Sociocultural values, attitudes and risk factors associated with adolescent cyberbullying in East Asia: A systematic review



Cyberbullying amongst adolescents is a rapidly growing and alarming global phenomenon that can significantly harm their well-being. Studying cyberbullying in East Asia is especially important, where peer pressure based on collectivistic ideals and rigid cultural scripts for social interactions remain strong. Furthermore, the countries represented in this review are amongst the top globally for internet usage, suggesting that adolescents in East Asia are likely to be excessive users of social media communication and be more exposed to various forms of cyberbullying. This systematic review summarizes findings from peer-reviewed journal articles and book chapters on cyberbullying amongst adolescents between the ages of 10 and 19 in East Asian countries (N = 21). SCOPUS, Google Scholar, and PsycINFO databases were searched for relevant work published between 2008 and 2020. Search strategies involved using keywords related to cyberbullying, adolescents, East Asia, and the name of each country represented in the region (China, South Korea, Japan, Hong Kong and Taiwan). Key factors associated with cyberbullying specific to adolescents in this region are identified and discussed in this review, such as gender socialization patterns and literacy with digital media communication, emphasis on academic achievement and school factors, urban-rural digital divide, relationship with parents and teachers, and collectivistic values. The present review highlights the need to pay further attention to the sociocultural context in future cyberbullying research and calls for more context-specific cyberbullying prevention programs and awareness initiatives.

cyberbullying; East Asia; collectivistic values; gender socialization; academic performance; adolescents
Author biographies

Miriam Sang-Ah Park

Department of Psychology, Nottingham Trent University, Nottingham, United Kingdom

Miriam Sang-Ah Park is a Senior Lecturer in Psychology at Nottingham Trent University, UK. Dr. Park is a cross-cultural psychologist and has a keen interest in self and relationship processes across cultures.

Karen Jennifer Golden

Department of Psychology, Monash University Malaysia, Subang Jaya, Selangor Malaysia

Karen Jennifer Golden is a Senior Lecturer in Psychology at Monash University Malaysia and a clinical psychologist whose research and practice focus on children and young people’s mental health and more specifically, developmental disorders.

Samuel Vizcaino-Vickers

Department of Psychology, Nottingham Trent University, Nottingham, United Kingdom

Samuel Vizcaino-Vickers is a psychology student at Nottingham Trent University and is a student member and research assistant at the cross-cultural psychology lab at the university.

Dung Jidong

Department of Psychology, Nottingham Trent University, Nottingham, United Kingdom

Dung Jidong is a lecturer in Psychology at Nottingham Trent University, UK. Dr. Jidong’s primary research focus is cultural mental health.

Sanjana Raj

Department of Psychology, Monash University Malaysia, Subang Jaya, Selangor Malaysia

Sanjana Raj is currently enrolled in an MSc programme (Psychology) at Utrecht University, Netherlands, and was formerly working on her Honours (Psychology) at Monash University Malaysia at the time this review was conducted.


Studies included in the systematic review are identified by an asterisk.

Ang, R. P. (2015). Adolescent cyberbullying: A review of characteristics, prevention and intervention strategies. Aggression and Violent Behavior, 25(Part A), 35–42.

Baek, J., & Bullock, L. M. (2014). Cyberbullying: A cross-cultural perspective. Emotional and Behavioural Difficulties, 19(2), 226–238.

Barlett, C., & Coyne, S. M. (2014). A meta-analysis of sex differences in cyber-bullying behavior: The moderating role of age. Aggressive Behavior, 40(5), 474–488.

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(2), 300–313.

Bartolo, M. G., Palermiti, A. L., Servidio, R., Musso, P., & Costabile, A. (2019). Mediating processes in the relations of parental monitoring and school climate with cyberbullying: The role of moral disengagement. Europe's Journal of Psychology, 15(3), 568–594.

Beckman, L., Hagquist, C., & Hellström, L. (2012). Does the association with psychosomatic health problems differ between cyberbullying and traditional bullying? Emotional and Behavioural Difficulties, 17(3-4), 421–434.

Bottino, S. M. B., Bottino, C. M. C., Regina, C. G., Correia, A. V. L., & Ribeiro, W. S. (2015). Cyberbullying and adolescent mental health: Systematic review. Cadernos de Saúde Pública, 31(3), 463–475.

*Chang, F.-C., Chiu, C.-H., Miao, N.-F., Chen, P.-H., Lee, C.-M., Huang, T.-F., & Pan, Y.-C. (2015). Online gaming and risks predict cyberbullying perpetration and victimization in adolescents. International Journal of Public Health, 60(2), 257–266.

*Chang, F.-C., Lee, C.-M., Chiu, C.-H., Hsi, W.-Y., Huang, T.-F., & Pan, Y.-C. (2013). Relationships among cyberbullying, school bullying, and mental health in Taiwanese adolescents. Journal of School Health, 83(6), 454–462.

*Chang, F.-C., Miao, N.-F., Chiu, C.-H., Chen, P.-H., Lee, C.-M., Chiang, J.-T., & Chuang, H.-Y. (2016). Urban–rural differences in parental Internet mediation and adolescents’ Internet risks in Taiwan. Health, Risk & Society, 18(3–4), 188–204.

Charalampous, K., Ioannou, M., Georgiou, S., & Stavrinides, P. (2020). Cyberbullying, psychopathic traits, moral disengagement, and school climate: The role of self-reported psychopathic levels and gender. Educational Psychology. Advance online publication.

Cross, D., Barnes, A., Papageorgiou, A., Hadwen, K., Hearn, L., & Lester, L. (2015). A social-ecological framework for understanding and reducing cyberbullying behaviours. Aggression and Violent Behavior, 23, 109–117.

David-Ferdon, C., & Hertz, M. F. (2007). Electronic media, violence, and adolescents: An emerging public health problem. Journal of Adolescent Health, 41(Suppl. 6), S1–S5.

Farrall, K. (2012). Online collectivism, individualism and anonymity in East Asia. Surveillance & Society, 9(4), 424–440.

Fenaughty, J., & Harré, N. (2013). Factors associated with distressing electronic harassment and cyberbullying. Computers in Human Behavior, 29(3), 803–811.

Han, Y., Kim, H., Ma, J., Song, J., & Hong, H. (2019). Neighborhood predictors of bullying perpetration and victimization trajectories among South Korean adolescents. Journal of Community Psychology, 47(7), 1714–1732.

Hinduja, S., & Patchin, J. W. (2009). Cyberbullying fact sheet: A brief review of relevant legal and policy issues. Cyberbullying Research Center.

Holtz, P., & Appel, M. (2011). Internet use and video gaming predict problem behavior in early adolescence. Journal of Adolescence, 34(1), 49–58.

