Intensive-neurofeedback Protocol for Children With ADHD: A Proof-of-concept Study Comparing iAPF-personalized and Standard Theta-beta-ratio Training

Overview

The first aim of this clinical trial is to test the feasibility and signal validity of a new approach to neurofeedback training (NF) using intensive EEG-based theta-beta NF for children with ADHD in the context of NF camps during school holidays. The second aim is to compare the efficacy of two neurofeedback protocols in reducing ADHD symptoms. Previous study results highlight that children with ADHD frequently show increased Theta-Beta-Ratios (TBR) in the qEEG, probably associated with attention difficulties, which may be ameliorated following neurofeedback training. However, the current state of research shows heterogenous findings regarding the efficacy of standard TBR NF for children with ADHD. Further study results suggest that personalized NF training protocols, based on the individual alpha peak frequency (iAPF), may be more effective in reducing ADHD symptoms than standardized ones. Therefore, in this proof-of-concept study of children with ADHD a standard TBR NF protocol is compared with an iAPF-personalized TBR NF (iAPF-TBR NF) protocol (based on the previously obtained iAPF). The study is designed as a randomized controlled intervention trial (RCT) with three assessment points (pre \[T1\], post \[T2\] and 6-month follow-up \[T3\]). Primary endpoints include the reduction of ADHD symptoms assessed by parent-, teacher- and self-report questionnaires. Furthermore, it is hypothesized that NF training is associated with better performance in a sustained attention and executive function test and a reduced TBR in qEEG, particularly following iAPF-TBR NF. The main questions are: * Is it feasible to train groups of up to 12 children with two sessions NF per day for an eight-day-period during their school holidays? * Does iAPF-TBR NF provide a valid neuromodulatory signal compared to the standard-TBR-NF protocol? Do the frequency boundaries demonstrate spectral stability across the 16 training sessions? * Does the personalized iAPF-TBR NF training reduce ADHD symptoms measured immediately after the training more than standard-TBR-NF training? (comparison T2-T1) * Does the personalized iAPF-TBR NF training reduce ADHD symptoms measured 6 months after the NF training more than standard TBR-NF training? (comparison T3-T1) * Does the reduction in ADHD symptoms measured immediately after the NF-training persist until the 6-month follow-up? Do possible differences between iAPF-TBR NF training and standard TBR NF training remain? (comparison T3-T2) Post-hoc analyses of the courses are carried out. In addition, selectivity analyses will be carried out for clinical subgroups (e.g. different ADHD profiles)

Detailed description

The study investigates the effectiveness of two NF approaches within a "school-holiday-camp"-setting. NF is a learning method based on neural plasticity, where specific EEG frequency bands are fed back in real-time. Participants will be randomly assigned to one of two conditions:

1. Standard-NF training targeting a reduction of the TBR with fixed reward frequencies for the entire group. 2. iAPF-TBR NF training targeting a reduction of the TBR with reward frequencies individually adjusted based on the child's pre-measured iAPF.

The training includes two sessions daily over eight camp days (a total of 16 sessions). While a small effect size (d = .2) would be expected for the comparison of iAPF-TBR NF and standard TBR NF requiring a total sample of N = 620 α= .05, 1-β = .8, G\*Power; Faul et al., 2007), the present study is designed as a preliminary proof-of-concept study including an adopted target sample size. Therefore, the target sample size is set at N = 40 participants (n = 20 per arm). This sample size is sufficient to detect a medium to large effect (d = .7) with α= .10 and 1-β = .7 using one-tailed testing. This directional testing is justified by the theoretical advantage of personalized iAPF-TBR over the standard-TBR NF. The results of this pilot study will serve as essential preliminary evidence to justify the scaling of the protocol in a fully powered RCT.

The effects will be evaluated at the EEG, parent-, teacher- and self-report questionnaires, and behavioral (CPT) levels. The main objective is to determine whether the personalized NF protocol leads to superior and more sustainable effects.

Baseline frequency bands: Prior to each neurofeedback session, a one-minute resting-state EEG baseline is recorded to establish individual gain thresholds for theta and beta power. To control for non-cortical influences such as EMG artefacts, Power in frequency band 20-40 Hz is additionally required to be below a baseline threshold.

For NF and QEEG the THERA PRAX® MOBILE 13-channel full-band DC-EEG devices will be used (neuroConn GmbH, Ilmenau, Germany). They include a THERA PRAX® MOBILE MONITOR (PC panel) with INTEL CPU Core i3, 15" TFT color monitor and Windows® 10. The EEG amplifier is the THERA PRAX® DC-EEG Amplifier with 13 unipolar channels with an input impedance of \< 10 GΩ, digitized with 24-bit-resolution and a sampling rate of 256/s. For skin preparation alcohol and abrasive gel (Nuprep Gel, D.O. Weaver, Aurora, CO), Ag/AgCl ring electrodes, covered with conductive paste (Ten20, D.O. Weaver) will be used. EEG, EOG and EMG data will be measured and stored by the THERA PRAX® system. The online processing of the measured EEG data during NF sessions uses a short-time Fourier-transformed moving average before the participants receive feedback on the monitor. As feedback, elements of a 15\*15 grid picture selected by the participant were uncovered if the dynamic reward condition (with respect to Baseline B: EMGLOW ≤ B - 2.0 μV and Theta ≤ B + 3.0 μV and Beta ≥ B + 3.0 μV activity) is reached for 250 ms , respectively. The length of the time window analyzed in each case is 1 s which is shifted in steps of 40 ms.

