Preliminary results of the Epidia4Kids study on brain function in children

Multidimensional ADHD-related symptomatology screening using multimodality biometry

Dados Bibliográficos

ID15516331
AutoresYanice Guigou, Alexandre Hennequin, Théo Marchand (0009-0009-4981-3161, Mines Saint-Étienne), Mouna Chebli, Lucie Isoline Pisella, Pascal Staccini (0000-0002-7608-4066, Cognition Behaviour Technology), Vanessa Douet (0000-0002-5162-8944, Université Côte d'Azur, autor correspondente), Vanessa Douet Vannucci
Ano2025
Volume16
Páginas1466107-1466107
Data de publicação2025-03-17
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Psychiatry (JOURNAL)
Identificadores do periódicoISSN: 1664-0640 • E-ISSN: 1664-0640
EditoraFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2025.1466107
PMID40165864
OpenAlexW4408504263
IdiomaEN
Referências citadas65

Attention-deficit hyperactivity disorder (ADHD) occurs in 5.9% of youth, impacting their health and social conditions often across their lifespan. Currently, early diagnosis is constrained by clinical complexity and limited resources of professionals to conduct evaluations. Scalable methods for ADHD screening are thus needed. Recently, digital epidemiology and biometry, such as the visual, emotional, or digit pathway, have examined brain dysfunction in ADHD individuals. However, whether biometry can support screening for ADHD symptoms using a multimodal tech system is still unknown. The EPIDIA4Kids study aims to create objective measures, i.e., biometrics, that will provide a comprehensive transdiagnostic picture of individuals with ADHD, aligning with current evidence for comorbid presentations. Twenty-four children aged 7 to 12 years performed gamified tasks on an unmodified tablet using the XAI4Kids ® multimodal system, which allows extraction of biometrics (eye-, digit-, and emotion-tracking) from video and touch events using machine learning. Neuropsychological assessments and questionnaires were administered to provide ADHD-related measures. Each ADHD-related measure was evaluated with each biometric using linear mixed-effects models. In contrast to neuro-assessments, only two digit-tracking features had age and sex effects (p < 0.001) among the biometrics. Biometric constructs were predictors of working memory (p < 0.0001) and processing speed (p < 0.0001) and, to a lower extent, visuo-spatial skills (p = 0.003), inattention (p = 0.04), or achievement (p = 0.04), where multimodalities are crucial to capture several symptomatology dimensions. These results illustrate the potential of multimodality biometry gathered from a tablet as a viable and scalable transdiagnostic approach for screening ADHD symptomatology and improving accessibility to specialized professionals. Larger populations including clinically diagnosed ADHD will be needed for further validation

Brain function · Multimodality · Psychiatry · Attention Deficit Hyperactivity Disorder · Clinical Psychology · Computer Science · EEG and Brain-Computer Interfaces · Medicine · Neural and Behavioral Psychology Studies · Neuroscience · Psychology