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DOI: 10.1542/peds.2013-2059
; originally published online February 17, 2014;Pediatrics Ellen C. Perrin
Naomi J. Steiner, Elizabeth C. Frenette, Kirsten M. Rene, Robert T. Brennan and
Randomized Control Trial
In-School Neurofeedback Training for ADHD: Sustained Improvements From a
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located on the World Wide Web at:
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of Pediatrics. All rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.
Boulevard, Elk Grove Village, Illinois, 60007. Copyright © 2014 by the American Academy
published, and trademarked by the American Academy of Pediatrics, 141 Northwest Point
publication, it has been published continuously since 1948. PEDIATRICS is owned,
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In-School Neurofeedback Training for ADHD: Sustained
Improvements From a Randomized Control Trial
WHAT’S KNOWN ON THIS SUBJECT: An estimated 9.5% of children
are diagnosed with attention-deficit/hyperactivity disorder
(ADHD), which affects academic and social outcomes. We
previously found significant improvements in ADHD symptoms
immediately after neurofeedback training at school.
WHAT THIS STUDY ADDS: This randomized controlled trial included
a large sample of elementary school students with ADHD who received
in-school computer attention training with neurofeedback or cognitive
training. Students who received neurofeedback were reported to have
fewer ADHD symptoms 6 months after the intervention.
abstract
OBJECTIVE: To evaluate sustained improvements 6 months after a 40-
session, in-school computer attention training intervention using
neurofeedback or cognitive training (CT) administered to 7- to 11-
year-olds with attention-deficit/hyperactivity disorder (ADHD).
METHODS: One hundred four children were randomly assigned to receive
neurofeedback, CT, or a control condition and were evaluated 6 months
postintervention. A 3-point growth model assessed change over time across
the conditions on the Conners 3–Parent Assessment Report (Conners 3-P),
the Behavior Rating Inventory of Executive Function Parent Form (BRIEF),
and a systematic double-blinded classroom observation (Behavioral
Observation of Students in Schools). Analysis of variance assessed
community-initiated changes in stimulant medication.
RESULTS: Parent response rates were 90% at the 6-month follow-up.
Six months postintervention, neurofeedback participants maintained
significant gains on Conners 3-P (Inattention effect size [ES] = 0.34,
Executive Functioning ES = 0.25, Hyperactivity/Impulsivity ES = 0.23) and
BRIEF subscales including the Global Executive Composite (ES = 0.31),
whichremainedsignificantly greater than gains found among children in
CT and control conditions. Children in the CT condition showed delayed
improvement over immediate postintervention ratings only on Conners 3-
P Executive Functioning (ES = 0.18) and 2 BRIEF subscales. At the 6-
month follow-up, neurofeedback participants maintained the same
stimulant medication dosage, whereas participants in both CT and
control conditions showed statistically and clinically significant increases
(9 mg [P=.002]and13mg[P,.001], respectively).
CONCLUSIONS: Neurofeedback participants made more prompt and
greater improvements in ADHD symptoms, which were sustained at the
6-month follow-up, than did CT participants or those in the control
group. This finding suggests that neurofeedback is a promising attention
training treatment for children with ADHD. Pediatrics 2014;133:483–
492
AUTHORS: Naomi J. Steiner, MD,
a
Elizabeth C. Frenette,
MPH,
a
Kirsten M. Rene, MA,
a
Robert T. Brennan, EdD,
b
and
Ellen C. Perrin, MD
a
a
The Floating Hospital for Children at Tufts Medical Center,
Department of Pediatrics, Boston, Massachusetts; and
b
Harvard
School of Public Health, Boston, Massachusetts
KEY WORDS
ADHD, neurofeedback, biofeedback, cognitive training, growth
model
ABBREVIATIONS
ADHD—attention-deficit/hyperactivity disorder
BOSS—Behavioral Observation of Students in Schools
BRIEF—Behavior Rating Inventory of Executive Function
CompAT—computer attention training
Conners 3-P—Conners 3–Parent Assessment Report
CT—cognitive training
RA—research assistant
Dr Steiner conceptualized and designed the study, drafted the
initial manuscript, and approved the final manuscript as
submitted. Ms Frenette and Ms Rene carried out the initial
analyses, reviewed and revised the manuscript, and approved
the final manuscript as submitted. Dr Brennan carried out the
growth model analyses, reviewed and revised the manuscript,
and approved the final manuscript as submitted.
