Sexual violence is a major public health issue within the United States, particularly that with perpetrators who are men and victims who are women. Understanding risk factors for sexual violence perpetration is necessary to decrease the overall severity of sexual violence. In past research, psychological reactance has been shown to be associated with sexual violence perpetration, yet there is limited research on this association. Additionally, previous research has found that other traits may enhance the predictive properties of psychological reactance and that sensation seeking can predict sexual violence risk factors and sexual violence perpetration. Yet there is little to no research on how sensation seeking and psychological reactance work jointly to predict sexual violence perpetration. This thesis aims to explore these factors as possible predictors for sexual violence perpetration and sensation seeking as a moderator of the relationship between reactance and sexual violence perpetration. A better understanding of these predictors could allow for new ways to understand sexual violence perpetration overall and aid in future research. Based on this information, reactance, sensation seeking, and their interaction effect are all expected to significantly predict sexual violence perpetration. The current study examined 226 participants who were men, single, attracted to women, and over the age of 18 living in the U.S. Participants were recruited from Amazon Mechanical Turk, and completed an online survey hosted on Qualtrics. Participants reported past sexual violence perpetration, sensation seeking, psychological reactance, and demographic information. Results provided partial support for the hypothesis. Findings indicated that higher levels of psychological reactance and sensation seeking were positively associated with sexual violence perpetration; however, sensation seeking as a moderator was not significant.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-2365 |
| Date | 01 January 2022 |
| Creators | Gabriel, Elana |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Honors Undergraduate Theses |
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