Gender and Cyber-bullying: Moderating Effects of Culture and Other Factors
Author(s):
Xitao Fan (presenting / submitting) Shaojing Sun (presenting)
Conference:
ECER 2015
Format:
Paper

Session Information

06 SES 05 A, Self and Other and the Internet

Paper Session

Time:
2015-09-09
11:00-12:30
Room:
104.Oktatóterem [C]
Chair:
Yvonne Fritze

Contribution

 Cyberbullying has become a common issue across the globe. Relevant research concerning cyberbullying has examined various relevant issues and topics, including possible correlates for cyberbullying behavior and psychological impact of cyberbullying, etc. Among the studies on cyberbullying, a focal question is about the relationship between gender and cyberbullying (e.g., Wang, Iannotti, & Luk, 2012).

It should be noted that extant research on cyberbullying mostly focused on demographic factors such as gender, age, and prevalence of bullying. Indeed, gender difference has been widely examined in both cyberbullying and traditional bullying research. In traditional bullying, gender patterns have been evident over time: boys were more likely to get involved in bullying than girls in general, and in direct physical bullying in particular.

Compared to research on traditional bullying, however, cyberbullying research has shown inconsistent findings regarding gender differences. A large amount of research has shown that males are more likely than females to be engaged in cyberbullying. For example, studies from the United Kingdom (Smith et al., 2008), the United States (Wang, Iannotti, & Luk, 2012), and Canada (Li, 2007) reported boys being overrepresented as cyberbullies. Barlett and Gentile (2012), with a large sample of college students in the U.S., identified a positive correlation between CB frequency and gender, with males showing higher frequency of being engaged in CB.

However, other studies did not report any gender differences in cyberbullying (Smith et al., 2008). As Griezel et al. (2008) pointed out, the cyberbullying literature was plagued by inconsistent findings on gender differences. To tackle this issue, it is important, among other things, to design and use psychometrically sound instruments to assess the cyberbullying behavior. For instance, Abeele and Cock (2013) surveyed 264 high-school students in Belgium, and found that males were more likely to be involved in direct bullying, rather than using such means as voice call or picture/video, whereas females were more likely to gossip via voice call or SMS. The findings suggested that the forms or patterns of cyberbullying would make a difference in the likelihood that one would be engaged in cyberbullying behavior. By surveying a large sample of public school students in Sweden, Beckman, Hagquist and Hellström (2012) reported no statistically significant gender differences in the involvement in cyberbullying behaviors.

Although cyberbullying is increasingly being recognized as a societal issue, there are many unanswered questions concerning gender differences in cyberbullying behaviors. More solid research findings about any gender differences, or lack thereof, in cyberbullying would allow researchers and practitioners to assess the different types and levels of cyberbullying involvement by male and female students. Better knowledge in this regard will help researchers and practitioners in designing and planning more effective preventive work and intervention, thus enhancing students’ mental and emotional health, as well as helping them to become better citizens in the long term.

Gender differences in cyberbullying behaviors could potentially be related to cultures, because cultural norms and expectations may influence the behaviors of gender groups. Because of this consideration, we were interested in capturing such potential influence when possible. For this purpose, we used the region of the study sample as a rough proxy for different cultures. More specifically, we had three levels for this study feature variable: North America, Europe/Australia, and Asia.

 

In this study we focus on the following main research questions:

1.     Is there a gender group difference in cyberbullying behaviors as reported in the previous empirical studies?

2.         What are the study features (e.g., study region or culture) that could have partially explained the inconsistencies in the findings concerning the gender group differences in cyberbullying behaviors across individual studies in the literature?

Method

Methods Quantitative meta-analysis was employed to synthesize research conducted in difference counties, and examined the effects of potential moderators on the gender-cyberbullying relationship. We used the databases of PsycInfo, EBSCO, and ERIC for literature research. Google Scholar was also used to locate any additional articles not included in those databases. Major keywords used for the search include cyberbullying, cyberbully, electronic bullying, cyber-victimization, online bullying, online aggression, and Internet bullying. The search covered articles published before October 1st of 2013, and yielded a total of 1447 entries. Because the focus of the currents study is on the relationship between gender and cyberbullying, we then examined these entries and identified those that included gender/sex in the articles. This reduced our search results to 803 articles. A final sample of 39 usable empirical research articles was included for our meta-analysis. Some articles produced more than one effect size, which is a common phenomenon in the practice of meta-analysis (Fan & Chen, 2001). As a result, the final sample of 39 research articles had a total of 100 effect sizes of gender difference in cyberbullying. The appendix provides the complete list of these 39 articles used in this meta-analysis, and some descriptive information relevant for this meta-analysis. Meta-analysis methods were used to quantitatively synthesize the findings from all these individual studies. Cohen's d, the standardized mean difference between gender groups in cyberbullying, was used to represent gender difference from each individual study. When the original data from an individual study were not in the form of Cohen's d (e.g., correlation coefficient, proportions, inferential t-statistic, F-statistic, etc.), mathematical transformation procedures in meta-analysis literature were applied to convert these into Cohen's d for quantitative synthesizing. General linear model analysis was used to assess the effect of the moderator variables (e.g., culture and other study feature characteristics) on the inconsistency of the effect sizes across the studies. Both fixed-effect model and random-effect model were applied to understand the how the effect sizes from individual studies varied.

