New York, SOARS Program:  Study Outcome Data

Adriana Steffens, PhD, BCN

Thomas Bolton, MA, BCTc


Eight-five (85) female and fifty-seven (57) male adults, ranging in age from 19 to 70 years (average age = 38), voluntarily participated in substance abuse counseling augmented by Mini-Q evaluation and at least 20 neurofeedback sessions, as part of the four year New York State-funded SOARS study.  Some abused alcohol, some abused one substance of choice, but many were poly drug-users.   Outcome measures included self and family reports of sustained abstinence, and comparison of pretreatment versus post-treatment measures for percentage of change on the MiniQ assessment, the DASS (assessing depression and anxiety), and an individualized Symptom-Tracking measure.  Completion rate of the study was 63% (dropout rate of 37% included participants who completed 10 or fewer neurofeedback sessions following initial assessment).  Completers reported a 93% rate of successful sustained abstinence, averaged a 34% improvement on the MiniQ (reflecting a process toward normalization of brainwave patterns) averaged a 43% reduction of self-reported emotional distress (e.g. depression, anxiety) on the DASS measure, and averaged a 38% reduction of their self-identified most problematic emotional/behavioral symptoms, as assessed via the Symptom Tracker.   The very promising results of this naturalistic research (program evaluation) are discussed in terms of a strength of ecologic realism (in paralleling what occurs in actual clinical practice where adjunctive neurofeedback is incorporated into substance abuse treatment), and with regard to research design limitations and restricted generalizability, owing to uncontrolled factors which may have influenced the findings.  Replication of the findings with improved design and statistical analytic procedures was recommended.



Drug abuse and addiction continues to devastate society on many levels.  A 2012 survey published by the Substance Abuse and Mental Health Service Administration (SAMHSA) found that the estimated number of heroin users in the United States has nearly doubled since 2007 (373,000 in 2007 to 669,000 in 2012)1.  In 2012, an estimated 156,000 individuals tried heroin for the first time, a significantly higher number of first-users than reported only six years earlier in 2006 (90,000).1 According to the National Drug Control Budget, the estimated cost of drug treatment programs in 2007 was $6.5 billion.  The budgeted amount has increased each year, with a the budget in 2015 set at $10.3 billion- an increase of $3.7 billion over 8 years.  During the same time span, the federal government decreased the amount of money devoted to drug prevention programs, from $1.9 billion to $1.3 billion, or a decrease of roughly $628 million. This type of budgetary cutback suggests that drug treatment prevention (and treatment) programs  are being accorded lower priority, possibly because they are not viewed as a cost-effective investment.    Yet, without such treatment, rates of drug use and relapse remain at an all-time high.  For example, a 2002 study found that about 60% of heroin addicts will relapse within one year (Gossop et al., 2002).  In order to procure sufficient funding, addiction treatment programs must utilize effective methods which significantly reduce relapse rates, and help to prevent relapse.  This would demonstrate that federal and state funded programs are having the desired impact (and by implication, saving money in the long run).

SAMHSA researchers also investigated individual alcohol usage. They found that nearly one quarter (23.0 percent) of persons age 12 and above admit to a binge alcohol pattern  - defined as consumption of five or more normal-sized alcoholic drinks on the same occasion during one day within the past 30 days – or roughly 59.7 million people.  The survey also found that roughly 17.0 million people reported heavy drinking (binge drinking on 5 or more days in the past 30 days). Additionally, an estimated 1.7 million underage persons (ages 12 to 20) were heavy drinkers (SAMSHA, 2012).

A follow up report, also published by SAMHSA, surveyed substance abuse facilities regarding the type of treatments being provided as well as the numbers of individuals receiving services. The report states, “Both the total numbers of substance abuse treatment facilities and clients in treatment increased slightly between 2003 and 2013.  The number of clients in treatment on the survey reference date increased by 14 percent, from 1,092,546 in 2003 to 1,249,629 in 2013.  Outpatient treatment was the most common form provided, offered by 82 percent of all facilities and was received by 90 percent of all clients in treatment.  Residential (non-hospital) treatment was offered by 24 percent of all facilities and was received by 9 percent of all clients in treatment.  Hospital inpatient treatment was offered by 5 percent of all facilities and was received by 1 percent of all clients in treatment” (SAMHSA, 2012).

The typical cost for outpatient addiction treatment is $10,000, and most private residential alcohol and drug rehab facilities charge between $20,000 and $32,000 for a typical 21 to 28 day stay, depending upon the level/intensity of services needed.  If one agrees with the finding that 60% of addicts typically relapse within one year, even with traditional forms of inpatient or outpatient treatment, then it could be argued that funds spent on  traditional outpatient treatment services, regardless of who has actually paid for the service, is not yielding cost-effective results (Gossop et. al., 2002).

Abnormal Brainwave Patterns Associated with Substance Addiction

Recent advances in neuroscience research has revealed abnormalities in brain function among various subtypes of addictive behavior, and addiction proneness.   Detoxified alcohol-dependent patients have been found to manifest lower overall brain power  (EEG total magnitude) relative to the normal controls (Niedermeyer and Lopez Da Silva, 1982; Johnstone, Gunkelman, and Lunt, 2005), and a relative power distribution  characterized by excessive fast wave (Beta or High Beta frequency) activity (e.g. Johnstone, et. al., 2005) and/or a deficiency in slow wave (Alpha and/or Theta range) activity (Olivennes et al. 1983; Peniston and Kulkowsky, 1989; Bauer, 2001a;  Saletu, et. al., 2002; Saletu-Zyhlarz, et al, 2004;  Polunina & Davydov 2004; Franken et al. 2004. )  Though not well researched, it has been hypothesized that this pattern involving cortical over-arousal  and/or under-arousal is heritable, and may predispose an individual to addiction as well as other disorders (Finn and Justus, 1999).   Alcohol consumption has been found to temporarily increase amplitudes of alpha and theta waves, thereby reducing cortical arousal, bodily tension, and enhancing subjective feelings of relaxation and well-being (Peniston and Kulowsky, 1989).   Hence, though having toxic effects upon the mind and body and negative consequences which accrue over time, in the short run it may act as a form of ‘self-medication’.  CNS hyperarousal is a physiological condition common to clinical problems, such as Anxiety, mixed depression-anxiety, OCD, and trauma-related disorders.          For example, prolonged hyperarousal of the right cerebral hemisphere has been associated with anxiety, inability to relax; chronic excess bodily tension, and proneness to panic states (Engels et. al. 2007; 2010).


