EDITORIAL article

Editorial: cyberbullying and mental health: an interdisciplinary perspective.

\nClaudio Longobardi

  • 1 Department of Psychology, University of Turin, Turin, Italy
  • 2 Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
  • 3 Faculty of Communication, Cultural and Society, Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland

Editorial on the Research Topic Cyberbullying and Mental Health: An Interdisciplinary Perspective

Introduction

Adolescents are at risk of various forms of peer victimization, particularly in the school context. However, in the last decade, with the development of new technologies and the proliferation of social media among adolescents, the phenomenon of cyberbullying has attracted the attention of researchers, practitioners, and policy makers, considering the impact of cyberbullying victimization on the psychological adjustment and psychophysical integrity of minors.

Knowledge of the phenomenon of cyberbullying is not only a scientific and theoretical curiosity, but also allows appropriate prevention and intervention strategies to be more effective. Although scientific research has identified cyberbullying as a risk factor for adolescent mental health, little is known about the possible mechanisms and mediating factors involved in this relationship. Theoretical models of the relationship between cybervictimization and mental health are underdeveloped, particularly in the emerging field of social neuroscience.

The goal of this Research Topic is to advance current knowledge of the relationship between cybervictimization and mental health, promote an interdisciplinary view of the phenomenon, and identify opportunities for prevention and intervention.

For the Research Topic, 13 contributions with different cultural backgrounds were compiled, including two literature reviews and 11 empirical studies, two of which applied a qualitative approach.

Literature Review and Theoretical Contributions

In their mini review, McLoughin et al. point out that there is a gap in the literature on how cyberbullying affects brain development. According to the authors, this is an important limitation, as developmental cognitive neuroscience could help us to understand which factors increase the likelihood of an adolescent becoming involved in cyberbullying, as either a victim or an aggressor, and to develop tailored interventions. In particular, the authors emphasize the importance of encouraging longitudinal studies using brain imaging techniques to understand how cyberbullying may affect brain development according to gender and age. The importance of interdisciplinary approaches is also emphasized by Auriemma et al. who propose a theoretical model for understanding the cyberbullying phenomenon based on complex and multifaceted constructs of empathy such as emotional contagion, theory of mind, compassion, prosocial behavior, egocentric bias, and individual traits.

Empirical Findings: Quantitative Data on Cyberbullying and Developmental Outcomes

Empirical articles have examined the relationship between cyberbullying and mental health in adolescents, pointing to possible mediating mechanisms. Wachs et al. found that high levels of alexithymia tended to mediate the relationship between cyberbullying victimization and measures of self-esteem and Internet addiction in three different countries: Germany, the Netherlands, and the United States.

The paper by Yu et al. from China attempts to expand knowledge of possible mechanisms to explain the relationship between cybervictimization and non-suicidal self-injury. Based on social control theory and the organism-environment interaction model, the authors report that school engagement is a possible mediating factor between cybervictimization and non-suicidal self-injury among adolescents with high sensation seeking.

In a large sample of Chinese adolescents, Chen et al. found that cybervictimization may increase the risk of deviant peer affiliation, which may help to explain the association between cybervictimization and increased drinking behavior among adolescents. In addition, the authors note that the personal growth initiative plays a mediating role. Consistent with the person-environment interaction model, the authors posit that personal growth initiative is a potential protective factor for the indirect effects of cybervictimization on adolescent drinking.

In a large sample of Chinese adolescents, Wang et al. confirm a significant correlation between cybervictimization and Internet addiction, identifying depression as a possible mediating factor. Interestingly, the authors note that positive peer affiliation does not appear to protect adolescents from negative outcomes when they experience high levels of cybervictimization. This suggests the need for further studies on the relationship between cybervictimization and mental health, and on the mediating role of peer relationships, particularly prosocial peer affiliation.

The pandemic situation and lockdowns around the world have created a context in which forms of cybervictimization can proliferate. The paper by Han et al. addresses the relationship between cyberbullying and mental health in the context of the COVID-19 pandemic and specifically targets a rural population of Chinese youth. In the context of the COVID-19 outbreak in 2020, the authors examined the associations between involvement in cyberbullying, resilient coping, and loneliness. They show that resilient coping strategies can reduce the association between cyberbullying and loneliness. Moreover, bullying victims tend to exhibit higher levels of loneliness and lower levels of resilient coping than perpetrators who engage in bullying alone or victims who engage in bullying alone.

The Italian paper by Saladino et al. adds to our knowledge of adolescents' personal cognitions and perceptions of cyberbullying and its consequences. In addition, the authors explain how these data can support cyberbullying prevention and intervention efforts in the school context.

Cyberbullying prevention cannot focus exclusively on victims and aggressors and must consider the entire social scene involved in the dynamics of bullying and cyberbullying. With this in mind, Jungert et al. experimental study addresses potential bystander figures and helps us to better understand when and why youth are motivated to help bullying victims. Research has only recently focused on the bystander figure, but we believe that understanding the factors involved in the predisposition and decision to help a victim of bullying or cyberbullying could have important implications for preventing and counteracting the phenomenon.

Research on the relationship between psychological well-being and cyberbullying has focused predominantly on adolescents, with little evidence on younger students. With this in mind, the brief report by Sidera et al. seeks to expand our knowledge on the relationship between cyberbullying victimization and psychological adjustment in elementary school. The authors report that 14% of the students surveyed had been victims of cyberbullying at least once in the past 2 months, and many of them reported having been victims of traditional bullying as well. The data show that males are at greater risk of being victims of cyberbullying than females, and that the impact of cyberbullying is greater on children who have not also experienced traditional bullying. It is possible that cyberbullying in childhood has different risk factors added to social exclusion ( Morese and Longobardi, 2020 ) and impacts on developmental processes than in adolescence, and future research in this area should be encouraged.

Another stage of the life cycle that appears to be under-researched is adulthood. There is limited research on the relationship between cyberbullying and psychological well-being in adults. In relation to this, Schodt et al. conducted two studies on the relationship between psychological symptoms and involvement in cyberbullying among American adults. In doing so, they attempted to fill a gap in the literature by finding an association between mental health measures and increased risk of involvement in cyberbullying as a victim or aggressor, particularly among men who use social media more. These data appear to differ in part from the literature for adolescents. Therefore, further research on the relationship between mental health and cyberbullying at any developmental stage should be encouraged.

Empirical Findings: Qualitative Research on Adolescents' Perceptions and Experiences of Cyberbullying

Two interesting qualitative research articles are found within this Research Topic. Li and Hesketh carried out semi-structured interviews with 41 students (12–16 years old) involved in traditional bullying and cyberbullying. The authors found that traditional bullying is more common than cyberbullying, although there is a great deal of overlap between the two types. They developed a conceptual framework which identified a number of risk factors at the organizational and individual levels, pointing to a lack of support from parents and teachers, even when needed, leading to poorer developmental and academic outcomes.

Mishna et al. have also sought to expand current knowledge about how adults, parents, and teachers perceive traditional bullying and cyberbullying. According to the authors, it is important to examine how adolescents and adults (who represent three critical relationship systems in the ecological context of bullying) conceptualize the nature and impact of peer victimization in online and offline contexts in order to identify more accurate and effective prevention and intervention strategies.

Conclusions

In conclusion, the Research Topic highlights the importance of considering cyberbullying as a risk factor for the psychological adjustment of individuals and adolescents in particular. It is important to increase our knowledge on the relationship between cyberbullying and mental health to understand which areas of individual functioning are affected and which mediating factors are involved. This knowledge will allow us to identify at-risk situations more accurately and implement prevention and intervention strategies more effectively.

The collected contributions point to the need to address and prevent forms of peer victimization, including cyberbullying. Prevention efforts must target all actors involved in the dynamics of bullying and cyberbullying—not only the victims and perpetrators of bullying, but also the observers and the adults (teachers and parents) among their peers. In this respect, the collected research contributions emphasize the importance of making individuals aware of the definition of the phenomenon of cyberbullying and its consequences, starting from the knowledge and personal perceptions that individuals—both adults and minors—develop regarding the phenomenon.

In addition, we believe it is important to increase the scientific knowledge on the relationship between cybervictimization and mental health at different developmental stages, including childhood and adulthood. In connection with this, we emphasize the importance of an interdisciplinary approach when studying the relationship between cyberbullying and psychological adjustment, and we believe that social neuroscience can help expand our knowledge and develop theoretical models that can contribute to prevention and intervention.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and have approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Morese, R., and Longobardi, C. (2020). Suicidal ideation in adolescence: a perspective view on the role of the ventromedial prefrontal cortex. Front. psycho. 11, 713.

PubMed Abstract | Google Scholar

Keywords: cyberbullying, mental health, adjustment (psychology), adolescents, cross cultural

Citation: Longobardi C, Thornberg R and Morese R (2022) Editorial: Cyberbullying and Mental Health: An Interdisciplinary Perspective. Front. Psychol. 12:827106. doi: 10.3389/fpsyg.2021.827106

Received: 01 December 2021; Accepted: 17 December 2021; Published: 12 January 2022.

