Preventing Prescription Stimulant Diversion and Medication Misuse Via a Web-Based Simulation Intervention
Phase: NA
Conditions: Prescription Drug Abuse (Not Dependent), Intentional Misuse
Sponsor: Trinity College

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Study Protocol and Statistical Analysis Plan 
 
Preventing Prescription Stimulant Diversion and Misuse Via a Web-Based Simulation 
Intervention 
Investigators: Laura Holt, Ty Schepis, and Alison Looby  
NCT: 04885166 
Grant number: 1R34DA048345-01A1 
Document Date: 2/19/2025  
 

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Study Protocol and Statistical Analysis Plan 
1. Statement of protocol design: In this clinical trial, we compared the frequency of 
prescription stimulant diversion and misuse in college-attending emerging adults 
randomized to either (1) a web-based simulation intervention focused on stimulant diversion 
(i.e., giving, selling, or trading one’s prescription medication) and stimulant misuse (i.e., 
using the medication differently from how it was prescribed) prevention, or (2) a web-based 
placebo presentation focused on psychological conditions commonly faced by college 
students. We randomized participants using the research randomizer website; participants 
were blind to their study group assignment. We recruited a total of 249 students. The 
principal and co-investigators, along with research assistants screened interested students 
to determine if they meet the eligibility criteria (i.e., a current prescription for a stimulant 
drug). Eligible participants were consented remotely and attended a one-hour remote 
session in which they completed a baseline questionnaire online (30 minutes) and then 
viewed the active simulation or the placebo presentation (30 minutes). One and two months 
after the baseline session, participants viewed two, 5-10 minute web-based info sessions 
respectively, that reinforced the content of either the active intervention or placebo. We then 
distributed web-based follow-up surveys 3 and 6 months after the baseline session. 
  
2. Characteristics of study data collection site(s): Data will be collected at three 
college/university sites: Trinity College (Hartford, CT); Texas State University (San Marcos, 
TX); University of Wyoming (Laramie, WY). 
 
3. Inclusion/exclusion criteria: Inclusion criteria: Undergraduate or graduate students, 
between the ages of 17 and 25, who are prescribed a stimulant medication for ADHD or a 
related condition (or have had a prescription in the last three months). Students must plan to 
remain enrolled in one of the three data collecting colleges/universities before the 
conclusion of the study (i.e., 6 months after the projected date for the baseline session). 
Exclusion criteria: None.  
  
4. Randomization/stratification plan: We used the research randomizer website 
(randomizer.org) to randomize participants to the active treatment or placebo condition (1:1). 
We stratified by history of prescription stimulant diversion (i.e., any instances of giving away, 
selling, or trading one’s stimulant medication during one’s lifetime). 
 
5. Definition of participants and plans to document participant flow: Consistent with the 
Consolidated Standards of Reporting Trials (CONSORT) guidelines for reporting on 
randomized controlled trials, we tracked and report: 
○ The number of individuals screened/assessed for eligibility.  
○ The number of participants enrolled and randomized to each condition, and the 
number who received the placebo or active intervention. “Participant” was defined as 
someone who consented to participate. Reasons were provided in cases where 
participants missed any of the randomized intervention/placebo sessions. 
○ The number of participants who participated in the 3- and 6-month follow-up 
assessments. Reasons for lack of participation in follow-up and/or discontinuation of 
intervention/placebo were provided.  
○ The number of participants included in the analysis and reasons any participants 
were excluded, if necessary. 
 
6. Intervention definition 

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● Active intervention: The 25-30 minute web-based simulation intervention, 
administered following the baseline survey, introduced the topics of non-medical 
prescription stimulant use, stimulant diversion, medical misuse and prescriber 
communication, and how they are interrelated. Module 1 discussed and depicted 
national prevalence rates of diversion and non-medical use of prescription 
stimulants (NMUPS) and risks associated with these behaviors. Module 2 taught 
effective strategies for resisting stimulant medication requests and allowed 
students to practice using these skills in interactive conversations with a virtual 
human. Module 3 taught behavioral strategies for communicating with one’s 
prescriber, improving adherence, and reducing stimulant medication misuse.  
○ Participants were invited via e-mail to view booster session #1 one month 
following the baseline session. The session, in the form of a slide deck, 
reviewed strategies that students could use to refuse requests for their 
stimulant medication from non-prescribed and prescribed students and 
strategies to communicate with their prescriber about their symptoms, 
dose, and side effects. Booster #2, administered two months later, 
reviewed the psychoeducational components of Modules 1 and 3 (e.g., 
lack of efficacy of stimulants for non-prescribed students; poorer 
academic/psychosocial outcomes associated with lack of adherence to 
medication). Each booster was administered online, lasted 5-10 minutes 
total, and contained 5 comprehension questions (multiple choice, 
true/false). Correct responses to each of the questions were viewable to 
participants.  
● Placebo intervention: In the 25-30-minute web-based placebo tutorial, students 
learned about the prevalence of psychological disorders in college students, their 
etiologies, psychiatric medications, and videos of students’ personal experiences 
navigating college with a diagnosis of an anxiety and learning disorder. Booster 
#1, one month following the baseline session, reviewed prevalence data and 
symptomatology for common psychological disorders. Booster #2, two months 
following the baseline, reviewed common forms of psychological and 
pharmacological treatment. Each booster was administered online, lasted about 
5-10 minutes total, and contained 5 comprehension questions (multiple choice, 
true/false). Correct responses to each of the questions were viewable to 
participants. 
 
