cyberbullying research paper introduction

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Cyberbullying Among Adolescents and Children: A Comprehensive Review of the Global Situation, Risk Factors, and Preventive Measures

Chengyan zhu, shiqing huang, richard evans.

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Edited by: Daniel Bressington, Charles Darwin University, Australia

Reviewed by: Alexandra Restrepo, University of Antioquia, Colombia; Si-Tong Chen, Victoria University, Australia

*Correspondence: Wei Zhang [email protected]

This article was submitted to Public Mental Health, a section of the journal Frontiers in Public Health

†These authors have contributed equally to this work and share first authorship

Received 2020 Nov 29; Accepted 2021 Feb 10; Collection date 2021.

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.

Background: Cyberbullying is well-recognized as a severe public health issue which affects both adolescents and children. Most extant studies have focused on national and regional effects of cyberbullying, with few examining the global perspective of cyberbullying. This systematic review comprehensively examines the global situation, risk factors, and preventive measures taken worldwide to fight cyberbullying among adolescents and children.

Methods: A systematic review of available literature was completed following PRISMA guidelines using the search themes “cyberbullying” and “adolescent or children”; the time frame was from January 1st, 2015 to December 31st, 2019. Eight academic databases pertaining to public health, and communication and psychology were consulted, namely: Web of Science, Science Direct, PubMed, Google Scholar, ProQuest, Communication & Mass Media Complete, CINAHL, and PsycArticles. Additional records identified through other sources included the references of reviews and two websites, Cyberbullying Research Center and United Nations Children's Fund. A total of 63 studies out of 2070 were included in our final review focusing on cyberbullying prevalence and risk factors.

Results: The prevalence rates of cyberbullying preparation ranged from 6.0 to 46.3%, while the rates of cyberbullying victimization ranged from 13.99 to 57.5%, based on 63 references. Verbal violence was the most common type of cyberbullying. Fourteen risk factors and three protective factors were revealed in this study. At the personal level, variables associated with cyberbullying including age, gender, online behavior, race, health condition, past experience of victimization, and impulsiveness were reviewed as risk factors. Likewise, at the situational level, parent-child relationship, interpersonal relationships, and geographical location were also reviewed in relation to cyberbullying. As for protective factors, empathy and emotional intelligence, parent-child relationship, and school climate were frequently mentioned.

Conclusion: The prevalence rate of cyberbullying has increased significantly in the observed 5-year period, and it is imperative that researchers from low and middle income countries focus sufficient attention on cyberbullying of children and adolescents. Despite a lack of scientific intervention research on cyberbullying, the review also identified several promising strategies for its prevention from the perspectives of youths, parents and schools. More research on cyberbullying is needed, especially on the issue of cross-national cyberbullying. International cooperation, multi-pronged and systematic approaches are highly encouraged to deal with cyberbullying.

Keywords: cyberbullying, children, adolescents, globalization, risk factors, preventive measures

Introduction

Childhood and adolescence are not only periods of growth, but also of emerging risk taking. Young people during these periods are particularly vulnerable and cannot fully understand the connection between behaviors and consequences ( 1 ). With peer pressures, the heat of passion, children and adolescents usually perform worse than adults when people are required to maintain self-discipline to achieve good results in unfamiliar situations. Impulsiveness, sensation seeking, thrill seeking, and other individual differences cause adolescents to risk rejecting standardized risk interventions ( 2 ).

About one-third of Internet users in the world are children and adolescents under the age of 18 ( 3 ). Digital technology provide a new form of interpersonal communication ( 4 ). However, surveys and news reports also show another picture in the Internet Age. The dark side of young people's internet usage is that they may bully or suffer from others' bullying in cyberspace. This behavior is also acknowledged as cyberbullying ( 5 ). Based on Olweus's definition, cyberbullying is usually regarded as bullying implemented through electronic media ( 6 , 7 ). Specifically, cyberbullying among children and adolescents can be summarized as the intentional and repeated harm from one or more peers that occurs in cyberspace caused by the use of computers, smartphones and other devices ( 4 , 8 – 12 ). In recent years, new forms of cyberbullying behaviors have emerged, such as cyberstalking and online dating abuse ( 13 – 15 ).

Although cyberbullying is still a relatively new field of research, cyberbullying among adolescents is considered to be a serious public health issue that is closely related to adolescents' behavior, mental health and development ( 16 , 17 ). The increasing rate of Internet adoption worldwide and the popularity of social media platforms among the young people have worsened this situation with most children and adolescents experiencing cyberbullying or online victimization during their lives. The confines of space and time are alleviated for bullies in virtual environments, creating new venues for cyberbullying with no geographical boundaries ( 6 ). Cyberbullying exerts negative effects on many aspects of young people's lives, including personal privacy invasion and psychological disorders. The influence of cyberbullying may be worse than traditional bullying as perpetrators can act anonymously and connect easily with children and adolescents at any time ( 18 ). In comparison with traditional victims, those bullied online show greater levels of depression, anxiety and loneliness ( 19 ). Self-esteem problems and school absenteeism have also proven to be related to cyberbullying ( 20 ).

Due to changes in use and behavioral patterns among the youth on social media, the manifestations and risk factors of cyberbullying have faced significant transformation. Further, as the boundaries of cyberbullying are not limited by geography, cyberbullying may not be a problem contained within a single country. In this sense, cyberbullying is a global problem and tackling it requires greater international collaboration. The adverse effects caused by cyberbullying, including reduced safety, lower educational attainment, poorer mental health and greater unhappiness, led UNICEF to state that “no child is absolutely safe in the digital world” ( 3 ).

Extant research has examined the prevalence and risk factors of cyberbullying to unravel the complexity of cyberbullying across different countries and their corresponding causes. However, due to variations in cyberbullying measurement and methodologies, no consistent conclusions have been drawn ( 21 ). Studies into inconsistencies in prevalence rates of cyberbullying, measured in the same country during the same time period, occur frequently. Selkie et al. systematically reviewed cyberbullying among American middle and high school students aged 10–19 years old in 2015, and revealed that the prevalence of cyberbullying victimization ranged from 3 to 72%, while perpetration ranged from 1 to 41% ( 22 ). Risk and protective factors have also been broadly studied, but confirmation is still needed of those factors which have more significant effects on cyberbullying among young people. Clarification of these issues would be useful to allow further research to recognize cyberbullying more accurately.

This review aims to extend prior contributions and provide a comprehensive review of cyberbullying of children and adolescents from a global perspective, with the focus being on prevalence, associated risk factors and protective factors across countries. It is necessary to provide a global panorama based on research syntheses to fill the gaps in knowledge on this topic.

Search Strategies

This study strictly employed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We consulted eight academic databases pertaining to public health, and communication and psychology, namely: Web of Science, Science Direct, PubMed, Google Scholar, ProQuest, Communication & Mass Media Complete, CINAHL, and PsycArticles. Additional records identified through other sources included the references of reviews and two websites, Cyberbullying Research Center and United Nations Children's Fund. With regard to the duration of our review, since most studies on cyberbullying arose around 2015 ( 9 , 21 ), this study highlights the complementary aspects of the available information about cyberbullying during the recent 5 year period from January 1st, 2015 to December 31st, 2019.

One researcher extracted keywords and two researchers proposed modifications. We used two sets of subject terms to review articles, “cyberbullying” and “child OR adolescent.” Some keywords that refer to cyberbullying behaviors and young people are also included, such as threat, harass, intimidate, abuse, insult, humiliate, condemn, isolate, embarrass, forgery, slander, flame, stalk, manhunt, as well as teen, youth, young people and student. The search formula is (cyberbullying OR cyber-bullying OR cyber-aggression OR ((cyber OR online OR electronic OR Internet) AND (bully * OR aggres * OR violence OR perpetrat * OR victim * OR threat * OR harass * OR intimidat * OR * OR insult * OR humiliate * OR condemn * OR isolate * OR embarrass * OR forgery OR slander * OR flame OR stalk * OR manhunt))) AND (adolescen * OR child OR children OR teen? OR teenager? OR youth? OR “young people” OR “elementary school student * ” OR “middle school student * ” OR “high school student * ”). The main search approach is title search. Search strategies varied according to the database consulted, and we did not limit the type of literature for inclusion. Journals, conference papers and dissertations are all available.

Specifically, the inclusion criteria for our study were as follows: (a). reported or evaluated the prevalence and possible risk factors associated with cyberbullying, (b). respondents were students under the age of 18 or in primary, junior or senior high schools, and (c). studies were written in English. Exclusion criteria were: (a). respondents came from specific groups, such as clinical samples, children with disabilities, sexual minorities, specific ethnic groups, specific faith groups or samples with cross-national background, (b). review studies, qualitative studies, conceptual studies, book reviews, news reports or abstracts of meetings, and (c). studies focused solely on preventive measures that were usually meta-analytic and qualitative in nature. Figure 1 presents the details of the employed screening process, showing that a total of 63 studies out of 2070 were included in our final review.

PRISMA flow chart diagram showing the process of study selection for inclusion in the systematic review on children and adolescents cyberbullying.

Meta-analysis was not conducted as the limited research published within the 5 years revealed little research which reported odds ratio. On the other hand, due to the inconsistency of concepts, measuring instruments and recall periods, considerable variation could be found in research quality ( 23 ). Meta-analysis is not a preferred method.