This trial has been registered at www.clinicaltrials.gov
(identifier NCT01583829).
www.pediatrics.org/cgi/doi/10.1542/peds.2013-2059
doi:10.1542/peds.2013-2059
Accepted for publication Dec 18, 2013
Address correspondence to Naomi J. Steiner, MD, Floating
Hospital for Children at Tufts Medical Center, 800 Washington St,
Box 334, Boston, MA 02111. E-mail: nsteiner@tuftsmedicalcenter.
org
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).
Copyright © 2014 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE: The authors have indicated they have
no financial relationships relevant to this article to disclose.
FUNDING: All phases of this study were supported by an
Institute of Education Sciences grant (R305A090100).
POTENTIAL CONFLICT OF INTEREST: The authors have indicated
they have no potential conflicts of interest to disclose.
PEDIATRICS Volume 133, Number 3, March 2014 483
ARTICLE
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Attention-deficit/hyperactivity disorder
(ADHD) is a neurodevelopmental dis-
order with core symptoms of inatten-
tion, hyperactivity, and/or impulsivity
and has a prevalence of 9.5% for 4- to 17-
year-olds in the United States.
1
Execu-
tive functioning is typically impaired in
children with ADHD, affecting their ac-
ademic achievement.
2
Medication and
behavior therapy are both viable treat-
ment options for ADHD,
3
but they both
have limitations. These limitations,
along with the pervasiveness of ADHD
symptoms in school, highlight the im-
portance of researching alternative
treatments that can be implemented in
the classroom setting. Computer atten-
tion training (CompAT) is an umbrella
term used to describe many computer
interventions that appear to be effec-
tive
4
and that might be possible to im-
plement on a large scale in school.
Based on theories of operant condi-
tioning and brain plasticity, the goal of
CompAT interventions is to decrease
ADHD symptoms and improve executive
functioning skills. CompAT interventions
may provide sustainable benefits even
after the intervention is terminated
through its conditioning and general-
ization components. Two typesof CompAT
interventions were evaluated in the cur-
rent study: neurofeedback and cognitive
training (CT).
EEG patterns in children with ADHD have
shown more theta wave activity and
increased theta:beta ratio in the frontal
cortex, compared with children without
ADHD.
5–7
Beta Waves in the frontal
cortex are associated with sustaining
attention and thinking, whereas theta
waves are prevalent when drowsy or
daydreaming. However, other studies
have not confirmed the finding that
children with ADHD have elevated
theta:beta ratios when compared with
controls.
8,9
The authors of these stud-
ies hypothesized that children in control
conditions also have elevated theta:
beta ratios than has been observed in
the past, potentially due to decreased
sleep (among other factors), making
the 2 groups look more alike. When
training attention, neurofeedback pro-
vides children with immediate auditory
and visual feedback regarding their
level of attention during each exercise.
Changes are enabled because of brain
plasticity of the frontal brain, which
continues to develop throughout child-
hood and into early adulthood.
10
Neu-
rofeedback therefore trains users to
monitor and change their brainwave
patterns, leading to behavioral changes.
11
Some studies have found that neuro-
feedback can decrease symptoms of
ADHD,
12–17
including improved attention,
18
behavior,
19
and cognitive improvements
20
up to 6 months postintervention as well
as at 2 years postintervention.
21
How-
ever, the evidence for its sustainability
remains unclear, because there are
limited studies examining follow-up
data, and those that do have small
sample sizes or no control condition.
13–15
In contrast, CT uses specifically de-
signed exercises to train attention,
working memory, and impulsivity through
ongoing feedback to reinforce correct
responses. Several studies suggest that
CT improves performance on working
memory tasks and decreases inatten-
tiveness, hyperactivity, and disruptive
behaviors.
22–26
The largest such trial
included only 44 children diagnosed
with ADHD, ages 7 to 12 years, and re-
ported results 3 months after com-
pleting a 20-session intervention.
26
Gevensleben et al
18
examined neuro-
feedback and CT after 6 months and
found that improvements in the neuro-
feedback condition on parent-reported
behavior scales were significantly su-
perior and sustained compared with the
CT condition. Unfortunately, significant
attrition makes this study’s generaliz-
ability unclear. A recent meta-analysis
regarding nonpharmacologic inter-
ventions for ADHD concluded that in-
creased evidence is needed for both
neurofeedback and CT interventions
before they can be supported as
treatments for ADHD.
