Novel EtG-Based Contingency Management for Alcohol in the Severely Mentally Ill
Phase: NA
Conditions: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Alcohol Dependence
Sponsor: Washington State University

Title of Study:  
Individualizing Incentives for Alcohol in the 
Severely Mentally Ill 
 
NCT number: NCT03481049 
Date of Document: 6/27/2025 
 

INTRODUCTION 
We thank the reviewers for their enthusiastic and thoughtful feedback on the initial application (impact 
score = 37, 26th percentile). We respond to their concerns below and place revised text in [bold brackets.] 
Unclear Power Estimates, Lack of Pilot Data. To address these concerns we removed the combined 
Shaping+High-Magnitude contingency management (CM) condition. We now propose a 3-group design to test 
whether the 2 CM adaptations (Shaping CM and High-Magnitude CM) outperform Usual CM and how they 
compare to one another in terms of clinical and cost outcomes. This change increases our statistical power, 
enables detailed power estimates based on previous research (Section 4.G.3), and permits better integration 
of the Addictions Neuroclinical Assessment (ANA) framework with our approach. We also now detail the study 
premise in Section 2.C. Integration of ANA. We now present hypotheses (Specific Aims & Section 2.A.6), 
background information (Section 2.A.6), and data analyses (Section 4.G.2) for our investigation of the relation-
ship between ANA variables and clinical outcomes across the full study sample and in each adaptation of CM.  
Each Study Component is Not Novel Alone. We rewrote Section 3 (Innovation). The revised proposal is 
highly innovative because our anticipated findings, combined with results from our initial funding period, will 
allow us to develop a personalized CM intervention for alcohol use disorders in which patients can be matched 
to CM conditions based on ethyl glucuronide (EtG) levels and ANA variables. Ours will also be the first CM 
study on alcohol use disorders to adapt CM for non-responders. Few prior studies have adapted CM; all have 
methodological flaws, and none addressed alcohol. Nor have any studies investigated whether adapted treat-
ments for co-occurring disorders improve outcomes in non-responders. Given the poor outcomes and high 
costs of heavy drinking with co-occurring serious mental illness (SMI), it is vital to understand how treatment 
efficacy can be improved. Our economic analysis is also novel; it will be the first to address a CM intervention 
for alcohol use and it includes a comprehensive set of cost and benefit outcomes. Some outcomes, such as 
heavy drinking days, have not been studied previously. Our focus on the ANA is also highly innovative, be-
cause no previous CM study has used a theoretical-based framework to investigate predictors of treatment re-
sponse, and no alcohol treatment study has used the ANA to predict outcomes. Thus, considering our strong 
study premise (Section 2.C) and improved rigor, this innovative proposal is likely to have high impact.  
Outcomes Not Published. A manuscript summarizing results of the trial conducted in the initial funding 
period was accepted for publication in the American Journal of Psychiatry (Section 2.B & Appendix); these re-
sults were also presented at 3 national conferences. Three other manuscripts based on study outcome data 
are under review, including one on the link between pre-randomization EtG levels and CM outcomes. As noted 
in the Publication List, this grant contributed to the support of 18 papers and 21 presentations. 
How Will Use of TAU be Assessed and Analyzed? We will monitor all units of non-study healthcare utili-
zation, including substance use and mental health treatment as usual (TAU), with the Non-Study Resources 
Form (Section 4.F.6), which is commonly used to document TAU services in cost-effectiveness research.1, 2 
We will also assess use of TAU through administrative data documenting all TAU encounters. We will analyze 
whether increased use of TAU is associated with improved outcomes (Section 4.G.2). How will Real World 
Treatment Costs be Estimated? The purpose of our economic evaluation is to inform “real world” healthcare 
decisions. Therefore, we will employ a resource costing method to estimate patient-level costs. This involves 
determining a price weight for each resource unit consumed and multiplying price weights by units of service.3-5 
Per-person costs are then computed by multiplying units of service by the respective unit price and summing 
the values. The resources required to implement the intervention in non-study environments will be valued by 
using price weights that reflect specified stakeholder perspectives – the payer of healthcare services, the 
treatment provider, and society (Section 4.G.2). How will Clinical Significance be Determined? We used 
published thresholds for determining clinical significance based on Miller & Manuel (2008): 12% point differ-
ences for dichotomous variables and 50% point differences for continuous measures as the basis for our pow-
er analyses.6 Results of previous CM studies are consistent with these thresholds. Our economic analyses will 
include time abstinent and heavy drinking days averted because these measures are clinically significant to 
consumers, clinicians, payers, and policymakers.   
Will Mental Health Clinicians Implement CM? We now include data from our previous work demonstrat-
ing that CM is an acceptable approach to mental health clinicians (Section 2.A.3). Currently the primary barrier 
to CM implementation is cost.7, 8 Concerns about Recruitment. We offer a more detailed justification for our 
recruitment projections and additional strategies to improve recruitment (Sections 4.C.1, 4.C.2). No Evidence 
for EtG Point-of-Care Test. We apologize for the confusion. We will use an EtG immunoassay, which requires 
an onsite benchtop analyzer, not point-of-care dipcards. This is necessary because point-of-care tests have a 
cutoff (300 ng/mL) that is insufficient to detect light drinking. Dipcards with lower cutoffs will be available in the 
near future, increasing CM feasibility. Drinking Goals Cannot be Imposed. We agree and will investigate 
whether drinking goals predict treatment outcomes by using an established measure (Section 4.F.7).9 
Other Issues are addressed in the application, including How Will Ability to Engage in Procedures be 
Assessed? (Section 4.D.3), Managing Suicidal and Homicidal Risk (Human Subjects), Several Personnel 
Not Named (Budget Justification), Lifetime Prevalence Overstates Annual Prevalence (Section 2.A.1). 

1. SPECIFIC AIMS 
We propose to determine whether modifications to contingency management (CM) can improve outcomes 
and reduce costs in heavy drinkers with serious mental illness (SMI). Up to 46% of adults with SMI experience 
an alcohol use disorder in their lifetimes.10 Alcohol use is associated with high rates of homelessness, hospital-
ization, HIV infection, cigarette smoking, and drug use in this group.11-16 CM offers patients rewards for absti-
nence and is a promising addiction treatment for adults with SMI.17-19 However, research on CM for alcohol use 
disorders (AUDs) has been limited by the lack of a feasible biomarker to verify abstinence.  
In the initial funding period we found that the alcohol biomarker 
ethyl glucuronide (EtG) could detect drinking for up to 5 days in the 
context of a randomized trial of CM.20-24 [In an article in the American 
Journal of Psychiatry] we report that CM participants were 3 times 
more likely to submit alcohol-negative EtG tests than controls.25 
They also reduced self-reported alcohol use and heavy drinking. The 
efficacy of CM was associated with EtG levels during a 4-week pre-
randomization period (Table 1). Participants with mean pre-randomization EtG < 500 ng/mL (i.e., light drinking) 
attained 2.5 times longer duration of continuous abstinence during CM relative to those with mean EtG > 
499 ng/mL (i.e., recent heavy drinking). This difference represents 2 additional weeks of abstinence. In fact, 
heavy drinkers attained a duration of abstinence equal to controls, suggesting they did not respond to CM.  
Two potential CM adaptations might improve outcomes for heavy drinkers. One is Shaping CM, 
which reinforces reductions in use before requiring abstinence and is associated with positive outcomes in 
people with severe cocaine or nicotine addiction.26-29 The other is High-Magnitude CM, which increases the 
magnitude of reinforcers for abstinence and is associated with reduced drug use in those who do not respond 
to a usual CM intervention or submit a drug-positive urine test prior to CM.30-32 While both strategies are asso-
ciated with increased abstinence in extant studies, no randomized trial has 1) compared both these approach-
es to usual CM or to each other, 2) investigated them in alcohol users or adults with SMI, 3) assessed their rel-
ative economic viability, or 4) identified which patients are more or less likely to respond to each approach.  
Therefore, we will compare the efficacy of these 2 adaptations to that of the CM intervention (Usual CM) 
employed in the initial funding period, as well as to one another, in a sample of 240 heavy drinkers with SMI 
recruited from 2 large treatment agencies. Participants with mean EtG > 499 ng/mL during a 4-week observa-
tion period will receive treatment as usual and be randomized to either a) 4 months of CM with standard rein-
forcement levels for submitting alcohol-negative samples (EtG < 100 ng/mL) (Usual CM); b) 4 months of CM 
with high-magnitude reinforcement for alcohol-negative samples (High-Magnitude CM); or c) 1 month of 
standard-magnitude CM for urine samples indicating light drinking (EtG < 500 ng/mL) followed by 3 months of 
standard-magnitude CM for alcohol-negative samples (Shaping CM). The primary outcome will be EtG-verified 
alcohol abstinence during the final 3 months of treatment (when all reinforcement is contingent on abstinence) 
and the 6 months of follow-up. We will also assess the impact of CM adaptations on secondary outcomes.   
Because the primary barrier to CM implementation is related to cost,7, 8 we will conduct a cost-benefit 
and cost-effectiveness analysis to assess the relative economic viability of each CM intervention. [Finally, little 
is known about moderators of outcomes in CM because past studies focused on moderators in isolation, 
without a theoretical model. We will use the NIAAA Addictions Neuroclinical Assessment (ANA)33 framework to 
determine how its 3 domains – executive functioning, negative emotionality, and alcohol-related 
incentive salience – predict treatment outcomes across CM adaptations.] This study promises to have a 
high impact because it will determine if CM adaptations can improve outcomes and reduce costs, and identify 
moderators of CM efficacy in a high-cost, complex, and understudied population. Our Specific Aims are to: 
1. Determine whether levels of alcohol abstinence during the last 3 months of treatment and a 6-month follow-
up period vary by CM condition. We hypothesize that participants in the 2 modified CM conditions will attain 
higher rates of abstinence than those in the Usual CM condition. 
2. Determine whether randomization groups differ on secondary alcohol outcomes, drug use, psychiatric se-
verity, HIV risk behavior, and cigarette smoking. We hypothesize that participants in the 2 modified CM 
conditions will attain better outcomes than those in the Usual CM condition.  
3. Conduct cost-benefit and cost-effectiveness analyses to determine the relative economic viability of the 3 
CM conditions. We hypothesize that the 2 modified CM conditions will dominate the Usual CM group, and 
the Shaping CM condition will be the most cost-effective. 
4. [Identify ANA-based moderators of CM treatment response across the sample and within CM conditions. 
We hypothesize that higher executive dysfunction, negative emotionality, and alcohol-related incentive sa-
lience will be associated with lower levels of alcohol abstinence across all CM conditions. We also hypoth-
esize that participants with higher levels of these characteristics will be more likely to respond to the modi-
fied CM conditions than to the Usual CM condition.] 
Table 1. Mean number of consecutive 
alcohol-negative samples 
 
