Integrating basic research with prevention/intervention to reduce risky substance use among college students

College students mandated to substance use courses: Age-of-onset as a predictor of contemporary polysubstance use

Objective: College campuses report alcohol and other drug policy violations as the most frequent reason students receive disciplinary referrals and, thus, are mandated to programming. This study sought to determine predictors of mandated students' alcohol use frequency, and the likelihood of early-onset alcohol using college students enrolled in mandated programming engaging in current polysubstance use. Methods and participants: Employing a purposive sampling method, n = 822 participants were recruited from a pool of students who violated their university's alcohol policy between October 2019 and July 2021. Results: Data analysis revealed early-onset alcohol use (p < .001), gender ID (p < .01), Greek Affiliation (p < .001), ethnicity (p < .05), and perceived norms (p < .001) significantly predicted alcohol frequency. Analysis also revealed engaging in early-onset alcohol use significantly predicted current participation in polysubstance use (p < 0.01), outside of controls. Conclusions: University programs should consider exploring polysubstance use targeted interventions to mitigate these harmful behaviors and associated negative consequences.

Genetically influenced externalizing and internalizing risk pathways as novel prevention targets

Objective: Risky substance use among college students is widespread, and associated with numerous adverse consequences. Current interventions focus primarily on students' current substance use; we hypothesize that shifting focus from current use to underlying risk factors is a complementary approach that may improve effectiveness of prevention/intervention programming. This approach aligns with the personalized medicine movement, which aims to harness knowledge about underlying etiological factors to provide individuals with specific information about their unique risk profiles and personalized recommendations, to motivate and enable individuals to better self-regulate their health. Method: Our group is building and evaluating an online Personalized Feedback Program (PFP) for college students that provides feedback about the individual's underlying genetically influenced externalizing and internalizing risk factors for substance use, along with personalized recommendations/resources. The project capitalizes on work from a university-wide research project (Spit for Science; S4S), in which > 12,000 students (˜70% of 5 years of incoming freshmen) are being followed longitudinally to assess substance use and related factors across the college years. In this article, we describe our foundational work to develop the PFP. Results: From the S4S data, we have identified risk factors across four domains (Sensation Seeking, Impulsivity, Extraversion, and Neuroticism) that are correlated with college students' substance use. We developed an online self-guided PFP, in collaboration with professionals from student affairs, and using feedback from students, with the ultimate goal of conducting a randomized clinical trial. Conclusion: The provision of personalized risk information represents a novel approach to complement and extend existing college substance use programming. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

E-cigarette use among young adults: A latent class analysis examining co-use and correlates of nicotine vaping

INTRODUCTION

Although a significant proportion of young adults report e-cigarette use (nicotine vaping), little is known about co-use with other substances, including correlates that predict co-use. The current study aimed to identify co-occurring substance use patterns and evaluate multiple correlates in a college student sample.

METHODS

435 participants (21.4 ± 2.9 years; 57% women; 41% Hispanic/Latina/o, 29% Asian-American/Pacific Islander, 17% Caucasian/White, 6% Multiracial, and 5% African-American/Black) from a large, urban university were recruited in-person and completed an online survey in the fall of 2018 and the spring of 2019.

RESULTS

Using latent class analysis (LCA), four substance use patterns were identified: Binge Drinkers (7%); e-cigarette Users (8%); Cannabis Users (14%); and Low Substance Users (71%). The e-cigarette Users class was characterized by moderate or greater use (>5 days of nicotine vaping in past 30-days) as well as past 30-day binge drinking and cannabis use. Higher levels of deviant peer affiliation (aOR = 1.28[1.11-1.47], p < .01), impulsivity-lack of premeditation (aOR = 1.36[1.05-1.78], p < .05), and lower levels of social anxiety (aOR = 0.94[0.88-0.99], p < .05), predicted membership in the e-cigarette Users class.

