Sustained effects of neurofeedback in ADHD: a systematic review and meta-analysis

Abstract

Neurofeedback (NF) has gained increasing interest in the treatment of attention-deficit/hyperactivity disorder (ADHD). Given learning principles underlie NF, lasting clinical treatment effects may be expected. This systematic review and meta-analysis addresses the sustainability of neurofeedback and control treatment effects by considering randomized controlled studies that conducted follow-up (FU; 2-12 months) assessments among children with ADHD. PubMed and Scopus databases were searched through November 2017. Within-group and between-group standardized mean differences (SMD) of parent behavior ratings were calculated and analyzed. Ten studies met inclusion criteria (NF: ten studies, N = 256; control: nine studies, N = 250). Within-group NF effects on inattention were of medium effect size (ES) (SMD = 0.64) at post-treatment and increased to a large ES (SMD = 0.80) at FU. Regarding hyperactivity/impulsivity, NF ES were medium at post-treatment (SMD = 0.50) and FU (SMD = 0.61). Non-active control conditions yielded a small significant ES on inattention at post-treatment (SMD = 0.28) but no significant ES at FU. Active treatments (mainly methylphenidate), had large ES for inattention (post: SMD = 1.08; FU: SMD = 1.06) and medium ES for hyperactivity/impulsivity (post: SMD = 0.74; FU: SMD = 0.67). Between-group analyses also revealed an advantage of NF over non-active controls [inattention (post: SMD = 0.38; FU: SMD = 0.57); hyperactivity-impulsivity (post: SMD = 0.25; FU: SMD = 0.39)], and favored active controls for inattention only at pre-post (SMD = - 0.44). Compared to non-active control treatments, NF appears to have more durable treatment effects, for at least 6 months following treatment. More studies are needed for a properly powered comparison of follow-up effects between NF and active treatments and to further control for non-specific effects.

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European Child & Adolescent Psychiatry (2019) 28:293–305
https://doi.org/10.1007/s00787-018-1121-4
REVIEW
Sustained eects ofneurofeedback inADHD: asystematic review
andmeta‑analysis
JessicaVanDoren1 · MartijnArns2,3,4 · HartmutHeinrich1,5 · MadelonA.Vollebregt4,6· UteStrehl7·
SandraK.Loo8
Received: 5 October 2017 / Accepted: 5 February 2018 / Published online: 14 February 2018
© The Author(s) 2018. This article is an open access publication
Abstract
Neurofeedback (NF) has gained increasing interest in the treatment of attention-deficit/hyperactivity disorder (ADHD). Given
learning principles underlie NF, lasting clinical treatment effects may be expected. This systematic review and meta-analysis
addresses the sustainability of neurofeedback and control treatment effects by considering randomized controlled studies
that conducted follow-up (FU; 2–12months) assessments among children with ADHD. PubMed and Scopus databases
were searched through November 2017. Within-group and between-group standardized mean differences (SMD) of parent
behavior ratings were calculated and analyzed. Ten studies met inclusion criteria (NF: ten studies, N=256; control: nine
studies, N=250). Within-group NF effects on inattention were of medium effect size (ES) (SMD=0.64) at post-treatment
and increased to a large ES (SMD=0.80) at FU. Regarding hyperactivity/impulsivity, NF ES were medium at post-treatment
(SMD=0.50) and FU (SMD=0.61). Non-active control conditions yielded a small significant ES on inattention at post-
treatment (SMD=0.28) but no significant ES at FU. Active treatments (mainly methylphenidate), had large ES for inattention
(post: SMD=1.08; FU: SMD=1.06) and medium ES for hyperactivity/impulsivity (post: SMD=0.74; FU: SMD=0.67).
Between-group analyses also revealed an advantage of NF over non-active controls [inattention (post: SMD=0.38; FU:
SMD=0.57); hyperactivity–impulsivity (post: SMD=0.25; FU: SMD=0.39)], and favored active controls for inattention
only at pre-post (SMD=− 0.44). Compared to non-active control treatments, NF appears to have more durable treatment
effects, for at least 6months following treatment. More studies are needed for a properly powered comparison of follow-up
effects between NF and active treatments and to further control for non-specific effects.
Keywords Neurofeedback· EEG biofeedback· ADHD· Meta-analysis· Sustainability· Follow-up
Introduction
Clinical guidelines for attention-deficit/hyperactivity disor-
der (ADHD) recommend multimodal treatment approaches,
with current evidence suggesting that medication, including
methylphenidate and various amphetamine formulations, in
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s0078 7-018-1121-4) contains
supplementary material, which is available to authorized users.
* Martijn Arns
martijn@brainclinics.com
1 Department ofChild andAdolescent Mental Health,
University Hospital Erlangen, Erlangen, Germany
2 Department ofExperimental Psychology, Utrecht University,
Utrecht, TheNetherlands
3 neuroCare Group, Munich, Germany
4 Research Institute Brainclinics, Bijleveldsingel 34,
6524ADNijmegen, TheNetherlands
5 kbo-Heckscher-Klinikum, Munich, Germany
6 Department ofCognitive Neuroscience, Donders Institute
forBrain, Cognition andBehaviour, Radboud University
Medical Centre, Nijmegen, TheNetherlands
7 Institute forMedical Psychology, University ofTuebingen,
Tuebingen, Germany
8 Department ofPsychiatry andBiobehavioral Science,
David Geffen School ofMedicine, University ofCalifornia,
LosAngeles, USA
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294 European Child & Adolescent Psychiatry (2019) 28:293–305
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conjunction with psychosocial treatment are most effec-
tive in the short-term [1]. Medication treatments have large
effect size in the acute treatment of ADHD [2] and, when
combined with psychosocial treatments, large effects up to
2years of treatment were observed [3, 4]. Nevertheless, it
is widely accepted that further treatments with long-lasting
effects have to be developed and evaluated.