A subset of addicts appears to be persistently cortically under-aroused (excessive frontal-central slow wave activity in resting state, similar to the pattern seen in ADHD and Depression) and would appear to have an inherent need to self-stimulate/active their brains to maintain homeostatic balance.   For example, stimulant addicts, as a group, have been found to demonstrate a QEEG pattern involving excessive slow wave activity fronto-centrally, with elevated High Beta wave activity over the anterior and posterior cingulate gyrus or ‘vertex pattern’ (Alper et al. 1990; Noldy et al. 1994; Prichep et al. 1996; Roemer et al. 1995; Trudeau et al. 1999).   Cocaine users have been found to show increased alpha relative power fronto-centrally, and in the parietal region.  Methampethamine users have been found to exhibit increased power in the slower waves, Theta and Delta, compared with non-drug using controls (Newton et al. 2003).  Increased Theta amplitude has been associated with mental states of reverie, dreaminess, fantasy, vivid imagery, and has been associated with reports of a ‘high’ with use of cocaine. (Reid et. al., 2006).   The elevated Theta and Delta amplitudes associated with Methamphetamine use are also correlated psychomotor slowing and frontal executive function deficits.


The natural course of addiction to these powerful mind-altering substances includes the disruption of production, storage, and release of neurotransmitters.   With chronic use, certain slow wave abnormalities become more pronounced, as the brain has become metabolically and biochemically challenged and no longer capable of generating the level of energy/activation required to produce higher frequencies.  For example, chronic stimulant abusers have been found to produces excess alpha amplitudes (excess idling state of the brain), with a deficit in Delta amplitude – the latter which has been correlated with the process of CNS demyelination (Alper et al. 1990;) and/or increased sensitivity of the EEG to the toxic effects produced by psychostimulants (Noldy et al. 1994; Prichep et al.;  Roemer et al. 1995; Trudeau et al. 1999).


A ‘vertex’ pattern (of  slow wave and fast wave activity) has been described in the literature, involving abnormally high amplitude of slow waves (2 to 10 Hz )together with excessive fast wave activity (elevated amplitudes of High Beta or >20Hz activity) along midline sites Fz, Cz, Pz, and Oz.   Such an abnormal pattern of activity at these sites (corresponding anatomically to the anterior and posterior cingulate gyrus) is hypothesized to involve projections from ‘dysregulated’ limbic areas which increase the potential for emotionally reactive, volatile and impulsive behavior.  The cortex compensates (to maintain a sense of stability) by over-producing High Beta waves, associated with inhibition, rigid control, and bodily tension.  This dysfunctional state of neostasis is associated with behaviors such as compulsivity, obsessive behaviors, rumination, fear and anxiety.   Connectivity/communication  patterns across hemispheres (homologous sites) also become disrupted, as indicated by phase and coherence abnormalities.  Coherence abnormalities have been associated with poor integration of the various cognitive functions needed for effective problem solving (Fingelkurts et al, 2006b).

An important prognostic finding is that hyperarousal of the frontal-central cortex (e.g. cingulate), such as overactivity in the High Beta range (>20Hz), especially at midline site Cz, is the single best QEEG predictor of poor treatment outcome and premature dropout/relapse (Winterer et. al., 1998; Bauer, 2001a. ).  That is, addicts whose resting brain state is persistently cortically hyper-aroused, especially along the central/midline area, are more likely than other addicts to have poor response to treatment, and much more prone to relapse than addicts whose resting brain state is less excitable/overaroused.   A related hypothesis is that these hyper-aroused relapsing patients require more CNS sedation than other patients who are trying to abstain from substance use (Sokhadze, Cannon, and Trudeau, 2008a; 2008b).

For a more in-depth review of QEEG/Neurofeedback research findings with addictions, , the reader is directed to the analysis by Sodhadze, et. al. (2008a; 2008b).   The present review is limited to studies most directly relevant to the present study focus.  But armed with this knowledge, the neurofeedback practitioner can now intervene in a more targeted and scientific manner, by using information about brain functioning to guide clinical hypotheses and specific interventions for each individual, in addition to the more generic aspects of addiction treatment.

Neurofeedback’s Efficacy as an Adjunct To Addictions Treatment

Accumulating evidence indicates that interventions designed to modify or even reverse anomalies in brain functioning (via medication of brainwave patterns) can yield improved rates of abstinence when combined with traditional forms of addiction treatment.

Neurofeedback for additive behaviors is an adjunct to other interventions.  It involves teaching the client basic relaxation and visualization skills to aid in calming the central nervous system.  Other forms of biofeedback may be utilized, such as yoga type breathing exercises, and neuro-meditation (incorporating Alpha, or Alpha-Theta training) which aims to guide the client’s brain into a receptive observer state where memories and emotions can be more easily accessed and experienced.   The person moves from a relaxed inactive state of awareness into a dreamy, often surreal, subconscious state where hypnogogic imagery, sounds, or sensations may briefly be experienced, as feedback is provided by changes in sounds which signal deeper or shallower levels of (sub) conscious awareness.

The earliest forms of neurofeedback treatment utilized the alpha-theta brainwave training protocol with success in published studies of inpatient alcoholic veterans (e.g. Peniston & Kulkowsky, 1989); and poly-drug users  (Scott et. al. 2005),  and effectiveness of the alpha-theta component in addictions treatment has replicated by others, in inpatient/residential and outpatient populations.     Eugene Peniston PhD. and Paul Kulkosky PhD., were the first to incorporate neurobiofeedback (Alpha-Theta training) and standard biofeedback (e.g. handwarming exercises, autogenic training, visualization) into a standard VA (12 step orientation) inpatient alcohol/substance rehabilitation program for veterans referred by their primary care physicians.  In the 1980s, VA inpatient/residential stays for addiction treatment were much longer than today, often 3 to 6 months in length.   Assigning veterans to an experimental group of N= 20 receiving both conventional treatment and a biofeedback/neurofeedback protocol  (vs. a conventional treatment control group of  N = 10), they began by teaching veterans how to use biofeedback techniques to reduce arousal level and calm themselves.   When the veterans were able to use these skills successfully, a second phase began involving 30 consecutive days of 30 minute alpha-theta training  (using a monopolar montage, with active sensor at O1,  and reference and ground sensors on the ears).

The alpha-theta method started with uptraining of the amplitude of the Alpha band (8 – 12 Hz) where participants received positive reinforcement (e.g. pleasant reward tone) each time they relaxed in a certain way to produce Alpha waves.   When alpha is dominant in the EEG, the individual experiences a passive state of   idling and relaxation, characterized by attention to the ‘here-and-now (conscious awareness of the present, without active cognitive processing).   A visual metaphor is often given of a ‘stream’ of consciousness.  Having attained a state where the dominant amplitude is in the Alpha frequency,  reinforcement is then proportionately shifted to the production of Theta waves (these may range from 4 to 7 Hz).   When the amplitude of Theta waves predominantes, the participant will experience a dreamlike state of reverie, with access to images of old memories and associated emotions, and other sensory phenomenoa.  Close to 10 minutes into the session, there may be a moment of crossover where the amplitude of Alpha (reducing) and the Theta (increasing) momentarily overlap at the same amplitude, the person may experience hypnogogic hallucinations and sudden insights/awareness.   After spending several minutes in Theta, reinforcement shifts to bring them back into the Alpha state where they can bring the memories and experiences to conscious awareness.

