Abnormal Child Behavior in primary school students: A Bayesian network analysis Le comportement anormal de l'enfant en école primaire : une analyse par réseau bayésien - 2025
Abnormal Child Behavior in primary school students: A Bayesian network analysis Le comportement anormal de l'enfant en école primaire : une analyse par réseau bayésien
Network analysis ADHD CTRS-R; S Psychometric scale Bayesian network Analyse par réseau TDAH CTRS-R; S Échelle psychométrique Réseau bayésien
Abstract :
[en] The Conners Teacher Rating Scale revised: short (CTRS-R: S) is a widely used psychometric instrument to screen for Attention Deficit and Hyperactivity Disorder (ADHD) as well as a broader construct of abnormal child behavior. In this study, we aimed to examine the network structure of abnormal child behavior using the CTRS-R: S in a sample of 525 French-speaking primary school students from Belgium. We employed Bayesian network analysis to estimate both the 28-item network and the network with the 8 items with the highest strength centrality, using the PC algorithm and bootstrapping to estimate the figures. Our study uncovered associations between inattention symptoms and learning disorders, shedding new light on the complexity of abnormal child behavior. We also identified different network structures, revealing a fresh perspective on the underlying mechanisms of these conditions. Our findings, though preliminary, are consistent with previous research and add to the burgeoning literature on Bayesian network analysis in abnormal child behavior research. Overall, our study underscores the complexity of the construct of abnormal child behavior and the importance of considering multiple factors in screening and diagnosis, emphasizing the need for a comprehensive approach to understanding and treating these disorders.
Disciplines :
Psychiatry
Author, co-author :
Till, Apolline; Chair of Artificial Intelligence and Digital Medicine, Department of Neuroscience, Faculty of Medicine, University of Mons, Mons, Belgium
Henry, Teague; Department of Psychology and School of Data Science, University of Virginia, Charlottesville, United States of America
Scutari, Marco; Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland
Briganti, Giovanni ; Université de Liège - ULiège > Département des sciences cliniques > Santé digitale ; Chair of Artificial Intelligence and Digital Medicine, Department of Neuroscience, Faculty of Medicine, University of Mons, Mons, Belgium ; Laboratoire de Psychologie Médicale, Faculté de Médecine, route de Lennik 808, Université libre de Bruxelles, Brussels, Belgium
Language :
English
Title :
Abnormal Child Behavior in primary school students: A Bayesian network analysis Le comportement anormal de l'enfant en école primaire : une analyse par réseau bayésien
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