Over the last decade, an increasing number of studies
investigating non-pharmacological treatments have been
published. Neurofeedback (NF), which aims at improving
self-regulation of brain activity (most often the electroen-
cephalogram, EEG) using a brain–computer interface, has
gained popularity [5]. A promising aspect of neurofeedback
is that it may rely on procedural learning, thereby poten-
tially allowing lasting effects and thus longer clinical benefit
after completion of neurofeedback treatment. In their review,
Arns and Kenemans [6] found that the clinical effects of
neurofeedback were maintained across 6 and 24-month fol-
low-up periods, with a trend for larger symptom decreases
for hyperactivity/impulsivity after 24months than after
6months, albeit only based on two randomized studies at
6months and only one at the 24-month follow-up, thus limit-
ing the generalizability of the findings. A systematic review
and meta-analysis that assess the sustainability of clinical
effects of NF studies is, therefore, desirable.
In recent years, several randomized control studies
(RCTs) and meta-analyses have been published on the effi-
cacy of neurofeedback for children with ADHD, overall
with mixed results and interpretations [7–11]. Regarding
RCTs published over the last decade, one major issue is
the lack of standardization of neurofeedback protocols and
implementations. Neurofeedback treatments using theta/
beta, slow cortical potential (SCP), or sensorimotor-rhythm
(SMR) protocols have been well studied and can be seen as
‘standard’ neurofeedback treatments (for review and discus-
sion see: Arns etal. [5] and Figure S-2 in Supplementary
Material). These ‘standard’ protocols have been selected
as the primary protocols for NF research based on findings
that children with ADHD have specific deficits in compari-
son with healthy controls: e.g. increased theta/beta ratios
in subgroups of ADHD patients hypothesized to be related
to inattention [12]; decreased contingent negative varia-
tion amplitudes (targeted by SCP training) [13]; addressing
hyperkinetic behavior by means of training sensorimotor
rhythm [14]. Application of these standard neurofeedback
protocols in ADHD have most consistently resulted in clini-
cal benefit in children with ADHD, whereas application of
other neurofeedback protocols has yielded more variable and
mixed results [5, 8]. A second issue with currently available
neurofeedback RCTs is that several studies deviated from
their initial clinical trials register, with samples ranging from
34% [15] to 60% [16, 17] smaller than their preregistered
sample size. This raises the likelihood of over-interpreting
results from these studies, which are insufficiently powered.
This issue is addressed using meta-analyses since effects are
combined across studies, resulting in increased statistical
power.
A third issue concerns the specificity of NF treatment
effects. While NF has been shown to be beneficial for the
treatment of ADHD symptoms, it remains a debate whether
behavioral improvements are the result of specific aspects
of the NF treatment such as the style of training, or active
learning of control over their brain state that is then gen-
eralized to daily life or whether non-specific treatment
effects such as unconditional positive regard of the thera-
pist, positive expectation of change, or repeated practice of
sitting at a computer for increasing lengths of time leads
to behavioral change. To control these non-specific or pla-
cebo effects, double-blind placebo-controlled studies are
often requested—comparable to what is considered as gold
standard in drug research. However, in regard to NF, there
are methodical and ethical issues to consider which have led
to the development of control conditions such as cognitive
training or EMG biofeedback and assessments for placebo
factors via evaluation scales [18, 19]. Though it is known
that placebo effects may last over longer periods [20], it
seems unlikely that they grow larger over time. Hence focus-
ing on longer-term outcomes of NF may also help to clarify
the placebo/specific vs. non-specific issue.
Two recent meta-analyses on the acute efficacy of neu-
rofeedback for children with ADHD published by the Euro-
pean ADHD Guidelines Group (EAGG) have used the inter-
esting concept of most-proximal (e.g. least blinded, often
parent ratings) versus probably blinded measures (most often
teacher ratings), assuming that the probably blinded meas-
ures (i.e., teacher ratings) are less susceptible to expecta-
tion/non-specific effects and, therefore, more valid [8, 11].
However, this approach has limitations. For example, par-
ent–teacher correlations on behavior rating scales are only
modestly correlated (ranging from 0.23 to 0.49) [21, 22],
suggesting different aspects of the disorder may be detected
by different raters or in different settings. Furthermore, in a
large candidate gene study, parent-rated hyperactive–impul-
sive behaviors were significantly associated with candidate
gene pathways whereas teacher ratings were not [23]. Addi-
tionally, teacher-ratings are sensitive to effects of methylphe-
nidate [24], which could possibly skew the interpretation of
studies that randomize ADHD treatments against a methyl-
phenidate control, when primarily relying on teacher reports.
Finally, for investigating long-term effects, it may not be
advisable to rely on teacher ratings, since the child may have
more than one teacher over time, potentially compromising
the reliability of the rating.
A second limitation of the aforementioned meta-analyses
is the use of between-group effect sizes, which is a good
practice for compiling results from studies that used similar
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295European Child & Adolescent Psychiatry (2019) 28:293–305
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designs and control groups; comparing for example, psycho-
stimulants to placebo. However, the utility of this method for
studying results across neurofeedback studies, with various
kinds of control groups (ranging from waiting lists, cogni-
tive training to medication), is more challenging. Therefore,
while between-group effect sizes are useful for controlling
for non-specific effects of treatment, they can miss clinical
effects of neurofeedback that are masked by the active or
semi-active control conditions, thus warranting the use of a
within-group effect-size approach, for example as used by
Arns etal. [7], or separately analyze the results for active vs.
semi-active control groups.