Coding Scheme

For coding, we created a comprehensive code scheme to include the characteristics. For cyberbullying, we coded five types proposed by Willard ( 24 – 26 ), which included verbal violence, group violence, visual violence, impersonating and account forgery, and other behaviors. Among them, verbal violence is considered one of the most common types of cyberbullying and refers to the behavior of offensive responses, insults, mocking, threats, slander, and harassment. Group violence is associated with preventing others from joining certain groups or isolating others, forcing others to leave the group. Visual violence relates to the release and sharing of embarrassing photos and information without the owners' consent. Impersonating and account forgery refers to identity theft, stealing passwords, violating accounts and the creation of fake accounts to fraudulently present the behavior of others. Other behaviors include disclosure of privacy, sexual harassment, and cyberstalking. To comprehensively examine cyberbullying, we coded cyberbullying behaviors from both the perspectives of cyberbullying perpetrators and victims, if mentioned in the studies.

In relation to risk factors, we drew insights from the general aggression model, which contributes to the understanding of personal and situational factors in the cyberbullying of children and adolescents. We chose the general aggression model because (a) it contains more situational factors than other models (e.g., social ecological models) - such as school climate ( 9 ), and (b) we believe that the general aggression model is more suitable for helping researchers conduct a systematic review of cyberbullying risk and protective factors. This model provides a comprehensive framework that integrates domain specific theories of aggression, and has been widely applied in cyberbullying research ( 27 ). For instance, Kowalski and colleagues proposed a cyberbullying encounter through the general aggression model to understand the formation and development process of youth cyberbullying related to both victimization and perpetration ( 9 ). Victims and perpetrators enter the cyberbullying encounter with various individual characteristics, experiences, attitudes, desires, personalities, and motives that intersect to determine the course of the interaction. Correspondingly, the antecedents pertaining to cyberbullying are divided into two broad categories, personal factors and situational factors. Personal factors refer to individual characteristics, such as gender, age, motivation, personality, psychological states, socioeconomic status and technology use, values and perceptions, and other maladaptive behaviors. Situational factors focus on the provocation/support, parental involvement, school climate, and perceived anonymity. Consequently, our coders related to risk factors consisting of personal factors and situational factors from the perspectives of both cyberbullying perpetrators and victims.

We extracted information relating to individual papers and sample characteristics, including authors, year of publication, country, article type, sampling procedures, sample characteristics, measures of cyberbullying, and prevalence and risk factors from both cyberbullying perpetration and victimization perspectives. The key words extraction and coding work were performed twice by two trained research assistants in health informatics. The consistency test results are as follows: the Kappa value with “personal factors” was 0.932, and the Kappa value with “situational factors” was 0.807. The result shows that the coding consistency was high enough and acceptable. Disagreements were resolved through discussion with other authors.

Quality Assessment of Studies

The quality assessment of the studies is based on the recommended tool for assessing risk of bias, Cochrane Collaboration. This quality assessment tool focused on seven items: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other sources of bias ( 28 ). We assessed each item as “low risk,” “high risk,” and “unclear” for included studies. A study is considered of “high quality” when it meets three or more “low risk” requirements. When one or more main flaw of a study may affect the research results, the study is considered as “low quality.” When a lack of information leads to a difficult judgement, the quality is considered to be “unclear.” Please refer to Appendix 1 for more details.

This comprehensive systematic review comprised a total of 63 studies. Appendices 2 , 3 show the descriptive information of the studies included. Among them, 58 (92%) studies measured two or more cyberbullying behavior types. The sample sizes of the youths range from several hundred to tens of thousands, with one thousand to five thousand being the most common. As for study distribution, the United States of America, Spain and China were most frequently mentioned. Table 1 presents the detail.

Descriptive information of studies included (2015–2019).

Prevalence of Global Cyberbullying

Prevalence across countries.

Among the 63 studies included, 22 studies reported on cyberbullying prevalence and 20 studies reported on prevalence from victimization and perpetration perspectives, respectively. Among the 20 studies, 11 national studies indicated that the prevalence of cyberbullying victimization and cyberbullying perpetration ranged from 14.6 to 52.2% and 6.3 to 32%, respectively. These studies were conducted in the United States of America ( N = 4) ( 29 – 32 ), South Korea ( N = 3) ( 33 – 35 ), Singapore ( N = 1) ( 36 ), Malaysia ( N = 1) ( 37 ), Israel ( N = 1) ( 38 ), and Canada ( N = 1) ( 39 ). Only one of these 11 national studies is from an upper middle income country, and the rest are from highincome countries identified by the World Bank ( 40 ). By combining regional and community-level studies, the prevalence of cyberbullying victimization and cyberbullying perpetration ranged from 13.99 to 57.5% and 6.0 to 46.3%, respectively. Spain reported the highest prevalence of cyberbullying victimization (57.5%) ( 41 ), followed by Malaysia (52.2%) ( 37 ), Israel (45%) ( 42 ), and China (44.5%) ( 43 ). The lowest reported victim rates were observed in Canada (13.99%) and South Korea (14.6%) ( 34 , 39 ). The reported prevalence of cyberbullying victimization in the United States of America ranged from 15.5 to 31.4% ( 29 , 44 ), while in Israel, rates ranged from 30 to 45% ( 26 , 42 ). In China, rates ranged from 6 to 46.3% with the country showing the highest prevalence of cyberbullying perpetration (46.30%) ( 15 , 43 , 45 , 46 ). Canadian and South Korean studies reported the lowest prevalence of cyberbullying perpetration at 7.99 and 6.3%, respectively ( 34 , 39 ).

A total of 10 studies were assessed as high quality studies. Among them, six studies came from high income countries, including Canada, Germany, Italy, Portugal, and South Korea ( 13 , 34 , 39 , 46 – 48 ). Three studies were from upper middle income countries, including Malaysia and China ( 37 , 43 ) and one from a lower middle income country, Nigeria ( 49 ). Figures 2 , 3 describe the prevalence of cyberbullying victimization and perpetration respectively among high quality studies.

The prevalence of cyberbullying victimization of high quality studies.

The prevalence of cyberbullying perpetration of high quality studies.

Prevalence of Various Cyberbullying Behaviors

For the prevalence of cyberbullying victimization and perpetration, the data were reported in 18 and 14 studies, respectively. Figure 4 shows the distribution characteristics of the estimated value of prevalence of different cyberbullying behaviors with box plots. The longer the box, the greater the degree of variation of the numerical data and vice versa. The rate of victimization and crime of verbal violence, as well as the rate of victimization of other behaviors, such as cyberstalking and digital dating abuse, has a large degree of variation. Among the four specified types of cyberbullying behaviors, verbal violence was regarded as the most commonly reported behaviors in both perpetration and victimization rates, with a wide range of prevalence, ranging from 5 to 18%. Fewer studies reported the prevalence data for visual violence and group violence. Studies also showed that the prevalence of impersonation and account forgery were within a comparatively small scale. Specific results were as follows.

Cyberbullying prevalence across types (2015–2019).

Verbal Violence

A total of 13 studies reported verbal violence prevalence data ( 15 , 26 , 34 , 37 – 39 , 42 , 43 , 47 , 48 , 50 , 51 ). Ten studies reported the prevalence of verbal violence victimization ranging from 2.8 to 47.5%, while seven studies claimed perpetration prevalence ranging from 1.5 to 31.8%. Malaysia reported the highest prevalence of verbal violence victimization (47.5%) ( 37 ), followed by China (32%) ( 43 ). China reported that the prevalence of verbal violence victimization ranged from 5.1 to 32% ( 15 , 43 ). Israel reported that the prevalence of verbal violence victimization ranged from 3.4 to 18% ( 26 , 38 , 42 ). For perpetration rate, Malaysia reported the highest level at 31.8% ( 37 ), while a study for Spain reported the lowest, ranging from 3.2 to 6.4% ( 51 ).

Group Violence

The prevalence of group violence victimization was explored within 4 studies and ranged from 5 to 17.8% ( 26 , 34 , 42 , 43 ), while perpetration prevalence was reported in three studies, ranging from 10.1 to 19.07% ( 34 , 43 , 47 ). An Israeli study suggested that 9.8% of respondents had been excluded from the Internet, while 8.9% had been refused entry to a group or team ( 26 ). A study in South Korea argued that the perpetration prevalence of group violence was 10.1% ( 34 ), while a study in Italy reported that the rate of online group violence against others was 19.07% ( 47 ).

Visual Violence

The prevalence of visual violence victimization was explored within three studies and ranged from 2.6 to 12.1% ( 26 , 34 , 43 ), while the perpetration prevalence reported in four studies ranged from 1.7 to 6% ( 34 , 43 , 47 , 48 ). For victimization prevalence, a South Korean study found that 12.1% of respondents reported that their personal information was leaked online ( 34 ). An Israel study reported that the prevalence of outing the picture was 2.6% ( 26 ). For perpetration prevalence, a South Korean study found that 1.7% of respondents had reported that they had disclosed someone's personal information online ( 34 ). A German study reported that 6% of respondents had written a message (e.g., an email) to somebody using a fake identity ( 48 ).

