TABLE 3.
Summary of regression analysis
| Variable | Cyberbullying |
|---|---|
| COVID‐19 Influence | .84*** |
| R2 | .71 |
| F Value | 485.39 |
| Durbin‐Watson Statistic | 2.01 |
Note: N = 200; *p < .05, **p < .01, ***p < .001.
Based on this table, the relationship between COVID‐19 influence as a social media usage determinant and cyberbullying is evident. In which our study used the COVID‐19 influence as a predictor for the outcome, cyberbullying. We initially assumed that COVID‐19 indirectly influenced the sudden increase of cyberbullying amongst Malaysian youth because people had to move everything home, including their social life. As a result, COVID‐19 has become a determinant of social media usage, which caused it to increase drastically among the youth. Hypothesis 1 predicts the relationship between COVID‐19 Influence and Cyberbullying. As shown in this table, COVID‐19 influence was significantly related to cyberbullying with beta values of .84. Thus, H1 received support. After proving that COVID‐19 is a determinant, we came to the creation of our study that COVID‐19 influence has intensified cyberbullying incidents. R2 of 0.709 indicates that 71% of the cyberbullying variation is indeed affected by its predictor, COVID‐19 influence. As for the COVID‐19 influence significance, its significance shows 0.00, evidently higher than the 0.01 significance level: hence, there is a strong significant relationship between Cyberbullying and COVID‐19 influence.