Hu, Q., Bernardo, A. B. I., Lam, S. W., & Cheang, P. K. (2018). Individualism-collectivism orientations and coping styles of cyberbullying victims in Chinese culture. Current Psychology, 37(1), 65–72.

*Huang, Y.-Y., & Chou, C. (2010). An analysis of multiple factors of cyberbullying among junior high school students in Taiwan. Computers in Human Behavior, 26(6), 1581–1590.

Inglehart, R., & Oyserman, D. (2004). Individualism, autonomy, self-expression: The human development syndrome. In Comparing cultures: Dimensions of culture in a comparative perspective (pp. 74–96). Brill.

Ji, L., Zhang, W., & Jones, K. (2016). Children’s experiences of and attitudes towards bullying and victimization: A cross-cultural comparison between China and England. In P. K. Smith, K. Kwak, & U. Toda (Eds.), School Bullying in Different Cultures, Eastern and Western Perspectives (pp. 153–169). Cambridge University Press.

Jung, J.-Y., Lin, W.-Y., & Kim, Y.-C. (2012). The dynamic relationship between East Asian adolescents’ use of the internet and their use of other media. New Media & Society, 14(6) 969–986.

*Jung, Y.-E., Leventhal, B., Kim, Y. S., Park, T. W., Lee, S.-H., Lee, M., Park, S. H., Yang, J.-C., Chung, Y.-C., Chung, S.-K., & Park, J.-I. (2014). Cyberbullying, problematic internet use, and psychopathologic symptoms among Korean youth. Yonsei Medical Journal, 55(3), 826–830.

Kiriakidis, S. P., & Kavoura, A. (2010). Cyberbullying: A review of the literature on harassment through the Internet and other electronic means. Family & Community Health, 33(2), 82–93.

Kirwil, L. (2009). Parental mediation of children's Internet use in different European countries. Journal of Children and Media, 3(4), 394–409.

Kowalski, R. M., Limber, S. P., & Agatston, P. W. (2012). Cyberbullying: Bullying in the Digital Age (2nd ed.). John Wiley & Sons.

Kowalski, R. M., Morgan, C. A., & Limber, S. P. (2012). Traditional bullying as a potential warning sign of cyberbullying. School Psychology International, 33(5), 505–519.

Låftman, S. B., Modin, B., & Östberg, V. (2013). Cyberbullying and subjective health: A large-scale study of students in Stockholm, Sweden. Children and Youth Services Review, 35(1), 112–119.

Lapidot-Lefler, N., & Barak, A. (2012). Effects of anonymity, invisibility, and lack of eye-contact on toxic online disinhibition. Computers in Human Behavior, 28(2), 434–443.

*Lee, C., & Shin, N. (2017). Prevalence of cyberbullying and predictors of cyberbullying perpetration amongst Korean adolescents. Computers in Human Behavior, 68, 352–358.

*Lee, J. Y., Kwon, Y., Yang, S., Park, S. Kim, E.-M., & Na, E.-Y. (2017). Differences in friendship networks and experiences of cyberbullying among Korean and Australian adolescents. Journal of Genetic Psychology, 178(1), 44–57.

Leung, A. N. M., Fung, D. C.-L., & Farver, J. M. (2018). A cyberbullying intervention for Hong Kong Chinese college students. Applied Research in Quality of Life, 13(4), 1037–1053.

Li, Q. (2007). New bottle but old wine: A research of cyberbullying in schools. Computers in Human Behavior, 23(4), 1777–1791.

*Li, Q. (2008). A cross-cultural comparison of adolescents' experience related to cyberbullying. Educational Research, 50(3), 223–234.

Microsoft. (2012). Online bullying WW among children 8–17.

Morales, M. (2011). Cyberbullying. Journal of Consumer Health on the Internet, 15(4), 406–419.

*Park, S., Na, E.-Y., & Kim, E.-M. (2014). The relationship between online activities, netiquette and cyberbullying. Children and Youth Services Review, 42, 74–81.

Patchin, J. W., & Hinduja, S. (2006). Bullies move beyond the schoolyard: A preliminary look at cyberbullying. Youth Violence and Juvenile Justice, 4(2), 148–169.

Patchin, J. W., & Hinduja, S. (2011). Traditional and nontraditional bullying among youth: A test of general strain theory. Youth & Society, 43(2), 727-751.

Patchin, J. W., & Hinduja, S. (2015). Measuring cyberbullying: Implications for research. Aggression and Violent Behavior, 23, 69–74.

Pettalia, J. L., Levin, E., & Dickinson, J. (2013). Cyberbullying: Eliciting harm without consequence. Computers in Human Behavior, 29(6), 2758–2765.

Piccoli, V., Carnaghi, A., Grassi, M., Straga, M., & Bianchi, M. (2020). Cyberbullying through the lens of social influence: Predicting cyberbullying perpetration from perceived peer-norm, cyberspace regulations and ingroup processes. Computers in Human Behavior, 102, 260–273.

*Rao, J., Wang, H., Pang, M. Yang, J., Zhang, J., Ye, Y., Chen, X., Wang, S., & Dong, X. (2019). Cyberbullying perpetration and victimisation amongst junior and senior high school students in Guangzhou, China. Injury Prevention, 25(1), 13–19.

Scheithauer, H., Smith, P. K., & Samara, M. (2016). Cultural issues in bullying and cyberbullying among children and adolescents: Methodological approaches for comparative research. International Journal of Developmental Science, 10(1-2), 3-8.

*Shin, N., & Ahn, H. (2015). Factors affecting adolescents’ involvement in cyberbullying: What divides the 20% from the 80%? Cyberpsychology, Behavior, and Social Networking, 18(7), 393–399.

Sittichai, R., & Smith, P. K. (2015). Bullying in South-East Asian countries: A review. Aggression and Violent Behavior, 23, 22–35.

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 and Psychiatry, 49(4), 376–385.

Thomas, H. J., Connor, J. P., & Scott, J. G. (2015). Integrating traditional bullying and cyberbullying: Challenges of definition and measurement in adolescents–A review. Educational Psychology Review, 27(1), 135–152.

*Udris, R. (2014). Cyberbullying among high school students in Japan: Development and validation of the Online Disinhibition Scale. Computers in Human Behavior, 41, 253–261.

*Udris, R. (2015). Cyberbullying in Japan: An exploratory study. International Journal of Cyber Society and Education, 8(2), 59–80.

Vandebosch, H., & Van Cleemput, K. (2009). Cyberbullying among youngsters: Profiles of bullies and victims. New Media & Society, 11(8), 1349–1371.

*Wang, C.-W., Musumari, P. M., Techasrivichien, T., Suguimoto, S. P., Tateyama, Y., Chan, C.-C., Ono-Kihara, M., Kihara, M., & Nakayama, T. (2019). Overlap of traditional bullying and cyberbullying and correlates of bullying amongst Taiwanese adolescents: A cross-sectional study. BMC Public Health, 19, Article 1756.