Impersonating and Account Forgery

Four studies reported on the victimization prevalence of impersonating and account forgery, ranging from 1.1 to 10% ( 15 , 42 , 43 ), while five studies reported on perpetration prevalence, with the range being from 1.3 to 9.31% ( 15 , 43 , 47 , 48 , 51 ). In a Spanish study, 10% of respondents reported that their accounts had been infringed by others or that they could not access their account due to stolen passwords. In contrast, 4.5% of respondents reported that they had infringed other people's accounts or stolen passwords, with 2.5% stating that they had forged other people's accounts ( 51 ). An Israeli study reported that the prevalence of being impersonated was 7% ( 42 ), while in China, a study reported this to be 8.6% ( 43 ). Another study from China found that 1.1% of respondents had been impersonated to send dating-for-money messages ( 15 ).

Other Behaviors

The prevalence of disclosure of privacy, sexual harassment, and cyberstalking were also explored by scholars. Six studies reported the victimization prevalence of other cyberbullying behaviors ( 13 , 15 , 34 , 37 , 42 , 43 ), and four studies reported on perpetration prevalence ( 34 , 37 , 43 , 48 ). A study in China found that 1.2% of respondents reported that their privacy had been compromised without permission due to disputes ( 15 ). A study from China reported the prevalence of cyberstalking victimization was 11.9% ( 43 ), while a Portuguese study reported that this was 62% ( 13 ). In terms of perpetration prevalence, a Malaysian study reported 2.7% for sexual harassment ( 37 ).

Risk and Protective Factors of Cyberbullying

In terms of the risk factors associated with cyberbullying among children and adolescents, this comprehensive review highlighted both personal and situational factors. Personal factors referred to age, gender, online behavior, race, health conditions, past experiences of victimization, and impulsiveness, while situational factors consisted of parent-child relationship, interpersonal relationships, and geographical location. In addition, protective factors against cyberbullying included: empathy and emotional intelligence, parent-child relationship, and school climate. Table 2 shows the risk and protective factors for child and adolescent cyberbullying.

Risk and protective factors of cyberbullying among children and adolescents.

In terms of the risk factors associated with cyberbullying victimization at the personal level, many studies evidenced that females were more likely to be cyberbullied than males ( 13 , 26 , 29 , 38 , 43 , 52 , 54 , 55 , 58 ). Meanwhile, adolescents with mental health problems ( 61 ), such as depression ( 33 , 62 ), borderline personality disorder ( 63 ), eating disorders ( 41 ), sleep deprivation ( 56 ), and suicidal thoughts and suicide plans ( 64 ), were more likely to be associated with cyberbullying victimization. As for Internet usage, researchers agreed that youth victims were probably those that spent more time online than their counterparts ( 32 , 36 , 43 , 45 , 48 , 49 , 60 ). For situational risk factors, some studies have proven the relationship between cyberbullying victims and parental abuse, parental neglect, family dysfunction, inadequate monitoring, and parents' inconsistency in mediation, as well as communication issues ( 33 , 64 , 68 , 73 ). In terms of geographical location, some studies have reported that youths residing in city locations are more likely to be victims of cyberbullying than their peers from suburban areas ( 61 ).

Regarding the risk factors of cyberbullying perpetration at the personal level, it is generally believed that older teenagers, especially those aged over 15 years, are at greater risk of becoming cyberbullying perpetrators ( 55 , 67 ). When considering prior cyberbullying experiences, evidence showed that individuals who had experienced cyberbullying or face-to-face bullying tended to be aggressors in cyberbullying ( 35 , 42 , 49 , 51 , 55 ); in addition, the relationship between impulsiveness and cyberbullying perpetration was also explored by several pioneering scholars ( 55 , 72 , 80 ). The situational factors highlight the role of parents and teachers in cyberbullying experiences. For example, over-control and authoritarian parenting styles, as well as inharmonious teacher-student relationships ( 61 ) are perceived to lead to cyberbullying behaviors ( 74 , 75 ). In terms of differences in geographical locations, students residing in cities have a higher rate of online harassment than students living in more rural locations ( 49 ).

In terms of the protective factors in child and adolescent cyberbullying, scholars have focused on youths who have limited experiences of cyberbullying. At the personal level, high emotional intelligence, an ability for emotional self-control and empathy, such as cognitive empathy ability ( 44 , 55 ), were associated with lower rates of cyberbullying ( 57 ). At the situational level, a parent's role is seen as critical. For example, intimate parent-child relationships ( 46 ) and open active communication ( 19 ) were demonstrated to be related to lower experiences of cyberbullying and perpetration. Some scholars argued that parental supervision and monitoring of children's online activities can reduce their tendency to participate in some negative activities associated with cyberbullying ( 31 , 46 , 73 ). They further claimed that an authoritative parental style protects youths against cyberbullying ( 43 ). Conversely, another string of studies evidenced that parents' supervision of Internet usage was meaningless ( 45 ). In addition to conflicting roles of parental supervision, researchers have also looked into the role of schools, and posited that positive school climates contribute to less cyberbullying experiences ( 61 , 79 ).

Some risk factors may be protective factors under another condition. Some studies suggest that parental aggressive communication is related to severe cyberbullying victims, while open communication is a potential protective factor ( 19 ). Parental neglect, parental abuse, parental inconsistency in supervision of adolescents' online behavior, and family dysfunction are related to the direct or indirect harm of cyberbullying ( 33 , 68 ). Parental participation, a good parental-children relationship, communication and dialogue can enhance children's school adaptability and prevent cyberbullying behaviors ( 31 , 74 ). When parental monitoring reaches a balance between control and openness, it could become a protective factor against cyberbullying, and it could be a risk factor, if parental monitoring is too low or over-controlled ( 47 ).

Despite frequent discussion about the risk factors associated with cyberbullying among children and adolescents, some are still deemed controversial factors, such as age, race, gender, and the frequency of suffering on the internet. For cyberbullying victims, some studies claim that older teenagers are more vulnerable to cyberbullying ( 15 , 38 , 52 , 53 ), while other studies found conflicting results ( 26 , 33 ). As for student race, Alhajji et al. argued that non-white students were less likely to report cyberbullying ( 29 ), while Morin et al. observed no significant correlation between race and cyberbullying ( 52 ). For cyberbullying perpetration, Alvarez-Garcia found that gender differences may have indirect effects on cyberbullying perpetration ( 55 ), while others disagreed ( 42 , 61 , 68 – 70 ). Specifically, some studies revealed that males were more likely to become cyberbullying perpetrators ( 34 , 39 , 56 ), while Khurana et al. presented an opposite point of view, proposing that females were more likely to attack others ( 71 ). In terms of time spent on the Internet, some claimed that students who frequently surf the Internet had a higher chance of becoming perpetrators ( 49 ), while others stated that there was no clear and direct association between Internet usage and cyberbullying perpetration ( 55 ).

In addition to personal and situational factors, scholars have also explored other specific factors pertaining to cyberbullying risk and protection. For instance, mindfulness and depression were found to be significantly related to cyber perpetration ( 76 ), while eating disorder psychopathology in adolescents was associated with cyber victimization ( 41 ). For males who were familiar with their victims, such as family members, friends and acquaintances, they were more likely to be cyberstalking perpetrators than females or strangers, while pursuing desired closer relationships ( 13 ). In the school context, a lower social likability in class was identified as an indirect factor for cyberbullying ( 48 ).

This comprehensive review has established that the prevalence of global childhood and adolescent victimization from cyberbullying ranges from 13.99 to 57.5%, and that the perpetration prevalence ranges from 6.0 to 46.3%. Across the studies included in our research, verbal violence is observed as one of the most common acts of cyberbullying, including verbal offensive responses, insults, mocking, threats, slander, and harassment. The victimization prevalence of verbal violence is reported to be between 5 and 47.5%, and the perpetration prevalence is between 3.2 and 26.1%. Personal factors, such as gender, frequent use of social media platforms, depression, borderline personality disorder, eating disorders, sleep deprivation, and suicidal tendencies, were generally considered to be related to becoming a cyberbullying victim. Personal factors, such as high school students, past experiences, impulse, improperly controlled family education, poor teacher-student relationships, and the urban environment, were considered risk factors for cyberbullying perpetration. Situational factors, including parental abuse and neglect, improper monitoring, communication barriers between parents and children, as well as the urban environment, were also seen to potentially contribute to higher risks of both cyberbullying victimization and perpetration.

Increasing Prevalence of Global Cyberbullying With Changing Social Media Landscape and Measurement Alterations

This comprehensive review suggests that global cyberbullying rates, in terms of victimization and perpetration, were on the rise during the 5 year period, from 2015 to 2019. For example, in an earlier study conducted by Modecki et al. the average cyberbullying involvement rate was 15% ( 81 ). Similar observations were made by Hamm et al. who found that the median rates of youth having experienced bullying or who had bullied others online, was 23 and 15.2%, respectively ( 82 ). However, our systematic review summarized global children and adolescents cyberbullying in the last 5 years and revealed an average cyberbullying perpetration rate of 25.03%, ranging from 6.0 to 46.3%, while the average victimization was 33.08%, ranging from 13.99 to 57.5%. The underlying reason for increases may be attributed to the rapid changing landscape of social media and, in recent years, the drastic increase in Internet penetration rates. With the rise in Internet access, youths have greater opportunities to participate in online activities, provided by emerging social media platforms.

