女同性恋
心理学
心理健康
毒物控制
自杀预防
家庭暴力
伤害预防
职业安全与健康
人为因素与人体工程学
潜在类模型
儿童期虐待
临床心理学
虐待儿童
精神科
发展心理学
医学
医疗急救
精神分析
数学
病理
统计
作者
Ruby Charak,Lillianne Villarreal,Rachel M. Schmitz,Michiyo Hirai,Julián D. Ford
标识
DOI:10.1016/j.chiabu.2019.01.007
摘要
Childhood abuse and neglect (CAN) and intimate partner violence victimization (IPV) is prevalent among lesbian, gay, and bisexual individuals (LGB). Identification of distinct patterns of childhood and adult victimization, including technology-mediated and face-to-face IPV, and their cumulative relations to mental/behavioral health challenges, among LGB people is needed to facilitate identification of at-risk individuals.Using latent class analysis, we first sought to identify patterns of lifetime interpersonal victimization, primarily five types of CAN and IPV in LGB emerging adults. Second, we examined if LGB-status and race/ethnicity predicted class-membership; third, we assessed differences between the latent classes on emotion dysregulation, depressive and anxiety symptoms, and alcohol use.Participants were 288 LGB adults between 18-29 years (M = 25.35, SD = 2.76; 41.7% gay/lesbian) recruited via Amazon MTurk.The 3-step LCA identified five-latent classes: high victimization, childhood emotional abuse and neglect, cybervictimization, adult face-to-face IPV, and lower victimization. People of color (including Hispanics) were more likely to be in the high victimization class, and bisexual individuals, especially bisexual women, in the childhood emotional abuse and neglect class. High victimization and childhood emotional abuse and neglect classes had elevated emotion dysregulation levels and depression and anxiety symptoms, and the high victimization class reported the highest levels of alcohol use.Findings suggest a detrimental effect of cumulative interpersonal victimization on emotion dysregulation and the mental/behavioral health of LGB emerging adults, with bisexuals and LGB-people of color at heightened risk of cumulative victimization and of related mental/behavioral health challenges.
科研通智能强力驱动
Strongly Powered by AbleSci AI