Interventions

• Behavioral Standard TBR-NF
  Training is based on the classic Theta-Beta-Ratio protocol, where the reward frequencies are fixed for the entire training group (Hao et al., 2022): Frequency bands with fixed division: Theta 4 - 8 Hz Alpha 8 - 13 Hz Beta 13 - 30 Hz Gamma 30 - 45 Hz * Upgrade Beta Frequencies: 13 - 30 Hz * Downgrade Theta Frequencies: 4 - 8 Hz * Aim: Reduce Theta-Beta Ratio * 10-20-electrode positions: Cz with reference and ground electrodes at A1 and A2 * Duration: 15 min.
• Behavioral iAPF -TBR-NF
  Reward frequencies are adjusted based on the child's iAPF to create a customized training protocol: Calculation of the frequency bands using T1-iAPF (Hao et al., 2022): Frequency bands with individual division: Theta 4 - 0.8 \* iAPF Hz Alpha 0.8 \* iAPF - 1.3 \* iAPF Hz Beta 1.3 \* iAPF - 3.0 \* iAPF Hz Gamma 3.0 \* iAPF - 45 Hz * Upgrade individually calculated beta frequencies * Downgrade individually calculated theta frequencies * Aim: Reduce Theta-Beta Ratio * 10-20-electrode position

Primary outcome measures

• Adverse effects [Time frame: Baseline at week 1, during week 5 and 6 after each neurofeedback session (intervention), post-measurement at week 10, follow-up-measurement at week 30]
• Drop-Out rate [Time frame: Baseline at week 1, during week 5 and 6 after each neurofeedback session (intervention), post-measurement at week 10, follow-up-measurement at week 30]
• Number of included segments [Time frame: During week 5 and 6 after each neurofeedback session (intervention)]
• Diagnostic system for mental disorders according to ICD-10 and DSM-5 for children and adolescents - III External report form ADHD specific (DISYPS-III FBB-ADHS; Döpfner et al., 2017) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]
• Child Behavior Checklist 6-18/R (CBCL; Döpfner et al., 2014) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]
• Teacher Report Form 6-18/R (TRF; Döpfner et al., 2014) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]
• Youth Self Report 11-18/R (YSR, Döpfner et al., 2014) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]
• Change in central theta and beta activity [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]

Secondary outcome measures (2)

• Behavior Rating Inventory of Executive Function (BRIEF; Drechsler et al., 2013) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]
• Continuous Performance Test (CPT, Knye et al., 2003) [Time frame: Baseline at week 1, post-measurement at week 10, follow-up-measurement at week 30]

Eligibility criteria

Inclusion criteria

• Children aged 6-13 years. Confirmed ADHD diagnosis (ICD 10: F90.0, F90.1, or F98.8)
• German-speaking children with normal or corrected vision.

Exclusion criteria

• Children with neurological disorders (e.g., Epilepsy)
• Children without an ADHD diagnosis
• Caregivers with inability to provide informed consent or complete questionnaires
• Participation in neurofeedback that was conducted in the year prior to the intended participation or is still ongoing.

The intake of medication or psychotherapeutic treatments and ICD-10 diagnosis are queried at T1, T2 and T3. These are recorded as control variables and are not exclusion criteria. The medication intake was kept constant during the NF training.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Triple blind

Primary purpose

Treatment

Study locations

Germany · 2 centers

• Bielefeld University — Bielefeld
• Philipps-University Marburg — Marburg

Publications

• Drechsler, R., & Steinhausen, H. C. E. (2013). Verhaltensinventar zur Beurteilung exekutiver Funktionen: Deutschsprachige Adaptation des Behavior Rating Inventory of Executive Function: BRIEF.
• Döpfner, M., Plück, J. & Kinnen, C. (2014). Deutsche Schulalter-Formen der Child Behavior Checklist von Thomas M. Achenbach. Hogrefe.
• Knye, M., Roth, N., Westhus, W. & Heine, A. (2003). Continuos Performance Test. Hogrefe.
• Döpfner, M., & Görtz-Dorten, A. (2017). Diagnostik-System für psychische Störungen nach ICD-10 und DSM-5 für Kinder und Jugendliche-III (DISYPS-III) (3. Aufl.). Hogrefe.
• Eldridge SM, Chan CL, Campbell MJ, Bond CM, Hopewell S, Thabane L, Lancaster GA; PAFS consensus group. CONSORT 2010 statement: extension to randomised pilot and feasibility trials. Pilot Feasibility Stud. 2016 Oct 21;2:64. doi: 10.1186/s40814-016-0105-8. eCollection 2016. PMID 27965879
• Hao Z, He C, Ziqian Y, Haotian L, Xiaoli L. Neurofeedback training for children with ADHD using individual beta rhythm. Cogn Neurodyn. 2022 Dec;16(6):1323-1333. doi: 10.1007/s11571-022-09798-y. Epub 2022 Apr 1. PMID 36408061
• Himmelmeier L, Waltereit R, Werheid K. Multi-method ADHD diagnostics in children: CBCL and TRF lead the way. Front Psychiatry. 2025 Nov 17;16:1668149. doi: 10.3389/fpsyt.2025.1668149. eCollection 2025. PMID 41334079

Identifiers

NCT: NCT07595783 · NF-2024-12

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