Pregnancy-associated Homicides (PAHs) are homicides committed while a woman is pregnant, and recent reports from Florida's Pregnancy-associated Mortality Review (PAMR) suggest that it is a leading cause of unnatural deaths for pregnant women. However, a study has not examined the motives, characteristics, and underlying factors behind these homicides. Therefore, this study explored Florida's Pregnancy-associated Intimate Partner Homicides (PAIPHs) using a sample of women that were reportedly pregnant at the time of their mortality (n=33), as well as a comparison group of not-pregnant women (n=33). To conduct the study, reported homicide data from news sources, police reports, and other public records from 2000 to 2019 were aggregated, coded, and analyzed. Findings show that there are differences between PAIPHs and Not-pregnant Intimate Partner Homicides (NPIPHs), and pregnancy is a risk factor for femicide. The primary motives were unwanted pregnancy or relationship, rejection, avoidance of prosecution, abuse exposure, doubts concerning the paternity of the child, and infidelity accusations. Although PAIPH and NPIPH victims were killed for leaving or threatening to leave the perpetrator, PAIPH victims were more likely to be killed because the perpetrator wanted to end the relationship. Most PAIPH victims were unmarried or recently married (less than a year), and Black women had the highest rate of victimization. As for PAIPH perpetrators,78.5% were Black, 30.3% were convicted felons, and some intentionally targeted the unborn child with a knife, gun or blunt force. The findings suggest a need for Maternal Intimate Partner Violence programs, policies, and interventions targeted towards pregnant women and their intimate partners, as well as strategies to combat firearm usage amongst convicted felons.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1135 |
Date | 01 January 2020 |
Creators | Spence, Sonya |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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