Early Intervention to Reduce Alcohol Misuse and Abuse in the Ohio Army National Guard
Phase: NA
Conditions: Alcohol Use
Sponsor: Keming Gao

 
 
 
 
 
 
 
 
 
Early Intervention to Reduce Alcohol Misuse and Abuse in the Ohio Army National Guard 
(Project GUARD) 
 
Protocol 
 
Version Date: 02/18/2019 
 
NCT Number: NCT02860442 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Objectives 
The proposed project, Project GUARD, is a fully-powered randomized controlled trial of a 
smartphone app which includes an alcohol brief intervention (SP-BI) versus an Enhanced Usual 
Care (EUC) condition for National Guard members in the State of Ohio who meet criteria for at-
risk drinking in the previous 4 months.   
 
The specific aims are to compare SP-BI and EUC in: 
1. Reducing the frequency and intensity of at-risk drinking at 4 -, 8- and 12-months; 
2. Decreasing binge drinking at 4-, 8- and 12 months. 
 
The secondary aims are to: 
1. Compare the SP-BI and EUC conditions in reducing the frequency of illicit drug use and 
depressive symptoms at 4-, 8- and 12-months; 
2. Examine if deployment status moderates the effect of intervention assignment (SP-BI or 
EUC) on post-intervention drinking, depressed feelings, and other substance use. 
 
Design 
After tailoring the content of the SP-BI intervention for NG soldiers, the proposed study will 
screen ~3,100 individuals over the three year enrollment period to identify 750 participants with 
at-risk drinking across the 2 sites. Participants in this study will be randomized to either the SP-
BI (n=375) or the EUC condition (n=375) and followed at 4, 8 and 12 months post-enrollment. 
The study is intended to address the primary and secondary aims and corresponding hypotheses 
listed below. 
 
Methods 
Participants who are randomized to the SP-BI condition will receive an informational brochure 
with resources available to members of the military related to mental health and alcohol use and 
will download a free app on to their smartphones. The app will be developed to be used on both 
Android and iPhone platforms and will be used over 12 weeks to deliver the study intervention. 
They will be contacted to complete 4-, 8-, and 12-month follow-up assessments. 
 
Those assigned to the control condition will receive an informational brochure with resources 
available to members of the military related to mental health and alcohol use. They will be 
contacted to complete 4-, 8-, and 12-month follow-up assessments. 
 
Randomization: 
After the baseline assessment is completed, participants will be assigned to one of the two study 
conditions (SP-BI or EUC) using a computerized randomization system. Random assignment 
will be stratified based on gender and an AUDIT-= score > 19.  
 
Intervention 
 
Brief Intervention 
Smart Phone (SP-BI) Content. Participants in the SP-BI condition will receive a 20-30 minute 
intervention session through an app program.  The intervention will be based on the FRAMES 

format: providing personalized Feedback (regarding substance use, risk factors), emphasis on 
Responsibility for change, Advice, Menu of options, Empathic clinical behaviors, and support of 
Self-efficacy regarding making changes. The intervention is designed to address the primary 
target behavior of alcohol use, and will include a tailored review of participants’ goals/values, 
feedback regarding their present alcohol use patterns and consequences (either actual 
experiences or potential based on risk behaviors), developing a discrepancy between their 
alcohol use and ability to meet goals and values through a decisional balance exercise, and 
formulation of a “change plan” tailored for each participant. 
 
Measures 
Background Characteristics. The Substance Abuse Outcomes Module (SAOM) will be used to 
measure background characteristics including basic demographics (i.e., gender, age, race, 
ethnicity, marital status) and other background variables (e.g., education, employment, income, 
legal history). The SAOM has undergone extensive reliability and validity examinations (Smith 
et al., 2006).  
 
Alcohol Use.  As recommended by (Babor, 2007; Babor & Hall, 2007; Babor et al, 2007) and the 
IOM Report (Institute of Medicine, 2012) we will administer the full AUDIT which includes the 
AUDIT-C ( Bush et al., 1998; Saunders et al., 1993)  assessing alcohol consumption using 3-
items: average quantity, average alcohol use frequency, and binge drinking (5 or more drinks/day 
for men; 4 or more drinks/day for women) over the past 4-months, and the 7 consequence 
questions.  In addition to the standard item responses (which are categorical groupings such as 5-
6 drinks), we will probe for exact numbers. Thus, for data analyses purposes, we will assess 
these alcohol consumption variables using counts and continuous response scales. Recent 
literature, including a review paper (Reinert & Allen, 2007) and population-based study (Dawson 
et al., 2005a, 2005b)  support the internal consistency, test-retest reliability, and accuracy of the 
AUDIT-C in identifying at-risk alcohol use (hazardous use).   
 
