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. Author manuscript; available in PMC: 2024 Aug 1.
Published in final edited form as: Drug Alcohol Depend. 2023 Jun 7;249:110818. doi: 10.1016/j.drugalcdep.2023.110818

Bridging the Gap between Genetic Epidemiological Research and Prevention: A Randomized Control Trial of a Novel Personalized Feedback Program for Alcohol and Cannabis Use

Maia Choi 1, Morgan N Driver 2, Emily Balcke 3, Trisha Saunders 4, Joshua M Langberg 5, Danielle M Dick 3
PMCID: PMC10449035  NIHMSID: NIHMS1910403  PMID: 37327509

Abstract

Background:

Risky substance use among college students is widespread and associated with numerous negative consequences. We created an online Personalized Feedback Program (PFP) for college students that targets genetically influenced risk pathways for substance use and provides feedback on four risk domains (Sensation Seeking, Impulsivity, Extraversion, and Neuroticism) along with individualized recommendations and campus resources. Methods: A pilot randomized controlled trial was conducted to evaluate the effects of the PFP on alcohol and cannabis use. First-year college students were randomized to one of four groups: (1) control, (2) PFP, (3) computer-delivered brief motivational intervention (BMI), and (4) combined group that included both the PFP and BMI (PFP+BMI). Students completed a baseline survey (n=251) that assessed alcohol and cannabis use and program satisfaction. Two follow-up surveys were administered at 30-days and 3-months post-intervention to evaluate longitudinal effects on substance use.

Results:

Participants reported high satisfaction with the PFP. There were no significant effects of intervention group on alcohol use at the follow-up timepoints, though trends were in the expected direction with participants in the PFP group showing decreased odds of alcohol use. There were significant reductions in cannabis use in the PFP group as compared to other groups.

Conclusions:

The PFP was met with high satisfaction and had a positive impact on reducing cannabis use. With cannabis use at a historic high among college-aged adults, further research evaluating the effects of the PFP is warranted.

Keywords: Prevention, personalized feedback, college, Alcohol, cannabis

Introduction

Problematic alcohol and cannabis use in college is widespread (Arria et al., 2017) and associated with serious negative consequences (Jackson et al., 2020). A 2021 study found 76% of college students report past-year alcohol use and 40% of students report past-year cannabis use (Patrick et al., 2022). Because college is a significant period of transition, effective prevention programs are needed to prevent initiation and escalation of harmful substance use.

The current standard prevention programs for college substance use are brief motivational interventions (BMIs), which have been adapted to online formats (Cole et al., 2018; Palfai et al., 2014), and more recently to address cannabis use (Montemayor et al., 2022; Riggs et al., 2018). BMIs provide students with information about how their substance use compares to peers, consequences associated with excessive use, and strategies to reduce risk for problems associated with risky drinking (Magill et al., 2017). Feedback provided in BMIs focuses entirely on substance use and not on the underlying risk factors that may contribute to elevated risk of hazardous substance use.

This is likely because the literature on college prevention has developed largely independently from the genetic epidemiological literature on pathways of risk for substance use. A robust body of evidence indicates two major pathways of genetically-influenced risk that contribute to the development of substance use problems (Colder et al., 2013; King et al., 2004; Meque et al., 2019; Trucco & Hartmann, 2021). The externalizing pathway is characterized by behavioral undercontrol, self-regulation deficits, and high reward sensitivity (Zucker et al., 2011). Externalizing traits such as impulsivity, sensation seeking, and extraversion are associated with an increased likelihood of problematic substance use (Edwards et al., 2016). The internalizing pathway involves problems with emotion regulation, reflected in anxious and depressive characteristics that are associated with later harmful substance use (Colder et al., 2019; Edwards et al., 2014; Hussong et al., 2011). Incorporating information about underlying risk factors may complement existing substance use programming to help students recognize traits that may lead to problems. One such program is Preventure, a personalized intervention for school-age adolescents (13–14 years old) targeting externalizing and internalizing characteristics (Conrod et al., 2008). It has shown positive short- and long-term effects on alcohol and cannabis use (Conrod & Castellanos, 2009; Conrod et al., 2013; Mahu et al., 2015; Newton et al., 2016; Newton et al., 2018; O’Leary-Barrett et al., 2010). However, aspects of this program, including delivery in a group setting, make implementation in a college setting impractical.

