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NeuroRegulation
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137!|!www.neuroregulation.org Vol. 2(3):137–148 2015 doi:10.15540/nr.2.3.137
Using Neurofeedback to Lower Anxiety Symptoms Using
Individualized qEEG Protocols: A Pilot Study
Stephanie M. Dreis, Angela M. Gouger, Edward G. Perez, G. Michael Russo, Michael A.
Fitzsimmons, and Mark S. Jones*
The University of Texas at San Antonio, San Antonio, Texas, USA
Abstract
Introduction: Anxiety disorders affect approximately 40 million Americans ages 18 and over (NIMH, 2015).
Although qualitative and small-scale quantitative neurofeedback (NF) studies show reduction in anxiety
symptoms, large-scale studies and quantitative electroencephalogram (qEEG) driven protocols are non-existent.
This retrospective pilot study intended to assess whether qEEG guided amplitude NF is viable in symptom
reduction of anxiety. Methods: Nineteen clients were assessed for anxiety, 14 were included in the data.
Demographics include age ranges from 11–61 (M = 31.71, SD = 16.33), 9 male and 5 female; six identified as
Caucasian, five as Hispanic/Latino, and three Caucasian/Hispanic ethnicity. Pre- and post-assessments included
the Zung Self-Rating Anxiety Scale, Screen for Child Anxiety Related Disorders (SCARED), and the Achenbach
System of Empirically Based Assessment (ASEBA). Clients received 30-min qEEG guided NF treatment
sessions, twice a week. The range of attended session was 7–28 (M = 12.93, SD = 6.32). Results:
Enhancement in clients’ well-being was evidenced by statistically significant improvement in symptom measures
scores. Although improvements for the two most anxiety-related categories on the ASEBA were not significant,
other anxiety-related categories did show significant improvement. Yet, qEEG findings were not statistically
significant. Directions for future research are discussed.
Keywords: anxiety; anxiety symptoms; qEEG guided amplitude neurofeedback; neurofeedback; z-scores
Citation: Dreis, S. M., Gouger, A. M., Perez, E. G., Russo, G. M., Fitzsimmons, M. A., & Jones, M. S. (2015). Using Neurofeedback to Lower
Anxiety Symptoms Using Individualized qEEG Protocols: A Pilot Study. NeuroRegulation, 2(3), 137–148. http://dx.doi.org/10.15540/nr.2.3.137
*Address correspondence to: Dr. Mark Jones, Department of
Counseling, The University of Texas at San Antonio, 501 Cesar Chavez
Blvd., Durango Building 3.304E, San Antonio, TX 78207, USA. Email:
mark.jones@utsa.edu
Copyright: © 2015. Dreis et al. This is an Open Access article
distributed under the terms of the Creative Commons Attribution License
(CC-BY).
Edited by:
Rex Cannon, PhD, Neural Potential, Florida, USA
Reviewed by:
John Davis, PhD, McMaster University, Ontario, Canada
Randall Lyle, PhD, Mount Mercy University, Iowa, USA
Introduction
According to the National Institute of Mental Health
(NIMH), anxiety disorders rank as the top leading
diagnosis by clinicians within the mental health field.
Anxiety disorders affect approximately 18% of the
United States population, or 40 million individuals
within a given year (NIMH, 2015). While the majority
of Americans experience stress periodically within
their lifespan, individuals diagnosed with anxiety
have severe pervasive symptoms that interfere with
their daily lives. Three of the most commonly
diagnosed types of anxiety disorders are:
generalized anxiety disorder, 6.8 million adult
Americans; panic disorder, 6 million adult
Americans; and social phobia, 15 million adult
Americans (NIMH, 2015). Psychotherapy, cognitive
behavioral therapy (CBT), exposure-based
treatment, stress management techniques,
meditation, and aerobic exercise are various
therapeutic modalities that may or may not be used
in conjunction with medication in the treatment of
anxiety disorders (NIMH, 2015).
With the onset frequently developing during
childhood, many anxiety disorders can be persistent
if not treated and present more frequently in women
at a 2:1 ratio (American Psychiatric Association,
2013). A variety of symptoms are reported by
individuals with anxiety disorders including: trouble
falling asleep and staying asleep, fatigue,
headaches, and muscle tension (NIMH, 2015).
More severe symptoms can include sudden and
repeated attacks of fear, pounding and racing heart,
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and purposely excluding oneself from certain people
or places.
Literature Review
Various biofeedback modalities have been
implemented by clinicians in the treatment of anxiety
including: electromyography (EMG), peripheral
temperature, and electrodermal response (EDR)
prior to neurofeedback’s (NF) popularization (Price &
Budzynski, 2009). NF, a subcategory of
biofeedback, is a method of self-regulation which
uses a brain-computer interface to promote neural
plasticity, by providing feedback to an individual
about their brain's electrical activity at a specific
scalp location in a specified frequency range
(Cannon, 2015). NF has been used to lower anxiety
symptoms in a variety of populations, as addressed
throughout the following reviewed literature.