Edited and reviewed by: Pablo Fernández-Berrocal , University of Malaga, Spain

Copyright © 2022 Longobardi, Thornberg and Morese. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Claudio Longobardi, claudio.longobardi@unito.it

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

  • Research article
  • Open access
  • Published: 28 May 2019

“I felt angry, but I couldn’t do anything about it”: a qualitative study of cyberbullying among Taiwanese high school students

  • Chia-Wen Wang   ORCID: orcid.org/0000-0002-5020-6395 1 ,
  • Patou Masika Musumari 2 ,
  • Teeranee Techasrivichien 1 , 2 ,
  • S. Pilar Suguimoto 1 , 3 ,
  • Chang-Chuan Chan 4 ,
  • Masako Ono-Kihara 2 ,
  • Masahiro Kihara 1 &
  • Takeo Nakayama 1  

BMC Public Health volume  19 , Article number:  654 ( 2019 ) Cite this article

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Cyberbullying is a growing public health concern threatening the well-being of adolescents in both developed and developing countries. In Taiwan, qualitative research exploring the experiences and perceptions of cyberbullying among Taiwanese young people is lacking.

We conducted in-depth interviews with a convenience sample of high school students (aged 16 to 18) from five schools in Taipei, Taiwan, without prior knowledge of their cyberbullying experiences. In total, 48 participants were interviewed.

We found that the experience of cyberbullying is common, frequently occurs anonymously and publicly on unofficial school Facebook pages created by students themselves, and manifests in multiple ways, such as name-calling, uploading photos, and/or excluding victims from online groups of friends. Exclusion, which may be a type of cyberbullying unique to the Asian context, causes a sense of isolation, helplessness, or hopelessness, even producing mental health effects in the victims because people place the utmost importance on interpersonal harmony due to the Confucian values in collectivistic Asian societies. In addition, our study revealed reasons for cyberbullying that also potentially reflect the collectivistic values of Asian societies. These reasons included fun, discrimination, jealousy, revenge, and punishment of peers who broke school or social rules/norms, for example, by cheating others or being promiscuous.

Conclusions

Our findings reveal the pressing need for the Taiwanese school system to develop cyberbullying prevention programmes considering the nature and sociocultural characteristics of cyberbullying.

Peer Review reports

In recent years, with the rapid growth of information and communication technologies (ICTs), including the internet, social networking services (SNSs), and smartphones, a particular form of bullying referred to as cyberbullying has emerged. Past studies have documented the adverse health effects of traditional bullying on victims, including but not limited to psychosomatic problems [ 1 ], anxiety and depression [ 2 ], and suicidal ideation and suicidal behaviours [ 3 ]. Cyberbullying is often characterized by anonymity and publicity [ 4 , 5 , 6 ] and may result in significantly more negative consequences than traditional bullying. Past studies have suggested that victims of cyberbullying experienced more distress and had a higher risk of suicide ideation and attempts than victims of traditional bullying at school [ 7 , 8 , 9 ].

Asia, with approximately 4.2 billion people, has the largest population in the world and has been experiencing exponential growth of ICT usage during the last few decades. One statistical report documented that internet usage in Asia has increased 1670% since 2000 [ 10 ]. In particular, the overall penetration of internet usage has exceeded 80% of the population in certain countries, such as Hong Kong (87.0%), Japan (93.3%), South Korea (92.6%), and Taiwan (87.9%) [ 11 ]. In this context, the pervasiveness of ICT usage is alarming considering the urgent and critical issue of cyberbullying in Asian countries [ 12 ]. Although this issue has received little attention, the phenomenon has been found to be pervasive among adolescents in Asia. Studies from Taiwan, China, South Korea, and Japan have shown prevalence rates ranging from 6.3 to 34.8% for cyberbullying perpetration and from 14.6 to 56.9% for cyberbullying victimization [ 13 , 14 , 15 , 16 ]. These studies suggest that factors such as gender [ 13 , 14 , 15 ], electronic media (instant messaging, chat rooms, websites and bulletin board systems, e-mail, cell phones, SNSs, etc.) [ 13 , 14 ], academic achievement [ 14 ], internet usage time [ 14 , 15 ], and prior traditional bullying experiences [ 14 , 15 ] are associated with cyberbullying.

Many studies on cyberbullying have been conducted in Western countries [ 5 , 7 , 17 , 18 , 19 , 20 , 21 ] using both qualitative and quantitative approaches, whereas research on cyberbullying in Asian regions [ 13 , 14 , 15 , 22 ], whether qualitative or quantitative, remains scarce. Furthermore, past studies on cyberbullying in Asia have predominately been conducted using a quantitative approach to analyse the prevalence and related factors regarding cyberbullying, yet adolescents’ experiences and perceptions in the Asian context have not received much attention.

Cyberbullying is context-dependent, namely, influenced by the sociocultural environment [ 13 ]. Some studies have suggested that sociocultural factors should be considered to understand differences in the cyberbullying phenomenon between Asian and Western countries. For example, Shapka and Law (2013) found that ethnic differences between Canadian adolescents of East Asian and European descent were related to cyberbullying engagement [ 23 ]. Li (2008) found different patterns regarding cyberbullying experiences between Canadian and Chinese students, also suggesting that access to various ICTs may increase the risk of being involved in cyberbullying [ 24 ]. Furthermore, a short-term longitudinal study indicated cultural differences in cyberbullying between U.S. students and Japanese students [ 25 ].

A qualitative approach offers a useful means to explore the cyberbullying experiences of adolescents in the Asian social context in depth. This study employed a qualitative approach to explore the experiences and perceptions of cyberbullying among high school students in Taiwan.

Study design, participants, and setting

This is a qualitative study conducted between June and November 2016 using convenience sampling of high school students aged 16–18 from five high schools in Taipei, Taiwan. Participants in this study were recruited without prior knowledge of their cyberbullying experiences either as victims or perpetrators owing to the difficulties of identifying the victims and perpetrators of cyberbullying as indicated in previous studies [ 5 , 21 ]. Teachers announced the interview opportunity in class to help recruit student volunteers. Given the sensitive nature of the topic of cyberbullying, the teachers did not mention the word “bullying” in the announcement. They mentioned only that the researchers wanted to interview students about their internet usage experiences. Subsequently, potential student volunteers contacted the teachers privately to obtain more details about the interview (namely, that the interview would address their opinions, perceptions and experiences regarding cyberbullying) to decide whether to participate. If the students and their legal guardians both agreed, then the researchers arranged an interview time. This study relied on voluntary participation. All participants and their guardians received information about the study’s purpose, its strict confidentiality, the voluntary nature of their participation, and their right to withdraw from the interview at any time. The participants and their guardians provided written informed consent prior to the interviews. Psychotherapy or mental health counselling was provided by the researcher during the study when requested by a participant. In addition, participants were referred to a hospital psychiatrist or clinical psychologist if they were found to be experiencing psychological distress or were identified as having severe suicidal ideation. We provided stationery and snacks to the students as tokens of appreciation for their time.

Data collection and analysis

Data were collected through in-depth interviews guided by a semi-structured questionnaire. All interviews were audio-recorded and conducted in Mandarin by the same researcher (first author), and each interview lasted 30 to 100 min. The interviews were conducted in a designated room at each school that was occupied only by the researcher and participant to ensure the participants’ privacy and confidentiality. Prior to the interviews, the participants answered a short questionnaire including questions regarding sociodemographic characteristics (age, gender, etc.) and internet and ICT-related factors (internet usage time, tools to access the internet, etc.). The interviews explored the students’ experiences and perceptions of cyberbullying. Table  1 displays the topics and items included in the in-depth interviews.

The interviews were transcribed verbatim and imported into QSR International’s Nvivo10 software. To perform the analyses, we used investigator triangulation and thematic analysis, an approach that involves familiarization with the data through an iterative process of reading the transcripts, generating codes, and arranging them into larger categorical groups (subcategories, categories, and themes) until a saturated thematic map of the data is obtained [ 26 ]. We revised and refined the themes until we achieved a consensus.

In total, 48 participants were interviewed [26 male students (54.2%) and 22 female students (45.8%)]. Most of the participants (77.1%) lived with both their parents, used a smartphone as a tool to access the internet (75.0%), and used the internet for at least 2 hours per day (66.7%) (Table  2 ).

Of the 48 participants, 12 students (25.0%) reported a personal history of being a victim of cyberbullying, and the majority of the victims [10 of 12 (83.3%)] also reported being witnesses. The remainder of the students (75.0%) reported witnessing cyberbullying by friends, classmates, or schoolmates; however, none of them reported ever being a perpetrator. We identified six main themes, which are presented below along with supporting quotes. In some instances, the quotes were slightly edited for fluency.

Theme 1: the sites of cyberbullying

Most participants [38 of 48 (79.2%)] reported that SNSs were the venues in which they were most likely to experience or witness cyberbullying, including unofficial school Facebook pages, personal Facebook pages, Instagram and Meteor (an SNS that is popular among Taiwanese high school students). In particular, they explained that cyberbullying often emerged on unofficial school Facebook pages. These pages are unrestricted and are created by students themselves to anonymously express their feelings or complaints concerning someone or something related to their school. One of the victims stated:

“I saw that they verbally abused me on our unofficial school Facebook page, and many idiots (schoolmates) didn’t know the truth, and then, they clicked the ‘Like’ button on that post. I felt angry that they agreed with the perpetrators. I couldn’t do anything about it [angry face].” [16, M]

Some participants [10 of 48 (20.8%)] also reported instances of cyberbullying such as uploading photos without approval through instant messaging applications such as LINE (a popular app in Taiwan for instant communication). One participant said:

“She felt angry that her classmates downloaded her Facebook photos without permission and re-uploaded the photos without her approval to the LINE class group.” [17, F]

A few of the participants [4 of 48 (8.3%)], particularly boys, indicated that online gaming, specifically multi-player or violent games, was another online context where they had witnessed or experienced cyberbullying. One victim said:

“They [the online game players] verbally abused me because my performance was poor. Then, they would command you to change the online game character. If you did not follow their requests, they would attack you repeatedly. I felt very uncomfortable when I played the game.” [17, M]

Theme 2: the features of cyberbullying

In the interviews, the participants reported some features of cyberbullying, including anonymity, publicity, and permanency, which result in negative feelings such as anger or sadness.