CM 
M (SD) 
Control 
M (SD) 
EtG < 500 ng/mL 
11.6 (10.7) 
4.9 (3.5) 
EtG > 499 ng/mL 
4.6 (6.9) 
3.7 (7.3) 

2. BACKGROUND, SIGNIFICANCE, AND NEED 
A. Improving Treatment for Alcohol Use and Serious Mental Illness 
2.A.1 Alcohol Use Disorders (AUDs) are Common and Lead to Poor Outcomes. Up to 46% of people 
with SMI, defined as schizophrenia spectrum, bipolar, and recurrent major depressive disorders, suffer from an 
AUD in their lifetimes, [with 13% (schizophrenia) to 26% (bipolar disorder) suffering from an AUD in the last 
year.10, 34-36] Relative to people with SMI who are not substance users, those who use alcohol and drugs 
experience higher levels of psychotic symptoms, use of inpatient psychiatric and emergency care, medical 
expenditures, homelessness, medication noncompliance, treatment attrition, suicidal behavior, cognitive 
impairment, and violence.11-16, 37-41  
2.A.2 Few Adults with SMI and AUDs Receive Effective Treatment. Few people receive treatment for 
co-occurring AUDs and SMI, and still fewer receive evidenced-based treatments.42, 43 Cognitive behavioral 
therapy, motivational interviewing,44-46 intensive case management,47 or a combination of these treatments48 
are associated with reductions in alcohol and drug use in adults with SMI, with effects comparable to non-SMI 
populations.17 However, these treatments are not widely available because of their relatively high cost, 
organizational barriers, and the need for extensive training of supervision of providers.49-51 Less costly and 
more feasible interventions are needed to improve outcomes.  
2.A.3 Contingency Management (CM) is Effective for Adults with SMI. CM interventions provide 
tangible reinforcers (i.e., vouchers, prizes) when patients demonstrate abstinence from substance use, 
typically with a urine test.52 In 5 meta-analyses, CM was associated with increased abstinence from illicit drugs 
and nicotine.52-56 Indeed, CM demonstrated larger reductions in drug use than other psychosocial treatments.54 
Although no economic analyses have been conducted on CM for AUDs, prior economic analyses of CM for 
illicit drug and cigarette smoking, indicate that CM is likely a good value.1, 57-60 In one economic study usual CM 
($240 in reinforcers) was found to be more cost-effective than a low-magnitude CM intervention ($80 in 
reinforcers), suggesting an association between a higher reinforcer magnitude and cost-effectiveness.60   
[Several studies have shown that CM is highly acceptable to addiction providers, and our own research 
indicates that 75% of community mental health clinicians would use CM if it was available.7, 61 CM is 
increasingly being implemented in clinical practice. For example, it is now available in the Veterans Affairs 
system.62 At present, the chief barrier to CM implementation is the cost of CM reinforcers and urine tests.7, 8]  
CM was associated with increased drug abstinence in 3 randomized controlled trials (RCTs) conducted in 
SMI populations.19, 48, 63 One RCT (N=129) used a cognitive behavioral intervention, including CM, to treat 
outpatients with substance use disorders and SMI. Those assigned to the treatment condition had higher rates 
of drug abstinence, better quality of life, and fewer inpatient treatment episodes than controls.48 In a study of 41 
adults with SMI and substance use disorders, we found that those who received access to Social Security 
benefits that were contingent on alcohol and drug abstinence and related behaviors achieved higher rates of 
abstinence than controls.63 In an RCT of 176 SMI outpatients receiving CM for stimulant drug abstinence, we 
observed that CM participants were 2.4 times more likely than controls to submit a stimulant-negative urine 
sample during treatment.19 They also had lower levels of alcohol use, injection drug use, cigarette smoking, 
and psychiatric symptoms, and they were 5 times less likely to experience psychiatric hospitalization.19, 64 
Differences in stimulant use continued during a 3-month follow-up period. Notably, these benefits were 
obtained without additional cost to providers or payers.58 Furthermore, participants who submitted a stimulant-
positive sample before randomization attained a shorter duration of abstinence during CM than 
participants whose pre-randomization samples were negative.65  
Few studies have assessed the efficacy of CM for AUDs, given the absence of a suitable biomarker to 
confirm alcohol abstinence.66 In our initial funding period we overcame this barrier by using EtG to verify 
abstinence. Results of the RCT for AUDs during our initial funding period provide further evidence of the 
efficacy of CM for adults with SMI (see Section 2.B.7).  
2.A.4 Usual CM is Ineffective for Severe Addictions. Usual CM interventions provide reinforcers of 
relatively low value for each urine sample indicating abstinence, with a total reinforcer value of $250-$400 over 
12 weeks.30 Substance use immediately before CM, as verified by urine drug test, is a consistent predictor of 
poor response to usual CM.65, 67-69 In a RCT of usual CM for cocaine dependence, participants who submitted a 
cocaine-positive urine sample before CM attained a median of $44 in CM reinforcers, which was 5 times less 
than participants with negative pre-treatment samples (median= $237).67 In another study, those who tested 
positive for stimulants at study entry submitted stimulant-positive urine samples 64% of the time during usual 
CM, while those who were stimulant-negative submitted positive samples only 18% of the time.68 Our study 
described in Section 2.A.365 and our preliminary data from the initial funding period (Section 2.B.7) also found 
an association of pre-treatment urine tests with outcomes in usual CM.  
2.A.5 CM Must be Modified to Treat Heavy Drinkers with SMI. Initial studies of CM in cigarette smokers 
and cocaine users showed that drug abstinence can be more effectively attained either by increasing the 
magnitude of reinforcement (high-magnitude) or by reinforcing successively closer approximations of 

abstinence (shaping), instead of requiring abstinence only.26-32, 69-71 In previous studies, high-magnitude CM 
(i.e., higher value of reinforcers) improved addiction treatment outcomes, particularly for those with recent pre-
treatment substance use.30-32, 71 While not all studies have found a link between high-magnitude CM and 
increased abstinence,72, 73 null results might stem from the use of samples that included participants with low-
severity addictions, who might not benefit from high-magnitude CM.  
Four studies investigated the efficacy of high-magnitude CM in people with severe addictions. In one, 29 
non-responders to a CM intervention for cocaine were exposed to high-magnitude CM (up to $3,480) and 
usual CM (up to $382). During high-magnitude CM, 45% attained 4 or more weeks of abstinence, while only 
5% achieved this goal during standard-magnitude CM.32 In another study, high-magnitude CM increased drug 
abstinence in 11 treatment-resistant cocaine and opioid users.31 In both of these studies, participants also 
submitted more opiate- and benzodiazepine-negative urine samples during high-magnitude CM relative to 
usual CM or usual care conditions. In a third study, 109 participants who submitted a pre-treatment cocaine-
positive urine sample were randomized to usual CM (reinforcer value $240), or high-magnitude CM (reinforcer 
value $560). For those assigned to high-magnitude CM, the duration of abstinence was 2.5 times longer than 
for those in usual care and 1.6 weeks longer than for those in standard CM. However, the latter difference was 
not statistically significant.30 In a fourth study, conducted by our group, we found that among 103 cigarette 
smokers, high-magnitude CM and pre-CM smoking-negative saliva tests were both correlated with higher rates 
of smoking abstinence during CM.69, 71 
Shaping CM involves reinforcing reductions in use before requiring abstinence. It is associated with better 
outcomes in people who do not respond to abstinence-based CM.26-28 One study randomized 95 adults to 
receive either 8 weeks of CM for cocaine abstinence or 3 weeks of a shaping CM condition, in which they were 
initially required to reduce cocaine metabolite levels by 25% to receive reinforcers, and then received 5 weeks 
of CM for total abstinence.27 After 8 weeks, participants in the shaping condition had higher rates of abstinence 
than the abstinence-only group. A series of studies, conducted by Lamb and colleagues supports the efficacy 
of shaping interventions for hard-to-treat cigarette smokers.26, 28, 29 In these studies, pre-intervention carbon 
monoxide readings were used to personalize targets for CM in shaping schedules. In an RCT of 96 hard-to-
treat smokers, participants who received shaping CM based on initial carbon monoxide results submitted 6 
times as many smoking-abstinent samples as those who received abstinence-based CM.29  
2.A.6 NIAAA’s Addictions Neuroclinical Assessment (ANA) Framework. [While CM is among the most 
effective interventions for substance use disorders, little information is available to predict treatment response. 
As noted in Sections 2.A.4 and 2.B.7, pre-treatment substance use predicts poor CM response. Other 
predictors of poor treatment response include withdrawal intolerance, a history of legal involvement, and low 
levels of motivation, as well as high levels of stressful events, passive coping, psychiatric symptoms, 
impulsivity, and non-adherence to other treatments.65, 74-78 However, previous studies have investigated these 
variables in isolation without a theoretical framework.  
Recently, NIAAA leadership proposed the ANA, a neuroscience-based framework for addiction.33 This 
approach postulates 3 domains – poor executive functioning (e.g., working memory, impulsivity), negative 
emotionality (e.g., depression, anxiety, psychological symptoms of withdrawal), and high levels of alcohol-
related incentive salience (e.g., thinking about alcohol, craving a drink) – as the primary factors that cause and 
maintain AUDs. The authors propose that ANA domains, assessed by self-report and cognitive testing, as well 
as genetic analysis, and eventually neuroimaging can be used to identify groups of patients who do not 
respond to existing treatments. The ANA also provides a framework to guide treatment adaptations to improve 
outcomes for specific groups of non-responders (e.g. those with high levels of executive dysfunction). It might 
also be used to match individuals to specific interventions based on their ANA characteristics. Therefore, the 
ANA provides a structure for developing a personalized medicine approach to AUD treatment.  
The ANA is particularly relevant to CM in our priority population, because 1) heavy drinkers and adults with 
SMI have high rates of executive dysfunction79 and negative emotionality; 2) heavy drinkers have high levels of 
alcohol-related incentive salience;80 3) combating alcohol-related incentive salience with an alternate reinforcer 
is the basis of CM;81 4) little research has described the impact of cognitive dysfunction on treatment outcomes 
for co-occurring disorders;17 and 5) we have observed that negative mood states are associated with poor 
outcomes in CM among adults with SMI, particularly in heavy drinkers (Section 2.B.8).65 Our overall hypothesis 
is that heavy drinkers with higher levels of executive dysfunction, negative emotionality, and alcohol-related 
incentive salience are more likely to respond to modified CM conditions than to Usual CM. We also 
hypothesize that ANA domains will be better predictors of treatment response in specific CM adaptations. For 
example, those with high alcohol-related incentive salience might respond better to the proposed High-
Magnitude  CM than to Shaping or Usual CM conditions, because a highmagnitude of reinforcers will likely be 
necessary to overcome high levels of alcohol-related incentive salience (i.e., reinforcing effects of alcohol).]  
B. Progress Report and Preliminary Studies 
2.B.1 Beginning & Ending Dates. Funding period: 3/1/12 to 2/28/15, no-cost extension through 7/31/16. 

