Genital Injuries in Adolescents after Sexual Assault

青少年性侵犯后的生殖器损伤

• 批准号: 7054346
• 负责人: RACHEL B BAKER
• 金额: $ 3.37万
• 依托单位: UNIVERSITY OF CINCINNATI
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-01-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7054346
• 关键词: adolescence (12-20); age difference; clinical research; crime victims; digital imaging; epidemiology; female; female reproductive system disorder; forensic medicine; human subject; injury; medical records; pigmentation; racial /ethnic difference; sex abuse; statistics /biometry; women' s health

DESCRIPTION (provided by applicant): Adolescents constitute the largest group of sexual assault victims. Even though physiologic theory suggests that their injuries may be different from injuries of adults, little is known about the prevalence and patterns of injuries that female adolescents sustain from sexual assault. The work conducted by the mentor's research team suggests that observed injuries may vary by the skin color of the victim, with higher injury prevalence in women with darker skin as compared to women with lighter skin. Because injuries are highly associated with decisions to prosecute and rates of conviction, it is crucial that all victims, regardless of age, race, or skin color, receive unbiased forensic examinations. The present study aims to describe the prevalence and patterns of injury that occur following sexual assault among adolescent females, including examining the association among age, race, skin color, and genital injury. A retrospective review of medical records will be conducted. Digital images will be analyzed to quantify skin color and classify injury. Regression models will be fit to determine the significance of age, race, and skin color as predictors of injury prevalence and pattern.

描述（由申请人提供）：青少年是最大的性侵犯受害者群体。尽管生理理论表明她们的伤害可能与成年人的伤害不同，但人们对女性青少年遭受性侵犯的伤害的普遍性和模式知之甚少。导师研究小组进行的工作表明，观察到的伤害可能因受害者的肤色而异，与浅色皮肤的女性相比，深色皮肤的女性受伤发生率更高。由于伤害与起诉决定和定罪率密切相关，因此所有受害者，无论年龄、种族或肤色，都必须接受公正的法医检查，这一点至关重要。本研究旨在描述青春期女性遭受性侵犯后发生的伤害的患病率和模式，包括检查年龄、种族、肤色和生殖器伤害之间的关联。将对医疗记录进行回顾性审查。将分析数字图像以量化肤色并对损伤进行分类。回归模型将适合确定年龄、种族和肤色作为损伤发生率和模式的预测因素的重要性。