To address the above concerns, we have conducted a
systematic review and meta-analysis of the post-treatment
follow-up period of randomized EEG NF studies among
children and adolescents with ADHD. Methodologically,
we (1) used within-group effect sizes to address the issue
of different control groups; (2) used between-group effect
sizes to control for non-specific effects of treatment; (3)
applied a meta-analytical approach to address the issue of
underpowered studies; and (4) focused on the sustainability
of treatment effects by looking specifically at the follow-up
(FU) period (i.e., pre-FU, post-FU time points), which will
provide information regarding the plausibility of sustainable
NF effects, relative to other treatments, in ADHD.
Method
Study selection
The protocol of this meta-analysis was not preregistered.
A literature search was conducted up to 29th of Novem-
ber 2017 via PubMed and Scopus by author JVD, look-
ing for studies investigating Neurofeedback or EEG Bio-
feedback in ADHD using combinations of the following
keywords: ‘Neurofeedback’, ‘EEG Biofeedback’, ‘Neu-
rotherapy’, ‘SCP’ OR ‘Slow Cortical Potentials’ AND
‘ADHD’, ‘ADD’, ‘Attention Deficit’ OR ‘Attention Deficit
Hyperactivity Disorder’. Furthermore, prior meta-analyses
and systematic review reference lists were inspected for
potentially missed studies [7, 8, 10, 11]. After exclusion of
duplicate publications, abstracts were screened for inclu-
sion criteria first by author HH and then by a research
assistant to prevent missing studies. Studies that remained
of interest were then screened based on their full text by
JVD. Inclusion criteria were: (1) randomized controlled
EEG neurofeedback trials published in peer-reviewed
journals; (2) primary diagnosis of ADHD; (3) mean child
age<18years old; (4) available data at a follow-up (FU)
time point for 2 to 12months post-treatment; (5) stand-
ardized mean and standard deviations (SD) for all three
assessments (pre, post, and FU) for at least one of the
following domains had to be available: inattention, hyper-
activity, or hyperactivity/impulsivity ratings from a DSM-
IV/5-based rating scale (these values were taken based on
availability with parental ratings taking priority, then self-
ratings and lastly teacher ratings); (6) publication avail-
able in English; (7) total study sample larger than N=10;
8) less than 50% of participants began or stopped taking
medication between post and FU assessments.
In most of the studies, ‘standard’ neurofeedback protocols
[5] were used, i.e., theta/beta and theta/SMR (sensorimotor
rhythm) training (defined as a down-training of theta and
up-training of beta and SMR, respectively) and slow corti-
cal potential training (SCP) training (addressing modulation
of positive and negative SCPs), for details see Table1 and
Supplementary Figure S-2. Exceptions were the studies of
Arnold etal. [25] and Bink etal. [26] which targeted more
EEG frequency bands (theta, alpha, SMR, and beta), and a
sensitivity analysis was conducted to separately assess the
effects for standard protocols. When the means and SDs
from a given study were not available, or it was unclear if
planned follow-up measurements were published, this infor-
mation was requested via email from the authors. If authors
did not respond or did not provide the missing information,
and if there was not sufficient information available based
on the publication, the study was excluded from the meta-
analysis. Studies were additionally screened for duplicate
data based on author, publication year, participant numbers
and trial registration number (if available). When possible
duplicate data was found, the authors were contacted to
clarify whether the data sets were independent.
Data extraction/outcome measures
Data were first extracted by JVD and checked by HH. The
following pre-, post- and FU-assessment measures were
extracted from the included studies:
1. Demographic and clinical data: age (mean and standard
deviation), medication use, ADHD subtype.
2. Experimental procedure: NF method, control method,
feedback electrode, average number of sessions, session
length.
3. Outcome measures:
Symptom domains: Assessed from parent report with
a validated ADHD rating scale (e.g., DSM-IV rating
scale [27], Conners [28], Barkley [29], FBB-HKS [30],
SWAN [31])
(i) Inattention
(ii) Hyperactivity/impulsivity (if no combined
measure was available, the hyperactivity score
was used).
