Neurofeedback Training for Opiate Addiction: Improvement
of Mental Health and Craving
Fateme Dehghani-Arani • Reza Rostami •
Published online: 20 April 2013
The Author(s) 2013. This article is published with open access at Springerlink.com
Abstract Psychological improvements in patients with
substance use disorders have been reported after neurofeedback
treatment. However, neurofeedback has not been
commonly accepted as a treatment for substance dependence.
This study was carried out to examine the effectiveness
of this therapeutic method for opiate dependence
disorder. The specific aim was to investigate whether
treatment leads to any changes in mental health and substance
craving. In this experimental study with a pre-post
test design, 20 opiate dependent patients undergoing
Methadone or Buprenorphine maintenance treatment were
examined and matched and randomized into two groups.
While both experimental and control groups received their
usual maintenance treatment, the experimental group
received 30 sessions of neurofeedback treatment in addition.
The neurofeedback treatment consisted of sensory
motor rhythm training on Cz, followed by an alpha-theta
protocol on Pz. Data from the general health questionnaire
and a heroin craving questionnaire were collected before
and after treatment. Multivariate analysis of covariance
showed that the experimental group achieved improvement
in somatic symptoms, depression, and total score in general
mental health; and in anticipation of positive outcome,
desire to use opioid, and relief from withdrawal of craving
in comparison with the control group. The study supports
the effectiveness of neurofeedback training as a therapeutic
method in opiate dependence disorder, in supplement to
Keywords Neurofeedback Opiate addiction Mental
Substance use disorder is characterized by physiological
dependence accompanied by the withdrawal syndrome upon
abstinence from the drug, psychological dependence with
craving, a pathological motivational state that leads to active
drug-seeking behavior, and tolerance, expressed in the
escalation of the dose needed to achieve a desired euphoric
state (Sadock and Sadock 2008). It is a chronic, relapsing
mental disease that results from the prolonged effects of
drugs on the brain (Dackis and O’Brien 2001; Volkow et al.
2003, 2004). Opiate dependence refers to a cluster of substance
use disorders with physiological, behavioral, and
cognitive symptoms, which, taken together, indicate repeated
and continuing use of opiate drugs despite significant
problems related to such use (Sadock and Sadock 2008).
Drug and opiate substance dependence can take control of
the brain and behavior by activating and reinforcing behavioral
patterns that are excessively directed to compulsive
drug use (Di Chiara 1999; Gerdeman et al. 2003).
The effects of pharmacological and behavioral treatment
for substance dependence have been criticized as being
limited (Fagan 1994). While major resources have been
employed to study and treat substance dependence, there
has been minimal improvement in success rates of treatment
and the relapse rate is typically over 70 % (Higgins
et al. 1995). Gossop et al. (2002) reported 60 % of heroin
addicts relapsed 1 year following substance dependence
treatment. Effective treatment for substance dependence
will always require a combined biological, physiological
and psychological approach. Few treatment programs
F. Dehghani-Arani (&) R. Rostami
Tehran, Islamic Republic of Iran
Department of Psychology, University of Tehran,
Tehran 1969713663, Iran
Appl Psychophysiol Biofeedback (2013) 38:133–141
address the neurological and physiological issues of substance
dependence (Sokhadze et al. 2008).
In recent years, the psychological and neurophysiologic
dimensions of substance dependence have attracted more
scientific attention (National Institute on Drug Abuse 2000).
Volkow et al. (1988) were the first to use positron emission
tomography (PET) to study the effects of cocaine on the
human brain. This study has played a central role in ascertaining
the interactions between the brain, drug and behavior
in humans. Studies have shown that some symptoms of
substance and opiate dependence such as craving, impulsiveness,
and psychological abnormalities, are connected to
pathological neurophysiology (Kaufman 2000; Dackis and
O’Brien 2001; Hubbard and Martin 2001; Volkow et al.
2003, 2004; Ardila et al. 1991). Quantitative electroencephalography
(QEEG) as a kind of brain mapping technique
can characterize some of these abnormalities (Newton et al.
