A multicenter effectiveness trial of QEEG-informed neurofeedback in ADHD: Replication and treatment prediction.

Introduction: Quantitative Electroencephalogram-(QEEG-)informed neurofeedback is a method in which standard neurofeedback protocols are assigned, based on individual EEG characteristics in order to enhance effectiveness. Thus far clinical effectiveness data have only been published in a small sample of 21 ADHD patients. Therefore, this manuscript aims to replicate this effectiveness in a new sample of 114 patients treated with QEEG-informed neurofeedback, from a large multicentric dataset and to investigate potential predictors of neurofeedback response.
Methods: A sample of 114 patients were included as a replication sample. Patients were treated with standard neurofeedback protocols (Sensori-Motor-Rhythm (SMR), Theta-Beta (TBR), or Slow Cortical Potential (SCP) neurofeedback), in combination with coaching and sleep hygiene advice. The ADHD Rating Scale (ADHD-RS) and Pittsburgh Sleep Quality Index (PSQI) were assessed at baseline, every 10th session, and at outtake. Holland Sleep Disorder Questionnaire (HSDQ) was assessed at baseline and outtake. Response was defined as ≥25% reduction (R25), ≥50% reduction (R50), and remission. Predictive analyses were focused on predicting remission status.
Results: In the current sample, response rates were 85% (R25), 70% (R50), and remission was 55% and clinical effectiveness was not significantly different from the original 2012 sample. Non-remitters exhibited significantly higher baseline hyperactivity ratings. Women who remitted had significantly shorter P300 latencies and boys who remitted had significantly lower iAPF's.
Discussion: In the current sample, clinical effectiveness was replicated, suggesting it is possible to assign patients to a protocol based on their individual baseline QEEG to enhance signal-to-noise ratio. Furthermore, remitters had lower baseline hyperactivity scores. Likewise, female remitters had shorter P300 latencies, whereas boys who remitted have a lower iAPF. Our data suggests initial specificity in treatment allocation, yet further studies are needed to replicate the predictors of neurofeedback remission.
(Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)