A study by Kerson, Sherman, and Kozlowski (2009)
illustrates how the various modalities of earlobe
temperature training, alpha suppression, and alpha
symmetry training were used in eight adults who
either were diagnosed with generalized anxiety
disorder or presented with multiple anxious
behaviors. Participants were assessed for high
alpha frequency at the International 10–20 Electrode
system sites Fp1, Fp2, F3, F4, F7, and F8. A 5-min
baseline electroencephalogram (EEG) of the
participants was recorded with their eyes open for
the initial measurement and with their eyes closed
for the secondary measurement. Post-baseline
measures were also recorded 1 week after the last
NF training occurred. The initial six sessions were
used to increase the participant’s earlobe
temperature. The following 6–16 sessions consisted
of decreasing alpha magnitude by 10% in the
anterior lobes for 30 or more minutes. Once alpha
was suppressed, the protocol shifted to
improvement of alpha symmetry by a 15% increment
for 30 minutes or more during 8–32 sessions. All
sessions were conducted on a biweekly basis.
Continued assessment of participants was
conducted throughout the study by means of The
State-Trait Anxiety Inventory (STAI; Spielberger,
1983) in which a significant improvement in scores
resulted. The pre- and post-mean change in EEG
was 1.41 z-scores towards the mean. Limitations
mentioned within the study include: a limited amount
of participants, lack of variance in protocols, and the
lack of a control group.
A study conducted by Cheon et al. (2015)
researched NF implemented on 77 adults diagnosed
with various psychiatric disorders within a psychiatric
setting. The following disorders are listed in order of
prevalence according to the research: depressive
disorders, anxiety disorders, sleep disorders,
somatoform disorders, adjustment disorders, bipolar
disorder, schizophrenia, attention-
deficit/hyperactivity disorder, alcohol dependence,
game addiction, and impulse control disorder.
Protocols were designed depending on the
participant’s chief complaint (e.g., anxiety, emotional
instability, lethargy, etc.), the opinion of the attending
psychiatrist, neuropsychiatric evaluation results, and
the subjective-symptom-rating scale. The clinical
Global Impression-Severity Scale (CGI-S; Busner &
Targum, 2007) and the Hill-Castro (2002) checklist
were also implemented on a weekly basis as a
measure of treatment effectiveness. NF protocols
included training sensorimotor rhythm (SMR), beta,
and/or also contained alpha-theta training. The
various frequency bandwidths which were rewarded
during training, included: SMR from 12 to 15 Hz,
beta from 15 to 18 Hz, theta from 5 to 8 Hz, and
alpha between 8 and 12 Hz. The individualized site
locations in which training was implemented
included: Fp1, Fp2, F3, F4, F7, F8, T3, T4, C3, C4,
P1, P2, O1, O2, and Oz based on the International
10–20 Electrode system. Alpha-theta training was
conducted at the PZ site location. Protocols were
evaluated and finalized during weekly NF meetings,
which included a team of three psychiatrists trained
in NF, as well as a trained NF therapist. The
number of appointments for a client’s training ranged
from 1 to 20 or more sessions. The Hill-Castro
Checklist score showed an improvement in multiple
symptom areas including anxiety (p = .0001). The
pre- and post-CGI score showed a significant
reduction in the severity of symptoms (p < .001).
Limitations mentioned within the study included
having a heterogeneous group and no control group,
as well as not utilizing the quantitative
electroencephalography (qEEG) to determine
protocols.
Singer (2004) used NF on two female dancers, 27
and 52 years of age, who had persistent levels of
performance anxiety. A STAI assessment was
taken by each participant before a NF session and
before each of their major dance performances. The
course of NF treatment included 20 sessions at the
time interval of 30 min per session. Sensors were
placed on site locations T3 and T4 and thresholds
were adjusted during each session dependent upon
the participant’s response. Post assessments
indicated a significant decrease in anxiety symptoms
associated with performance. The trait anxiety
portion of the first participant’s assessment indicated
a decrease in score from 59 to 43.5, while the state
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portion underwent a decrease in score of 66 to 44.
The trait anxiety portion of the second participant's
assessment indicated a decrease in score as well
from 52 to 36, while the state portion underwent a
decrease in score of 56 to 30. Limitations to this
study included: a small sample size, lack of
individualized protocols, and no control group.
