Typologies of Adolescent Delinquent Behaviors and Prediction of Latent Delinquent Groups Using Machine Learning Algorithms

نویسندگان

چکیده

Objectives: With the advances in digital technologies, adolescents are more likely to engage multiple types of delinquent behaviors; however, few studies have considered various delinquencies with a multidimensional approach. Therefore, this study aimed identify latent groups based on and examine groups’ predictors using machine learning approaches.Methods: Using nationally representative data (N = 8,210; male 52.17%), class analysis was conducted 10 behaviors self-reported by adolescents. A random forest then employed predict 53 including demographic (6 items), personal (44 environmental levels (3 items). The Mplus program used for analysis, R version 4.0.5 analysis.Results: Three were identified categorized as “high online delinquency” (3.2%), “drink/media (26.8%), “low (70.0%). Random found adolescents’ perception harmful substances most important variable predicting groups. Partial dependence plots showed higher interest substances, lower ability respond substances; access environment, grade; autonomy control ability, classification high delinquency group.Conclusion: This classified three while considering detailed delinquencies. prominent approaches suggest useful prevention programs.

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ژورنال

عنوان ژورنال: Adong haghoeji

سال: 2022

ISSN: ['2234-408X', '1226-1688']

DOI: https://doi.org/10.5723/kjcs.2022.43.4.499