Siber mağduriyet, akran zorbalığı, karanlık üçlü, riskli davranışlar ve prososyal davranışların siber zorba olan/olmayan ergenleri doğru sınıflandırma düzeyi
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Tarih
2022
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İnönü Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Bu araştırmanın amacı ergenlerdeki siber mağduriyet, akran zorbalığı, karanlık üçlü kişilik özellikleri, riskli davranış ve prososyal davranışların ergenlerin siber zorba olup olmadığını ne düzeyde yordadığını belirlemektir. Bu araştırma kesitsel desende gerçekleştirilmiş betimsel bir nicel araştırma olup keşfedici korelasyonel modelde tasarlanmıştır. Araştırmaya 2021-2022 eğitim öğretim yılında İnönü Üniversitesi'ndeki 9 fakülte ve 1 meslek yüksekokulunda öğrenim gören toplam 952 öğrenci katılmıştır. Araştırmada veri toplama araçları olarak Yenilenmiş Siber Zorbalık/Mağduriyet Envanteri 2, Akran Zorbalığı Ölçeği, Kısaltılmış Karanlık Üçlü Ölçeği Türkçe Formu, Riskli Davranışlar Ölçeği, Olumlu Sosyal Davranış Eğilimi Ölçeği ve kişisel bilgi formu kullanılmıştır. Araştırmanın verileri yüzde-frekans analizi ve lojistik regresyon analizi ile incelenmiştir. Lojistik regresyon analizi gerçekleştirilmeden önce örneklemin yeterli büyüklükte olduğu belirlenmiş, uç veriler belirlenerek analize dahil edilmemiş ve değişkenler arasındaki korelasyon katsayıları incelenerek çoklu bağlantı problemi olmadığı görülmüştür. Araştırma sonucunda örneklemdeki ergenlerin %47'sinin siber zorbalık sürecine zorba, mağdur veya zorba/mağdur (hem zorba hem de mağdur) olarak dahil olduğu; %53'ünün siber zorbalığa dahil olmadığı saptanmıştır. Ergenlerin %30'unun siber zorba, %40'ının siber mağdur, %7'sinin sadece siber zorba, %17'sinin sadece siber mağdur, %23'ünün ise zorba/mağdur olduğu belirlenmiştir. Elde edilen lojistik regresyon modelinde siber zorbalık ile araştırmada ele alınan yordayıcı değişkenler arasında ilişki olduğu, modelin uyum iyiliğinin yeterli düzeyde olduğu ve siber zorbalıktaki varyansın %25'ini açıkladığı tespit edilmiştir. Elde edilen modelin siber zorba olan ve olmayan ergenleri %79 oranında doğru sınıflandırdığı; modeldeki yordayıcı değişkenlerden siber mağduriyet, akran zorbalığı, alkol kullanımı, antisosyal davranışlar ve beslenme alışkanlıklarının siber zorba olan ve olmayan ergenlerin yordanmasına anlamlı katkılar sağladığı belirlenmiştir.
The aim of this study is to determine to what extent adolescents' cyber victimization, peer bullying, dark triad personality traits, risk behavior and prosocial behaviors predict cyberbully and non-cyberbully adolescents. This research is a descriptive quantitative research conducted in a cross-sectional design and designed in an exploratory correlational model. A total of 952 students studying at 9 faculties and 1 vocational school at İnönü University in the 2021-2022 academic year participated in the research. Revised Cyberbullying/Victimization Inventory 2, Peer Bullying Scale, Short Dark Triad Scale Turkish Form, Risk Behaviors Scale, Prosocial Tendencies Scale and personal information form were used as data collection tools in the study. The data of the study were analyzed by percent-frequency analysis and logistic regression analysis. Before performing the logistic regression analysis, it was determined that the sample was large enough, outlier data were not included in the analysis, and the correlation coefficients between the variables were examined and it was seen that there was no multicollinearity problem. As a result of the research, it was determined that 47% of the adolescents in the sample were involved in the cyberbullying process as a bully, victim or bully/victim (both bully and victim); 53% of them were not involved in cyberbullying. It was determined that 30% of the adolescents are cyberbullies, 40% are cyber victims, 7% are only cyberbullies, 17% are only cyber victims, and 23% are bullies/victims. In the logistic regression model obtained, it was determined that there was a relationship between cyberbullying and the predictive variables in the study, that the goodness of fit of the model was sufficient and it explained 25% of the variance in cyberbullying. It was determined that the model accurately classified cyberbully and non-cyberbully adolescents at the rate of 79%, and cyber victimization, peer bullying, alcohol use, antisocial behaviors and nutrition habits among the predictive variables in the model made significant contributions to the prediction of cyberbully and non-cyberbully adolescents.
The aim of this study is to determine to what extent adolescents' cyber victimization, peer bullying, dark triad personality traits, risk behavior and prosocial behaviors predict cyberbully and non-cyberbully adolescents. This research is a descriptive quantitative research conducted in a cross-sectional design and designed in an exploratory correlational model. A total of 952 students studying at 9 faculties and 1 vocational school at İnönü University in the 2021-2022 academic year participated in the research. Revised Cyberbullying/Victimization Inventory 2, Peer Bullying Scale, Short Dark Triad Scale Turkish Form, Risk Behaviors Scale, Prosocial Tendencies Scale and personal information form were used as data collection tools in the study. The data of the study were analyzed by percent-frequency analysis and logistic regression analysis. Before performing the logistic regression analysis, it was determined that the sample was large enough, outlier data were not included in the analysis, and the correlation coefficients between the variables were examined and it was seen that there was no multicollinearity problem. As a result of the research, it was determined that 47% of the adolescents in the sample were involved in the cyberbullying process as a bully, victim or bully/victim (both bully and victim); 53% of them were not involved in cyberbullying. It was determined that 30% of the adolescents are cyberbullies, 40% are cyber victims, 7% are only cyberbullies, 17% are only cyber victims, and 23% are bullies/victims. In the logistic regression model obtained, it was determined that there was a relationship between cyberbullying and the predictive variables in the study, that the goodness of fit of the model was sufficient and it explained 25% of the variance in cyberbullying. It was determined that the model accurately classified cyberbully and non-cyberbully adolescents at the rate of 79%, and cyber victimization, peer bullying, alcohol use, antisocial behaviors and nutrition habits among the predictive variables in the model made significant contributions to the prediction of cyberbully and non-cyberbully adolescents.
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Eğitim ve Öğretim
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Haylı, R. G. (2022). Siber mağduriyet, akran zorbalığı, karanlık üçlü, riskli davranışlar ve prososyal davranışların siber zorba olan/olmayan ergenleri doğru sınıflandırma düzeyi. Yayınlanmış Doktora Tezi. İnönü Üniversitesi, Malatya.