The majority of participants [32 of 48 (66.7%)] stated that cyberbullying was characterized by anonymity, indicating that perpetrators could attack victims but remain anonymous. According to the victims, nearly half of the victims [5 of 12 (41.7%)] stated that in their experience, they were cyberbullied anonymously. They mentioned that they felt powerless when being bullied online. This feeling was mostly related to the fact that the perpetrators were anonymous, precluding the victims from taking action to resolve the issue (for example, by removing inappropriate content from SNSs), as expressed in the following statements:

“Someone attacked and verbally abused me online, and what he/she said was not the truth. It’s been hurtful to me. Things got worse, and some people believed what that person posted about me. I felt like I couldn’t defend myself, and whatever I said, people didn’t believe me.” [16, F]
“If the perpetrator is anonymous, you don’t know who he/she is, and you cannot ask him/her to delete the content [degrading photos or embarrassing videos].” [17, F]

In addition, some of the participants [11 of 48 (22.9%)] mentioned how the perpetrators remained anonymous on social media sites. For example, Crush Ninja was popular among students for managing their own anonymous pages as well as public unofficial school Facebook pages to maintain anonymity or hide their IP addresses. One participant said:

“They [the perpetrators] verbally abused someone on our unofficial school Facebook page. However, their names were not shown on that page. They submitted their posts to the third-party platform (CrushNinja), and then the posts were submitted by the third-party platform without revealing their identities.” [18, M]

This study found that an anonymous social media site called Meteor is highly popular among Taiwanese high school students. On this site, perpetrators can attack victims without revealing their identities. One victim stated:

“Someone verbally abused me and my friend on Meteor. I felt very hurt. The post was anonymous and did not show who posted the message. I didn’t know who attacked us.” [16, F]

In addition, half of the participants [25 of 48 (52.1%)] frequently mentioned the public nature of cyberbullying, resulting in public exposure of the victims and easy engagement of other cyber bystanders as one of the participants described:

“Sometimes, they [the perpetrators] directly write your student number, and your classmates will recognize you through your student number and tag you [on Facebook]. Then, they would verbally abuse you jointly.” [16, F]

Some participants [12 of 48 (25.0%)] mentioned that they felt awful or hurt due to the permanency of cyberbullying on SNSs. From the victims’ perspective, some victims [4 of 12 (33.3%)] felt angry that they could not remove demeaning or embarrassing content themselves. Additionally, a few participants [5 of 48 (10.4%)] felt terrified that once posted online, the content would remain there forever. The participants stated:

“I think our unofficial school Facebook page should be removed. Someone called me names on it. I felt very uncomfortable [angry face].” [18, F]
“The posts on our unofficial school Facebook page would remain online forever. Even if you later felt sorry about attacking the victims, you couldn’t withdraw what you posted.” [16, F]
“One of my classmates wanted to remove what she had posted on our unofficial school Facebook page. Although she contacted the manager of our unofficial school Facebook page, the manager did not remove the post.” [16, F]

Theme 3: the types of cyberbullying

The participants reported that the most common type of cyberbullying was name-calling (gossiping) [38 of 48 (79.2%)], followed by posting photos [12 of 48 (25.0%)] and exclusion (isolation) [4 of 48 (8.3%)], as shown in the following statements:

Name-calling (gossiping)

“They [the perpetrators] created two accounts on Instagram. One was open to the public, and the other one was privately shared between a few good friends. They used the private account to gossip and call other classmates or schoolmates names. ” [17, F]
“She gossiped about me on her private Instagram account, and one of my classmates who followed her account took a screenshot of the malicious gossip and forwarded it to me.” [16, F]

Posting photos

“I once witnessed someone intentionally posting a girl’s photo using an anonymous account on our unofficial school Facebook page. He [or she] took the photo of the girl, uploaded it, and verbally abused her. I felt like s/he [the perpetrator] intentionally did it to hurt the girl.” [17, F]

Exclusion (isolation)

The participants reported that to isolate them, perpetrators would exclude victims by creating a group on LINE that included all their classmates except for the victims. The participants stated:

“He is very bai-mu [a slang term in the local Taiwanese language used to describe an individual who does not understand a situation and then engages in inappropriate behaviour to annoy other people], so classmates dislike him, and he is not in our LINE class group; none of our classmates have included him in the group, although sometimes important class announcements are posted on the group [without informing him].” [17, F]
“Well, a girl was rude, so our classmates disliked her. They created a group (on LINE) to speak ill of her. All our classmates were included in that group except for her. I was also included in that group, although I didn’t want to be. However, if I quit the group, it would be like I was on her side. So, I didn’t know what to do.” [17, F]

The overlap with traditional bullying

Although we did not explicitly ask about traditional bullying, we found an overlap between cyberbullying and traditional bullying. Some of the victims [4 of 12 (33.3%)] of cyberbullying also reported having experienced traditional bullying at school. They reported that they felt sad for being bullied not only at school but also on the internet. One of the victims stated:

“When I was walking over, they [the classmates] called me bitch, and they often gossiped about me. I couldn’t do anything because no one stood by my side [sad face]. If I fought back, they would attack me even more aggressively…Someone [publicly] insulted me [on Meteor, a highly popular SNS among Taiwanese high school students] and gossiped that I had sex with someone and called me a bitch.” [16, F]

Theme 4: motivation for cyberbullying

The participants mentioned several reasons for cyberbullying, including fun, punishment, discrimination, jealousy, and revenge.

Nearly half of the participants [23 of 48 (47.9%)] reported that the most common reason for cyberbullying was “ for entertainment or for fun. ” One participant stated:

“They felt that it was fun to post his [a classmate with emotional disorders] videos on the Facebook page.” [18, M]

For punishment

Some participants [15 of 48 (31.3%)] reported that other schoolmates (or classmates) were annoyed because the victims did something wrong at school, such as cheating or being sexually promiscuous, or the victims were rude or bai-mu , which is why the victims were then bullied. The participants stated:

“A girl in our class was verbally abused on our unofficial school Facebook page because she cheated on an exam. She was depressed for a long time.” [17, F]
“A girl was repeatedly attacked on our unofficial school Facebook page because she was hooking up with many guys at our school, and her real name was posted openly.” [18, M]
“I saw that a schoolmate’s name was posted and that he was verbally abused on our unofficial school Facebook page. I knew him because we were classmates in 10 th grade. He is bai-mu and obnoxious. Many people hate him, including me.” [18, M]

For revenge

Revenge as a reason for cyberbullying was mentioned by a few participants [5 of 48 (10.4%)]. For example, one of the participants described an incident of cyberbullying that occurred in her class. A victim of traditional bullying could not tolerate his perpetrator’s constant teasing of him in class, and the victim therefore took revenge on the perpetrator online. The participant stated:

“The boy thought that it was very funny to tease him [the victim]. In the beginning, I thought that it was funny, too. However, he made fun of him almost every class. It turned out that XXX [the victim’s name] anonymously verbally abused the boy who always made fun of him on our unofficial school Facebook page.” [16, F]

For discrimination

In a few instances [3 of 48 (6.3%)], minorities (sexual minorities and disabled students) at school were the targets of cyberbullying. Participants reported the following:

“I have been insulted [on Facebook Messenger] by my schoolmates because I’m homosexual. They called me the lady boy and told me that I’m disgusting.” [17, F]
“We created a specific page for him [a student with emotional disorders] on Facebook to post his behaviours. [He (the victim)] cannot control his emotions... sometimes a video in which he was shouting was posted....” [18, M]

From jealousy

A few participants [2 of 48 (4.2%)] mentioned that some of the perpetrators were jealous of the victims’ success in sports or academics as one of the participants described:

“ Not only was he an athlete on the national team but his academic performance was also excellent. Some schoolmates felt that he was up on a high horse. So, they attacked him on our unofficial school Facebook page. ” [17, F]

Theme 5: ambiguity and context dependency

The notion of cyberbullying was not clear to many of the participants, which caused confusion regarding whether certain behaviours would be considered cyberbullying. Many participants [26 of 48 (54.2%)] found distinguishing between cyberbullying and “ just having fun ” on LINE or other SNSs difficult. This difficulty is illustrated in the following quotes:

“They posted my photo as the cover photo of our LINE class group, but I did not care because I thought they were just kidding.” [17, M]
“He [an unfamiliar classmate] uploaded my photo, and I didn’t like it. I’m not sure whether this behaviour could be called cyberbullying.” [18, M]

In addition, the participants mentioned that whether a particular behaviour would be considered cyberbullying was based on the nature of the relationship of the involved students. They argued that between good friends, actions are interpreted as jokes, but these actions would be perceived as cyberbullying attacks if they came from unfamiliar people. For example, the participants explained:

“My sleeping photos have often been posted as the cover photos of our LINE class group since the 10 th grade. However, I do not care. I know that they are kidding rather than trying to hurt me. Additionally, the classmates who always post my photos have a good relationship with me, so I feel that it’s OK. If unfamiliar people [classmates or schoolmates] post my photos, I will demand that they remove the photos. It depends on the relationship with that person [to differentiate between jokes and cyberbullying].” [18, F]
“They uploaded my photos on the LINE group. We were good friends, so I felt very amused. I thought they were just kidding.” [16, M]

Theme 6: coping strategies of victims

Coping with cyberbullying seemed difficult; half of the victims [6 of 12 (50.0%)] reported that they ignored the bullying. However, some of the victims reported coping strategies, including talking with friends, expecting teachers to intervene, confrontation, and leaving the group.

