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Longitudinal study examines how adolescent strains predict cyber deviance trajectories, suggesting targeted interventions are needed.
This study aims to investigate developmental heterogeneity in cyber deviance during adolescence and the role of adolescent-specific strains in predicting trajectory group assignment. Using longitudinal data from over 3,000 eighth-grade students across 5 years, group-based trajectory modeling identified distinct developmental patterns of cyber deviance. Multinomial logistic regression models were employed to examine the relationship between strain variables and trajectory group membership. A four-group developmental model was the most optimal fit for the data. Strain variables, including appearance-related stressors and delinquent peer influence, significantly predicted trajectory groups with higher cyber deviance levels. Interventions aiming to mitigate adolescent cyber deviance should address stressors such as appearance-related strains and delinquent peer influence, and promote responsible online behavior, particularly among high-risk groups.
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Choi et al. (2026) studied this question.
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