Conditions: Depression Dual Diagnosis Drug Addiction
Allocation: RANDOMIZED | Intervention model: PARALLEL
Enrollment: 65
Healthy volunteers: no

Brief summary:
Methamphetamine (MA) addiction is a public health concern that causes substantial harm to individual users, and imposes an economic burden in the U.S. totaling up to $48.3 billion annually. This study proposes to address a critical aspect of this problem: the lack of any proven, FDA-approved pharmacological treatments for MA users. The proposal combines an intervention designed to improve energy metabolism in the brain, and a neuroimaging technique capable of measuring the neurochemicals that represent cerebral bioenergetic function. The study will replicate and extend a key neuroimaging finding from the investigators recent MA studies: that MA users have decreased phosphocreatine (PCr) levels in the brain, compared to healthy volunteers. Phosphocreatine is the substrate reservoir for the creatine kinase reaction, which reversibly converts PCr into adenosine triphosphate (ATP), the brain's major energy supply, and creatine. Neuronal energy demands are met through a shift in reaction equilibrium, which is designed to maintain the concentration of ATP constant. Research results from the investigators recent study also showed that female MA users have lower brain PCr levels compared to male users. These findings join the converging lines of evidence that MA use is associated with mitochondrial dysfunction, i.e. deficient energy metabolism, in the brain. Frequently, MA users also experience depression, as well as cognitive deficits. Interestingly, both of these entities are also linked to mitochondrial dysfunction in the brain.

The long-term goal of this research program is to define the alterations in brain chemistry that underlie MA use disorders, and to utilize translational magnetic resonance spectroscopy (MRS) neuroimaging to identify rational brain-based treatment targets. Once a hypothesis-driven intervention is identified, MRS can then be further employed in treatment studies, to verify that "target engagement" is achieved. The specific aims of this proposal are an example of this stepwise scientific process: the nutritional supplement creatine will be tested in a randomized, placebo-controlled study of women with MA use disorders, to investigate creatine's effect on cerebral PCr levels, depressive symptoms, and MA usage.

Detailed description:

Arms:
arm 1: 5 grams of daily creatine monohydrate for 8 weeks arm 2: 5 g of placebo for 8 weeks arm 3: None

Interventions: intervention 1: Creatine monohydrate
Intervention descriptions: intervention 1: None

Protocol document:
Prot_SAP_000.pdf: 
Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 1 
STUDY PROTOCOL 
 
PROTOCOL TITLE: A Randomized Double-Blind Controlled Trial of Creatine in 
Female Methamphetamine Users 
PROTOCOL VERSION: 2.08 
PROTOCOL DATE: September 5, 2018 
PROTOCOL NUMBER: IRB_00073034 
PRINCIPAL INVESTIGATOR: Perry Renshaw, MD, PhD, MBA 
Professor of Psychiatry 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 
CO-INVESTIGATORS: Deborah Yurgelun-Todd, PhD 
Professor of Psychiatry 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 
 
Erin McGlade, PhD 
Research Assistant Professor of Psychiatry 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 
 
Amanda Bakian, PhD 
Assistant Professor of Psychiatry 
Family and Preventative Medicine | University of Utah 
650 Komas Drive 
Salt Lake City, UT 84108 
 
Younghoon Sung, MD, MS 
Assistant Professor of Psychiatry 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 
 
Xianfeng Shi, PhD 
Research Instructor of Psychiatry 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 
 
Kelly Lundberg, PhD 
Associate Professor of Psychiatry 
Director of Assessment and Referral Services 
Department of Psychiatry | University of Utah 
450 South 900 East 
Salt Lake City, UT 84112 
 
Lindsay Scholl, BS 
Study Coordinator 
The Brain Institute | University of Utah 
383 Colorow Drive 
Salt Lake City, UT 84108 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 2 
 
 
Investigator’s Agreement 
 
1. I have read this protocol and agree that the study is ethical. 
2. I agree to conduct the study as outlined and in accordance with all applicable regulations 
and guidelines. 
 
 
 
 
 
 
 
 
 
 
 
 
Signature of Principal Investigator 
 
 
 
 
           
 
 
Perry F. Renshaw 
 
 
 
 
 
 
09/05/2018 
 
        
 
 
Name of Principal Investigator (printed or typed)   
 
 
Date 
 
 
 
           
 
 
 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 3 
BACKGROUND AND SIGNIFICANCE 
 
Methamphetamine Causes Neuronal Excitotoxicity That Involves Bioenergetic 
Compromise: 
Methamphetamine (MA) addiction is a chronic relapsing conditions that causes 
devastating physical and psychiatric harm to affected individuals [1]. These include increased 
risk of psychosis [2], depression/anxiety [1], suicidal behavior [3], completed suicide [4], and 
even all-cause mortality when compared to users of cocaine, alcohol or cannabis [5]. However, 
since discontinuation of MA use leads to negative emotional states, abstinence from MA poses 
intense difficulty for dependent individuals. Given these observations, basic and clinical 
research studies have focused on the development of new pharmacological interventions [6], 
but have not led to Food and Drug Administration (FDA) approved pharmacotherapies that 
improve cognitive deficits and depressive symptoms during MA discontinuation [7]. 
Methamphetamine has deleterious effects on dopaminergic brain systems [8], and 
prolonged amphetamine exposure is associated with Parkinson’s disease [9]. Animal studies 
suggest that MA use predisposes to Parkinson’s via degeneration of the midbrain dopaminergic 
neurons that project to striatum [10]. A recent epidemiologic study found a significant correlation 
between the development of Parkinson’s disease (165% higher risk) in MA users followed for up 
to 10 years [11]. This finding was replicated in a larger sample of MA users (n=40,472) versus 
an appendicitis group (n=207,831; hazard ratio=1.76), and even a cocaine group (n=35,335; 
hazard ratio=2.44) [12].  
Converging evidence implicates mitochondrial dysfunction in MA toxicity [8, 13-15]. 
Mitochondrial pathways interact to cause MA-induced neuronal apoptosis and death [16]. MA 
inhibits enzyme complexes of the electron transport chain, resulting in dopaminergic 
neurotoxicity because electron transport chain inhibitors increase reactive species [17-19]. 
Inhibition of complex I activity by MA [16] also decreases ATP production. MA produces 
mitochondrial fragmentation in progenitor cells [20], releasing apoptogenic molecules from 
mitochondria [21]. 
 
Brain Phosphocreatine (PCr) Levels and Glutamate Excitotoxicity in Methamphetamine  
Use: 
A key phosphorus (31P) magnetic resonance spectroscopy (MRS) finding from our 
ongoing research is significantly decreased phosphocreatine (PCr) in MA users, an effect that is 
greater in females than males [22]. Notably, in rats creatine administration significantly 
increases the brain content of both creatine and PCr [23]. In human studies, the increase in 
brain total creatine (PCr + creatine) after oral creatine supplementation is a finding replicated by 
three independent groups, including ours [24-26]. 
The importance of assessing glutamatergic systems in MA users is attested to by the fact 
that more than 80% of neurons are excitatory, and that greater than 90% of synapses release 
glutamate [27]. Of relevance to our preliminary proton (1H) MRS findings showing an association 
between the glutamine/glutamate ratio and lifetime MA use, it has been reported that PCr 
stimulates synaptic glutamate uptake thereby reducing extracellular glutamate [28], which is 
another potential neuroprotective mechanism of creatine. Importantly, depletion of PCr and ATP 
is an early event in glutamate excitotoxic neurodegeneration [29, 30]. Therefore, based on our 
finding of decreased PCr in MA users, it is of interest that a recent 1H-MRS investigation 
reported that glutamate levels in frontal white matter are significantly higher in abstinent MA 
users versus control subjects [31], which is compatible with MA-induced neurotoxicity.  
 
Female Methamphetamine Initiation, Addiction and Relapse are Influenced by  
Depression:   
The prevalence of pre-morbid depressive disorders in MA users is high, with a majority 
reporting a significant lifetime history of depression [1, 3, 70]. For example in one study [70], MA 
users had a 62% rate of depression and a 23% rate of suicidality prior to MA use.  After MA was 
initiated, the rate of depression increased to 79% [70]. Studies reporting gender differences in 
psychopathology have found that MA use is associated with depression in both adult [60] and 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 4 
adolescent [71] females. In one study, depressive symptoms were endorsed on the Addiction 
Severity Index (ASI) by 68% of female MA users [3]. In another, early-onset MA use in females 
was significantly associated with premorbid depressive disorders, while the same was not true 
for males [72]. Female MA users with depression are less likely to be employed, more likely to 
use MA to manage their mood, use more grams of MA per 30-day period, use MA more times 
per day on more consecutive days, and are more likely to be binge users [73]. The diagnosis 
and treatment of depression and anxiety in MA users is complicated by the fact that withdrawal-
associated dysphoria is persistent, and may be the result of MA-induced neurotoxicity [74]. 
Therefore, an ideal intervention for depression and anxiety in the setting of MA addiction would 
be one that targeted both neurotoxicity and negative emotional states. 
Research has shown that females may respond better to treatment of MA use disorders 
than males [60, 75]. In fact, patient gender predicts both treatment engagement and abstinence 
during rehabilitation [76], a gender difference not found in cocaine- or alcohol-dependent 
research samples [77]. As a result, the recommendation has been made to take gender into 
account in developing treatments for MA use disorders [60, 75]. 
 