Walker (2009) implemented a study based upon
whether NF could lower anxiety symptoms for 19
clients diagnosed with post-traumatic stress disorder
(PTSD). Four clients, who were originally diagnosed
with PTSD and in the NF group, but had dropped out
after the qEEG, were included in the control group.
Each client received a qEEG using the NeuroGuide
software. Results were compared to the Lifespan
Normative database. Excessive high frequency beta
(21–30 Hz) was then downtrained for five to seven
sessions for each site that presented excessive high
frequency beta; 10 Hz activity was uptrained at the
same sites. The sites were in various and multiple
areas depending on where the excessive beta was
located, as protocols were determined by a qEEG.
A self-rated anxiety Likert scale from 1 to 10 was
also used to determine the presence of anxiety
symptoms each participant had felt. The number of
sessions per individual ranged from five to seven.
Participants who had NF training had a significant
reduction in self-rated anxiety with a pre-treatment
score of 5/10 to 7/10, to a post-treatment score of
0/10 to 2/10, and 1 month after NF training the
scores remaining between 0/10 to 2/10. Subjects
who did not have NF training had little or no
reduction in self-rated anxiety 3 months after their
qEEG. Limitations with this study include using a
self-rating scale for anxiety rather than an evidence-
based assessment.
A study by Scheinost et al. (2013) evaluated 10
subjects with contamination anxiety to undergo
functional magnetic resonance imaging (fMRI) NF
training and compared their neural connectivity with
real-time functional magnetic resonance imaging (rt-
fMRI). A matched control group of 10 subjects that
received sham fMRI-NF (SNF) of their matched pair
was used. Subjects had an initial fMRI to localize
their activity in the orbitofrontal cortex (OFC) from
contamination anxiety. They then met with a
psychologist to discuss strategies for manipulating
brain activity that could later be refined during fMRI-
NF. There were eight sessions total where subjects
were shown contamination-related photos and
asked to rate their anxiety on a scale of 1 to 5. The
first and the last session consisted of subjects being
asked to implement the personal coping
mechanisms, which they would typically use to try to
lessen their anxiety. The middle six sessions
consisted of 90 min of fMRI-NF. The fMRI-NF
sessions consisted of subjects receiving cues of
when to increase activity their OFC area, when to
decrease activity, and when to rest based on their
OFC output. Resting cues included a neutral image.
Between-group differences in fMRI’s were identified
using Wilcoxon’s rank-sum test. The fMRI-NF group
reported greater self-reported reduction in anxiety (p
= 0.02) compared to the SNF group (p = 0.45). The
fMRI-NF group had significant (p < 0.05) neural
changes compared to the SNF group as recorded by
the last fMRI taken several days after the last fMRI-
NF session. The fMRI-NF group had significant
decrease in connectivity for the brain regions
associated with emotion processing, including: the
insula and adjacent regions, the hippocampi,
parahippocampal and entorhinal cortex, the right
amygdala, the brain stem in the vicinity of the
substantia nigra, the temporal pole, superior
temporal sulcus, thalamus, and fusiform gyrus. The
fMRI-NF group also had an increased degree of
connectivity that was seen in prefrontal areas
associated with emotion regulation and cognitive
control, including: right lateral prefrontal cortex and
bilateral portions of Brodmann’s area 8. This study
illustrated how changes directly resulting from fMRI-
NF were possible and how structural changes can
last days after a fMRI-NF session. This study also
supported the idea of finding and confirming a
localized area related to a symptom and using that
area for fMRI-NF. Limitations to this study include
low number of fMRI-NF sessions and a small sample
size.
These studies illustrate how NF can be a viable tool
in lowering anxiety symptoms. They each have their
strengths and limitations. A substantial limitation is
either using the same protocol for each patient
and/or using a protocol based on symptoms alone.
Protocols based on symptoms alone and/or using
the same protocol for each patient bypasses the
time, cost, and training of running a qEEG
(Thompson & Thompson, 2003). Hammond (2010)
expresses the importance of using a qEEG to
identify heterogeneity in brain wave patterns, finding
comorbidities, and looking for effects from
medication.
Krigbaum and Wigton (2014) argue the importance
of qEEG guided and z-score NF as it allows the
clinician to develop a more individualized treatment
plan which encompasses a qEEG baseline, history,
and clinical status of the client. Wigton and
Krigbaum (2015a) further assert how 19-channel z-
score NF (19ZNF) protocols facilitate identifying the
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link between localized cortical dysfunctions and
connectivity issues associated with mental health
symptoms. In this modality, qEEG metrics are
compared to a normative database to create z-
scores; then, those z-scores are incorporated into
the NF protocol in real time during the session. This
allows for pre-treatment assessment, a helpful tool
in measuring progress with the client, and combining
real-time assessment with the operant conditioning
of NF. Thus, 19ZNF training is used to bring these
scores closer to the mean, otherwise known as
normalizing. Moreover, 19ZNF protocols also
reduce the number of sessions, which is more
economical for the clients. Wigton and Krigbaum’s
pilot study used 19ZNF to train the deviant z-scores.
