“So... my child...” - How Child ADHD Influences the Way Parents Talk

Attention-deficit/hyperactivity disorder (ADHD) exerts a psychological burden not only on affected individuals but also on their social support systems. Of particular interest are the parents, who often face challenges related to their child's condition, including its impact on their own mental well-being. The interaction among the child's symptomatology, parental mental health, and the parent-child relationship is a crucial area of investigation. Expressed Emotion (EE), as assessed through the Preschool Five Minute Speech Sample (PFMSS), serves as a valuable measure. However, manual annotation of EE can be cumbersome and impractical for continuous monitoring. To address this, we propose leveraging machine learning methods. This study presents an initial exploration into predicting children's ADHD diagnosis using linguistic and paralinguistic features derived from the PFMSS. Despite achieving a UAR score of 67.1 %, our results have not surpassed the performance of manually annotated EE.