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296 European Child & Adolescent Psychiatry (2019) 28:293–305
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Table 1 Characteristics of included studies
Study or subgroup Year N (FU) Age Treatment FU
(months)
Assessment
instrument
Medicated/
total NMedication
dosagea
Neurofeedback
Heinrich etal. [36] 2004 13 11.1±1.6 SCP (Cz); 25 sessions of 50min 3 FBB-HKS 6/13 No change
Gevensleben etal. [52] 2010 38 9.9±1.3 SCP+theta (4–8Hz)/beta (13–20Hz); Cz; 36 sessions of 50min 6 FBB-HKS 0/38 No change
Arnold etal. [25] 2013 25 9.0±1.5 Theta/alpha↓; beta/SMR↑; Cz; 40 sessions of 45min 2 Conners DSM 7/25 Increased
Li etal. [39] 2013 31 10.8±2.6 MPH (pre)+NF; theta (4–8Hz)/SMR (12–15Hz); electrode NR;40 ses-
sions of 25–30min
6 ADHD RS-IV 31/31 Decreased
Meisel etal. [37] 2013 12 9.5±1.8 Theta (4–7Hz)/beta 15–20Hz); Cz or FCz; 40 session of 30min 2 ADHD RS-IV 2/12 Increased
Steiner etal. [34] 2014 34 8.4±1.1 Theta (4–8Hz)/SMR (12–15Hz); electrode NR; 40 sessions of 45min 6 Conners 27/34 Maintained
Christiansenb2014 18 8.7±1.4 SCP; Cz; 30 sessions of 50min 6 Conners DSM 1/18 Decreased
Bink etal. [26] 2016 41 15.8±3.3 TAU+NF; theta/alpha (4–7, 8–11Hz) ↓, SMR (13–15Hz) ↑, beta/
gamma (22–36Hz) ↓; Cz; 40 sessions of 30min
12 ADHD RS-IV
(self-report)
19/41 NR
Duric etal. [38] 2017 24 11.3±2.8 Theta (4–7Hz)/beta (16–20Hz); Cz; 30 sessions of 40min 6 Barkley 0/24 No change
Gelade etal. [35] 2017 20 9.8±1.9 Theta (4–8Hz)/beta (13–20Hz); Cz; 30 sessions of 45min 6 SWA N 0/20 No change
Control conditions
Gevensleben etal. [52] 2010 23 9.4±1.1 Attention training; 36 sessions of 50min 6 FBB-HKS 0/23 No change
Arnold etal. [25] 2013 11 8.7±2.1 Sham neurofeedback; 40 sessions of 45min 2 Conners DSM 0/11 No change
Li etal. [39] 2013 29 10.4±2.9 MPH (pre)+non-feedback attention training 40 sessions of 25–30min 6 ADHD RS-IV 29/29 Maintained
Meisel etal. [37] 2013 11 8.9±1.5 MPH (inferior dosage: 1mg/kg/day) 2 ADHD RS-IV 11/11 No change
Steiner etal. [34] CT 2014 34 8.9±1.0 Cognitive training; 40 sessions of 45min 6 Conners 14/34 Increased
Steiner etal. [34] WL 2014 36 8.4±1.1 Wait list 6 Conners 20/36 Increased
Christiansenb2014 21 8.9±1.2 Self-management; 30 sessions of 50min 6 Conners DSM 6/21 Increased
Bink etal. [26] 2016 19 16.2±3.4 TAU 12 ADHD RS-IV
(self-report)
12/19 NR
Duric etal. [38] 2017 28 10.8±2.4 MPH (1mg/kg/day; range: 20 to 60 mg) 6 Barkley 29/29 No change
Gelade etal. [35] MPH 2017 21 9.0±1.2 MPH (5–20mg daily) 6 SWA N 21/21 NR
Gelade etal. [35] PA 2017 17 9.6±1.8 Physical activity training; 28 sessions of 30min 6 SWA N 0/17 No change
For neurofeedback (NF) protocols, frequency bands and feedback electrodes are listed. Parent ratings were considered (except for Bink etal. [26] which used self-reports)
SCP slow cortical potential, SMR sensorimotor rhythm, MPH methylphenidate, PA physical activity, FBB-HKS German ADHD rating scale for parents, ADHD RS-IV ADHD Rating Scale-IV,
Conners Conners questionnaire subscale, Conners DSM DSM subscale within the Conners questionnaire; SWAN strengths and weaknesses of ADHD symptoms and Normal Behavior Scale, NR
not reported
a For more study details see Table S-4
b Unpublished data from Christiansen etal. [40]
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297European Child & Adolescent Psychiatry (2019) 28:293–305
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These measures were used as treatment endpoints at post-
treatment and FU relative to baseline values. Additionally,
the change from post-treatment to FU was assessed to deter-
mine if changes occurred after the treatment had stopped.
Meta‑analysis
A random effects model (due to inherent heterogeneity
between studies) and the inverse variance statistical method
was used to calculate the standardized mean difference
(SMD), 95% confidence intervals, and χ2 statistic using
RevMan version 5.3 [32]. Within-group and between-group
analyses were conducted for the following time points using
the means and standard deviations provided in the papers or
by the authors: (1) pre- and post-treatment; (2) pre-treatment
and follow-up; (3) post-treatment and follow-up. Within-
group analyses used the values as presented in the papers (no
additional calculation was necessary). Between-group means
were calculated by subtracting the mean of the second time
point from the mean of the first time point (ex. pre-treatment
minus post-treatment, pre-treatment minus FU-treatment,
post-treatment minus FU-treatment). The standard devia-
tion of the first point was used for analysis.
Although active treatment effects are not the main focus
of this paper, the control conditions were analyzed as a
whole and assessed using two sub-analyses (non-active and
active control conditions) to provide a frame of reference
for the effects of neurofeedback against different type of
controls. Due to the diversity of the control conditions, we
chose to separate them as ‘active’ (proven to have a clinical
effect in the treatment of ADHD: methylphenidate and self-
management training) and ‘non-active’ (all conditions that
do not classify as active). For a more detailed explanation
of these groupings see Table S-2 in the supplement. See
Tables S-5 and S-6 for values used. When the χ2 statistic of
a sample (Qt) was significant (p<0.05)—indicating that
the variance among effect sizes is greater than expected by
sampling error—studies were assessed for possible heteroge-
neity causes and the resulting studies were omitted from the
meta-analysis, for example based on the type of treatment
(separating active and non-active conditions in the control
groups). Active treatments were defined as medication or
psychotherapy (self-management) that was started system-
atically after pre-treatment assessment. Additionally, a sen-
sitivity analysis was conducted including only studies that
used standard NF protocols (theta/beta, theta/SMR, or SCP).