Creatine is a Novel Strategy for Cognitive Enhancement and Neuronal Repair in MA  
Addiction: 
Our preliminary data, combined with the extant literature, suggest that creatine 
administration is a safe, hypothesis-driven strategy for: (a) Increasing brain PCr, NAA and 
GABA levels, thus providing neuroprotection and neuronal repair; (b) Reducing both depression 
and anxiety symptoms; and (c) Improving cognitive deficits in female MA users. Based on 
evolving understanding of MA neurotoxicity, a novel therapeutic strategy that has been 
suggested is to utilize cognitive enhancement and neuronal repair as pharmacotherapy targets 
in stimulant addiction [56, 57]. This stems, in part, from the fact that solely addressing the drug's 
addictive properties may be insufficient to address the diverse neuropathological injuries caused 
by MA [15]. However, in the absence of approved medications for MA use disorders, an initial 
step toward pursuing this innovative strategy is to assess the clinical and translational impact of 
a neuroprotective agent such as creatine in MA users.  
 
Summary Significance and Relevance for This Proposal:   
The lack of safe and effective pharmacological treatments for MA use disorders is a 
critical barrier to improved treatment outcomes. This proposal builds on the published 
translational findings of reduced PCr[22] and NAA [34, 124] levels in MA use disorders, and the 
clinical and neuroimaging findings from our preliminary study of creatine for MA-using females.  
At the same time, it follows the recommendation of experts – including NIDA Director Dr. Nora 
Volkow and the eminent substance abuse researcher Dr. George Koob – that strategies outside 
the brain dopamine reward system be adopted [56, 125, 126]. Achievement of these Specific 
Aims would validate the notion of neuroprotective agents as potential treatments for MA 
addiction [15], and in particular those which are also capable of improving mood/anxiety and 
cognitive symptoms. Incorporating pre- and post-treatment imaging into studies of substance 
misuse can facilitate identification of the neural predictors and correlates of effective MA 
treatment [127]. Because the effects of drug use on brain function impede patients' ability to 
benefit from treatment, studies of drug-related alterations in neurobiology utilizing translational 
study designs are warranted [127]. Thus, we propose an 8-week, randomized, placebo-
controlled trial of creatine for females with MA addiction.  
 
Specific Aims for this proposal are: 1. To define the extent of restoration in bioenergetic 
dysfunction and neuronal viability following creatine supplementation in female MA users.  We 
hypothesize that creatine will be superior to placebo in the degree of improvement in PCr and 
NAA levels, measured with 31P-MRS and 1H-MRS. Changes to the glutamine/glutamate ratio 
and GABA will be assessed in an exploratory manner. 2. To assess creatine's 
antidepressant/anxiolytic effect in female MA users. We hypothesize that creatine will be 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 5 
superior to placebo in reducing Hamilton Depression Rating Scale (HAMD) and Beck Anxiety 
Inventory [97] scores.3.To Measure the Degree of Cognitive Improvement Associated with 
Creatine in Female MA Users. We hypothesize that creatine will be associated with greater 
improvement in cognitive function tests, compared with placebo. In addition to these Specific 
Aims, we will examine urine drug testing results in an exploratory manner, to determine whether 
creatine vs. placebo is associated with a greater number of MA-free tests 
 
In addition to these Specific Aims, we will monitor subjects' MA use, as improvements in brain 
bioenergetics, mood/anxiety and may decrease MA usage. Therefore, we will record urine drug 
testing results, to determine whether creatine vs. placebo is associated with a greater number of 
MA-free tests during the 8 weeks of randomized treatment.  
 
PARTICIPANT SELECTION CRITERIA 
 
123 women will be randomly assigned in a 1:1 ratio to either creatine or placebo for eight 
weeks. Table 1 outlines eligibility criteria. 
TABLE 1 INCLUSION AND EXCLUSION CRITERIA 
INCLUSION CRITERIA: 
¡ 
Female gender, ages 18-55 inclusive 
¡ 
Current primary diagnosis of MA dependence or abuse, with MA preferred drug of abuse 
(Lifetime MA use > 20 grams) 
¡ 
Current diagnosis of Major Depressive Disorder (MDD)  
¡ 
Current HAMD score > 10 
¡ 
Clinical Global Impressions–Severity (CGI-S) depression score > 4 
¡ 
If taking a psychotropic medication for depressed mood, regimen must be stable for > 4 
weeks prior to randomization  
EXCLUSION CRITERIA: 
¡ 
Persons unable to provide adequate informed consent  
¡ 
Persons who are at clinically significant suicidal or homicidal risk 
¡ 
Primary substance-related diagnosis other than MA dependence or abuse 
¡ 
Comorbid substance dependence diagnosis, other than nicotine (substance abuse 
diagnoses are not excluded) 
¡ 
Positive pregnancy test, due to the unknown effects of MRI scanning on the unborn fetus 
¡ 
Positive test for antibody to the Human Immunodeficiency Virus (HIV)  
¡ 
History of renal disease 
¡ 
Clinically significant medical or neurological illness identified by history, physical exam 
and laboratory testing 
¡ 
Known or suspected intellectual disability, or developmental disorder, e.g. autism 
¡ 
History of hypersensitivity reaction to creatine  
WITHDRAWAL / EARLY TERMINATION CRITERIA: 
¡ 
Withdrawal of informed consent 
¡ 
Suicide attempt 
¡ 
Psychiatric hospitalization 
¡ 
Onset of bipolar disorder or psychotic disorder 
¡ 
Positive pregnancy test 
¡ 
Incarceration 
¡ 
Inability to comply with study protocol 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 6 
 
DESIGN 
 
 
The proposed study will use a randomized, double-blind, placebo-controlled design. 123 
participants will be randomly assigned in a 1:1 ratio to placebo or 5 grams of daily creatine 
treatment for eight weeks. We also plan to recruit 24 age-matched females (18-55). 
 
STUDY PROCEDURES 
 
All procedures performed by study personnel are research-related. None of the study 
activities will be considered standard of care. There will be no cost to study subjects for their 
participation. Participants will be compensated for their time and travel. Table 2A and 2B 
outlines the schedule of study procedures for treated participants and healthy controls. 
Consent will be obtained before any study procedures are initiated. Potential participants 
will be informed of the study and offered a consent form to review. They will be encouraged to 
discuss study participation with their relatives. If a potential participant expresses interest in 
study participation, the informed consent process will be conducted. After the informed consent 
process, individuals will be offered time to consider study participation and to ask questions. 
Subjects and parents/guardians will have the opportunity to discuss the study with a study team 
member in a setting free of coercion. The language of the informed consent form is written at a 
level easily understood by the subject and any questions asked by the subject will be answered 
honestly and free of bias. A specific meeting time will be set up between a study team member 
and the participant where the entire informed consent document will be carefully explained in its 
entirety. The length of the meeting will be designed so there is the necessary amount of time for 
all questions to be answered.   
Randomization of participants to the two treatment conditions will take place according 
to a randomization list generated prior to the start of recruitment. 47 (50%) will be randomized to 
placebo. The study will be conducted as a double-blind trial, with neither participants nor 
research staff aware of participant assignment. Except in cases of medical emergency, the 
double-blind will not be "broken" until recruitment is closed and the final participant has 
completed 8 weeks of treatment with investigational drug. There is no "washout period" for any 
participant in this study, and participants randomized to placebo will continue treatment with a 
psychotropic medication throughout their time in the study. 
At the screening visit, an ECG will be conducted in order to examine the heart and ensure 
participant safety; an adult cardiologist will also evaluate all individuals during the screening 
phase. If during the MRI/MRS scans we unexpectedly discover something that warrants further 
inspection, we will refer the participant to her primary care provider for follow-up, along with the 
MRI/MRS report that shows the findings. Any costs related to following up on unexpected 
findings will be the responsibility of her and/or her insurance provider. In conjunction with the 
brain scans performed pre- and post-treatment, a brief battery of cognitive tests will be 
administered, to evaluate change associated with creatine or placebo. Trained 
psychometricians administer tests on the day of scanning. Scoring is done blind to subjects' 
group status, clinical ratings and imaging results. The cognitive testing battery instruments were 
¡ 
Treatment with electroconvulsive therapy (ECT) 
¡ 
Increase in HAMD score > 25% from baseline 
¡ 
Serious adverse event 
¡ 
HEALTHY CONTROL SUBJECTS: 
¡ 
Female gender, ages 18-55 inclusive 
¡ 
No current or past DSM-5 diagnosis, as determined by clinical and structured interviews 
¡ 
No first-degree relatives with known or suspected DSM-5 diagnosis  
 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 7 
chosen because they are sensitive to frontal lobe integrity: the Wisconsin Card Sorting Task 
(WCST)[129], the Stroop Color-Word Test[130, 131], and the Wechsler Memory Scale (WMS-
IV)[132].Furthermore, the WCST[133], Stroop Test[134] and WMS-IV [90]each have been 
associated with performance deficits in MA users. 
 