Unlike Wigton and Krigbaum (2015a), this research
is a pilot study which used single-channel qEEG
guided amplitude training, rather than z-score
training, for three reasons: (1) it is commonly used
by many practitioners, (2) it is a straightforward
method for students in training to learn before
advancing to other modalities, and (3) the numerous
one- or two-channel qEEG-guided amplitude training
studies which exist in the literature, as reviewed by
Wigton and Krigbaum (2015b). Therefore, based on
the literature review, this retrospective pilot study
sought to assess whether individualized qEEG-
guided protocol amplitude NF is viable in symptom
reduction of anxiety-related disorders.
Methods
Clients
Clients contacted the Sarabia Family Counseling
Center at the University of Texas at San Antonio
(UTSA) to receive therapy and NF treatment free of
charge. Clients learned about the clinic through
community referral sources and/or university media
relations. Upon calling, clients were screened by
clinically licensed, doctoral-level students in the
UTSA Department of Counseling to determine if they
met the criteria for anxiety-spectrum disorders. If the
individual satisfied the clinical criteria, as well as the
required biweekly availability and willingness to
complete the treatment requirements on an ongoing
basis, the clients were then scheduled to meet with
a NF student clinician. Prior to completing any
formal assessments of anxiety, student clinicians
acquired a comprehensive informed consent from
each client. As retrospective research, the study
was deemed to be exempt from review by the UTSA
Institutional Review Board.
The pilot study started with 19 clients that were seen
over a period between one or two semesters;
however, the average number of sessions that
clients acquired was approximately 12.9 sessions.
In order to preserve our sample size we relaxed the
inclusion criteria to a minimum of seven sessions
per client. Three clients were excluded from the
study because they dropped out without completing
the full round of sessions or completing the final
assessments. The data sets of two clients were
excluded from the study; of the two clients that were
excluded, one client had previously received a
regimen of NF treatment and the other admitted to
daily use of cannabis. A total of 14 clients are
represented in the data. Of the included clients,
demographics consisted of 9 males and 5 females.
Clients ranged in age from 11 to 61 years of age
with the average age being 31.71 (SD = 16.33)
years of age. Six clients identified as Caucasian,
five as Hispanic/Latino, and three identified as mixed
Caucasian and Hispanic ethnicity (see Table 1).
Table 1
Client Demographics
Client
#
Age
Gender
Ethnicity
Number of
Sessions
1
17
M
Hispanic
14
2
20
F
Hispanic
26
4
48
F
Hispanic
28
6
52
M
Caucasian
12
7
15
F
Caucasian
10
8
50
M
Caucasian
14
10
21
M
Hispanic
8
11
11
M
Hispanic
Caucasian
Mix
11
12
37
M
Hispanic
Caucasian
Mix
8
13
26
F
Hispanic
7
14
18
M
Hispanic
Caucasian
Mix
10
15
25
M
Caucasian
12
16
61
F
Caucasian
11
17
43
M
Caucasian
10
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Therapists
The student clinicians consisted of master’s-level
students within a program certified by the nationally
accredited Council for Accreditation of Counseling
and Related Education Programs (CACREP).
These students are also in the supervision phase of
pursuing their Board Certification in NF (BCN); thus,
were overseen by a certified and licensed
supervisor. Students had previously completed the
required didactic coursework that is recognized by
The Biofeedback Certification International Alliance
(BCIA; http://www.bcia.org).
Measures
A within-subjects research design was implemented,
which included the following pre-conditional and
post-conditional assessments: the Screen for Child
Anxiety-Related Disorders (SCARED) for children
and adolescents, the Zung Self-Rating Anxiety Scale
for adults, the age-appropriate self-reports for the
Achenbach System of Empirically Based
Assessment (ASEBA), and qEEG. The symptom
measurements were selected on: the bases of their
focus on anxiety symptoms, widespread acceptance
in the therapeutic community, and standardization.
The qEEG measures assessed deviances from a
normative database, which were then used to
develop individualized protocols for training. Pre-
and post-assessment comparisons were made using
z-score changes, where improvement is assumed
when scores move toward the mean (z = 0). Some
of the challenges related to this form of measure are
discussed below, but z-score comparisons provide
one form of common reference with which to
compare individualized protocols across the
treatment group (Wigton & Krigbaum, 2015a).
