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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The current study assessed a wide range of offense supportive cognitions in relation to the perpetration of physical intimate partner violence (IPV). This research used both implicit and explicit measures in a U.K. sample of 19 male IPV perpetrators recruited from a community-based IPV intervention program and 20 men from the community with no history of IPV. The study also explored the ability of the implicit measures to differentiate between the two groups. The cognitions assessed included gender-role stereotype, attitudes condoning violence against a partner, attitudes condoning violence in general, hostile attitudes toward women, sense of entitlement in the relationship and over the intimate partner (control and dominance), and general sense of entitlement. Participants completed a number of established self-report measures and a series of computer-based reaction time tasks including two implicit association tests, one go/no-go association task, and four sentence judgment tasks. Significant group differences emerged across all measures both at the explicit and at the implicit level. Most implicit measures had very good discriminatory power, and the combination of all implicit measures showed excellent discriminatory power, equal to that of the explicit measures combined. These findings suggest that some IPV perpetrators hold offense supportive cognitions that may have become fairly well established and have started to operate at an automatic level. Implicit measures could be useful tools for risk assessment purposes and identification of treatment needs alongside already established measures.

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