TABLE 2A Schedule of Procedures for Methamphetamine-dependent Females 
 
Screening 
Treatment Phase 
 
Follow Up 
Phase 
Study Week →  
-2 to 0a 
1* 
2* 
3* 
4* 
5* 
6* 
7* 
8* 
9 
10 
11 
Informed Consent, 
Demographics 
X 
 
 
 
 
 
 
 
 
 
 
 
Medical History & 
Physical Exam, ECG 
X 
 
 
 
 
 
 
 
 
 
 
 
Hematology & 
Chemistries 
X 
 
 
 
 
 
 
 
 
X 
 
 
Phlebotomy for 
Creatinine Levels 
X 
 
 
 
X 
 
 
 
 
X 
 
 
HIV 
X 
 
 
 
 
 
 
 
 
 
 
 
Pregnancy Test and vital 
signs 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
PRISM Diagnostic 
Interview  
X 
 
 
 
 
 
 
 
 
 
 
 
ASI 
X 
 
 
 
 
 
 
 
 
X 
 
 
Randomization to 
Creatine or Placebo  
X 
 
 
 
 
 
 
 
 
 
 
 
Treatment with Creatine 
or Placebo 
 
X 
X 
X 
X 
X 
X 
X 
X 
 
 
 
 
Urine Drug Screen / 
Other Drug Use 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
Concomitant 
Medications 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
 
Food Frequency 
Questionnaire 
X 
 
 
 
 
 
 
 
 
X 
 
 
Cognitive Tests: WCST, 
STROOP and WMS-IV 
(with WASI 
vocabulary)*** 
X 
 
 
 
 
 
 
 
 
X 
 
 
Adverse Events 
 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
Treatment Program 
Attendance 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
Clinical Scales: HAMD**, 
BAI**, CGI-S**, C-SSRS 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 
X 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 8 
31P-MRS and 1H-
MRS**** 
X 
 
 
 
 
 
 
 
 
X 
 
 
*During the 8 Treatment Weeks, MA Subjects Have 2 Study Visits Per Week (separated 
by > 48 hours) 
**Procedure will be collected at one of the twice weekly visits 
***MA subjects with difficulty scheduling the cognitive testing appointment may be 
allowed to omit these measures and continue in the study as to not delay treatment 
and in order to facilitate timely enrollment, which is critical for this population. 
****If an individual is screened and determined to be a good fit for study participation 
but also has a contraindication to MRI scanning, the principal investigator may allow 
them into the study, however, they will not be scanned for their safety. 
CGI-S = Clinical Global Impressions-Severity Depression Score; C-SSRS = Columbia-Suicide 
Severity Rating Scale; HAMD = Hamilton Rating Scale for Depression; BAI = Beck Anxiety 
Inventory; PRISM = Psychiatric Research Interview for Substance and Mental Disorders; 
STROOP = Stroop Color Word Test; WCST = Wisconsin Card Sorting Test; WMS-IV = 
Wechsler Memory Scale; WASI = Wechsler Abbreviated Scale of Intelligence; ASI = Addiction 
Severity Index. 
aScreening may happen over the course of 2-3 visits. 
 
TABLE 2B Schedule of Procedures for Healthy Controls 
 
Screening 
 
Final 
Visit 
Study Week →  
-1 to 0a 
1 
2 
3 
4 
5 
6 
7 
8 
9 
Informed Consent, Demographics 
X 
 
 
 
 
 
 
 
 
 
Medical History & Physical Exam, 
ECG 
X 
 
 
 
 
 
 
 
 
 
Hematology & Chemistries 
X 
 
 
 
 
 
 
 
 
 
Phlebotomy for Creatinine Levels 
X 
 
 
 
 
 
 
 
 
 
HIV 
X 
 
 
 
 
 
 
 
 
 
Pregnancy Test 
X 
 
 
 
 
 
 
 
 
X 
PRISM Diagnostic Interview  
X 
 
 
 
 
 
 
 
 
 
Food Frequency Questionnaire 
X 
 
 
 
 
 
 
 
 
 
X 
Urine Drug Screen / Other Drug Use 
X 
 
 
 
 
 
 
 
 
X 
Concomitant Medications 
X 
 
 
 
 
 
 
 
 
X 
Vital Signs 
X 
 
 
 
 
 
 
 
 
X 
Cognitive Tests: WCST, STROOP 
and WMS-IV (with WASI 
vocabulary) 
X 
 
 
 
 
 
 
 
 
X 
Treatment Program Attendance 
X 
 
 
 
 
 
 
 
 
X 
Clinical Scales: HAMD**, BAI**, 
CGI-S**, C-SSRS 
X 
 
 
 
 
 
 
 
 
X 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 9 
31P-MRS and 1H-MRS 
X 
 
 
 
 
 
 
 
 
X 
CGI-S = Clinical Global Impressions-Severity Depression Score; C-SSRS = Columbia-Suicide 
Severity Rating Scale; HAMD = Hamilton Rating Scale for Depression; BAI = Beck Anxiety 
Inventory; PRISM = Psychiatric Research Interview for Substance and Mental Disorders; 
STROOP = Stroop ColorWord Test; WCST = Wisconsin Card Sorting Test; WMS-IV = 
Wechsler Memory Scale; WASI = Wechsler Abbreviated Scale of Intelligence. 
aScreening may happen over the course of 2-3 visits. 
 
RISKS AND BENEFITS TO STUDY PARTICIPANTS 
• 
During the intake and assessment interview, participants may become emotionally upset 
when asked about their psychiatric history including suicide attempts, or physical and sexual 
abuse.  
• 
There is a 50% chance that the participant will be assigned to placebo, in which they will not 
receive creatine. 
• 
Participants may experience discomfort or swelling when blood is drawn for laboratory 
tests. Rarely, infection can result from blood draws.  
• 
It is possible that the participant’s illness could worsen during the study. This could be 
related or unrelated to the study. Individuals with Major Depressive Disorder are at risk for 
depression, suicidal ideation, and suicide attempts as part of their illness. If the participant’s 
illness worsens to the point that the study doctor considers them a danger to themselves or 
others, they will be hospitalized. If the participant is hospitalized they will be withdrawn from 
the study. In the event of hospitalization, the participant or the participant’s insurance 
company will be responsible for the associated costs. 
• 
It is possible that treatment with creatine will not be effective for the participant’s depression, 
and that study participation will therefore delay the start of effective treatment. 
• 
The researchers will take precautions to safeguard the participant’s confidentiality, but it is 
possible that a breach of confidentiality could occur. A Certificate of Confidentiality has been 
obtained for this study. 
• 
The participants may experience gastrointestinal discomfort as a result of taking study 
medication. We recommend taking the study medication with food to reduce possible 
stomach discomfort. 
• 
MRI/MRS scans do not use ionizing radiation like x-rays or CT scans.  Instead, magnetic 
fields and radio waves are used to take the pictures. There are no known risks related to 
MRI scans – other than the risk of injury when metallic objects are brought into the scanning 
room by mistake. Serious injury can occur during an MRI scan to persons who have: 
o Cardiac (heart) pacemakers. 
o Metal clips on blood vessels (also called stents). 
o Artificial heart valves. 
o Artificial arms, hands, legs, etc. 
o Brain stimulator devices. 
o Implanted drug pumps. 
o Cochlear [6] implants. 
o Ocular [118] implants or known metal fragments in eyes. 
o Exposure to shrapnel or metal fillings 
o Other metallic surgical parts. 
o Orthodontic braces on the teeth. 
o Body jewelry or piercings that cannot be removed for the scan. 
o Certain tattoos with metallic ink (please tell us if your child has a tattoo) 
o Certain transdermal (skin) patches such as NicoDerm (nicotine for tobacco 
dependence), 
o Transderm Scop (scopolamine for motion sickness), or Ortho Evra (birth control) 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 10 
 
If the participants have any such devices, or has had a surgery where metal devices 
were placed in their body, they cannot take part in the study unless cleared for MRI 
scanning by the surgeon who implanted the medical device(s) or unless the principal 
investigator allows the individual to take part in the study without being scanned. 
 
• 
Serious risks exist if ferromagnetic objects (things that stick to magnets) are brought into the 
scanning area. These items can become dangerous flying objects, and are not allowed near 
the MRI scanner. 
• 
The FDA has approved the 3T scanner for routine clinical studies in children. The FDA has 
decided that MRI machines of 8T or less do not pose a risk. Although the scans we are 
using in this study have no known risks, there could be ill effects that are delayed, such that 
they have not yet been recognized by the FDA. The brain scans do not cause pain. Apart 
from the scanner noise, the participant will not know the scan is taking place. 
• 
Inside the scanner, some people experience claustrophobia (fear of being in small spaces), 
dizziness, headaches, or a metallic taste in the mouth. Some people experience double 
vision or see flashing lights. These symptoms are temporary, and will stop when the 
participant leaves the scanner.  
• 
The participant may feel cramped inside the scanner. There is a mirror placed inside the 
scanner so that your child can see his or her face, and look out into the scanning room. The 
technologist will be able to hear the participant at all times. 
• 
Very rarely, someone having an MRI scan feels a tingling in his or her back. This is due to 
the magnetic field changing quickly during the scan.  
• 
The precautions taken will avoid all the known risks related to MRI scans.  The participant 
can stop the scan at any time. 
 