7. Regulatory Issues 
○ Reporting mechanisms of the AEs/SAEs to the IRB and NIDA:  Research 
Assistants (RAs) report on AE/SAEs whenever they are detected during regular 
study contacts. Potential SAEs include: a) mental status deterioration to the extent 
that overnight hospitalization was needed (including clinically significant suicidal or 
homicidal ideation), b) physical health deterioration to a degree that acute, overnight 
medical services were needed, and c) clinically significant increases in substance 
use that necessitated inpatient hospitalization.  
○ All research staff completed the required institutional training on research with 
Human Subjects and the IRB maintains copies of their certification. Study staff were 
trained in the monitoring and reporting of adverse events and understood that the 
responsibility is to document and report adverse events reported by study 
participants, independent of determinations made at the time or later of the 
relationship between the event and participation in the study. An Adverse Event 
Monitoring Form was completed for any suspected adverse events. The form 

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includes information about the details of the event, follow-up procedures as 
necessary (e.g., steps taken by RAs and PI), potential relation to study participation, 
and signature lines for all appropriate study personnel.  
○ RAs report SAEs immediately to the site PI after discovery. Deaths and possibly 
study-related SAEs are reported to the DSMB and the NIDA Program Officer within 
72 hours of discovery and to the local IRB per policies. All SAEs are reported to the 
Data Safety Monitoring Board (DSMB) in quarterly reports.  
○ At monthly research team meetings, all adverse events were reviewed (cumulative 
and past month). Aggregate reports of AEs/SAEs were sent to the IRB annually as 
part of study continuations and quarterly to DSMB members as part of DSM reports. 
○ Reporting mechanisms of IRB actions to NIDA: The PI was responsible for 
informing NIDA of any actions taken by the Institutional Review Board as a result of 
its reviews of the project. 
○ Report of changes or amendments to the protocol: The PI reported major 
changes in the protocol or study, including protocol amendments, regulatory 
decisions such as suspension or termination of subject recruitment, changes in the 
IRB approval status, and other problems or issues that could have a significant 
impact on participants.  
 
8. Outcome measures: 
● Primary  
○ Frequency of diversion will be assessed at baseline, 3- and 6-months. 
At baseline, participants will note how many times they have engaged in 
diversion (i.e., giving away, selling, or trading one’s prescribed stimulant 
medication) during the previous year and in the last 90 days. 
○ Intention to divert at all time points will be assessed with the following 
questions: “How likely is it that you will give away your stimulant 
medication in the next three months?” and “How likely is it that you will 
sell or trade your stimulant medication in the next three months?”  
○ We will assess medical misuse of prescription stimulants by inquiring 
about ways in which students might be using their stimulant medication in 
different ways from how it was prescribed. 
○ User satisfaction will be assessed immediately following the 
intervention. Specifically, we will assess the usefulness, information 
quality, and interface quality of the simulation. 
○ Usability of the simulation will be assessed immediately following the 
intervention. Participants will indicate perceived usefulness, user control, 
and impact of the simulation. 
○ Booster engagement. We will determine engagement in one or both 
online booster sessions by summing the number of correct answers to the 
five comprehension questions embedded in each of the two online 
boosters. 
● Secondary 
○ Self-efficacy to resist diversion will be assessed with two questions: 
“Please rate your confidence to (1) resist giving away your stimulant 
medication, (2) resist selling your stimulant medication.”   
○ Resistance strategy use. Participants who were approached for, but did 
not divert their stimulant medication, will be asked to indicate (open-
ended response) how they turned down the request. 

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○ Perceived behavioral norms. Participants will indicate, on a scale from 
0-100, what percent of students, on average, engage in (1) diversion and 
(2) non-medical prescription stimulant use. 
○ Risk perception. Participants will report on perceived legal risks 
associated with prescription drug diversion and perceived harm from 
NMUPS and medical misuse. 
○ Participants will report on any communication with their prescriber 
regarding their adherence to their prescription or any concerns they have 
regarding the dose, frequency of administration, and/or side effects. 
○ We will assess other substance use (i.e., binge drinking, and/or 
marijuana, cocaine, heroin, methamphetamine, or hallucinogen use, or 
other prescription drug misuse) in the previous 90 days. 
 
