Publications by authors named "Morgan N Driver"

College students engage in high rates of risky substance use. Standard college prevention strategies focus on providing feedback about current substance use behaviors and harm reduction strategies but do not address the underlying genetically-influenced risk factors impacting these behaviors. We created an online Personalized Feedback Program (PFP) for college students that targets genetically-influenced externalizing and internalizing risk pathways and provides personalized recommendations and campus resources.

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Introduction: The utility of genetic risk information relies on the assumption that individuals will use the information to change behavior to reduce risk of developing health problems. Educational interventions designed to target elements of the Health Belief Model have shown to be effective in promoting behaviors for positive outcomes.

Methods: A randomized controlled trial (RCT) was conducted in 325 college students to assess whether a brief, online educational intervention altered elements of the Health Belief Model that are known to be associated with motivations and intentions to change behavior.

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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.

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For the return of polygenic risk scores to become an acceptable clinical practice in psychiatry, receipt of polygenic risk scores must be associated with minimal harm and changes in behavior that decrease one's risk for developing a psychiatric outcome. Data from a randomized controlled trial was used to assess the impact of different levels of hypothetical polygenic risk scores for alcohol use disorder on psychological distress, risk perception, and intentions to change drinking behaviors. The analytic sample consisted of 325 participants recruited from an urban, public university.

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Introduction: As gene identification efforts have advanced in psychiatry, so have aspirations to use genome-wide polygenic information for prevention and intervention. Although polygenic risk scores (PRS) for substance use and psychiatric outcomes are not yet available in clinical settings, individuals can access their PRS through online direct-to-consumer resources. One of these widely used websites reports that alcohol use disorder is the third most requested PRS out of >1,000 conditions.

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Substance use disorders (SUDs) incur serious social and personal costs. The risk for SUDs is complex, with risk factors ranging from social conditions to individual genetic variation. We examined whether models that include a clinical/environmental risk index (CERI) and polygenic scores (PGS) are able to identify individuals at increased risk of SUD in young adulthood across four longitudinal cohorts for a combined sample of N = 15,134.

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Genome-wide association studies aim to identify genetic variants that are associated with a disease phenotype in order to enhance precision medicine efforts. Despite the excitement surrounding the promise of precision medicine and interest among the public in accessing personalized genetic information, there has been little effort dedicated to understanding how complex genetic risk information could be incorporated into clinical practice to inform prevention, screening, and treatment. In this article, we briefly summarize the literature on the impact of receiving genetic risk information on health-related behavior, discuss the limitations of these studies, and outline the challenges that will need to be overcome, along with suggested next steps for future studies, to understand the true promise of precision medicine.

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Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.

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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 to 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.

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An exponential growing number of individuals are accessing genetic risk information via direct to consumer companies. Alcohol dependence is the third most accessed genetic risk score on a publicly available direct to consumer website. Better understanding of the degree to which individuals are interested in receiving personalized genetic feedback, the factors that relate to interest, and genetic knowledge will be critical to lay the foundation for precision medicine initiatives, especially for substance use and psychiatric outcomes, where less is known.

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Genome-wide association studies are rapidly advancing our understanding of the genetic architecture of complex disorders, including many psychiatric conditions such as major depression, schizophrenia, and substance use disorders. One common goal of genome-wide association studies is to use findings for enhanced clinical prediction in the future, which can aid in identifying at-risk individuals to enable more effective prevention screening and treatment strategies. In order to achieve this goal, we first need to gain a better understanding of the issues surrounding the return of complex genetic results.

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