2.B.2 Specific Aims. Aim 1: To conduct an RCT to determine whether a 12-week CM intervention that 
provides reinforcement for alcohol abstinence (measured by EtG) and treatment attendance would be 
successful in reducing alcohol use in 79 people with alcohol dependence and SMI who received treatment as 
usual. Aim 2: To determine whether the CM intervention succeeded in improving addiction treatment 
attendance. Aim 3: To determine whether the CM intervention led to improvements in related outcomes.  
2.B.3 Significance. This was the first adequately powered RCT of CM that used EtG, an accurate and 
feasible alcohol biomarker, to treat AUDs, and only the second RCT of CM in people with SMI.  
2.B.4 Participant Enrollment and Retention. A total of 121 adults met inclusion criteria. Eighty-four (69%) 
completed the 4-week induction period and 79 were randomized to CM (n=40) or Non-Contingent (NC) control 
(n=39) conditions. Twenty-six CM participants (65%) and 29 NC participants (74%) completed treatment. Thirty 
CM participants (75%) and 30 NC participants (77%) completed at least one follow-up interview, representing 
an improvement in retention relative to our previous SMI study, particularly in the CM group. Better retention 
was likely due to our 4-week induction period. 
2.B.5 EtG and Self-Reported Alcohol Use. We found that an EtG > 499 ng/mL detects 71% of heavy 
drinking in the past 2 days and 58% of light drinking in the same period, but only 59% of heavy drinking in the 
past 5 days. In contrast, EtG > 100 ng/mL detects 77% of light drinking in the past 2 days and 79% of heavy 
drinking in the past 5 days.21 Therefore, an EtG level > 499 ng/mL equates to recent heavy drinking, while a 
result of 100-499 ng/mL equates to recent light drinking or heavy drinking during the last 3-5 days.  
2.B.6 CM Is Effective. As described in the Appendix, CM participants were 3.1 times (95% CI=2.2-4.5) 
more likely than controls to submit alcohol-negative samples during treatment.25 The duration of alcohol 
abstinence (defined as the number of consecutive alcohol-negative EtG samples) was twice as long in the 
CM group as in controls (CM M=8.6, SD=12.6, controls M=4.1, SD=1.2, p<0.05). The mean EtG level (409 
ng/mL, SE=40 ng/mL) in CM participants was lower than in controls (735 ng/mL, SE=41 ng/mL, p< 0.05). CM 
participants reported fewer days of alcohol use in treatment (M=3.7, SE=1.6) and follow-up (M=3.3, SE=1.4), 
compared to controls (treatment M=12.0, SE=1.5, p<0.05, follow-up M=10.7, SE=1.4, p<0.05). Those in CM 
were less likely to than controls to report heavy drinking in treatment (OR=3.5, 95% CI=2.3-5.2) and follow-up 
(OR=4.9, 95% CI=1.8-13.5). CM participants were more likely than controls to submit stimulant-negative urine 
samples during treatment (OR=3.2, 95% CI=2.0-5.1) and follow-up (OR=4.6, 95% CI=1.2-17.1), and smoking-
negative carbon monoxide breath samples during treatment (OR=5.4, 95% CI=1.9-15.0).  
2.B.7 Heavy Drinkers do Not Respond to Usual CM. The efficacy of CM was associated with average 
EtG levels during a 4-week induction (i.e., pre-randomization) period. CM participants with mean pre-
randomization EtG < 500 ng/mL (light drinking) attained continuous abstinence that was 2.3 times longer than 
those with mean EtG > 499 ng/mL (recent heavy drinking; p=0.03; see Table 1). This equals 2 weeks of 
additional abstinence. Light drinkers also attained a duration of continuous drug abstinence that was 5 times 
longer (M=10.7, SD=9.5) than heavy drinkers (M=1.9, SD=3.0). Finally, CM participants with pre-treatment EtG 
> 499 ng/mL had levels of abstinence similar to controls, indicating that they did not respond to CM.  
2.B.8 Depression is Linked to Poor Outcomes in Heavy Drinkers. [As predicted by the ANA, heavy 
drinkers (n=42, EtG > 499 ng/mL) with a major depressive disorder attained an average of 1 EtG-negative 
urine sample during treatment (SE=2.2), whereas non-depressed participants averaged 5.6 consecutive EtG-
negative samples (SE=1.5; p<0.05). Among heavy drinkers in CM (n=16), those with depression attained less 
abstinence than non-depressed participants. The difference was not statistically significant, likely due to 
insufficient power. Notably, depression was not associated with alcohol abstinence in light drinkers. 
These findings support our premise that ANA domains can predict alcohol abstinence in heavy drinkers.]  
C. Summary of Significance and Scientific Premise 
[Our long-term goal is to create a personalized medicine approach to CM in which patients are matched to 
a specific type of CM intervention based on their pre-treatment clinical characteristics (e.g., EtG level, ANA 
variables). CM is an effective intervention, and psychosocial treatments have been shown to improve 
outcomes for patients with co-occurring disorders.17, 54 However, many patients do not respond to these 
treatments. The absence of rigorous research on how to improve the efficacy of treatments for co-occurring 
disorders is a major barrier to better care for this population.17, 18 Therefore, by investigating the efficacy of CM 
adaptations, we will address a major gap in the literature on CM and on the treatment of co-occurring 
disorders. The significance of our approach is enhanced by the fact that heavy drinkers with SMI – a high 
cost, complex, and understudied population – have very limited options for effective outpatient care. 
As a result, they rely on costly acute and inpatient care.13 If results support our hypotheses, modified CM 
approaches could offer heavy drinkers with and without SMI an effective treatment option.  
The premise for Aim 1 is robust because 1) our pilot data demonstrate that those who engaged in heavy 
drinking before randomization did not respond to usual CM, 2) previous studies support the efficacy of high-
magnitude and shaping CM in illicit drug users and smokers, 3) these studies had methodological weaknesses 
(e.g., small samples sizes), 4) they did not focus on AUDs, and 5) they did not compare high-magnitude and 

shaping CM. Determining the efficacy of shaping CM might have particular relevance for AUDs, relative to 
illegal drugs or cigarette smoking, because reductions in drinking (especially heavy drinking days) lead to 
clinical and cost benefits.82, 83 The premise for Aim 2 is based on our studies that demonstrate secondary 
effects of CM on non-targeted drug use, cigarette smoking, psychiatric symptoms, and hospitalization. The 
premise for Aim 3 is based on the limited economic literature suggesting that CM is a “valuable” approach, and 
one study that observed a relationship between reinforcer magnitude and cost-effectiveness.60 No economic 
studies have addressed AUDs, or treatment non-responders, or included a comprehensive, meaningful set of 
measures of outcomes and resource utilization, or compared proposed adaptations to Usual CM. We propose 
comprehensive measures of study and non-study resources. Our “real-world” price weights will offer 
stakeholders an accurate, meaningful estimate of the “true costs” of CM adaptations for a high-need group. We 
propose that the Shaping CM will dominate the other conditions, because shaping may lead to increased 
clinical benefit without increasing the costs of reinforcers. The economic analysis will affect both policy and 
practice, since the primary barrier to CM implementation is the cost of reinforcers and urine tests.7, 8 The 
premise for Aim 4 is described in detail in Section 2.A.6; in brief, the ANA provides a framework for identifying 
subgroups of heavy drinkers who are more or less likely to respond to the proposed CM interventions.]  
3. INNOVATION 
[Our proposal is highly innovative. First, it will be one of very few CM studies to investigate how CM can be 
modified to improve outcomes for non-responders, and the only one to focus on alcohol. Second, it will be the 
first study to determine whether modifications to a co-occurring disorders treatment improve outcomes in non-
responders. Third, it will be the first adequately powered RCT of a high-magnitude CM intervention to treat 
non-responders. Previous research involved within-subject comparisons or insufficient sample sizes to detect 
differences between low- and high-magnitude approaches.30-32, 71 Fourth, it will be only the second RCT to 
compare shaping CM to abstinence-based CM interventions; notably, the first addressed tobacco instead of 
alcohol. Our focus on a shaping CM intervention for AUDs is therefore highly innovative, and it might have 
significant clinical applications for patients who are initially unwilling to become abstinent. Fifth, it will be the 
first RCT to compare outcomes between high-magnitude and shaping CM conditions. Sixth, we propose CM 
adaptations that are clinically feasible, rather than approaches such as percentile schedules that might be 
overly burdensome for clinicians. Seventh, our economic analysis is novel, as it will be the first comprehensive 
economic evaluation of CM for AUDs. In addition, we will include cost-benefit and cost-effectiveness analyses 
of our CM adaptations for multiple stakeholders (payers, providers, society) and multiple measures of 
effectiveness: quality-adjusted life-years (QALYs), time abstinent, and heavy drinking days averted (see 
Section 4.G.2). QALYs are an important economic measure, yet only 2 extant CM economic evaluations have 
incorporated them as an outcome measure, and we conducted both of them.1, 58 Eighth, the addition of heavy 
drinking days averted as an economic outcome is novel and timely, as this outcome is highly valued by clinical 
stakeholders and policymakers. Ninth, this will be the first CM RCT to investigate a set of treatment modifiers 
using a theoretical framework (ANA) relevant to heavy drinkers, adults with SMI, and the CM adaptations we 
propose. While ANA variables have been investigated before, ours will be the first alcohol treatment study 
to investigate the ANA as a framework for predicting outcomes. If results support our hypotheses, 
clinicians will be able to use pre-treatment EtG levels and ANA variables to match patients with the type 
of CM that is most likely to achieve positive outcomes. In addition, the proposed study will be the first 
multi-site CM trial of adults with SMI, one of few CM studies to use a follow-up longer than 3 months, and the 
first to use the NIH Toolbox in adults with co-occurring disorders.]  
4. APPROACH 
A. Investigative Team 
Michael McDonell, PhD 
(PI), is an Associate Professor 
in the Elson S. Floyd College 
of Medicine and the Associate 
Director of the Initiative for 
Research and Education to 
Advance Community Health at 
Washington State University 
(WSU). He is the Principal 
Investigator (PI) or Project 
Lead of 3 RCTs of CM as a treatment for AUDs. His research uses the EtG biomarker to implement and 
evaluate CM in adults with SMI, as well as in American Indians and Alaska Natives. His current research 
involves 5 sites across the US. He has authored 26 peer-reviewed articles and obtained 5 externally funded 
grants in collaboration with the Co-Investigators on this application.  
Table 2. Expertise of study investigators 
Expertise 
McDonell McPherson Murphy 
Roll 
Chaytor 
Ries 
CM for Alcohol 
Lead 
√ 
 
√ 
 
√ 
Ethyl glucuronide 
Lead 
√ 
 
 
 