27
The current study is novel for several
reasons. The research team conducted
the first in-school translational efficacy
trial comparing neurofeedback, CT, and
control conditions. Previous studies
have mostly been conducted in labo-
ratories or in clinical settings. This ef-
ficacy trial targeted a precise age range
of children 7 to 11 years of age, as
opposed to previous studies that in-
cluded diverse developmental age
ranges. Many studies are smaller
without a control group and failed to
find group differences. Last, very few
studies reported follow-up results.
Pre- to postintervention, we found sig-
nificantly greater improvements in
ADHD symptoms, including attention
and executive functioning, among
neurofeedback participants compared
with the control and CT conditions.
28
In
the present article, we report outcomes
6 months after the conclusion of the in-
tervention. We hypothesized that partic-
ipants receiving neurofeedback would
maintain improvements in attention and
executive functioning compared with
control or CT conditions and that med-
ication dosage would remain stable.
METHODS
Participants
Students with ADHD who were attending
1 of 19 public elementary suburban or
urban schools in the Greater Boston
area were eligible to participate in the
randomized trial. Inclusion criteria in-
cluded the following: (1) child in second
or fourth grade, (2) clinical diagnosis of
ADHD made by the child’s clinician, and
(3) ability to speak and understand
English well enough to follow the pro-
tocol, although English was not neces-
sarily the participant’sfirst language.
Exclusion criteria included (1) a coex-
isting diagnosis of conduct disorder,
autism spectrum disorder, or other
484 STEINER et al at Harvard University on February 19, 2014pediatrics.aappublications.orgDownloaded from
serious mental illness (eg, psychosis)
and (2) an IQ measured by the Kaufman
Brief Intelligence Test ,80, to limit
confounding factors and requirements
of extensive amendments to the inter-
vention protocol that could affect stan-
dardized implementation. The study was
located in schools, and investigators
had no clinical responsibility for the
children’s medical care. Therefore,
children were included on the basis of
their clinician’s diagnosis of ADHD, and
were included regardless of whether
they were taking medications for ADHD.
Parents of all participants were in-
formed that they should continue to
adhere to scheduled clinician visits
and standard community treatments
(including counseling and medication
management) independent of study
participation, and medication use was
not suspended for treatments or as-
sessments. The study was approved by
the Tufts Medical Center Institutional
Review Board, and written informed
consent and child assent were obtained.
Enrollment of the first cohort occurred
from May to September 2009 and from
May to September 2010 for the second
cohort. All preintervention assessments
were conducted in October, and inter-
ventions were initiated in November of
each year. For each cohort, the research
coordinator balanced participants on the
basis of school district, gender, and medi-
cation status, and then assigned them via
a computer random number generator
into 3 conditions (neurofeedback, CT, and
control). Before enrollment, parents were
told their child would be randomly
assigned into 1 of these 3 conditions, and
were informed of their child’sgroup
status after assignments were made.
Interventions
Participants received in-school 45-
minute intervention sessions 3 times
per week, monitored by a trained re-
search assistant (RA), for 40 sessions
over 5 months. The same protocol was
used for both intervention conditions.
RAs received a standardized 2-week
training to administer neurofeedback
and CT, followed by a posttraining test
and direct observation assessments.
RAs filled out a standardized session
checklist for each child at every session
to monitor implementation fidelity.
The specific neurofeedback system used
(Play Attention, Unique Logic and Tech-
nology, Fletcher, NC) detects 2 frequency
ranges, 1 in the low-frequency theta
brainwave range (4–8 Hz) and another
in the high-frequency beta brainwave
range (12–15 Hz).
29
The brainwaves are
measured by an EEG sensor embedded
in a standard bicycle helmet centrally
located on the top of the skull, and 2
other EEG sensors one a grounding
sensorand the other a reference, on the
chin straps located bilaterally on the
mastoids. Through practice, partic-
ipants learn to manipulate the figures
on the screen, resulting in suppression
of theta and an increase in beta activity.
As the theta:beta ratio changes, an al-
gorithm is used so that participants
score points on the computer program
and learn how to improve attention on
the 6 different exercises.
The specificCTinterventionused(Cap-
tain’s Log, BrainTrain, North Chesterfield,
VA) comprises exercises that train dif-
ferent areas of cognition, which may be
designed into personalized exercise
protocols. The system is well designed
for large-scale delivery, because there is
automatic level advancement after each
exercise.