Although our review aims to provide a broader picture of cyberbullying, it is well-noted in extant research that difficulties exist in accurately estimating variations in prevalence in different countries ( 23 , 83 ). Many reasons exist to explain this. The first largely relates poor or unclear definition of the term cyberbullying; this hinders the determination of cyberbullying victimization and perpetration ( 84 ). Although traditional bullying behavior is well-defined, the definition cannot directly be applied to the virtual environment due to the complexity in changing online interactions. Without consensus on definitions, measurement and cyberbullying types may vary noticeably ( 83 , 85 ). Secondly, the estimation of prevalence of cyberbullying is heavily affected by research methods, such as recall period (lifetime, last year, last 6 months, last month, or last week etc.), demographic characteristics of the survey sample (age, gender, race, etc.), perspectives of cyberbullying experiences (victims, perpetrators, or both victim and perpetrator), and instruments (scales, study-specific questions) ( 23 , 84 , 86 ). The variety in research tools and instruments used to assess the prevalence of cyberbullying can cause confusion on this issue ( 84 ). Thirdly, variations in economic development, cultural backgrounds, human values, internet penetration rates, and frequency of using social media may lead to different conclusions across countries ( 87 ).

Acknowledging the Conflicting Role of the Identified Risk Factors With More Research Needed to Establish the Causality

Although this review has identified many personal and situational factors associated with cyberbullying, the majority of studies adopted a cross-sectional design and failed to reveal the causality ( 21 ). Nevertheless, knowledge on these correlational relationships provide valuable insights for understanding and preventing cyberbullying incidents. In terms of gender differences, females are believed to be at a higher risk of cyberbullying victimization compared to males. Two reasons may help to explain this. First, the preferred violence behaviors between two genders. females prefer indirect harassment, such as the spreading of rumors, while males tend toward direct bullying (e.g., assault) ( 29 ) and second, the cultural factors. From the traditional gender perspective, females tended to perceive a greater risk of communicating with others on the Internet, while males were more reluctant to express fear, vulnerability and insecurity when asked about their cyberbullying experiences ( 46 ). Females were more intolerant when experiencing cyberstalking and were more likely to report victimization experiences than males ( 13 ). Meanwhile, many researchers suggested that females are frequent users of emerging digital communication platforms, which increases their risk of unpleasant interpersonal contact and violence. From the perspective of cultural norms and masculinity, the reporting of cyberbullying is also widely acknowledged ( 37 ). For example, in addition, engaging in online activities is also regarded as a critical predictor for cyberbullying victimization. Enabled by the Internet, youths can easily find potential victims and start harassment at any time ( 49 ). Participating in online activities directly increases the chance of experiencing cyberbullying victimization and the possibility of becoming a victim ( 36 , 45 ). As for age, earlier involvement on social media and instant messaging tools may increase the chances of experiencing cyberbullying. For example, in Spain, these tools cannot be used without parental permission before the age of 14 ( 55 ). Besides, senior students were more likely to be more impulsive and less sympathetic. They may portray more aggressive and anti-social behaviors ( 55 , 72 ); hence senior students and students with higher impulsivity were usually more likely to become cyberbullying perpetrators.

Past experiences of victimization and family-related factors are another risk for cyberbullying crime. As for past experiences, one possible explanation is that young people who had experienced online or traditional school bullying may commit cyberbullying using e-mails, instant messages, and text messages for revenge, self-protection, or improving their social status ( 35 , 42 , 49 , 55 ). In becoming a cyberbullying perpetrator, the student may feel more powerful and superior, externalizing angry feelings and relieving the feelings of helplessness and sadness produced by past victimization experiences ( 51 ). As for family related factors, parenting styles are proven to be highly correlated to cyberbullying. In authoritative families, parents focus on rational behavioral control with clear rules and a high component of supervision and parental warmth, which have beneficial effects on children's lifestyles ( 43 ). Conversely, in indulgent families, children's behaviors are not heavily restricted and parents guide and encourage their children to adapt to society. The characteristics of this indulgent style, including parental support, positive communication, low imposition, and emotional expressiveness, possibly contribute to more parent-child trust and less misunderstanding ( 75 ). The protective role of warmth/affection and appropriate supervision, which are common features of authoritative or indulgent parenting styles, mitigate youth engagement in cyberbullying. On the contrary, authoritarian and neglectful styles, whether with excessive or insufficient control, are both proven to be risk factors for being a target of cyberbullying ( 33 , 76 ). In terms of geographical location, although several studies found that children residing in urban areas were more likely to be cyberbullying victims than those living in rural or suburban areas, we cannot draw a quick conclusion here, since whether this difference attributes to macro-level differences, such as community safety or socioeconomic status, or micro-level differences, such as teacher intervention in the classroom, courses provided, teacher-student ratio, is unclear across studies ( 61 ). An alternative explanation for this is the higher internet usage rate in urban areas ( 49 ).

Regarding health conditions, especially mental health, some scholars believe that young people with health problems are more likely to be identified as victims than people without health problems. They perceive health condition as a risk factor for cyberbullying ( 61 , 63 ). On the other hand, another group of scholars believe that cyberbullying has an important impact on the mental health of adolescents which can cause psychological distress consequences, such as post-traumatic stress mental disorder, depression, suicidal ideation, and drug abuse ( 70 , 87 ). It is highly possible that mental health could be risk factors, consequences of cyberbullying or both. Mental health cannot be used as standards, requirements, or decisive responses in cyberbullying research ( 13 ).

The Joint Effort Between Youth, Parents, Schools, and Communities to Form a Cyberbullying-Free Environment

This comprehensive review suggests that protecting children and adolescents from cyberbullying requires joint efforts between individuals, parents, schools, and communities, to form a cyberbullying-free environment. For individuals, young people are expected to improve their digital technology capabilities, especially in the use of social media platforms and instant messaging tools ( 55 ). To reduce the number of cyberbullying perpetrators, it is necessary to cultivate emotional self-regulation ability through appropriate emotional management training. Moreover, teachers, counselors, and parents are required to be armed with sufficient knowledge of emotional management and to develop emotional management capabilities and skills. In this way, they can be alert to the aggressive or angry emotions expressed by young people, and help them mediate any negative emotions ( 45 ), and avoid further anti-social behaviors ( 57 ).

For parents, styles of parenting involving a high level of parental involvement, care and support, are desirable in reducing the possibility of children's engagement in cyberbullying ( 74 , 75 ). If difficulties are encountered, open communication can contribute to enhancing the sense of security ( 73 ). In this vein, parents should be aware of the importance of caring, communicating and supervising their children, and participate actively in their children's lives ( 71 ). In order to keep a balance between control and openness ( 47 ), parents can engage in unbiased open communication with their children, and reach an agreement on the usage of computers and smart phones ( 34 , 35 , 55 ). Similarly, it is of vital importance to establish a positive communication channel with children ( 19 ).

For schools, a higher priority is needed to create a safe and positive campus environment, providing students with learning opportunities and ensuring that every student is treated equally. With a youth-friendly environment, students are able to focus more on their academic performance and develop a strong sense of belonging to the school ( 79 ). For countries recognizing collectivist cultural values, such as China and India, emphasizing peer attachment and a sense of collectivism can reduce the risk of cyberbullying perpetration and victimization ( 78 ). Besides, schools can cooperate with mental health agencies and neighboring communities to develop preventive programs, such as extracurricular activities and training ( 44 , 53 , 62 ). Specifically, school-based preventive measures against cyberbullying are expected to be sensitive to the characteristics of young people at different ages, and the intersection of race and school diversity ( 29 , 76 ). It is recommended that school policies that aim to embrace diversity and embody mutual respect among students are created ( 26 ). Considering the high prevalence of cyberbullying and a series of serious consequences, it is suggested that intervention against cyberbullying starts from an early stage, at about 10 years old ( 54 ). Schools can organize seminars to strengthen communication between teachers and students so that they can better understand the needs of students ( 61 ). In addition, schools should encourage cyberbullying victims to seek help and provide students with opportunities to report cyberbullying behaviors, such as creating online anonymous calls.

Conclusions and Limitations

The comprehensive study has reviewed related research on children and adolescents cyberbullying across different countries and regions, providing a positive understanding of the current situation of cyberbullying. The number of studies on cyberbullying has surged in the last 5 years, especially those related to risk factors and protective factors of cyberbullying. However, research on effective prevention is insufficient and evaluation of policy tools for cyberbullying intervention is a nascent research field. Our comprehensive review concludes with possible strategies for cyberbullying prevention, including personal emotion management, digital ability training, policy applicability, and interpersonal skills. We highlight the important role of parental control in cyberbullying prevention. As for the role of parental control, it depends on whether children believe their parents are capable of adequately supporting them, rather than simply interfering in their lives, restricting their online behavior, and controlling or removing their devices ( 50 ). In general, cyberbullying is on the rise, with the effectiveness of interventions to meet this problem still requiring further development and exploration ( 83 ).

Considering the overlaps between cyberbullying and traditional offline bullying, future research can explore the unique risk and protective factors that are distinguishable from traditional bullying ( 86 ). To further reveal the variations, researchers can compare the outcomes of interventions conducted in cyberbullying and traditional bullying preventions simultaneously, and the same interventions only targeting cyberbullying ( 88 ). In addition, cyberbullying also reflects a series of other social issues, such as personal privacy and security, public opinion monitoring, multinational perpetration and group crimes. To address this problem, efforts from multiple disciplines and novel analytical methods in the digital era are required. As the Internet provides enormous opportunities to connect young people from all over the world, cyberbullying perpetrators may come from transnational networks. Hence, cyberbullying of children and adolescents, involving multiple countries, is worth further attention.