*Wong, D. S. W., Chan, H. C. O., & Cheng, C. H.-K. (2014). Cyberbullying perpetration and victimization among adolescents in Hong Kong. Children and Youth Services Review, 36, 133–140.

*Wright, M. F., Aoyama, I., Kamble, S. V., Li, Z., Soudi, S., Lei, L., & Shu, C. (2015). Peer attachment and cyber aggression involvement among Chinese, Indian, and Japanese adolescents. Societies, 5(2), 339–353.

*Yang, S. C., Lin, C.-Y., & Chen, A.-S. (2014). A study of Taiwanese teens' traditional and cyberbullying behaviors. Journal of Educational Computing Research, 50(4), 525–552.

*Yang, S.-J., Stewart, R., Kim, J.-M., Kim, S.-W., Shin, I.-S., Dewey, M. E., Maskey, S., & Yoon, J.-S. (2013). Differences in predictors of traditional and cyber-bullying: A 2-year longitudinal study in Korean school children. European Child & Adolescent Psychiatry, 22(5), 309–318.

*Yang, X., Wang, Z., Chen, H., & Liu, D. (2018). Cyberbullying perpetration among Chinese adolescents: The role of interparental conflict, moral disengagement, and moral identity. Children and Youth Services Review, 86, 256–263.

*You, S., & Lim, S. A. (2016). Longitudinal predictors of cyberbullying perpetration: Evidence from Korean middle school students. Personality and Individual Differences, 89, 172–176.

*Zhou, Z., Tang, H., Tian, Y., Wei, H., Zhang, F., & Morrison, C. M. (2013). Cyberbullying and its risk factors among Chinese high school students. School Psychology International, 34(6), 630–647.

Additional information

Editorial record

First submission received:
February 10, 2019

Revisions received:
December 30, 2019
August 13, 2020
November 20, 2020
December 12, 2020

Accepted for publication:
December 18, 2020

Editor in charge:
Michel Walrave

Full text


Amongst adolescents, cyberbullying is a prominent form of cybercrime that has gained attention for being a significant and growing public health issue, as well as for its association with other delinquent or criminal behaviors (e.g., Beckman et al., 2012; Låftman et al., 2013; Smith et al., 2008). Cyberbullying has been found to have a major negative impact on adolescent health, leading to serious psychological, social, and physical problems such as isolation, depression, and stress (Kiriakidis & Kavoura, 2010; Låftman et al., 2013). The range of issues associated with cyberbullying involves and affects not only victims but also bullies/perpetrators, bully/perpetrator-victims (those who are both perpetrators and victims of cyberbullying), and bystanders (Baek & Bullock, 2014). For instance, higher levels of depressive mood were found in victims, bullies, and bully-victims of cyberbullying (Chang et al., 2013). Researchers have argued that this form of bullying can lead to more severe consequences than traditional bullying given the ubiquitous nature of online interactions (Beckman et al., 2012; Kowalski, Morgan et al., 2012). Indeed, the uniqueness of cyberbullying stems from the technological aspect that eliminates geographical limits, further facilitated by convenience, anonymity, and publicity (Lapidot-Lefler & Barak, 2012; Morales, 2011; Thomas et al., 2015).  

Cyberbullying in East Asia

This systematic review examined sociocultural values, attitudes, and risk factors for cyberbullying amongst adolescents in East Asia, namely China (including Hong Kong), South Korea, Japan, and Taiwan, aiming to discuss how these factors work within the framework of the East Asian context. Only a few studies have pointed out the importance of examining cultural characteristics and their impact on cyberbullying behaviors in developing effective prevention and intervention programmes around the world (Baek & Bullock, 2014; Bottino et al., 2015). Cross et al. (2015) argued that a framework that allows for a contextual perspective and further examination of the interpersonal and social, normative processes in research could lead to better understanding and reduction of cyberbullying behaviors. However, as cyberbullying is a relatively recent phenomenon, research on the topic is growing but limited in non-Western contexts. Even in the instances where research is conducted in non-Western or non-English speaking parts of the world, conceptualizations and measurements are often ‘borrowed’ rather than developed with different contexts in mind (Scheithauer et al., 2016).

Examining cyberbullying in East Asia is especially important, for these countries are amongst the top globally for internet usage (Wright et al., 2015). While the inclusion of countries for East Asia differs slightly from one study to another, there is a consensus that these countries share core similarities such as languages based on Chinese characters and cultural aspects relating to Confucianism and Buddhism (Farrall, 2012). Moreover, these East Asian countries share other common socio-political factors that link them together. These factors include national policies promoting active usage of the latest communication technologies and high levels of various types of internet connectedness in adolescents such as communication, research participation and information sharing (J.-Y. Jung et al., 2012). Adolescents in East Asia might be more exposed to cyberbullying due to increased internet usage, and indeed, Leung et al. (2018) suggested that prevalence rates for cyberbullying are certainly higher in East Asia. Furthermore, Microsoft (2012) also reported that in countries like China, the prevalence rate for bullying was higher online than offline. However, the exponential growth and development of online communication in these East Asian countries has not been matched with extensive research within the region.

The similarity in cultural values in the Confucian(-influenced) societies of East Asia has often been noted and discussed compared to Western cultures, where these values lead to group-focused as opposed to self-focused views and behaviors (Inglehart & Oyserman, 2004). Collectivistic and interdependent values place a strong emphasis on maintaining group relations, social conformity and avoiding interpersonal conflict. These emphasized values in East Asian cultures can influence cyberbullying behaviors in this region specifically. For instance, Ji et al. (2016) proposed that strong social norms in collectivistic cultures such as China can lead to lower tolerance for deviant behaviors amongst group members, resulting in lower involvement in bullying in these countries. On the other hand, strong social norms and collectivistic values can lead to more acquiescence and conformity in these cultures, and one may suspect that the prevalence and severity of cyberbullying behaviors are higher in this region (see Han et al., 2019). Also, there might be unique contributing factors for bullying specific to East Asian adolescents, who may be more likely to cyberbully others as a way of conforming to the group norm or for penalising someone who does not adhere to such collectivistic ideals.

Furthermore, it is worth noting that gender socialization experience, parent-child relationships, and cultural norms in East Asia tend to differ from the West. These factors have been implicated to influence cyberbullying amongst adolescents in this region, and have also been known to vary somewhat even amongst the countries (Barlett et al., 2014; Hu et al., 2018; Huang & Chou, 2010; Kirwil, 2009). For instance, East Asian culture places a stronger emphasis on socializing males to be assertive and aggressive, which could lead to more males involved in cyberbullying. Additionally, more restrictive communication in parent-child relationships in East Asian culture could lead to less cyberbullying reporting and mediation, as opposed to other cultures where parent-child communication may be more open and non-hierarchical.