This reinforcement pattern designed to facilitate alternation between states of Alpha and Theta continues for the remainder of the session.  In some cases, it is followed by 10-15 minutes of reinforcement of Alpha, to help the individual emerge from a drowsy state into a more alert but relaxed state.   The outcome was remarkable of the Peniston and Kulkowsky studies was nothing short of remarkable; those in the experimental group showed improvement at termination of treatment, and more importantly, they sustained high abstinence rates of 70% for up to a year, relative to a much lower rate of abstinence in the control condition alone (treatment as usual).

Fahrion  (1992, 1995) studied one alcohol client intensively during an alpha-theta training session.  The subject had been abstinent for 18 months but was experiencing stress-related craving for alcohol and fears of relapse.  Incorporating EEG biofeedback significantly lowered stress and increased relaxed states which significantly reduced cravings.  Fahrion and colleagues replicated the Peniston and Kulkowsky study with 39 felony-convicted inmates undergoing addiction treatment, and similarly found at 13 month post-treatment follow-up that approximately 80% maintained abstinence (Fahrion, 1992).

Bill Scott, PhD. and David Kaiser, PhD conducted what many consider the ‘cadillac’ study of incorporating both fast wave and slow wave (alpha-theta) training into an existing treatment program.   Sponsored by UCLA (CRI-HELP study), 121 polysubstance dependent patients undergoing intensive residential treatment based on the “Minnesota Model” (12-step treatment supported by group, family, and individual counseling) were randomly assigned into a control group (treatment as usual, no neurofeedback) and an experimental group (treatment as usual, plus neurofeedback).   Experimental subjects were pre-assessed via the Test of Variables of Attention (The TOVA Company, 1991) and the MMPI.   The TOVA data were used to determine if subjects were primarily inattentive (hypo-aroused) or impulsive (hyper-aroused) subtypes, in keeping with the DSM-III subtypes identified at that time.

Experimental patients were given 10 to 20 sessions of neurofeedback, with the goal of ‘normalizing’ their performance on the TOVA.   This neurofeedback initially consisted of training the left hemisphere at sites Fpz and C3 [Enhance Beta (15 to 18hz) ; Inhibit Delta-Theta (2  to 7 hz) and Inhibit High Beta (22-30 Hz then shifting to right hemisphere training at sites C4 and Pz [Enhance SMR (12 – 15Hz); Inhibit Delta-Theta (2 to 7 Hz) and High Beta (22 – 30 Hz).]

The sites were chosen by co-author, David Kaiser, to maximize coverage of the cortex with the fewest number of sites.   Fast wave training (Beta/SMR) to re-stabilize the EEG was developed and advocated by Barry Sterman, Joel Lubar, and Susan and Sigfriend Othmer, pioneers in the field of neurofeedback treatment.    Experimental subjects were re-assessed with the TOVA after 10 neurofeedback sessions;  if TOVA scores had normalized, they were then switched to a single channel monopolar montage Alpha Theta protocol at Site Pz, where Alpha was reinforced (8 – 11 Hz) and Theta was reinforced (5 to 8 Hz).   Alpha-Theta sessions  were conducted (twice per day for 15 consecutive days; each session lasting up to an hour on average) used relaxation induction and imagery scripts.

Statistically and clinically significant improvements were obtained by the experimental group on MMPI clinical scales, as compared to the control group.  Experimental subjects stayed in treatment significantly longer compared to the control group.   At one-year post study, 36 of the 47 completing experimental subjects were abstinent, compared to 12 of 27 control subjects.     Anecdotally, the Chairman of the CRI-Help study reportedly remarked, “It must be recognized that we are dealing here not only with typical research subjects but rather with the most difficult type of addict currently in rehabilitation.  Most were assigned to CRI-Help by the courts or their care was otherwise mandated.  To have observed this kind of improvement over what we consider to be a model, state-of-the-art program already is simple remarkable.”  He concluded that when these results are confirmed in other studies “they will change the standard of care in the field.”

EEG biofeedback was also used in the Kansas prison system on criminal subjects characterized as “hard-core” addicts, also producing significant improvement when incorporating the alpha-theta protocol.    Fahrion, et. al. (1995) reported the results of a randomized study of alpha-theta training on 520 inmates, using group-training equipment.  There were about equal numbers of alcoholics, marijuana and cocaine users in the experimental and control groups.    While initially there appeared to be no significant overall difference between experimental and control groups at a two year outcome followup, further analyses of age, race, and drug of choice revealed Neurofeedback to be a more effective treatment for younger, non-white, and non-stimulant substance abusers, who were less likely to relapse than the controls.   In contrast to the findings of Scott, et. al., cocaine abusers did not appear to benefit from the neurofeedback training.  However, the methodology differed from Scott, et. al., and did not include use of the TOVA, nor did it include preliminary Beta/SMR training to normalize TOVA scores.

In recent years, financial for additional neurofeedback research has been approved by the National Institute of Health and the National Institute of Mental Health, due to the promising findings of the aforementioned seminal studies.   In an NIMH-supported study examining the efficacy of EEG biofeedback in treating opiate dependence disorder, Dehghani-Arani et al. (2013) used neurofeedback (consisting of sensory motor rhythm training at central-midline site Cz, followed by an alpha-theta protocol at parietal-midline site Pz), and found not only improved abstinence rates among individuals with opiate-abuse disorders but other psychological improvements as well.  A multivariate analysis found the experimental group to show significantly greater reduction in reports of somatic symptoms, depression, and general mental health composite scores than control subjects.  They also found decreases in self-reported ratings of desire to use opioids, and reduction of craving/withdrawal symptoms, relative to the control group. The study supports the effectiveness of neurofeedback training as a therapeutic method in opiate dependence disorder, in supplement to pharmacotherapy.

Anecdotally, there are several limitations of using alpha-theta approach.   It requires many sessions (e.g. Scott et. al. performed 30 to 45 sessions in their study, employing a combination of traditional neurofeedback, alpha-theta, and alpha training sessions).  Patients can experience intense abreactions (emotional and sensory-perceptual experience during the session) which can be difficult to tolerate, or even frightening.  Moreover, patients who have recently withdrawn from benzodiazepine, barbiturate, or opioid-based medications or substances may achieve limited benefit from alpha-theta therapy, from anecdotal reports of neurotherapists.  Persons with EEG profiles involving excessive slow wave activity (high amplitudes of  Delta, Theta, Alpha) might even show worsening of concentration and mental alertness/cognitive efficiency when given the original Peniston alpha-theta protocol alone (without some preliminary normalizing of the EEG with fast-wave training).