Building upon this foundational work, we developed the Personalized Feedback Program (PFP), an online program for college students that provides feedback about students’ genetically influenced externalizing and internalizing traits (i.e., Sensation seeking, Impulsivity, Extraversion, and Neuroticism) and how these factors relate to substance use, mental health, and wellbeing, along with personalized recommendations and resources. Further interactive elements in the program allowed students to practice goal setting and focus on decision making in different scenarios. Details about the development and content of the PFP can be found in Dick et al. (2022). An initial open trial suggested students were highly satisfied with the program and reported intentions to use more university resources and reduce drinking after completing the program (Choi et al., 2023). The primary aim of this pilot study was to conduct a small, randomized control trial (RCT) to test efficacy of the PFP as related to short-term impacts on alcohol and cannabis use. We hypothesized that the PFP program would be associated with a lower likelihood of alcohol and cannabis at two follow-up timepoints compared to the control and BMI groups. We also tested a combined PFP+BMI group to examine whether receiving personalized information about underlying risk factors would enhance effects associated with BMIs focused on reducing harmful patterns of use.

Methods

Participants and Recruitment

Participants were recruited through the Spit for Science Registry, a university-wide research registry with the goal of understanding pathways of risk for substance use and related mental health outcomes across the college years (Dick et al., 2014). Incoming first-time college students who completed the initial Spit for Science survey in Fall 2021 were asked if they wanted to learn more about the current spin-off study. Participants who indicated interest were invited to participate via email on a rolling basis and recruitment ran for a total of 13 weeks between August 2021 and December 2021. To increase participation, the current study became available to students enrolled in Psych SONA, a database of current university research studies that are actively recruiting participants, at week 8. All participants provided consent, and the study was approved by the university’s Institutional Review Board.

Study Design

At timepoint 1 (T1), participants completed the baseline survey, which included items related to demographics, behavior, life experiences, substance use, and mental health via REDCap (Harris et al., 2009). After completion of the baseline survey, participants were randomly assigned to one of four groups, described further below: (1) control, (2) PFP, (3) brief motivational intervention (BMI), and (4) combined group that included both the PFP and BMI (PFP+BMI). Participants were emailed a REDCap link that directed them to their assigned group and post-intervention survey.

Intervention Groups

Control.

Participants were presented with a list of university resources available to them (e.g., Recreation and Well-Being, Student Counseling Center). Each resource linked out to its respective web page. The resources listed matched those provided throughout the PFP. Participants were emailed the resource list upon completion of the program.

PFP.

Participants completed the PFP (Dick et al., 2022). After completion, students were given the opportunity to download a copy of their personalized results and were emailed their results.

BMI.

Participants completed a computer-delivered Brief Alcohol Screening and Intervention for College Students (BASICS) (Dimeff, 1999) intervention based on BMI content/principles. Students answered items regarding their alcohol consumption and related problems and were given a personalized feedback report on their drinking behaviors and possible harms. Participants were able to download their BMI feedback directly to their device.

PFP+BMI.

In the combined group, participants first completed the PFP and then completed the BMI.

At the end of each intervention, students were directed back to REDCap to answer a brief set of survey questions related to their experiences with the program and their future intentions regarding alcohol and drug use.

Approximately 30 days and 3 months post-intervention (defined by their date of initial participation at T1), participants were invited via email to complete the online Timepoint 2 (T2) and Timepoint 3 (T3) follow-up assessments in REDCap. Participants were compensated with an Amazon gift card after completion of each survey.

Sample Characteristics

283 participants were randomized to one of four intervention groups. However, not all participants that were randomized completed their assigned intervention. 253 participants completed the intervention at T1, 222 participants completed the 30-day follow-up, and 214 completed the 3-month follow-up. Due to program errors and deviation from the study protocol, 7 participants were excluded from all analyses, and 4 participants were removed from T2 analyses. Figure 1 displays additional details about the sample sizes across the study groups and timepoints.