2003). The spontaneous EEG activity of substance and opiate
dependence patients is characterized by alterations
mainly within the alpha, theta and beta bands (Alper et al.
1998; Sokhadze et al. 2008), which may be the result of
prolonged substance use itself (Ardila et al. 1991; Marchesi
et al. 1992; O’Mahony and Doherty 1996).
The limitations of pharmacotherapy and behavioral
therapy, combined with knowledge from studies on nerophysiological
abnormalities in substance dependence,
underline the need for alternative and/or complementary
therapies for these disorders, with long lasting effects and
minimal side effects (Hubbard and Martin 2001). Neurofeedback
appears to be a promising alternative due to
effects such as reduced drug seeking symptoms, improved
psychological and neurophysiological variables and longer
periods of abstinence that have been reported in the literature
after neurofeedback treatment (Peniston and Kulkosky
1989; Masterpasqua and Healey 2003; Scott et al.
2005v Sokhadze et al. 2008).
Neurofeedback as a branch of biofeedback technology, is
an operant conditioning technique used to reinforce or inhibit
specific forms of EEG activity (Scott et al. 2005v Kaiser and
Othmer 2000). It is a therapeutic method designed to train the
mind and body to act in a more optimal way in order to
improve emotional, cognitive, physical, and behavioral
experiences (Demos 2005). Today, based on the research in
neuropathology, we can use this method to turn abnormal
rhythms and frequencies (based on QEEG) into normal (or
relatively normal) rhythms and frequencies, and following
that, turn abnormal psychological states into normal ones
(Gunkelman and Johnstone 2005). Neurofeedback has been
used as a therapeutic method to treat different types of disorders,
for example attention deficit hyperactivity disorder
(Kropotov et al. 2007; Strehl et al. 2006; Rossiter 2004; Fuchs
et al. 2003), epilepsy (Kotchoubey et al. 2001), depression
(Putman 2001), anxiety and affective disorders (Hammond
2005; Vanathy et al. 1998), fibromyalgia (Muller et al. 2001),
and obsessive compulsive disorder (Hammond 2003), and
also to enhance attention andmemory performance in healthy
subjects (Wilson et al. 2006; Hanslmayr et al. 2005; Egner
et al. 2002; Vernon et al. 2003). This technique also has been
used as a therapeutic method for substance or alcohol
dependent patients, and results have corroborated the efficiency
of neurofeedback treatment on negative neuropsychological
consequences of these disorders (Sokhadze et al.
2008; Scott et al. 2005; Frederick et al. 2005; Burkett et al.
2004;Masterpasqua andHealey 2003;Lawrence 2002;Kaiser
et al. 1999; Peniston and Saxby 1995).
Alpha training was the first neurofeedback (EEG biofeedback)
protocol that was employed in substance and
alcohol dependence disorders. Research by Passini et al.
(1977) has shown the effects of alpha neurofeedback
training in reducing anxiety and improving aspects of
personality in drug dependence patients. Goldberg and
Hillier (1979) reported that their alpha conditioning program
reduced drug use and increased self-control in 4
patients addicted to opioids. Afterward the treatment of
addictive disorders by EEG biofeedback or neurofeedback
was popularized by the work of Eugene Peniston (Peniston
and Kulkosky 1989, 1991) and became popularly known as
the Peniston Protocol. In Peniston’s (1989) neurofeedback
study, ten alcoholic patients underwent approximately 40
alpha-theta brain wave training sessions. These patients
had all failed previous hospital residential treatment programs.
Eight of them remained generally abstinent at least
three years after neurofeedback treatment (Peniston and
Kulkosky 1989). This protocol also resulted in a decrease
of 13 on the millon clinical multiaxial inventory scales
(MCMI), including anxiety, whereas traditional treatment
produced decreases of only two points on these scales
(Peniston and Kulkosky 1991).
