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This research was partially funded by: Ministerio de Ciencia e Innovacion, Proyectos de Transicion Ecologica y Transicion Digital TED2021-130980B-I00, Proyectos de Redes de Investigacion RED2022-134259-T, UC3M (Grant for the requalification of permanent lectures, David Delgado-Gomez), Instituto Salud Carlos III (ISCIII), grant number DTS21/00091, co-funded by the European Union, Consejeria de Educacion e Investigacion: PEJ-2021-AI/SAL-2147, Social responsibility grants from the Social Council of the Carlos III University of Madrid.

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A data science approach to optimize ADHD assessment with the BRIEF-2 questionnaire

Publicado en:Translational Neuroscience. 15 (1): 20220349- - 2024-10-08 15(1), DOI: 10.1515/tnsci-2022-0349

Autores: Caselles-Pina, Lucia; del Amo, Paula Serna; Aguado, David; Lopez-Castroman, Jorge; Sanjuan-Antunez, Juan de Dios; Delgado-Gomez, David

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Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. A key challenge associated with this condition is achieving an early diagnosis. The current study seeks to anticipate and delineate the assessments offered by both parents and teachers concerning a child's behavior and overall functioning with the Behavior Rating Inventory of Executive Function-2 (BRIEF-2). Mothers, fathers, and teachers of 59 children diagnosed or in the process of being assessed for ADHD participated in this study. The responses provided by 59 mothers, 59 fathers, and 57 teachers to the BRIEF-2 questionnaire were collected. The performance of various feature selection techniques, including Lasso, decision trees, random forest, extreme gradient boosting, and forward stepwise regression, was evaluated. The results indicate that Lasso stands out as the optimal method for our dataset, striking an ideal balance between accuracy and interpretability. A repeated validation analysis reveals an average positive correlation exceeding 0.5 between the inattention/hyperactivity scores reported by informants (mother, father, or teacher) and the predictions derived from Lasso. This performance is achieved using only approximately 18% of the BRIEF-2 items. These findings underscore the usefulness of variable selection techniques in accurately characterizing a patient's condition while employing a small subset of assessment items. This efficiency is particularly valuable in time-constrained settings and contributes to improving the comprehension of ADHD.

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