√ 
Statistics/Methods 
 
Lead 
√ 
√ 
 
 
Cost Analysis 
 
 
Lead 
 
 
 
CM Schedules 
√ 
√ 
 
Lead 
 
 
Assessment 
 
 
 
 
Lead 
 
Co-Occurring SMI 
√ 
 
 
√ 
 
Lead 

Sterling McPherson, PhD, is an Assistant Professor and the Director of Biostatistics in the College of 
Medicine at WSU and Associate Director for Analytics at Providence Medical Center. He has authored more 
than 55 publications and was the lead analyst for 9 CM studies, including those led by Dr. McDonell. Dr. 
McPherson investigates behavioral and pharmacological treatments for addictions, missing data analyses, and 
innovative longitudinal methods. He will assist in protocol development and oversee all data analyses. 
Sean Murphy, PhD, is an Associate Professor in the Department of Health Policy and Administration at 
WSU. He is a health economist specializing in economic analyses in substance use treatment trials and has 
conducted economic analyses of CM.1, 58 Dr. Murphy will design and conduct all economic analyses. 
John Roll, PhD, is a Professor and Vice Dean of Research in the College of Medicine at WSU. He has 
been a PI of an NIH Center of Excellence and a PI or Co-Investigator on many large CM studies. He will 
provide expertise in developing CM schedules of reinforcement to maximize reductions in substance use.  
Naomi Chaytor, PhD, ABPP, is an Associate Professor in the College of Medicine at WSU. She is a 
board-certified clinical neuropsychologist whose research focuses on cognitive and psychological predictors of 
treatment outcomes in adults with chronic conditions. She will oversee training, quality control, and 
interpretation of all cognitive and emotional assessment instruments.  
Richard Ries, MD, is a Professor of Psychiatry at the University of Washington with more than 30 years of 
experience conducting research on co-occurring disorders, including serving as a PI on 2 RCTs of CM in SMI 
populations. Dr. Ries will provide extensive expertise in treating co-occurring disorders, serve as the study 
medical director, supervise the Seattle site, and assist with dissemination of results.  
B. Overview of Study 
Activities 
We propose a highly 
rigorous evaluation of 3 CM 
interventions 
for 
heavy 
drinking in a sample of 240 
adults with SMI. To recruit a 
sufficient number of recent 
frequent 
heavy 
drinkers 
(mean EtG > 499 ng/mL), we 
anticipate the need to recruit 
400 participants altogether. 
All will receive psychiatric 
and addiction treatment as 
usual. As shown in Figure 1, 
these 400 participants will 
first take part in a 4-week 
induction period during which 
they will receive reinforcers 
for submitting 3 urine samples per week, regardless of EtG results.  
Participants who meet secondary eligibility criteria (N=240; see Section 4.D.2) will be randomized to 
receive either a) 4 months of standard-magnitude reinforcement CM for submitting alcohol-negative samples 
(EtG < 100 ng/mL) (Usual CM); b) 4 months of high-magnitude CM for submitting alcohol-negative samples 
(High-Magnitude CM); or c) 1 month of standard-magnitude CM for submitting urine samples that indicate 
light drinking (EtG < 500 ng/mL), followed by 3 months of standard-magnitude CM for submitting alcohol-
negative samples (Shaping CM). Our CM paradigm will use the variable magnitude of reinforcement 
procedure (VMRP; see Section 4.E.2), in which participants draw from a bowl for chances to receive items and 
gift cards. Groups will differ only on the number of draws they receive (Usual vs. High-Magnitude), or the 
contingency by which they are allowed to engage in draws (light drinking vs. abstinence).  
Randomized participants will complete follow-up assessments at 1, 3, and 6 months to assess long-term 
outcomes. The primary outcome will be alcohol abstinence, assessed as EtG < 100 ng/mL, during the last 3 
months of treatment (when all reinforcers are contingent on abstinence) and the 6-month follow-up period. We 
will describe group differences in heavy drinking, other alcohol outcomes, drug use, psychiatric symptoms, and 
health behaviors. We will also estimate the costs associated with implementing and sustaining each CM 
intervention in a clinical setting, and determine which condition provides the most economic value. Finally, we 
will assess whether ANA variables are useful in predicting alcohol abstinence during the 3 CM interventions.  
C. Sampling and Recruitment Plan 
4.C.1 Sampling Plan. [The sample will be drawn from 12,000 outpatients with SMI receiving care at 2 
large mental health organizations: Community Psychiatric Clinic in Seattle, WA (metro population ~3 million) 
and Frontier Behavioral Health in Spokane, WA (metro population ~666,000; see Letters of Support). Each site 
Figure 1. Overview of study procedures 

reports that about 25% of their consumers (3,000 overall) suffer from AUDs. Based on screening conducted in 
our previous study, we estimate that 60% of this subsample (1,800) will meet criteria for heavy drinking during 
Year 1 of the proposed study. The two study sites anticipate a total of 500 new patients who are heavy drinkers 
each year. This equates to an overall recruitment pool of 3,050 over 3.5 years (1,800 in Year 1 and then 500 
new consumers annually for 2.5 years). We will recruit 13% (N=400) and randomize 8% (n=240) of eligible 
heavy drinkers to meet our goals. In our initial funding period, 1.5 research staff recruited 121 participants at 1 
site over 2 years, and 84 met criteria for randomization. This equates to 40 consented and 28 randomized 
participants per year per full-time staff effort. For this proposal, 3.65 research staff (more than twice as many) 
will recruit participants at 2 sites over 3.5 years. Using these parameters, we will be able to recruit 515 
participants and randomize 357. These numbers exceed our recruitment goals by 23% and 33%, respectively. 
If more than 400 heavy drinkers are needed to randomize 240, we will continue recruitment until we reach our 
goal. If accrual is much lower than anticipated, Drs. McDonell and Ries will approach other community mental 
health centers where they collaborate on other studies and arrange to expand recruitment to those sites.]  
4.C.2 Recruitment, Screening, and Informed Consent. Our recruitment and consent procedures were 
developed and refined during our previous RCTs of CM with this population [and our community based-RCTs 
with other populations.] Recruitment materials will be placed in clinic waiting rooms, drop-in centers, and other 
locations where potential participants congregate. Clinic staff will distribute study recruitment materials that ask 
consumers if they are interested in participating in the study. Research staff will also offer regular recruitment 
presentations at addictions and mental health treatment groups. [We will also expand recruitment to other 
agencies, shelters, detox facilities, and hospitals that serve patients with co-occurring disorders; post flyers 
throughout Seattle and Spokane; and advertise in newspapers (including newspapers for homeless adults), 
Craigslist, Facebook, websites, radio, and press releases.]  
Interested patients who contact study staff will be screened. Potentially eligible patients will be scheduled 
for an in-person baseline appointment, during which study staff will explain the purpose of the study and the 
procedures involved. Next, they will administer a brief screening measure that assesses capacity to consent to 
research procedures.84 If results indicate concerns about competency to provide consent, the potential 
participant will complete the MacArthur Competency Assessment Tool for Clinical Research (MacCAT-CR), the 
gold standard for assessing informed consent capacity.85 Only those who demonstrate capacity to provide 
informed consent will be enrolled. Participants will review and sign the consent form in the presence of study 
staff, who will read the form aloud as needed.  
D. Eligibility and Randomization  
4.D.1 Initial Eligibility. Eligibility criteria were selected to enable accurate assessment of intervention 
efficacy while maximizing the generalizability of study results. The PI will make final decisions regarding 
eligibility. Inclusion criteria are 1) 4 or more standard drinks on 5 or more occasions in the prior 30 days; 2) 
DSM-5 86 diagnosis of AUD, moderate to severe; 3) DSM-5 diagnosis of schizophrenia or schizoaffective 
disorder, bipolar I or II, or recurrent major depressive disorder (>1 episode); 4) age 18-65 years; and 5) receipt 
of, or eligibility to receive, treatment as usual at study sites. Exclusion criteria are 1) current DSM-5 diagnosis 
of substance use disorder, severe; 2) inability to demonstrate competency to provide consent on MacCAT-CR; 
3) risk of medically dangerous alcohol withdrawal (i.e., seizure within the last 12 months, concern by participant 
or clinician regarding a potentially dangerous withdrawal); 4) prior diagnosis of dementia; and 5) determination 
by the PI and Dr. Ries (medical director) that participation would be medically or psychiatrically unsafe. 
4.D.2 Induction Period. Eligible participants will take part in a 4-week induction period, during which they 
will engage in the VMRP procedure 3 times a week (Section 4.E.2) for providing urine samples. At each visit, 
they will receive 3 draws for prizes when they provide urine samples, regardless of whether the samples are 
positive for alcohol use. Those who provide at least 1 urine sample during each of these 4 weeks will receive a 
$20 bonus incentive. Consistent with previous studies using this approach,87 only participants who 
demonstrate that they are frequent heavy drinkers and [continue to attend study visits] will be randomized. In 
our initial funding period, use of the induction period resulted in a CM completion rate of 65%, which exceeds 
published CM retention rates in non-SMI populations. Therefore, participants who 1) attain an average EtG 
score of > 499 ng/mL (indicating recent heavy drinking) and 2) attend at least 1 study visit during the final 
week of the induction period will be randomized. Given pilot data indicating that 53% of our sample during 
the initial funding period (n=42) had a mean induction EtG > 499 ng/mL, as well as our screening procedures 
to rule out light drinkers, we anticipate that at least 60% of the 400 consented participants (n=240) will be 
eligible for randomization. We will continue to recruit participants until 240 participants are randomized. 
Participants who do not meet criteria for randomization will be referred to other available AUD treatments.  
4.D.3 Randomization Procedures. We will randomize 240 participants to treatment conditions by using 
permuted block randomization. We will stratify across the following variables: 1) study site, 2) gender, and 3) 
baseline EtG level > 1,000 ng/mL, which indicates very heavy recent drinking. Dr. McPherson will randomize 
all participants to treatment conditions and will not have direct contact with participants. 

