Evaluation of The Role of Quantitative Electroencephalogram in The Diagnosis of Attention Deficit Hyperactivity Disorder in School Age Children

Background: Attention Deficit Hyperactivity Disorder (ADHD) is among the most frequently diagnosed and treated conditions in child psychiatry. Quantitative electroencephalogram (QEEG) has recently shown diagnostic value across psychiatric disorders, including ADHD. Studies consistently report elevated theta and/or reduced beta activity as characteristic of ADHD, with potential to support clinical subgrouping.Aim: This study examined the diagnostic efficiency of QEEG in distinguishing children with ADHD from healthy controls, evaluated the relationship between QEEG variables—particularly the theta/beta ratio (TBR)—and ADHD behavioral patterns, and explored the potential of QEEG-based subgrouping. Methods : A case-control design included 45 children with ADHD (aged 6–12 years, IQ ≥ 90) and 30 age- and sex-matched healthy controls. EEG data were recorded using 19 scalp electrodes according to the International 10–20 System, with artifact-free epochs analyzed over an average of 60 seconds. Results: Compared to controls, ADHD children demonstrated reduced alpha power across all regions, with significant reductions in frontal, temporal, parietal, and occipital sites (e.g., F7, F3, C3, O1, Cz). Beta 1 power was lower, notably in F3, while theta power was elevated across channels, especially at Fp1 and F3. Consequently, ADHD subjects exhibited significantly higher TBR, suggesting its utility as a diagnostic marker. Subgroup analysis revealed four ADHD EEG patterns: excess beta activity, excess delta (slow) waves, excess theta activity, and non-spectral elevation (NSE). The highest TBR occurred in the excess-theta subgroup, followed by excess-delta, while NSE and excess-beta groups showed lower or control-like ratios. This challenges TBR as a stand-alone diagnostic tool but supports its complementary value. Behavioral analysis showed inattentive symptoms were most pronounced in the excess-theta group, followed by excess-delta and excess-beta groups, while NSE showed minimal difference. Hyperactivity/impulsivity was significantly increased in the excess-theta subgroup. Overall ADHD severity was highest in the excess-theta group, followed by excess-beta, excess-delta, and NSE. Conclusion: QEEG demonstrates clinical utility in ADHD diagnosis by revealing distinct electrographic abnormalities, most notably reduced alpha power, increased slow-wave (theta) activity, and decreased fast-wave (beta) power. While TBR can support diagnostic differentiation, it is not universally reliable across subtypes. Findings highlight ADHD as a heterogeneous disorder with multiple electrophysiological subtypes, underscoring the need for further research into their behavioral, prognostic, and treatment correlations.