Ignoring cyberbullying/taking no action

Half of the victims [6 of 12 (50.0%)] reported that they ignored cyberbullying or took no action when they experienced cyberbullying.

“They verbally abused me on our unofficial school Facebook page. I thought that they had nothing better to do and I just ignored it [cyberbullying].” [18, F]
“I felt angry, but I couldn’t do anything about it [cyberbullying] since he/she remained anonymous. I could not figure out who attacked me.” [17, F]

Talking with friends

Three of the 12 victims (25.0%) talked with friends to express their feelings. One victim said:

“I felt very angry, but I couldn’t do anything about it. The one thing that I could do was talk to my friends. My friends comforted me and told me not to take it so seriously.” [18, F]

Expecting teachers to intervene

In a few instances [2 of 12 (16.7%)], the victims explained that responding to cyberbullying was difficult due to the anonymity of the perpetrators and expressed the hope that teachers could identify the perpetrators. However, they felt that teachers could not address cyberbullying since the perpetrators remained anonymous. One participant described the following:

“I think that the teachers should deal with cyberbullying. However, the teachers may not be able to find out who the perpetrator is due to anonymity.” [18, F]

Confrontation

In a few cases [2 of 12 (16.7%)] where the victim knew the identity of the perpetrator, some victims felt angry or hurt and confronted the perpetrator(s) to demand the removal of demeaning content from SNSs. A victim stated:

“ He [the classmate] uploaded my photo as his Facebook profile picture, but I demanded that he remove my photo.” [18, M]

Leaving the group

Only one of the 12 victims (8.3%) mentioned she left a chat group in response to cyberbullying. She said:

“ They [the schoolmates] were gossiping about me on the chat group on Facebook Messenger, but I didn’t reply to the message and quit the chat group.” [17, F]

Table  3 displays the percentage representations of the six themes.

To our knowledge, this is the first qualitative study to explore cyberbullying among Taiwanese high school students. Most previous studies have used a quantitative approach [ 13 , 22 , 27 ]. However, due to the complexity and sensitivity of cyberbullying, quantitative studies may not fully capture the breadth and depth of the problem.

From the results, we found some similarities and differences between Asian and Western contexts. Regarding the sites of cyberbullying, similar to Western societies [ 28 , 29 ], cyberbullying predominantly occurs through SNSs. However, our study highlighted that students consistently mentioned cyberbullying experienced or witnessed on their unofficial school Facebook pages, which has rarely been reported in other studies. In Taiwan, many high school students have created unofficial school Facebook pages to express their feelings or complaints concerning someone or something at school. The anonymity and publicity [ 6 , 30 ] of such sites were utilized to provide a cover for insults, humiliation, personal attacks, or assaults, allowing many cyber bystanders to attack victims jointly. The anonymity and publicity of cyberbullying, together with its permanency, create serious negative consequences that may cause long-term psychological effects for cyber victims.

With respect to the types of cyberbullying, name-calling (gossiping), posting photos, and an overlap with traditional bullying have also been reported in the Western context [ 18 , 31 , 32 , 33 , 34 ]. In this study, we found that students used SNSs (Instagram) to gossip or call other people names, implying that they may learn about name-calling (gossiping) via Instagram as victims or bystanders. We recommend that future studies should address this issue to clarify whether students are actively participating in cyberbullying.

In addition, we found that group exclusion was very common, as reported in other Asian societies [ 14 , 35 , 36 ]. This study found that students used group exclusion to isolate a victim, for example, by creating a LINE group including everyone except for the victim(s). Previous studies from China and Hong Kong have documented group exclusion, including the use of online text to socially isolate victims [ 35 ] or kicking someone out of a chat room [ 14 ]. Such exclusion may cause feelings of isolation, helplessness, or hopelessness, producing mental health effects in victims of cyberbullying because people place the utmost importance on interpersonal harmony and a sense of belonging due to the Confucian values in collectivistic Asian societies [ 13 , 37 , 38 ].

Regarding the motivations for cyberbullying, fun [ 39 ], discrimination [ 40 , 41 ], jealousy [ 42 ], and revenge [ 39 , 41 , 42 , 43 ] were consistent with previous studies in Western societies. In addition, we found that punishment may be a significant motivation to cyberbully peers who break school rules, such as cheating, or social norms, such as traditional heterosexual roles [ 44 ] in Asian societies. In particular, group conformity is an important social rule in Asian society [ 38 ]; in this study, if students did something wrong or were different from others, as in the case of sexual minorities, they were easily targeted by other students.

In this study, we found that cyberbullying is ambiguous or highly context-dependent in Asian countries. Previous Western studies [ 20 , 45 ] have mentioned “intention” as a critical criterion to distinguish cyberbullying from cyber jokes. However, our study showed that the distinction between cyberbullying and conventional jokes and pranks between friends was not clear to many students. Judgments regarding whether a particular act or behaviour could be considered cyberbullying were based on the closeness to or the nature of the relationship with the perpetrator. Therefore, most behaviours, however offensive, would be regarded as a joke or “ just for fun ” if they were performed by someone close because participants felt that such behaviours were not performed with the intent to hurt someone. This observation may explain why many high school students mentioned that cyberbullying was carried out for entertainment or fun. We suggest that in addition to the intention of the perpetrator, his or her relationship with peers can be used to define cyberbullying among adolescents in the Asian context. Additionally, power imbalance is an essential criterion for defining cyberbullying [ 45 , 46 ]. Perpetrators may expose victims publicly, issuing psychological threats and causing the victims to feel powerless in the face of the potential cyber audience (based on the number of comments, likes, and shares) [ 47 ].

Regarding coping strategies, consistent with one study in China, most victims reported that they ignored the attacks [ 14 ]. This behaviour may indicate that passive coping strategies are predominantly adopted in Asian societies because these societies value interpersonal harmony and tolerance due to the social rules in relationships, again implying the core Confucian values in Asian contexts.

In contrast, active coping strategies, such as attempting to resolve problems or blocking a bully, have been commonly reported in Western countries [ 32 , 48 ].

Although this study provided some insight into Taiwanese students’ experiences and perceptions of cyberbullying, we need to acknowledge some limitations. First, despite our efforts to ensure privacy during the interview, place participants at ease, and maintain strict confidentiality, students were reluctant to report being victims or perpetrators of cyberbullying (in the interviews, we found that a few participants initially spoke in the third person. However, they later spoke in the first person to disclose their stories). Due to the sensitive nature of the topic and the social desirability effect, we may have failed to capture some important aspects of cyberbullying in this study, especially the cyber perpetrators’ perspective. Second, voluntary participation may have introduced a self-selection bias.

The experience of cyberbullying appears to be common among high school students and occurs in multiple forms (name-calling, posting photos, exclusion from online groups, etc.) and on multiple platforms (Facebook and instant messaging applications). Our findings underscore the pressing need for the Taiwanese school system to take action to prevent and stop cyberbullying, including developing students’ and teachers’ skills and appropriate response strategies, considering the nature of cyberbullying and sociocultural characteristics in Taiwan.

Availability of data and materials

This study is based on qualitative data, including observation field notes and interview transcripts. The participants did not consent to have their full transcripts shared publicly.

Abbreviations

Information and communication technologies

  • Social networking services

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Acknowledgements

We appreciate the contribution and cooperation of all participants and school teachers in this study.

Chia-Wen Wang was supported by the 2016 Kyoto University School of Public Health – Super Global Course travel scholarship to Taiwan through the Top Global University Project “Japan Gateway: Kyoto University Top Global Program” and a scholarship from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

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CW, MOK and MK conceived the study design. CW carried out the interviews. CW, MOK and MK discussed, revised and refined the themes. CW and PM drafted the manuscript, which was edited by TT, SS, MK and TN. MOK and CC helped supervise the whole process of the study. All authors read and approved the final manuscript.

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Wang, CW., Musumari, P.M., Techasrivichien, T. et al. “I felt angry, but I couldn’t do anything about it”: a qualitative study of cyberbullying among Taiwanese high school students. BMC Public Health 19 , 654 (2019). https://doi.org/10.1186/s12889-019-7005-9

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  • Cyberbullying
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qualitative research questions about cyberbullying

Defining cyberbullying: a qualitative research into the perceptions of youngsters

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  • 1 Department of Communication Studies, University of Antwerp, Antwerpn, Belgium. [email protected]
  • PMID: 18721100
  • DOI: 10.1089/cpb.2007.0042

Data from 53 focus groups, which involved students from 10 to 18 years old, show that youngsters often interpret "cyberbullying" as "Internet bullying" and associate the phenomenon with a wide range of practices. In order to be considered "true" cyberbullying, these practices must meet several criteria. They should be intended to hurt (by the perpetrator) and perceived as hurtful (by the victim); be part of a repetitive pattern of negative offline or online actions; and be performed in a relationship characterized by a power imbalance (based on "real-life" power criteria, such as physical strength or age, and/or on ICT-related criteria such as technological know-how and anonymity).