Our study has several limitations. First, national representative studies are scarce, while few studies from middle and low income countries were included in our research due to language restrictions. Many of the studies included were conducted in schools, communities, provinces, and cities in high income countries. Meanwhile, our review only focused on victimization and perpetration. Future studies should consider more perspectives, such as bystanders and those with the dual identity of victim/perpetrator, to comprehensively analyze the risk and protective factors of cyberbullying.

Data Availability Statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author/s.

Author Contributions

SH, CZ, RE, and WZ conceived the study and developed the design. WZ analyzed the result and supervised the study. CZ and SH wrote the first draft. All authors contributed to the article and approved the submitted version.

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.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2021.634909/full#supplementary-material

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Peer-reviewed

Research Article

The impact of cyberbullying on mental health outcomes amongst university students: A systematic review

Contributed equally to this work with: Aahan Arif, Muskaan Abdul Qadir

Roles Conceptualization, Data curation, Methodology, Writing – original draft

Affiliations Medical College, Aga Khan University Hospital, Karachi, Pakistan, Research & Development Wing, Society for Promoting Innovation in Education, Aga Khan University Hospital, Karachi, Pakistan

Roles Conceptualization, Data curation, Writing – original draft

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Department of Surgery, Division of Thoracic Surgery, JFK University Medical Center, Hackensack Meridian School of Medicine, Edison, New Jersey, United States of America

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Nursing and Midwifery, Aga Khan University Hospital, Karachi, Pakistan

• Aahan Arif, 
• Muskaan Abdul Qadir, 
• Russell Seth Martins, 
• Hussain Maqbool Ahmed Khuwaja

• Published: November 13, 2024
• https://doi.org/10.1371/journal.pmen.0000166
• Peer Review
• Reader Comments

Cyberbullying is increasingly prevalent globally, particularly among young individuals. Cybervictims may be at an increased risk of adverse psychological outcomes. This systematic review aims to summarize the mental health effects of cyberbullying among college and university students. A systematic search of PubMed, Cochrane, and Embase databases was performed to identify studies reporting mental health effects of cybervictimization among college/university students until April 15, 2023. Risk of bias assessment was conducted using the National Institute of Health (NIH) tool. The review is registered on PROSPERO (CRD42023429187). Thirty-two studies involving 29,593 students were included. Depression showed a significant association with cyber-victimization in 16/20 studies (prevalence: 15–73%). Anxiety was significant in 12/15 studies (27–84.1%), stress in 3/3 studies (32–75.2%), and suicidal behavior in 4/9 studies (2–29.9%). Cybervictimization weakly but significantly correlated with lower self-esteem in 4 out of 6 studies (r = -0.152 to -0.399). Fear of perpetrators was reported in 2 out of 2 studies (12.8–16%), while decreased academic concentration/productivity was found in two studies (9–18%). Cybervictims were more likely to engage in substance abuse (adjusted odds ratio: 2.37 [95% confidence interval: 1.02–5.49]; p = 0.044). The majority of articles were of good quality (22/32). This review demonstrates a high prevalence of adverse mental health outcomes among cybervictims, including depression, anxiety, stress, and suicidal behavior. Based on these findings, we recommend that institutions of higher education worldwide introduce zero tolerance policies against cyberbullying, implement screening processes to identify affected students, and provide psychological therapy within their institutions.

Citation: Arif A, Qadir MA, Martins RS, Khuwaja HMA (2024) The impact of cyberbullying on mental health outcomes amongst university students: A systematic review. PLOS Ment Health 1(6): e0000166. https://doi.org/10.1371/journal.pmen.0000166

Editor: Wenjie Duan, East China University of Science and Technology, CHINA

Received: March 17, 2024; Accepted: September 28, 2024; Published: November 13, 2024

Copyright: © 2024 Arif et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data generated and analyzed during this study are included in this published article.

Funding: The authors declare that they have no source of funding.

Competing interests: The authors declare that they have no competing interests.

Introduction

With the increasing popularity of social media in the past decade, bullying has found its way into the digital sphere. Cyberbullying, defined as bullying via electronic means [ 1 ], has become increasingly prevalent across the globe, with more than half of adults in the United States (US) with access to the internet having had a cyberbullying experience [ 2 ].

Bullying is recognized as a global public health issue, since individuals exposed to bullying are more likely to develop mental health problems [ 3 ]. While cyberbullying may be seen as an extension of traditional bullying, its impact on mental health has the potential to be far more devastating given the anonymity and lack of supervision in the cyberspace [ 4 ]. This anonymity enables bullies to hide behind online aliases and continue to inflict psychological distress on their victims. In addition, an online platform magnifies the reach of a cyberbully, with subsequent mental health repercussions being potentially more far reaching than those observed in traditional bullying [ 5 ]. The issue of cyberbullying is of greater concern among university students as they spend considerable time on the internet and social media services and are thus at higher risk of cybervictimization [ 6 ]. Youth is a pivotal time in one’s development, as physical, emotional, and social changes during this period of transition can predispose individuals to developing mental health problems [ 7 ].

While cyberbullying has been explored amongst adults in general, the burden of this phenomena and consequent psychological distress remains to be comprehensively investigated amongst college and university students who represent a high-risk population [ 8 ]. Thus, in this systematic review, we aim to summarize the mental health outcomes associated with cybervictimization amongst university students.

The review was conducted in accordance with the PRISMA guidelines [ 9 ]. This systematic review is registered on PROSPERO (CRD42023429187).

Search strategy

We conducted a systematic search of MEDLINE, Cochrane, Embase, and Google Scholar on 15/04/2023 to identify articles discussing cybervictimization and mental health outcomes at the undergraduate or postgraduate university level ( Fig 1 ). The search string was divided into three components as follows: cyberbullying and associated synonyms, mental health and associated synonyms, and university and associated synonyms ( S1 Search strings ).

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https://doi.org/10.1371/journal.pmen.0000166.g001

Selection criteria

The following were the inclusion criteria required for articles to be shortlisted:

• Population: Students currently enrolled in undergraduate or postgraduate educational institutions.
• Intervention: Cyberbullying during undergraduate or postgraduate education.
• Control: No experience of cyberbullying.
• Outcome: Any adverse mental health outcomes.

Study selection

Articles identified using the search string were imported into Google Sheets, and duplicates were removed. The titles and abstracts of all the articles were screened as per the eligibility criteria by two members (AA and MAQ) of the research team. In cases of ambiguity, consensus was reached by a third member (RSM) of the team and the senior author (HMAK). Following this, a final list of articles meeting the selection criteria was created.

Quality assessment

Quality assessment was performed using the National Institutes of Health (NIH) tool for Quality Assessment of Observational Cohort and Cross-Sectional Studies [ 10 ]. Two authors (AA and MAQ) independently assessed the quality of each individual article. Criteria 9, 11, and 14 of the NIH tool [ 10 ] were deemed “major” criteria, while criteria 10, 12, and 13 were considered not applicable as they were for cohort studies. The remaining criteria were deemed “minor” criteria. Articles where all three major criteria were mentioned were deemed to be of good quality. Articles with two major criteria mentioned were deemed of fair or good quality based on minor criteria as per the authors’ discretion. The remaining articles were deemed poor. Following this, any discrepancies were discussed, and consensus was resolved in consensus with a third author (RSM) and the senior author (HMAK).

Data extraction and management

Data was extracted to Google Sheets on 10/06/2023 by two authors (AA and MAQ). Extracted parameters included author name, year of publication, country of publication, sample size, age of participants, cyberbullying measurements, and mental health outcomes measured. Moreover, statistical measures used to evaluate mental health outcomes as well as their associated results were also extracted.

Statistical analysis

Publication bias was assessed using R. version 4.3.0. Outcomes where prevalences was available for at least three articles were included. To evaluate outcomes, the Free-man Turkey double arcsine transformation was utilized, with subsequent generation of funnel plots ( S1 – S7 Figs ). Funnel plots were then tested for statistical evidence of bias using the Begg funnel plot test.

Study characteristics

A total of 32 articles, spanning 2010–2023, met the selection criteria and were included in the systematic review ( Fig 1 ). Characteristics of the included studies are shown in Table 1 . A total of 29,593 students, with mean ages ranging from 19.55–23.79 years [ 11 , 12 ], were included across the 32 articles. The commonest countries of origin of the articles were the US [ 11 , 13 – 24 ] (n = 13), Spain [ 25 – 28 ] (n = 4), and Canada [ 12 , 24 , 29 ] (n = 3). Sample sizes ranged from 107 to 6740 participants [ 22 , 30 ]. Of the 32 articles, 23 utilized pre-existing questionnaires from the literature [ 11 , 12 , 16 – 19 , 22 – 28 , 31 – 35 ] while the remainder used self-developed tools. The percentage of male students ranged from 19.8–68.7% [ 25 , 36 ].

https://doi.org/10.1371/journal.pmen.0000166.t001

Prevalence of cybervictimization

The prevalence of cybervictimization ranged from 6.9% to 84.3% [ 12 , 24 ]. When comparing prevalence between genders, 4 articles [ 19 , 30 , 32 , 35 ] found cybervictimization to be significantly more common amongst female students.