In 1992, Fahrion, Walters, Coyne and Allen replicated
these results in a controlled case study. They also reported
a decrease in stress-related, blood based beta endorphins
and in substance craving in patients. In researches completed
by Bodehnamer and Callaway (2004) and Burkett
et al. (2004) on crack-cocaine abusers improvements in
mental state, craving and neurological functions have been
reported. In another experimental study, participants who
received neurofeedback treatment (alpha-theta training)
showed significant improvement in their mood and in their
Minnesota multiphase personality inventory-2 (MMPI-2)
scales (Raymond et al. 2005). Follow-up studies showed
the constancy of treatment outcomes in alcohol or drug
addicted clients who completed an alpha-theta neurofeedback
training program (Kelley 1997; Bodenhamer-Davis
and BeBeus 1995; Trudeau 2000).
In a more recent study Scott et al. (2005) gave mixed
substance dependence patients feedback on their brain’s
134 Appl Psychophysiol Biofeedback (2013) 38:133–141
electrical activity in conjunction with conventional treatment.
They reported that their treatment doubled the
recovery rate for drug dependence. In addition to improving
the success rate for recovery from use of drugs, the
study documented significant improvements in the ability
of the experimental group to focus their thinking and
information processing. Moreover, the experimental subjects
exhibited significant improvement in some relevant
measures of psychological functioning. After only 45 days
of treatment, nearly one-third of the control group had
dropped out of treatment prematurely and left the residential
facility, compared to only 6 % for the experimental
group. Even thought all of the works presented thus far
were conducted on adults, Trudeau (2005) also suggested
that neurofeedback could be effective for helping adolescents
with substance use disorders.
Despite all these promising results, neurofeedback treatment
has not yet beenaccepted as a standard therapy for
substance dependence disorders because there are only a few
studies in this field, andmost of themhave been conducted on
alcoholic patients. In this study we examined the effectiveness
of the neurofeedback method combined with pharmacotherapy
in opiate dependence. We believe this is the first
study to examine the effects of neurofeedback treatment in
addition to Methadone or Buprenorphine maintenance treatment
(MMT/BMT) on improvement of comorbid abnormalities
in opiate dependent patients. A comprehensive
assessment was carried out on general psychological health
and substance craving. This study aimed at answering (a) if
neurofeedback treatment leads to an improvement in mental
health and craving for opiates and (b) if the two experimental
and control groups differ in mental health and craving variables.
This paper compares results from both groups.
Materials and Methods
The participants were 20 men, aged 20–50 years, who had
opiate dependence disorder according to DSM-IV-R criteria.
The main substances on which they were dependent were
opium, heroin, and/or crack heroin. The route of administration
was smoking. None of participants were intravenous
addicts. They had no additional anoxia, head trauma, stroke,
encephalitis or HIV. Participants were recruited from an
outpatient clinic for substance dependence disorders treatment.
They had received at least 3 months of Methadone or
Buprenorphine maintenance treatment (MMT/BMT) for
substance dependence disorder. Just two participants (one in
the experimental group and another one in the control group)
had been receiving Buprenorphine maintenance treatment.
For patients under Methadone maintenance treatment, Suboxone,
that has also Naloxone as a part of substance dependence
pharmacotherapy, was the formulation of Methadone
that had been used. The prescribed Methadone was in liquid
form. During the incoming phase a complete blood and urine
test had been taken from all participants. None of them had
any substance usage during the last 10 days.
After providing informed consent, all 20 participants
were initially evaluated for general psychological health
and opiate craving. The patients were then randomized into
the experimental and control groups, with the constraint
that the groups be matched regarding age (average of
30 years old), education, and general health scores. Table 1
shows key demographic information for the two groups.
Both groups were under Methadone or Buprenorphine
maintenance treatment for substance dependence disorder.
The experimental group also received 30 sessions of neurofeedback
in addition to their usual MMT/BMT.
Indeed, the patients in this study, was the same as those
contained in our previous publication (Dehghani-Arani
et al. 2010) and the treatment procedure as well. But this
paper examines a different set of measures on the subjects.
The neurofeedback program for the experimental group
lasted 2 months (30 50-min sessions). The control group
patients were receiving their usual treatment without neurofeedback.
