Dating violence (DV) victimization in adolescence has been shown to be predictive of both negative emotions and delinquent behavior later in life. However, research that delves into DV victimization and subsequent outcomes, such as deviant behavior, is largely atheoretical. Robert Agnew's general strain theory (GST) provides a theoretical framework to address this limitation. In focusing on negative interactions with others, the theory posits that strain produces negative affect states which leads to deviant or criminal coping. Prior research has identified victimization as a strain, a type of noxious stimuli, which is significantly related to negative emotionality, crime, and deviance. I build on this literature by examining the relationship between dating violence victimization, negative emotionality, and substance use. In addition, little research to date has examined the role that biological factors play in moderating these relationships. Using Add Health, and drawing on two separate, but related, theories, I explore whether the serotonin transporter gene (5-HTTLPR) interacts with dating violence victimization to affect depressive symptoms and self-reported substance use. The analytic strategy involved a series of logistic regressions separated by gender. Results show DV victimization is significantly related to increased odds of binge drinking in males, DV victimization is significantly related to marijuana use for both males and females, and 5-HTTLPR moderates the effect of DV victimization on marijuana use for females only. Although depression does not mediate the relationship between DV victimization and substance use, results show depressive symptoms are independently associated with increased odds of marijuana use. Utility of a GST and biosocial model, implications, and avenues for future research are discussed.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6557 |
Date | 01 January 2017 |
Creators | Yohros, Alexis |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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