Instrumentation
The qEEGs were acquired via 19-channel
recordings in the eyes-closed and eyes-open
conditions in a resting state, using a BrainMaster
(BrainMaster Technologies, Inc., Bedford, Ohio)
Discovery 24 high-impedance amplifier and
NeuroGuide (Applied NeuroScience, Inc., Largo,
Florida) software. Recordings utilized correct size
Electro-Cap (Electro-Cap International, Inc., Eaton,
Ohio) 10–20 electrode appliances, which were fitted
as per manufacturer’s guidelines and ear-clip leads
placed. Preparation of electrodes was performed in
a manner adequate to achieve impedance levels of
less than 5,000 Ω (Jones, 2015). NF was provided
utilizing BrainMaster Atlantis two-channel amplifiers
and BioExplorer (CyberEvolution, Inc., Seattle,
Washington) software. Electrode site preparation
was done by cleaning site, ground, and reference
locations with rubbing alcohol and abrading using
PCI prep pads and Nuprep. Gold-plated electrodes
were attached to the clients using Ten-20 paste.
Impedance measurements were taken to insure that
interelectrode impedance was less than 5,000 Ω
(Jones, 2015).
Protocols
Clients agreed to attend a minimum total number of
15 NF training sessions that were to be held at the
same time, twice per week, and free of charge.
Participants were instructed to discontinue the
consumption of caffeine or any other non-essential
substances that may alter the qEEG significantly,
such as supplements or medications. At least a 24-
hour window prior to the qEEG recording was
suggested for clients to restrict consumption for non-
essential substances, unless otherwise medically
directed. All medically directed substances were
factored into qEEG interpretation and protocol
development.
Collectively, participants underwent an average of
12.93 sessions of NF with a range of 7 to 28 total
sessions. Participants that did not meet our original
set threshold of 15 sessions were included due to
the aspect of increasing our client size for a
sufficient statistical interpretation. A total of 181
sessions were completed between all of the
participants (see Table 1). These training protocols
consisted of amplitude uptraining and/or
downtraining of selected frequency bands based on
qEEG findings. Protocol selections were based on
current research and reflect markers found to be
associated with anxiety issues (Dantendorfer et al.,
1996; Demerdzieva & Pop-Jordanova, 2011; Gold,
Fachner, & Erkkilä, 2013; Gunkelman, 2006;
Gurnee, 2000; Heller, Nitschke, Etienne, & Miller,
1997; Johnstone, Gunkelman, & Lunt, 2005;
Machleidt, Gutjahr, Muegge, & Hinrich, 1985; Price
& Budzynski, 2009; Savostyanov et al., 2009;
Siciliani, Schiavon, & Tansella, 1975; Stern, 2005, p.
196; Tharawadeepimuk & Wongsawat, 2014;
Walker, 2009).
Based on the preferences of the clients and clinical
judgment of the practitioners, feedback was
presented using a variety of formats: games,
animations, sounds, and analogical presentations
(such as the size of boxes representing the
amplitude of the respective bandpass filtered EEG
signals). Thresholds were set manually at the
beginning of the session based on the aimed
percentage of a successful reward rate of
approximately 50% of the time. Periodic
adjustments were made to the threshold settings
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within and between sessions as needed to shape
behavior towards the client’s specific treatment
goals. Records were made for each session, which
included: frequency bands, threshold settings,
session average amplitude levels, type of feedback
utilized, and significant details from client reports
and clinician impressions. EEG data was recorded
for each session.
Table 2
Training Sites and Frequency Bands for Each Client
Client #
EC/EO
Site
Band1
Decrease
Band2
Increase
Band3
Decrease
Combined
Sites
1
EO
Pz
8–12
2
EO
F2
5–7
10–12
20–25
Fz/F4
4
EO
Pz
7–9
25–29
6
EO
Pz
7–12
17–22
7
EO
CPz
21–27
Cz/PZ
8
EO
Cz
7–9
12–15
19–24
10
EO
Fz
5–9
12–15
25–30
11
EO
Cz
20–25
25–30
12
EO
Cz
3–6
25–30
13
EO
Cz
4–7
18–25
14
EO
Cz
3–5
12–15
20–25
15
EO
Cz
1–5
12–15
25–30
16
EO
Fz
3–5
12–15
8–11
17
EC
Pz
8–10
25–30
Note. Combined sites = two 10/20 sites adjacent to selected 10/10 site. Client number column omits clients whose data was
excluded.
Statistical Analysis
The statistical analysis for the symptom measure
assessments were paired t-tests using IBM SPSS
Statistics Version 22. Quantitative analysis was
performed using NeuroGuide software, which was
exported in by topographical and tabular form.
Further analysis was done using Microsoft Excel
2010 and IBM SPSS Statistics Version 22.
Computations were done for the frequency bands
trained for each client. Given sites, number of
bands, and frequency range of bands were unique
to each client (see Table 6), it was not feasible to
compare simple amplitude changes across clients.