Cyberbullying: Definition and Implications

Cyberbullying has been defined by Patchin and Hinduja (2006, p. 152) as any “wilful and repeated harm inflicted through computers, cell phones, and other electronic devices”. However, a lack of an established definition of cyberbullying has been noted, partially due to the complexity of defining different types of bullying behaviors and involved parties online (Beckman et al., 2012). Some authors argue on the repetition aspect of the definition for cyberbullying, as online contents can be viewed and shared repeatedly (Piccoli et al., 2020; Udris, 2014). Some scholars also highlighted the need to address the power imbalance between the victim and the perpetrator in cyberbullying (Fenaughty & Harre, 2013). Patchin and Hinduja (2015) later expanded on their own definition by including an imbalance of power as a key element and characteristic of cyberbullying. This addition is important to note considering the dynamics of peer relationships and perpetrator/victim characteristics. Furthermore, Piccoli et al. (2020) also suggested that the imbalance can result from the discrepancy between users’ technical abilities as those who are more apt at using online platforms and communication channels have advantages over those who may not. Overall, research on cyberbullying has examined a variety of processes and characteristics, including risk factors related to perpetration and victimization, gender differences, reporting frequency, coping styles, and the negative consequences of cyberbullying. The aim of the present review was to explore some selected processes and characteristics of cyberbullying such as perpetrators’ demographics and factors associated with cyberbullying perpetration in light of the unique sociocultural factors that have been illustrated in studies of adolescent cyberbullying in East Asia.


The following databases were used to identify the relevant articles: Google Scholar, Scopus and PsycInfo. Figure 1 below summarizes the review process in a flowchart diagram. Search keywords such as “cyberbullying”, “online bullying” and “online aggression” were entered separately and also in combinations with further specifying words/criteria such as “adolescents”, “youth”, “East Asia” and also each of the country’s names with the addition of Hong Kong as a territory with a degree of autonomy. Table 1 includes the full list of keywords used in the search. A total of 472 articles were identified. Only studies published from January 2008 to January 2020 and written/published in the English language were used. Studies with participants between the ages of 10 and 19 were included. Studies were only included if they consisted of Asian participants living in East Asia either as the only sample or in comparison with other samples (other Asian or Western samples). Only studies that specifically discussed cyberbullying either as the sole focus of the paper or in comparison with traditional bullying involving offline behaviors were included.

Reviews and theoretical essays without original research were excluded.  After reviewing the abstracts, 395 studies were excluded for not meeting the inclusion criteria. For instance, some of these articles were excluded as they were: studies with samples that were non-Asian or Asian immigrants, studies with participants older than 19, or studies that focused on other cyber-behaviors and not cyberbullying. 45 articles remained after excluding duplicate articles from different databases, and 21 articles were selected for the final review and discussion. The other 24 articles were excluded for not meeting sample inclusion criteria or not discussing cyberbullying as a key variable in the study. 

From the studies that were identified as eligible, the following information was extracted: the authors, definition of cyberbullying, demographic characteristics of participants (age/grade, sex, and region), the design of the study, the materials and statistical analyses that were used and the key findings of the study.  Table 2 summarizes the key information from the studies included in the review.

Figure 1. Flow Diagram of Literature Search and Inclusion/Exclusion Process.


Table 1. Search Keywords for the Systematic Review.


Cyberbullying-related Terms

Age group/Population

“East Asia”



“South Korea”




“Online bullying”



“Online aggression”


Hong Kong


“School-age children”


Table 2. Characteristics of Reviewed Studies on Adolescent Cyberbullying in Asia.

Country & Region

Definition of Cyberbullying





Sociocultural Findings

Chang et al. (2013)







Bullying or harassment through the Internet, cell phones or other electronic devices (David-Ferdon & Hertz, 2007)

N = 2,992 10th grade high school students in Taipei. 52% males 

Cross-sectional survey

Survey measuring cyberbullying, cybervictimization, school bullying, school victimization, demographic characteristics including sex, academic performance and Internet risk behavior. Rosenberg Self-esteem Scale. Center for Epidemiological Studies- Depression Scale

Logistic Regression

34% involvement in cyberbullying (bullies, bully-victims and victims). Higher perpetration (7.0%) and victimisation (16.3%) amongst males than perpetration (4.5%) and victimization (5.8%) amongst females. High unwanted sexual solicitation reported. Lower academic students more likely to be bully-victims.

Chang et al. (2015)








N = 2,315 10th grade (11th grade at follow up) students. 51% males.

Longitudinal survey

Survey with questions on cyberbullying perpetration and victimization, traditional bullying perpetration and victimization, game and Internet use, exposure to media violence, risky Internet use, cyberbullying resistance efficacy and demographics

Multiple logistic regression

Males more likely to be cyberbullying perpetrators and victims than females. Females more likely to cease cyberbullying. Making rude comments online most prevalent form of bullying behavior.

Chang et al. (2016)








N = 1,576 participants from Yilan county (rural) and 1767 participants from Taipei (urban). Both parents and adolescents.

Cross-sectional survey

Survey measuring use of Internet, risky Internet behaviors, Internet skills, parental mediation, Internet harm (including cyberbullying) and demographics

Chi-square statistics, T-tests and multiple regression analyses

Urban adolescents experienced less cybercrime than rural adolescents but more cyberbullying. Parental mediation negatively correlated with cyberbullying victimisation.

Y.-E. Jung et al. (2014)






South Korea

Intentional and repeated harm inflicted through the use of electronic devices

N = 4,531 students from South Korea (11-14 years). 51.5% males

Cross-sectional survey

Survey with cyberbullying, problematic internet use and psychopathologic symptoms

Chi-square test, t-test and ANOVA

9.7% involved in cyberbullying: 3.3% were only victims; 3.4% were only perpetrators; 3.0% were victim-perpetrators. Significantly more males were involved in cyberbullying and the youths involved in cyberbullying had significantly more psychopathologic symptoms

Huang & Chou (2010)








N = 545 (7th to 9th grade) students from northern and southern Taiwan. 47.1% males.

Cross-sectional survey

Survey with demographics and cyberbullying experience questions as bullies, victims and bystanders

Correlations, T-test and ANOVA

34.9% reported cyberbullying victimization, 20.4% perpetration and 63.4% reported bystander experiences. Being threatened and being made fun of most prominent behaviors. Males had higher bystander, victim and bullying experiences than females. Bystanders showed indifference towards cyberbullying and were least likely to take action. All groups were more likely to tell parents than teachers.

C. Lee & Shin (2017)






South Korea

Intentional acts to intrigue or harass someone using email, chat services, SNS, or other electronic communication media (Patchin & Hinduja, 2011)

N = 4,000 Korean adolescents (54.1% males).