QEEG-guided neurofeedback may present a viable alternative option to augment traditional addiction treatment.   Quantitative EEG (QEEG) assessment involves subjecting raw EEG data to computer-based Fast Fourier (analog to digital) transformation  to create a topographical brain map, yielding mathematically and statistically-derived indices of aspects of brain functioning (e.g. amplitude, phase/coherence, dominant frequency, asymmetry analysis).   The brainmap (QEEG) is used to develop individualized protocol that identifies sites that are statistically most deviant from average, and which frequencies should be enhanced vs, inhibited (based upon the topography of the map).  By beginning to normalize the EEG, the brain begins to function more optimally and flexibly, with increased self-other awareness, and better control over mood states and behavior.  With less intrusion of mood states to prompt cravings, and an overall arousal pattern that is closer to normal, the need for substances to self-regulate moods may diminish as well as interest in the substance.


Study Design and Hypothesis

The present study tested the hypothesis than inclusion of QEEG-guided Neurofeedback in a ‘treatment as usual’ addiction program (involving individual counseling, psychoeducation, and in some instances psychopharmacologic management) would result in a higher-than-expected percentage of improvement in participants.   Unfortunately, outcome data were unavailable for comparison  with regard to NY state-funded programs utilizing ‘treatment as usual’ approaches, nor did we have the option of including a no-treatment control group, for ethical and practical reasons.

The present study, which occurred over a 4 year period, was funded by the State of New York, Office of Research for Mental Hygiene, and conducted between 2010 to 2105.  A total of 188 consenting participants seeking addictions treatment volunteered to receive an abbreviated form of Quantitative Electroencephalography (QEEG) called MiniQ, as well as EEG biofeedback (also known as neurofeedback) to assist in maintaining recovery.  Individual assessments were conducted via 2 channel, 12 site, Mini-QEEG studies, in both eyes-closed and eyes-open conditions; raw data were inspected and artifacts removed, prior to processing of the raw data via the New Mind clinical QEEG interpretive system (developed by Neurofeedback Pioneer, Richard Soutar, Ph.D.).   Based upon the results of the eyes-open QEEG brainmap, individualized treatment protocols were developed for each client.  EEG neurofeedback sessions were provided to clients individually by BCIA-certified Neurofeedback practitioners.   The research program initially allowed for only 20 one hour EEG biofeedback sessions, although the number of sessions was increased later in the program based upon the tremendous amount of positive feedback provided by both clients and the addictions professionals providing counseling.  The professionals included addictions counselors, social workers and drug court teams.  By the last year of the program, some participants had received as many as 50 EEG biofeedback sessions.  The subjects, all of whom participated voluntarily, were referred for alcohol abuse and/or substance abuse which included heroin, crack/cocaine, opiates, and methamphetamine.




One hundred forty two volunteers, enrolled in the NYSOARS program in an upstate N.Y. area, engaged in QEEG-Guided neurofeedback training.  There were 85 females and 57 males.  Participants ranged from 19 to 70 years of age, with a mean age of 38 years old; many were poly-drug users.  (With regard to study attrition, participants who completed fewer than 10 sessions of neurofeedback training were considered study dropouts, and their data was omitted from the final analysis, which focused solely on study completers.)   After undergoing informed consent procedures, each participant was administered an abbreviated Quantitative Encephalograph (Mini-Q) in both eyes-closed and eyes-opened conditions.  Visually inspected and artifacted “qat” data files for each participant were uploaded to the NewMind QEEG Database for data processing/analysis, which included normative comparison with average adults and with a clinical sample, to ascertain  degree of statistical deviation from the normative range, defined as within plus/minus 1 standard deviation.

Based upon map topography and various mathematical computations (e.g. total amplitude, relative amplitude, dominant frequency, coherence, asymmetry, etc.), suggested training protocols derived from a ‘best fit’ proprietary algorithm generated from the eyes opened MiniQ map, or in some cases from eyes-closed map (depending upon whether or not the individual can better tolerate the eyes opened or eyes closed training procedure).   Prior to MiniQ assessment, each participant completed an intake interview from a local recovery support center that screened them for criteria for inclusion into the program (evidence of an addiction; willing/able to comply with training; willing to engage in individual or group counseling oriented toward alcohol/substance abstinence incorporating psychoeducation, monitoring, and relapse prevention principles).



Overview of MiniQ Assessment and Neurofeedback Methods

All participants received trained based on their individualized treatment protocol, tailored from MiniQ results via the New Mind Expert QEEG System.    Participants attended group counseling or individual counseling with a licensed Clinical Social Worker or Certified Addictions Professional.   Some participants were being prescribed psychotropic medications by their primary care medical provider or by a Psychiatrist.

The majority of participants engaged in two neurofeedback training sessions per week; a small percentage completed only one session per week.  Two sessions per week is the prevailing (but not rigidly applied) agreed-upon standard among Neurofeedback practitioners.  None of the participants completed less than one session per week.

The MiniQ data was recorded using Brainmaster Atlantis Mini Q II hardware, and Brainmaster version 3.7 software.  The Mini-Q protocol involves serial (pairwise) acquisition of data from twelve 10-20 sites.   Six pairs of sites are measures (one pair at a time) for one continuous minute of recording, with site pairings as follows:    Fz-Cz; F3-F4; C3-C4; P3-P4; T3-T4; O1-O2.   To facilitate data collection, participants were fitted with an electrocap (Electrocap International, Inc., Dayton, Ohio) which incorporates linked ears reference electrodes, and ground electrode within the cap.   After cleaning the scalp and earlobes with an alcohol pad, electro-conductive gel (“electrogel”) is injected with a blunt-tipped syringe at various 10-20 sites around the cap, and connections are checked for clear signal and acceptably low impedence, prior to data acquisition.   Six minutes of data are acquired (on the six site pairs) first in the eyes closed position, and then in the eyes opened position.   Maps are typically acquired between 9am and noon, to minimize effects of diurnal variation upon the QEEG.  Participants are shown types of artifacts that can occur (e.g. physical movement, eye blink, eye movement, muscle bracing or tensing, etc.) and asked to remain as still as possible during each measurement (with breaks between measurements) to minimize the occurrence of artifacts (false readings) in the raw data.