The neurofeedback training protocols in every
session focused on Sensory Motor Rhythm (SMR) training
in the Cz (the central brain cortex) area (Scott et al. 2005)
and alpha-theta in the Pz (the parietal brain cortex) area
(Peniston and Kulkosky 1989), each lasting 20 min, using a
Thought Technology Procomp2 system.
The brain’s electrical activity was displayed on a monitor
in the form of an audio-visual exercise. The feedback
Table 1 Demographic data for the experimental and control groups
Group N Age Education (years) Abstinence (month)
Mean SD Range Mean SD Range Mean SD Range
Experimental 10 30.3 7.01 21–45 14.5 1.8 12–16 3.2 1.93 1–6
Control 10 29.1 6.5 21–40 14 1.9 12–17 3.6 2 1–7
Total 20 29.7 6.64 21–45 14.25 1.86 12–17 3.2 1.9 1–7
Appl Psychophysiol Biofeedback (2013) 38:133–141 135
informed patients of their success in making changes. The
training was introduced as a computer game in which
they could score points by using their brain waves. Participants
were advised to be attentive to the feedback and
to find the most successful mental strategy to get as many
points as possible. No other specific instructions were
given to them.
In SMR training protocol on the Cz area, the active
electrode was placed at Cz with a left-ear reference (A1).
The right earlobe was connected to circuit ground. In this
program the reinforcement band was SMR (12–15 Hz)
frequency band, and the suppressed frequency were delta
(2–5 Hz), theta (5–8 Hz) and high beta (18–30 Hz), frequency
bands. Thresholds were adjusted in a way that if the
participant maintained the reinforcement band above the
threshold for 80 % of the time during at least 0.5 s, and the
suppressed band under the threshold for 20 % of the time,
feedback was received. Whenever participants could
maintain the reinforcement band’s above the threshold for
90 % of the time during two continuous trials, the threshold
was changed automatically so that it was closer to the
optimal threshold (Scott et al. 2005).
Feedback in the alpha-theta training protocol on the Pz
area was in audio format only. In this protocol, the participants
closed their eyes, and only listened to the sound
being played to them. Three pathways connected with this
protocol were related to the theta (5–8 Hz), alpha
(8–12 Hz), and beta (15–18 Hz) frequency bands, with one
additional pathway to control delta (2–5 Hz). The initial
sessions were used to train patients to decrease alpha levels
that were above 12 mV (peak to peak), while augmenting
theta, until there was ‘‘crossover.’’ This was defined as the
point at which the alpha amplitude dropped below the level
of theta. Subsequent to achieving the first crossover, both
alpha and theta frequencies were augmented and the delta
frequency range was also inhibited. This was intended to
discourage the sleep transition during low-arousal states.
Each alpha-theta session began with the subject sitting
in a chair with eyes closed. The active electrode was placed
at Pz with a left-ear reference (A1) and right-ear ground
(A2). Two distinct tones were employed for alpha and theta
reinforcement, with the higher pitched sound used to index
the higher-frequency alpha band. At the start of each session,
the therapist spent 3–5 min reading a script of guided
imagery to the experimental subject that dealt with identified
essential elements of maintaining abstinence. After
the guided imagery, it was made clear to the subject that
the objective of the training did not involve explicit
rehearsal of the script during the neurofeedback. Subjects
reporting previous meditative practices were asked not to
use them during the training, because meditation has been
observed to override alpha-theta reinforcement effects
(Scott et al. 2005). Following the alpha-theta training,
subjects were given the opportunity to process their experience.
When it appeared that the subject’s delta activity
started to elevate and that sleep might be occurring during
training, subjects were told prior to their next session to
move a limb if they heard the therapist say for example
‘‘left hand’’. Subsequently, during sessions where delta was
elevating toward no responsiveness levels, the feedback
sounds were inhibited in order to discourage the sleep
transition. (Peniston and Saxby 1995; Scott et al. 2005).
