A Latent Class Analysis of Online Victim-Offender Overlap among Chinese Youth: Examining Overlap Risks across Online Deviance Types

Abstract

This study aims to comprehensively test the applicability of lifestyle exposure theory (LET) against other criminogenic and victimogenic factors in predicting the differential risks of online offending-victimization overlap across multiple types of online deviance. Using self-reported survey data from 3,741 Chinese college students, the study performed Latent Class Analysis (LCA) and posterior multinomial logistic regression analysis. The LCA identified five latent classes of offending-victimization overlap, with only 6% of respondents reporting high overlap risk. Posterior multinomial logistic regression analysis showed that LET indicators and gender emerged as the most robust predictors of overlap risks compared to other theory-driven (e.g., control and routine activity theories) and sociodemographic factors. The current study accentuates the importance of methodological diversity in examining victim-offender overlap.