Mental health outcomes

The commonest reported mental health outcomes were depression [ 11 , 12 , 14 – 19 , 21 , 23 , 26 , 27 , 31 – 35 , 37 – 39 ] (n = 20 articles), anxiety [ 16 – 20 , 23 , 24 , 26 , 27 , 31 – 33 , 38 – 40 ] (n = 15 articles), and suicidality [ 16 , 21 , 27 , 29 , 34 , 36 , 37 , 41 , 42 ] (n = 9 articles). Among the 20 articles discussing depression, 16 articles [ 11 , 12 , 14 , 16 – 19 , 23 , 26 , 27 , 33 – 35 , 37 – 39 ] found that cybervictimization was significantly associated with the development of depression ( Table 2 ). Cybervictimization was significantly associated with the development of anxiety in 12 articles [ 16 – 20 , 23 , 26 , 27 , 33 , 38 – 40 ] and suicidality in 4 [ 16 , 27 , 34 , 37 ] articles. Cybervictimization was found to be associated with greater psychological symptoms (e.g., distress, excessive rumination, loneliness, etc.) in 4 studies [ 16 , 26 , 31 , 36 ], lower self-esteem in 4 articles [ 12 , 17 , 28 , 39 ], higher stress in 3 studies [ 27 , 33 , 38 ], internet/social media addiction in 2 articles [ 39 , 40 ], and overall poorer mental well-being in 2 articles [ 32 , 33 ]. A comprehensive account of the statistical measures used in each individual study is shown in ( S1 Table ) .

https://doi.org/10.1371/journal.pmen.0000166.t002

Out of the 32 articles, 22 were deemed to be of good quality [ 11 , 14 – 17 , 20 , 22 , 23 , 25 – 28 , 31 , 33 – 40 , 42 ], 8 of fair [ 12 , 13 , 18 , 19 , 24 , 29 , 30 , 32 ], and 2 of poor quality [ 21 , 41 ] ( S1 Table ) . Criteria 1 11–42, 4, 11–19, 21–31, 33, 34, 36–42, 9 [ 11 – 20 , 23 – 39 , 42 ], 11 [ 11 , 12 , 14 – 20 , 22 , 23 , 25 – 28 , 30 – 40 , 42 ], and 14 [ 11 , 14 – 17 , 20 , 23 – 28 , 31 , 33 – 40 , 42 ] of the NIH tool [ 10 ] were met by more than 50% of articles. Criteria 9 referred to the validation of the study exposure questionnaire [ 10 ] and was met by 28 articles [ 11 – 20 , 23 – 39 , 42 ]. Criteria 11 referred to the validation of the study outcome questionnaire [ 10 ] and was met by 27 articles [ 11 , 12 , 14 – 20 , 22 , 23 , 25 – 28 , 30 – 40 , 42 ].

Publication bias

A total of seven outcomes (anger, anxiety, depression, lack of concentration/loss of productivity, sadness, stress, and suicidality) across eleven articles were analyzed for potential publication bias [ 13 , 16 , 18 , 21 , 24 , 27 , 29 , 30 , 33 , 41 , 42 ]. Strong evidence of publication bias was found when evaluating anxiety (p = 0.0415). The remainder of outcomes demonstrated no study publication bias ( S1 – S7 Figs ).

The current digital landscape has sparked an interest in the widespread mental health impact of cyberbullying. Research, however, has largely focused on adolescents and high school students, resulting in a scarcity of literature regarding university students. Even the handful of studies conducted previously on the topic are by and large unstandardized, with articles varying considerably in terms of participants’ sociodemographic characteristics. To our knowledge, ours is the first-ever systematic review on adverse mental health outcomes associated with cyberbullying among university students.

The prevalence of cybervictimization was found to vary across studies from 6.9% to 84.3% [ 3 , 24 ]. This wide variation may be attributed to the lack of a uniform definition of cyberbullying. While the term may seem self-explanatory, cyberbullying encompasses a range of online behaviors, making it difficult to define the term operationally. In addition, a variety of different survey instruments were used to measure cyberbullying across studies, with twelve of the articles employing a self-designed questionnaire [ 13 , 14 , 20 , 21 , 29 , 30 , 36 , 38 – 42 ]. Moreover, there were differences seen in the amount and frequency of negative exposure that would be required to qualify as cyberbullying. For instance, some articles considered exposures within the last 12 months to meet the criteria of cyberbullying [ 17 ], some within the last 6 months [ 30 ], and some only in the last 2 months [ 25 ]. These discrepancies compound the ambiguity of the term and allow perpetrators to continue their harmful actions without being held accountable.

Students who are targeted may be unsure if their experience qualifies as cyberbullying and thus may not report it. When victims are unable to recognize and report their experience as abuse, they are susceptible to feelings of shame and guilt, which not only takes a toll on their mental health but also often allows victimization to continue [ 92 ]. Standardization of the definition of cyberbullying would allow for proper identification of students at risk, as well as more consistent reporting.

Furthermore, literature has demonstrated the impact of cultural contexts on the perception and response to bullying, where western cultures were found to be more forthcoming and receptive towards the entity [ 93 ]. These results are not dissimilar to our findings, where certain outcomes such as anger and depressive symptoms were seen to be higher amongst eastern regions [ 30 , 32 ]. Thus, it may be possible that increased awareness and openness to cybervictimization may enable improved coping and reduced development of outcomes in certain geographic regions, however, further research is necessitated to warrant this assumption. To counter the alarming rates of cyberbullying among students, it is also essential for university administrations to design efficient and confidential reporting systems and equip their students with the insight to recognize cyberbullying. This will enable students to report incidents without guilt or fear of criticism.

Our results show that depression and anxiety are the most frequent adverse mental health outcomes reported among cybervictims. This finding is consistent with similar studies conducted amongst adolescents and teenagers [ 94 ], which further reaffirms the need for implementing interventions across all age groups. Though interventions have been studied extensively at the adolescent level; there is a significant lack of literature in the setting of higher education [ 95 ]. Literature has demonstrated that interventions in the university setting have included interventional videos, zero-tolerance policies, and cyberbullying reporting systems however limited research has been conducted on the effectiveness of such interventions [ 46 , 47 ]. Furthermore, barriers towards intervention access are difficult to address, with studies finding university students to be apprehensive when seeking help due to perceptions of cyberbullying as a “juvenile” issue [ 96 ]. As such, it is imperative that further research is conducted to determine systemic barriers towards intervention access, and the impact of a wider array of interventions in the higher education setting. In addition to primary interventions to reduce the prevalence of cyberbullying across universities, targeted psychological interventions can be implemented for individuals who are already experiencing these adverse effects to also allow for tertiary prevention of outcomes. Counselling services have been prevalent amongst institutes of tertiary education, with research demonstrating positive impact towards mental and academic outcomes amongst university students [ 97 , 98 ]. Thus, targeted counselling amongst victims of cyberbullying may enable the development of effective coping strategies, although further research is warranted to substantiate this assumption. This would help alleviate the burden of mental health issues as well as help improve the overall wellbeing among university students.

Our review has several limitations. Firstly, the tools and definitions used to define and measure cyberbullying and mental health outcomes differed across studies and precluded statistical pooling of data. As such, there is considerable heterogeneity across the dataset thus limiting the generalizability of the data and potentially underestimating or overestimating of the prevalences of mental health outcomes. This heterogeneity further signifies the need to establish a uniform framework to identify and counteract cybervictimization. Despite this limitation, however, our study is the first systematic review to evaluate the impact of cyberbullying in developing mental health outcomes, thus highlighting a critical avenue for further research. Secondly, only 22 out of the 32 included articles 11,14–17,20,22,23,25–28,31,33–37,60,62,63,73] were deemed to be of good quality, with the rest being fair or poor, with such articles failing to validate their study questionnaires. Such lack of validation may result in a lower quality of evidence, due to reduced reliability of results and a potential increase in study bias preventing inference of study outcomes. These findings were manifested in our review, where ten articles were found to be fair or poor, thus increasing the potential for heterogeneity and reduced validity of the conclusions drawn. Similarly, the majority of articles included in this study were of a cross-sectional study design, further preventing accurate inference of causality in the relationship between cybervictimization and mental health outcomes. Due to these limitations, it is possible that the conclusions drawn within this review may be over or under-estimated. As such, it is imperative that further research is conducted emphasizing a longitudinal and robust approach, thus allowing for a more accurate assessment of mental health outcomes. Lastly, elements of recall, social desirability, and publication bias may have been present owing to the cross-sectional design and sensitive nature of the studies. Our results demonstrated that publication bias was only found in one outcome (anxiety), however, due to the limited number of articles evaluating outcomes, it is possible that further publication is present. Thus, it is imperative that great nuance is employed when interpreting our results, however, the studies included in this review were conducted across a wide range of settings, which increases the generalizability of our conclusions.

Conclusions

In this review, we demonstrate that cyberbullying has an immense psychological burden on university students, increasing the risk of depression, anxiety, stress, and even suicidal behaviour. We recommend that institutions of higher education across the globe enact zero-tolerance policies regarding cyberbullying, implement accessible reporting systems among student bodies, develop anonymous mental health screening programs for students, and provide appropriate psychological care to those who experience cyberbullying.

