# Cyberbullying Analysis in Intercultural Educational Environments Using Binary Logistic Regressions
## 4 Results  
Firstly, the Kruskal-Wallis test was performed to determine whether there are meaningful differences between the study groups and the dimensions of the two subscales. The results revealed that significant differences exist in both subscales (\(p\leq 0.05\)) [60] (Table 2). After detecting significant differences, it was decided to identify those who are more likely to become cybervictims or cyberbullies through the use of binary logistic regression. We took into account the grouping variables of religion, ethnicity, race, and the total number of the questionnaire answers as dependent variables, which included the three dimensions assessed. In this analysis, the differences obtained in the Kruskal-Wallis H test were confirmed. The odds ratios pointed to students of the Muslim religion having a higher chance of becoming cybervictims (aOR 2.423529; 95% CI 0.2-26.8), followed by those of the Buddhist religion (aOR 1.864486; 95% CI 0.9-3.7), and those who did not practice any religion (aOR 1.446902; 95% CI 1.0-2.1). On the other hand, the students of Jewish religion were more likely to be cyberbullies (aOR 3.804348; 95% CI 1.0-14.3), followed by those who did not practice any religion (aOR 1.422808; 95% CI 1.0-2.1), and Taoists (aOR 1.297821; 95% CI 0.7-2.6) (Table 3). Concerning the ethnic variable, the results reveal that the gypsy ethnic students have a higher chance of becoming cybervictims (aOR 1.532874; 95% CI 0.7-3.3), followed by those \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Cybervictims** & \multicolumn{2}{c}{**Cyberbullies**} \\ \hline
**Variables** & **Sig. Asymptotic H test** & **Variables** & **Sig. Asymptotic H test** \\ \hline Religion & 0.01 & Religion & 0.01 \\ Ethnicity & 0.00 & Ethnicity & 0.01 \\ Race & 0.00 & Race & 0.01 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: H Kruskal–Wallis Test for independent samples. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Cybervictims** & **Cyberbullies** \\ \hline
**Religions** & **aOR (95\% CI)** & **aOR (95\% CI)** \\ \hline Judaism & 0.4400458 (0.2–0.9) & 3.804348 (1.0–14.3) \\ Christian & 0.8073335 (0.6–1.1) & 0.7378129 (0.5–1.0) \\ Islam & 2.423529 (0.2–26.8) & 0.6048615 (0.3–1.48) \\ Buddism & 1.864486 (0.9–3.7) & 0.3368984 (0.3–0.4) \\ Taoism & 0.6002950 (0.2–2.4) & 1.297821 (0.7–2.6) \\ Any Religion & 1.446902 (1.0–2.1) & 4.422808 (1.0–2.1) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Analysis of the Binary Logistic Regression showing the association between religions and the profile of cybervictims and cyberbullies. from an Armenian ethnicity (aOR 1.210682; 95% CI 0.4-4.2), those from a Celtic ethnicity (aOR 1.208824; 95% CI 0.2-8.6), and those from a Mongolian ethnicity (aOR 1.106063; 95% CI 0.7-1.7). As for the cyberbullies scale, it is the Gypsy ethnicity (aOR 2.116573; 95% CI 1.0-4.6) followed by the Mongolian ethnicity (aOR 1.009394; 95% CI 0.6-1.6) which are the ones with the highest odds (Table 4). Regarding the analysis of the race variable, the results reveal a greater probability of becoming cybervictims for students of Asian origin (aOR 3.273453; 95% CI 0.9-12.4), followed by students of African origin (aOR 2.054859; 95% CI 1.0-4.0) and those of indigenous origin (aOR 1.331949; 95% CI 0.9-1.9). Regarding the cyberbullies scale, the results indicated that the probability was higher for the Asian race (aOR 4.043243; 95% CI 0.9-18.2), followed by the indigenous race (aOR 1.093528; 95% CI 0.7-1.6) (Table 5). The analyses were carried out on the joint sample of the autonomous community of Andalusia. The results obtained are presented below, with the application of binary logistic regressions in each of the samples selected for each province (Tables 6-8) in order to deepen the probabilities of acquiring the role of cybervictim or cyberbullly in each religion, ethnicity, and race of the ten provinces analyzed.