Description of original award (Fiscal Year 2016, $32,000)
Statement of the Problem: Negative physical health sequelae have been strongly linked to sexual violence among women; however, the majority of this research relies on samples of middle to upper-class and white non-Hispanic women. Additionally, factors such as socioeconomic status (SES) have led to the documented health disparities in racial and ethnic minorities; yet, it is unclear whether sexual violence exacerbates existing health disparities among survivors. Furthermore, the ways in which formal help-seeking in criminal justice agencies affects the health of survivors is not clearly understood, particularly for minority and disadvantaged women. This study seeks to address these gaps by assessing the impact of social and economic factors (race, ethnicity, and SES) on the relationship between multiple characteristics of sexual victimization and long-term physical health outcomes. Findings will inform criminal justice policy aimed at improving the wellbeing and quality of life for survivors as well as best practices for coordinated victim assistance efforts, such as Sexual Assault Response Teams (SARTs).
Research Design and Methods: This study aims to: 1) identify health outcomes of sexual victimization among survivors based on race, ethnicity, and SES; 2) determine which characteristics of sexual victimization are related to health outcomes based on race, ethnicity, and SES; 3) determine how disclosure to police and healthcare professionals affect health outcomes based on race, ethnicity, and SES; and 4) assess moderation effects of race, ethnicity, and SES between sexual victimization characteristics and health outcomes. Data from the 2010 National Intimate Partner and Sexual Violence Survey (NISVS) will be used. The sample includes women from Black non-Hispanic, Latina/Hispanic, and white non-Hispanic racial and ethnic groups reporting lifetime experiences with sexual victimization. Based on NISVS rates of sexual victimization, sample sizes are expected to be at least 300 per group.
Analysis: Multi-group structural equation modeling (SEM) will used to examine group invariance and moderation effects in the model between Black, Latina, and white women and between low SES and high SES women within each racial and ethnic group. Best practices for SEM (Brown, 2015; Kline, 2015) will be used to establish the reliability and validity of measurement models and to build and test the multi-group models.
Products, Reports, and Data Archiving: Findings will be widely disseminated through a published dissertation, peer-reviewed publications, and academic and practitioner conference presentations. ca/ncf
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