Suggested training protocols for amplitude training were derived from the New Mind Expert QEEG system, based upon eyes-open or eyes-closed analyzed map data  and a proprietary clinical algorithm.   Each training protocol was individually tailored to the individual’s own unique brainwave pattern, based upon areas of strength vs. weakness with regard to location (focal 10-20 sites, homologous site pairings, regions), and quantitative measures of total EEG power, relative power (amplitude) per frequency band, dominant frequency (highest amplitude within a frequency band), inter-hemispheric coherence between homologous left/right site pairings, and asymmetry comparison of the left vs. right hemisphere.   For the sake of simplicity, patterns could be described in terms of any combination of ‘brain too slow’ (elevated amplitudes in Delta, Theta, and Alpha frequency ranges), ‘ brain too fast’ (elevated amplitudes in the Beta and High-Beta frequency ranges), hypo-coherent (homologous site is under-communicating), hyper-coherent (homologous site pairing is over-communicating), and asymmetry (in the alpha band, right > left is expected, with left > right associated with physiological and psychological aspects of depression; in the beta band, left> right is expected, with right > left associated with physiological and psychological aspects of anxiety).   Midline analysis is also performed, as certain disorders (ADHD, OCD) and their subtypes have been found to involve abnormal amplitudes in certain frequency bands.

Training involves setting reinforcement ratios, for training up amplitudes (enhance or Go) or training down amplitudes (inhibit Stop), or no training (Ignore).  Typical reinforcement ratios involve rewarding (positive reinforcement) for either increasing or decreasing a particular frequency band(s), and the optimal range is generally rewarding 70% to 80% of the time.  (Rewarding 100% of the time for correct responses would make the task too easy, and would become dull and unchallenging.  Rewarding infrequently, such as 50% or 60% of the time would make the task too difficult and frustrating, referred to as ‘ratio strain’).  One a participant starts performing well, the neurotherapist adjusts (lowers) the reward ratio to make the task a little more challenging and effortful, but without causing ratio strain and fatigue.  Brief breaks are permitted, when the participant requires them, and no reinforcement occurs during that idle period.  If the task is clearly too difficult, the neurotherapist makes it easier by gradually increasing the reward ratio.   One frequency that is always inhibited, at an easy rate (90% reward) is High Beta.  Abnormally elevated amplitudes of High Beta are unwanted for several reasons.   High Beta is associated with anxiety, and muscle bracing/tension, and we do not want to encourage or reward (reinforce) anxiety and muscle tension.

Different frequency bands are reinforced, for each hemisphere.  For example, in ‘asymmetry training’, Beta (15 – 20Hz)  is often trained up at a specific site(s) in the left hemisphere (if amplitude is too low and needs to be increased), and may be trained down (inhibited) in the right hemisphere (if Beta amplitude is too high there).   SMR or Low Beta (13-15 Hz), and/or Alpha (the central 9 - 11 hz part of the band) are often trained up in the right hemisphere.   Excessive amplitudes of slow wave (Delta, Theta, and/or Alpha) activity (+1 or +2 SDs above normal range) are trained down in one or both hemispheres, depending upon what the QEEG shows.   In some individuals, midline sites (e.g. Fpz, Fz, Cz, Pz, Oz) may be trained, reinforcing or inhibiting certain frequency bands.   Again, the type of training depends on the topography of the map (site locations statistically identified as most deviant from Z = 0) and the calculated indices (e.g. amplitude, asymmetry, coherence) requiring remediation.   Some trial and error using clinical experience and judgement, may also necessary (if a participant is not showing progress, moving slightly off site, or to a different site location;  reducing the number of indices being simultaneously trained or adjusting the reinforcement ratios).

“Amplitude training”, which involves training up or down amplitudes of certain frequency bands at homologous sites and/or central sites, is the traditional and most researched form of neurofeedback.  Amplitudes are measured in microvolts (millionths of a volt).  This is accomplished via careful preparation of the scalp and placement of sensors,  and a very sophisticated yet compact analog to digital EEG box (such as Brainmaster Atlantis or Discovery units), which cleans up and amplifies the signal.   Frequency bands are customarily (but not rigidly) defined as follows:  Delta (1Hz to 3 Hz); Theta (4 Hz to 7 Hz); Alpha (8 Hz to 12 Hz); Low Beta/SMR (13Hz to 15Hz); Beta (15 Hz to 20Hz); High Beta (20 Hz to 30Hz); Gamma (38 to 45 Hz).   Some neuroscientists or practitioners subdivide the bands (e.g. Low Theta =4-5Hz; High Theta = 6-7 Hz; Low Alpha = 8 -10Hz; High alpha = 11-12Hz).  They may also subdivide Beta into Beta1, Beta2, Beta3 by frequency range.

In New Mind protocols, it is customary to maintain an inhibit of at least 10% to 20% on High Beta (seeking lowering of High Beta amplitude, but using a relatively easy reward criteria), regardless of the training protocol being used, because measurement of High Beta is potentially contaminated by muscle tension (EMG) artifact, and the Neurofeedback Practitioner does not want to run the risk of inadvertently training  participants to increase muscle tension (which is already typically too high).

Prior to each EEG biofeedback (neurofeedback) session participants engaged in breathing exercises using the Wild Divine computerized biofeedback instructional program that teaches effective breathing practices (with goal of enhancement of parasympathetic NS activity) and how to increase heart rate variability and heart-brain rhythm  coherence via breathing practices.                 The practice was meant to teach participants how to better balance between sympathetic and parasympathetic nervous system activity (most participants presenting with clinical disorders have an imbalance involving excessive sympathetic and deficient parasympathetic activity)  to calm the participant before engaging in EEG biofeedback sessions.  Periodically participants completed self-report assessments, such as Symptom Trackers.

Each neurofeedback training session was 30 minutes in length and participants were able to choose either an eyes-opened or eyes-closed training option.   In the eyes-opened training condition, a DVD movie, or a standard video game (purchased through Brainmaster) was presented.  Rewards involved lightening of the screen with DVD movies, or allowing movement of, and scoring of points by, the animated video game character.   In the eyes closed condition, the participant would focus their attention in such a manner to elicit an increase in volume of music, or the frequency of a pleasant tone.


Assessment Measures

Psychometric assessment data was collected and integrated with neurometric MiniQ data to shed light on clinical problems (e.g. identify high risk individuals requiring further intervention) and to generate an individualized neurofeedback training protocol.   Psychometric instruments developed and validated by NewMind Center to complement MiniQ assessment include the Cognitive Emotional Checklist (CEC), the Metabolic Checklist, and the Interactive Self Inventory (ISI).  These psychometric measures, due to their proprietary and assessment-focused nature, were not utilized as outcome measures.  These four assessments were administered at baseline (initial MiniQ assessment), and repeated after the participant completed approximately 20 neurofeedback training sessions, and results pretreatment and posttreatment were discussed with participants, post-treatment, as part of debriefing.