30
The standardized protocol
developed for this study is composed of
14 auditory and visual exercises tar-
geting areas of attention and working
memory. Each exercise is interactive
and lasts ∼5 minutes. Both systems are
commercially available.
Primary Outcome Measures
Outcome measures included parent
reports of ADHD symptoms and executive
functioning, medication use, and sys-
tematic classroom observations of
behavior. All outcome measures were
obtained pre- and postintervention, and
6 months later.
The Conners 3–Parent Assessment Re-
port (Conners 3-P; Multi-Health Sys-
tems Inc, North Tonawanda, NY) is a
validated and standardized instrument
to assess ADHD symptoms,
31
including
9 subscales comprising 2 summary
scales summed together as a Global
Index. The Behavior Rating Inventory of
Executive Function (BRIEF) (PAR Inc,
Lutz, FL) is a validated and standard-
ized instrument that assesses execu-
tive functioning,
32
including 8 subscales
comprising 2 indices summed together
in the Global Executive Composite. Both
parents, if available, completed the
Conners 3-P and BRIEF.
The Behavioral Observation of Students
in Schools (BOSS; Pearson Education,
Inc, New York, NY)
33
is a systematic
interval recording observation system
for coding classroom behavior and
reports on engagement (active or pas-
sive) and off-task behaviors (motor,
verbal, and passive). Data output from
observations are objective quantitative
assessments, which can help reduce
observer bias, and consist of raw data
as well as the percentage of intervals
the participant was recorded as en-
gaged or off-task. The BOSS has been
found to be reliable between observ-
ers,
34
to differentiate between children
with ADHD and their typically developing
peers,
35
and to be sensitive to treatment
effects.
36
The BOSS was completed 3
times at each time point (ie, before the
intervention, immediately after the in-
tervention, and 6 months after the in-
tervention) for all study participants by
trained RAs
37
who were unaware of the
participants’randomization conditions.
The participants were unaware that
they were being observed.
A Medication Tracking Questionnaire
was completed by the primary parent at
each time point to track medication
type, dosage, and history. No direct
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PEDIATRICS Volume 133, Number 3, March 2014 485
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consultation regarding medication was
discussed with parents, who were en-
couraged to continue their regularly
scheduled visits with their clinician.
Stimulant medications were converted
into methylphenidate equivalencies by
the research team to compare dosage
over time. The reliability of parent
reports was assessed by comparing
name and dosages of medication at
each time point. Ambiguous responses
were clarified by direct communication
with parents and clinicians.
Data Analysis
Analysis of variance was conducted to
assess baseline differences in de-
mographic data between randomiza-
tion conditions. Missing items within
multiitem scales were resolved by using
expectation maximization imputation,
38
which is an iterative imputation method
suitable for low-frequency missing data
and/or when SEs are not of primary
concern.
39
When a full questionnaire was
missing, it was dropped from the analy-
sis and addressed directly through the
analytic strategy described below. Be-
cause this study investigated whether
the 2 CompAT interventions are superior
to community treatment alone, and
whether neurofeedback is superior to CT,
this randomized controlled trial is con-
sidered a superiority trial and analyses
are presented with 1-tailed tests.
40–42
The central focus of these analyses was
to evaluate whether the observed
changes in core ADHD symptoms be-
tween the start and end of the treatment
period were sustained at the 6-month
follow-up. Changes in parent-reported
and classroom observation measures
were investigated by 3-point growth
models by using a multilevel approach
to assess change over the 3 time points
(preintervention, postintervention, and
6-month follow-up) to compare neuro-
feedback and CT with the control.
43–45
Our approach used all available data,
including the reports from 2 parents
when available at all 3 time points.
These models allow for the estimation
of reliability of measurement and
change within the overall estimation,
and can flexibly accommodate un-
balanced data, so a participant can be
included at a time point even if only 1
parent questionnaire was available at
any or all of the time points. For the
BOSS, 3 observations at all 3 time
points were used to estimate re-
liability.
46
This linear model estimates
the best-fitting line to the 3 time points.
Comparisons between neurofeedback
and CT were undertaken using mul-
tivariate general linear hypothesis
tests.
47
For ease in interpretation and
comparison with other studies, ap-
proximate effects sizes (expressed as
standardized mean differences, Cohen’sd)
were computed from the neurofeed-
back and CT coefficients from the
growth models; however, to the best of
our knowledge, no other study of Com-
pAT reports growth coefficients and,
furthermore, standard calculations do
not accommodate all of the parameters
estimated in a multilevel model.