E. Study Interventions 
4.E.1 Treatment as Usual. The Community Psychiatric Clinic (CPC) in Seattle is a dually licensed 
chemical dependency and mental health agency with 4 large clinics, as well as other locations throughout 
Seattle. Its mental health program provides case management, medication management, group and individual 
counseling, vocational services, and housing services based on the needs of each consumer. Consumers can 
be seen daily for services, but are more often seen once or twice per month. CPC provides intensive outpatient 
addiction treatment, with a focus on treating adults with co-occurring mental illness. Addiction groups are 2 to 3 
times per week. Integrated dual disorders treatment is also available. Addiction providers use cognitive 
behavioral therapy, motivational interviewing, and 12-step facilitation. Frontier Behavioral Health (FBH) is the 
largest provider of mental healthcare in Spokane County. At its 8 locations, FBH provides case management 
(including assertive community treatment), medication management, group psychotherapy, crisis 
management, and  supported employment. Consumers can be seen as often as daily, but typically see a 
clinician once or twice per month, depending on need. While FBH is not a certified chemical dependency 
provider, it offers an integrated dual disorders program that provides group and individual therapy. Clinicians 
use cognitive behavioral therapy, motivational interviewing, and 12-step facilitation. Consumers who suffer 
from substance use disorders but are not enrolled in this program are referred to local addiction agencies.  
4.E.2 Variable Magnitude of Reinforcement Procedure (VMRP). Participants in the 3 CM conditions will 
engage in VMRP each time they meet criteria for obtaining reinforcers over the 16-week treatment period. 
Groups will differ only by the number of times they engage in VMRP (Usual CM vs. High-Magnitude CM) or the 
criterion required to receive reinforcement (light drinking vs. abstinence). VMRP will involve drawing from a 
bowl of 500 chips, some of which represent prizes with different dollar amounts. Fifty percent will say “good 
job” (no prize), 41.8% will result in a small prize ($1 to $5 value), 8% will result in a large prize ($20 to $30 
value), and 0.2% will result in a jumbo prize ($80 to $100 value). For each urine sample that meets 
reinforcement criteria, participants will complete the corresponding number of draws. Table 3 summarizes the 
available number of prize draws and earnings, both maximum and expected, for each CM condition. The actual 
maximum payout will depend on urine test results and the percentage of study visits attended. The number of 
drawings will escalate with each full week (3 consecutive samples) that meets criteria for reinforcement. 
Missing samples or samples that do not meet reinforcement criteria will result in a reset to the original number 
of draws (3 draws for Usual and Shaping CM, 14 draws for High-Magnitude CM) on the next occasion when 
the participant provides a sample that meets reinforcement criteria. If a reset occurs, participants must provide 
3 consecutive samples that meet reinforcement criteria before they are returned to the number of draws they 
previously accumulated. This procedure reduces the probability of relapse after abstinence is initiated.88  
4.E.3 Types of Reinforcers. Prizes will be displayed in cabinets in study offices at clinic sites. They will be 
selected on the basis of participant feedback in our previous studies with this population, and will likely include 
toiletries, small clothing items, gift cards, mp3 players, DVD players, digital cameras, and smartphones.  
4.E.4 Usual CM Condition. Participants in the Usual CM condition will receive the same CM intervention 
administered in the initial funding period and in numerous other studies.55 They will earn at least 3 VMRP 
draws each time they submit an alcohol-negative urine sample (EtG < 100 ng/mL), and they will receive an 
additional draw for each week (3 consecutive alcohol-negative samples) of abstinence. Continuously abstinent 
participants will receive 18 draws for alcohol-negative tests at each of their week 20 appointments. Missing or 
alcohol-positive samples will result in a reset to 3 draws, as explained above in Section 4.E.2. 
4.E.5 High-Magnitude CM. Participants in this group will be required to demonstrate alcohol abstinence 
(EtG <100 ng/mL) to receive reinforcers. However, they will receive twice as many VMRP prize draws overall 
relative to the Usual CM group for submitting alcohol-negative samples during the 16-week treatment period, 
since they will earn at least 14 draws for each negative sample. Note that, although the initial number of draws 
in the High-Magnitude 
group is about 3 times 
higher than in the Usual 
CM 
group, 
the 
difference in the number 
of draws will become 
less pronounced over 
the 16-week treatment 
period, 
and 
will 
ultimately 
approximate 
twice as many chances to engage in VMRP (see Table 3). One additional draw will be accumulated for each 
week (3 continuous alcohol-negative samples) of abstinence. Continuously abstinent participants will be able 
to earn 29 draws for alcohol-negative samples at each appointment in week 20. Missing or alcohol-positive 
samples will result in a reset to 14 draws, as explained above in Section 4.E.2.  
Table 3. Summary of CM schedules and maximum earnings for randomized groups 
CM Group 
Criteria for Reinforcement 
Maximum 
# of Prize 
Draws 
Maximum/ 
Expected 
Payout 
Usual 
EtG< 100 ng/mL (abstinence) in weeks 5-20 
504 
$1,097/$500 
High-Magnitude EtG< 100 ng/mL (abstinence) in weeks 5-20 
1032 
$2,248/$1,000 
Shaping 
EtG< 500 ng/mL (light drinking) in weeks 5-8 
EtG< 100 ng/mL (abstinence) in weeks 9-20 
504 
$1,097/$500 

4.E.6 Shaping CM. Participants will receive the same number of VMRP prize draws as the Usual CM 
group. However, during the first 4 weeks of treatment (weeks 5-8), the criterion for engaging in VMRP will be 
light drinking (EtG < 500 ng/mL) rather than abstinence. During the final 3 months of treatment (weeks 9-20) 
the criterion for receiving reinforcers will shift to alcohol abstinence (EtG < 100 ng/mL). Participants will earn at 
least 3 draws for each urine sample indicating no heavy drinking during weeks 5-8 and no alcohol use at all 
during weeks 9-20. An additional draw will be accumulated for each consecutive week (3 consecutive samples) 
in which participants meet all criteria for receiving reinforcers. Those who continuously meet criteria for 
reinforcers will be able to earn 18 draws at each of their week 20 appointments. Missing samples or samples 
that do not meet criteria for reinforcement will result in a reset to 3 draws, as explained above in Section 4.E.2. 
F. Data Collection and Measures 
4.F.1 Schedule. Data collection will occur during the study period (weeks 1-20, including baseline 
assessment, induction, and treatment) and the follow-up period (weeks 21-47) as shown in Table 4. Baseline 
data collection will take ~120 minutes and include urine tests, self-reported data, and cognitive tests. 
Participants will provide urine samples every Monday, Wednesday, and Friday during the study period. At each 
visit, they will complete brief self-report questionnaires on alcohol use. Weeks 4, 8, 12, 16, and 20 will include 
45-minute data collection visits to assess other outcomes. During follow-up, participants will be scheduled for 
45-minute visits at weeks 25, 33, and 47. They will receive a $30 gift card for completing the baseline interview 
and a $20 gift card for completing each interview in weeks 4, 8, 12, 16, 20, 25, 33, and 47.  
4.F.2 Measures Overview. Baseline data will include assessment of eligibility criteria and measures for 
Aims 1-4. Our primary outcome (Aim 1) is biochemically confirmed alcohol abstinence, measured 3 times per 
week during the final 12 weeks of the treatment period (weeks 9-20) and 3 times total during the 6-month 
follow-up period. Aim 2 outcomes will be collected in a similar fashion. Cost data will be collected for 12 
months before and after randomization. Aim 3 outcomes consist primarily of self-reported use of non-study 
Table 4. Data collection schedule 
Measure 
Baseline 
Wk 0 
Induction 
Wk 1-4 
Treatment 
Wk 5-20 
Follow-up 
Wk 25, 33, 47 
Eligibility Criteria 
 
 
 
 
DSM-5 inclusion/exclusion diagnosis (interview) 
√ 
 
 
 
Consumer at participating agency (self-report) 
√ 
 
 
 
Age (self-report) 
√ 
 
 
 
Current heavy drinking (self-report) 
√ 
 
 
 
Health and risk factor exclusions (self-report/observation) 
√ 
 
 
 
Primary Outcome 
 
 
 
 
Alcohol use (ethyl glucuronide) 
√ 
3x / Wk 
3x / Wk 
Every visit 
Other Secondary Outcomes 
 
 
 
 
Any/Heavy drinking: ATLFB (self-report) 
√ 
3x / Wk 
3x / Wk 
Every visit 
Recent heavy drinking (ethyl glucuronide) 
√ 
3x / Wk 
3x / Wk 
Every visit 
Alcohol cravings (self-report) 
√ 
Weekly 
Weekly 
Every visit 
Alcohol/ drug severity: ASI-Lite (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
Drug use (biochemical) 
√ 
3x / Wk 
3x / Wk 
Every visit 
Cigarette Timeline FollowBack (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
Nicotine dependence: Fagerstrom (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
HIV risk behavior (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
Psychiatric symptoms: PANSS (interviewer rating)  
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
Economic Measures  
 
 
 
 
Drug Abuse Treatment Cost Analysis Program tool 
 
 
 
Wk 47 
Healthcare use by patient medical records 
Past 12 mo Throughout 
Throughout 
Throughout 
Non-Study Resources Form (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
Quality-Adjusted Life-Years: EQ-5D (self-report) 
√ 
Wk 4 
Wk 8,12, 16, 20 
Every visit 
ANA Moderators 
 
 
 
 
Negative emotionality: NIH Toolbox (self-report) 
√ 
Weekly 
 
 
Executive functioning: NIH Toolbox/MCQ  
(cognitive tests/self-report) 
√ 
 
 
 
Alcohol incentive salience (self-report/cognitive tests) 
√ 
 
 
 
Adverse Events 
 
 
 
 
Alcohol withdrawal: SHOT (interviewer rating) 
√ 
3x / Wk 
3x / Wk 
Every visit 
Participant safety (self-report/observation) 
√ 
3x / Wk 
3x / Wk 
Every visit 

