Do Adolescent-Specific Strains Explain Developmental Trajectories of Cyber Deviance?

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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Publication Details

Journal
Crime & Delinquency
Published
2026-01-15
DOI
https://doi.org/10.1177/00111287251408699
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
0.00
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article

Do Adolescent-Specific Strains Explain Developmental Trajectories of Cyber Deviance?

Julak Lee, Jaeyong Choi, Ko-Hsin Hsu
Crime & Delinquency
Impact of Technology on Adolescents
article

Do Adolescent-Specific Strains Explain Developmental Trajectories of Cyber Deviance?

Julak Lee, Jaeyong Choi, Ko-Hsin Hsu
article en

Abstract

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.

Crime & Delinquency
West Chester University (US), Kutztown University (US), Chung-Ang University (KR)
Reduced inequalities
Openalex Percentile: Top 88%
Impact of Technology on Adolescents
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