48
All
growth models were estimated by using
HLM version 7.0.
42
All other analyses and
data treatment were conducted by us-
ing SYSTAT version 13.0.
49
Paired ttests were conducted to eval-
uate stimulant medication differences
in methylphenidate equivalencies within
randomization conditions between pre-
intervention and the 6-month follow-up.
An analysis of covariance was con-
ducted to evaluate medication dosage
differences among the randomization
conditions at 6-month follow-up, con-
trolling for preintervention stimulant
medication dosages.
RESULTS
Of the 104 children in the study, 102
completed the intervention. Of these,
only 4 did not complete the 6-month
follow-up assessment (n= 98) (Fig 1).
The mean response rates of the parent
questionnaires for pre- and postinter-
vention data were 94% for the primary
parent and 77% for the secondary par-
ent. At the 6-month follow-up, response
rates were 90% for the primary parent
and 82% for the secondary parent. The
BOSS was completed 3 times for each
participant at preintervention, post-
intervention, and 6-month follow-up for
100% of participants. At baseline, 95% of
participants showed clinically signifi-
cant scores $65 on the Diagnostic and
Statistical Manual of Mental Disorders,
Fourth Edition, ADHD Inattention and/or
ADHD Hyperactive-Impulsive subscales.
At baseline, 49% of participants were
taking medication. There were no sta-
tistically significant differences be-
tween randomization conditions at
baseline with regard to gender, family
income, race, medication use, or base-
line ADHD symptoms (Table 1). There were
no significant differences between par-
ticipants who completed or who did not
complete the intervention, or between
randomization conditions at 6-month
follow-up regarding gender, family in-
come, or race. There were no adverse
side effects in neurofeedback or CT
interventions reported on the session
checklists.
Growth Model Analysis
The majority of distributions for the
measures at each time point and the
changes were approximately symmet-
rical and tailed, but normality could not
be assumed for all scales, so we relied
on the robust SEs available in HLM
42
in
the assessment of hypotheses in the
Conners 3-P, BRIEF, and BOSS models.
The slopes of the primary scales of
research interest on the Conners 3-P,
BRIEF, and BOSS are displayed to show
change over time by condition.
Parent-Reported Measures
Participants in the neurofeedback con-
dition showed significant improvements
over time compared with the control
condition on Conners 3-P in the intervention-
targeted areas of inattention, executive
functioning, and hyperactivity/impulsivity
486 STEINER et al at Harvard University on February 19, 2014pediatrics.aappublications.orgDownloaded from
as well as in 4 of 6 general behavior
subscales (Table 2 and Supplemental
Table 4) and on all 3 BRIEF summary in-
dexscalesaswellas7of8BRIEFsubscales
(Table 2 and Supplemental Table 5). Par-
ticipants in the CT condition showed
significant improvements over time
compared with the control on only 1 of
the 5 Conners 3-P subscales (Table 2)
and on 2 of 8 BRIEF subscales (Sup-
plemental Table 5). Furthermore, par-
ticipants in the neurofeedback condition
showed significant improvements over
time compared with the CT condition
on 6 Conners 3-P subscales (Supple-
mental Table 4) and on 6 BRIEF sub-
scales (Supplemental Table 5). See
Fig 2 for observed participant mean
scores across the 3 study time points
by condition in core ADHD and execu-
tive functioning areas.
Classroom Observation
Results from the linear growth model
did not show sustained change; how-
ever, the linear model was not a good fit
for Off-task Motor/Verbal, therefore
a quadratic model was estimated and
significant improvements were found in
the neurofeedback condition compared
with the control (P= .04). There were no
differences found between neurofeed-
back and CT conditions on classroom
observation measures (Table 3).
FIGURE 1
CONSORT (Consolidated Standards of Reporting Trials) diagram.
a
In a small number of cases, parent or teacher data were missing; therefore, sample sizes
may be somewhat smaller than is indicated here.
