Online aggressor/targets, aggressors, and targets: a comparison of associated youth characteristics

Ybarra, Michele L.; Mitchell, Kimberly J.

doi:10.1111/j.1469-7610.2004.00328.x

Cited by 982 publications

(900 citation statements)

References 16 publications

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“…Previous research has indicated that cyber-aggression perpetration and victimization are related to higher levels of delinquency (Hinduja & Patchin, 2007;Ybarra & Mitchell, 2004a). Studies of traditional bullying also have documented a prospective mean-level relationship between externalizing and bullying perpetration (Sourander et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, research consistently describes adverse consequences of cyber-aggression, including problem behavior, depressed mood, and lowered self-esteem (e.g. Ybarra et al, 2007;Ybarra & Mitchell, 2004a;Ybarra et al, 2006). However, no research to date has examined how the developmental course of these risks relates to subsequent perpetration and victimization of cyber-aggression.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, youthful perpetrators and victims of cyber-aggression have concurrently high levels of alcohol use (Ybarra, Diener-West, & Leaf, 2007) and substance use, including marijuana (Hinduja & Patchin, 2008). Likewise, cyber-aggression perpetration is linked with a higher prevalence of problem behaviors such as physical aggression and damaging property (Ybarra & Mitchell, 2004a), and perpetration and victimization are related to frequent substance use and delinquency (Hinduja & Patchin, 2007;Ybarra & Mitchell, 2004b). Finally, there is an apparent link between cyber-aggression and poor mental health, including lowered self-esteem (Brighi, et al, 2012;Patchin & Hinduja, 2010) and elevated depressive symptoms (Wang, Nansel, & Iannotti, 2011;Ybarra & Mitchell, 2004b;Ybarra, Mitchell, Wolak, & Finkelhor, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Mapping Developmental Precursors of Cyber-Aggression: Trajectories of Risk Predict Perpetration and Victimization

Modecki

Barber

Vernon

2012

J Youth Adolescence

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Technologically mediated contexts are social arenas in which adolescents can be both perpetrators and victims of aggression. Yet, there remains little understanding of the developmental etiology of cyber aggression, itself, as experienced by either perpetrators or victims. The current study examines three-year latent within-person trajectories of known correlates of cyber-aggression, problem behavior, (low) self-esteem, and depressed mood, in a large and diverse sample of youth (N = 1364; 54.6% female; 12-14 years old at T1 ). Findings demonstrate that developmental increases in problem behavior across grades 8-10 predict both cyber-perpetration and victimization in grade 11. Developmental decreases in self-esteem also predicted both grade 11 perpetration and victimization. Finally, early depressed mood predicted both perpetration and victimization later on, regardless of developmental change in depressed mood in the interim. Our results reveal a clear link between risky developmental trajectories across the early high school years and later cyber-aggression and imply that mitigating trajectories of risk early on may lead to decreases in cyber-aggression at a later date.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping Developmental Precursors of Cyber-Aggression: Trajectories of Risk Predict Perpetration and Victimization

Modecki

Barber

Vernon

2012

J Youth Adolescence

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“…Studies in England, Canada, Australia and USA report a rate of 4%-25% of youth c-victimization and a rate of 11%-17% of c-bullying (Campbell, 2005;Li, 2006;NCH, 2005;Noret & Rivers, 2006;Ybarra & Mitchell, 2004).…”

Section: Bullying and Cyberbullying 8mentioning

confidence: 99%

“…Hostile Attribution Bias and Outcome Expectancies have been found in school Bullying and Cyberbullying 11 11 bullying and aggression between peers, but it has not been examined if the same applies to c-bullying. No research has assessed cognition in c-bullying, nor has any attempted to identify common cognitive factors between t-bullying and c-bullying.Finally, we aimed to see if roles in t-bullying predict the same roles in c-bullying, and test the hypothesis that t-victims engage in c-bullying in order to "take revenge" (Ybarra & Mitchell, 2004). This is also a very new area of research and previous studies have failed to find consistent results due to methodological differences and limitations (Raskauskas & Stoltz, 2007;Ybarra & Mitchell).…”

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confidence: 98%

Peer and cyber aggression in secondary school students: the role of moral disengagement, hostile attribution bias, and outcome expectancies

Pornari

Wood

2009

Aggressive Behavior

429

287

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The present study investigated the relationship between cognitive mechanisms applied by people to rationalize and justify harmful acts, and engagement in traditional and cyber bullying among school children. We examined the contribution of Moral Disengagement (MD), Hostile Attribution Bias, and Outcome Expectancies and we further explored the individual contribution of each MD mechanism. Our aim was to identify shared and unique cognitive factors of the two forms of bullying. Three hundred and thirty nine secondary school children completed self-report measures that assessed MD, Hostile Attribution Bias, Outcome Expectancies, and their roles and involvement in traditional and cyber bullying. We found that MD total score positively related to both forms of bullying. Furthermore, traditional bullying positively related to children's moral justification, euphemistic language, displacement of responsibility and outcome expectancies, and negatively associated with hostile attribution bias. Moral justification also related positively to cyberbullying.Cyberbullying and cybervictimization were associated with high levels of traditional bullying and victimization, respectively. The results suggest that MD is a common feature of both traditional and cyber bullying, but it seems that traditional bullying demands a higher level of rationalisation or justification. Moreover, the data suggest that the expectation of positive outcomes from harmful behavior facilitates engagement in traditional bullying. The differential contribution of specific cognitive mechanisms indicates the need for future research to elaborate on the current findings in order to advance theory and inform existing and future antibullying school interventions. Bullying is a subtype of aggression defined as an intentional and repeated aggressive behavior by a group or individual, towards a victim who cannot readily defend himself/herself (Olweus, 1999). Smith and Sharp (1994) describe it as ''a systematic abuse of power'' (p. 2). School bullying is not rare. Various studies in different countries have reported a rate of victimization between 9% -32% and a rate of bullying between 4% -27% (Berger, 2007;Smith et al., 1999). Bullying can be physical (e.g. hitting, kicking), behavioral (e.g. stealing one's lunch,), verbal (e.g. threats, insults), and relational (e.g. exclusion from a group) (Berger). It can be direct or indirect (Underwood, 2000) and it can vary in terms of intensity, duration and motives (Tattum, 1994). In general, boys engage in more physical forms of bullying and girls in more indirect/relational bullying (Rivers & Smith, 1994;Scheitauer, 2002).Bullies and victims suffer from, and are at risk of various psychosocial problems (Card, 2003;Haynie et al., 2001;Hawker & Boulton, 2000;Nansel, Overpeck, Saluja, & Ruan, 2004;Olweus, 1999;Picket et al., 2002).Those who are both bullies and victims, otherwise called aggressive victims, are at higher risk (Duncan, 1999;Wolke, Woods, Bloomfield, & Karstadt, 2000), because they are prone to both ...

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Psychosocial Risk Factors Associated With Cyberbullying Among Adolescents

Sourander

Klomek

Ikonen

et al. 2010

Arch Gen Psychiatry

652

427

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Online aggressor/targets, aggressors, and targets: a comparison of associated youth characteristics

Cited by 982 publications

References 16 publications

Mapping Developmental Precursors of Cyber-Aggression: Trajectories of Risk Predict Perpetration and Victimization

Mapping Developmental Precursors of Cyber-Aggression: Trajectories of Risk Predict Perpetration and Victimization

Peer and cyber aggression in secondary school students: the role of moral disengagement, hostile attribution bias, and outcome expectancies

Psychosocial Risk Factors Associated With Cyberbullying Among Adolescents

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