The Cognitive Emotional Checklist (CEC) is a 47 item self-report proprietary measure    assessing neurologic symptoms that have been demonstrated via neurologic brain lesion studies and neuroimaging perfusion studies to be associated with specific brain regions.      Responses consist of ratings of severity on a Likert-type scale rating from 0 to 3 (0=None; 1 = Mild; 2 = Moderate;  3= Severe).   Client ratings for each item are entered/uploaded to the NewMind system, and color-coded graphs and head maps are         illustrated based upon statistical deviation from average (e.g. Green = within +/- SD;     Light Blue =    -1SD; Dark Blue = -2SD; Red = +1 SD; Yellow = +2SD).   This color-coding system is utilized by other QEEG brainmapping systems.  Cognitive symptoms are clustered under headings such as Attention, Memory,  Executive Functions;  emotional symptoms are categorized by association with Hypoarousal, Avoidance, and        Hyper-arousal.  Self-report ratings are compared to EEG findings corresponding to specific 10-20 site locations.   The level of concordance/agreement between the client’s self-report and their neurometric data from the MiniQ (indices of brain functioning) can be directly compared.  Discussion of the MiniQ assessment data can be a very   educational, insight-promoting, and validating  process for a client.

The Interactive Self Inventory (ISI; Soutar, 2006; 2015) is a 135 item personality assessment measure developed by Richard Soutar, Ph.D. (NewMind Center) which samples emotional and behavioral characteristics (identified via lesion and functional  neuroimaging  research) to be correlated with brain location and function.   Originally intended to discriminate peak performers from average performers and to discriminate between normal and clinically significant levels of distress symptoms,  it has been cross      validated between samples of peak performers, clinical populations and normal  populations, and normative ranges are established for each group.  Items were based upon items contained in well-validated and standardized instruments of psychopathology and personality, but the measure was conceptualized to emphasize interpersonal behavior patterns and consequences of those interpersonal behavior patterns – no known clinically focused  instruments with good discriminant and construct validity were available in the            psychometric field at that time.   An initial item pool was refined psychometrically (internal consistency reliability; content validity and concurrent validity with measures such as the Beck Depression and Anxiety inventories), and items retained including some that involved reverse scoring, to aid in identifying valid profiles.  Items are rated by participants on a 4 point ordinal-interval scale assessing degree of being problematic (0 =     none; 1 = Mild= 2 = Moderate= 3 = Severe).

The ISI has demonstrated good discriminative properties in Peak Performers ( ccessful executives, high achievers, high performing athletes) from Average Performers.   The ISI has also demonstrated good concurrent and construct validity as assessed via acceptably high correlations with other self-report measures such as the Beck Depression Inventory, Beck Anxiety Inventory, and Beck Hopelessness Scale (see original development and validation studies of these instruments by Aaron Beck and colleagues

Multi-axial dimensions assessed by the ISI include Avoidant vs. Interactive, Dependence vs. Independence, Competitive vs. Cooperative;  Perfectionistic vs. Flexible; Assertiveness vs. Passivity;  Impulsivity vs. Regulated; Inhibited vs. Relaxed; Depressed vs. Anxious.   The inputted data is computer-scored and interpreted by the New Mind Expert QEEG system, generating a bar graph with normative ranges (for normal, clinical, peak performer ranges) identifying potential interpersonal problem areas of concern.  Neurofeedback training has been found to remediate problematic   interpersonal behavior patterns, as individuals develop greater self-other awareness, inhibitory control, and decisional flexibility. The Approach and Avoidant dimensions correlate strongly with hemispheric asymmetry patterns described in the neuroscience literature (e.g. Davidson,  2000; Herrington, et. al., 2010).  The Impulsivity vs. Regulated    dimensions have been found to correlate with elevated amplitudes of Theta in the frontal- central regions and with performance on the Test of Variables of Attention (TOVA) and   the Anxiety and Depression dimensions correlate highly with the Beck Depression and Beck Anxiety Inventories (Richard Soutar, Ph.D., unpublished study).  Areas to be addressed are indicated in the printed map output, delineated as  'Guides To Change.'

            The Physiological Questionnaire was adapted from the work of Devis  Kharrazian (2013), is designed to highlight any physiological/metabolic  symptoms the participant is reporting to be experiencing.  A participant will rate symptoms they may be experiencing based on how frequently they occur and how severe that symptom is.  Metabolic factors, such as blood sugar instability, possible Adrenal or Thyroid irregularities, and other factors can affect (typically slow) the rate of progress of neurofeedback training, and may need to be brought to the attention of one’s primary care  condition for further assessment  and treatment/management.  

Outcome Measures

            Depression Anxiety Stress Scales (DASS; Lovibond and Lovibond, 1995):   In addition to the New Mind assessment instruments, a Depression Anxiety and Stress Scale was completed by all participants.  This assessment was obtained from School of Psychology at the University of New South Wales, Sydney, Australia.   The DASS is comprised of 42 self report items, each reflecting a negative emotional state, rated on a 4-point Likert Scale assessing frequency/severity over the previous week (range is from 0 = does not        apply to me at all, to 3 = applies to me very much or most of the time. )  The sum of the  relevant 14 items for each scale constitute the participants' scores for each of Depression, Anxiety and Stress, with subscales consisting of 2 to 5 items.   The Depression scale has subscales assessing dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest/involvement, anhedonia and inertia.  The Anxiety scale assesses autonomic arousal, skeletal muscle effects, situational anxiety and subjective experience of anxious affect.  The Stress scale's subscales highlight levels of non-chronic arousal through difficulty relaxing, nervous arousal and being easily upset/agitated, irritable/over-reactive and impatient.

Symptom Tracker:  An un-normed symptom tracker was also utilized, whereby    participants identified and rated the severity of the most problematic symptoms/problems.  Participant’s ratings can be compared across time measurements with regard to percentage change on each symptom.



Results are reported descriptively, in terms of percentage change at post-treatment, relative to pre-treatment (baseline).   Parametric statistical tests (e.g. Repeated Measures ANOVA) were not utilized in the analyses.    Percentage change was felt to be a measure easily grasped understood by lay persons and policy makers.  The disadvantage of using percentages is that it cannot be stated with statistical certainty (probability) that the results would have differed from that expected by chance alone.  However, those familiar with addiction rehab. programs will recognize our percentage improve as higher than usually reported.

Data from the Cognitive Emotional Checklist, Physiological Questionnaire, and Interpersonal Style Inventory (ISI) were utilized psychotherapeutically, to educate participants about their nature of their problems and symptoms; namely, the degree of congruity between their self-report and the objective electrophysiological (MiniQ) data.   Data from these measures were not analyzed for descriptive purposes.

The MiniQ, the DASS, and the Symptom Tracking measure were utilized as the primary outcome measures (of percentage of improvement) from pretreatment to post-treatment.   The MiniQ is an objective electrophysiological measure, and the DASS is a subjective self-report measure.   Other descriptive statistics (reported earlier) included the percentage of completers versus dropouts, and the percentage of partcipants self-reporting successful abstinence (versus continued use of substances) at the completion of the study.

Study Demographics

Of the 142 referrals to the program the demographics included a gender distribution of 60% female and 40% male.  The goal was to approximate an equal distribution of males and females in the program.

The age distribution analysis indicated the average of participants was 38 years old.  There were no participants under 18 years old and no participants who exceeded 70 years of age.