To assess publication bias, MetaWin version 2.1 [33] was
used to calculate the fail-safe number (Rosenthal’s method:
a<0.05).
Results
A total of ten studies met inclusion criteria for at least one
of the parameters and conditions, resulting in ten studies in
the NF arm and nine studies in the control arm (two control
studies had two control groups [34, 35]). See Figure S-1
for the Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRISMA) inclusion flow diagram and
Table1 for characteristics of included studies. The PRISMA
checklist is available in the supplementary material (Table
S-1). The supplementary material has a complete list of
inclusions (Table S-4) and exclusions (Table S-3). Included
studies resulted in a total of 506 participants with ADHD
(256 neurofeedback, 250 control). Follow-up time periods
were 2months (K=2), 3months (K=1), 6months (K=6)
and 12months (K=1).
The control group from Heinrich etal. [36] was excluded
because most of the controls began psychotherapy between
post and FU (personal communication with first author). The
2-month FU time point from the Meisel etal. [37] study
was included instead of the 6-month FU because over 50%
of their NF participants began medication between post-
and 6-month FU measurements while only two participants
started taking medication between post and 2-month FU. The
combined NF+MPH arm of Duric etal. [38] was excluded
since the NF treatment was accompanied by another active
treatment, which did not allow differentiation of treatment
effects; this differed from other studies in which NF children
could receive medication if they had been already medicated
prior to study participation, ensuring that the baseline meas-
urements already included medication effects. The supple-
mentary analysis was used from Gelade etal. [35] instead
of the primary analysis to account for participant drop-out
and medications change. For the majority of the studies, data
were available for participants who completed assessments
at all three time points (pre-, post-, FU) with the exception
of Li etal. [39], in which drop-out from baseline to FU were
3.13% (N=1) for the NF group and 9.38% (N=3) for the
control group.
Regarding medication change for included studies, the
number of participants who began or stopped taking med-
ication did not change over time for most of the studies,
with the exception of four [25, 26, 37, 40]. In summary: of
the total NF participants three stopped taking medication
[pre-post (N=2), post-FU (N=1)], while nine began tak-
ing medication [pre-post (N=1), post-FU (N=8)]; for the
control group only one participant stopped taking medica-
tion from post to FU time point. Dosage was allowed to
be changed in five studies (see Table1); however, dosage
change was variable with some groups maintaining (one NF,
one control), decreasing (two NF) or increasing (two NF,
three control) dosage. See Table S-4 for details.
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298 European Child & Adolescent Psychiatry (2019) 28:293–305
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Within‑group analyses
Inattention
Forest plots and results for inattention are presented in
Fig.1; Bar plots in Figure S-3. The test for heterogeneity
was not significant for NF at pre-post (χ2=9.69, df=9,
n.s.) or pre-FU (χ2=12.37, df= 9, n.s.), while controls
did display significant heterogeneity for both pre-post
(χ2=27.95, df=10, p<0.05) and pre-FU (χ2=29.60,
df=10, p<0.05) when all controls were included. When
considering non-active controls only, heterogeneity was no
longer significant for the pre-post measurement (χ2=6.72,
df=6, n.s.), but remained significant for the pre-FU meas-
urement (χ2=14.02, df=6, p<0.05). When only active
controls were included, pre-post heterogeneity remained
significant (χ2= 10.12, df = 3, p < 0.05) while pre-FU
(χ2=0.48, df=3, n.s.) was not significant. These results
suggest that when heterogeneity is significant for controls,
it will be useful to examine SMDs for active and non-active
controls separately, which will be done for the remainder
of the paper. This reduces the number of studies examined,
however, and caution will be used when interpreting the
results. Heterogeneity was non-significant for all groups for
the post-FU measurement: NF (χ2=2.29, df=9, n.s.); non-
active (χ2=4.05, df=6, n.s.); active (χ2=7.40, df=3, n.s.).
NF yielded a significant medium effect size (SMD=0.64;
95% CI 0.45, 0.82) for the change from the pre- to post-
treatment measurements and a significant large effect size
(SMD=0.80; 95% CI 0.58, 1.01) for the change from pre-
to FU measurement; however, post-treatment to FU was
not significant (SMD=0.14; 95% CI − 0.03, 0.31). For
non-active controls, a small, significant effect for pre-post
(SMD=0.28; 95% CI 0.05, 0.51) was found but the small
effect at pre-FU was no longer significant (SMD=0.29;
95% CI − 0.04, 0.63). When looking at only active controls,
there were large, significant effect sizes at both pre-post (sig-
nificant heterogeneity) (SMD=1.08; 95% CI 0.45, 1.72)
and pre-FU (non-significant heterogeneity) (SMD=1.06;
95% CI 0.73, 1.39). Post-treatment to FU was not significant
for either control group. The fail-safe numbers for NF were:
pre-post (156.0), pre-FU (190.7). For the control conditions,
the fail-safe numbers were: 1. non-active controls: pre-post
(11.2), pre-FU (1.1); 2. active controls: pre-post (13.5), pre-
FU (55.2).
Hyperactivity/impulsivity
Forest plots and results for hyperactivity/impulsivity are
presented in Fig.2; Bar plots in Figure S-3. The test for
heterogeneity was not significant for any of the hyperactiv-
ity/impulsivity measurements, indicating that the variance
of SMD was not large enough to be attributed to sampling
error only (see Fig.2). For comparability to the inatten-
tion domain, the active and non-active control groups are
reported separately.
