AUTHOR=Micoulaud-Franchi Jean-Arthur , Geoffroy Pierre Alexis , Fond Guillaume , Lopez Régis , Bioulac Stéphanie , Philip Pierre TITLE=EEG neurofeedback treatments in children with ADHD: an updated meta-analysis of randomized controlled trials JOURNAL=Frontiers in Human Neuroscience VOLUME=8 YEAR=2014 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2014.00906 DOI=10.3389/fnhum.2014.00906 ISSN=1662-5161 ABSTRACT=

Objective: We undertook a meta-analysis of published Randomized Controlled Trials (RCT) with semi-active control and sham-NF groups to determine whether Electroencephalogram-neurofeedback (EEG-NF) significantly improves the overall symptoms, inattention and hyperactivity/impulsivity dimensions for probably unblinded assessment (parent assessment) and probably blinded assessment (teacher assessment) in children with Attention Deficit Hyperactivity Disorder (ADHD).

Data sources: A systematic review identified independent studies that were eligible for inclusion in a random effects meta-analysis.

Data extraction: Effect sizes for ADHD symptoms were expressed as standardized mean differences (SMD) with 95% confidence intervals.

Results: Five identified studies met eligibility criteria, 263 patients with ADHD were included, 146 patients were trained with EEG-NF. On parent assessment (probably unblinded assessment), the overall ADHD score (SMD = −0.49 [−0.74, −0.24]), the inattention score (SMD = −0.46 [−0.76, −0.15]) and the hyperactivity/impulsivity score (SMD = −0.34 [−0.59, −0.09]) were significantly improved in patients receiving EEG-NF compared to controls. On teacher assessment (probably blinded assessment), only the inattention score was significantly improved in patients receiving EEG-NF compared to controls (SMD = −0.30 [−0.58, −0.03]).

Conclusions: This meta-analysis of EEG-NF in children with ADHD highlights improvement in the inattention dimension of ADHD symptoms. Future investigations should pay greater attention to adequately blinded studies and EEG-NF protocols that carefully control the implementation and embedding of training.