This study hypothesizes that self-control and opportunity variables affect heterogeneity in developmental trajectories of bullying victimization. Using data from a follow-up study of 2,351 Korean adolescents, the study incorporates a latent class growth analysis approach to identify subgroups, each with a unique pattern of the trajectories. The model yields three subgroups of bullying victims: the early-onset and decreaser, the increaser and late-peak, and the normative groups. Results suggest that, compared to the normative group, the early-onset and decreasing group members manifest lower levels of self-control and engage in a greater range of delinquent behaviors. Also, the impact of low self-control on group membership was attenuated after controlling for those opportunity variables, indicating a partially mediating relationship. Social guardianship variables distinguished normative groups from other victim groups. Further, members of the increaser and late-peak group were more likely than the early-onset and decreaser group members to engage in cyber deviance over the long-term.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/0306624X221102793 | DOI Listing |
Rev Esc Enferm USP
January 2025
Manisa Public Hospital, Manisa, Türkiye.
Objective: The present study examines the relationship between social media addiction and cyberbullying among adolescents.
Method: This descriptive study was conducted with the participation of 1,058 adolescents aged 14 to 17, between September 1, 2018, and January 1, 2019, in the Central Anatolian region of Türkiye. Data were collected using the Adolescent Data Collection Form, the Revised Cyber Bullying Inventory II, and the Social Media Disorder Scale for Adolescents - Short Form.
J Interpers Violence
January 2025
It is well known that some youth are both victims and perpetrators of bullying. However, it remains unclear whether the victim-perpetrator overlap contains specific characteristics, such as bias. Using data from the United States Health Behavior among School-aged Children survey from 2009 to 2010 ( = 8,739), this study investigated the victim-perpetrator overlap for school bullying, with emphasis on assessing whether the perpetrators of biased (i.
View Article and Find Full Text PDFThis study examined whether, for bullying perpetrators, admitting to their behavior was associated with specific psychosocial characteristics, and whether it predicted decreases in bullying behavior and a higher responsiveness to a successful anti-bullying program after 9 months of implementation. It also investigated whether participation in an anti-bullying program deterred admitting to the behavior. At pretest, our sample included 5,908 children and early adolescents ( : 11.
View Article and Find Full Text PDFAggress Behav
January 2025
Institute of Psychology, Czech Academy of Sciences, Brno, Czech Republic.
Reputational peer nominations are a common method for measuring involvement in aggression-related behaviors, encompassing the roles of aggressor, victim, and defender, but may be influenced by students' affective (dis)liking relationships. This social network study investigated whether dyad- and group-level (dis)liking relationships affect perceptions of classmates' involvement in physical aggression and explored the moderating roles of classroom moral disengagement and defending norms. The study employed a longitudinal design with two time points 6 months apart, encompassing 27 classrooms and 632 early adolescents.
View Article and Find Full Text PDFPsychol Trauma
January 2025
Department of Applied Social Sciences, Hong Kong Polytechnic University.
Objective: This study investigates the connections among various forms of violence experienced by adolescents, both online and offline, including bullying, cyberbullying, child maltreatment, and witnessing parental intimate partner violence (IPV). The aim was to elucidate the patterns of these adversities to enhance understanding from a child-centered perspective.
Method: We conducted an online survey with a sample of 934 parents ( = 41.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!