Supporting information

S1 checklist. this file includes the prisma checklist used in the synthesis of the systematic review..

https://doi.org/10.1371/journal.pmen.0000166.s001

S1 Search strings. This file includes the search strings used in the review of literature.

https://doi.org/10.1371/journal.pmen.0000166.s002

S1 Table. This file includes the supplementary tables that are relevant to the body of the manuscript.

https://doi.org/10.1371/journal.pmen.0000166.s003

S1 Data. This file includes the data availability tables that are relevant to data curation in the systematic review.

https://doi.org/10.1371/journal.pmen.0000166.s004

S1 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

https://doi.org/10.1371/journal.pmen.0000166.s005

S2 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

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S3 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

https://doi.org/10.1371/journal.pmen.0000166.s007

S4 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

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S5 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

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S6 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

https://doi.org/10.1371/journal.pmen.0000166.s010

S7 Fig. This file includes a supplementary figure relevant to the main body of the manuscript.

https://doi.org/10.1371/journal.pmen.0000166.s011

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Understanding Bullying and Cyberbullying Through an Ecological Systems Framework: the Value of Qualitative Interviewing in a Mixed Methods Approach

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Recognized as complex and relational, researchers endorse a systems/social-ecological framework in examining bullying and cyberbullying. According to this framework, bullying and cyberbullying are examined across the nested social contexts in which youth live—encompassing individual features; relationships including family, peers, and educators; and ecological conditions such as digital technology. 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 such as motivations and dilemmas, which might not be accessed through quantitative studies. Through use of a longitudinal and multi-perspective mixed methods study, the purpose of the current paper is to demonstrate the ways qualitative interviews contextualize quantitative findings and to present novel discussion of how qualitative interviews explain and enrich the quantitative findings. The following thematic areas emerged and are discussed: augmenting quantitative findings through qualitative interviews, contextualizing new or rapidly evolving areas of research, capturing nuances and complexity of perspectives, and providing moments for self-reflection and opportunities for learning.

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A Comparison of Traditional Victims, Cyber Victims, Traditional-Cyber Victims, and Uninvolved Adolescents: A Social-Ecological Framework

A qualitative meta-study of youth voice and co-participatory research practices: informing cyber/bullying research methodologies, a qualitative exploration of college students’ perceptions of cyberbullying.

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Introduction

Bullying and cyberbullying are increasingly recognized as complex phenomena that are considered relationship problems (Mishna et al., 2021a ; Pepler et al., 2010 ; Pepler, 2006 ; Spears et al., 2009 ). Appreciating that individuals are embedded in and both shape and are shaped by systems of relationships (Bronfenbrenner & Morris, 2007 ), researchers often endorse an ecological systems framework as paramount and comprehensive in examining bullying and cyberbullying phenomena Footnote 1 (Espelage, 2014 ; Newman et al., 2018 ; Thornberg, 2015 , 2018 ). According to this approach, individuals are embedded in and affected by interconnected and layered systems (Bronfenbrenner, 1979 , 1992 ). Children’s social-emotional development at school is consequently shaped not only by children’s relationships with their teachers and peers, but also by the interconnections between these relationships and the other layers of social ecology, all of which are considered to contribute to social behavioral patterns (O'Moore & Minton, 2005 ). Bullying and cyberbullying are examined across the nested social contexts in which youth live—encompassing individual features, peer relationships, school, family, and ecological climate such as societal norms and conditions as well as online technology (Cross et al., 2015 ; Johnson, 2010 ; Nesi et al., 2018 ). An ecological systems framework is considered an overarching approach that many theories complement and within which they fit (Bauman & Yoon, 2014 ).

The purpose of the current paper is to demonstrate the contributions of qualitative research in understanding the phenomena of bullying and cyberbullying and enriching and complementing the findings of quantitative methodology (Creswell & Creswell, 2018 ). Qualitative inquiry of bullying and cyberbullying provides a research methodology capable of bringing to the fore salient discourses and otherwise invisible nuances that might not be accessed through quantitative studies (Dennehy et al., 2020 ).

There are advantages to utilizing mixed methods in conducting research on various topics including cyberbullying (Creswell & Creswell, 2018 ). When engaging with complex phenomena such as cyberbullying, conceptual and methodological multiplicity offers distinct insights into research questions (McKim, 2017 ; Thornberg, 2011 ). When quantitative and qualitative research are used in combination, it is possible to obtain deeper as well as more comprehensive and accurate understanding of young people’s experiences, which increases the likelihood of informing strategies and responses that can effectively address the needs of children and adolescents (Crivello et al., 2009 ; Darbyshire et al., 2005 ; Fevre et al., 2010 ). The quality of findings may be strengthened when researchers use mixed methods because the data are triangulated (Crivello et al., 2009 ). Data generated through diverse research methods can both complement and contradict each other, which offers an opportunity to better understand the complexities of cyberbullying (Hemming, 2008 ). While quantitative approaches strive for objectivity by examining general concepts, such as cyberbullying, and parceling those concepts into specific, concrete, and understandable behaviors (Fevre et al., 2010 ), qualitative interviews give voice to children and youth, enabling them to express their thoughts and feelings about themselves, their relationships, environments, and the world in which they live (Mishna et al., 2004 ; Chaumba, 2013 ; Dennehy et al., 2020 ; Patton et al., 2017 ).

Through qualitative interviewing, we can step outside the bounds of adult thinking, gaining insights and discovering unanticipated differences in the perceptions of adults and children (Dennehy et al., 2020 ; O’Farrelly, 2021 ). To understand the phenomena of bullying and cyberbullying and inform effective prevention and intervention strategies, it is argued, children’s own views, “are at the heart of these efforts” (O’Farrelly, 2021 , p. 43). Thus, we present findings from the qualitative component of our Canadian federally funded mixed methods longitudinal study on cyberbullying from the perspectives of school-aged youth and their parents and teachers, entitled Motivations for Cyber Bullying: A Longitudinal and Multi-Perspective Inquiry Footnote 2 (Mishna et al., 2016 ).

Background Study Description

The objectives of our longitudinal mixed methods study were to (1) explore youth experiences and perspectives and their parents’ and teachers’ conceptions of cyberbullying; (2) explore how youth and adults view the underlying motivations for cyberbullying; (3) document the prevalence rates of cyberbullying victimization, witnessing, and perpetration; (4) identify risk and protective factors for cyberbullying involvement; and (5) explore social, mental health, and health consequences of cyberbullying among children and youth aged 9 to 18 (grades 4, 7, and 10) over 3 years.

In addressing the objectives, we use an explanatory sequential mixed methods design (Creswell & Creswell, 2018 ). The study comprised a 2-phase data collection approach in which we first collected the quantitative data and then used findings from the first phase to design and plan the qualitative data phase. The quantitative findings informed both our selection of interview participants and the focus of questions we wanted to explore further in the interviews. The overall intent of the qualitative interviews was to enrich and expand upon the quantitative findings and perhaps generate and explore similarities and contradictions (Creswell & Creswell, 2018 ). In the current paper, we briefly review key quantitative findings. We then discuss the qualitative findings and how they provide more depth and insight and demonstrate the complexities of bullying and cyberbullying motivations, behaviors, and attitudes. In so doing, we present novel discussions of how the qualitative interviews augment the quantitative findings.

Participants

Three participant groups were included in the baseline study sample: (1) students in 4th ( n  = 160), 7th ( n  = 243), and 10th ( n  = 267) grades; (2) their teachers ( n  = 103); and (3) their parents ( n  = 246). A stratified random sampling strategy was utilized to select participants. First, a random sample of 19 schools was drawn from one of the largest school boards in North America. Schools were stratified into three categories of need (low, medium, and high) based on an index developed by the school board that ranked schools on external challenges to student achievement (Toronto District School Board, 2014 ). This stratification ensured representation of ethno-cultural and socioeconomic diversity—factors that potentially impact access to Information and Communication Technologies (ICTs), experiences of cyberbullying, and the manifestation of negative outcomes (Lenhart et al., 2015 ; Steeves & Marx, 2014 ). In year 3 of the study, 10 additional schools were recruited for participation to follow those students transitioning from elementary/middle school to middle/secondary school. A total of 29 schools participated in the study. All students in the selected grades at the original participating schools were invited to participate, as were their parents and teachers.

Participating students and their parents provided data in all 3 years of the study, while matching teachers provided data in year 1 only (as student participants’ teachers changed each year). All three participant groups completed quantitative questionnaire packages, and a sub-sample of each group participated in individual interviews. Quantitative data were collected from students and parents in each year of the study, while qualitative data were collected during years 1 and 3, to allow for enough time to elapse for changes in perceptions of cyberbullying to emerge.

Quantitative Measures and Analysis

In year 1, students completed a 45–60-min quantitative questionnaire package in the school setting, while parents completed a questionnaire package by mail. Questionnaires for teachers, which took approximately 45–60 min to complete, were administered in the participating schools. This study utilized several quantitative measures, including standardized measures and measures developed specifically for the study. Student, parent, and teacher surveys obtained information related to experiences with bullying/cyberbullying (Mishna et al., 2012 ; Unpublished Survey), socio-demographics, and Information and Communication Technology (ICT) use. Standardized measures assessing student mental health, health, social, and behavioral issues included Child Behavior Check List (Achenbach, 2001a ), Teacher Report Form (Achenbach, 2001b ), Youth Self Report Form (Achenbach, 2001c ), Self-Perception Profile for Children (Harter, 1985b ), Self-Perception Profile for Adolescents (Harter, 2012 ), Social Support Scale for Children (Harter, 1985a ), and Social Support Behaviors Scale (Vaux et al., 1987 ).

Descriptive analyses were conducted to calculate frequencies for categorical variables and means and standard deviations for continuous variables. We summarized socio-demographic variables among participants in each grade level (4, 7, 10). Items for each outcome scale (e.g., Social Support Scale for Children) were summed to calculate total or subscale scores for each measure.

