The absence of a framework or policy to address bullying in South Africa compels the country to rely on pieces of legislation that are closely related to anti-bullying laws such as the Child Justice Act 75 of 2008 and Protection from Harassment Act 71 of 2011. Over-reliance on pieces of legislation creates challenges for victims of these bullying crimes because most of the relational aggression exerted towards victims goes unpunished. Some of the adolescents take the law into their own hands, thus, exacerbate and increases the complexity of bullying crimes. Due to advancements in Information and Communications Technology, bully-victim behaviour does not only take place in physical environments such as schools, but it takes place anywhere, anytime (24/7) on Mobile Social Networks. In 2011, a cyberbullying study by the Centre of Justice and Crime Prevention reported that 69.7% of the youth in South Africa falls in the category of bully-victims. This is alarming given that few studies focus on the role of bullyvictims in South Africa. The exact cause for mobile bully-victim behaviour is unclear, and previous studies have highlighted it is between aggressive behaviour and social integration. Therefore, this study examined aggressive behaviour and social integration to determine which of these two factors contribute the most to mobile bully-victim behaviour. Additionally, mobile social network features that enable this behaviour were investigated. The factors that lead to aggressive behaviour and social integration, resulting in mobile bully-victims, were identified through a literature review. Paper-based surveys were issued to Johannesburg high school adolescents. Johannesburg was mainly selected based on finding by previous studies, which highlighted that most of the online bullying and victimisation happens amongst adolescents in Johannesburg. After data was collected, the results were analysed using Statistica version 13.5. The analysis revealed that, indeed, both aggressive behaviour and social integration cause mobile bully-victim behaviour, however, social integration contributed more than aggressive behaviour. The findings also revealed that WhatsApp and Instagram were the most utilized social networks by mobile bullyvictims. There were no differences between males and females when it comes to mobile bullyvictim behaviour. The causes of mobile bully-victim behaviour that have been identified in this study can be used as a starting point to develop legislation/framework aimed at combating mobile bully-victim behaviour. Given that mobile bully-victims are more suicidal and suffer from depression, psychologists and therapists can use the knowledge obtained from this study to develop psychological treatments specifically for mobile bully-victims.

The purpose of this research was to investigate the effects of prosocial videogames, played both singly and cooperatively, and aggressive videogames, played both singly and competitively, on children's prosocial behavior. Eighty boys and 80 girls, half third and fourth graders, and half seventh and eighth graders, were randomly assigned to one of five conditions. In a control condition, children answered questions about videogame experience and enjoyment. In two of the treatment conditions, children played a videogame with prosocial content (a human-like fantasy character rescuing another from danger); half of the children played this game singly, while the other half played cooperatively. In the other two conditions, children played an aggressive videogame (stylized boxing), with half of the children playing singly and the other half competing. Following exposure to one of these conditions, each child's game score, game enjoyment rating, level of donating, and level of helping were measured. The results of a three-way analysis of variance (sex x grade x treatment) on donating yielded significant effects for age, F(1, 140) = 34.12, p = Although prosocial videogame play did not increase prosocial responding, aggressive videogame play clearly suppressed this behavior. The failure of the prosocial condition to accelerate donating and helping might be due to the relatively brief exposure used in this study (10 minutes) and/or to the particular prosocial videogame utilized. The failure of the cooperative and competitive game modes to affect prosocial behavior may have been due to the age of the children or to the possibly aversive effects of the type of cooperation required.

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The general aggression model (GAM) has suggested that the interaction between person factors (e.g., personality variables) and situation factors (e.g., playing violent video games [VVGs]) can increase individuals’ aggressive behaviors through their cognition (e.g., hostile attributions), affect (e.g., negative affect), and/or arousal. The present study employed a modified competitive reaction time task to test the effects of shyness, violent (vs. nonviolent) gameplay, and shyness on individuals’ positive–negative affect, hostile attributions, and aggressive behaviors. In addition, the present study also employed structural equation modeling (SEM) to test the mediation (by cognition and affect) and moderation (by shyness). Results showed that playing a VVG increased aggressive behaviors, negative affect, and hostile attributions primarily among shy participants. In addition, the results of SEM also revealed that this moderating role was mediated by negative affect and hostile attributions. The present study supported GAM and showed that individuals’ aggressive behaviors are differentially susceptible to VVGs, depending on their level of shyness in a “for bad and for worse” manner.

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Two studies were conducted to investigate the relationship between age, personality factors and aggressive driving behavior. In Study 1, 1122 volunteers completed an online survey that included questionnaires on demographic data, personality factors, and driving behavior. Personality factors were measured using the Revised Competitiveness Index, the Sensation Seeking Scale, the Big Five Inventory, and the Cook Medley Hostility Scale, whereas aggressive driving behavior was measured using the Aggressive Driving Behavior Scale (ADBS). The majority of the volunteers were female (786 versus 336), while ages ranged from 18 to 87. In Study 2, 98 volunteers from Study 1 were recruited to perform driving simulations on two scenarios. These volunteers consisted of 52 females and 46 males, with ages ranging from 18 to 83. Results from both studies produced positive correlations between aggressive driving behavior and competitiveness, sensation seeking, hostility, extraversion, and neuroticism, while negative correlations were obtained between aggressive driving behavior and age, agreeableness, conscientiousness, and openness. No significant correlation was obtained between gender and aggressive driving behavior. Most importantly, scores in the ADBS were positively correlated to a composite of scores measuring aggressive driving behavior in the simulator. This pattern of results not only validates the ADBS, but it also provides another mechanism to study aggressive driving behavior.

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