Identifying victimization clusters across people with intellectual disabilities: A latent class analysis

Research has shown high rates of victimization among people with intellectual disabilities (ID), but victimization clusters have not been previously explored. We address the gap by examining how reported victimization experiences are grouped into different classes and identifying differences in the characteristics of the individuals in each class. We conducted a cross-sectional self-report study with a sample of adults with an ID diagnosis (n = 260). We gathered data about the participants' victimization experiences and socio-demographics, and then subjected the data to latent class analysis (LCA). Three different classes were detected: High victimization (n = 27, 10.4 %); medium victimization, low sexual (n = 97, 37.3 %); and low victimization (n = 136, 52.3 %). The results highlight the experiences of sexual and physical victimization among the high-victimization class, in which women are overrepresented, and physical victimization among the medium-victimization class. The study also found that experiences of assault and bias attacks occur to a varying extent across all three classes. The LCA and poly-victimization methods showed substantial agreement but also differences when identifying the most victimized participants. In addition, we detected significant differences between classes in gender, type of school attended, place of residence, legal incapacity, type of support needed, secondary disability and poly-victimization status. We detected distinct underlying ingroup patterns of victimization and sociodemographic inter-class differences that contribute to a better understanding of victimization within the population in question. The results have prevention and intervention implications for caregivers and providers of services for people with ID.