A novel approach to ADHD classification based on severity and emotional impairment: Findings from artificial intelligence analysis

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a disorder characterized by symptoms of inattention and executive dysfunction, although there is not always agreement on the onset, course and long-term stability of the diagnosis. This study aims to detect differences in the cognitive profile according to the subtype of ADHD following a professional diagnosis and to propose an alternative classification. The scores obtained for each cognitive construct were compared using the Student’s t-test. In order to explore different diagnostic categories based on groupings made by Artificial Intelligence (AI) subjects were grouped based on their performance through the K-means clustering technique. The results obtained by Artificial Intelligence (AI) identified groups based on the severity of the cognitive profile and the presence of emotional impairment. Difficulties in perceived planning within family and school environments were highlighted as major risk factors in the severity of ADHD in children. Emotional disturbances perceived by both parents, such as depressive symptoms, anxiety, and somatization, were observed subsequently. In accordance with the results, an alternative way to classify ADHD is possible, involving categorization according to the presence or absence of emotional impairment, along with the severity of impairment in attentional and executive functions.