Cross-sectional survey

Survey with demographics, cyberbullying experience, application (SNS, online games) use, empathy, parental attachment, satisfaction with school life and offline violence

Logical regression to determine the predictors of cyberbullying perpetration

Approximately 1/3 involved in cyberbullying as bully (6.3%), victim (14.6%), or bully/victim (13.1%). Boys, and those with high time spent on SNS, experience of being cyberbullied, and offline bullying perpetration were more likely to be involved in cyberbullying perpetration.

J. Y. Lee et al. (2017)






Cross-cultural study on South Korea (East Asia) and Australia

Wilful and repeated harm inflicted through the use of computers, mobile phones and other electronic devices (Hinduja & Patchin, 2009)

N = 520 Korean adolescents (51.2 % males) and N = 401 Australian adolescents (48.9% males) aged 12-15 living in major cities

Cross-sectional survey

Survey on cyberbullying and bullying, size of friendship networks and demographics

Chi-square comparisons by gender and age, correlations and logistic regression

40.6% of Australians and 30.2% of Koreans have engaged in cyberbullying behaviors. Twice as many Australians have experienced victimisation compared to Koreans. Gender difference only observed in Australian adolescents with victimization and witnessing online.

Li (2008)






Cross-cultural study on China (East Asia) and Canada (North America)

The use of electronic communication devices to bully others

N = 157 (45% male) Canadian students and = 197 (54% male) Chinese students (12-15 years old).

Cross-sectional survey.

Survey with question on cyberbullying, reporting to school and beliefs on intervention

Chi-squared analyses and descriptives

More Canadian students than Chinese students reported cyberbullying perpetration. No differences in victimisation. More Chinese students (bystanders and victims) chose to tell adults in schools and believed that they would intervene and could resolve the situation.

Park et al. (2014)






South Korea


N = 1,200 adolescents (12-15 years old). 51.3% males.

Cross-sectional survey

Structured interview with questions on traditional bullying, cyberbullying, netiquette, Internet use, communication with parents and demographics

Regression analyses, and correlations

20.4% cyberbullies, 25.8% victims and 35.2% bystanders. No gender differences found. Frequent communication with parents negatively correlated with cyberbullying involvement. Urban youth more involved in cyberbullying.

Rao et al. (2019)







Repeated, intentional act done with the purpose of harming another person through technologies such as email, text messaging, SNS and instant messaging; Can be carried out by a group or an individual

N = 2,590 adolescents (average age = 14.1). 59.7% male.

Cross-sectional survey

Survey with demographics, experiences of cyberbullying perpetration and victimization and coping strategies

Multinomial logistic regression

28% cyberbullies, 44.5% victims within the past 6 months. Males more likely to be perpetrator, victim and perpetrator-victim. Males with lower academic achievement, higher hours spent online and experiencing physical discipline from parents more likely to be both perpetrator and victim.

Shin & Ahn (2015)






South Korea


N = 1,036 students (45.6% males) in middle and high schools in Seoul (average age = 15.2).

Cross-sectional survey

Survey with demographics, time spent on media, media activities, digital literacy, school satisfaction, cyber-confidence & cyberbullying experience

Stepwise logistic regression

Younger students who spend more time playing games (on weekdays), with high confidence in cyberspace and active in using mobile phones are more likely to be involved in cyberbullying.

Udris (2014)








N = 887 senior high school students (average age = 16.3; 42.6% males).

Cross-sectional survey

Survey with demographics, online disinhibition, and cyberbullying experience

Logistic regression

Online disinhibition significantly predicted cyberbullying perpetration.

Udris (2015)







Harmful behavior that is intentional and repetitive, and involves the use of ICTs

N = 899 high school students aged between 15 and 19 (42.6% males)

Cross-sectional survey

Survey with cyberbullying activities (past and in the last six months), technology use and demographics

Logistic regression

Phone use in class, internet importance, number of online friends and experience of cybervictimization in the past six months significantly predicted cyberbullying perpetration.

Wang et al. (2019)







Bullying and harassment of others by means of new electronic technologies

N = 2,028 high-school students (10th-11th grade students)

Cross-sectional survey

Survey with demographics, questions on traditional bullying and cyberbullying, academic performance and school climate, internet usage and addiction, and psychological symptoms

Logistic regression

Significant associations between adolescents who were bullies and alcohol use, negative school climate. 48.7% of those involved in cyberbullying were also involved in traditional bullying.

Wong et al. (2014)






Hong Kong


N = 1,917 6th- 8th grade students. 12-15 years old, M = 13.46. 54.6% males.

Cross-sectional survey

Survey with questions on self-efficacy, empathy, feelings towards school, psychosocial conditions and demographics, cyberbullying and traditional bullying perpetration and victimization, reaction to cyberbullying


More males reported cyberbullying perpetration (16%) than females (14.8%). More males also reported more victimisation (13.4%) than females (12.8%). Most prevalent types of cyberbullying behavior were being teased or insulted in online social groups or forums and having photos or videos uploaded to the Internet without consent.

Wright et al. (2015)






Cross-cultural study on China, Japan and India (South Asia)


N = 683 students from China, 480 from India, 474 from Japan. 11-15 years old. 51.7% males.

Cross-sectional, cross-cultural survey (China, India and Japan).

Survey with questions on individualism and collectivism, traditional aggression, cyber aggression, peer attachment and demographics


Indian adolescents more individualistic, exhibited the most perpetration and victimisation followed by China and then Japan. More males than females in India and China reported involvement. No gender differences in Japan.  Peer attachment in all countries negatively correlated with cyber aggression involvement.

S.-J. Yang et al. (2013)






South Korea


N = 1,344 4th grade students (aged 10) assessed with parents in Kwangju.  Follow-up two years later. 603 males and 584 females at baseline. 481 males and 467 females at follow-up

Longitudinal survey

Survey with Peer-Victimization Scale, Bullying Behavior Scale, cyberbullying perpetration and victimization items, Children’s Depression Inventory, State-Trait Anxiety Inventory, Self-Esteem Inventory, Ways of Stress Coping Checklist, Strengths and Difficulties Questionnaire, DuPaul’s ADHD Rating Scale, General Health Questionnaire and Demographics

Logistic Regression

At follow-up, 11.1% reported cyberbullying perpetration, 5.4% victimization and 5.1% bully-victims. Lower academic performance associated with perpetration and victimization. 

S. C. Yang et al. (2014)








N = 837 5th- 12th grade students in Southern Taiwan. 52% males.

Cross-sectional survey

Bullying Behaviors Scale (measures both traditional bullying and cyberbullying) and demographics

Correlations, T-tests and ANOVA

Sending nasty messages, ignoring someone’s posting and harassment most prevalent forms of bullying behavior. Sexual cyberbullying not as common, but seen as one of the least serious.  Males more likely to be bullies, victims and bystanders than females.

