| Literature DB >> 33869877 |
Abstract
The spread of the COVID-19 pandemic has transformed the way people live, work, and socialize, and has perhaps even altered the reasons why they harass one another. To our knowledge, the present study is one of the first studies to address cyberbullying among university students during the COVID-19 pandemic. Additional objectives were to reveal the causes and types of cyberbullying that university students from East and Southeast Asia have experienced because of COVID-19, and to explore the relationship between cyberbullying and self-esteem. Of the 525 university students from different East and Southeast Asian countries and varied academic backgrounds who were invited to participate in the study, 310 students agreed and were included. Moreover, a sample of 400 Jordanian undergraduate students, who participated in cyberbullying against East and Southeast Asian students on social media, answered a questionnaire to reveal their reasons for engaging in bullying during the COVID-19 pandemic. This study also examined the relationship and differences between sex and nationality. The findings revealed that cyberbullying contributed to low self-esteem in students of East and Southeast Asian descent who were victims of bullying. Men were more likely to be bullies and cyberbullies than women. The bullies admitted that the main reason for cyberbullying was humor, and that they were unaware that their harsh or aggressive behaviors could be categorized as bullying. This study aimed to make a positive contribution to the scant literature on cyberbullying/cyber racism among university students in an Arab country. We believe our findings can help guide the formulation of policies and solutions that address cyberbullying, especially between resident and foreign students.Entities:
Keywords: COVID-19; Cyberbullying; Jordan; Nationality discrimination; Self-esteem; Social stigma; University students
Year: 2021 PMID: 33869877 PMCID: PMC8045034 DOI: 10.1016/j.heliyon.2021.e06711
Source DB: PubMed Journal: Heliyon ISSN: 2405-8440
Frequency distribution of four items related to bullying (Data Set 2).
| Bullies (Jordanian students) | No | Yes | ||
|---|---|---|---|---|
| Items | Frequency | % | Frequency | % |
| Do you believe that East and Southeast Asians are responsible for the pandemic and for spreading the virus? | 2 | 0.5 | 398 | 99.5 |
| Was it your intention to hurt and offend them? | 340 | 85 | 60 | 15 |
| Do you have a reason for doing this, other than humor? | 364 | 91 | 36 | 9 |
| Were you aware that your actions are equivalent to bullying? | 365 | 91.3 | 35 | 8.8 |
Frequency distribution of demographic variables.
| Demographic Variables | Frequency | % |
|---|---|---|
| Male | 187 | 60.3 |
| Female | 123 | 39.7 |
| Chinese | 104 | 26 |
| Korean | 26 | 6.5 |
| Indonesian | 60 | 15 |
| Singaporean | 42 | 10.5 |
| Thai | 32 | 8 |
| Filipino | 9 | 2.3 |
| Malaysian | 37 | 9.3 |
| Male | 190 | 47.5 |
| Female | 210 | 52.5 |
Reliability statistics (Cronbach's alpha and composite reliability) for scale and subscale variables.
| Variables | Cronbach's Alpha | Composite Reliability | N of Items |
|---|---|---|---|
| Adjusted CYBVICS | 0.808 | 0.701 | 18 |
| Self-esteem scale | 0.887 | 0.897 | 5 |
| Reason for cyberbullying | 0.724 | 4 |
CYBVICS, Adolescent Cyber-Victimization Scale.
Figure 1Nationality, Data Set 1 (East and Southeast Asian students) N = 310.
Descriptive statistics of the CYBVICS.
| East and Southeast Asian Students | N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | |
|---|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | |||||||
| Chinese | 104 | 33.7596 | 5.37613 | 0.52717 | 32.7141 | 34.8051 | 19 | 5 |
| Korean | 26 | 3.4615 | 4.54516 | 0.89138 | 28.6257 | 32.2974 | 22 | 4 |
| Indonesian | 60 | 25.3833 | 5.39017 | 0.69587 | 23.9909 | 26.7758 | 18 | 43 |
| Singaporean | 42 | 29.9762 | 3.1038 | 0.47893 | 29.009 | 3.9434 | 26 | 38 |
| Thai | 32 | 24.2188 | 4.41211 | 0.77996 | 22.628 | 25.8095 | 2 | 4 |
| Filipino | 9 | 28 | 0.86603 | 0.28868 | 27.3343 | 28.6657 | 27 | 29 |
| Malaysian | 37 | 25.8378 | 4.6816 | 0.76965 | 24.2769 | 27.3988 | 2 | 35 |
| Total | 310 | 29.2516 | 6.05487 | 0.34389 | 28.5749 | 29.9283 | 18 | 5 |
ANOVA results of the CYBVICS.
| Sum of Squares | df | Mean Square | F | Sig. | |
|---|---|---|---|---|---|
| Between Nationalities | 4327.267 | 6 | 721.211 | 31.213 | 0 |
| Within Nationalities | 7001.107 | 303 | 23.106 | ||
| Total | 11328.374 | 309 |
Multiple comparisons (dependent variable: CYBVICS, bootstrapped Tamhane's T2 test).