The 28-item form of the general health questionnaire
(GHQ-28) and the 45-item form of the heroin craving
questionnaire (HCQ-45) were used to obtain general psychological
health and opiate craving information before
and after treatment.
The general health questionnaire (GHQ) is a selfadministered
screening questionnaire designed to detect
probable psychiatric disorder in primary care settings
(Goldberg 1972). It is highly popular and widely used in
research (e. g., Lobo et al. 1986; Gureje and Obikoya 1990;
Schmitz et al. 1999). It was developed by Goldberg and
Hiller in 1972 for diagnosing non psychotic mental disorders
in health centers. This questionnaire is equipped with
the proper questions to ascertain the severity of mental
disorders (Robins and Brooks 1981). Benjamin et al.
(1983) have emphasized use of the shorter 28-item version
of this questionnaire in order to save on costs and time in
important research projects, when studying the general
status of mental health of patients. The 28 section form of
this questionnaire, compiled by Goldberg and Hillier
(1979), has four subscales: physical signs, anxiety and
sleep disorders, social disorders, and severe depression
subscales. A Total score is also obtained. Reliability
coefficients have ranged from 0.78 to 0.95 in various
studies (Furukawa et al. 2001; Goldberg 1972).
The heroin craving questionnaire includes 45 questions
with a 7 level Likert scoring system (with some items reverse
scored). Respondents indicate the degree to which they agree
with each statement along a 7-point Likert-type scale ranging
from ‘‘Strongly disagree’’ to ‘‘Strongly agree’’. This instrument
provides five main subscales, all of which were included
in analysis: anticipation of positive outcome, relief from
withdrawal, intention and plan to use substance, desire to use
substance, and lack of control over use. Research supports
the validity and reliability (0.69–0.93) of the subsections of
this questionnaire in measuring the severity of craving in
patients with heroin or other opiate dependence disorders
(Heinz et al. 2006; Sayette et al. 2000).
The results obtained in the pre and post-treatment phases
for the experimental and control groups were analyzed by
the SPSS.16 tool.
136 Appl Psychophysiol Biofeedback (2013) 38:133–141
In order to check the effect of the pre-treatment phase in an
effort to find whether neurofeedback plus pharmacotherapy
(MMT/BMT) is more effective than pharmacotherapy
alone, the multivariate analysis of covariance (MANCOVA)
was used. For this purpose the scores in post-treatment
subscales of general health questionnaire and Heroin
Craving Questionnaire as the dependent variables, the
intervention (in two levels) as the independent variable and
the score of pre-treatment indexes as the covariate variables,
were used for analysis. After checking the hypothesis
of linearity, homogeneity of regression lines, and homogeneity
of variances, the effect of intervention with the
dependent variables was examined.
General Health Questionnaire
Descriptive statistics for the experimental and control
groups, pre and post, for the GHQ-28 are shown in Table 2
and graphically displayed in Fig. 1. MANCOVA results
are provided in Table 3, where it is seen that the intervention
produced significant improvement for physical
symptoms, depression, and the total score of mental health.
It can be argued that the independent variable had caused a
significant difference between the experimental and control
groups. No differences were found for anxiety or social
Heroin Craving Questionnaire
Descriptive statistics for the experimental and control
groups, pre and post, for the HCQ may be found in Table 4
and graphically displayed in Fig. 2. MANCOVA results,
provided in Table 5, show that the intervention led to
significant improvements for anticipation of positive outcome,
desire to use, and relief from withdrawal.No changes
were noted for plan to use and lack of control.
