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This two-wave longitudinal study identified configurations of social rejection, affiliation with aggressive peers, and academic failure and examined their predictivity for reactive and proactive aggression in a sample of 1,479 children and adolescents aged between 9 and 19 years. Latent profile analysis yielded three configurations of risk factors, made up of a non-risk group, a risk group scoring high on measures of social rejection (SR), and a risk group scoring high on measures of affiliation with aggressive peers and academic failure (APAF). Latent path analysis revealed that, as predicted, only membership in the SR group at T1 predicted reactive aggression at T2 17 months later. By contrast, only membership in the APAF group at T1 predicted proactive aggression at T2.
This two-wave longitudinal study identified configurations of social rejection, affiliation with aggressive peers, and academic failure and examined their predictivity for reactive and proactive aggression in a sample of 1,479 children and adolescents aged between 9 and 19 years. Latent profile analysis yielded three configurations of risk factors, made up of a non-risk group, a risk group scoring high on measures of social rejection (SR), and a risk group scoring high on measures of affiliation with aggressive peers and academic failure (APAF). Latent path analysis revealed that, as predicted, only membership in the SR group at T1 predicted reactive aggression at T2 17 months later. By contrast, only membership in the APAF group at T1 predicted proactive aggression at T2.
This article investigated how the development of deviant behavior in adolescence is influenced by the variability of deviant behavior in the peer group. Based on the social information-processing (SIP) model, we predicted that peer groups with a low variability of deviant behavior (providing normative information that is easy to process) should have a main effect on the development of adolescents’ deviant behavior over time, whereas peer groups in which deviant behavior is more variable (i.e., more difficult to process) should primarily impact the deviant behavior of initially nondeviant classroom members. These hypotheses were largely supported in a multilevel analysis using self-reports of deviant behavior in a sample of 16,891 adolescents in 1,308 classes assessed at two data waves about 1-year apart. The results demonstrate the advantages of studying cross-level interactions to clarify the impact of the peer environment on the development of deviant behavior in adolescence.