Expected Outcomes

The findings revealed that gender differences in cyberbullying behaviors varied across different regions (i.e., North America, Europe/Australia, and Asia), with the largest gender difference observed in the Asian samples, followed by that of North American samples, and by the Europe/Australia samples showing almost no gender difference. Such observed regional differences could be the result of cultural factors related to the psycho-social behaviors of males and females in different cultures. Barlett et al. (2014) discussed that cyberbullying should be conceptualized as a societal and cultural phenomenon. The findings in this study could be explained by the self-construal theory (Barlett et al., 2014). Although Asian cultures are characteristic of interdependent self-construal that would discourage bullying others, such a self-construal could be more deep-rooted in Asian females than in Asian males. Bergeron and Schneider (2005) discussed that cultures featuring collectivistic values, high moral discipline, a high level of egalitarian commitment, among others, showed lower levels of aggression than their counterparts. However, our findings suggested that such cultural influences may not be uniform or consistent for different subpopulations (e.g., males vs. females) in a particular culture. Particularly, in Asian countries, females could be more likely to conform to cultural norms and expectation than males, and hence are less likely to be involved in cyberbullying. It should be noted that this study was about gender difference in cyberbullying behaviors, but not about cultural difference in cyberbullying behaviors. So the findings did not suggest that Asian samples (or males) exhibited more cyberbullying behaviors than samples from other regions. In addition to cultural variations discussed above, our findings also showed that other conceptual and measurement factors (e.g., modality of cyberbullying, quality of research design) significantly moderated the magnitude of the relationship between gender and cyberbullying.

References

Abeele, M. V., & Cock, R. (2013). Cyberbullying by mobile phone among adolescents: The role of gender and peer group status. Communications, 38, 107-118. Barlett, C. P., & Gentile, D. A. (2012). Attacking others online: The formation of cyberbullying in late adolescence. Psychology of Popular Media Culture, 1, 123-135. Barlett, C. P., Gentile, D. A., Anderson, C. A., Suzuki, K., Sakamoto, A., Yamaoka, A., & Katsura, R. (2014). Cross-cultural differences in cyberbullying behavior: A short-term longitudinal study. Journal of Cross-Cultural Psychology, 45, 300-313. Beckman, L., Hagquist, C., & Hellström, L. (2012). Does the association with psychosomatic health problems differ between cyberbullying and traditional bullying? Educational & Behavioral Difficulties, 17, 421-434. Bergeron, N., & Schneider, B. H. (2005). Examining cross-national differences in peer-related aggression: A quantitative synthesis. Aggressive Behavior, 31, 116–137. Fan, X., & Chen, M. (2001). Parental involvement and students’ academic achievement: A meta-analysis. Educational Psychology Review, 13, 1-22. Griezel, L., Craven, R. G., Yeung, A. S., & Finger, L. R. (2008, December). The development of a multi-dimensional measure of cyberbullying. Paper presented at the Australian Association for Research in Education, Brisbane. Olweus, D. (2012). Comments on cyberbullying articles: A rejoinder. European Journal of Developmental Psychology, 9, 559-568. Smith, P. K., Mahdavi, J., Carvalho, M., Fisher, S., Russell, S., & Tippett, N. (2008). Cyberbullying: Its nature and impact in secondary school pupils. Journal of Child Psychology & Psychiatry, 49, 376-385. Wang, J., Iannotti, R. J., & Luk, J. W. (2012). Patterns of adolescent bullying behaviors: Physical, verbal, exclusion, rumor, and cyber. Journal of School Psychology, 50, 521-534.

Author Information

Xitao Fan (presenting / submitting)
University of Macau
Taipa
Shaojing Sun (presenting)
Fudan University (China)

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