As such, the absolute values of the positive and
negative z-scores were used instead as a way to
compare a common metric of pre- and post-changes
across clients. The process involved calculating z-
scores using NeuroGuide software, exporting the
results in tabular form using 1 Hz bins, transforming
the z-scores to use absolute value, then averaging
the transformed values for the respective frequency
band(s) used for each client. If more than one
frequency band was trained at a time (such as
downtraining and/or uptraining), the z-score values
for the bands trained were then averaged for each
client and the statistical analysis was completed
between the pre- and post-assessments as a group
using paired t-tests. As opposed to merely
averaging the absolute power at each of the
treatment sites, z-score results were used in order to
provide a common measure that was applicable
across all frequency bands. Due to the 1/frequency
characteristic of the EEG spectrum, with typical
alpha peaks, power measures are not consistent
across the frequency spectrum. In addition, alpha
power measures typically vary significantly between
eyes-closed and eyes-open recording conditions.
For example, if the power of the frequency band of
8–12 Hz changes by 1 µV, such a change may not
be comparable to a 1 µV change in the frequency
band of 20–25 Hz.
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Results
Symptom Measures
All grouped averaged pre-post comparisons of the
three assessments resulted in improvements. A
cumulative summary of these results are presented
in Table 3.
On the Zung Anxiety Scale, for 11 adult clients, the
mean of the pre-scores was 46.00 (SD = 9.07) and
the mean of the post-scores was 38.83 (SD = 7.37).
The t-test yielded a statistically significant
improvement, with t(10) = 4.59, p < 0.001. While
nine clients reported a decrease in their scores, 2 of
the 11 clients, reported an increase. See Table 4 for
the pre-post scores for each client.
For the SCARED, for three minor clients, the mean
of the pre-scores was 37.22 (SD = 14.47) and the
mean of the post-scores was 21.33 (SD = 13.65).
The t-test resulted a statistically significant
improvement, with t(2) = 27.71, p < 0.001. All clients
had improved self-report scores. See Table 5 for
the individual pre-post scores.
On the ASEBA, for all categories averaged, the
mean of the pre-scores was 63.27 (SD = 6.51) and
the mean of the post-scores was 59.33 (SD = 6.35).
The results of the t-test was a statistically significant
improvement, with t(17) = 8.75, p < 0.001.
Moreover, scores on all 18 categories of the ASEBA
improved; see Table 6 the pre-post scores for each
category. Improvements in the categories most
specific to anxiety symptoms, that is,
Anxious/Depressed and Anxiety Problems, were not
statistically significant. The checklists do, however,
assess for symptoms frequently associated with
anxiety, such as withdrawal, somatic issues, thought
problems, internalizing, and avoidance; and
improvements in these areas were statistically
significant.
Table 3
Group Averaged Pre-Post Assessment Results
Assessment
(n)
Pre-
scores
M
(SD)
Post-
scores
M
(SD)
t(df)
p
Zung Anxiety
Scale (n = 11)
46.00
(9.07)
38.82
(7.37)
4.59(10)
< 0.001
SCARED
Scale (n = 3)
37.22
(14.47)
21.33
(13.65)
27.71(2)
< 0.001
ASEBA Across
All Categories
(n = 14)
63.27
(4.88)
59.33
(4.67)
8.76(17)
< 0.001
Table 4
Zung Anxiety Scale
Client #
Pre-scores
Post-scores
2
60
51
4
56
39
6
38
30
8
44
36
10
42
33
12
42
33
13
35
37
14
44
45
15
62
52
16
40
34
17
43
37
Mean (SD)
46.00 (9.07)
38.83 (7.37)
Note. t(10) = 4.59, p < 0.001.
Table 5
SCARED Scale
Client #
Pre-scores
Post-scores
1
28
12
7
30
15
11
54
37
Mean (SD)
37.22 (14.47)
21.33 (13.65)
Note. t(2) = 27.71, p < 0.001.