Figure 1:

Figure 1:

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Flowchart of Participants in the RCT

The mean age of the sample was 18.25 (SD=0.76). 82% of the sample self-reported their sex as female. 67% of the sample self-identified as cisgender woman. 46% self-identified as White, 17% self-identified as Black/African American, 19% self-identified as Asian, 10% of the sample identified as mixed race, and 7% identified as Hispanic/Latino.

Measures

Measures

Demographic information

Demographic variables assessed at T1 included age, biological sex at birth, gender identity, race/ethnicity, and current living situation.

Alcohol use

Alcohol use was measured using the frequency item from the Alcohol Use Disorder Identification Test (Bohn et al., 1995). Due to low variability in frequency of use, alcohol use was dichotomized to indicate whether an individual endorsed any alcohol use. Individuals who reported using “just once” to “4 or more times a week” were coded as 1. Individuals who responded “never” were coded as 0. Lifetime alcohol use was assessed at T1. At T2 and T3, alcohol use in the past-30 days was assessed.

Cannabis use

Cannabis use was measured used the frequency item from the Cannabis Use Disorder Identification Test (Adamson & Sellman, 2003). Due to low variability in frequency of use, cannabis use was dichotomized to indicate whether an individual endorsed any cannabis use. Individuals who reported using “just once” to “4 or more times a week” were coded as 1. Individuals who responded “never” were coded as 0. Lifetime cannabis use was assessed at T1. At T2 and T3, cannabis use in the past-30 days was assessed.

Satisfaction

Six items were included to assess participants’ opinions about their intervention at T1. An example of the statements includes “I would recommend this program to a friend.” Six additional items were included to assess the three active interventions (e.g., “My profile seemed accurate”). Response options ranged from “strongly disagree” to “strongly agree.”

Analysis Plan

Descriptive analyses were calculated for participant demographic characteristics and other variables of interest. The primary outcome of interest was differences in alcohol and cannabis use across the four intervention groups overtime. Multinomial logistic regression analyses were used to test if intervention group predicted alcohol and cannabis use at T2 and T3 while controlling for lifetime use at T1. For all regression analyses, the PFP was set as the reference group.

Results

Alcohol and Cannabis Use

At baseline, 49% of the total sample reported lifetime alcohol use and 35% reported lifetime cannabis use. There were no significant differences in alcohol use or cannabis use across the four groups (p > .05), indicating randomization was successful.

Table 1 shows the percent of individuals who reported alcohol and cannabis use at 30-days (T2) and 3-months (T3) post-intervention.

Table 1:

Results from Multinomial Logistic Regression Analyses of Alcohol Use and Cannabis Use by Group and Percentage of Individuals Reporting Substance Use Across Groups

Alcohol use
 Cannabis use
T2 T3 T2 T3
Predictors OR 95% CI p % OR 95% CI p % OR 95% CI p % OR 95% CI p %
Intercept/PFP* 0.05 0.02 –0.15 <0.001 29.09 0.1 0.04 – 0.23 <0.001 30.36 0.05 0.02 – 0.13 <0.001 14.55 0.03 0.01 – 0.09 <0.001 8.93
Control 1.27 0.48 – 3.40 0.629 33.33 1.63 0.65 – 4.14  0.298 36.54 3.07 1.02 – 9.22 0.045 31.48 3.92 1.15 – 13.38 0.029 23.08
BMI 1.72 0.62 – 4.73 0.294 33.96 2.18 0.87 – 5.51 0.097 40.74 1.55 0.50 – 4.86 0.447 20.37 3.45 1.02 – 11.69 0.046 22.64
Both 1.96 0.74 – 5.17 0.173 43.64 1.12 0.45 – 2.80 0.8 33.96 2.35 0.79 – 7.01 0.125 29.09 6.82 2.08 – 22.32 0.002 35.85
T1 use 21.71 9.42 – 50.01 <0.001 10.33 5.09 – 20.97 <0.001 13.76 6.38 – 29.68 <0.001 9.87 4.58 – 21.30 <0.001
Observations 214 Observations 213 Observations 218 Observations 214
R2 Nagelkerke 0.44 R2 Nagelkerke 0.32 R2 Nagelkerke 0.37 R2 Nagelkerke 0.33
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*

Within each block, % reflect the PFP group; multinomial regression results are for the intercept. The % column indicates the percent of individuals who reported alcohol or cannabis use at the respective timepoints.