We cannot promise any benefits to the participants from being in the study. However, there are 
some possible benefits to the participants if they participate in this study: 
• 
Participants will receive a thorough medical and psychiatric evaluation, and will be followed 
more closely than in routine clinical care. 
 
Other than direct benefits to the participants, there are possible indirect benefits: 
• 
Results from the study will help doctors understand the way creatine affects MA users with 
depression, and thus, this could help us improve treatment options. 
• 
The brain scans may improve our understanding of the biology of depression in female MA 
users. However, that would not directly benefit the participants. 
• 
The participants will receive a copy of the clinical MRI of their brain, if they wish. A copy of 
the MRI scan report will also go to the research team. 
 
DATA SAFETY MONITORING PLAN 
The study team will perform monitoring of the study records on a continuous basis.  Co- 
investigator, Young-Hoon Sung, will oversee data accuracy and completeness.  
 
a. Adverse Events/Serious Adverse Events to the IRB, FDA and NIDA 
i. 
Reporting to the University of Utah Institutional Review Board. Adverse events (AEs) 
and Serious Adverse Events (SAE) that are unexpected and unrelated will be 
reported to the University of Utah Institutional Review Board (IRB) with the annual 
request for study continuation. For AEs/SAEs that are unexpected, related to study 
participation and place participants at risk will be reported via the IRB’s electronic 
reporting system as soon as possible after the PI learns of the event, but in all cases 
within 10 working days.  


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 11 
ii. 
Reporting to the Food and Drug Administration. The PI shall notify the Food and 
Drug Administration (FDA) in a written investigational new drug [118] safety report of 
any adverse experience associated with the use of the drug that is both serious and 
unexpected. In each written IND safety report, the investigators shall identify all 
safety reports previously filed with the IND concerning a similar adverse experience, 
and shall analyze the significance of the adverse experience in light of the previous, 
similar reports. Each notification shall be made as soon as possible and in no event 
later than 15 calendar days after the sponsor's initial receipt of the information. Each 
written notification may be submitted on FDA Form 3500A or in a narrative format 
(foreign events may be submitted either on an FDA Form 3500A or, if preferred, on a 
CIOMS I form; reports from animal or epidemiological studies shall be submitted in a 
narrative format) and shall bear prominent identification of its contents, i.e., "IND 
Safety Report." Each written notification to FDA shall be transmitted to the FDA new 
drug review division in the Center for Drug Evaluation and Research or the product 
review division in the Center for Biologics Evaluation and Research that has 
responsibility for review of the IND. If the FDA determines that additional data are 
needed, the agency may require further data to be submitted. 
a. The study team will send an annual report 60 days within the “study may 
proceed” date. 
iii. 
Reporting to the National Institute on Drug Abuse. The PI will notify the grant 
program officer by email of SAEs as soon as possible and in no event later than 15 
calendar days. Other AEs will be summarized in the annual progress report.  
b. Reporting IRB Actions to NIDA. The grant program officer will be made aware of IRB actions 
via email correspondence from the PI.  
c. Reporting Protocol Changes. Changes to the protocol will be submitted to the IRB and FDA 
for approval before the changes are implemented. Once the IRB and FDA have issued 
approval of protocol changes, the PI will submit a summary of the protocol changes and the 
protocol to the grant program officer. The NIDA program officer must agree upon proposed 
protocol changes before they can be implemented. 
d. Reporting Protocol Violations/Deviations to the IRB and FDA 
i. 
Reporting to the University of Utah Institutional Review Board. If a protocol 
violation/deviation meets one or more of the following criteria, the PI will submit the 
violation/deviation via ERICA within 10 working days from the time the investigator 
learns of the event. 
• 
Intended to eliminate apparent immediate hazard to a research participant; or 
• 
Harmful (caused possible harm to participants or others, or places them at 
increased risk of harm – including physical, psychological, economic, or social 
harm, such as breach of confidentiality); or 
• 
Possible serious or continued noncompliance (such as a deviation that has 
happened previously and is now being repeated). 
ii. 
Reporting to the Food and Drug Administration. Protocol violations/deviations will be 
summarized in the annual IND report.  
 
Trial Stopping Rules 
In our open-label study of 5 grams of daily creatine for 8-weeks, there were no unanticipated 
problems or SAEs reported. Considering this is a feasibility study of double-blind, placebo-
controlled creatine at the same dose as our open-label study, and the open-label creatine was 
well tolerated with a low side effect profile, we have not adopted rules for stopping the study. 
We have, however, developed criteria for early termination of participants and the criteria are 
listed below: 
• 
Suicide attempt 
• 
Psychiatric hospitalization 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 12 
• 
Onset of bipolar disorder or psychotic disorder 
• 
Positive pregnancy test 
• 
Incarceration 
• 
Inability to comply with the study protocol 
 
IMAGING METHODS AND DATA ANALYSIS  
 
1. Neuroimaging Protocol 
i. 
Magnetic Resonance Imaging (Siemens Trio 3T MRI system) 
 
MRI scans will be conducted twice:  at the baseline visit, and following 8 weeks of 
treatment with study drug.  The 3.0 Tesla Siemens whole-body clinical scanner (Siemens 
Medical Solutions, Erlangen, Germany) located within the University Neuropsychiatric Institute 
(UNI) will be used to acquire this data. Participants will first undergo a routine anatomic MRI 
protocol, which includes MRI images acquired in the axial and coronal planes. Specifically, the 
anatomic scan protocol consists of a T1 weighted structural scan (MPRAGE), and double-echo 
T2 weighted scan, and a Fluid Attenuated Inversion Recovery scan (FLAIR). The purposes of 
the MR anatomic screening session include screening subjects for gross structural 
abnormalities and acquiring images for use in brain cortical thickness measurements. Anatomic 
MRI examinations will be performed with a quadrature radio-frequency coil. After localization, 
anatomical imaging will be obtained using a T1-weighted, sagittal oriented 3D-Magnetization 
Prepared Rapid Gradient Echo (MPRAGE) sequence (TR/TE/TI 2100/3.97/1100 ms, matrix 
256x256, FOV 256x256 mm, flip angle 12 degree, slice thickness 1.5 mm, slab 192 mm, 
bandwidth 190 Hz/pixel). Axial proton-density and T2 weighted images will be acquired to 
screen for brain structural abnormalities using 2D Double echo T2 weighted turbo spin echo 
(TSE) sequence (TR 7110 ms, TE 28/84 ms, FOV 240x210, slice thickness 3 mm, flip 150°, 
bandwidth 179 Hz/pixel). FLAIR sequence (TR/TE/TI 8000/90/2500 ms, slice thickness 5 mm, 
FOV 240x168, voxel size 0.8x0.6x5.0 mm, bandwidth 200 Hz/pixel, turbo factor 13) will be used 
to detect juxtacortical-cortical lesions. All anatomic MRI images will be read by a board-certified 
Radiologist to screen for structural abnormalities.  
 
ii. 
Measurement of In-Vivo Brain Chemistry Using Phosphorus-31 Magnetic 
Resonance Spectroscopy (31P-MRS)  
a. Phosphorus MRS 
Phosphorus spectroscopy data will be acquired on the same Siemens 3T system. We 
aim to keep the duration of each MRSI examination at or under 25 minutes.  A 3D-MRSI 
sequence with elliptically weighted phase-encoding will be used to collect 31P-MRSI data to 
minimize T2 signal decay.  Acquisition parameters will be: data matrix size 16x16x8; TR 2000 
ms; tip-angle 90 degree for hard RF pulse; Rx bandwidth ±1 kHz; complex-points 1024; readout 
duration 256 ms; pre-acquisition delay 0.3ms; FOV 240x240 mm2 ; 16 NEX. 
 
iii. 
Spectral Analysis of 31P-MRS Data 
Spectroscopy will be analyzed using Liner Combination of Model Spectra (LCModel) 
[135], which analyzes an in vivo spectrum as a linear combination of model in vitro spectra from 
individual metabolite solutions. This model is fully automatic and user independent. A nearly 
model-free constrained regularization method is used for convolution and baseline. For 
quantification, absolute metabolite concentrations (institutional units) will be estimated using the 
unsuppressed water signal as an internal concentration reference. Also, total creatine levels will 
be used as a denominator for calculating the relative concentration for the comparison with 
previous reports. The standard Siemens libraries of model metabolite spectra provided with 
LCModel will be used in the basis set. The metabolites from the basis set will include alanine, 
aspartate, creatine, gamma-amino butyric acid, glucose, glutamine, glutamate, 
glycerophosphocholine, glutathione, myo-inositol, scyllo-inositol, lactate, N-acetylaspartate, N-


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 13 
acetylaspartylglutamate, phosphocholine, phosphocreatine, phosphoethanolomine, scyllo-
inositol, and taurine. For the reliability of detection, the Cramer-Rao lower bounds (CRLB) will 
be determined:  the acceptable upper limit of estimated standard deviations will be set at 20% 
[136].   
 
