Impulsivity, Peers, and Delinquency: A Dynamic Social Network Approach
Objectives Drawing on criminological research about peer delinquency and self-control, we employ a network perspective to identify the potential paths linking impulsivity, peers, and delinquency. We systematically integrate relevant processes into a set of dynamic network models that evaluate these...
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| Otros Autores: | ; |
| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| En: |
Journal of quantitative criminology
Año: 2023, Volumen: 39, Número: 3, Páginas: 735-768 |
| Acceso en línea: |
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| Sumario: | Objectives Drawing on criminological research about peer delinquency and self-control, we employ a network perspective to identify the potential paths linking impulsivity, peers, and delinquency. We systematically integrate relevant processes into a set of dynamic network models that evaluate these interconnected pathways. Methods Our analyses use data from more than 14,000 students in Pennsylvania and Iowa collected from the evaluation of the PROSPER partnership model. We estimate longitudinal social network models to disentangle the paths through which impulsivity and delinquency are linked in adolescent friendship networks. Results We find evidence of both peer influence and homophilic selection for both impulsivity and delinquency. Further, results indicate that peer impulsivity is linked to individual delinquent behavior through peer influence on delinquency, but not on impulsivity. Finally, the results suggest that impulsivity moderates both influence and selection processes, as adolescents with higher levels of impulsivity are more likely to select delinquent peers but less likely to change their behavior due to peers. Conclusions In sum, this study offers a more holistic framework and stronger theoretical tests than similar studies of the past. Our results illustrate the need to consider the simultaneous network processes related to peers, impulsivity, and delinquency. Further, our findings reveal that a large dataset with ample statistical power is a valuable advantage for detecting the selection processes that shape friendship networks. |
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| ISSN: | 1573-7799 |
| DOI: | 10.1007/s10940-022-09547-8 |