The purpose of this three-paper dissertation is to address existing gaps in the literature by examining the intersections of gender-based violence (intimate and non-intimate partner) (GBV) among key-affected populations, defined as women engaged in sex trading in intimate relationships, HIV-positive women, and/or low-income, substance-involved women. This dissertation includes three papers that examine: 1) IPV and recent sex trading among a sample of substance-involved women in intimate sexual relationships in New York City; 2) the prevalence and correlates of GBV among a sample of HIV-positive women in Kazakhstan; and 3) the synergistic effects of IPV, HIV, and substance use on mental health (depression and suicidality) among a sample of high-risk women in relationships in Kazakhstan. This dissertation is guided by the ecological systems framework, intersectionality, and syndemic theory. Key findings from the dissertation highlight the pervasive nature of GBV among vulnerable women who engage in high-risk behaviors and/or live in high-risk settings. Specifically, key findings from papers one and two show higher than average prevalence of GBV among women who engage in sex trading as well as HIV-positive women. Findings from this dissertation also suggest that women who report depression, individual and partner sexual and drug risk-behaviors, and HIV-related stigma are more likely to report GBV than those who do not; and that women who have higher levels of social support and food security are less likely to report GBV and poor mental health. Findings also have several implications for GBV and HIV prevention/intervention efforts within the U.S. and in Kazakhstan, including scaling up efforts to address GBV by multiple perpetrators, stigma, trauma and mental health, drug and sexual risk among couples, and food stability.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8JH3M50 |
| Date | January 2016 |
| Creators | Jiwatram-Negron, Tina |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0021 seconds