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Table 6
Achenbach Behavior Checklists (ASEBA)
Category
Pre
Post
t(df)
p
Anxious/Depressed
69.57
66.86
1.212(13)
.247
Withdrawn
66.21
61.64
2.329(13)
.037
Somatic Complaints
65.14
60.71
2.74(13)
.017
Thought Problems
66.29
57.86
3.042(13)
.009
Attention Problems
69.07
63.43
2.112(13)
.055
Aggressive Behavior
61.79
56.93
2.62(13)
.021
Rule-breaking
Behavior
60.00
55.43
4.738(13)
< .001
Intrusive
44.07
43.14
1.153(10)
.276
Internalizing
69.36
64.93
2.174(13)
.049
Externalizing
59.71
54.07
2.713(13)
.018
Critical Items
52.57
49.14
3.612(10)
.005
Total Problems
65.79
60.79
2.557(13)
.024
Depressive Problems
(DSM)
69.50
68.79
0.306(13)
.764
Anxiety Problems
(DSM)
65.36
64.64
0.49(13)
.632
Somatic Problems
(DSM)
62.36
59.21
1.717(13)
.110
ADHD Problems
(DSM)
66.29
63.00
1.47(13)
.165
Avoidant Personality
Problems (DSM)
66.00
61.93
2.194(13)
.047
Antisocial Personality
Problems (DSM)
59.79
55.36
3.169(13)
.007
Category Mean (SD)
63.27(6.50)
59.33(6.34)
Note. Bolded values are statistically significant.
Quantitative EEG Results
While not all clients realized improvements in z-
scores, the difference between pre- and post-
measurement showed a decrease in absolute z-
score values, averaged across all cases, from 1.21
(SD = 0.73) to 1.10 (SD = 0.62). The improvement
was not statistically significant, however. Table 7
provides the pre-post average z-scores for each
client. It should be noted that one-channel
amplitude training was employed as the method of
NF, not z-score training.
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Table 7
Results Pre-Post qEEG Z-scores
Client #
Pre-scores
z-score
Post-scores
z-score
1
1.51
0.77
2
1.67
2.32
4
0.77
1.29
6
1.33
1.50
7
0.77
1.44
8
0.70
0.70
10
0.84
0.32
11
2.91
0.49
12
0.75
1.08
13
2.54
2.37
14
0.60
0.89
15
1.10
0.90
16
0.64
0.55
17
0.77
0.72
Mean (SD)
1.21 (0.73)
1.10 (0.62)
Note. Z-score pre-post difference was not statistically
significant.
Discussion
Symptom improvement was shown with various
assessments including: the self-report ASEBA, Zung
Anxiety Scale, and SCARED. While two of the most
anxiety-specific categories of the ASEBA yielded
improvements that were not statistically significant,
other anxiety-related categories resulted in
significant improvement, and overall the
improvement in averaged scores across categories
were statistically significant. Taken together, the
symptom scales present evidence of a significant
improvement in the client’s sense of wellbeing.
Interestingly, two categories of the ASEBA that
showed robust improvement were Rule-Breaking
and Antisocial Personality. A number of researchers
have examined the comorbidity of anxiety disorders
and Antisocial Personality Disorder or Conduct
Disorder, with some evidence of a correlation
(Galbraith, Heimberg, Wang, Schneier, & Blanco,
2014; Goodwin & Hamilton, 2003; Hodgins, De Brito,
Chhabra, & Côté, 2010). This relationship may
serve as an added dimension to the ongoing study
based on this pilot, or as an additional focus of
research.
The parent rating version of the SCARED was
administered, but results presented some problems
in interpretation. In one instance, the parents rated
their child in opposite ways—one parent reported a
large improvement, while the other parent reported a
large worsening of symptoms. In this case there
was significant parental conflict and one parent
divulged that they were divorcing. Due to the
confounding nature of the parental reports, only self-
reports on the assessments were included for
analysis. Parental ratings can be included as the
size of the sample increases in the future.
A small sample size and the lack of a control group
was a roadblock to an effective research design in
some aspects of the study. There were also
limitations based on clients receiving therapeutic
care (as self-reported) and experimenter bias/skill
level. This experimenter bias could have resulted in
a response-expectancy effect (Kirsch, 2009).
Furthermore, some clients experienced confounding
life stressors that could have influenced treatment
and medication effects that were not present during
the pre- and post-qEEG. Treatment was provided to
clients who clearly had characteristics that
compromised the quality of data that might be
gained from them. They included clients who were
inconsistent in attendance, exhibited substance
abuse issues (data was excluded), experienced
significant life events (such as relational or financial
crises), or had mental or medical disorders that
possibly reduced the effect of the treatment. This
may have resulted in spending a portion of the
sessions engaged in active listening and numerous
client-centered or CBT therapeutic interventions in
different ways and to various extents with the clients.
The relative merits of various strategies of
controlling for these variations in the future are being
considered.
Quantitative designs are descriptive or experimental
in nature. A descriptive study establishes only
associations between variables and an experimental
usually establishes causality. Unfortunately, many
variables were not accountable or annotatable. One
such effect was positive reinforcement. The
presentation and style of secondary reinforcers
varied based on student-clinician decisions and
were not directly addressed in this study. Operant
and classical conditioning techniques were
employed to make the feedback as much of a
positive reinforcement as possible. This included
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the selection of feedback type based on client
preference. Some clients expressed preferences for
one or more of available options or classes of
options, which included: games, animations, sounds
(including music), or analogical feedback (such as
boxes that grow and shrink in size based on which
wave analysis was trained). Positive reinforcement
was also provided via verbal prompts and coaching.