Study Completers versus Non-Completers (Dropouts)

One hundred and forty two individuals were referred to the program, only 63% of those completed it.  The 37% of the participants who did not complete the program included some that never attended the initial appointment, some who underwent the QEEG assessment but failed to follow up to complete even one neurofeedback session, and those who began participating in neurofeedback sessions, but dropped out shortly afterward.  Those participants who completed the study averaged 21 sessions of neurofeedback.

Percentage improvement (from pretreatment to post-treatment) was computed for the 63 percent of participants who were study completers.   Of the study completers, 93% reported successful abstinence, compared to 7% who did not report successful abstinence from their substance(s) of choice.

It was found that females were more interested in engaging in the EEG biofeedback program,  however,  as indicated by __ females having completed the program and ___ males having completed the program   (You may want to present a bar graph, showing  percentages.

Initially Enrolled   Completer Dropout                    Intially Enrolled   Completer Dropout

Male                                                                Female


Evaluation Of Outcome Measures

Data from the Cognitive Emotional Checklist, Physiological Questionnaire, and Interpersonal Style Inventory (ISI) were utilized psychotherapeutically, to educate participants about their nature of their problems and symptoms; namely, the degree of congruity between their self-report and the objective electrophysiological (MiniQ) data.   Data from these measures were not analyzed for descriptive purposes.

The MiniQ, the DASS, and the Symptom Tracking measure were utilized as the primary outcome measures (of percentage of improvement) from pretreatment to post-treatment.   The MiniQ is an objective electrophysiological measure, the DASS is a normed subjective self-report measure, and the Symptom Tracker is an un-normed individualized state measure of symptoms (assessing how the individual has felt over the past week).

The New Mind Expert QEEG system allows a direct comparison (% change) between pre-treatment and post-treatment maps, as an objective electrophysiologic index of improved brain health (improved stability and efficiency of brain functioning).  It utilizes Retrograde (deviation further away from the norm) and Anterograde (movement closer to the norm).  Prominent neuroscientist researchers have hypothesized that compensatory processes occur in the brain, in a nonlinear manner as part of brain plasticity (e.g. Pascual-Leon, Amedi, Fregni, and Mirabet, 2005).  Neurofeedback experts have anecdotally described a reorganizational and self-corrective process whereby the brain initially responds to neurofeedback by ‘moving away from the Z score norm’, (as if veering off course) until it finds its most efficient/optimal setting, at which point amplitudes of various frequency bands begin to normalize in an expected pattern.    The New Mind computations of change incorporate both retrograde and anterograde aspects, in determining overall (positive) change.

DASS post-treatment scores were compared to DASS-pre-treatment scores to assess subjectively experienced frequency/severity of negative mood states.    The degree of (positive) change was computed inversely as percent improvement (rather than percent decrease in score at post-treatment, relative to pre-treatment baseline).

Symptom trackers (where participants identified and rated those problems most salient and disruptive) allowed for a more individualized assessment and monitoring of symptom levels.  It also allowed Participants to get some sense of how they were progressing.  The study design was intended to be naturalistic, and trackers were utilized to aid in maintaining motivation and effort.  Percentage improvement (computed as a measure of the average/overall change across various symptoms being tracked) was calculated between post-treatment and post-treatment symptom trackers.


Descriptive Statistical Findings

In terms of changes in QEEG measurements, the average improvement across all study participants was 34% (improvement was calculated by NewMind map comparison index, indicating scores more closely approximating the normal distribution).   Percent change (toward the norm) incorporates both score deviations away from the norm (retrograde change) and scores moving closer to the norm (anterograde change

Total scores on the DASS (self-report) were calculated at the beginning of the program and again at the conclusion of the program.  The overall change in the combination of all depression anxiety and stress scale was 43% reduction in symptoms associated with the neurofeedback training experience.

Similarly, on the Symptom Tracking measure (where participants identified their most problematic symptoms, and then rated these problems were rated in terms of severity), overall change in symptoms was computed between the initial and final measurements.  The results indicated an average 38% reduction in symptomology.   The highest reported reduction in symptomatology on the Symptom Tracker was 79.6 percent.   These percentages are presented below, for QEEG, DASS and Symptom Tracker measures, and again specifically for the Symptom Tracker Measure.

Similarly, closer examination of the QEEG change measure indicated that the highest percentage of change was 55% (with the mean % change being 34%, as previously reported).  The QEEG measure is objective corroboration of the self-report measures that actual change occurred at a neurophysiological level, as well as a subjective psychological level (report of symptom reduction; report of improved abstinence).


The results of this study point toward the efficacy of the QEEG Guided approach to EEG biofeedback training with individuals who were in drug treatment programs.  Many of the participants were referred by their mental health counselors, addictions counselors and drug court programs.  The length of time in treatment varied from those who still use and are trying to change their behaviors to those who had years in recovery but still struggled with cravings and stress related symptoms.

The program ran for a total of four years.  The overall program was consistent with previous outpatient studies that has shown efficacy when using versions of QEEG guided biofeedback for those who suffer with substance abuse (deBeus, 2007; Scott & Kaiser, 1998; Scott, et. al. 2002;  2005;  Sokhadze et. al, 2007, 2008a; 2008b; Trudeau, 2000, 2005, 2008; Trudeau et. al., 1999).

Through the process of acquiring and discussing QEEG and other initial assessment data, participants were open to the notion that addictions have a neurologic (brain-based) aspect, namely dysregulation of the normal brain wave pattern (e.g. brain too fast, brain too slow, or a combination of both).  Many have suffered with problematic symptoms throughout their lives and many reported having difficulties as far back as middle school.  Approximately 44% of participants reported previous head trauma resulting from accidents and sports injuries such as concussions.  A high percentage of the participants reported dysfunctional homes and adverse childhood experiences (consistent with the findings of the The CDC-Kaiser Permanente Adverse Childhood Experiences (ACE) Study, one of the largest investigations of childhood abuse and neglect and later-life health and well-being (Felitti et. al. 1998).

Hospital visits were minimal for participants.  Participants reported to feel less stressed, less anxious and less depressed as sessions progressed.  They reported better quality sleep and significantly less pain.   Previously, these ‘target’ symptoms that were highly related to desire to engage in use of the substances of choice.  With the reduction of the problematic symptoms, participants were less likely to relapse.    Many of the study completers reported that  EEG biofeedback has changed their lives for the better, with much better quality of life.  They reported improved relationships both in the home and the workplace.  Those participants who were employed reported better performance on the job and some reported being told for the first time by a superior that they were doing a good job.  Family members of the participants were also interviewed periodically throughout the program by counselors, and many expressed amazement and appreciation for the positive changes that were evident.

