A Meta-analysis on Gender and Cyber-victimization: Culture and Beyond

Author(s):

Xitao Fan(presenting / submitting)Shaojing Sun(presenting)

Conference:

ECER 2015

Network:

WERA Focal Meeting

Format:

Paper

Session Information

WERA SES 09 E, Integration of Technology and Education: International Perspectives on Pros and Cons

Paper Session

Time:

2015-09-10

11:00-12:30

Room:

334. [Main]

Chair:

Janna De Gouveia

Contribution

Introduction and Research Questions

Cyber-victimization (CV) and the related issues have been receiving increasing amount of attention in recent years. The concern for CV is not only on the complex nature and manifestations of this phenomenon, but also on the detrimental effects of CV on the well-being of the CV victims.

Gender difference, or lack thereof, in cyber-victimization has been a prominent issue in this research area. Research findings on gender differences in cyber-victimization, however, have been inconsistent. While many studies (e.g., Ackers, 2012; Craig et al., 2009) showed that females were more likely to experience cyber victimization than males, other studies (e.g., Huang & Chou, 2010; Popovic-Citic et al., 2011) suggested otherwise. Furthermore, some studies (e.g., Li, 2006) did not show statistically significant gender differences in cyber victimization, even though males were more likely to bully and cyberbully others than were females. These contradicting research findings point to potential issues pertaining to cultural differences, research design, context of study, and quality of measurement in the area of cyberbullying research. As Brown, Demaray, and Secord (2014) summarized, inconsistencies in gender differences may result from a variety of factors including, but not limited to, different samples, different cultural settings of study, different reference time periods in measurement, and different sampling methods.

Issues plaguing research on CV can be generally divided into conceptual, measurement, design and analysis ones. First and foremost are researchers’ and respondents’ understandings of key terms such as bullying or victimization. For instance, using a sample of secondary school students in Taiwan, Chen and Cheng (2013) compared two experimental conditions: providing a definition of bullying on the survey questionnaire versus not having such a definition. They did not find any statistically significant differences in prevalence rates of bullying and victimization between the respondents under these two conditions. The authors discussed that failure to detect a difference could be due to the overlap of respondents’ implicit definitions and researchers’ formal definition of bullying. The authors also called for further research on gender-based bullying and victimization across cultural-specific conditions. However, Smith et al. (2002) compared participants from 14 countries, and identified significant cultural differences in the meaning of the term bullying (e.g., in China vs. Italy). Adolescents of different age groups also varied in their understandings of the term.

The present study attempted to synthesize the prior research findings on the relationship between gender and cyber victimization. Specifically, the foci of this study were to address the following questions:

RQ1: What is the general gender group difference in cyber victimization as reported in the existing empirical studies?

RQ2: What are the study features and characteristics (e.g., culture, types of measurement) that could have partially explained the inconsistencies in the findings concerning the gender group differences in cyber victimization 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 searched 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 for the search included the following terms, as well as various combinations thereof, cyberbullying, cyberbully, electronic bullying, cyber victimization, Internet victimization, online bullying, online victimization, and Internet bullying. The search, covering articles published up to Oct. 01 of 2013, yielded a total of 1447 entries. Because the focus of the current study is on the relationship between gender and cyber victimization, we then examined the search entries for information on gender groups, and eliminated any that did not have such information. This filtering reduced our search results to 803 articles. We considered the following criteria while deciding whether to include an article for meta-analysis. First, the study must report empirical findings on the relationship between gender and cyber victimization. As such, those studies of qualitative nature were excluded. Second, we differentiated cyberbullying from cyber victimization. In other words, being a bully in cyberspace is different from being a target of cyberbullying, though these two phenomena could be related to each other. Our focus was on gender and victimization. Therefore, articles that only reported findings on cyberbullying but not cyber victimization were excluded. Third, we only included articles that provided sufficient information for us to obtain an effect size for gender difference in CV. 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 collection of 42 usable empirical research articles had a total of 152 effect sizes.

Expected Outcomes

Conclusion and Findings Of great interest is the finding that the Asian males were shown to be more likely to experience cyber-victimization than their female counterparts, while the opposite were reported for gender groups in North American and European samples. Such a finding echoes Popovic-Citic et al. (2011) argument that cultural difference may be an important factor in influencing victimization, and certain cultural norms might serve as explanatory factors about why females were less likely to experience cyber victimization in the region of Serbia. Costa, Terracciano, and McCrae’s (2001) view on pan-cultural and cross-cultural patterns of gender differences may help shed some light on the finding of our study. The former pattern means that certain gender difference is biologically based and is uniform across cultures, supporting an evolutionary perspective. The latter one, however, posits that gender difference in certain attribute could vary in terms of its magnitude and even direction across cultures. Furthermore, gender difference on certain variables (e.g., personalities) may be heightened in some cultures but be masked in others. Our finding lends support to the cross-cultural pattern of gender difference in cyber victimization. The discrepancy of gender difference between Asian and western regions may be related to masculinity, a dimension of culture (Hofstede, 1998). As Hofstede argued, gender difference is more likely to be delineated and accentuated in a masculine culture. In other words, in masculine cultures, being nurtured to deal with feelings may make females be more sensitive or susceptible to negative emotions, hurt, or victimization, both in physical and virtual world. In contrast, it may be the opposite in relatively feminine cultures (e.g., China). Our results also showed that other measurement factors (e.g., reporting time frame) significantly moderated the magnitude of the relationship between gender and cyberbullying.

References

References Ackers, M. J. (2012). Cyberbullying: Through the eyes of children and young people. Educational Psychology in Practice, 28, 141-157. Brown, C. F., Demaray, M. K., & Secord, S. M. (2014). Cyber victimization in middle school and relations to social emotional outcomes. Computers in Human Behavior, 35, 12-21. Chen, L., & Cheng, Y. (2013). Prevalence of school bullying among secondary students in Taiwan: Measurements with and without a specific definition of bullying. School Psychology International, 34, 707-720. Costa, P. T., Terracciano, A., & McCrae, R. R. (2001). Gender differences in personality traits across cultures: Robust and surprising findings. Journal of Personality & Social Psychology, 81, 322-331. Craig, W., Harel-Fisch, Y., Fogel-Grinvald, H., Dostaler, S., Hetland, J., Simons-Morton, B., & Pickett, P. (2009). A cross-national profile of bullying and victimization among adolescents in 40 countries. International Journal of Public Health, 54, 216–224. Fan, X., & Chen, M. (2001). Parental involvement and students’ academic achievement: A meta-analysis. Educational Psychology Review, 13, 1-22. Huang, Y., & Chou, C. (2010). An analysis of multiple factors of cyberbullying among junior high school students in Taiwan. Computers in Human Behavior, 26, 1581-1590. Li., Q. (2006). Cyberbullying in schools: A research of gender differences. School Psychology International, 27, 157-170. Popovic-Citic, B., Djuric, S., & Cvetkovic, V. (2011). The prevalence of cyberbullying among adolescents: A case study of middle schools in Serbia. School Psychology International, 32, 412-424. Smith, P. K., Cowie, H., Olafsson, R. F., Liefooghe, A. P., Almeida, A., Araki, H., et al. (2002). Definitions of bullying: A comparison of terms used, and age and gender differences, in a fourteen-country international comparison. Child Development, 73, 1119–1133.

Author Information

Xitao Fan (presenting / submitting)

University of Macau, Macau S.A.R. (China)

Shaojing Sun (presenting)

Fudan University, China

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