healthcare resources, QALYs, days of alcohol abstinence, and heavy drinking days averted. We will collect 
data on each ANA domain to test for predictors of alcohol abstinence during CM interventions. 
4.F.3 Eligibility Criteria. Age and frequency of recent drinking will be assessed by phone screening. The 
Structured Clinical Interview for DSM-5 (SCID-5) interview, clinical trials version,89 will be administered to 
assess diagnostic inclusion (SMI, AUDs) and exclusion criteria. Competency to provide informed consent will 
be assessed as described in Section 4.C.2.  
4.F.4 Primary Outcome. Our primary outcome will be alcohol abstinence during the last 3 months of 
treatment and the 6-month follow-up period. At each study visit, urine samples will be collected and analyzed 
onsite for EtG by using the [commercially available Diagnostic Reagents Incorporated EtG immunoassay on an 
Indiko Bench Top Analyzer (ThermoFischer Scientific, Freemont, CA).] We will use the assay to create a 
binary indicator of alcohol use defined by EtG < 100 ng/mL. That threshold was used in our first funding period 
and in our ongoing CM trials. While it is not associated with false positives due to non-beverage alcohol 
exposure,21, 22 we will ask participants to abstain from using all alcohol-containing products, like hand sanitizer.  
4.F.5 Secondary Outcomes. Alcohol use: Days of self-reported abstinence and heavy drinking will be 
assessed at each visit by the Alcohol Timeline FollowBack,90 which measures the frequency and amount of 
daily drinking. Recent heavy drinking will also be assessed by EtG tests with a cut-off of 500 ng/mL.22 The 
Addiction Severity Index Lite91 will assess the impact of alcohol use on psychiatric, legal, medical, and family 
functioning, as well as self-reported drug use and its severity. We will assess alcohol cravings by using a 10 
cm visual analog scale anchored at 0 (no craving) and 100 (most intense craving possible). Drug use: At each 
study visit, urine samples will be tested for opioids, amphetamine, methamphetamine, cocaine, and cannabis 
with EZ-split point-of-care immunoassays. Health-impairing behaviors: The Timeline FollowBack method will 
assess the number of cigarettes smoked daily.90 The Fagerstrom Test of Nicotine Dependence92 will assess 
the presence and severity of nicotine dependence. HIV risk behavior will be assessed with the brief HIV Risk 
Behavior Scale.93 Psychiatric symptoms: The Positive and Negative Syndrome Scale (PANSS),94 a 
commonly used measure, will be used to monitor the clinician-rated severity of positive (e.g., hallucinations) 
and negative (e.g., avolition) symptoms of schizophrenia-type illness, as well as mood and anxiety symptoms.  
4.F.6 Economic Measures. The average administrative cost of CM will be estimated by using a modified 
version of the Drug Abuse Treatment Cost Analysis Program (DATCAP) instrument.95 DATCAP is a 
standardized, customizable tool that can estimate the costs of programs in various settings. Costs in our 
analysis will include labor, office and urine testing supplies, and CM reinforcers. A detailed costing method will 
be used to value other resources. Data on within-study resource use will be retrieved from study records. Data 
on use of non-study medical resources (e.g., medication and use of inpatient, outpatient, and emergency 
services) will be collected from patients’ electronic health records and supplemented with self-reported data 
from the Non-Study Resources Form (NSRF). Use of non-medical resources (e.g., travel time to medical care) 
will also be self-reported and collected by the NSRF. The validity of self-reported data on healthcare use is well 
established.96-99 Resource unit-cost information will be gathered from various relevant sources. The health-
related quality-of-life preference weights required to calculate QALYs for the cost-effectiveness analysis (see 
Section 4.G.2) will be obtained from the EuroQol 5D (EQ-5D).100, 101 Among generic, preference-based 
instruments, EQ-5D is the most widely used.102 See Table 4 for information on the timing of data collection. 
4.F.7 ANA Framework. We will use the NIH Toolbox, a brief, comprehensive, standardized assessment 
normed on people aged 3-85 years and administered by computer, to assess negative emotionality and 
executive functioning.103, 104 The NIH Toolbox uses computerized adaptive testing, so it can be administered 
efficiently and accurately. Its Emotion battery, which includes measures of negative emotionality (e.g., anger, 
fear, sadness) can be completed in less than 5 minutes. The Emotion battery will be completed at baseline and 
then weekly during induction to accurately assess mood. Other measures will be administered at baseline only. 
The NIH Toolbox Cognition battery requires 30 minutes to complete and includes measures of executive 
functioning, episodic memory, language, processing speed, working memory, and attention. These comprise 
the Fluid Cognition Composite Score, our primary measure of executive functioning. We will supplement this 
battery with the Monetary Choice Questionnaire (MCQ), a delayed discounting measure from the PhenX 
Toolkit.105 Alcohol-related incentive salience will be measured with the Obsessive-Compulsive Drinking 
Scale, a self-report measure of frequency and consequences of alcohol-related thoughts and behaviors,106 and 
the Stimulus-Response Compatibility Task, a performance-based measure of approach-avoidance of alcohol-
related cues.107 We will administer non-ANA measures that might impact outcomes. These include the Stages 
of Change Readiness and Treatment Eagerness Scale, a measure of motivation to change alcohol use,108 
and [an item from the Treatment Experiences and Expectancies questionnaire that assesses drinking goals.9] 
4.F.8 Adverse Events. The risk of adverse events related to study procedures is low.109 Trained research 
staff will assess symptoms of alcohol withdrawal (sweating, hallucinations, disorientation, and tremors) at each 
visit by using the SHOT, a brief but comprehensive measure.110 Withdrawal symptoms will be reported 
immediately to Dr. McDonell, and as appropriate to clinicians for treatment. All adverse events will be handled 
according to our Data Safety Monitoring Plan. 

G. Data Analysis  
4.G.1 General Data Analytic Strategy. We will analyze outcome data in a manner consistent with 
previous RCTs of CM.19, 55 We will analyze our primary and secondary outcomes longitudinally across the final 
12-weeks of CM (when all reinforcers are contingent on alcohol abstinence) and the 6 month follow-up period 
to estimate the effects of CM. Below we discuss our strategy for the primary outcome of alcohol use, which is 
very similar to our strategy for Aim 2 outcomes. We will compute means and standard deviations for 
continuous variables and percentages and frequencies for categorical variables. Measures that fail to satisfy 
the assumptions of parametric tests will be transformed to adjust for differences in variability or skewness. 
Alternatively, nonparametric tests may be used. Our alpha threshold for statistical significance will be 0.05.  
4.G.2 Specific Data Analytic Techniques. Groups will be compared for differences in demographics and 
pre-treatment drug and alcohol use, including data collected during the baseline interview and the 4-week 
induction period. We will evaluate sex as a biological variable by investigating whether sex moderates 
treatment outcomes. Comparisons will use analysis of variance (ANOVA) for continuous variables and chi-
square tests for categorical variables (with Bonferroni-adjusted follow-up tests if necessary). Variables that 
differ between groups at baseline and during the induction period will be used as covariates in subsequent 
analyses, as will baseline measures that co-vary with the outcome measures.  
Aims 1 and 2. Recent alcohol use will be documented by using urine test results (binary outcome: EtG < 
100 ng/mL or EtG > 100 ng/mL) and analyzed by using generalized estimating equations (GEE), generalized 
regression, and Cox proportional hazard regression techniques. Other outcome measures will be derived from 
recent alcohol use, such as 1) alcohol use (yes/no) over time; 2) longest duration of abstinence; 3) total 
number of periods of alcohol abstinence; 4) time to first alcohol abstinence; and 5) time to relapse after a 
specified period of alcohol abstinence. These outcomes will be examined across CM condition, time, and the 
CM condition-by-time interaction to determine whether one condition is superior to the others in promoting 
discontinuation of alcohol use. Additional analyses will be conducted by defining alcohol use in various 
clinically descriptive ways, such as the mean number of heavy drinking days or heavy drinking months across 
groups. Group comparisons of other Aim 2 outcomes will be assessed and evaluated in a similar fashion (e.g., 
longest duration of drug abstinence, mean HIV risk score). 
Analyses will be conducted on the intent-to-treat sample (n=240). This is a conservative approach aimed at 
avoiding overestimation of the treatment effect. It includes all participants who were randomly assigned to 
treatment conditions, regardless of treatment completion. GEE models will be used to evaluate the differential 
change in primary and secondary outcomes by study condition over the 12-month study period (1 month 
before the baseline interview plus the 1-month induction, 4-month treatment, and 6-month follow-up periods), 
and whether condition interacts with change over time. This approach allows us to characterize between-group 
differences in longitudinal outcomes. We hypothesize that the modified interventions (High-Magnitude CM and 
Shaping CM) will lead to higher rates of alcohol abstinence than the Usual CM intervention. If the condition-by-
time interaction variable is significant, we will conduct planned comparisons to examine the hypothesized 
pattern for each outcome. Such an approach will allow us to test this set of hypotheses with specificity. We will 
also conduct a direct comparison of the High-Magnitude CM group and the Shaping CM group.  
Aim 3. We will conduct a systematic economic evaluation of the 3 CM conditions. We will estimate the 
relative economic value of each intervention by conducting cost-benefit and cost-effectiveness analyses. The 
economic evaluation will follow the guidelines recommended by the Panel on Cost Effectiveness in Health 
and Medicine,5 Glick et al.4 and Drummond.111 Cost-benefit analyses will entail determining the costs of each 
condition and extrapolating the downstream savings resulting from reduced alcohol consumption and reduced 
alcohol-related consequences relative to Usual CM, at which point the estimated net benefit of each condition 
can be compared. The primary outcome will be the incremental cost-effectiveness ratio (ICER), which will be 
the incremental cost of one CM condition relative to another, divided by the incremental effectiveness of one 
CM condition relative to another. The most cost-effective condition will be identified by using the rules of 
dominance and extended dominance.4, 112 The primary economic effectiveness outcome in the denominator of 
each ICER will be the QALY, a measure that incorporates both duration and health-related quality-of-life, and 
is recommended as the primary effectiveness outcome measure for economic evaluation studies by the 
Panel on Cost Effectiveness in Health and Medicine.5 In addition to capturing a wider range of consequences 
than clinical effectiveness measures, QALYs permit comparisons across diseases and interventions, enabling 
broader economic interpretation. In addition, generally accepted cost-effectiveness thresholds for defining 
value have been established for QALYs, but not for clinical measures.113-115 Nevertheless, we will also 
calculate ICERs by using the clinical effectiveness measures of duration of alcohol abstinence, to permit 
comparisons with existing economic evaluations of CM interventions that relied on measures of abstinence, 
and number of heavy drinking days averted a clinically significant alcohol outcome measure.57  
Analyses will be conducted from the perspectives of the payer of healthcare services (i.e., the insurer), the 
treatment provider, and society. The payer and provider represent important perspectives, given the pivotal 
role played by each in sustaining the intervention, while the societal perspective is recommended as the 