Publication types

  • Multicenter Study
  • Aggression / classification*
  • Focus Groups
  • Psychology, Adolescent
  • Psychology, Child
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9 facts about bullying in the U.S.

Many U.S. children have experienced bullying, whether online or in person. This has prompted discussions about schools’ responsibility to curb student harassment , and some parents have turned to home-schooling or other measures to prevent bullying .

Here is a snapshot of what we know about U.S. kids’ experiences with bullying, taken from Pew Research Center surveys and federal data sources.

Pew Research Center conducted this analysis to understand U.S. children’s experiences with bullying, both online and in person. Findings are based on surveys conducted by the Center, as well as data from the Bureau of Justice Statistics, the National Center for Education Statistics and the Centers for Disease Control and Prevention. Additional information about each survey and its methodology can be found in the links in the text of this analysis.

Bullying is among parents’ top concerns for their children, according to a fall 2022 Center survey of parents with children under 18 . About a third (35%) of U.S. parents with children younger than 18 say they are extremely or very worried that their children might be bullied at some point. Another 39% are somewhat worried about this.

Of the eight concerns asked about in the survey, only one ranked higher for parents than bullying: Four-in-ten parents are extremely or very worried about their children struggling with anxiety or depression.

A bar chart showing that bullying is among parents' top concerns for their children.

About half of U.S. teens (53%) say online harassment and online bullying are a major problem for people their age, according to a spring 2022 Center survey of teens ages 13 to 17 . Another 40% say it is a minor problem, and just 6% say it is not a problem.

Black and Hispanic teens, those from lower-income households and teen girls are more likely than those in other groups to view online harassment as a major problem.

Nearly half of U.S. teens have ever been cyberbullied, according the 2022 Center survey of teens . The survey asked teens whether they had ever experienced six types of cyberbullying. Overall, 46% say they have ever encountered at least one of these behaviors, while 28% have experienced multiple types.

A bar chart showing that nearly half of teens have ever experienced cyberbullying, with offensive name-calling being the type most commonly reported.

The most common type of online bullying for teens in this age group is being called an offensive name (32% have experienced this). Roughly one-in-five teens have had false rumors spread about them online (22%) or were sent explicit images they didn’t ask for (17%).

Teens also report they have experienced someone other than a parent constantly asking them where they are, what they’re doing or who they’re with (15%); being physically threatened (10%); or having explicit images of them shared without their consent (7%).

Older teen girls are especially likely to have experienced bullying online, the spring 2022 survey of teens shows. Some 54% of girls ages 15 to 17 have experienced at least one cyberbullying behavior asked about in the survey, compared with 44% of boys in the same age group and 41% of younger teens. In particular, older teen girls are more likely than the other groups to say they have been the target of false rumors and constant monitoring by someone other than a parent.

They are also more likely to think they have been harassed online because of their physical appearance: 21% of girls ages 15 to 17 say this, compared with about one-in-ten younger teen girls and teen boys.

A horizontal stacked bar chart showing that older teen girls stand out for experiencing multiple types of cyberbullying behaviors.

White, Black and Hispanic teens have all encountered online bullying at some point, but some of their experiences differ, the spring 2022 teens survey found. For instance, 21% of Black teens say they’ve been targeted online because of their race or ethnicity, compared with 11% of Hispanic teens and 4% of White teens.

Hispanic teens are the most likely to say they’ve been constantly asked where they are, what they’re doing or who they’re with by someone other than a parent. And White teens are more likely than Black teens to say they’ve been targeted by false rumors.

The sample size for Asian American teens was not large enough to analyze separately.

A bar chart showing that black teens more likely than those who are Hispanic or White to say they have been cyberbullied because of their race or ethnicity

During the 2019-2020 school year, around two-in-ten U.S. middle and high school students said they were bullied at school . That year, 22% of students ages 12 to 18 said this, with the largest shares saying the bullying occurred for one day only (32%) or for between three and 10 days (29%), according to the most recent available data from the Bureau of Justice Statistics (BJS) and the National Center for Education Statistics (NCES).

Certain groups of students were more likely to experience bullying at school. They include girls, middle schoolers (those in sixth, seventh or eighth grade), and students in rural areas.  

The most common types of at-school bullying for all students ages 12 to 18 were being made the subject of rumors (15%) and being made fun of, called names or insulted (14%).

A bar chart showing that girls, middle schoolers and rural students are among the most likely to say they were bullied at school in 2019-2020.

The classroom was the most common location of bullying that occurred at school in 2019-2020, the BJS and NCES data shows. This was the case for 47% of students ages 12 to 18 who said they were bullied during that school year. Other frequently reported locations included hallways or stairwells (39%), the cafeteria (26%) and outside on school grounds (20%).

Fewer than half (46%) of middle and high schoolers who were bullied at school in 2019-2020 said they notified a teacher or another adult about it, according to the BJS and NCES data. Younger students were more likely to tell an adult at school. Around half or more of sixth, seventh and eighth graders said they did so, compared with 28% of 12th graders.

Students who reported more frequent bullying were also more likely to notify an adult at school. For instance, 60% of those who experienced bullying on more than 10 days during the school year told an adult, compared with 35% of those who experienced it on one day.

In 2021, high schoolers who are gay, lesbian or bisexual were about twice as likely as their heterosexual counterparts to say they’d been bullied, both at school and online, according to the Centers for Disease Control and Prevention . In the 12 months before the survey, 22% of high school students who identify as gay, lesbian or bisexual – and 21% of those who identify as questioning or some other way – said they were bullied on school property. That compares with 10% of heterosexual students. The data does not include findings for transgender students.

A dot plot showing that high schoolers' experiences with bullying vary widely by sexual orientation.

The trend is similar when it comes to electronic bullying through text or social media: 27% of high school students who identify as lesbian, gay or bisexual say they experienced this in the 12 months before the survey, as did 23% of those who identify as questioning or some other way. That compares with 11% of those who identify as heterosexual.

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Theoretically Predicting Cyberbullying Perpetration in Youth With the BGCM: Unique Challenges and Promising Research Opportunities

The psychological variables and processes germane to cyberbullying need additional empirical attention—especially for adolescent samples. Myriad studies and meta-analytic reviews have confirmed the deleterious psychological and behavioral consequences of being cyber-victimized. We argue that one method to curtail such effects is to inform interventions aimed at reducing cyberbullying perpetration regarding the why and for whom cyberbullying is likely. This review expands on these issues and emphasizes the Barlett Gentile Cyberbullying Model (BGCM) as the only validated cyberbullying-specific theory to predict cyberbullying perpetration. Our principal thesis is that the wealth of research validating the BGCM has been with adult samples and applying the BGCM to adolescents presents both challenging and exciting research opportunities for future research and intervention development in youth.

Today's technologically savvy youth have near instantaneous Internet accessibility at their fingertips. Indeed, findings from a 2018 Pew Research Center Study showed that 45% of US youth (aged 13–17) reported being online “almost constantly,” which is a 21% increase from 2014 to 2015 (Anderson and Jiang, 2018 ). While such Internet use and accessibility have undoubtedly aided in the rapid speed of communication and dissemination of ideas and knowledge, some individuals decide to engage in antisocial online behaviors, such as cyberbullying. Smith et al. ( 2008 ) defined cyberbullying as an “aggressive intentional act carried out by a group or individual, using electronic forms of contact, repeatedly and over time against a victim who cannot easily defend him or herself” (p. 376). Prevalence data shows that 37% of youth worldwide reported being cyber-victimized and 24% report cyberbullying others (Microsoft, 2012 ). Moreover, the same 2018 Pew Research Center Study (Anderson and Jiang, 2018 ) revealed that 24% of US youth indicated that social media had a mostly negative effect on their peers, and, of those youth, 27% noted that bullying and rumor spreading was the main reason for such negativity. These statistics alone beget the importance of reducing the likelihood of cyber-victimization. Barlett ( 2017 ) argued that one route to preventing cyber-victimization is to understand the processes and variables that predict cyberbullying perpetration with the ultimate goal of better developing successful cyberbullying intervention programs. The purpose of the current review is to (a) discuss recent theoretical developments elucidating the underlying processes germane to cyberbullying, (b) delve into the theoretical challenges and exciting future research possibilities that youth samples offer cyberbullying theory, and (c) discuss our primary predictions concerning intervention efforts.

Theoretically Predicting Cyberbullying

Theory is arguably the most important part of the scientific method. Parsimonious and falsifiable theory guides hypotheses to yield scientific discoveries that help scientists understand behavior. Early, atheoretical, research was paramount to understand the scope (prevalence, sex differences, grade differences, etc.) of the “cyberbullying problem,” which eventually matured to utilize existing social psychological, communication, and sociological theories to explain why and for whom cyberbullying perpetration is more likely (c.f., Barlett, 2017 , 2019 ). For instance, Heirman and Walrave ( 2012 ) utilized theory to predict cyberbullying perpetration from cyberbullying attitudes, social norms, and perceived behavioral control through cyberbullying intentions in a sample of Belgian youth. Various social and communication-based theories have been shown to reliably predict cyberbullying perpetration, such as General Strain Theory (Paez, 2018 ), Routine Activities Theory (Navarro and Jasinski, 2013 ), General Aggression Model (Kokkinos and Antoniadou, 2019 ), Social-Ecological Model (Guo et al., 2021 ), Uses and Gratifications (Tanrikulu and Erdur-Baker, 2021 ), Online Disinhibition Effect (Udris, 2014 ), and others.

