The association between school exclusion,delinquency and subtypes of cyber- and F2F-victimizations: Identifying and predicting risk profiles and subtypes using latent class analysis |
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| Institution: | 1. Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Rosenau Hall, CB #7440, 135 Dauer Drive, Chapel Hill, NC 27599, USA;2. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 137 E. Franklin St., Suite 203, CB#8030, Chapel Hill, NC 27514, USA;3. Department of Sociology, University of California Davis, 2247 Social Sciences & Humanities, One Shields Avenue, Davis, CA 95616, USA;4. Department of Epidemiology, Gillings School of Global Public Health and Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, 137 E. Franklin St., Suite 306, CB# 7435, Chapel Hill, NC 27514, USA;1. Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, PR China;2. Department of Epidemiology, School of Public Health, University of California, Los Angeles, CA, USA;1. EA 3188, Psychology Laboratory and FR “EDUC”, University of Franche-Comté, Besançon, France;2. EA 2114, “Psychology of the Various Stages of Life (PAV)” Laboratory, François Rabelais University, Tours, France;3. EA 6291, “Cognition, Health & Socialization” Laboratory, University of Reims, France;1. South Dakota State University, United States;2. Baylor University, United States |
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| Abstract: | This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed. |
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| Keywords: | Cybervictimization Bullying Academic performance Aggression Latent class analysis |
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