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

Background: Research has shown high rates of victimization among people with intellectual disabilities (ID), but victimization clusters have been barely explored. Objective: We address the gap by examining how reported victimization experiences are grouped into different classes and identifying diff...

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Detalles Bibliográficos
Autores: Díaz-Faes, Diego A., Codina, Marta, Pereda Beltran, Noemí
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/210802
Acceso en línea:https://hdl.handle.net/2445/210802
Access Level:acceso abierto
Palabra clave:Víctimes
Persones amb discapacitat mental
Violència
Victims
People with mental disabilities
Violence
Descripción
Sumario:Background: Research has shown high rates of victimization among people with intellectual disabilities (ID), but victimization clusters have been barely explored. Objective: 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. Methods: 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). Results: 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. Conclusion: We identified 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.