X. Yang et al. (2018)







Aggression intentionally and repeatedly carried out in an electronic context against a person who cannot easily defend him/herself (Kowalski, Limber et al., 2012)

N = 649 high school students (aged 11-19 years) in China. 52% males.

Cross-sectional survey

E-bullying Scale for adolescents, interparental conflicts, moral disengagement and moral identity

Multiple mediation model & moderated mediation model using SPSS and the macro PROCESS

Cyberbullying perpetration had a significant positive
correlation with gender, time spent online and moral disengagement; interparental conflict had a significant effect through moral disengagement (positively).

You & Lim (2016)






South Korea

Invasion of private information, insulting language use, multiple types of threats, rumours and abuse

N = 3,449 students aged 12-14 (50% male)

Longitudinal survey

Survey with cyberbullying perpetration and offline bullying/victim experience and psychological predictors such as self-esteem and sociality

Logistic regression models

Students in the cyberbullying group had higher levels of daily internet use, previous offline bullying experience. Lack of self-control and high level of aggression linked to more cyberbullying.

Zhou et al. (2013)







Intentional, repeated and aggressive act/behavior carried out by a group or individual instrumentally employing ICT

N = 1,438 grades 10-12 students from central China (57.4% male)

Cross-sectional survey

Survey with cyberbullying inventory, traditional bullying scale, demographics, Internet usage, motivation for cyberbullying and parent and teachers’ supervision of Internet usage

Correlations, ANOVA, T-tests and Chi-square analyses

34.9% reported cyberbullying perpetration and 56.9% reported victimization. Kicking someone out of a chat room most prevalent form of cyberbullying behavior. Males (39.6%) more likely to be perpetrators than females. (28.3%). Males (59.8%) also more likely to be victims than females (52.9%). Students with low academic achievement more likely to be perpetrators. 45.8% of victims ignore/do not react. Participants who report talking to someone for help choose to talk to friends/classmates (65.6%), followed by parents (28.9%) and siblings (27.8%) and then to teachers (2.8%).

Results and Discussion

Prevalence of Cyberbullying

Amongst the studies included in the review, the prevalence rates of cyberbullying victimization varied from 5.4% in South Korea (S.-J. Yang et al., 2013) to 20.4% in Taiwan (Huang & Chou, 2010), which was twice the prevalence rate for traditional bullying (Chang et al., 2013) to 56.8% in China (Zhou et al., 2013). The range of results as can be viewed in Table 2 indicates that it would be difficult to measure overall prevalence rates in a consistent manner, even within the same country given the differences in the conceptualization and measurement of cyberbullying. Furthermore, the varied sample sizes and methods used to investigate cyberbullying prevalence make it even tougher to estimate the prevalence accurately. However, they do serve to illustrate the severity of the problem amongst adolescents in Asia and point to the need for further examination.

The reviewed studies suggest that there seem to be culturally specific factors that shape views and behaviors relating to cyberbullying in East Asia. Two of the reviewed cross-cultural studies comparing cyberbullying perpetration found East Asian adolescents to report lower incidences of bullying behavior compared to their Western counterparts (J. Y. Lee et al., 2017; Li, 2008). Such findings could further support the argument that higher endorsement of collectivism and stronger interdependent self-construal amongst Asians may serve as a protective factor for cyberbullying (Barlett et al., 2014). However, this could also be due to cultural differences in what is viewed as cyberbullying and requires further examination. For example, Wang et al. (2019) noted that there can be sociocultural differences in perceptions of what constitutes bullying, with some societies and cultures applying a more lenient view than others. S. C. Yang et al. (2014) found that in Taiwan, certain sexual bullying behaviors online were rarely perceived as harmful, but instead as something playful that should not be taken too seriously.

Media/Digital Communication Factors and Related Individual Differences

Being insulted or kicked out of chat rooms has been implicated as the most prevalent form of cyberbullying behaviors in some of the reviewed studies (Chang et al., 2015; Wong et al., 2014; Zhou et al., 2013). Several variations exist of cyberbullying behaviors that are also dependent on the most popular technological tool used. For example, Huang and Chou (2010) revealed chat rooms to be the most popular online communication medium used in Taiwan. The reasons behind the popularity of certain communication media over others as well as specific bullying behaviors have not been sufficiently explored in past research but would be of great relevance in formulating prevention programs. Cyber-confidence and attitudes toward specific behaviors tended also to be associated with bullies. Shin and Ahn (2015) found that self-confidence in cyberspace in general seemed to be associated with cyberbullying involvement in their South Korean study, where those who were more self-confident in expressing themselves and navigating through the cyberspace were more likely to be bullies.

Time spent online seems to be positively associated with cyberbullying perpetration.  X. Yang et al.’s (2018) study of Chinese adolescents found that adolescents who spent more time online were more prone to engage in cyberbullying behaviors. Similarly, C. Lee and Shin (2017) attributed higher rates of ownership as well as frequent use of smartphones and applications/social media platforms amongst South Korean adolescents as the major cause/source of cyberbullying. C. Lee and Shin (2017) also attributed online disinhibition and anonymity to be the main causes of cyberbullying. Additionally, they also found a relatively large percentage of their participants (13.1%) to be both bullies and victims, which suggests that there could be a high rate of retaliation amongst those who experience cyberbullying as victims.

Gender Differences in Cyberbullying Perpetration

Gender differences were a focus of examination for several of the reviewed studies. The broader literature across the globe, particularly studies conducted in Western contexts, have produced contradictory results regarding gender, with some showing no gender differences and others larger participation for females in cyberbullying (Låftman et al., 2013; Li, 2007; Pettalia et al., 2013; Vandebosch & Van Cleemput, 2009).  However, the reviewed studies suggest a strong leaning towards male involvement in all aspects of the cyberbullying experience.  Majority of the reviewed studies conducted in East Asia reported higher rates of cyberbullying perpetration and victimization amongst males than females (e.g., Chang et al., 2015; Huang & Chou, 2010; C. Lee & Shin, 2017; Rao et al., 2019; Wong et al., 2014; S.-J. Yang et al., 2013; Zhou et al., 2013).   Huang and Chou (2010) further highlighted that bystander experiences were also more common amongst males, suggesting that males were more likely to be involved in all aspects of cyberbullying than females. However, three of these studies also noted that gender differences amongst cybervictims were either absent or weaker than the differences observed between the perpetrators (Chang et al., 2015; Zhou et al., 2013).  Additionally, it was discovered in one study that females were more likely to stop cyberbullying perpetration than males were (Chang et al., 2015). Another important gender difference noted in cyberbullying behavior was the higher likelihood of males retaliating with cyberbullying when they were victimized (Wong et al., 2014).

