Suchergebnisse

Bullying is defined as repeated aggressive behavior (Kowalski & Limber, 2007; Olweus, 1993, and as such has been recognized as a significant social issue. Furthermore, we know that the incidence of bullying behaviors increases with the students' age (Cassidy, Jackson & Brown, 2009; Green-Forde, 2014; Kowalski & Limber, 2007). Cyber bullying, electronic/ online bullying, or online social cruelty is, according to Kowalski & Limber (2007), a relatively new kind of bullying through email, instant messaging, chat room exchanges, digital messages etc. (Kowalski et al, 2012). The goal of this paper is to give an overview of epidemiological studies and effective cyberbullying prevention aimed at children and adolescents. Some authors state that a student is cyberbullied if it happens two or three times a month, while others suggest that a frequency of once or twice a month is sufficient for the existence of the phenomenon (Olweus, 2012a; Hinduja & Patchin, 2012; Menesini, 2012; Kowalski & Limber, 2007). This difference between these threshold is what accounts for the discrepancies found in the data and results of various studies. Thus, we may talk about 4,5% to 24% of cyberbullied children, as in various international studies. Croatian data are similar, with 4,9 % to 29% of cyberbullied students, depending of the definition (Child Protection Center Zagreb, 2013; Zadravec et al., 2014.; Pregrad et al., 2011). The physical and psychological health, and academic performance in the context of bullying and cyberbullying are sometimes similar (Kowalski & Limber, 2013). Social cognitive theory and media effects model are a theoretical framework used to identify main categories which could explain cyberbullying, noting the following: individual factors, family, school, peers and media (Felson, 1996). Cyberbullying behaviors are connected to perception problems, hyperactivity, anger, aggression, problems of behavior control, low sociability, feeling of revenge and feeling unsecure at school (Sourander et al., 2010; Nixon, 2014). School-based intervention/ prevention programs for traditional bullying are often successful and could be used in modified forms for cyberbullying prevention programs (Ttofi & Farrington, 2011 in Slonje, Smith & Frisen, 2013). In Croatia, several preventive programs are being implemented, aimed at bullying in schools, designed for implementation in local communities and financed by local governments or the national administration (Zadravec et al., 2014). These cyberbullying programs are still not, though they should be, part of some broader anti-bullying programs. The aim of conducting effective preventive programs, including cyberbullying interventions, is to decrease bullying and cyberbullying in schools and improve the school climate. The goal is also to reduce students' hyperactivity, anger, aggression and problems of behavior control and initiate better self-efficacy.

Background: The children of male veterans with combat-related posttraumatic stress disorder (PTSD) are at particularly high risk of emotional and behavioral problems. However, no studies have examined non-suicidal self-injury (NSSI) in this population of youth. Aims: To determine the prevalence and psychosocial correlates of lifetime NSSI in a sample of psychiatric outpatient adolescent offspring of Croatian PTSD male veterans. Method: Consecutive outpatient adolescent offspring of Croatian male PTSD veterans, aged 12 to 18 years, were assessed on the Deliberate Self Harm Inventory, the Youth Self-Report, the Family Assessment Device, the Parental Bonding Instrument and the Demographics Questionnaire. Results: Of the whole sample, 52.7% of adolescents reported NSSI at least once during their lifetime. Lifetime NSSI was significantly associated with internalizing symptoms (adjusted odds ratio (OR) = 2.14; 95% confidence interval (CI): 1.04–4.42, p = .040), poor family functioning (adjusted OR = 6.54; 95% CI: 2.02–21.22, p = .002), lower maternal and paternal care (adjusted OR = 0.47; 95% CI: 0.40–0.56, p = .000 and adjusted OR = 0.82; 95% CI: 0.73–0.91, p = .000, respectively) and higher paternal control (adjusted OR = 1.84; 95% CI: 1.59–2.14, p = .000) in multivariate analysis. No association was found between lifetime NSSI and any of the socio-demographic variables. Conclusion: NSSI is a significant clinical problem in outpatient adolescent offspring of PTSD male veterans, which may be influenced by clinical and family factors. Interventions aimed at reducing internalizing symptoms and improving family functioning and parental behaviors are needed in the treatment of adolescent offspring of male PTSD veterans engaging in NSSI.