For NF, a significant medium effect size (SMD=0.50;
95% CI 0.33, 0.68) was found for the pre-post measurement
and a medium effect size (SMD=0.61; 95% CI 0.43, 0.79)
for the pre-FU measurement; the post-FU measurement was
not significant (SMD=0.11; 95% CI − 0.06, 0.28).
Analysis of non-active control groups indicated that none
of the measurements (pre-post, pre-FU, post-FU) were sig-
nificant. When only active controls were considered, there
were significant medium effect sizes for both pre-post
(SMD=0.74; 95% CI 0.41, 1.06) and pre-FU (SMD=0.67;
95% CI 0.35, 0.99). For both control analyses, post-FU was
not significant. The fail-safe numbers for NF were: pre-post
(107.6), pre-FU (163.4). For the controls, the fail-safe num-
bers were: 1. non-active controls: pre-post (0), pre-FU (0);
2. active controls: pre-post (25), pre-FU (18.4).
Between‑group meta‑analysis
Forest plots and results for inattention and hyperactivity/
impulsivity are presented in Fig.3.
Inattention
The test for heterogeneity was significant when including all
studies at pre-post (χ2=30.60, df=10, p<0.05) and signif-
icant at pre-FU (χ2=33.27, df=10, p<0.001). Considering
only trials with non-active control conditions, heterogeneity
was not significant for the pre-post measurement (χ2=7.83,
df=6, n.s.) or the pre-FU measurement (χ2=7.48, df=6,
n.s.). For active controls, heterogeneity was not significant
for pre-post (χ2=5.00, df=3, n.s.) or for pre-FU (χ2=7.05,
df=3, n.s.).
When including only studies with non-active con-
trol conditions, a significant small effect size for pre-post
(SMD=0.38; 95% CI 0.14, 0.61) and a medium effect size
for pre-FU (SMD=0.57; 95% CI 0.34, 0.81) were observed
favoring neurofeedback. When only active controls were
included, a pre-post effect size favoring active controls was
significant (SMD=− 0.44; 95% CI − 0.86, − 0.02) but at
pre-FU it was no longer significant. Post-training to FU was
not significant for either analysis.
Hyperactivity/impulsivity
The test for heterogeneity was not significant for any of the
hyperactivity/impulsivity measurements, indicating that
the variance of SMD was not large enough to be attributed
to sampling error only. The between-group analysis of all
control groups resulted in a significant small effect size
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299European Child & Adolescent Psychiatry (2019) 28:293–305
1 3
favoring NF (SMD=0.32; 95% CI 0.15, 0.49) at pre-FU,
pre-post was not significant. When including only non-
active control groups (done for comparison with inatten-
tion, not due to heterogeneity), results favored NF with a
significant small effect for the pre-post (SMD=0.25; 95%
CI 0.05, 0.45) measurement and a small effect for pre-FU
(SMD=0.39; 95% CI 0.19, 0.59). Including only active
controls resulted in no significant findings for either pre-
post or pre-FU. For both control analyses post-FU was not
significant; however, post-FU did show a trend toward sig-
nificance favoring neurofeedback over all control groups
(p=0.08; SMD=0.15; 95% CI − 0.02, 0.32].
Sensitivity meta‑analysis: ‘standard’ NF training
See Tables S-7 and S-8 for details regarding this analysis.
Inattention
The tests for heterogeneity as well as effect sizes were simi-
lar to those seen in the within-group and between-group
analyses including all studies, with slightly stronger effect
sizes seen for the sensitivity analysis regarding pre-post and
pre-FU time points (increase in SMD ranging from 0.01 to
0.14), however, with small changes in both directions for
post-FU (change ranging from − 0.02 decrease to 0.02
increase).
Hyperactivity/impulsivity
The tests for heterogeneity as well as effect sizes were simi-
lar to those seen in the within-group and between-group
analyses including all participants (decrease of 0.01 SMD
to increases in SMD up to 0.02).
Discussion
This meta-analysis investigated the effects of neurofeedback
and control conditions directly after treatment and during a
follow-up period (2–12months post-treatment), in which
Fig. 1 Forest Plot of within-group analysis for inattention param-
eter. Total standardized mean difference (SMD) with 95% confidence
interval, overall effect, and heterogeneity are reported. Due to signifi-
cant heterogeneity in the initial control analysis, additional analyses
examining non-active and active controls separately were included.
Pre-Post refers to the difference in means at pre- and post-measure-
ment, and similarly for pre-FU and post-FU
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300 European Child & Adolescent Psychiatry (2019) 28:293–305
1 3
no additional neurofeedback sessions or booster sessions
were performed. For neurofeedback, a medium SMD for
inattention and hyperactivity/impulsivity were found post-
treatment, which changed to a large SMD for inattention and
remained a medium SMD for hyperactivity/impulsivity at
follow-up (relative to baseline). Non-active control groups
yielded a significant small effect size at pre-post that was
no longer significant at FU for inattention, and there were
no significant effects found for the hyperactivity/impulsivity
domain. Active controls had significant large effect sizes for
inattention and medium effect sizes for hyperactivity at both
pre-post and pre-FU. The between-group analysis was found
to significantly favor NF over non-active control groups for
both inattention and hyperactivity/impulsivity at pre-post
(small effect sizes) and pre-FU (small to medium effect
sizes). Active controls were found to be significantly supe-
rior regarding inattention at pre-post but no longer at follow-
up. In summary, focusing on the pre-treatment to follow-up
results, neurofeedback was superior to non-active control
groups and similarly effective for inattention and hyper-
activity/impulsivity compared to active treatments. These
findings provide evidence that there are sustained clinical
benefits after neurofeedback and active treatments over an
average 6–12month follow-up period, whereas effects of
non-active control groups are no longer significant at FU.