One noteworthy limitation of applying such theories to understand malicious online behavior is the inability to differentiate cyber and traditional bullying perpetration. Barlett ( 2019 ) noted the importance of being able to theoretically predict cyberbullying incrementally from traditional bullying, despite the high correlation between these two forms of bullying ( r = 0.45; Kowalski et al., 2014 ). Indeed, understanding cyberbullying perpetration incrementally from traditional bullying may offer important insights into better predicting cyberbullying and may also lead to better interventions focused on decreasing cyberbullying. Notably, there is reason to expect the theoretical processes involved in cyberbullying to differ from traditional bullying processes. Although certain predictors share common variance with both types of bullying, such as callous-unemotional traits (e.g., Antoniadou et al., 2016 ), low empathy (e.g., Del Rey et al., 2016), narcissism (e.g., van Geel et al., 2017 ), and others, Vandebosch and Van Cleemput ( 2008 ) and others (Menesini and Nocentini, 2009 ) noted several differences between traditional and cyberbullying that necessitate attention. First, cyberbullying involves no physical contact between the bully and the victim due to the online nature of the harm. Thus, one's physical stature (height, weight, muscle mass) is likely less important in online contexts than face-to-face situations (Barlett et al., 2017b ). Second, the online environment affords an online aggressor an increased perception of anonymity (Wright, 2013 , 2014 ), which, according to online disinhibition effect (Suler, 2004 ), increases the likelihood of online antisocial behaviors (Udris, 2014 ). Currently, there is only one empirically validated theory that predicts cyberbullying perpetration incrementally from traditional bullying while exploiting these differences between both forms of bullying: the Barlett Gentile Cyberbullying Model (BGCM; Barlett and Gentile, 2012 ).

The basis for the BGCM is traditional aggression-based learning theories, such as the General Learning Model (GLM; Gentile et al., 2014 ) and General Aggression Model (GAM; Anderson and Bushman, 2002 ), which explicates the importance of initial behaviors predicting subsequent behaviors. The GAM was derived to offer a more comprehensive theory of aggression compared to other domain-specific aggression-focused predecessors (e.g., Script Theory, Priming, Cognitive Neo-Association Theory, Excitation Transfer Theory, and others; c.f., Anderson and Carnagey, 2004 ). The GAM consists of distal and proximate processes. Briefly, the proximate GAM posits that two input factors: situational (e.g., provocation) and personality (e.g., being male) either individually or interactively influence the internal state, which consists of inter-correlated aggressive thoughts, aggressive feelings, and physiological arousal. Changes to one, or any combination, of internal state variables cause higher-order attributional processes to be engaged to yield either premeditated or impulsive aggressive or non-aggressive behavior. Knowing the input factors juxtaposed with subsequent changes to the internal state and attributional processes can accurately predict the likelihood of aggression (Gentile and Bushman, 2012 ). GAM further posits two feedback loops. The first is that after an enacted act of aggression the victim's response feeds back into the situational input factor to continue a possible cycle of aggressive responding. The second feedback loop has the ensuing aggressive response and subsequent victim's response lead to distal GAM processes. The distal GAM posits that continued and positively reinforced learning of aggressive actions, stimuli, etc. will eventually lead to the development of one's aggressive personality through several knowledge structures: aggressive attitudes, desensitization, aggressive scripts and schemas, and aggressive biases. Finally, the proximate and distal GAM are connected as one's aggressive personality formed using distal processing is an important personality input factor in the proximate GAM.

The GLM was derived to further explicate the learning mechanisms germane to the General Aggression Model. Gentile et al. ( 2014 ) noted the many influences that learning has on GAM processing at both the proximate and distal levels. For instance, classical and discriminate learning can influence the strength and direction in the correlations between the internal state variables. Moreover, repeated learning encounters (single episodes in the GAM) and practice can reinforce, develop, and automatize the knowledge structures that help derive one's aggressive personality.

The GLM and GAM tenets regarding how single episodes of aggression act as repeated learning encounters and practice to yield behavior are the primary theoretical underpinnings of the BGCM. For instance, Gentile and Bushman ( 2012 ) showed that the best predictor for future aggression is a history of aggression and multiple longitudinal studies have shown that early cyberbullying perpetration shows significant stability over time (e.g., Sticca et al., 2013 ; Zhang et al.). Indeed, a meta-analysis of longitudinal studies showed that the relationship between early and later cyberbullying perpetration was positive and significant ( r = 0.43; Marciano et al., 2020 ). This relationship highlights the continued learning aspect of BGCM.

According to both the GAM and GLM, internal and/or external reinforcement for antisocial behaviors shapes the likelihood of continued behavior and learning. In their seminal work, Bandura et al. ( 1963 ) found that children are more likely to harm a toy Bobo doll if they witness an adult getting praised for aggressing against the same doll earlier. Subsequent work has confirmed that positive reinforcement from peers often leads to subsequent aggression (Jung et al., 2018 ). Overall, reinforcement—especially positive—helps guide and develop future behavior. Specific to cyberbullying, research has shown that positive reinforcement from friends or family correlates with cyberbullying perpetration (Barlett and Gentile, 2012 ). Moreover, Bastiaensens et al. ( 2016 ) found that the likelihood of a bystander joining a cyberbullying attack increased when normative pressure from friends, class group members, parents, and teachers was high, further emphasizing the role that reinforcement has on cyberbullying perpetration.

Figure 1 displays the current operationalization of the BGCM. Adapted from the previously noted GLM and GAM learning postulates, this model begins with the basic premise that early initial cyber-aggressive incidents act as learning trials by which the perpetrator (a) believes in the irrelevance of muscularity for online bullying (BIMOB) and (b) perceives themselves to be anonymous. As argued previously, research has suggested that BIMOB and anonymity perceptions are but two of the key differences between cyber and traditional bullying (Vandebosch and Van Cleemput, 2008 ). Continued positively reinforced cyber-aggressive behaviors further reinforce and automatize these, and possibly other, constructs to develop positive cyberbullying attitudes. Adhering to social psychological theory, the development of these attitudes eventually predicts cyberbullying perpetration behavior (see Barlett, 2017 for review). Figure 2 displays the temporal ordering of how cyberbullying perpetration develops in accordance with BGCM over time in conjunction with learning theory and assuming a positively reinforced online and/or in-person environment.

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The Barlett Gentile Cyberbullying Model (BGCM).

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The development of the BGCM with continued experiences over time.

The tenets of the BGCM have been well-researched and validated. Indeed, scholars have shown that (a) anonymity perceptions predicts cyberbullying attitudes (Barlett, 2015 ), (b) BIMOB predicts cyberbullying attitudes (Barlett et al., 2017a ), and (c) cyberbullying attitudes predict subsequent cyberbullying behavior (Doane et al., 2014 ). Moreover, longitudinal data has validated the entire model and found that Wave 2 cyberbullying attitudes mediate the relationships between (a) Wave 1 BIMOB and Wave 3 cyberbullying perpetration and (b) Wave 1 anonymity perceptions and Wave 3 cyberbullying perpetration (with waves separated by ~3 months; Barlett et al., 2017a ). Moreover, the BGCM has been validated cross-culturally (Barlett et al., 2021 ). Finally, and most importantly, studies have shown that these effects remain while statistically controlling for traditional bullying perpetration by covarying this measured variable in primary path models (Barlett and Helmstetter, 2018 ).

Specifically related to the learning tenets of BGCM, Barlett and Kowalewski ( 2019 ) conducted a short-term four-wave longitudinal study (with approximately a 3 month lag between waves) with emerging adults. Scholars measured anonymity perceptions and BIMOB at Wave 1, cyberbullying attitudes at Wave 2, and cyberbullying perpetration at Wave 3. Results supported the BGCM tenets; however, and more importantly, results further showed that Wave 3 cyberbullying perpetration predicted anonymity perceptions and BIMOB measured at Wave 4. This latter finding suggests that cyberbullying behaviors continued to reinforce and increase subsequent learned cyberbullying-related knowledge structures consistent with BGCM theorizing.

Finally, empirical evidence suggests that the BGCM is robust. Indeed, the tenets of the BGCM have been shown in (a) youth (Barlett, 2015 ) and adults alike (Barlett and Gentile, 2012 ), (b) using correlational (Barlett et al., 2019 ) and longitudinal studies (Barlett and Kowalewski, 2019 ), and in several countries across the world (e.g., USA, Brazil, Australia, China, Singapore, Japan, and Germany; Barlett et al., 2021 ). Overall, the amount of replicated findings across multiple studies on various samples with different empirical designs suggests a valid theoretical model.

Cyberbullying in Youth: Exciting Challenges and Future Work

We believe that the BGCM is important for understanding cyberbullying perpetration; however, one valid criticism of the BGCM is that the theoretical postulates have been largely validated on adult samples. Will the tenets of the BGCM—collectively—be substantiated in a youth sample? There are reasons to both be optimistic and pessimistic for such theoretical applications. Clearly, extensive future research is desperately needed, and, thus, we can only speculate based on existing theory and research to answer this question.

The most important issue in applying the BGCM to youth is the age of the child. First, participant age is a significant predictor of cyberbullying perpetration. Indeed, in their meta-analysis, Kowalski et al. ( 2014 ) showed a weak, yet significant, effect of age on cyberbullying perpetration ( r = 0.05). The direction of these and other (e.g., Del Rey et al., 2016b ; Barlett and Chamberlin, 2017 ; Beyazit et al., 2017 ; Cho and Yoo, 2017 ) effects suggest that cyberbullying increases across adolescence. The BGCM accounts for the linear relationship between age and cyberbullying via its learning postulates. In theory, younger youth may not have had many, if any at all, experiences aggressing against another person online, which effectively negates the learning tenets germane to BGCM processes. Eventually, in accordance with Figure 2 , early initial antisocial online actions likely lead to the development and automatization of learned cyberbullying predictors (anonymity, BIMOB, and, eventually, cyberbullying attitudes).