Revised Injury Behavior Checklist (RIBC). The original injury behavior checklist was developed 
for adolescent (Starfield, 1991) and revised for adults (Longabaugh et al., 2001). Participants 
indicate in the past year how often each of 18 injuries occurred, if they were treated by a doctor 
for the injury, and if alcohol was consumed within 2 hours of the injury.  Prior research 
demonstrates the RIBC is related to outcomes following a brief intervention (Longabaugh et al., 
2001). The RIBC has been modified to include two collapsed questions for intentional and 
unintentional injury. 
 
Other Drug Use. The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST 
3.0) is an 6-item questionnaire developed as a brief screen for at-risk use of psychoactive 
substances (WHO Assist Working Group, 2002) including:  tobacco, alcohol, cannabis, cocaine, 
amphetamine-type stimulants, sedatives, hallucinogens, inhalants, opioids, and other drugs. We 
will use the item that measures how often each substance was used in the past 4 months.  
 
Depressive Symptoms. The PHQ-9 (Kroenke et al., 2001) will further assess symptoms of 
depression; it has 94% specificity and 99% sensitivity for current major depressive disorder. The 
total score ranges from 0-27, with severity defined as: none (0-5), mild (6-10), moderate (11-15), 
major (16-20), severe (21+).  Recent suicidal ideation will be assessed with one question: “Have 

you thought that you would be better off dead or that you wanted to hurt yourself in some way?" 
from the PHQ-9, and the four additional questions, “Did you have a period of time where you 
thought about death a lot?”, “ Did you feel so low you thought a lot about committing suicide?”,  
“Did you make a plan as how you might do it?”,  “Did you attempt suicide?” A positive response 
to any of these question will create a “flag” in the computer that will prompt staff (regardless of 
study condition) to implement a protocol for further assessment for harm to self. 
 
Self-efficacy. A revised, version of the Modified Drinking Motives Questionnaire (DMQ-R) 
(Grant et al., 2007) will be used to assess self-efficacy across a variety of high-risk situations. 
Greater self-efficacy predicts positive outcomes following alcohol treatment (Annis & Graham, 
1998; Breslin et al., 2000; LaBrie et al., 2005a, 2005b, 2005c) conceptually is a key component 
of MI,100 and is related to less alcohol use among at-risk drinkers (Walton, 2007a, 2007b) 
Psychological Distress. The Generalized Anxiety Disorder 7 (GAD-7) questionnaire is used for 
screening and severity measuring of generalized anxiety disorder and will be used as a measure 
of perceived anxiety (Lowe et al., 2008). 
 
The Post-Traumatic Disorder Checklist-Military Version (PCL-5) will be used to measure DSM-
V PTSD symptoms  (Weathers et al., 2013).  We will also include items from the Mini-
International Neuropsychiatric Interview (MINI) to assess PTSD symptoms (Sheehan et al., 
1998). 
 
Unit Risk Inventory. Items from the Unit Risk Inventory (Army Center for Substance Abuse 
Program, 2011), developed by the Army Substance Abuse Program are included to assess 
financial situation, suicidality and drinking attitudes in the military. 
 
Healthcare Service Use.  We will use the Treatment Services Review to measure health services 
use. It has adequate reliability and validity (French, 2000; Kaminer et al., 1998; McLellan et al., 
1992). We will focus on services for the following problem areas: prescription opioid and 
sedative use, alcohol use, and psychiatric treatment.  The timeframe will be modified to measure 
past 4 months service utilization. 
 
Readiness to Change.  We will also have additional questions related to the importance and 
confidence to change as separate components of readiness to change. We will measure with the 
use of visual analog rulers; these rulers have been shown to correlate with longer surveys, and to 
predict outcomes in alcohol intervention studies (Daeppen et al., 2007; Hesse, 2006; LaBrie et 
al., 2005).  
 
Social Support. Social support will be assessed using the Deployment Risk and Resilience 
Inventory (DRRI) (King et al., 2006). The DRRI survey instrument is used to assess the key 
deployment-related factors implicated in the health and well-being of military veterans.  With the 
nature of military deployment changing, with a larger proportion of women, National Guard and 
Reserves being deployed for more contemporary conflicts, the DRRI was developed to provide a 
more comprehensive assessment of the current combat-related experiences.  
 
Alcohol-related consequences. The Young Adult Alcohol Consequences Questionnaire (Barry et 
al., 2012; Kahler et al., 2005; Tripp et al., 2015) will be used to measure consequences of alcohol 

use. This measure has been used in the National Guard population. 
 