Post processing of 31P-MRS data will be conducted using jMRUI software (jMRUI v. 4.0, 
European Community) with the AMARES algorithm (Advanced Method for Accurate, Robust and 
Efficient Spectral fitting of MRS data with use of prior knowledge).  Before fitting the FID (Free-
induction-decay) data, a Hamming filter will be applied to reduce signal contamination from 
neighboring voxels, with apodization of 10 Hz line broadening. Fourier transformation, frequency 
shifts correction, and zero-order/first order phase correction as well as baseline correction will 
be applied. The structural image-processing tool FSL (FMRIB Software Library, Release 4.1, 
The University of Oxford) will be used to account for gray matter, white matter, and 
cerebrospinal fluid (CSF), in order to correct the partial volume effects on metabolite 
concentrations. The MRS grid will be positioned over the images in an identical fashion between 
baseline and treatment scans for each participant. The peak area for each 31P-MRS metabolite 
will be calculated as a percentage of the total phosphorus signal.  
Overall Analytic Strategy: The analyses proposed are generalized estimating equations (GEE) 
regression modeling, which will be used for our longitudinal data analyses with group 
comparison across treatment visits for the variables of metabolite levels, depression/anxiety 
symptoms, and cognitive tests. GEE allows robust estimations of standard errors and permits 
adjustment for time-varying covariates. We assume that measurements made closer in time are 
more correlated than those made farther apart. Thus, first-order autoregressive structure is 
assumed. For our repeated measurement data, GEE fits a population-averaged model with 
working correlation structure to statistically evaluate the time effect of creatine supplementation. 
We will control for age, other drug abuse, anxiety scores, and tissue partial volume effects in 
each GEE model. Sidak multiple comparison procedure will be employed to adjust for family 
wise error (FWE) rate. The Sidak tests make conservative controls of FWE, giving slightly 
smaller adjusted p-values than the Bonferroni correction. 
Overall Power and Sample Size Calculations: For this pilot study, considering a 20% attrition 
rate, 95 participants will be recruited to achieve a sample size of 75. To determine the minimum 
effect that would likely be detected with a sample size of 75, a power analysis was performed. 
Effect for the power analysis was specified as average baseline (over two measures) HAM-D 
scores compared with average HAM-D scores during active treatment (over eight measures). A 
gradual onset of effect during active treatment is assumed, starting with an effect of 0 and 
ending with an effect of 0.5, resulting in an average effect during treatment of 0.25. The effect to 
be tested was treated as a linear combination of the separate measures (y*), and a pattern of 
correlation of 0.5 was used. This generated a standard deviation [105] for y* that will be different 
from the within-occasion SD for Y itself. Then the effect magnitude specified was divided by the 
SD(y*) to generate an “effective” or de facto effect size, which resulted in an effect size of 1.09 
with a power of 0.87.  
Statistical Analysis for Specific Aim 3: Cognitive testing data with a repeated measures design 
will evaluate the cognitive improvement after 8 weeks of creatine supplementation, specifically 
in executive and working memory deficits, found in MA users. The relative improvements on 
WCST, Stroop and WMS-IV scores associated with creatine versus placebo will be tested 
conservatively with the assumption of independence among comparisons. Independent 
variables include a time variable of "visit" (baseline and 8 weeks of treatment), creatine” 
(placebo or creatine group), and an interaction term, "creatine × visit", where a significant 
interaction will indicate significant differences between treatments. The depression effect will be 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 14 
tested by stratifying depressed and non-depressed MA users.  Power and Sample Size 
Calculations: Previous reports, meta-analysis, and our preliminary data suggest that the 
cognitive deficits of MA users have medium-to-large (0.5 to 0.8) effect size, especially in the 
episodic memory, compared to healthy subjects.Thus, the proposed sample size (n=76) will 
have enough power (> 80%) based on Cohen's guidelines with adjusted Sidak p-values of 
0.0169. [137, 138] 
 
ADMINISTRATIVE RESPONSIBILITIES 
 
Resources: 
The facilities at the University of Utah that are available for the proposed research 
include the following: the Brain Institute, Assessment and Referral Services and UNI. The Brain 
Institute currently occupies 5,900 square feet of office and laboratory space in a building in the 
University of Utah Research Park adjacent to the Health Sciences campus. It also occupies 
clinical space in UNI, the site of the Brain Institute’s PRISMA 3T MRI research scanner. 
Assessment and Referral Services [4] is a freestanding clinic within the Department of 
Psychiatry. It occupies 6000 square feet in downtown Salt Lake City close to public 
transportation and approximately three miles from the University of Utah. It consists of 20 full 
time staff and approximately 30 part time staff. Salt Lake Behavioral Health Services contracts 
with ARS to provide three different functions. One is to provide assessments and referrals for 
individuals in Salt Lake County who have been arrested for driving under the influence; or who 
are seeking substance abuse services voluntarily or due to other court mandates. The third is to 
provide Interim Group Services (IGS), which are free groups for individuals awaiting Salt Lake 
County funded substance abuse treatment services.  
 
Recruitment of Participants:  
Primarily, participants will be recruited from ARS. Staff at ARS will refer women who 
identify methamphetamine as their primary drug of choice to the study staff. In addition, women 
will be recruited from the Clinical Assessment Center (CAC) at UNI. Staff at CAC will contact 
members of the study team to inform them if a MA-using woman interested in participating. The 
study team member will then follow-up with the interested woman to arrange a screening 
assessment.  
Study information flyers will also be hung at ARS, 12-step recovery program meeting locations, 
Fellowship Hall, other drug-use referral locations, and public transportation such as buses and 
trax. Additionally, participants will be recruited by radio advertisements on select radio stations 
in the Salt Lake City area. 
Study details will also be available on utahbrain.org.  
CONTROL OF INVESTIGATIONAL DRUG 
 
The University of Utah Research Pharmacy will prepare and dispense the 
creatine/placebo. They will dispense the study medication in a blinded fashion to a study team 
member, and it will be stored at room temperature in a locked office that is accessible only to 
research personnel. The study will be conducted in compliance with all applicable FDA 
regulations for IND studies.  
The blind will be broken following the culmination of the study or at the request of a 
medical professional dealing with a medical emergency in a case in which it would help a study 
participant. The Research Pharmacy will be contacted in order to break the blind.  
 
DATA COLLECTION, MANAGEMENT AND PROTECTED HEALTH INFORMATION 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 15 
 
The study team will create case report forms (CRFs) for data collection. The consent, 
permission and assent forms, CRFs, laboratory results, radiology reports, MRI registration 
forms, and other necessary documents will be filed in each study participant’s binder. Study 
participant binders will contain protected health information such as name, date of birth, age, 
address, and phone number. Binders will be stored in locked cabinets located in locked offices.  
Only essential study team members will have access to participant binders.   
Using a password-protected computer with access limited to study personnel, the 
research team will maintain a computerized screening and enrollment log. Participant screening, 
eligibility status, and consent for participation status will be recorded in this log. Before the 
performance of any study procedures, potential participants (and where applicable their 
parent(s) or guardians(s)), verbal and written informed consent will be obtained.  When a 
participant is screened for study eligibility, they will be assigned a screening ID number. The 
individual will maintain the screening ID until they have completed the first scanning visit. If a 
subject is determined to be ineligible during screening, the reason for the screen failure will be 
recorded on the computerized screening and enrollment log. Once a subject has completed 
screening enrolled for study participation, they will be assigned a subject ID number, which will 
be used to identify all of the data collected from them during the study.   
Data from CRFs will be entered into SPSS. No personal identifiers from study 
participants will be entered into SPSS. Forms that have missing or inconsistent data will be 
recorded in the database; however a “missing data” code will be entered in place of each piece 
of missing or inconsistent data.  Two study team members -- the individual who enters the data, 
and a second individual monitoring data entry -- will check each CRF form entered into SPSS 
for accuracy and completeness.   
 
RECORD RETENTION 
 
In keeping with 21CFR312.57, study records will be maintained for at least two years 
after the drug is approved by the FDA or after shipment and delivery of the drug for 
investigational use has ceased and the FDA has been notified.  
 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 16 
 