As the study progresses in the future with additional
clients, it may be possible to analyze these
variations for significant differences in treatment
outcomes.
There was variability in the skill and experience
levels of the student counselors. Students were at
various levels in their studies within their degree
program. Some students had significant experience
with NF, while most were novices. Student
counselors who were taking an advanced NF
course, as an elective to their counseling degree
program, saw clients in the counseling department's
center. In addition to an introductory course, some
of the students had completed one or two semesters
of advanced practical and theoretical applications in
NF. During the previous courses, the students had
worked with one or more NF software systems, had
practiced performing NF on other students, and had
NF procedures designed for themselves, which were
based on qEEG analysis. Some of the students had
completed counseling skills courses, practicum and
internship hours, while others were novices to
counseling. In one case, the student had been the
counselor for the client they were seeing for NF
treatment as part of a counseling practicum course
one semester prior. Controls for the effect of
student bias and skill level differences were:
supervision from the professor who monitored via
informal verbal reports from students and clients,
session notes, closed-circuit television, and weekly
case conferences.
"Neurofeedback training is all about learning. Each
person's rate of learning is unique; some respond
more quickly than others do" (Demos, 2005, p. 127).
As such, a combined client-centered and
quantitative approach is best used in the future. In
this case, a quasi-experimental approach needs to
be designed. Clients would need to previously be
scored on self-efficacy, anxiety scores, and
education of basic NF principles. If all scales can be
quantified, then limitations, placebo effect, and
counselor technique can be assessed during the
design phase, and several uncontrolled variables
can be at least factored. Excluding students from
treating clients with whom they have any previous
clinical or personal relationship (e.g., previous
student and talk therapy clients they may have had
in practicum or internship portions of degree path).
Other client variables to control for, as affecting
possible treatment outcomes, would include: adjunct
therapies (concurrently used or attending),
medications, familial/financial/extraneous life
stressors and major life events, injuries/illnesses,
changes in sleep, and other therapeutic lifestyle
changes, that is, diet, exercise, meditation. Future
considerations need to assess whether counselor-
client therapeutic modalities need to be standardized
amongst clinicians to established protocols of
breathing techniques, mindfulness, and meditation in
hopes of decreasing variability.
A few clients in the study were taking psychotropic
medications, such as benzodiazepine-class
anxiolytics and SSRIs. While these effects on the
EEG were assessed as part of the qEEG analysis,
they remain as a confounding variable for treatment
outcomes. As the study continues with the addition
of more clients each semester, accounting for this
variable will make statistical analysis more robust.
This will be accomplished by (1) setting up a
comparison between medicated and non-medicated
clients, and (2) excluding medicated client data.
Training was conducted using amplitude measures
and monopolar site placements only. While this was
by design, it excluded other forms of NF which may
be based on connectivity measures and multiple site
placements. As noted above in the results section,
while z-score calculations were used in the statistical
analysis of EEG changes, the training did not utilize
z-score training, but qEEG-guided protocols. Two
clients, for example, were given posterior alpha
enhancement training based on qEEGs that
reflected the low-amplitude fast phenotype. One of
these clients had a fast alpha peak frequency,
showing an elevated z-score in the 11–12 Hz range
with normal z-scores for 8–10 Hz. But, the protocol
for this client included uptraining 8–10 Hz (and
downtraining 25–30 Hz). In this case, it was
expected that the absolute z-score might actually
show an increase, which turned out to be the case.
Although the client successfully modified the
amplitudes of both frequency bands, with
accompanying symptom improvement, these results
present a confounding factor in the z-score analysis.
The study may have also been strengthened by the
addition of a learning curve. This will be added in
future analyses.
Finally, it is worth emphasizing that the setting of the
study is a community counseling center, located on
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a university campus, operated as part of a graduate
counseling educational program. As such, the
prevailing values in the treatment are (1) the well-
being and therapeutic needs of clients, and (2) the
learning opportunities for students. Students in the
NF program are taught an integrative model of NF
and psychotherapy; as such, they naturally carried
this approach into their sessions with clients. It
became obvious to the professor and students that
these priorities, at times, took precedence over a
purely NF-based research design in ways that may
have compromised the acquisition of “clean” data. It
is hoped that as the study continues, the ongoing
addition of more clients and students will enable the
clearer identification of the sole effects of NF.
Nonetheless, the study may replicate the common
practices of most NF practitioners and hold value in
that regard.
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Received: August 5, 2015
Accepted: September 27, 2015
Published: October 8, 2015
