred and seven children (272 girls and 135 boys) from 6 to 16 years old (213 with ADHD diagnosis, 105 inattentive children, 108 combined-type, and 194 controls) were evaluated. First, a factor analysis of AULA variables was conducted in order to reduce data to factor and 5 factors or components that account for 82.37% of the total variance were obtained from 407 subjects, namely, sustained attention, impulsivity control, processing speed, response variability, and control of motor activity. Second, a discriminant analysis was then performed on data obtained by participants from whom the five factors were obtained, showing that AULA presents moderate levels of both specificity and sensitivity. Finally, in order to study whether AULA adds relevant information in the diagnosis of ADHD, a cluster analysis was carried out, showing 4 clusters in the analysis of conglomerates with the control group and 6 groups of clusters in the ADHD group. In summary, AULA test shows adequate external validity, allows correct classification of children with and without attentional problems, and confirms and provides additional ADHD diagnostic information that it is essential for the design of interventions.
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«Finally, in order to study whether AULA adds relevant information in the diagnosis of ADHD, a cluster analysis was carried out, showing 4 clusters in the analysis of conglomerates with the control group and 6 groups of clusters in the ADHD group. In summary, AULA test shows adequate external validity, allows correct classification of children with and without attentional problems, and confirms and provides additional ADHD diagnostic information that it is essential for the design of interventions.
In relation to the complementary information provided by AULA for the diagnosis of ADHD and oriented to a cognitive behavioral intervention, AULA enhances the relevance of dimensions related about how to behave, to cope with tasks, or even how to face and solve problems in a way that is not provided by the behavioral diagnosis obtained with DSM scales and EDAH. However, as it has been observed in obtained clusters, groups are differentiated on the basis of the presence of hyperactivity and/or impulsivity. Thus, AULA will differentiate subgroups in an efficient way, that is, it will specify executive profiles not previously detected by mean of traditional diagnostic tools or procedures. In summary, AULA provides information about performance in different domains and discriminates between impulsivity and hyperactivity.»
Zulueta, Aitziber; Díaz-Orueta, Unai; Crespo-Eguilaz, Nerea; Torrano, Fermín
Virtual Reality-based Assessment and Rating Scales in ADHD Diagnosis
Psicología Educativa, vol. 25, no. 1, 2019, pp. 13-22
Colegio Oficial de Psicólogos de Madrid
Este proyecto ha recibido financiación de la Unión Europea del programa de investigación e innovación
Horizon 2020 bajo el acuerdo Nº 733901
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