9. Sample size. To arrive at our anticipated sample size of 300 participants, we used the effect 
size (d=.20) from a meta-analysis of 43 interventions that evaluated longer-term effects of 
brief interactive interventions with college students on alcohol consumption. Power was 
estimated using generalized linear model in SAS where an exemplary data file was created 
assuming a stable (same) effect size of 0.2 across the 3- and 6-month time points with an 
autocorrelation of 0.6 and 150 students randomized to each condition (300 total). With a 
two-sided test and an alpha of 0.05, power is 0.80 to detect a significant treatment effect 
across the two time points. Assuming an attrition rate of 5% between time points 
(culminating in 270 students at month 6) power is 0.78 to detect a significant treatment 
effect across the six month trial. Only participants randomized to one of the two conditions 
will be included in the data analysis.   
 
10. Key adherence variables will include whether participants respond to the questions 
associated with the 1-month follow-up booster, the 2-month follow-up booster, the 3-month 
follow-up survey, and the 6-month follow-up survey. 
 
11. Key safety variables. Safety data will include treatment retention, study withdrawals, and 
AEs/SAEs by treatment condition.  
 
12. Data analysis plan: 
 
○ We modeled diversion risk using the following indicators at baseline, 3- and 6- 
months: number of occasions when a participant sold his/her stimulant medication; 
gave his/her medication away; traded his/her medication in the last 90 days; and 
intention to divert in the next three months. We initially planned to model stimulant 
medication misuse using the following indicators at baseline, 3- and 6-months: the 
total number of occasions when a participant used an alternative route of 
administration, took more than his/her recommended dose, took less than his/her 
recommended dose, took someone else’s stimulant medication, took a stimulant 
medication with alcohol or other drugs, or intentionally got high on his/her prescribed 
stimulant medication. We ultimately elected to operationalize medication misuse 
without the inclusion of taking less than one’s recommended dose, given that prior 
research has typically not included this behavior in measures of medication misuse. 
Using Mplus statistical software, a SEM with the factors diversion risk and 
medication misuse measured at three time points (baseline, 3-month, 6-month 
follow-up) was be created. The model included autoregressive paths between 
sequential time points and treatment condition was an exogenous variable predictive 

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of the factors at each time point. This approach permitted tests for change across 
time and for the effect of treatment condition on each factor at each time point.   
○ To test if the effects of the intervention on diversion risk or stimulant medication 
misuse at the six-month follow-up are moderated by demographic (i.e., sex, 
race/ethnicity, age, class year) or psychosocial factors (i.e., other substance use, 
history of conduct problems), a path model with intervention and the moderating 
factors (with product variables) as exogenous variables and diversion risk (and 
medication misuse, respectively) as endogenous variables will be run. 
○ To determine whether the intervention produced change in our secondary outcomes, 
we examined whether there were differences between the treatment and placebo 
conditions in (1) self-efficacy to avoid diversion, (2) resistance strategy use, (3) 
knowledge about diversion and NMUPS norms and risks, and (4) prescriber 
communication. Knowledge about NMUPS norms and risks was measured at 
baseline and 3-months; resistance strategy use will be measured at 3- and 6-
months. Prescriber communication and self-efficacy to avoid diversion were 
measured at baseline and at the 3- and 6- month follow-ups. Similar to the primary 
outcomes, SEM was used to model these outcomes and test if treatment condition is 
causal for any of these outcomes across time points they are measured.   
○ If we show an effect of the intervention on one or both of our primary outcomes, we 
will assess the extent to which change in resistance strategy self-efficacy, knowledge 
about norms and risks, resistance strategy use, and/or prescriber communication 
mediated associations between the intervention and the primary outcomes (i.e., 
diversion risk, medication misuse). This was accomplished using a multilevel 
mediation model (where repeated measures are nested within students) in Mplus.   
○ To assess usability of, and satisfaction with the simulation, we calculated means 
for the user satisfaction and usability measures and compared them to the control 
group.  
 
13. Interim Analyses and Rules for Stopping: One year after the first participant was enrolled, 
and each year after, the investigators conducted interim analyses on the two primary 
outcomes, prescription stimulant diversion and misuse of one’s prescribed stimulant 
medication, to ensure that differences between the active intervention and placebo groups 
were not unduly large. If there were a large effect (Cohen’s d = .8) favoring the placebo 
group, the investigators would be concerned that the active intervention was iatrogenic and 
therefore would consider discontinuing the trial. On the other hand, if there were a large 
difference (Cohen’s d = .8) favoring the active intervention group, the trial may need to be 
discontinued so that the placebo group could receive a more effective intervention.