Table 2 Descriptive indexes for the GHQ-28 prior to and following treatment
Variables Experimental Control
Mean Standard deviations Mean Standard deviations
Pre Post Pre Post Pre Post Pre Post
Physical Symptom 7.9 3 3.6 2.44 8 7 3.6 4.16
Anxiety 8.5 5.4 3.13 2.71 8 7 3.57 4.9
Social Functions 7.1 5.4 4.53 2.75 7 6 4.88 3.4
Depression 7.5 2.3 5.7 2.4 8 6 6.24 5.08
Total Scores 31.1 16.1 11.64 8.03 32.4 26.9 15.32 11.68
Fig. 1 Pre and post results of GHQ subscales in Experimental and
Table 3 Results of MANCOVA for GHQ subscales in the experimental
and control groups
Variable F Sig. Eta squared
Physical symptom 6.37 .02* .35
Anxiety 1.41 .25 .09
Social functions .18 .67 .02
Depression 4.36 .04* .27
Total scores 4.27 .04* .26
df = (1,19)
Appl Psychophysiol Biofeedback (2013) 38:133–141 137
The purpose of the present study was to explore if neurofeedback
training could enhance existing treatment for opiate
dependence disorder. Although previous attempts at using
neurofeedback as a treatment method have showed positive
results, such studies have typically possessed a number of
technical limitations that have reduced their usefulness especially
as regards opiate disorders. For instance most of them
have been focused on alcoholic patients and there are few
experimental studies with a control group for opiate dependence
disorders. Further, most of the latest research has consisted
of case studies. Furthermore none of them has carried
out studies comparing neurofeedback and Methadone or Buprenorphine
maintenance treatment. Therefore in the present
experimental study we examined the effectiveness of neurofeedback
in comparison with MMT/BMT in two groups of
opiate dependence patients, with a pre versus post treatment
evaluation. This study focused on general psychological
health and opiate craving in patients.
Neurofeedback was shown to decrease the craving to
use substance and improve general mental health in opiate
dependence patients. Some studies on alcohol dependence
patients (Passini et al. 1977; Bodehnamer and Callaway
2004; Burkett et al. 2004; Raymond et al. 2005) found
improvements like ours when comparing treatment to
controls. For example, Scott et al. (2005) showed an
increase in psychological health in mixed substance
dependence patients receiving neurofeedback training,
while Passini et al. (1977) and Peniston and Kulkosky
(1989, 1991) found significant differences regarding anxiety
signs in their study, that we could not achieve it in this
study. Results obtained from the latest studies were based
Table 4 Descriptive indexes of the HCQ prior to and following treatment
Variables Experimental Control
Mean Standard deviations Mean Standard deviations
Pre Post Pre Post Pre Post Pre Post
Anticipation of positive outcome 29.3 19.4 8.65 4.11 29 29.3 8.56 15.82
Intention and plan to use 15.53 13.7 5.95 5.63 15.5 16.3 5.96 8.08
Desire to use 14.5 11.3 5.93 5.37 14.3 16.7 5.93 8.38
Lack of control over use 12.8 10.7 5.49 4.9 12.8 12 5.49 8.21
Relief from withdrawal 18 14.42 4.77 5.27 18.12 19 4.95 9.63
Fig. 2 Pre and post results of HCQ subscales in Experimental and
Table 5 Results of MANCOVA for HCQ subscales in the experimental
and control groups
Variable F Sig. Eta squared
Anticipation of positive outcome 9.32 .009** .41
Intention and plan to use .09 .77 .0
Desire to use 10.48 .006** .45
Lack of control over use .5 .49 .04
Relief from withdrawal 5.97 .03* .32
DF = (1,19)
DF degrees of freedom
138 Appl Psychophysiol Biofeedback (2013) 38:133–141
on long term neurofeedback training; however the current
study has been able to obtain the same results, except for
anxiety, but over a much shorter period of time. Continuing
therapy could potentially lead to additional positive outcomes
such as improvement in anxiety.
Our results, combined with those of others, suggest that
neurofeedback training over a long period may be more
effective than pharmacotherapy alone in treating substance
use and in promoting mental health. Although pharmacotherapy
can lead to some improvements in patients, side
effects, instability, and the high risk of relapse, are some of
the main limitations of using pharmacotherapy alone
(Fagan 1994; Gossop et al. 2002). Neurofeedback attempts
to address the fundamental operational functions of the
brain and acts as a mechanism for the brain to self-regulate.
Its goal is to correct irregular brain functions and consequently
improve psychological abnormalities. Furthermore
research confirms the stability of neurofeedback effects and
its prevention of negative side effects (Hammond 2005).
