Combining Process Data and Subjective Ratings to Optimize ADHD Diagnostics

Abstract: This article addresses current practices in attention-deficit/hyperactivity disorder (ADHD) diagnosis and their limitations. As a proposed improvement, we introduce a newly developed ADHD test battery for children aged 6 – 12 that integrates subjective ratings from parents and teachers with computer-based process data. The process data include parameters from the reaction time distributions of tasks measuring inhibition of irrelevant stimuli (flanker task) and impulse control (go/no-go task). The normed composite score of this test battery is derived via logistic regression in a way that optimizes discriminative power to distinguish between children with and without ADHD. Using a sample of 710 children (including 58 with ADHD), we demonstrate that this composite score is superior to scores derived exclusively from either performance-based process data or subjective ratings alone. We discuss these findings in relation to current ADHD diagnostic practices and consider their implications for future refinements to the scientific conceptualization of ADHD.