Neuroeconomic Predictors of Adolescent Risky Decision-Making

dc.contributor.authorLauharatanahirun, Ninaen
dc.contributor.committeechairCasas, Brooksen
dc.contributor.committeememberChiu, Pearl H.en
dc.contributor.committeememberKim-Spoon, Jungmeenen
dc.contributor.committeememberBall, Sheryl B.en
dc.contributor.departmentPsychologyen
dc.date.accessioned2019-06-01T06:00:38Zen
dc.date.available2019-06-01T06:00:38Zen
dc.date.issued2017-12-07en
dc.description.abstractAdolescence is a critical developmental period characterized by neurobiological changes and exposure to novel experiences. According to the Center for Disease Control, approximately 70% of adolescent deaths in the United States are due to risky behaviors such as reckless driving and risky sexual behavior (Kann et al., 2016). In order to better understand what drives adolescent risk-taking, the current studies utilized an interdisciplinary approach, which combined behavioral economic models and functional magnetic resonance imaging (fMRI) to understand neurobehavioral mechanisms of risky choice. The focus of the current studies is to investigate the extent to which neurobehavioral mechanisms of risky choice change across adolescence, and to identify individual differences that explain real-world risky behavior. In Study 1, we show that behavioral sensitivity to risk and neural correlates of risk processing change across a critical period of adolescence. Importantly, our results indicate that individual differences in neural, not behavioral risk sensitivity are predictive of future engagement in health risk behaviors. In Study 2, we examined the relation between inter-individual differences in adolescent expectations of valued rewards and self-reported risky behavior using an adapted behavioral economic model. Implications and future directions for adolescent risky decision-making are discussed.en
dc.description.abstractgeneralAccording to the Center for Disease Control, approximately 70% of adolescent deaths in the United States are due to risky behaviors such as reckless driving and risky sexual behavior (Kann et al., 2016). In order to prevent and reduce such risk-taking behavior during adolescence, it is essential to improve our current understanding of the mechanisms contributing to risky decision-making. One promising mechanism that may be critical in guiding adolescents either toward or away from risky behavior is the extent to which adolescents are sensitive to the risk or likelihood of receiving potential rewarding outcomes. To this end, the current work leveraged the used of a longitudinal design with an interdisciplinary approach that combined the use of behavioral economic models, functional magnetic resonance imaging (fMRI), and developmental psychological theory to better understand how adolescents develop risk sensitivity at both the behavioral and neural levels. Importantly, our results in Study 1 indicated that individual differences in neural, not behavioral risk sensitivity are predictive of future engagement in health risk behaviors. In Study 2, we used an adapted behavioral economic model to identify individual differences in adolescent expectations of valued rewards, and assess the relation of these differences to self-reported risky behavior. This research illuminates the critical role that neurobehavioral risk sensitivity might play during risky decision-making, which may have implications for the prevention and amelioration of adverse health risk behaviors.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.format.mimetypeapplication/pdfen
dc.identifier.othervt_gsexam:13269en
dc.identifier.urihttp://hdl.handle.net/10919/89669en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectadolescenceen
dc.subjectrisky decision-makingen
dc.subjectfMRIen
dc.subjectindividual differencesen
dc.subjectlongitudinalen
dc.titleNeuroeconomic Predictors of Adolescent Risky Decision-Makingen
dc.typeDissertationen
dc.type.dcmitypeTexten
thesis.degree.disciplinePsychologyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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