CONCLUSIONS

The most pervasive co-occurring substance use was observed among the e-cigarette Users class. Young adults reporting moderate or greater levels of nicotine vaping tended to engage in binge drinking and cannabis use, which may ultimately increase risk of deleterious health outcomes. Deviant peer affiliation and impulsivity-lack of premeditation (but not internalizing symptoms) predicted membership in the e-cigarette Users class; consequently, public health efforts may benefit from increased selectivity in targeting young adults for e-cigarette prevention and intervention services.

Unpacking Genetic Risk Pathways for College Student Alcohol Consumption: The Mediating Role of Impulsivity

BACKGROUND

The period of college represents a particularly risky developmental stage with regard to alcohol use, as college students engage in more risky drinking behaviors than their noncollege peers, and such problematic alcohol use is associated with far-reaching negative consequences. Existing findings from genome-wide association studies (GWAS) indicate that alcohol consumption has a complex polygenic etiology. Currently, there is a lack of studies examining genetic risk for alcohol consumption using polygenic risk scores (PRS) in college samples. In this study, we examined whether alcohol-specific and risky behavior-related PRS were longitudinally associated with alcohol consumption among college students and whether this effect might be partially mediated by impulsivity domains.

METHODS

The sample included n = 2,385 European ancestry (EA) and n = 1,153 African ancestry (AA) college students assessed over the course of 4 years. To indicate genetic risk, 2 PRS were created based on recent large-scale GWAS: alcohol consumption (Liu et al., 2019) -drinks per week (DPW)-PRS and risky behaviors (Linnér et al., 2019) -RISK-PRS. The main outcome was alcohol consumption, measured across 4 waves of follow-up data. The UPPS-P impulsivity subscales were examined as mediators of the genetic effect on alcohol consumption.

RESULTS

The results from structural equation modeling showed that among EA students, both DPW-PRS and RISK-PRS had significant positive effects on alcohol consumption above and beyond UPPS dimensions and control variables. RISK-PRS explained larger portion of variance in alcohol consumption than DPW-PRS. RISK-PRS showed a significant indirect effect on alcohol consumption through sensation seeking and lack of perseverance; no significant indirect effect of DPW-PRS was found. No significant association of either PRS or alcohol consumption was found for AA participants.

CONCLUSIONS

The current results found that PRS related to more broadly defined risky behaviors predicted alcohol consumption across college years and that this association was partially mediated via dimensions of impulsivity.

Post-GWAS in Psychiatric Genetics: A Developmental Perspective on the "Other" Next Steps

As psychiatric genetics enters an era where gene identification is finally yielding robust, replicable genetic associations and polygenic risk scores, it is important to consider next steps and delineate how that knowledge will be applied to ultimately ameliorate suffering associated with substance use and psychiatric disorders. Much of the post-genome-wide association study discussion has focused on the potential of genetic information to elucidate the underlying biology and use this information for the development of more effective pharmaceutical treatments. In this review we focus on additional areas of research that should follow gene identification. By taking genetic findings into longitudinal, developmental studies, we can map the pathways by which genetic risk manifests across development, elucidating the early behavioral manifestations of risk, and studying how various environments and interventions moderate that risk across developmental stages. The delineation of risk across development will advance our understanding of mechanism, sex differences and risk and resilience processes in different racial/ethnic groups. Here, we review how the extant twin study literature can be used to guide these efforts. Together, these new lines of research will enable us to develop more informed, tailored prevention and intervention efforts.