There is precedent for extending the BGCM to youth samples. Indeed, portions of the BGCM have been shown valid in youth populations. For instance, Barlett ( 2015 ) used a short-term four wave longitudinal study (with time lags of ~3 months) of US adolescents (average age is 15.50 years) and showed that the relative weight of early (e.g., Wave 1 and 2) BGCM variables on predicting later (e.g., Wave 4) cyberbullying perpetration is substantial. Namely, results showed high levels of Wave 1 cyberbullying attitudes and anonymity perceptions predicted Wave 4 cyberbullying behavior. Moreover, Wright ( 2014 ) sampled US youth and showed that anonymity predicted cyberbullying perpetration (see also Wang and Ngai, 2021 ). Finally, extensive work has shown that cyberbullying attitudes correlate (Shim and Shin, 2016 ; Handono et al., 2019 ) with cyberbullying perpetration in youth.

However, several important, yet untested, questions remain that hinge on a new research paradigm. In order to fully test the learning postulates of the BGCM in youth, researchers must somehow reliably identify a population of children who have neither been cyber-victimized nor committed cyber-aggressive actions 1 . Then, scholars would have youth complete several questionnaires to assess the theoretical predictors of cyberbullying, such as those expounded by Kowalski et al. ( 2014 ). Using longitudinal or daily diary methods researchers would need to monitor and assess if and when youth engaged in a cyber-encounter (either sending or receiving harmful online messages) using validated measures that assess frequency of cyberbullying perpetration. Finally, scholars should continue to monitor these youth over time to assess their anonymity perceptions, BIMOB, cyberbullying attitudes, and cyberbullying perpetration. This hypothetical study can help answer key proceeding questions:

Number of Learning Trials

The first important question that needs empirical investigation is how many learning trials are needed to initiate BGCM's learning processes? Without knowing the factors and age critical for predicting one's first cyberbullying experiences, it is difficult to theoretically predict how many learning trials are necessary to engage BGCM processes. For some, it is likely that only one cyber-aggressive action is needed to learn that they are anonymous and believe that their physical stature is irrelevant in the online world. For others, several cyber-aggressive actions are needed to achieve the same degree of learning. Although we cannot yet pinpoint the exact number of learning trials to accurately predict future cyberbullying perpetration, we can surmise that personality and learning differences likely predict the speed with which attitudes and knowledge are learned. Indeed, the General Learning Model (Gentile et al., 2014 ) argues that environmental (e.g., parental influences) and biological (e.g., sex) modifiers influence the extent to which people learn social behaviors. For instance, Nivette et al. ( 2014 ) found evidence to suggest that aggression was highest for males who are from countries that have high gender inequality in a sample of 7–13 year old European youth with diverse immigrant backgrounds. Moreover, recent data suggest that how “well off” a family is and residing country both differentially predict cyberbullying perpetration in a sample of youth across 41 countries (Li et al., 2020 ). These, and other, data suggest the influence of both environmental and biological predictors of antisocial behavior, consistent with learning theory.

In short, no published study that we are aware of has tested the number of learning trials needed to develop the knowledge structures necessary to predict cyberbullying perpetration in accordance with BGCM. However, identifying the number of cyber-aggressive trials needed likely depends on several biological and environmental modifying variables, including age, SES, country, and reinforcement.

Predicting Cyberbullying

The second unanswered question that has theoretical bearing is: what variables predict the likelihood of one's first cyber-aggression experience? Understanding what personality and situational variables predict when youth decide to engage in their first cyber-aggressive actions has important implications for prevention. As an example, if researchers identified that owning a cellular phone predicts the first cyber-aggressive behavior, then parents and prevention experts can pair cyberbullying prevention tactics (e.g., protective factors; Kowalski et al., 2014 ) with cellular phone acquisition to hopefully reduce future cyberbullying. As alluded to earlier, it is likely difficult to empirically capture youth's first cyber-aggressive experience. Despite the research showing substantial mean-level changes in personality traits (e.g., agreeableness) from age 10 to 60+ (Soto et al., 2011 ), which may predict cyberbullying (van Geel et al., 2017 ), scholars could investigate personality predictors (see Kowalski et al., 2014 for several such variables) or situational predictors. A study by Englander ( 2018 ) sampled US youth (grades 3–5) and showed that the likelihood of being a cyberbully was higher if children owned a cellular phone, despite the low prevalence of cyberbullying behavior at that age (see also Englander, 2019 ). By extension, perhaps youth who have never cyberbullied before and are eventually provided with a cellular phone will be more likely to engage in their first cyberbullying experience than their peers who do not own a cellular phone.

Cyberbullying Theory and Interventions

Overall, we believe that research endeavors delving into further understanding cyberbullying perpetration has both theoretical and practical implications. First, continued research into the theoretical developments should help scholars better understand the psychological mediators and moderators that predict cyberbullying perpetration. Our hope is that theory can guide such research endeavors. Many interesting research questions abound, especially as the technological landscape shifts. If future scholars choose to utilize BGCM theorizing, there are several possibilities for BGCM expansion. For instance, cyberbullying and traditional bullying differ in many ways—not just anonymity perceptions and BIMOB—that need empirical investigation. For instance, research has shown that online permanency beliefs correlate with cyberbullying perpetration (Wright, 2013 ) and are more important in the online than face-to-face world. Moreover, the ability for one single online aggressive act to be shared, liked, copied and pasted in other formats, and distributed to others almost instantaneously is another difference that needs empirical attention. These, and perhaps other differences, should be tested for possible integration into BGCM theorizing akin to how BIMOB and anonymity perceptions are placed. Finally, BIMOB focuses on muscularity as an estimate of power; however, other definitions of power could have theoretical implications, such as popularity.

Another possible area for future theoretical work is to examine other possible mediators that could explain why cyberbullying perpetration is likely. Recall that the BGCM explicates positive cyberbullying attitudes as the lone mediator; however, more are likely possible. Consistent with the distal GAM and GLM, cyberbullying-related scripts, schemas, and biases may also be key mediators. We are unaware of any research examining these variables, and such future work is warranted. Furthermore, cyberbullying intentions are likely a key mediator that could be integrated into BGCM. Several studies have shown that cyberbullying attitudes and behavior both correlate significantly with cyberbullying intentions (e.g., Heirman and Walrave, 2012 ; Pabian and Vandebosch, 2014 ; Auemaneekul et al., 2019 ).

Finally, continued work should focus on the variables that may moderate the relationships in the BGCM. We already discussed both age of participant and previous cyberbullying exposure (either as a victim or as a perpetrator); however, others likely exist. For instance, meta-analytic findings have shown that aggression, problematic Internet use, social support, and other variables predict cyberbullying perpetration (Kowalski et al., 2014 ). These, and other, variables could also affect BGCM processing. For example, Barlett et al. ( 2019 ) found that technology access and time spent online significantly correlated with cyberbullying attitudes and perpetration, which may suggest that various technology-related variables moderate existing BGCM relationships (such moderation tests were not conducted in the study).

In addition to the basic extensions of the BGCM, there are several applied implications that warrant consideration. Perhaps the most important is how continued validated research can further our intervention efforts to increase the efficacy of such programs. Several reviews of the literature (Espelage and Hong, 2017 ; Lancaster, 2018 ; Tanrikulu, 2018 ) and meta-analytic findings (Gaffney et al., 2019 ) have shown that cyberbullying intervention programs are mostly successful. For instance, one study had German youth (aged 11–17 years) randomly assigned to a control group, a short-term intervention group, or a long-term intervention group. For the latter two groups, participants received a Media Heroes training program—an intervention focused on teaching youth various skills (i.e., empathy), knowledge (i.e., Internet risks, legal consequences, definitions), and engaging in activities (i.e., role-playing, debates, presentations) to purportedly reduce cyberbullying (Schultze-Krumbholz et al., 2016 ). Results showed an (a) increase in cyberbullying for the control group over time, (b) no change in cyberbullying for those in the short-intervention group (a 1 day program with four 90 min sessions), and (c) a decrease in cyberbullying for those in the long-term intervention group (a 10 week program with one 90 min session per week; Wölfer et al., 2014 ).

Fortunately, several of these interventions use curricula derived directly from validated social psychological, communication, and sociological theories. For instance, Media Heroes (Chaux et al., 2016 ), CONRED (Del Rey et al., 2016a ), and Doane et al.'s ( 2016 ) video intervention all incorporated the Theory of Planned Behavior/Reasoned Action, which posits that subjective norms, attitudes, and perceived behavioral control predict behavior indirectly through intentions. Media Heroes, for example, molded their intervention curricula onto Theory of Planned Behavior by mapping specific modules onto the tenets of the theory, such as consequences of cyberbullying onto attitudes, class climate onto subjective norms, and online self-protection onto perceived behavioral control (Wölfer et al., 2014 ). In our opinion, Media Heroes is a perfect example of how intervention curricula derived from theory can successfully alter cyberbullying perpetration in youth. Subsequent examples of interventions derived from other theories abound.

