Which Measures From a Sustained Attention Task Best Predict ADHD Group Membership?

Area of Science:

• Neuroscience
• Psychology
• Child Development

Background:

• Sustained attention difficulties are a core feature of Attention-Deficit/Hyperactivity Disorder (ADHD).
• Identifying reliable measures of sustained attention is crucial for accurate ADHD diagnosis in children.

Purpose of the Study:

• To determine which specific metrics derived from the Sustained Attention to Response Task (SART) best predict an ADHD diagnosis.
• To evaluate the diagnostic utility of various SART performance measures in a pediatric population.

Main Methods:

• A cohort of 129 children diagnosed with ADHD and 129 matched controls completed the fixed SART.
• Performance metrics including errors (commission, omission), response time variability (SDRT, tau, SFAUS), and signal detection measures (d-prime, criterion, mu) were analyzed.

Main Results:

• Several SART measures successfully differentiated children with and without ADHD.
• The most effective classifiers were d-prime (AUC 0.75), tau (0.74), SDRT (0.74), omission errors (0.72), commission errors (0.71), and SFAUS (0.70).
• Mean response time, criterion, and sigma did not effectively classify participants.

Conclusions:

• Specific SART-derived measures, particularly d-prime, tau, and SDRT, demonstrate strong potential for classifying ADHD in children.
• These findings can inform the selection of sensitive and specific measures for future ADHD research and clinical assessment.