appropriate reference case.5 All values will be adjusted for inflation. Since no follow-up measurements will be 
taken beyond 12 months following baseline, discounting for time preference will not be required.4, 5 Given the 
differences in mechanisms to generate data, separate multivariable generalized-linear models (GLMs) will be 
estimated to predict the mean value of each resource category at each time point. GLMs permit us to choose 
the most appropriate mean and variance functions according to fit with the data.4 A multivariable GLM will also 
be used to predict health-related quality of life preference weights for each participant at each time point. 
QALYs gained by the intervention will then be estimated by using the area under the curve.4, 5, 116 The method 
of recycled predictions will be used to obtain the final predicted mean values for each study group and 
resource, which will then be summed and tested according to the relevant perspective.4 To account for 
sampling uncertainty in point estimates, both the p-values and standard errors, as well as the confidence 
intervals for the ICER, will be estimated by using nonparametric bootstrapping techniques within the 
multivariable framework. Parametric methods based on parameters obtained from bootstrapping will be used 
to estimate acceptability curves, which illustrate the probability that the intervention is a good value for different 
willingness-to-pay thresholds (e.g., cost-per-QALY). Sensitivity analyses will be performed to account for 
uncertain precision in assumptions and parameter estimates applied in the analysis.5 
[Aim 4. We will examine whether the ANA moderators (executive functioning, negative emotionality, 
alcohol-related incentive salience) interact with CM, and if so, with which CM condition. This will help us 
determine whether a given moderator significantly modified the impact of CM on alcohol abstinence. First, we 
will create an interaction term of CM condition by the moderator in question and examine whether the 
interaction is significant. Second, if the interaction is significant, we will examine whether the outcome varies 
within each CM condition across 3 categories of the moderator in question: 1) Mean ±1 standard deviation, 2) 
> 1 standard deviation, and 3) < 1 standard deviation. This will be accomplished by conducting a planned 
linear trend analysis or simple effects analysis for each CM condition, since we hypothesize that, for example, 
more executive dysfunction will produce worse treatment outcomes.117, 118 Although we anticipate that this 
association will hold true for each condition, we also hypothesize that the effect will be more pronounced in the 
Usual CM condition. If appropriate for a clearer clinical interpretation, we will use centering (i.e., subtracting the 
mean from all participant values on the measure) on the moderator being examined, which is consistent with 
current expert recommendations.117]  
Missing Data. We have developed extensive tracking procedures to reduce missing data, which will be 
handled in a manner consistent with current expert recommendations.19, 69, 119-121 We will use maximum 
likelihood or multiple imputation and extensive sensitivity analyses, including “missing not at random” 
approaches, to examine the robustness of treatment effects under varying assumptions. These approaches 
are preferable to other data imputation approaches, such as mean imputation.122 
4.G.3 Power Analysis. [Aims 1 and 2. Our choice of sample size for randomization (n=240) is based on 
statistical power calculations for the primary aim of reducing alcohol use and the secondary aim of improving 
other outcomes during the final 3 months of the intervention and the 6-month follow-up period. We estimated 
power by using clinically significant cutoff estimates in conjunction with previously reported effect sizes of 
adapted CM interventions.6, 123 Clinically significant cutoffs derive from studies of addiction treatment clinicians, 
who report that a 10-12% difference in dichotomous outcomes (such as percent abstinent), or a 50% decline 
compared to the base rate, or a doubling of continuous measures such as number of weeks abstinent, would 
be enough to justify adoption of a given treatment in their practice.6 This measure of clinical significance for 
continuous outcomes represents a large effect size. If used exclusively to guide our power analyses, this 
threshold would leave the current trial powered only on a doubling of continuous measures, which could lead to 
overlooking potentially meaningful effects. Thus, we powered our analysis primarily on clinically meaningful 
differences in binary outcomes. This approach gives us adequate power to detect clinically meaningful 
improvements in continuous outcomes that are less than double the continuous measures.  
Background. In one sample of difficult-to-treat cocaine users, the lowest effect observed was a 10% 
increase in the proportion of negative urine samples submitted by high-magnitude CM participants compared 
to those in usual CM.30 In a similar sample of cocaine users, a difference of 32% was found between usual 
versus high-magnitude CM groups.32 In a sample of difficult-to-treat methadone maintained cocaine users, 
abstinence increased by 14% in high-magnitude CM.31 Thus high-magnitude CM has been shown to 
consistently produce clinically meaningful and statistically significant results among patients who smoke or use 
illicit drugs.  
Although shaping CM is less studied, a trial with hard-to-treat smokers found a 17% increase in smoking-
negative samples submitted by shaping CM participants relative to usual CM participants. Shaping CM 
participants also submitted an average of 21 smoking-negative samples, while usual CM participants submitted 
an average of 3.5 smoking-negative samples. These differences meet the above criteria for clinical 
significance.  
With regard to our Aim 2 outcomes, we highlight findings from a study with cocaine users identified as non-
responders to usual CM. When participants received high-magnitude CM, opiate abstinence increased by 14% 

and benzodiazepine abstinence increased by 11% relative to when participants received usual CM.32 In 
another study of CM for cocaine use in methadone patients, opiate abstinence increased by 8% in participants 
receiving high-magnitude CM.31 Finally, a study utilized data from a large national schizophrenia treatment trial 
to establish a threshold for statistical significance in PANSS outcomes (our psychiatric severity measure). They 
found that a change in PANSS score of 34% was considered a clinically significant difference.123 While this is 
lower than the cutoff for clinical significance noted above (i.e., 50% decline), our power analyses demonstrate 
that the proposed trial will be able to detect such an effect size, as well as slightly smaller differences. 
Aim 1 and 2 Power Analysis. While we will randomize 240 participants, our power calculations are based 
on a sample size of n=180, or 60 per group, to adjust for an estimated attrition of 25% after randomization. We 
emphasize that our methodology for handling missing data will help to recapture some of the power lost to 
attrition. All power analyses use an alpha threshold for statistical significance of 0.05. Power analyses for Aims 
1 and 2 are based on both binary and continuous outcome measures (e.g., negative or positive for alcohol use, 
longest duration of abstinence). For binary measures, our trial will have at least 85% power to detect a 7% 
difference between treatment groups. We will also maintain at least 83% power to detect an 8% difference in 
binary outcomes when conducting our planned comparisons after our initial, omnibus test. For continuous 
measures, our trial will have at least >99% power to detect a 50% mean reduction in measures of continuous 
alcohol use (e.g., heavy drinking days) between treatment groups. We will also maintain at least >99% power 
to detect an 50% mean decrease in continuous alcohol use measures (e.g., heavy drinking days) when 
conducting our planned comparisons after our initial, omnibus test. Our estimates for continuous outcomes 
might seem well informed but overly optimistic in the context of the literature on clinical significance. Therefore, 
we performed a second power analysis for clinically informative but less clinically important effects. Notably, 
we will still maintain at least 83% power to detect a 25% mean reduction in continuous outcome measures 
(e.g., heavy drinking days) between treatment groups. We will also maintain at least 88% power to detect a 
30% mean reduction in continuous alcohol use measures when conducting our planned comparisons after our 
initial, omnibus test. This result is important, given the clinical significance threshold of a 34% decrease noted 
above for PANSS scores. Our power estimates for Aims 1 and 2 in this section demonstrate that we will have 
sufficient power to detect effects that are slightly smaller, not only than those previously reported, but also than 
those found to be clinically significant, even after accounting for attrition. 
Aim 3 Power Analysis. Power analyses for cost-effectiveness analyses are based on assumptions 
regarding differences in cost and effect, standard deviations of cost and effect, the correlation of the difference 
in cost and effect, desired confidence and power levels, and the maximum willingness-to-pay value.124, 125 
Using a range of values for each of these factors, as well as the target sample size of 180 (60 per group), we 
estimated the power for the primary outcomes of these analyses: cost per QALY, cost per abstinent year, and 
cost per heavy drinking day averted. We estimate at least 80% power to be 95% confident that an intervention 
is a good value at the commonly cited lower-bound willingness-to-pay threshold of $50,000 per QALY.114, 115 
Power for the cost-benefit analysis is more speculative. However, if the intervention cost is $396 (SD=$41) and 
there is a cost offset of $1,000 from reductions in use of high-cost healthcare services,2, 58 the net benefits 
would be $604. To achieve 80% power, the standard deviation of the cost offset would have to be less than 
$1,650. While difficult to forecast, it is not unreasonable to have a standard deviation less than 165% of the 
mean cost offset. Hence, we should have sufficient power for our cost-benefit analysis. 
Aim 4 Power Analysis. For binary outcomes (e.g., submissions of EtG-negative samples), our trial will 
have at least 81% power to detect a 10% difference across the moderator (e.g., executive functioning) by 
group interactions. We will also maintain at least 80% power to detect a 13% difference in binary outcomes in 
our simple effects analysis or linear trend analysis to probe the interaction further. For continuous outcomes, 
our trial will have at least 80% power to detect a 30% mean reduction in continuous alcohol use measures 
(e.g., heavy drinking days) across the moderator (e.g., executive functioning) by group interactions. We will 
also have at least 82% power to detect a 44% mean reduction in continuous alcohol use measures (e.g., 
heavy drinking days) when conducting our simple effects analysis or linear trend analysis to probe the 
interaction further. Our planned analyses for Aim 4 provide sufficient power for nearly every scenario, even 
with a conservative estimate, because our missing data strategy will help to recover much of the lost power.] 
H. Timeline 
Project Phase 
Year 1 
Year 2 
Year 3 
Year 4 
Year 5 
Start-up 
 
 
 
 
 
 
 
 
 
 
Recruitment 
 
 
 
 
 
 
 
 
 
 
Induction/Treatment period 
 
 
 
 
 
 
 
 
 
 
Follow-up 
 
 
 
 
 
 
 
 
 
 
Data analysis 
 
 
 
 
 
 
 
 
 
 
Dissemination of results 
 
 
 
 
 
 
 
 
 
 

PROTECTION OF HUMAN SUBJECTS & RISKS TO THE SUBJECTS 
A. Overview of Human Subjects Involvement, Sources of Materials, and Risks  
A.1 Human Subjects Involvement and Characteristics. Participants will be 400 heavy drinkers 
diagnosed with moderate to severe alcohol use disorders (AUDs) and serious mental illness (SMI): 
schizophrenia, schizoaffective disorder, bipolar I or II, or recurrent major depressive disorder. All participants 
will be receiving treatment as usual at one of two partnering treatment agencies. Participants will be involved in 
the study for an 11-month period. Participants who meet inclusion/exclusion criteria and provide informed 
consent will take part in a study baseline interview and a 4-week induction period where reinforcement is 
delivered for providing urine samples 3 times a week. After the 4-week induction all participants who 1) attain 
an average EtG score of >499 ng/mL (suggesting frequent heavy drinking) AND 2) attend at least 1 study visit 
during the final week of the induction period will be randomized to treatment conditions. Based on pilot data 
and our screening procedures which will rule out light drinkers, we anticipate at least 60% of the 400 initially 
eligible participants will meet criteria for randomization (n=240). These participants will then be randomized to 
take part in one of the three contingency management (CM) interventions. All those who do not meet criteria 
for randomization will be referred to other AUD treatments available at our partnering agencies, and when 
necessary, other local providers.  
During the 16-week treatment period, participants will submit urine samples 3 times a week to assess 
alcohol use. The 16-week treatment period will be followed by a 6-month follow-up period where outcomes will 
be assessed at 1-, 3-, and 6-months after the treatment phase. During the induction and treatment periods 
participants will complete other study outcome measures (e.g., self-report) on a monthly basis. Participants will 
be reimbursed for study participation at baseline ($30), completion of the induction period ($20), and at each of 
their monthly interviews (8 X $20). The CM intervention duration is similar to previous studies.55   
It is expected that the demographics of participants in this study will reflect the overall gender and ethnic 
characteristics of the consumers currently receiving services at Community Psychiatric Clinic and Frontier 
Behavioral Health. 
A.2 Source of Study Materials. Research materials obtained from participants will include data on 
demographics, personal characteristics, psychological assessments, alcohol and drug use, urine specimens, 
and healthcare utilization. At the baseline interview each participant will sign a Health Insurance Portability and 
Accountability Act (HIPAA) form authorizing release of electronic medical records. Data and materials will be 
available only to authorized staff in a de-identified  manner. All data with information concerning an individual 
participant, including urine samples and medical utilization data, will be marked with a unique code rather than 
the participant’s name. The link between the code and the name will be stored on a password protected 
encrypted excel file that is only accessible by study staff. All medical utilization data will be transferred to 
investigators using an encrypted data transfer system. Direct identifiers will be removed from these data as 
soon as possible. To the extent possible, no information about a participant will be released to anyone without 
the participant’s explicit written consent, except in the event of a medical emergency, when pertinent medical 
information will be given to medical personnel caring for the participant, or as required by law. 
A.3 Handling of Urine Samples. Urine is not considered a biohazard. However, over the last 8 years we 
have handled over 20,000 urine samples and have developed detailed procedures for the handling of urine. 
When handling urine all study staff will wear gloves, eye protection, and lab coats. They will follow appropriate 
disposal procedures for all urine and laboratory consumables. If a urine sample is observed to contain blood, 
our research staff will immediately place the urine sample in a biohazard bag and dispose of it at appropriate 
Washington State University biohazard receptacles located at each site.  
A.4 Potential Risks. The anticipated physical, psychological, social, and legal risks are minimal. However, 
as in all trials of this nature, possible outcomes include unauthorized disclosure of confidential information; 
discomfort or embarrassment related to urine collection or questionnaires dealing with personal habits, 
lifestyles, or drug or alcohol use; and possible unwanted encounters with friends or associates at the treatment 
center. If participants find any aspects of their involvement in the program psychologically or otherwise 
uncomfortable, they will be encouraged to discontinue participation and assisted in finding a more acceptable 
form of treatment. Alcohol withdrawal is another risk of study participation. Suicidal and homicidal thoughts and 
behaviors might also occur. Our team has extensive experience managing such behaviors. We describe how 
we will manage these risks in detail below.  
B. Adequacy of Protection against Risks 
B.1 Recruitment and Informed Consent. Clinic staff will give all potential participants a study brochure 
and a form asking if they would like to be contacted by study staff. Study staff will also describe the study at 
group treatment sessions and provide study contact information. Study staff will then either obtain contact 