The significant improvement in symptoms at FU for both
inattention and hyperactivity–impulsivity in the neurofeed-
back conditions indicates that NF results in lasting effects for
approximately 6months and potentially up to 1year. Com-
parison of effect-sizes between neurofeedback and active
control groups showed overlapping confidence intervals
(also visualized in Figure S-3), and no significant difference
in the between-group analysis, suggesting NF and active
controls having similar effects in the respective FU period;
however, this finding needs to be viewed with caution due
to the small number of studies in the active controls groups
(K=4). The tendency in the within-group analyses for a
small further improvement in the NF group (inattention:
Fig. 2 Forest Plot of within-group analysis for hyperactivity/
impulsivity parameter. Total standardized mean difference (SMD)
with 95% confidence interval, overall effect, and heterogeneity are
reported. Analysis of the control condition separately for non-active
and active controls was conducted for comparability to the inattention
parameter analysis. Pre-Post refers to the difference in means at pre-
and post-measurement, and similarly for pre-FU and post-FU
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301European Child & Adolescent Psychiatry (2019) 28:293–305
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SMD=0.14; hyperactivity/impulsivity: SMD=0.11) from
post-treatment to FU, albeit not significant, is in line with the
further improvement effects seen after two-year follow-up
[6, 41]. This tendency was non-existent and moves primarily
in the opposite direction (SMD=− 0.1 to 0) for the active
and non-active controls (see Figure S-3). Accordingly, post-
FU results of the between-group analyses were slightly in
favor of NF (SMDs between 0.1 and 0.2, with a statistical
trend for hyperactivity/impulsivity) suggesting that effects
may become significant with further studies available. In any
case, current results do support the sustainability of the clin-
ical benefits of neurofeedback after cessation of treatment.
Regarding the use of medication, we only focused on
follow-up periods of 2–12months, and effects for active
treatments demonstrated sustained clinical benefit for these
periods (in which children were actively taking medication).
This is line with previous studies which demonstrated clini-
cal benefits of psychostimulant medication at 12months [42]
and 24months [3, 4]; however, the clinical benefits of psy-
chostimulant medication (when naturalistically assessed) are
not empirically supported for longer follow-up periods of
2–8years [43–45]. Despite this, recent epidemiological stud-
ies have found that continued controlled medication intake
can have positive benefits for patients with ADHD [46–48].
However, Swanson etal. [49] reported that at 12–16-year
follow-up of long-term medication use (both consistent and
inconsistent use over this time period) was not associated
with reduced symptom severity, but it was associated with
decreased adult height. These contrasting findings suggest
that while medication may have some long-term benefits,
the adherence of medication intake may be problematic and
long-term medication exposure may be related to potential
Fig. 3 Forest Plot of between-group analysis for inattention and
hyperactivity/impulsivity parameter. Total standardized mean differ-
ence (SMD) with 95% confidence interval, overall effect, and hetero-
geneity are reported. Analysis of the studies separately for non-active
and active controls was conducted for comparability to the inattention
parameter analysis. Pre-Post refers to the difference in means at pre-
and post-measurement, and similarly for pre-FU and post-FU
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302 European Child & Adolescent Psychiatry (2019) 28:293–305
1 3
physical side effects. The follow-up periods used in our
study were probably not long enough to demonstrate the
decreased efficacy of medication as reported in the above
studies [43–45], and since these studies were controlled dur-
ing the FU periods and not naturalistic, it is likely that medi-
cation adherence was high. While NF follow-up treatment
effects have not been studied for such long-time intervals,
the short-term clinical effects of NF appear to be sustained
(without continued training) for an average 2–12month FU,
suggesting potential promise of this approach for sustained
clinical benefit in ADHD.
Interestingly, a strong point of our findings is that, despite
past heterogeneity in the application of neurofeedback pro-
tocols [5], most of the studies included in this paper used
‘standard NF protocols’, the exceptions being Arnold etal.
[25] and Bink etal. [26]. Additionally, Arnold etal. [25]
used an ‘entertaining’ NF protocol that may not be compat-
ible with principles of learning theory. However, the use of
uniform protocols by most of the papers is also evidenced by
the absence of significant heterogeneity. Considering only
standard protocols, we found that the results supporting NF
over non-active controls are slightly strengthened when only
including standard NF protocols. This finding supports the
continued use of these protocols for future NF studies. Addi-
tionally, our significant findings are in line with those of
Cortese etal. [8] who demonstrated significant between-
group effects even for ‘probably blinded’ ratings (teacher
ratings) at post-treatment when only standard NF protocols
for total ADHD and inattention symptoms were considered.
When considering placebo effects of NF training, they
may still operate at follow-up but we are not aware of ten-
dencies for further improvements of placebo effects for
other treatments of other disorders. NF treatment is found
to be superior to non-active controls in this analysis, and
the effects of non-active controls were not significant at FU,
neither for inattention nor hyperactivity/impulsivity. These
findings support the idea that NF does indeed have a differ-
ent, specific effect due to its actual training and not simply
due to the non-specific or placebo effects related to the set-
ting, the therapist–patient relationship or expectations. To
verify this more RCT’s using controls that closely mimic
NF training are required.
Possible limitations andopen questions
Results of the current meta-analysis should be interpreted in
line with its limitations.