Barrett Impulsiveness scale. Measures impulsive behaviors including behaviors related to motor 
control, non-planning, attention, internal stimulation, & external motivation (Patten et al., 1995). 
 
The Conflict Tactics Scales (CTS). The Conflict Tactic Scales (Straus, 1990) is the most widely 
used measure of domestic violence. We will use a collapsed version of the CTS to measure 
partner and non-partner violence.  
 
Dimensions of Anger Reactions. The DAR measures anger disposition directed towards others 
primarily measures Trait Anger. The DAR is a psychometrically strong measure, potentially 
useful for the evaluation of anger in PTSD (Forbes et al., 2004; Novaco & Chemtob, 2002). 
 
Post-app assessment. The post-intervention assessment will include questions regarding 
importance and usefulness of the app will occur following the 12 week SP-BI. 
 
Statistical Analysis Plan (SAP) 
To minimize the likelihood of chance associations (i.e., protect against Type I errors) which can 
occur when multiple, unplanned analyses are conducted with large data sets, analyses for testing 
the main study hypotheses will be planned a priori, and will be limited to the examination of 
specific outcomes. In addition, analyses that are central to the purpose of the study will be clearly 
identified as confirmatory hypotheses, and will be clearly identified as separate from exploratory 
analyses.  This plan of analyses is intended to outline the primary data analytic approaches that 
will be used to test the hypotheses for the specific aims. We will utilize an “intent-to-treat” 
approach in all analyses to be conservative in our estimate of intervention effects.   
 
It is our standard practice to begin with descriptive data analyses to determine distributions of 
key variables, calculate transformations or collapse categories, if necessary, and review data for 
outliers and anomalies.  Tests for linearity, independence, missingness, and distributional 
assumptions (e.g., normality) will also be performed.  Normalizing transformations of the 
dependent variables will be utilized when appropriate. We will validate the randomization 
scheme by comparing the initial groups on key variables that could be associated with the 
outcomes, such as age, race, initial alcohol use severity, comorbidity, self-efficacy and stage of 
change.  Stratified randomization should equalize the intervention groups on the key variables of 
gender and diagnosis of alcohol use disorder. Where we identify significant differences between 
groups, we will either adjust for these variables in analysis.   
 
In general, for longitudinal analysis we will use repeated measures regression mixed effects 
models for continuous and non-normally distributed variables. We will use procedures SAS 
PROC MIXED for continuous variables and PROC GLIMMIX for dichotomous and count data 
(either Poisson or negative binomial), both of which allow for subject-specific inference (e.g., 
allows for the estimation of subject-specific effects of interventions). The selection of the 
covariance matrix in the PROC MIXED procedure will be determined by the distribution of the 
data (e.g., normally) and covariance structure. The random parameter specified will be the 
subject effect and we will test for random slopes and intercepts. One of the advantages of these 
analytic approaches is that all available data are used in the analysis, rather than case-wise 

deletion if a follow-up interview is missing (see below for more detail). All analyses of the 
intervention and EUC condition will adjust for the two randomization stratification variables, 
gender and diagnosis of alcohol use disorder.   
 
 
Missing data. To minimize missing data, we will make every effort to gather follow-up 
information for all participants. Specific strategies to retain participants that have proven 
successful in our prior research are described above. The use of mixed effects regression to 
model individual trajectories will allow the use of data from all participants (including those with 
incomplete follow-up data) and provides unbiased parameter estimates that account for missing 
data under the missing-at-random assumption.148 If our examination of the pattern of 
missingness suggests that the missing-at-random assumption is untenable, we will handle 
missing data with a pattern mixture model.149 Where we have missing data on individual 
variables that are necessary for analysis, we will impute using SAS PROC MI to perform 
multiple imputation of missing data and PROC MIANALYZE to combine the results of PROC 
MI. We have found that sometimes 5 imputations are not enough to achieve optimum results and 
we increase number of imputations until we see each variable having 100 degrees of freedom or 
more.   
 
Power Analyses.  We propose to enroll a relatively large N at baseline (750, or 375/baseline 
group) in order to have sufficient power to:  (1) detect potentially smaller differences in 
outcomes of SP-BI compared to EUC as SP-BI has potential for successful implementation even 
if effect sizes are smaller because of the relatively low cost to maintain this technology-based 
intervention, and (2) have sufficient power for tests of moderators of the interventions. 
Longitudinal mixed effects models for binomial, count, and continuous dependent variables will 
be used to test the aims. We estimate power for an anticipated reduced sample size at 12 months 
assuming a conservative 80% follow-up (achieved in our previous studies with this population), 
even though our proposed mixed models use all available follow-up data.