information for consumers who indicate interest in participation or will be contacted directly by interested 
consumers. Study recruitment materials will also be posted at locations that adults with co-occurring disorders 
are likely to frequent, such as transit centers and local hospitals. Study staff will contact potential participants to 
provide additional study information and screen for recent heavy drinking. Recruitment materials will be 
approved by the Washington State University Institutional Review Board. Initial interviews with potential 
participants and all subsequent contacts will be conducted in private offices at each study site. All information 
containing participant contact information will be stored in locked file cabinets in locked offices at each site.  
Informed consent will be obtained in writing from all potential participants before research participation. 
During the initial interview, potential participants will be told about the study’s purpose and all procedures 
involved. For those who decide to participate, study staff will administer the University of California, San Diego 
Brief Assessment for Capacity to Consent (UBACC), a brief screener of capacity to consent to research 
procedures designed for adults with psychiatric illness.84 Those who cannot demonstrate capacity to provide 
informed consent on this screener will be administered the MacArthur Competency Assessment Tool for 
Clinical Research (MacCAT-CR), a comprehensive, gold standard tool for assessing capacity to provide 
informed consent for adults with SMI.85 Only people with a demonstrated capacity to provide informed consent 
on these measures will be enrolled in the study. Staff will emphasize that there is no pressure to participate, 
that referral to alternative treatment will be provided if participants do not wish to continue in the study, and that 
potential participants are encouraged to speak to Dr. McDonell or study staff about any concerns related to 
study participation. Issues of confidentiality will be discussed in detail. Interested adults will then read and sign 
the informed consent form in the presence of study staff, or study staff will read the form to them and witness 
their signature. Two forms will be signed, one for the participant to keep and another for study records. The 
latter form will be kept in a locked file separate from participant data. Participants who have questions about 
informed consent or any other aspect of the research at any time will be directed to Dr. McDonell. Participants 
will complete a baseline interview within 2 weeks of signing the consent form. All research staff will receive 
extensive training in appropriate procedures to obtain informed consent, including administering measures of 
capacity to provide informed consent. They will conduct a mock consent interview for Dr. McDonell to ascertain 
the adequacy of the consent process and ensure consistency in the process across participants. Dr. McDonell 
has extensive experience in consenting adults with SMI through his previous studies.  
B.2 Protection Against Other Risks. All study staff will be trained to be sensitive to issues surrounding 
confidentiality and other forms of participant risk. If at any time a participant expresses discomfort over any 
activity of the treatment program, staff will be told to discontinue the distressing activity and seek consultation 
to minimize risk. All data will be directly entered into a password-protected and encrypted RedCap database. 
The database will be hosted on a secure server at Washington State University and backed-up nightly. Study 
identification numbers will be the only identifier entered into the database. We will also request a Certificate of 
Confidentiality for this study from the NIAAA. 
Potential participants will be thoroughly screened to eliminate candidates with disorders or conditions that 
are contraindicated, including high risk of alcohol withdrawal. Social risks from participation are expected to be 
minimal, since sensitive material is unlikely to be divulged. We will emphasize the confidential nature of all data 
collected in this study to potential participants. We will also explain thoroughly our safeguarding procedures. 
Participants who are judged by project investigators at any point to be a danger to self or others, or who are 
judged to be in grave danger due to continued alcohol or drug use or to medical or psychiatric problems, will be 
discontinued from the study but actively connected with appropriate treatment services. Details on this safety 
procedure will be included in the study consent form.  
While our exclusion criteria are intended to prevent the participation of patients who are likely to experience 
dangerous alcohol withdrawal, we anticipate that withdrawal symptoms might occur, especially if the CM 
interventions are effective. Study staff will be trained to assess any and all symptoms of withdrawal and 
administer the SHOT, a brief and well validated measure of alcohol withdrawal symptoms, at each 
appointment.110 If withdrawal symptoms are observed, they will be immediately reported to Dr. McDonell. He 
will consult with Dr. Ries, as well as site medical personnel to decide how to best manage these symptoms. All 
sites are experienced and prepared to handle alcohol withdrawal. Dr. Ries has over 30 years of experience in 
the medical management of alcohol withdrawal. We have used this procedure in 3 RCTs of CM for alcohol use 
disorders and have had no cases of dangerous alcohol withdrawal. Any event that might affect participants’ 
safety will be immediately reported to the Dr. McDonell, who will work with local healthcare providers to ensure 
participant safety.  
[Through their research studies and clinical experience, Drs. McDonell and Ries have extensive expertise 
managing suicidal and homicidal risk in adults with co-occurring disorders. Dr. McDonell, a licensed clinical 
psychologist, has 8 years of experience managing serious adverse events, including suicidal and violent 
thoughts and behavior in adults with co-occurring disorders. Through our studies, we have developed and 

implemented protocols to manage suicide-risk and aggressive and violent behavior. Participants who report a 
suicidal attempt or self-harm behavior in the last thirty days and/or report repeated suicidal thoughts during the 
previous two weeks will be assessed for suicide risk by a treatment as usual clinician before they leave the 
clinic. The clinician will then determine the appropriate plan for managing suicide risk and refer participants to 
crisis or emergency services, if necessary. Study staff will also notify Dr. McDonell when suicidal behavior or 
ideation is reported and the outcome of the clinician’s assessment. Participants will be notified of this 
procedure at informed consent. All research staff will be trained in this procedure by Dr. McDonell, who has 
over 5 years of experience providing dialectical behavior therapy to patients with chronic suicidality and 
addiction. We have utilized this procedure in 3 of our CM RCTs and it is effective, with no-suicidal behaviors 
occurring after our procedure was implemented.  
Consistent with the literature, we have observed extremely low rates of homicidal ideation or violent 
behavior in our studies of adults with SMI. During the thousands of visits with over 300 participants, 2 
participants have made verbal threats or engaged in violent behavior (shoving a staff member). We have 
managed each of these situations in close collaboration with treatment as usual clinicians. Because our 
research takes place in community clinics, research staff will be trained in and comply with all clinic safety 
procedures. All threats of violence will be taken seriously by study staff who will follow clinic and study 
procedures, staff these cases with the Drs. McDonell and Dr. Ries, and call 911 if a potentially life threatening 
situation occurs. Additionally, study staff will follow all laws pertaining to mandated reporting of child or elder 
abuse. All of these events will also be reported to the study’s Data Safety Monitoring Board, the National 
Institutes of Health, and the Institutional Review Board, as described in the Data Safety Monitoring Plan.]  
B.3 Adverse Events. We have developed project stopping rules to protect the safety of study participants. 
In the case of a Serious Adverse Event (as defined by the FDA and the Washington State University 
Institutional Review Board), the study will be stopped and no further enrollment will take place until an 
investigation of the event has been conducted by Dr. McDonell , the Co-Investigators, the Data Safety 
Monitoring Board, and Partnering Agency Leadership. A determination of the association of the adverse event 
with the study intervention will be made and appropriate modification of the protocol will be executed if an 
association is suspected. If protocol modifications to ensure the safety of future study participants cannot be 
executed, the study will be terminated. Serious Adverse Events will be reported to the Washington State 
University Institutional Review Board within 24 hours and to the appropriate program officer of the National 
Institutes of Health within 48 hours. Dr. McDonell must decide whether the event should be classified as 
serious or not by using standard FDA guidelines for Serious Adverse Events. Non-serious events will be 
reported to the Data Safety Monitoring Board quarterly and to the program official and Institutional Review 
Board annually.  
B.4 Data Safety Monitoring Plan and Board. This Human Subjects Research meets the National 
Institutes of Health definition of a Phase II clinical trial. This clinical trial requires registration in 
ClinicalTrials.gov. Because this is a multi-site trial an appropriate Data Safety Monitoring Board and Plan has 
been developed and is described in the Data Safety Monitoring Plan section of the application.  
C. Potential Benefits 
The minimal risks anticipated for study participants are reasonable in relation to the anticipated benefits, 
because heavy drinkers will receive potentially valuable treatment for their heavy drinking at no cost. 
Identification of effective treatment of heavy drinkers who suffer from SMI may also provide useful information 
to current treatment systems and thereby benefit others. The study will also provide useful data about the cost 
effectiveness of CM interventions to the partnering agencies, as well as information to clinicians about CM 
adaptations that might be particularly effective for specific individuals. The data collected in the proposed study 
will have a high level of external validity and may serve to render CM interventions more effective for this 
population. 
D. Importance of Knowledge to be Gained 
The results of the proposed research may lead to more effective treatment for heavy drinkers who suffer 
from SMI and heavy drinkers more generally. Potential improvements in secondary outcomes, estimates of 
cost-effectiveness, and a better understanding of the moderators of alcohol abstinence are important 
contributions to the scientific literature and will provide important information to consumers, treatment providers 
and policy makers. Once tested, this intervention can be disseminated in community mental health centers and 
other places where adults with alcohol use disorders and SMI are treated.  
E. ClinicalTrials.gov Requirements 
This proposal includes an applicable clinical trial that requires registration in ClinicalTrials.gov. 

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