| Nationality 1 | Nationality 2 | Mean Difference (Nationality1-Nationality2) | Std. Error | 95% CI lower | 95% CI upper | p | Cohen's d | |
|---|---|---|---|---|---|---|---|---|
| Chinese | Thai | 9.54 | ∗ | 0.96 | 7.51 | 11.41 | 0 | 1.85 |
| Chinese | Indonesian | 8.38 | ∗ | 0.87 | 6.54 | 1.18 | 0 | 1.56 |
| Singaporean | Thai | 5.76 | ∗ | 0.94 | 3.79 | 7.46 | 0 | 1.55 |
| Chinese | Malaysian | 7.92 | ∗ | 0.9 | 6.1 | 9.85 | 0 | 1.52 |
| Korean | Thai | 6.24 | ∗ | 1.2 | 3.73 | 8.46 | 0 | 1.4 |
| Chinese | Filipino | 5.76 | ∗ | 0.6 | 4.58 | 7.06 | 0 | 1.11 |
| Singaporean | Malaysian | 4.14 | ∗ | 0.91 | 2.38 | 6.06 | 0 | 1.06 |
| Singaporean | Indonesian | 4.59 | ∗ | 0.85 | 2.82 | 6.41 | 0 | 1 |
| Korean | Malaysian | 4.62 | ∗ | 1.17 | 2.25 | 7.03 | 0 | 1 |
| Korean | Indonesian | 5.08 | ∗ | 1.11 | 2.88 | 7.25 | 0 | 0.99 |
| Filipino | Thai | 3.78 | ∗ | 0.85 | 1.9 | 5.3 | 0 | 0.96 |
| Chinese | Singaporean | 3.78 | ∗ | 0.72 | 2.22 | 5.21 | 0 | 0.78 |
| Singaporean | Filipino | 1.98 | ∗ | 0.58 | 0.87 | 3.03 | 0 | 0.69 |
| Chinese | Korean | 3.3 | ∗ | 1.05 | 1.08 | 5.48 | 0.001 | 0.63 |
| Korean | Filipino | 2.46 | ∗ | 0.92 | 0.82 | 4.13 | 0.004 | 0.62 |
| Filipino | Indonesian | 2.62 | ∗ | 0.73 | 1.07 | 4.03 | 0 | 0.52 |
| Filipino | Malaysian | 2.16 | ∗ | 0.81 | 0.61 | 3.8 | 0.004 | 0.51 |
| Malaysian | Thai | 1.62 | 1.08 | -0.66 | 3.48 | 0.068 | 0.36 | |
| Indonesian | Thai | 1.16 | 1.05 | -0.91 | 3.19 | 0.133 | 0.23 | |
| Korean | Singaporean | 0.49 | 0.99 | -1.31 | 2.45 | 0.312 | 0.13 | |
| Malaysian | Indonesian | 0.45 | 1.03 | -1.57 | 2.39 | 0.33 | 0.09 | |
∗ Difference significant at the 5% level (2-tailed).
Levene's Test is significant ( P < 0.05).
Correlation between cyberbullying and self-esteem.
| Self-esteem scale | ||
|---|---|---|
| Pearson Correlation | -.682∗∗ | |
| Sig. (2-tailed) | 0 | |
| N | 310 | |
∗∗ Correlation is significant at the .01 level (2-tailed).
Comparison of the CYBVICS scores by sex across nationalities.
| Nationality | Male | Female | Welch robust test of equality of means | Cohen's d | ||
|---|---|---|---|---|---|---|
| Mean | Std. Deviation | Mean | Std. Deviation | |||
| Chinese | 35 | 4.5 | 31.8 | 6.1 | F(1,65.0) = 7.89, p = .007 | 0.61 |
| Korean | 31.38 | 4.06 | 29 | 5.1 | F(1,16.0) = 1.55, p = .231 | 0.53 |
| Indonesian | 26.32 | 6.12 | 23.77 | 3.37 | F(1,16.0) = 4.31, p = .042 | 0.48 |
| Singaporean | 28.48 | 1.81 | 33.31 | 2.81 | F(1,16.6) = 32.3, p < .001 | -2.24 |
| Thai | 26.08 | 5.74 | 23.1 | 3.02 | F(1,14.7) = 2.78, p = .117 | 0.71 |
| Filipino | 28 | 0.87 | - | - | - | - |
| Malaysian | 29.05 | 4.01 | 22.44 | 2.38 | F(1,29.6) = 37.6, p < .001 | 1.99 |
Tests of between-subjects effects: Dependent variables for the CYBVICS.
| Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
|---|---|---|---|---|---|
| Corrected Model | 5,374.718a | 12 | 447.893 | 22.343 | 0 |
| Intercept | 162,496.5 | 1 | 162,496.5 | 8,106.189 | 0 |
| Sex | 262.125 | 1 | 262.125 | 13.076 | 0 |
| Nationality | 3,957.645 | 6 | 659.607 | 32.905 | 0 |
| Sex ∗ Nationality | 648.67 | 5 | 129.734 | 6.472 | 0 |
| Error | 5,953.656 | 297 | 2.046 | ||
| Total | 276,582 | 310 | |||
| Corrected Total | 11,328.374 | 309 |
R square = coefficient if determination.
R Squared = .474 (Adjusted R Squared = .453).
Figure 2Error bar plots of mean CYBVICS scores by nationality and sex.