Explanations regarding the higher rates amongst males have focused on cultural contexts that encourage aggression in males and more docile behavior in females, thereby making cyberbullying a more acceptable behavior for young males (Chang et al., 2013).  Y.-E. Jung et al. (2014) also found that the perpetrator group is associated with rule-breaking and aggressive behaviors, which one may note to be exhibited by males. Furthermore, boys are encouraged to be brave and aggressive towards other boys and not girls, which may explain why girls are less likely to become cybervictims as well (Zhou et al., 2013). A consequence may be limited exposure to the cyberscape, reducing their risks of getting involved in cyberbullying.  Barlett and Coyne (2014) have also suggested that gender and age can have an interactional effect, where males showed higher levels of cyberbullying in later adolescence compared to females. The findings suggested that further exploration is needed in the relationship between gender and cyberbullying involvement and studying how the interactions of the two might differ across countries. Factors such as online behaviors (including preferred online media) and differential access to the Internet for different genders could all be contributing to gender differences in cyberbullying and should be examined further. Moreover, further attention should be paid to individuals who are gender non-conforming in East Asia, especially as they may be seen to violate social norms and thus more likely to be victimised.

Academic Achievement and Other School-Related Factors

Certain risk factors for cyberbullying perpetration and victimization such as involvement in traditional bullying, risky internet behaviors and maladaptive interpersonal relationships have been commonly discussed throughout literature (e.g., Ang, 2015; Bottino et al., 2015; Kiriakidis & Kavoura, 2010).  However, some of the risk factors may be more uniquely significant or may be explained by the cultural background. An example of such a factor is academic performance, which holds greater significance in Asian countries. Three of the reviewed studies implicated academic achievement as a factor relevant to perpetration as well as victimization (Chang et al., 2013; S.-J. Yang et al., 2013; Zhou et al., 2013).  Chang et al.’s (2013) results highlighted lower academic performance to have a significant correlation with students who were cyberbully-victims. Lower academic performance has also been associated with adolescents more likely to be perpetrators and not victims (Zhou et al., 2013).  Furthermore, S.-J. Yang et al.’s (2013) longitudinal study with Korean school children indicated a relationship between lower academic performance and cyberbullying perpetration as well as victimization.

Academic achievement could also be a signifier of social acceptance and status in peer groups in the East Asian countries. Therefore, those adolescents with lower academic achievement might be likely to be victimized because they lack social status. Simultaneously, they could be more likely to become perpetrators as they might seek different avenues to validate themselves. Furthermore, the internet offers a means of escape for both groups of people and just engaging more with the internet would increase their risks of perpetration and victimization (S.-J. Yang et al., 2013).  Huang and Chou (2010) discussed the relationship between cyberbullying and academic achievement and the differences in Western and non-Western contexts. In the former, high academic achievement is likely to correlate with lower social acceptance and higher victimization, which contrasts with Asian countries where academic achievement is highly valued. These results call for further research that explores adolescents’ relationships and attitudes towards academic achievement and the impact of these on cyberbullying and how these might vary across countries.

In parallel with this, other school-related factors may have a more significant impact on East Asian adolescents. For instance, Wong et al. (2014) found participants’ sense of belonging to the school to have an important predictive effect on cyberbullying perpetration; poorer sense of belonging was associated with the likelihood of engaging in cyberbullying behaviors. Research often has found a negative and significant link between school climate and cyberbullying perpetration (e.g., Bartolo et al., 2019; Charalampous et al., 2020; Wang et al., 2019). Negative school culture, including perceptions of school harmony and perceived belonging, seems to have a close link with both perpetration and victimization and requires further research attention. The mediating role of school climate in the relationship between personality traits (e.g., psychopathy) and cyberbullying has also been highlighted (see Charalampous et al., 2020). The effect of school climate on cyberbullying may be even more pronounced in the Asian context where group belonging and harmony are valued.

Urban-Rural Digital Divide

Another sociocultural factor that emerged in the review is the urban-rural digital divide (Chang et al., 2016; Park et al., 2014). Studies have shown that urban students experience more cyberbullying perpetration and victimization (Chang et al., 2016; Park et al., 2014). Although these findings can be attributed to more exposure to the Internet, it would be interesting to explore whether characteristics associated with rural communities such as closer ties in the community have an essential role to play. Chang et al. (2016) looked at cyberbullying in Taiwan along with other types of cybercrime victimization such as having passwords or money stolen online. Their results suggested total higher cybercrime victimization for rural adolescents but cyberbullying on its own was more common amongst urban adolescents. These findings warrant further research to assess how community factors and internet penetration and literacy interact in the cyberbullying process. Another important way the urban-rural digital divide may impact cyberbullying prevalence is via lack of parental mediation and lower internet skills (Chang et al., 2016). Analysis of the interactions of different factors highlighted that parental mediation had a stronger relationship with cyberbullying than whether the person was urban/rural, and when the two were examined together, parental mediation rendered the urban/rural differences insignificant. However, parental mediation remains strongly influenced by urban/rural differences and therefore the impact of the urban-rural digital divide possibly works indirectly through parental mediation on cyberbullying victimization. Conclusively, internet competence and literacy have become important issues for consideration and regional and community differences need to be integrated into preventive approaches that will involve parents as well.

Reporting Cyberbullying and Relationships With Authority/Adults

There seems to be contrasting evidence as to whether adolescents in East Asia found it important to report cyberbullying or to take direct action against cyberbullying behaviors as observers. Some of the reviewed studies found choosing not to report instances of cyberbullying or ignoring it to be relatively common in their participants (Chang et al., 2013; Huang & Chou, 2010; Zhou et al., 2013). Reluctance to make a report or take action against cyberbullying on the part of both victims and school administrations has been associated with Taiwanese values based on Confucianism that emphasize interpersonal harmony, lack of conflict and tolerance amongst students (Chang et al., 2013; Huang & Chou, 2010).  Huang and Chou (2010) noted that bystanders were particularly indifferent to reporting cyberbullying and were disinclined to get involved. Zhou et al. (2013) found that Chinese adolescents were more likely to talk to their friends about cyberbullying and least likely to talk to their teachers. Importantly, the lack of reporting to maintain social relations may serve as an impediment in tackling the problem of cyberbullying (Huang & Chou, 2010).

On the other hand, Li’s (2008) study found that Chinese students were more likely to have faith that their teachers could resolve the situation, and therefore were more likely to tell an adult about the situation than Canadian students were. These cultural differences were attributed to the Chinese culture, whereby teachers and students have traditional relationships based on principles of authority and obedience that resemble the relationships between parents and children (Li, 2008). The differences in the results obtained by Li (2008) and Zhou et al. (2013) may suggest that changes could be taking place in this regard, however, and further research is required to expand these findings.

Parent-child communication has been identified as vital to reducing the risks of cyberbullying in several parts of the world (Chang et al., 2015; Holtz & Appel, 2011). The findings above indicate how strongly the dynamics of the relationships between adolescents and their parents and teachers can affect how situations are dealt with. Prevention initiatives and media literacy programs that inform on the risks of cyberbullying in East Asia should be built on the foundations of the communication style preferred by adolescents in the region for them to be truly effective.