The attrition rate seen in the present study (37%) is comparable to  that reported in the research literature (Stark, 1992, Wikizer et. al., 1994; Stanton et. al., 1997; Drake et. al., 1998; Dutra, et. al., 2008).   Dutra et. al. 2008, performed  a meta-analysis to investigate the effectiveness of treatments varying according to specific interventions and specific drug use disorders (studies using alpha-theta neurofeedback and QEEG –guided neurofeedback were not included in that review).  They reported the following:

“Approximately one-third of the participants across all conditions dropped out before treatment completion    (35.4%). Mean dropout among control conditions was 44.6%. Across all substance use groups, cocaine and opiate patients tended to have higher mean dropout rates (42.0% and 37.0%, respectively) than patients treated for cannabis and polysubstance use (27.8% and 31.3%, respectively).  Contingency      management demonstrated the lowest dropout rates (29.4%), followed by general cognitive behavior therapy (35.3%) and cognitive behavior therapy plus contingency management (44.5%). Only two studies provided relapse prevention dropout rates   (57.0%), and these studies were specific to cocaine treatment.” (Dutra. et. al., 2008, page 183).

The present study was naturalistic, which means that many factors and sources of variance were not controlled for (as would be in experimental designs).   There was a self-selection factor evident, as only the most motivated or interested persons would commit voluntarily to a treatment regimen requiring at least 20 sessions following the initial session, as well as followup assessments.    The frequency/consistency rate of appointments varied across participants, given that many of the participants were attending other appointment such as support groups, private therapy sessions, continuous drug testing, and some reported to drug court programs.  That is, some were able to attend weekly appointments (same day of week, same time of day) on a consistent basis, and others had a less routine pattern of attendance.   The sheer number of overall appointments was often overwhelming to participants.   Outreach was insufficient, there were many organizations in the local communities that were not aware of the program and found out too late in the program to refer their clients.  This had the effect of limiting the referral base to certain organizations,  referral sources, and regions, as opposed to more varied referral sources.

A further limitation of the study was that initially the NY SOARS program only provided one QEEG and 15 sessions per participant.  As the program progressed the participants had to plead with the administration to increase the amount of sessions, much the way a clinical practitioner has to deal with an insurance company to increase the number of therapy sessions.   Fortunately, the number of sessions was increased to 20 sessions and by the fourth year of the program the amount of sessions was increased to 50.   Hence, the number of allowable sessions varied almost each year of the SOARS program.    Because length of program could have impacted the outcome of the program, and could not be standardized,  there is heterogeneity in the data in terms of number of sessions, which could not be controlled for apriori, and this is a source of potential unwanted variance.

Overall many of the participants were pleased and grateful for the opportunity to participate in such a successful program and report that they would certainly continue if the opportunity arose.  The participants did not have the financial resources to continue on an “out of pocket” situation.

Use of parametric statistical tests, such as a within-subjects repeated measures Analysis of Variance (ANOVA), or Multiple Analyses of Variance (MANOVA) design would have greatly increased the precision of measurement.  For example, it would have allowed us to make statements regarding probability that the outcomes (improvements) were not merely due to chance.  The authors are clinicians and not statisticians, and there was no money in the budget to hire a statistician.   Hence, we had to be content with descriptive statistics, and cannot state with more certainty that the treatment probably ‘caused’ the desired outcome.  At best, we can state that there appears to be a favorable association between use of neurofeedback and a decrease in symptoms /improvement in abstinence rates/improvement in QEEG score measures.

There was no random assignment to treatment condition.   The funding allocated was not for research purposes, but for treatment.  All individuals willing to participate in the neurofeedback component were provided the opportunity.   Moreover, a control group (treatment as usual, without the neurofeedback option) could not be included for practical and ethical reasons, so we cannot differentiate the effects of neurofeedback from those of treatment as usual, based upon the present study.  Moreover, inclusion of a sham neurofeedback condition was not an option; had it been possible to include such a group, it may have allowed us to address the question of how much the placebo effect of using a novel and promising treatment may have influenced the outcome.

Those who work in the addiction field are painfully aware that sustained success is hard to come by, and that relapses and dropouts are common.   Our study suggests that QEEG guided neurofeedback may have an important role to play, in combination with other addiction interventions (individual counseling).  Replication of the study with improvements in study design, to reduce potential confounds and other sources of unwanted variance, would be the logical next step.  This might include random assignment to conditions (conventional treatment as usual, conventional treatment plus neurofeedback, conventional treatment plus sham neurofeedback), with efforts where possible to keep participants and principle researchers blinded to group status.  Improved measures might include structured interview schedules, full QEEG measures, assessment of changes in evoked potentials, random administration of quantitative urine and sputum assays or hair analysis.  More precision of measurement (e.g. frequent measurement via a time series) and sophisticated statistical analysis may help to reveal subtle fluctuations that occur during the course of treatment.   Such a study would require proper funding, of course, and research funding is limited and extremely competitive.

It would have also been useful to have been able to study the effects of other lifestyle and holistic factors in recovery, such as how nutrition, exercise, and meditation/structured breathing exercises to reduce arousal associated with cravings may impact the outcome of any program intended to help those in recovery.  For example, many participants reported that self-regulation skills, such as breathing exercises, became important coping skills and likely were a contributory factor toward success with many participants.

Based upon the preliminary data analysis presented here, and feedback received from participants and their families,  the SOARS program (having taken the added step of incorporating QEEG-guided neurofeedback into a conventional outpatient addiction recovery program, was successful in that it was perceived as beneficial by those in recovery and their families/supports, and would appear to promote physiological and psychological well-being.  Participants who had struggled with abstinence reported improvements in sleep quantity and quality, stress management, and more positive and hopeful moods and outlooks.  A subset of patients with a concomitant diagnosis of Post Traumatic Stress Disorder further reported fewer “flashbacks” and overall less troubled by the disorder

At the very least, is our sincere hope that by providing a preliminary measure of program effectiveness, it can be shown to taxpayers and law makers alike that this type of program is valuable and cost-effective to recipients, their family, and society as a whole.   A more in-depth statistical analysis is planned, to evaluate factors such as possible gender differences in treatment success, and whether the program was relatively more effective for certain types of substance addictions than others.  We hope to analyze differences between dropouts vs. completers in the present study.   This information could be helpful in identifying those most likely to complete and benefit from neurofeedback training in the future, to guide assessment and allocation of scare resources.  Although debatable, successful completion may be partially dependent on the length/intensity of the outpatient program, with longer or more intensive programs tending to have more favorable outcomes than brief, lower intensity programs (Stark, 1992, Wikizer et. al., 1994; Stanton et. al., 1997; Drake et. al., 1998; Dutra, et. al., 2008).   We hope to further analyze our data set to address the question of whether longer/more intensive treatment yielded stronger/better outcomes.  It is also hoped that a funding source can be obtained to allow follow-up assessment of participants, to determine if gains made in treatment are continuing to hold over time.



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