Table 1 presents the results from the multinomial logistic regressions which tested the likelihood of alcohol use and cannabis use as compared to the PFP group. Odds of drinking in the other three groups at T2 and T3 were not significantly different than the PFP group, all p > .05, though trends were in the expected direction for the single group comparisons, with individuals in the control and BMI groups reporting higher odds of alcohol use relative to the PFP group. T1 alcohol use predicted subsequent alcohol use at T2 and T3 (p < .001). At T2, the control group was associated with an increased likelihood of cannabis use as compared to the PFP group, OR = 3.07, 95% CI [1.02, 9.22], p = .045. At T3, participants in the control, BMI, and BMI+PFP groups were significantly more likely to endorse cannabis use than participants in the PFP group, all p < .05. T1 cannabis use significantly predicted cannabis use at T2 and T3 (p < .001).

Satisfaction with the PFP

All satisfaction items indicated high acceptance of the PFP program. For example, among participants who completed the PFP, 93% strongly agreed or agreed that “It was helpful to learn about the ‘good’ and ‘not so good’ aspects of my personality” and 83% strongly agreed or agreed that “My personality profile seemed accurate.”

Discussion

This present randomized controlled trial is a small pilot study intended to collect initial data on the efficacy of a newly developed prevention program for college students as compared to standard educational interventions. Primary analyses focused on assessing whether individuals who completed the PFP were less likely to use alcohol and cannabis as compared to individuals who received resources only or a standard BMI-based program. There were no significant effects of intervention group on alcohol use at the follow-up timepoints, though trends were in the expected direction with participants in the PFP group showing decreased odds of alcohol use compared to the other three groups. The lack of significant findings with alcohol may be because overall alcohol use was low for our sample of college students, likely due to COVID-19. Further, this was a small pilot study that had insufficient power to detect small effects. Future studies should test the PFP in a larger sample of college students and for a longer period of time as students are more exposed to risky drinking opportunities throughout their college experience.

There were significant reductions in cannabis use in the PFP group as compared to other groups. At the 30-day follow-up, individuals in the control group were three times more likely to endorse cannabis use than individuals in the PFP. Further, at the 3-month follow-up individuals in the control and BMI groups were also at least 3 times more likely to endorse cannabis use than the PFP group. In contrast to what we expected, individuals in the BMI+PFP group were more likely to endorse to cannabis use than the PFP only group. This may reflect “information overload” leading the BMI+PFP group to be less effective. Our satisfaction data suggest this may be the case with slightly lower levels of satisfaction (e.g., “The length of the program was appropriate” and “I enjoyed the program”) in the BMI+PFP condition.

There was high satisfaction among individuals who received the PFP, demonstrating participants found the program enjoyable, informative, and easy to use. Taken together with preliminary indication that the PFP is associated with reductions in substance use, particularly cannabis, these are promising results and warrant additional research with the PFP program.

Highlights.

  • Not required for brief communication.

Acknowledgments

This project is supported by R34AA027347 (DMD, JML) from the National Institute on Alcohol Abuse and Alcoholism (NIAAA). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIAAA. This research was further made possible by Spit for Science. Spit for Science has been supported by Virginia Commonwealth University, P20 AA017828, R37AA011408, K02AA018755, P50 AA022537, and K01AA024152 from the National Institute on Alcohol Abuse and Alcoholism, and UL1RR031990 from the National Center for Research Resources and National Institutes of Health Roadmap for Medical Research. Spit for Science was also supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number U54DA036105 and the Center for Tobacco Products of the U.S. Food and Drug Administration. The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH or the FDA. Data from this study are available to qualified researchers via dbGaP (phs001754.v2.p1).

Footnotes

Declaration of Competing Interest

No conflict declared

CRediT authorship contribution statement

Maia Choi, Morgan Driver, Emily Balcke, Trisha Saunders, Joshua Langberg, Danielle Dick

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