While some of the studies included here do simultane-
ously use medication and NF (which may influence the
results), the number of participants taking medication did
not change for most studies, (only in two studies the NF
participants began taking medication between pre- and FU
measurement [25, 37]), suggesting that medication changes
are not an explanation for the effects found here. Addition-
ally, while dosage was allowed to be changed in five of these
studies, two NF groups decreased dosage and two increased
dosage while three control groups increased dosage. These
changes should not bias the data in favor of the NF, but
rather suggest that the NF effects may be slightly masked by
the dosage increase seen in the control groups.
When comparing the between-group effect sizes for pre-
to post-treatment between this study (Fig.3) and the latest
EAGG meta-analysis by Cortese etal. [8], a small effect
for inattention (SMD=0.36) and hyperactivity/impulsivity
(SMD=0.26) was found. In the current study, SMD’s are
lower when including all controls (inattention: SMD=0.09;
hyperactivity/impulsivity: SMD=0.16) and nearly identi-
cal when considering only non-active controls (inattention:
SMD=0.38; hyperactivity/impulsivity SMD=0.25). This
indicates that the studies we have included are representa-
tive and not biased towards more effective studies (opposite
file-drawer problem, i.e. higher likelihood that positive stud-
ies are more often published). But, while we attempted to
address the file drawer problem by assessing the fail-safe
numbers for our analysis, a potential reporting bias cannot be
definitively excluded. However, our finding of much larger
fail-safe numbers for NF (generally≥100) than for control
conditions (active<56, non-active<12) do suggest that
the NF condition results are probably not influenced by a
reporting bias.
Inherently when investigating FU periods, there are addi-
tional limitations involved including completer bias (a bias
is introduced because of the factors that cause a person to be
involved during a FU time-point) and the lack of an intention
to treat analysis (ITT) available for studies using a FU time
point. This type of analysis is considered more conservative
than the per protocol analyses found in the majority of the
papers included here. We chose specifically to not run a risk
of bias assessment because this model does not work well for
NF studies since it relies heavily on blinding, which poses a
problem since most NF studies were not blinded.
As already mentioned, more carefully designed RCTs
with longer follow-up time periods are needed before defi-
nite conclusions can be drawn. However, the meta-analysis
of Cortese etal. [8] on the acute effects of NF was comprised
of studies with a comparable design (“well-controlled”) and
about the same number of participants (ca. 500). Therefore,
this meta-analysis on follow-up effects at the present time
may also allow us to derive the first relevant conclusions
about the lasting effects of NF treatment.
Future research should focus on addressing both post- and
FU-effects of NF and other non-pharmacological treatments
for ADHD. Additionally, based on the current findings of
within-group effects, placebo or non-specific treatment
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303European Child & Adolescent Psychiatry (2019) 28:293–305
1 3
effects in NF cannot be ruled out and better controls for these
effects should continue to be investigated. Finally, it should
be noted that the specificity of neurofeedback effects cannot
only be derived from RCTs and a meta-analysis of RCTs
investigating behavioral outcome. Associations between the
behavioral and neurophysiological level (e.g., neuroregula-
tion skills) have already been documented with respect to the
post-treatment outcome [17, 50, 51], but are largely missing
from the literature that has conducted FU measurements.
These parameters provide an additional method to evaluate
treatment effects and should be included in future research
of long-term follow-ups.
Conclusion
Our meta-analytic results of NF treatment follow-up sug-
gest that there are sustained symptom reductions over time
in comparison with non-active control conditions. The
improvements seen here are comparable to active treat-
ments (including methylphenidate) at a short-term FU of
2–12months. As such, NF can be considered a non-phar-
macological treatment option for ADHD with evidence of
treatment effects that are sustained when treatment is com-
pleted and withdrawn. Future research should focus on the
comparison of standardized NF treatments with standard-
ized control treatments, controlling for unspecific effects
and changes in additional treatments (medication). Given
the need for additional treatments for ADHD with long-term
outcomes, clinical trials of NF should aim for primary out-
come measures that compare pre-treatment with systematic
long-term follow-up behavioral ratings, to address sustain-
ability of effects.
Acknowledgements The authors recognize Dr. Nezla Duric, Dr. Hanna
Christiansen, Dr. Naomi Steiner and Dr. L. Eugene Arnold for provid-
ing additional information that made inclusion of their data in this
meta-analysis possible.
Funding No funding was provided for this project.
Compliance with ethical standards
Conflict of interest MA reports options from Brain Resource (Sydney,
Australia); is director and owner of Research Institute Brainclinics, a
minority shareholder in neuroCare Group (Munich, Germany), and a
co-inventor on 4 patent applications (A61B5/0402; US2007/0299323,
A1; WO2010/139361 A1; WO2017/099603 A1) related to EEG,
neuromodulation and psychophysiology, but does not own these nor
receives any proceeds related to these patents; Research Institute
Brainclinics received research funding from Brain Resource (Sydney,
Australia) and neuroCare Group (Munich, Germany), and equipment
support from Deymed, neuroConn and Magventure; however, data
analyses and writing of this manuscript were unconstrained. US has
been paid for public speaking by Novartis, Medice, neuroCare, the
German Society for Biofeedback, and Akademie König und Müller.
All other authors have indicated no potential conflicts of interest rel-
evant to this article to disclose.
Open Access This article is distributed under the terms of the Crea-
tive Commons Attribution 4.0 International License (http://creat iveco
mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribu-
tion, and reproduction in any medium, provided you give appropriate
credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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