Thus pharmacotherapy can be used to maintain the initial
balance between physiological and psychological health in
substance dependent patients (Gossop et al. 2002), and then
neurofeedback training can be used to guide the patient
towards longer lasting health and balance.
There are several opinions about the fundamental mechanisms
of effectiveness of neurofeedback training as a
therapeutic method in substance use disorders. Several (Ochs
1992; Peniston 1994) suggest that the most active (and
apparently transformational) properties of neurofeedback
protocols in substance dependency treatment involve
teaching participants to intentionally increase the amplitude
and coherent interaction of both their alpha and theta
brainwave frequencies in either of the brain locations. The
mechanism of alpha-theta neurofeedback may lie in its
ability to allow participants to better tolerate stress, anxiety,
and anxiety eliciting situations, which are particularly evident
during the initial phases of recovery (Scott et al. 2005).
Some other theories focus on conditional normalization
of reinforcement systems in the brain. Blum et al. (2000),
focusing on the reward deficiency syndrome that leads to
substance craving, suggested that neurofeedback training
can initiate a neurological normalizing shift. Following this
idea, some studies stated that an apparent neurological
‘‘normalization’’ is responsible for shifting the trained
subject into a physical state of comfortable calmness.
When chemically dependent patients are calm they often
have a neurologically based inability to experience pleasant
feelings from simple stimulation (Fahrion et al. 1992;
Salansky et al. 1998). Dysfunction of this pleasant feeling
is the most important factor ‘‘forcing’’ patients to feel
craving and to use substances (Kreek et al. 2005).
On the other hand Cowan (1994) suggested that the
apparent effectiveness of such training may be due to the
enhanced imprinting of positive temperance suggestions
and the feeling of inner empowerment which the alphatheta
state seems to encourage. In another opinion, McPeak
et al. (1991) suggested that self-induced altered-states such
as those found in various forms of meditation, can sometimes
replace the self destructive pursuit of alcohol and
drugs. On the basis of this, Rosenfeld (1992) questioned
whether there would be any difference between Peniston’s
neurofeedback protocol, general relaxation, and hypnotic
suggestion. Others suggest that the same results can be
accomplished with meditation procedures alone (Taub
et al. 1994).
Finally, as studies have shown, in the treatment of
substance dependence disorder, no single program can lead
to a cure by itself (Gossop et al. 2002). While taking into
consideration the complexity of the dimensions of this
disorder, treatment programs must be able to affect various
factors and not be prone to the problems of previous
methods, such as relapsing, instability, and other side
effects (Trudeau 2000). The results of this study suggest
neurofeedback training may produce additional benefits for
increasing mental health in patients addicted to opiates, as
well as being feasibly integrated with other methods.
In the current study, although we tried to control different
factors in the process of neurofeedback training, due
to the fact that we used technology in neurofeedback, and it
is a new method, patient’s hope and motivation for the new
treatment, could have heightened the effects noted. Despite
this, the use of a placebo group could have strengthened the
current design of the program and created more control
over other aspects of the program. The high costs of the
technology and time involved in neurofeedback, it was not
feasible to use a placebo group. Future research projects
need to consider incorporating attention/placebo condition
to control the effects of interfering factors, so that the
benefits of neurofeedback training can be seen more
clearly. Inclusion of larger samples and longer term outcomes
are needed to increase the level of validity of the
results as well. Furthermore, the current research could not
be carried out on patients with opiate dependence without
also using the pharmacotherapy. In the future studies, one
group should receive neurofeedback without receiving
pharmacotherapy, which will permit a test of the individual
and unique contributions of each approach. Finally in this
study we did not repeat blood and urine tests for substance
use. So we could not mention the abstinence range during
the study. Future studies should include continuous
assessments of these types.
Open Access This article is distributed under the terms of the
Creative Commons Attribution License which permits any use, distribution,
and reproduction in any medium, provided the original
author(s) and the source are credited.
Appl Psychophysiol Biofeedback (2013) 38:133–141 139
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