TABLE 1 Participant Characteristics
NF CT Control
n34 34 36
Age, mean (SD), y 8.4 (1.1) 8.9 (1.0) 8.4 (1.1)
Male gender, n23 22 25
Race, n
White 23 24 29
Black or African American 3 1 3
Asian 7 8 4
Fourth grade
a
,n21 28 22
Family income #$74 999, n13 12 12
Suburban school district, n24 25 27
IQ, mean (SD)
IQ composite 106.6 (13.9) 108.4 (14.3) 108.9 (15.4)
Verbal IQ 101.3 (16.7) 103.9 (19.4) 105.1 (16.3)
Nonverbal IQ 109.6 (12.5) 110.2 (12.1) 109.7 (17.7)
ADHD medication, n15 14 20
Medication MPH equivalent
b
, mean (SD) 28.9 (14.4) 24.2 (10.2) 25.1 (15.9)
Counseling (private), n978
School services: IEP/504 Plan, n27 22 21
Conners 3-P Global Index, mean (SD) 75.77 (13.46) 70.89 (10.83) 74.61 (12.08)
BRIEF Global Executive Composite, mean (SD) 66.30 (10.00) 61.75 (6.59) 64.65 (9.02)
BOSS Engaged, mean (SD) 72.16 (12.40) 73.37 (13.30) 78.20 (11.67)
BOSS Off-Task , mean (SD) 30.17 (17.10) 25.87 (15.05) 21.14 (13.87)
IEP, Individualized Education Plan; MPH, methylphenidate; NF, neurofeedback.
a
Significant difference between conditions.
b
Only includes participants who were taking a stimul ant medication.
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TABLE 2 Primary Measures: Parent Results
Observed Data
a
Growth Model Estimates
b
Preintervention Postintervention Six-Month
Follow-up
Coefficient 95% CI NF Versus
Control
CT Versus
Control
NF Versus
CT
Approximate
Effect Size
c
Conners 3-P–core ADHD symptoms
Inattention
Control 76.72 (10.02) 75.16 (10.47) 74.58 (10.03) 21.26 22.56 to 0.05 20.12
NF 80.07 (10.77) 71.43 (10.79) 70.06 (13.17) 23.67 25.81 to 21.52 ** 20.34
CT 74.78 (9.50) 70.21 (10.31) 67.56 (9.05) 21.55 23.75 to 0.64 20.14
DSM-IV-ADHD Inattention
Control 75.45 (11.20) 73.90 (11.91) 73.42 (11.45) 21.25 22.31 to 20.19 20.11
NF 79.20 (11.65) 70.13 (11.76) 68.45 (14.30) 23.45 25.36 to 21.55 ** 20.29
CT 73.48 (10.11) 70.07 (10.51) 66.13 (11.91) 21.88 23.78 to 0.02 20.16
Executive Functioning
Control 69.26 (11.64) 70.36 (12.56) 70.52 (12.38) 20.10 21.14 to 0.94 20.0082
NF 72.23 (12.16) 65.97 (13.16) 65.00(14.65) 23.02 24.88 to 21.16 ** 20.25
CT 67.46 (12.04) 66.00 (12.12) 62.45 (11.28) 22.18 23.91 to 20.45 * 20.18
Hyperactivity/Impulsivity
Control 77.03 (13.77) 75.42 (14.51) 77.16 (13.60) 0.67 20.53 to 1.87 0.05
NF 76.92 (13.54) 72.73 (14.38) 72.36 (16.34) 23.19 25.27 to 21.11 ** 20.23
CT 72.04 (13.69) 73.07 (15.75) 72.19 (12.92) 20.03 21.91 to 1.85 20.01
DSM-IV-ADHD Hyperactive-Impulsive
Control 75.45 (13.61) 74.84 (14.00) 65.16 (14.41) 1.11 20.12 to 2.35 0.08
NF 75.43 (13.76) 71.33 (14.51) 72.14 (15.94) 22.90 24.91 to 20.90 ** ** 20.21
CT 69.00 (13.71) 71.43 (15.73) 71.01 (13.25) 0.34 21.47 to 2.15 20.02
BRIEF–summary indices
Behavior Regulation Index
Control 60.84 (11.62) 61.36 (10.35) 60.39 (11.79) 0.39 20.64 to 1.42 0.04
NF 62.43 (11.52) 59.03 (10.05) 59.82 (11.70) 22.43 24.22 to 20.65 * 20.23
CT 59.29 (8.65) 59.86 (10.28) 59.07 (9.60) 20.50 21.97 to 0.97 20.05
Metacognition Index
Control 65.45 (8.41) 65.48 (9.45) 67.13 (8.07) 0.26 20.56 to 1.08 0.03
NF 66.93 (9.69) 62.77 (9.09) 60.80 (12.37) 22.92 24.50 to 21.35 ** 20.33
CT 62.14 (6.67) 61.33 (8.22) 60.21 (7.87) 20.91 22.20 to 0.39 20.10
Global Executive Composite
Control 64.65 (9.02) 64.81 (9.04) 65.48 (8.36) 0.23 20.65 to 1.10 0.0249
NF 66.30 (10.00) 62.07 (8.86) 61.02 (11.57) 22.75 24.37 to 21.13 ** * 20.31
CT 61.75 (6.59) 61.46 (8.30) 60.29 (7.30) 20.65 21.96 to 0.65 20.07
CI, confidence interval; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; NF, neurofeedback.