 
BIBLIOGRAPHY 
 
1. 
Darke, S., et al., Major physical and psychological harms of methamphetamine use. 
Drug and alcohol review, 2008. 27(3): p. 253-62. 
2. 
Sato, M., A lasting vulnerability to psychosis in patients with previous methamphetamine 
psychosis. Ann N Y Acad Sci, 1992. 654: p. 160-70. 
3. 
Zweben, J.E., et al., Psychiatric symptoms in methamphetamine users. The American 
journal on addictions / American Academy of Psychiatrists in Alcoholism and Addictions, 
2004. 13(2): p. 181-90. 
4. 
Marshall, B.D. and D. Werb, Health outcomes associated with methamphetamine use 
among young people: a systematic review. Addiction, 2010. 105(6): p. 991-1002. 
5. 
Callaghan, R.C., et al., All-cause mortality among individuals with disorders related to 
the use of methamphetamine: A comparative cohort study. Drug and alcohol 
dependence, 2012. 
6. 
Elkashef, A., et al., The NIDA Methamphetamine Clinical Trials Group: a strategy to 
increase clinical trials research capacity. Addiction, 2007. 102 Suppl 1: p. 107-13. 
7. 
Xi, Z.X. and E.L. Gardner, Hypothesis-driven medication discovery for the treatment of 
psychostimulant addiction. Current drug abuse reviews, 2008. 1(3): p. 303-27. 
8. 
Davidson, C., et al., Methamphetamine neurotoxicity: necrotic and apoptotic 
mechanisms and relevance to human abuse and treatment. Brain research. Brain 
research reviews, 2001. 36(1): p. 1-22. 
9. 
Garwood, E.R., et al., Amphetamine exposure is elevated in Parkinson's disease. 
Neurotoxicology, 2006. 27(6): p. 1003-6. 
10. 
Guilarte, T.R., Is methamphetamine abuse a risk factor in parkinsonism? 
Neurotoxicology, 2001. 22(6): p. 725-31. 
11. 
Callaghan, R.C., et al., Incidence of Parkinson's disease among hospital patients with 
methamphetamine-use disorders. Mov Disord, 2010. 25(14): p. 2333-9. 
12. 
Callaghan, R.C., et al., Increased risk of Parkinson's disease in individuals hospitalized 
with conditions related to the use of methamphetamine or other amphetamine-type 
drugs. Drug Alcohol Depend, 2012. 120(1-3): p. 35-40. 
13. 
Virmani, A., F. Gaetani, and Z. Binienda, Effects of metabolic modifiers such as 
carnitines, coenzyme Q10, and PUFAs against different forms of neurotoxic insults: 
metabolic inhibitors, MPTP, and methamphetamine. Annals of the New York Academy of 
Sciences, 2005. 1053: p. 183-91. 
14. 
Tata, D.A. and B.K. Yamamoto, Interactions between methamphetamine and 
environmental stress: role of oxidative stress, glutamate and mitochondrial dysfunction. 
Addiction, 2007. 102 Suppl 1: p. 49-60. 
15. 
Krasnova, I.N. and J.L. Cadet, Methamphetamine toxicity and messengers of death. 
Brain research reviews, 2009. 60(2): p. 379-407. 
16. 
Gluck, M.R., et al., Parallel increases in lipid and protein oxidative markers in several 
mouse brain regions after methamphetamine treatment. Journal of neurochemistry, 
2001. 79(1): p. 152-60. 
17. 
Jenkins, J.A., et al., The influence of gender and the estrous cycle on learned 
helplessness in the rat. Biol Psychol, 2001. 58(2): p. 147-58. 
18. 
Bisagno, V., R. Bowman, and V. Luine, Functional aspects of estrogen neuroprotection. 
Endocrine, 2003. 21(1): p. 33-41. 
19. 
Argov, Z., et al., Bioenergetic heterogeneity of human mitochondrial myopathies: 
phosphorus magnetic resonance spectroscopy study. Neurology, 1987. 37(2): p. 257-62. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 17 
20. 
Tian, C., L.C. Murrin, and J.C. Zheng, Mitochondrial fragmentation is involved in 
methamphetamine-induced cell death in rat hippocampal neural progenitor cells. PloS 
one, 2009. 4(5): p. e5546. 
21. 
Jayanthi, S., et al., Methamphetamine induces neuronal apoptosis via cross-talks 
between endoplasmic reticulum and mitochondria-dependent death cascades. FASEB 
journal : official publication of the Federation of American Societies for Experimental 
Biology, 2004. 18(2): p. 238-51. 
22. 
Sung, Y.H., et al., Decreased frontal lobe phosphocreatine levels in methamphetamine 
users. Drug Alcohol Depend, 2013. 129(1-2): p. 102-9. 
23. 
Royes, L.F., et al., Effectiveness of creatine monohydrate on seizures and oxidative 
damage induced by methylmalonate. Pharmacology, biochemistry, and behavior, 2006. 
83(1): p. 136-44. 
24. 
Dechent, P., et al., Increase of total creatine in human brain after oral supplementation 
of creatine-monohydrate. The American journal of physiology, 1999. 277(3 Pt 2): p. 
R698-704. 
25. 
Lyoo, I.K., et al., Multinuclear magnetic resonance spectroscopy of high-energy 
phosphate metabolites in human brain following oral supplementation of creatine-
monohydrate. Psychiatry research, 2003. 123(2): p. 87-100. 
26. 
Pan, J.W. and K. Takahashi, Cerebral energetic effects of creatine supplementation in 
humans. American journal of physiology. Regulatory, integrative and comparative 
physiology, 2007. 292(4): p. R1745-50. 
27. 
Raichle, M.E. and D.A. Gusnard, Appraising the brain's energy budget. Proceedings of 
the National Academy of Sciences of the United States of America, 2002. 99(16): p. 
10237-9. 
28. 
Xu, C.J., et al., Phosphocreatine-dependent glutamate uptake by synaptic vesicles. A 
comparison with atp-dependent glutamate uptake. The Journal of biological chemistry, 
1996. 271(23): p. 13435-40. 
29. 
Beal, M.F., Mitochondrial dysfunction in neurodegenerative diseases. Biochim Biophys 
Acta, 1998. 1366(1-2): p. 211-23. 
30. 
Tsuji, K., et al., Transient increase of cyclic AMP induced by glutamate in cultured 
neurons from rat spinal cord. J Neurochem, 1995. 65(4): p. 1816-22. 
31. 
Sailasuta, N., et al., Metabolic Abnormalities in Abstinent Methamphetamine Dependent 
Subjects. Substance abuse : ] research and treatment, 2010. 2010(4): p. 9-20. 
32. 
Chang, L., et al., Additive effects of HIV and chronic methamphetamine use on brain 
metabolite abnormalities. The American journal of psychiatry, 2005. 162(2): p. 361-9. 
33. 
Ernst, T., et al., Evidence for long-term neurotoxicity associated with methamphetamine 
abuse: A 1H MRS study. Neurology, 2000. 54(6): p. 1344-9. 
34. 
Nordahl, T.E., et al., Low N-acetyl-aspartate and high choline in the anterior cingulum of 
recently abstinent methamphetamine-dependent subjects: a preliminary proton MRS 
study. Magnetic resonance spectroscopy. Psychiatry research, 2002. 116(1-2): p. 43-52. 
35. 
Sekine, Y., et al., Metabolite alterations in basal ganglia associated with 
methamphetamine-related psychiatric symptoms. A proton MRS study. 
Neuropsychopharmacology : official publication of the American College of 
Neuropsychopharmacology, 2002. 27(3): p. 453-61. 
36. 
Smith, L.M., et al., Brain proton magnetic resonance spectroscopy in children exposed to 
methamphetamine in utero. Neurology, 2001. 57(2): p. 255-60. 
37. 
Sung, Y.H., et al., Relationship between N-acetyl-aspartate in gray and white matter of 
abstinent methamphetamine abusers and their history of drug abuse: a proton magnetic 
resonance spectroscopy study. Drug and alcohol dependence, 2007. 88(1): p. 28-35. 
38. 
Taylor, M.J., et al., Effects of human immunodeficiency virus and methamphetamine on 
cerebral metabolites measured with magnetic resonance spectroscopy. Journal of 
neurovirology, 2007. 13(2): p. 150-9. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 18 
39. 
Patel, T.B. and J.B. Clark, Synthesis of N-acetyl-L-aspartate by rat brain mitochondria 
and its involvement in mitochondrial/cytosolic carbon transport. The Biochemical journal, 
1979. 184(3): p. 539-46. 
40. 
Clark, J.B., N-acetyl aspartate: a marker for neuronal loss or mitochondrial dysfunction. 
Developmental neuroscience, 1998. 20(4-5): p. 271-6. 
41. 
Bates, T.E., et al., Inhibition of N-acetylaspartate production: implications for 1H MRS 
studies in vivo. Neuroreport, 1996. 7(8): p. 1397-400. 
42. 
Addolorato, G., et al., Novel therapeutic strategies for alcohol and drug addiction: focus 
on GABA, ion channels and transcranial magnetic stimulation. 
Neuropsychopharmacology : official publication of the American College of 
Neuropsychopharmacology, 2012. 37(1): p. 163-77. 
43. 
Nishiyama, T., et al., Haplotype association between GABAA receptor gamma2 subunit 
gene (GABRG2) and methamphetamine use disorder. Pharmacogenomics J, 2005. 5(2): 
p. 89-95. 
44. 
Lin, S.K., et al., Gender-specific contribution of the GABA(A) subunit genes on 5q33 in 
methamphetamine use disorder. Pharmacogenomics J, 2003. 3(6): p. 349-55. 
45. 
Gerasimov, M.R., et al., Gamma-vinyl GABA inhibits methamphetamine, heroin, or 
ethanol-induced increases in nucleus accumbens dopamine. Synapse, 1999. 34(1): p. 
11-9. 
46. 
Willuhn, I., et al., Dopamine signaling in the nucleus accumbens of animals self-
administering drugs of abuse. Current topics in behavioral neurosciences, 2010. 3: p. 
29-71. 
47. 
Ranaldi, R. and K. Poeggel, Baclofen decreases methamphetamine self-administration 
in rats. Neuroreport, 2002. 13(9): p. 1107-10. 
48. 
Li, S.M., et al., GABA(B) receptor agonist baclofen attenuates the development and 
expression of d-methamphetamine-induced place preference in rats. Life Sci, 2001. 
70(3): p. 349-56. 
49. 
DeMarco, A., et al., Racemic gamma vinyl-GABA (R,S-GVG) blocks methamphetamine-
triggered reinstatement of conditioned place preference. Synapse, 2009. 63(2): p. 87-94. 
50. 
Voigt, R.M., et al., Administration of GABA(B) receptor positive allosteric modulators 
inhibit the expression of previously established methamphetamine-induced conditioned 
place preference. Behavioural brain research, 2011. 216(1): p. 419-23. 
51. 
Voigt, R.M., A.A. Herrold, and T.C. Napier, Baclofen facilitates the extinction of 
methamphetamine-induced conditioned place preference in rats. Behav Neurosci, 2011. 
125(2): p. 261-7. 
52. 
Agmo, A., et al., GABAergic drugs inhibit amphetamine-induced distractibility in the rat. 
Pharmacology, biochemistry, and behavior, 1997. 58(1): p. 119-26. 
53. 
Mizoguchi, H. and K. Yamada, Pharmacologic Treatment with GABA(B) Receptor 
Agonist of Methamphetamine-Induced Cognitive Impairment in Mice. Current 
neuropharmacology, 2011. 9(1): p. 109-12. 
54. 
Arai, S., et al., GABAB receptor agonist baclofen improves methamphetamine-induced 
cognitive deficit in mice. European journal of pharmacology, 2009. 602(1): p. 101-4. 
55. 
Vocci, F.J., Cognitive remediation in the treatment of stimulant abuse disorders: a 
research agenda. Experimental and clinical psychopharmacology, 2008. 16(6): p. 484-
97. 
56. 
Sofuoglu, M., Cognitive enhancement as a pharmacotherapy target for stimulant 
addiction. Addiction, 2010. 105(1): p. 38-48. 
57. 
Loftis, J.M. and M. Huckans, Cognitive enhancement in combination with 'brain repair' 
may be optimal for the treatment of stimulant addiction. Addiction, 2011. 106(5): p. 1021-
2. 
58. 
Cohen, J.B., et al., Women with methamphetamine dependence: research on etiology 
and treatment. Journal of psychoactive drugs, 2007. Suppl 4: p. 347-51. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 19 