Collectivistic Values and Related Cultural Factors

Studies have highlighted the possible protective impact that collectivistic values can have on cyberbullying, often by way of strengthening social ties, especially in reducing cyberbullying involvement and influencing coping from cyberbullying (Park et al., 2014).  Wright et al.’s (2015) cross-cultural study compared cyberbullying amongst Chinese, Japanese and Indian adolescents as well as their leanings towards individualistic and collectivistic attitudes. Their study found that the greatest peer attachment was reported amongst those who were uninvolved in cyberbullying, and bully-victims had the lowest levels of peer attachment. Their study highlighted that cyberbullying perpetration and victimisation were high when peer attachment was low and the level of individualism high. The opposite was also true with the interaction of higher levels of peer attachment and high levels of collectivism predicting lower levels of cyberbullying involvement. Future research could look at whether an emphasis on certain collectivistic values that reduce the risks of involvement in cyberbullying can be integrated into prevention and treatment programs.

Other cultural aspects of collectivism seem to have an impact on involvement in cyberbullying in East Asian adolescents. Udris’ (2014) Japanese study, for instance, found that minimisation of authority/rules was found to be a significant predictor of cyberbullying in his research. Considering the strong social norms and conformity in Japan, these results are not surprising, and may explain the particular mechanisms relating/leading to cyberbullying in East Asia.  C. Lee and Shin (2017) argue that parental support can be a moderator in preventing cyberbullying perpetration, given the importance of the strong parent-child bond in the region. X. Yang et al. (2018) found interparental conflicts to have an indirect effect on cyberbullying perpetration in Chinese adolescents. The relationship between interparental conflicts and cyberbullying perpetration behaviors were significantly mediated by moral disengagement and moral identity. This finding suggests that the Chinese adolescents’ development of self-identity was affected by the family environment and conflicts at home, which then made them more prone to engage in cyberbullying. What is also significant about X. Yang et al.’s (2018) findings is that moral disengagement in these adolescents led them to hold such an attitude where they regarded misbehaviors such as cyberbullying as merely ‘joking’. Such a phenomenon would not be specific to East Asian adolescents solely. However, strong group norms in this cultural zone can lead such attitudes to be shared, exacerbated, or normalised further.

Limitations and Suggestions for Future Research

The foremost limitation of the findings discussed in this review may be the representativeness of the samples in the reviewed articles. Most of the studies were conducted in major cities such as Taipei and Seoul, and there was a lack of consideration for the diversity of adolescent experience online across different settings. Moreover, while it is believed that most of the countries in East Asia continue to hold a strong emphasis on the values of Confucianism, the extent to which these values may be similar across these countries remains to be further explored. There was no direct comparison of the cultural values across the studies and countries included in the review for cultural dimensions. Also, this review did not pay particular attention to issues relating to gender and social norms around gender such as policing of heterosexuality or gender conformity and how such factors play a role in cyberbullying in East Asia. Other factors such as prejudice based on political, ethnic, linguistic or religious motivations merit more attention in further research in the region. Lastly, while studies have shown differences in cyberbullying prevalence in rural and urban areas, whether this picture is changing in the context of increasing mobile phone use in all adolescents remains to be investigated. It may be the case that this gap is closing as young people in rural areas nowadays have near equal internet penetration rates and thus may be equally susceptible to cyberbullying.

Despite these limitations, this review provides direction to future research and adds valuable information to a field that is rapidly growing and extremely relevant in the current global context. Also, the impact of cultural factors can extend to other types of cybercrime, workplace cyberbullying and problematic internet usage. The sociocultural factors affecting workplace bullying, for instance, may be particularly important due to collectivistic values that emphasise harmony, subordination and hierarchical group dynamics. The prevalence and popular methods used in different types of cyberbullying and other forms of online aggression may also differ across regions. The successful prevention of such behaviors will be focused on exploring the factors that facilitate the growth of such crimes in a particular region over others. Sittichai and Smith (2015) highlighted the importance of considering imbalance of power in cyberbullying research, and of including a definition and conceptualization of cyberbullying that takes account of the power criterion. Furthermore, more consistency with the definition across future studies is desired, especially with regards to what is meant by repetition (e.g., same perpetrator repeating the insult vs. others sharing/perpetrating the initial insult). A more consistent definition and measurement of cyberbullying can help decrease the large disparity in the reported prevalence rates across studies, although there is also the danger that this can result in lack of sensitivity to how the issue is understood in different cultural contexts. Such considerations may also be particularly useful in understanding motivations and dynamics surrounding cyberbullying in East Asia where one might find higher power distance. More contextual approaches and understandings of cyberbullying across cultures would be advisable. Moreover, sociocultural factors such as the urban-rural digital divide that may make some people more susceptible to bullying over others and economic opportunities are all important variables that should be examined closely in future research.


The findings from the reviewed East Asian studies have demonstrated that cyberbullying is influenced by the cultural context in which it occurs. The present review highlighted the unique factors associated with cyberbullying in East Asia and thus the need for further research in the area. If future research can successfully replicate and extend some of these findings, particularly in terms of the values built on social cohesion, this knowledge can be integrated into cyberbullying awareness initiatives that enhance values that reduce cyberbullying involvement and also encourage reporting of such behaviors. Societies such as those studied that place a strong emphasis on maintaining social harmony may be inadvertently discouraging reporting of cyberbullying and encouraging a wider acceptance of certain kinds of cyberbullying behaviors. This trend could also have influenced the findings in the reviewed studies, as Asian students may not have felt comfortable opening up about certain types of cyberbullying. This could indicate that the prevalence rates are possibly much higher than estimated. This possibility was pointed out in the case of sexual harassment by S. C. Yang et al. (2014) as a contributor towards lower reporting. Therefore, further research is required in this area, not only to obtain accurate prevalence rates, but also to redefine cyberbullying and attitudes towards it and encourage reporting, which is essential to solving the problem.

Additionally, the highlighted issues point towards the factors that may be more pertinent in the East Asian context and the role that future research can play in this regard, particularly as cyberbullying is established as an important public health concern for adolescents. Sociocultural factors, such as an emphasis on academic achievement, gender socialization for males, and digital media skills, aid in the identification of those most vulnerable to cyberbullying perpetration and victimization.  Regional and international differences as illustrated by the reviewed cross-cultural studies should be investigated further to highlight the unique mechanisms through which cyberbullying operates. The influence of culture and other factors on cyberbullying indicate that truly successful training, prevention and intervention programs need to be based on research that takes into account the specific cultural contexts, including differences within the region and all the relevant social factors that come into play. Finally, awareness initiatives that can successfully take the contextual factors into account will be necessary, especially amongst the countries where there is a lack of research.


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