a
Data are presented as means (SD).
b
The growth model coefficient estimates for NF and CT represent the difference in the linear slopes between the intervention conditions and the control condition over the 3 time points. A multivariate general linear hypothesis test was conducted to
determine differences between the NF and CT slopes over the 3 time points.
c
Approximate effect size estimate for linear growth coefficient.
*P,.05, ** P,.01.
488 STEINER et al at Harvard University on February 19, 2014pediatrics.aappublications.orgDownloaded from
Medication Analysis
Among participants receiving stimulant
medication, the mean dosage change in
the neurofeedback condition from pre-
intervention to 6-month follow-up was
a 0.70-mg methylphenidate-equivalent
increase (P= .44). In both CT and con-
trol conditions, parents reported sig-
nificant increases: 13.08 mg for CT (P=
.02) and 9.14 mg for the control (P,
.001). No between-group dosage differ-
ence was found at 6-month follow-up,
controlling for preintervention (P=.08).
DISCUSSION
The outcomes of these analyses are
promising. Parents of children in the
neurofeedback condition reported sus-
tained improvements 6 months after
the intervention, compared with those in
the control condition. In the CT condition,
areas of executive functioning that did
not show statistically significant change
immediately after the intervention
showed a significant change by the 6-
month follow-up assessment compared
with the control condition. Even after
the intervention had stopped, parents
continued to notice improvements in
response to both interventions. Al-
though similar to the Arns et al
12
meta-
analysis, improvements seen in the
hyperactivity/impulsivity-related scales in
the neurofeedback condition are sur-
prising, because hyperactivity was not
directly targeted in the intervention.
Nevertheless, these findings suggest that
when children’s focus increases, phys-
ical activity level is reduced.
Clinician’s management of medication
was conducted independently of the
study protocol. It is noteworthy that par-
ticipants in the neurofeedback condition
showed maintenance of stimulant med-
ication dosage while presumably ex-
periencing the same physical growth
and increased school demands as CT
and control condition peers, whose med-
ication dosage increased clinically and
statistically (9- to 13-mg methylphenidate-
equivalent units).
This study used multiple sources and
types of data including questionnaires
from parents, systematic classroom
observations of behavior, and medication.
Because children had a different teacher
at pre- and postintervention compared
with the 6-month follow-up, teacher re-
ports were not included in these anal-
yses. The inclusion of the systematic
classroom observations provided a valid
double-blinded representation of the
children’s behavior in the classroom.
Randomization of subjects to treatment
conditions, as applied in this study, is the
gold standard for clinical trials. Even
though stratified by gender, school sys-
tem, and medication status and well
balanced regarding demographic char-
acteristics across all 3 randomized
conditions, the participants in the 3
conditions appeared to differ in the se-
verity of baseline ADHD symptoms. How-
ever, none of these differences reached
significance, and it is unclear how these
differences in baseline severity might
have affected the results. Furthermore,
we relied on growth models to isolate
change over time, not status at post-
treatment or follow-up; our time coding,
which centered time at posttreatment,
was selected to reduce the correlation of
initial status and change.
Parents were aware of the type of in-
tervention their child received, which
was unavoidable, because 1 of the sys-
tems uses a helmet and the other does
not. Parents were informed that the 2
interventions were both commercially
available and had achieved similarly
encouraging results in previous studies
at the time of enrollment. At postin-
tervention, we found no differences in
FIGURE 2
Observed participant mean scores across 3 study time points. NF, neurofeedback.
ARTICLE
PEDIATRICS Volume 133, Number 3, March 2014 489
at Harvard University on February 19, 2014pediatrics.aappublications.orgDownloaded from
satisfaction with the intervention be-
tween parents with participants in the
neurofeedback condition and parents
with participants in the CT condition, sug-
gesting that parent bias most likely did
not affect their reporting of the measures.