59. 
Brecht, M.L., et al., Methamphetamine use behaviors and gender differences. Addictive 
behaviors, 2004. 29(1): p. 89-106. 
60. 
Dluzen, D.E. and B. Liu, Gender differences in methamphetamine use and responses: a 
review. Gender medicine, 2008. 5(1): p. 24-35. 
61. 
Lubman, D.I., et al., The impact of co-occurring mood and anxiety disorders among 
substance-abusing youth. J Affect Disord, 2007. 103(1-3): p. 105-12. 
62. 
Glasner-Edwards, S., et al., Risk factors for suicide attempts in methamphetamine-
dependent patients. The American journal on addictions / American Academy of 
Psychiatrists in Alcoholism and Addictions, 2008. 17(1): p. 24-7. 
63. 
Kuo, C.J., et al., Causes of death of patients with methamphetamine dependence: a 
record-linkage study. Drug and alcohol review, 2011. 30(6): p. 621-8. 
64. 
van, d.P.E.A., et al., Executive control deficits in substance-dependent individuals: a 
comparison of alcohol, cocaine, and methamphetamine and of men and women. Journal 
of clinical and experimental neuropsychology, 2009. 31(6): p. 706-19. 
65. 
Milesi-Halle, A., et al., Sex differences in (+)-amphetamine- and (+)-methamphetamine-
induced behavioral response in male and female Sprague-Dawley rats. Pharmacology, 
biochemistry, and behavior, 2007. 86(1): p. 140-9. 
66. 
Reichel, C.M., et al., Sex differences in escalation of methamphetamine self-
administration: cognitive and motivational consequences in rats. Psychopharmacology, 
2012. 
67. 
Holtz, N.A., et al., Reinstatement of methamphetamine seeking in male and female rats 
treated with modafinil and allopregnanolone. Drug and alcohol dependence, 2012. 
120(1-3): p. 233-7. 
68. 
Allen, P.J., et al., Chronic creatine supplementation alters depression-like behavior in 
rodents in a sex-dependent manner. Neuropsychopharmacology : official publication of 
the American College of Neuropsychopharmacology, 2010. 35(2): p. 534-46. 
69. 
Lyoo, I.K., et al., A randomized, double-blind placebo-controlled trial of oral creatine 
monohydrate augmentation for enhanced response to a selective serotonin reuptake 
inhibitor in women with major depressive disorder. Am J Psychiatry, 2012. 169(9): p. 
937-45. 
70. 
Hall, E.D., et al., Neuroprotective effects of the dopamine D2/D3 agonist pramipexole 
against postischemic or methamphetamine-induced degeneration of nigrostriatal 
neurons. Brain Res, 1996. 742(1-2): p. 80-8. 
71. 
Yen, C.F. and M.Y. Chong, Comorbid psychiatric disorders, sex, and methamphetamine 
use in adolescents: a case-control study. Comprehensive psychiatry, 2006. 47(3): p. 
215-20. 
72. 
Yen, C.F. and Y.C. Su, The associations of early-onset methamphetamine use with 
psychiatric morbidity among Taiwanese adolescents. Substance use & misuse, 2006. 
41(1): p. 35-44. 
73. 
Semple, S.J., et al., Psychosocial and behavioral correlates of depressed mood among 
female methamphetamine users. Journal of psychoactive drugs, 2007. Suppl 4: p. 353-
66. 
74. 
Dyer, K.R. and C.C. Cruickshank, Depression and other psychological health problems 
among methamphetamine dependent patients in treatment: Implications for assessment 
and treatment outcome. Australian Psychologist, 2005. 40(2): p. 96-108. 
75. 
Hser, Y.I., E. Evans, and Y.C. Huang, Treatment outcomes among women and men 
methamphetamine abusers in California. Journal of substance abuse treatment, 2005. 
28(1): p. 77-85. 
76. 
Hillhouse, M.P., et al., Predicting in-treatment performance and post-treatment outcomes 
in methamphetamine users. Addiction, 2007. 102 Suppl 1: p. 84-95. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 20 
77. 
Walton, M.A., et al., Individual and social/environmental predictors of alcohol and drug 
use 2 years following substance abuse treatment. Addictive behaviors, 2003. 28(4): p. 
627-42. 
78. 
Salo, R., et al., Psychiatric comorbidity in methamphetamine dependence. Psychiatry 
research, 2011. 186(2-3): p. 356-61. 
79. 
Conway, K.P., et al., Lifetime comorbidity of DSM-IV mood and anxiety disorders and 
specific drug use disorders: results from the National Epidemiologic Survey on Alcohol 
and Related Conditions. The Journal of clinical psychiatry, 2006. 67(2): p. 247-57. 
80. 
Glasner-Edwards, S., et al., Psychopathology in methamphetamine-dependent adults 3 
years after treatment. Drug and alcohol review, 2010. 29(1): p. 12-20. 
81. 
Glasner-Edwards, S., et al., Anxiety disorders among methamphetamine dependent 
adults: association with post-treatment functioning. The American journal on addictions / 
American Academy of Psychiatrists in Alcoholism and Addictions, 2010. 19(5): p. 385-
90. 
82. 
Kelly, T.M., D.C. Daley, and A.B. Douaihy, Treatment of substance abusing patients with 
comorbid psychiatric disorders. Addictive behaviors, 2012. 37(1): p. 11-24. 
83. 
Zorick, T., et al., Poor response to sertraline in methamphetamine dependence is 
associated with sustained craving for methamphetamine. Drug and alcohol dependence, 
2011. 118(2-3): p. 500-3. 
84. 
Shoptaw, S., et al., Randomized, placebo-controlled trial of sertraline and contingency 
management for the treatment of methamphetamine dependence. Drug and alcohol 
dependence, 2006. 85(1): p. 12-8. 
85. 
Won, M., et al., Manic-switch induced by fluvoxamine in abstinent pure 
methamphetamine abusers. Journal of psychiatry & neuroscience : JPN, 2003. 28(2): p. 
134-5. 
86. 
Shoptaw, S., et al., Randomized, placebo-controlled trial of bupropion for the treatment 
of methamphetamine dependence. Drug and alcohol dependence, 2008. 96(3): p. 222-
32. 
87. 
Colfax, G.N., et al., Mirtazapine to reduce methamphetamine use: a randomized 
controlled trial. Archives of general psychiatry, 2011. 68(11): p. 1168-75. 
88. 
Salo, R., et al., Attentional control and brain metabolite levels in methamphetamine 
abusers. Biol Psychiatry, 2007. 61(11): p. 1272-80. 
89. 
Salo, R., et al., Preliminary evidence of reduced cognitive inhibition in 
methamphetamine-dependent individuals. Psychiatry Res, 2002. 111(1): p. 65-74. 
90. 
McCann, U.D., et al., Persistent cognitive and dopamine transporter deficits in abstinent 
methamphetamine users. Synapse, 2008. 62(2): p. 91-100. 
91. 
Aharonovich, E., E. Nunes, and D. Hasin, Cognitive impairment, retention and 
abstinence among cocaine abusers in cognitive-behavioral treatment. Drug Alcohol 
Depend, 2003. 71(2): p. 207-11. 
92. 
Rae, C., et al., Oral creatine monohydrate supplementation improves brain performance: 
a double-blind, placebo-controlled, cross-over trial. Proc Biol Sci, 2003. 270(1529): p. 
2147-50. 
93. 
Watanabe, A., N. Kato, and T. Kato, Effects of creatine on mental fatigue and cerebral 
hemoglobin oxygenation. Neurosci Res, 2002. 42(4): p. 279-85. 
94. 
Werb, D., et al., Methamphetamine use and malnutrition among street-involved youth. 
Harm Reduct J, 2010. 7: p. 5. 
95. 
Forrester, J.E., K.L. Tucker, and S.L. Gorbach, The effect of drug abuse on body mass 
index in Hispanics with and without HIV infection. Public Health Nutr, 2005. 8(1): p. 61-8. 
96. 
Quach, L.A., et al., Drug use and other risk factors related to lower body mass index 
among HIV-infected individuals. Drug Alcohol Depend, 2008. 95(1-2): p. 30-6. 
97. 
Frank, G.K., et al., Neuroimaging studies in eating disorders. CNS Spectr, 2004. 9(7): p. 
539-48. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 21 
98. 
Roser, W., et al., Metabolic changes in the brain of patients with anorexia and bulimia 
nervosa as detected by proton magnetic resonance spectroscopy. Int J Eat Disord, 
1999. 26(2): p. 119-36. 
99. 
Castro-Fornieles, J., et al., Adolescent anorexia nervosa: cross-sectional and follow-up 
frontal gray matter disturbances detected with proton magnetic resonance spectroscopy. 
J Psychiatr Res, 2007. 41(11): p. 952-8. 
100. 
Ludwig, D.S., et al., Dietary fiber, weight gain, and cardiovascular disease risk factors in 
young adults. JAMA, 1999. 282(16): p. 1539-46. 
101. 
Balsom, P.D., K. Soderlund, and B. Ekblom, Creatine in humans with special reference 
to creatine supplementation. Sports Med, 1994. 18(4): p. 268-80. 
102. 
Casey, A. and P.L. Greenhaff, Does dietary creatine supplementation play a role in 
skeletal muscle metabolism and performance? Am J Clin Nutr, 2000. 72(2 Suppl): p. 
607S-17S. 
103. 
Stead, L.M., et al., Is it time to reevaluate methyl balance in humans? Am J Clin Nutr, 
2006. 83(1): p. 5-10. 
104. 
Guerrero-Ontiveros, M.L. and T. Wallimann, Creatine supplementation in health and 
disease. Effects of chronic creatine ingestion in vivo: down-regulation of the expression 
of creatine transporter isoforms in skeletal muscle. Molecular and cellular biochemistry, 
1998. 184(1-2): p. 427-37. 
105. 
Dringen, R., et al., Metabolism of glycine in primary astroglial cells: synthesis of creatine, 
serine, and glutathione. Journal of neurochemistry, 1998. 70(2): p. 835-40. 
106. 
Wyss, M. and R. Kaddurah-Daouk, Creatine and creatinine metabolism. Physiological 
reviews, 2000. 80(3): p. 1107-213. 
107. 
Rawson, E.S. and J.S. Volek, Effects of creatine supplementation and resistance 
training on muscle strength and weightlifting performance. J Strength Cond Res, 2003. 
17(4): p. 822-31. 
108. 
Dalbo, V.J., et al., Putting to rest the myth of creatine supplementation leading to muscle 
cramps and dehydration. Br J Sports Med, 2008. 42(7): p. 567-73. 
109. 
Robinson, T.M., et al., Dietary creatine supplementation does not affect some 
haematological indices, or indices of muscle damage and hepatic and renal function. 
British journal of sports medicine, 2000. 34(4): p. 284-8. 
110. 
Kim, H.J., et al., Studies on the safety of creatine supplementation. Amino acids, 2011. 
40(5): p. 1409-18. 
111. 
Shao, A. and J.N. Hathcock, Risk assessment for creatine monohydrate. Regulatory 
toxicology and pharmacology : RTP, 2006. 45(3): p. 242-51. 
112. 
Rodriguez, N.R., M.N.M. Di, and S. Langley, American College of Sports Medicine 
position stand. Nutrition and athletic performance. Medicine and science in sports and 
exercise, 2009. 41(3): p. 709-31. 
113. 
Beal, M.F., Neuroprotective effects of creatine. Amino acids, 2011. 40(5): p. 1305-13. 
114. 
Klein, A.M. and R.J. Ferrante, The neuroprotective role of creatine. Subcell Biochem, 
2007. 46: p. 205-43. 
115. 
Burrows, K.B., G. Gudelsky, and B.K. Yamamoto, Rapid and transient inhibition of 
mitochondrial function following methamphetamine or 3,4-
methylenedioxymethamphetamine administration. European journal of pharmacology, 
2000. 398(1): p. 11-8. 
116. 
Cadet, J.L., S. Jayanthi, and X. Deng, Methamphetamine-induced neuronal apoptosis 
involves the activation of multiple death pathways. Review. Neurotox Res, 2005. 8(3-4): 
p. 199-206. 
117. 
Deng, X., et al., Methamphetamine induces apoptosis in an immortalized rat striatal cell 
line by activating the mitochondrial cell death pathway. Neuropharmacology, 2002. 
42(6): p. 837-45. 