Despite these theoretical and practical implications, the theories used to derive intervention curricula for youth are not specific to cyberbullying. True, Media Heroes includes information about cyberbullying (e.g., legal issues); however, none of their curriculum focus on aspects of cyberbullying devoid of traditional bullying. We have already articulated the importance of such theoretical differentiation. None of the cyberbullying specific theories, such as the BGCM, are used to derive intervention theory for youth; however, such extensions are welcome. First, as already discussed, there is preliminary evidence that BGCM tenets apply to youth. Second, research has shown that an intervention that teaches individuals that they are not as anonymous as they believe can reduce anonymity perceptions, which causes changes in cyberbullying perpetration 2 months later in emerging adults (Barlett et al., 2020 ). Therefore, an intervention that incorporates BGCM postulates should help to reduce cyberbullying perpetration through a reduction in either anonymity perceptions, BIMOB, and/or cyberbullying attitudes. Future research should validate such intervention efforts.

One valid criticism is that intervention curricula derived from cyberbullying-specific theories are unnecessary. Indeed, if research has confirmed that interventions are already successful when cyberbullying theory is not incorporated, then why utilize cyberbullying theory? For instance, Gradinger et al. ( 2015 ) showed successful changes in cyberbullying with a more generalized anti-bullying program (ViSC) that is absent any cyberbullying instruction. This is an important and valid criticism of our argument. We are unaware of any evidence to suggest that interventions derived from cyberbullying theory are statistically different from interventions derived from other social psychological, sociological, or communication based curricula. However, perhaps an existing intervention that incorporates some module(s) or lesson(s) about issues specific to cyberbullying prediction, such as anonymity perceptions, could further enhance the success of such interventions that use traditional bullying reduction skills (e.g., empathy). This is speculation and future research should compare these interventions.

A second applied extension of our work is that parents, and other caregivers, can help reduce cyberbullying. Our central thesis is that cyberbullying is a learned behavior through the BGCM lens. Thus, parents, peers, school counselors, etc. can help reduce the likelihood of cyberbullying by disrupting the learning germane to cyberbullying. Data from several studies support such claims. For instance, poor communication with parents has been shown to positively predict cyberbullying (e.g., Romero-Abrio et al., 2019 ), whereas a positive communicative relationship with parents can decrease cyberbullying (e.g., Park et al., 2014 ).

Final Remarks

In conclusion, we aim to present a review of the literature that we feel can add to our existing knowledge of theoretically predicting cyberbullying perpetration in youth. Since the majority of research on cyberbullying theory is validated on adults, but cyberbullying perpetration interventions are largely delivered to adolescents, there is a disconnect that needs to be addressed. We hope that this review can create cyberbullying research programs that can answer these, and other, important basic and applied questions.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1 We view this “blank slate” approach as essential – if such a sample can be found. Indeed, assessing learning longitudinally would ideally have participants never have engaged in the behavior at baseline and then monitoring changes over time. We are presuming here that youth (vs. adults) would be more likely to have never engaged in cyberbullying or be cybervictimized. However, there may be pockets of the adult population that also have never been involved in these cyber-behaviors, and, therefore, these questions are valid for those adults – if they can be identified.

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  1. Qualitative Methods in School Bullying and Cyberbullying Research: An

    School bullying research has a long history, stretching all the way back to a questionnaire study undertaken in the USA in the late 1800s (Burk, 1897).However, systematic school bullying research began in earnest in Scandinavia in the early 1970s with the work of Heinemann and Olweus ().Highlighting the extent to which research on bullying has grown exponentially since then, Smith et al. found ...

  2. Cyberbullying Among Adolescents and Children: A Comprehensive Review of

    Additional records identified through other sources included the references of reviews and two websites, Cyberbullying Research Center and United Nations Children's Fund. ... qualitative studies, conceptual studies, book reviews, news reports or abstracts of meetings, and (c). studies focused solely on preventive measures that were usually meta ...

  3. What Counts?: A Qualitative Study of Adolescents' Lived Experience with

    Introduction. Estimates of the prevalence of adolescent cyberbullying vary immensely, with reported rates of victimization ranging from 2% to 72% 1-3.This range partly reflects a lack of consistency about what, exactly, constitutes cyberbullying 4,5.For instance, experts disagree about the degree to which traditional elements of bullying, such as existence of a power differential, matter in ...

  4. Qualitative Methods in School Bullying and Cyberbullying Research: An

    PDF | On Aug 12, 2022, Paul Horton and others published Qualitative Methods in School Bullying and Cyberbullying Research: An Introduction to the Special Issue | Find, read and cite all the ...

  5. Frontiers

    Two interesting qualitative research articles are found within this Research Topic. Li and Hesketh carried out semi-structured interviews with 41 students (12-16 years old) involved in traditional bullying and cyberbullying. The authors found that traditional bullying is more common than cyberbullying, although there is a great deal of ...

  6. (PDF) Understanding Bullying and Cyberbullying Through ...

    Qualitative inquiry of bullying and cyberbullying provides a research methodology capable of bringing to the fore salient discourses such as dominant social norms and otherwise invisible nuances ...

  7. "I felt angry, but I couldn't do anything about it": a qualitative

    Cyberbullying is a growing public health concern threatening the well-being of adolescents in both developed and developing countries. In Taiwan, qualitative research exploring the experiences and perceptions of cyberbullying among Taiwanese young people is lacking. We conducted in-depth interviews with a convenience sample of high school students (aged 16 to 18) from five schools in Taipei ...

  8. Young people's conceptualizations of the nature of cyberbullying: A

    The literature search focused on primary studies which had used qualitative methods to explore young people's perceptions of cyberbullying. Mixed-method studies were included if the qualitative component was clearly delineated. Studies including open-ended questions as a qualitative element in an otherwise quantitative questionnaire were excluded.

  9. (PDF) An explorative qualitative study of cyberbullying and

    Cyber Bullying Tendency among Y oung Generation during COVID-19 Pan- demic. Institute of Industry and Academic Research Incorporat ed , 100-110.Retrieved from

  10. PDF Giving Victims of Bullying a Voice: A Qualitative Study of Post

    ing qualitative research focused on topics such as whether youth justify bullying behavior, how youth view bullying as a school related issue, why youth believe bullying occurs, ... and mixed methods studies have examined how cyber vic-tims cope with cyber bullying (Price and Dalgleish 2010; Slegova and Cema 2011), there have been limited ...

  11. PDF Cyberbullying and gender: a qualitative study of how middle school

    cyberbullying, cyberbullying is manifested in a wider range of venues and audiences, as it is not confined by location, and can potentially have a far-reaching impact with the use of social media. Thus, scholars have postulated that there are "significant qualitative differences" (Lee, Hong, Resko, & Tripodi, 2017, p.

  12. Defining cyberbullying: a qualitative research into the ...

    Data from 53 focus groups, which involved students from 10 to 18 years old, show that youngsters often interpret "cyberbullying" as "Internet bullying" and associate the phenomenon with a wide range of practices. In order to be considered "true" cyberbullying, these practices must meet several criteria. They should be intended to hurt (by the ...

  13. Understanding Bullying and Cyberbullying Through an Ecological Systems

    In discussing how qualitative research contributes to understanding bullying and cyberbullying and complements quantitative findings, the following new thematic areas are discussed: augmenting quantitative findings through qualitative interviews, contextualizing new or rapidly evolving areas of research, capturing nuances and complexity of ...

  14. (PDF) Defining cyberbullying: A qualitative research into the

    When referring to bullying that occurs via electronic means in general, it might therefore be worthwhile to consider the use of a more appropriate term (e.g., electronic bullying, digital bullying). On the other hand, the question What is cyberbullying? often leads to a numeration of media and interpersonal experiences that might be considered ...

  15. Cyberbullying and its influence on academic, social, and emotional

    The current study is designed to address two research questions: (1) does cyberbullying affect college students' emotional state, ... As there's very little research on the effect of cyberbullying on undergraduates students, especially in light of the availability of hand held devices (mainly smartphones) and the dependence on the internet for ...

  16. PDF An explorative qualitative study of cyberbullying and ...

    In a pre-pandemic qualitative study on cyberstalking, cyberharass-ment and cyberbullying against students and staf, Short et al. (2016) showed that online communication is ambiguous and there is a need for the promotion of online norms to which young people and staf can adhere.

  17. PDF Qualitative Methods in School Bullying and Cyberbullying Research: An

    School bullying research has a long history, stretching all the way back to a questionnaire study undertaken in the USA in the late 1800s (Burk, 1897). However, systematic school bullying research began in earnest in Scandinavia in the early 1970s with the work of Heinemann (1972) and Olweus (1978). Highlighting the extent to which research on ...

  18. 9 facts about bullying in the U.S.

    Pew Research Center conducted this analysis to understand U.S. children's experiences with bullying, both online and in person. Findings are based on surveys conducted by the Center, as well as data from the Bureau of Justice Statistics, the National Center for Education Statistics and the Centers for Disease Control and Prevention.

  19. Theoretically Predicting Cyberbullying Perpetration in Youth With the

    Clearly, extensive future research is desperately needed, and, thus, we can only speculate based on existing theory and research to answer this question. The most important issue in applying the BGCM to youth is the age of the child. ... Cyber-bullying and cyber-victimization among undergraduate student ... Defining cyberbullying: a qualitative ...

  20. 50 questions with answers in CYBERBULLYING

    Question. 3 answers. Dec 17, 2023. Determine the appropriate method for selecting a sample to study the issue of cyberbullying. Relevant answer. Zekrollah Morovati. Dec 22, 2023. Answer. when ...