CONCLUSIONS
Neurofeedback participants showed
significant improvements that were
sustained 6 months after the interven-
tion compared with those in the control
and CT conditions, as reported by the
parents consistently on all of the core
ADHD subscales and executive func-
tioning scales. Participants in the CT
condition showed significant improve-
ment 6 months after the intervention
period on 2 executive functioning sub-
scales. Medication dosage was sustained
among participants in the neurofeed-
back condition, whereas for CT and
control conditions it was increased. The
finding that neurofeedback was supe-
rior to CT on multiple scales further
supports its efficacy as a treatment
of children with ADHD. Effects were
reported earlier in the neurofeedback
condition than in the CT condition and
were also stronger at the 6-month
follow-up period, showing the promise
of neurofeedback as a treatment with
sustained gains for children with ADHD.
This is the first large randomized con-
trolled trial to evaluate the long-term
efficacy of in-school CompAT. Despite
the paucity of scientific data, both
neurofeedback and CT training systems
are currently being used in school
systems across the United States,
29,30
underlining the importance of sys-
tematic studies of their effectiveness.
The direct impact of attention deficits
on academic progress makes schools
an ideal setting for such an interven-
tion, because all children with ADHD in
all communities could potentially have
access to these services on an ongoing
basis. A next important step will be to
assess individual participant differ-
ences to evaluate which factors might
be associated with the most progress
on the respective interventions and to
study older developmental age cohorts.
ACKNOWLEDGMENTS
We thank Tahnee Sidhu and Katie Tom-
asetti from Tufts Medical Center for
their extensive contributions to this re-
search project. We appreciate the assis-
tance of Dr David Gotthelf, PhD, of the
Newton Public Schools, Principal Simon
Ho and Zhen Su of the Boston Public
Schools, and the administrators and
teachers of both school systems. Dr
R. Chris Sheldrick, PhD, provided wise
advice from the beginning of the pro-
ject. We also acknowledge the following
former RAs affiliated with Tufts Medical
Center for their hard work on this study:
Susan Mangan, Minakshi Ratkalkar,
Lauren Rubin, Wendy Si, Melissa Arbar,
Stefanie Moynihan, Neena Schultz, Eliz-
abeta Bourchtein, Kolleen Burbank,
Heather Bentley, Amanda Civiletto, Joyce
Kao, and Jessica Charles, as well as stu-
dents Cathryn Magielnicki and Lisa Ngu
from Tufts University and Jessica Ben-
nett and Jessica Chen from Northeast-
ern University. We also acknowledge
all of the participants and their families.
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ADULT TASTES: Last week I was at the frozen food section of the supermarket
staring at rows of frozen desserts and practically rendered immobile by in-
decision. I was looking for a special frozen dessert for a friend of mine who likes
dessert and specifically chocolate ones. Of course, there were many varieties of
chocolate, chocolate chip, and chocolate fudge ice creams. However, I was drawn
to the gelatos, possibly because of my culinary experiences while traveling in
Italy, but also because of gelato’s remarkable flavors. I could choose from Ar-
gentine caramel, Belgium milk chocolate, and German Chocolate Cake. I even-
tually settled on a pint of Sea Salt Caramel gelato despite the fact that it cost more
than a half-gallon of ice cream. Evidently, I am not the only adult captivated by the
rich flavors found in gelato and willing to pay a bit more for the experience.
As reported in The Wall Street Journal (Life & Culture: November 12, 2013), sales
of gelato in the US jumped almost 90% in 2012 while sales of ice cream and ice
cream products remained flat. Gelato and premium ice cream makers have been
attempting to lure adults into buying more for themselves by introducing more
complex and exotic flavors. The interest in more obscure flavors may be due to
the spread of the food culture through TV shows and social media. Occasionally,
the flavors do not work out well. For example, tasters found a peach-champagne
sorbetto (a non-dairy gelato) with mint to be too intense and the line was
dropped. As for me, I am thrilled with all the new flavors. Still, I tend to gravitate to
the caramel gelatos which for at least one company have become the top selling
gelatos –selling even more than vanilla. As for my friend, she was very pleased
with my selection, as was I.
Noted by WVR, MD
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DOI: 10.1542/peds.2013-2059
; originally published online February 17, 2014;Pediatrics Ellen C. Perrin
Naomi J. Steiner, Elizabeth C. Frenette, Kirsten M. Rene, Robert T. Brennan and
Randomized Control Trial
In-School Neurofeedback Training for ADHD: Sustained Improvements From a
Services
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