Placebo-Controlled Creatine in Meth Users (R01) 
 
 
 22 
118. 
Prass, K., et al., Improved reperfusion and neuroprotection by creatine in a mouse 
model of stroke. J Cereb Blood Flow Metab, 2007. 27(3): p. 452-9. 
119. 
Mirecki, A., et al., Brain antioxidant systems in human methamphetamine users. J 
Neurochem, 2004. 89(6): p. 1396-408. 
120. 
Sestili, P., et al., Creatine supplementation affords cytoprotection in oxidatively injured 
cultured mammalian cells via direct antioxidant activity. Free Radic Biol Med, 2006. 
40(5): p. 837-49. 
121. 
Brustovetsky, N., et al., Calcium-induced cytochrome c release from CNS mitochondria 
is associated with the permeability transition and rupture of the outer membrane. J 
Neurochem, 2002. 80(2): p. 207-18. 
122. 
Sullivan, P.G., et al., Dietary supplement creatine protects against traumatic brain injury. 
Ann Neurol, 2000. 48(5): p. 723-9. 
123. 
Dolder, M., et al., Inhibition of the mitochondrial permeability transition by creatine kinase 
substrates. Requirement for microcompartmentation. J Biol Chem, 2003. 278(20): p. 
17760-6. 
124. 
Nordahl, T.E., et al., Methamphetamine users in sustained abstinence: a proton 
magnetic resonance spectroscopy study. Archives of general psychiatry, 2005. 62(4): p. 
444-52. 
125. 
Volkow, N.D., et al., Addiction: beyond dopamine reward circuitry. Proceedings of the 
National Academy of Sciences of the United States of America, 2011. 108(37): p. 15037-
42. 
126. 
Koob, G.F., L.G. Kenneth, and B.J. Mason, Development of pharmacotherapies for drug 
addiction: a Rosetta stone approach. Nature reviews. Drug discovery, 2009. 8(6): p. 500-
15. 
127. 
Potenza, M.N., et al., Neuroscience of behavioral and pharmacological treatments for 
addictions. Neuron, 2011. 69(4): p. 695-712. 
128. 
Furukawa, T.A., et al., Evidence-based guidelines for interpretation of the Hamilton 
Rating Scale for Depression. Journal of clinical psychopharmacology, 2007. 27(5): p. 
531-4. 
129. 
Heaton RK, C.G., Talley JL, Kay GG, Curtiss G, Wisconsin Card Sorting Test Manual - 
Revised and Expanded, F.P.A.R. Lutz, Editor. 1993. 
130. 
JR, S., Studies of interaction in serial verbal reactions. Journal of Experimental 
Psychology, 1935. 18: p. 643-662. 
131. 
Jensen, A.R. and W.D. Rohwer, Jr., The Stroop color-word test: a review. Acta Psychol 
(Amst), 1966. 25(1): p. 36-93. 
132. 
D, W., Wechsler Memory Scale: Administrative and Technical Manuals, T.P. 
Corporation, Editor. 2009: San Antonio, TX. 
133. 
Hosak, L., et al., Comparison of Wisconsin Card Sorting Test results between Czech 
subjects dependent on methamphetamine versus healthy volunteers. Psychiatr Danub, 
2012. 24(2): p. 188-93. 
134. 
Simon, S.L., et al., The effect of relapse on cognition in abstinent methamphetamine 
abusers. J Subst Abuse Treat, 2004. 27(1): p. 59-66. 
135. 
Provencher, S.W., Estimation of metabolite concentrations from localized in vivo proton 
NMR spectra. Magn Reson Med, 1993. 30(6): p. 672-9. 
136. 
Provencher, S.W., Automatic quantitation of localized in vivo 1H spectra with LCModel. 
NMR Biomed, 2001. 14(4): p. 260-4. 
137. 
Cohen, J., A power primer. Psychol Bull, 1992. 112(1): p. 155-9. 
138. 
J, C., Statistical power analysis for the behavioral sciences. 2nd ed. 1988, Hillsdale, NJ: 
Erlbarum: Lawrence Erlbaum Associates.