A Genomically Informed Education System? Challenges for Behavioral Genetics

The exponential growth of genetic knowledge and precision medicine research raises hopes for improved prevention, diagnosis, and treatment options for children with behavioral and psychiatric conditions. Although well-intended, this prospect also raise the possibility-and concern-that behavioral, including psychiatric genetic data would be increasingly used-or misused-outside the clinical context, such as educational settings. Indeed, there are ongoing calls to endorse a "personalized education" model that would tailor educational interventions to children's behavioral and psychiatric genetic makeup. This article explores the justifications for, and prospects and pitfalls of such endeavors. It considers the scientific challenges and highlights the ethical, legal, and social issues that will likely arise should behavioral genetic data become available (or be perceived as such) and are routinely incorporated in student education records. These include: when to disclose students' behavioral and psychiatric genetic profile; whose genomic privacy is protected and by whom; and how students' genetic data may affect education-related decisions. I argue that the introduction of behavioral genetics in schools may overshadow the need to address underlying structural and environmental factors that increase the risk for psychiatric conditions of all students, and that the unregulated use of student behavioral genetic profiles may lead to unintended consequences that are detrimental for individuals, families and communities. Relevant stakeholders-from parents and students to health professionals, educators, and policy-makers-ought to consider these issues before we forge ahead with a genomically informed education system.

Alcohol-Impaired Driving: The Influence of Adverse Rearing Environments, Alcohol, Cannabis Use, and the Moderating Role of Anxiety

BACKGROUND

The rate of alcohol-impaired driving (AID) increases during the college years and students who have reported adverse rearing environments appear to be at increased risk for the development of alcohol and drug use behaviors. Alcohol and cannabis are the most commonly used drugs by college students, and these substances are particularly predictive of substance-impaired driving.

OBJECTIVES

The present study aimed to investigate whether adverse rearing environment experiences and level of alcohol and cannabis use are related to the frequency of alcohol-impaired driving and whether anxiety might buffer or accelerate this effect.

METHODS

Data regarding adversity, drug use, anxiety, and AID were obtained from 1,265 students annually, from first to final year of college, over four waves (Mean Age at wave 1 = 18.5 years).

RESULTS

Structural equation modeling supported associations among childhood adversity, alcohol, cannabis, and anxiety symptoms. A significant mediation effect was found such that adversity was predictive of AID via alcohol use and cannabis use. Among men, anxiety symptoms accelerated the path from increased cannabis use and decelerated the path from increased alcohol use to AID frequency. Conclusions/Importance: Childhood adversity is a developmental risk precursor to drug use and AID, whereas anxiety might serve a risk or protective factor to AID, contingent on the drug used.

Risk Factors for School Dropout in a Sample of Juvenile Offenders

Backgrounds: The high rates of school dropout worldwide and their relevance highlight the need for a close study of its causes and consequences. Literature has suggested that school dropout might be explained by multiple causes at different levels (individual, family, school, and neighborhood). The aim of the current study is to examine the relation between individual (defiant attitude, irresponsibility, alcohol abuse, and illegal drugs use), family (educational figure absent and parental monitoring), school factors (truancy and school conflict) and school dropout. Method: Judicial files of all juvenile offenders (218 males and 46 females) with a judicial penal measure in Asturias (Spain) in the year 2012 were examined. Multivariate logistic regression analyses were performed to estimate the relationships between school dropout and individual, family and school variables. Results: As for the individual characteristics, results showed that school dropouts were more irresponsible than non-dropouts. Also they had higher rates of illegal drug use and alcohol abuse. Moreover, lack of parental monitoring emerged as a key predictive factor of school dropout, beyond the type of family structure in terms of the presence of both or only one educational figure. Finally, school factors did not show a significant relationship to school dropout. Conclusions: These findings indicate that school dropout is a multidimensional process. School and family policies that emphasize the role of parental monitoring and prevent alcohol and substance abuse are recommended.

The Genetics of Addiction: Where Do We Go From Here?

We have made tremendous progress in understanding the genetic epidemiology of substance use problems. We understand a good deal about the genetic architecture of substance use disorders with respect to other psychiatric conditions, and how genetic influences change across development and as a function of the environment. We are further behind in identifying specific genes involved in substance use disorders. However, rather than blindly charging ahead with expensive gene identification efforts, our field would benefit from more thoughtful discussion about what strategies to pursue-both genetic and environmental-to have the greatest impact on reducing substance use problems.