Findings on Prevalence and Reporting

The quantitative findings in the larger study (Mishna et al., 2015 ) show that rates of cyber witnessing were higher than cyberbullying and victimization at each assessment. In year 1, 24.2 percent reported cyber witnessing, 10.7 percent cyber victimization, and 2.9 percent cyberbullying. In year 2, 21.5 percent reported cyber witnessing, 7.6 percent cyber victimization, and 1.6 percent cyberbullying. In year 3, 25.1 percent reported cyber witnessing, 10.8 percent cyber victimization, and 2.5 percent cyberbullying. Similarly, rates of witnessing traditional bullying were higher than perpetration and victimization at each assessment. In year 1, 53.0% reported witnessing traditional bullying, 23.5% victimization, and 7.8% perpetration. In year 2, 42.6% reported witnessing traditional bullying, 17.3% victimization, and 4.3% perpetration. In year 3, 35.7% reported witnessing traditional bullying, 19.2% victimization, and 5.4% perpetration (Mishna et al., 2015 ). Of note, nearly half of all students (48.3%), who reported cyberbullying involvement in our survey, reported that they had not told an adult about what was happening online (Mishna et al., 2015 ). Moreover, 69.5% of students reported that cyberbullying and physical bullying are equally serious, and 64.5% believed that cyberbullying and “real” life verbal bullying are also equally serious (Mishna et al., 2015 ). These quantitative results serve as a springboard for the following discussion of qualitative findings, demonstrating that qualitative interviews reveal nuanced similarities and differences in the views of adults and youth, elucidating important interconnections among the levels of the ecological system (Mishna et al., 2004 , 2009 ; Dennehy et al., 2020 ).

Qualitative Interview Data Collection and Analysis

Student participants in 4th grade ( n  = 20), 7th grade ( n  = 21), and 10th grade ( n  = 16) in the qualitative sub-sample were purposively selected for interviews from the larger quantitative sample, based on gender, grade, school need level, and whether they reported bullying/cyberbullying victimization, perpetration, or witnessing. After selecting student participants, their teachers ( n  = 30) and parents ( n  = 50) were invited to participate in interviews. Interviews lasted approximately 1 h, ranging in length from 30 to 90 min. All year 1 interviews (with students, parents, and teachers) took place in the school setting and utilized a semi-structured interview guide. Following preliminary analysis, this interview guide was refined for use in the year 3 follow-up phone interviews with the students and parents. Areas explored with students comprised understanding of cyberbullying and how it compares with traditional bullying, experiences of online aggression, and others’ attitudes and responses. Questions were informed by existing literature and the research team’s considerable experience. Parent and teacher interviews included questions on their awareness and understanding of cyberbullying, their child or student’s involvement in cyberbullying, links between cyber and traditional bullying, support, and their responses to cyberbullying.

Using a grounded theory inquiry, data were concurrently analyzed and theorized through constant comparison (Birks & Mills, 2015 ; Corbin & Strauss, 2008 ). Through this iterative process, the team used initial interview data and theoretical categories to inform and refine subsequent interview guides and data collection (Charmaz, 2014 ). The team members individually coded a portion of interviews to establish preliminary analytic focuses and inductively identify preliminary themes. Consistent with a grounded theory approach, no hypotheses guided data analysis and coders sought to bracket their biases through reflexive journaling and team discussions of assumptions (Corbin & Strauss, 2008 ). During team meetings, each interview was collectively coded, building upon, revising, and/or removing codes proposed by the initial coder. Emerging categories were developed and expanded. Axial coding promoted connections within and between categories and subcategories and enabled synthesis and explanation (Birks & Mills, 2015 ; Charmaz, 2014 ; Corbin & Strauss, 2008 ). Numerous preliminary codes were identified based on emerging themes that were generated and discussed. A holistic “middle-order” approach to coding resulted in a condensed number of initial codes (Saldaña, 2015 ). Axial coding was then used to identify connections within and between themes and subthemes (Birks & Mills, 2015 ; Charmaz, 2006 , 2014 ; Corbin & Strauss, 2008 ). Through this iterative process of open, holistic, and focused coding, key themes emerged related to the understanding of traditional and cyberbullying according to the perspectives of the students, parents, and teachers. Measures were employed to ensure trustworthiness and authenticity. Prolonged engagement over the 3 years of the study ensured thick descriptions of the youth and adult narratives (Lietz & Zayas, 2010 ). Rigor was established through documentation for auditing purposes (Padgett, 2008 ). Trustworthiness and transferability were further ensured through reflexive journaling, bracketing, and dense descriptions (Corbin & Strauss, 2008 ).

While we use examples from our published manuscripts derived from our study entitled, “Motivations of Cyberbullying,” in the current manuscript, we identify new thematic areas and demonstrate how our qualitative interviews complement our quantitative findings. In analyzing findings across the study publications and datasets, we have not previously drawn the conclusions. The unique contribution of the current manuscript is the use of findings of previous publications to generate broader conclusions about the benefits of a mixed-methods approach (qualitative interviews and quantitative survey data) that makes visible the connections across ecological systems levels.

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 perspectives, and providing moments for self-reflection and opportunities for learning.

Augmenting Quantitative Findings Through Qualitative Interviews

By examining process, context, and meaning for participants, qualitative methodology can augment quantitative findings. Quantitative methodology establishes outcomes and causal relationships and puts forth generalization and predictions (Yilmaz, 2013 ). Our background study which was a longitudinal multi-informant mixed methods study (Tashakkori et al., 1998 ) used grounded theory (Strauss & Corbin, 1998 ) and a longitudinal quantitative design to aid understanding of nuances related to cyberbullying (Mishna et al., 2009 ). In creating opportunities for the voices of young people to be heard (Carroll & Twomey, 2020 ; Gilgun & Abrams, 2002 ), qualitative methodology is especially useful for phenomena that are largely unstudied and/or rapidly evolving, such as cyberbullying, by explicating process and a holistic understanding and directions for future research (Mishna & Van Wert, 2013 ; Gilgun & Abrams, 2002 ).

In our paper, “Benchmarks and bellwethers in cyberbullying: The relational process of telling” Footnote 3 (Mishna et al., 2020 ), the qualitative analysis revealed relational processes among students that occurred when they considered whether to tell adults about their bullying and cyberbullying experiences. As noted above, almost half of the students who reported cyberbullying involvement relayed that they had not told an adult. Qualitative findings, however, exposed complex interactions that informed their decision-making processes. Reticent about speaking with adults, students turned to friends. It emerged that in addition to sharing, telling friends often served as a bellwether to gauge whether to proceed and report the situation to an adult. Often minimizing the severity of their ordeal, many students had decided against informing adults, frequently mentioning their concern about making a “big deal.” Participant interviews further revealed that media reports of high-profile cases involving cyberbullying can serve as benchmarks through which to assess the severity of their own personal experiences. The qualitative findings in our study helped to contextualize the quantitative data by unpacking and making visible the reasoning and contributing factors, thus increasing understanding of what informs youth’s decisions regarding whether and who to tell about cyberbullying involvement. By augmenting the quantitative data detailing the proportion of youth who do not tell adults, particulars attained through qualitative interview data help to inform and direct prevention and intervention strategies that are concrete and actionable for addressing the more challenging aspects of cyberbullying involvement and disclosure. In offering insights on the relational dynamics among peers and between youth and adults with respect to cyberbullying, the qualitative analysis gave voice to these interconnected layers of the youths’ ecological environment.

Contextualizing New or Rapidly Evolving Areas of Research

While cyberbullying is no longer considered a new phenomenon, the rapid development of technology is continually altering the cyber landscape, creating a need for perpetual knowledge generation (Odgers & Jensen, 2020 ; Rosa et al., 2019 ) and for evolving definitions, measurements, and responses (Spears et al., 2009 ). Moreover, rapid and ongoing technological advances create unique challenges for practitioners, policy makers, and researchers, in remaining current and responding to cyberbullying (George & Odgers, 2015 ; Jäger et al., 2010 ). With youth at the forefront of technological advances in many ways, qualitative methodology is well suited to elicit the experiences and perspectives of young people in promoting in-depth understanding of youth cultures, dynamics, and processes (Thornberg & Knutsen, 2011 ).

The data collection for our background study occurred between 2012 and 2014, during the early stages of attention to and research on sexting (sending and receiving sexually explicit images, videos, and text among youth). In the quantitative questionnaires, we included one question related to sexting for students in grades 7 and 10 and their parents and teachers. Our quantitative survey found that 15.6% of students in grades 7 and 10 had seen nude or sexual photos of friends, family, boyfriend, girlfriend, or other romantic partner online or over a cell phone. Furthermore, 27.8% of teachers had witnessed or were aware of their students viewing sexually explicit images, video, or text on cell phones at school. The data indicated that digital sending and receiving of sexually explicit images, video, or text was a new phenomenon among youth participants in grades 7 and 10 in a rapidly changing digital environment.

We did not explicitly inquire about sexting in the interviews with students, parents, and teachers. Rather, we asked participants about the students’ negative experiences with cyber technology. During analysis of the interview data, however, sexting emerged as a new and pertinent phenomenon among youth, which generated knowledge about rapidly evolving cyber dynamics that warranted further attention and inspired a paper entitled, “Gendered and sexualized bullying and cyberbullying: Spotlighting girls and making boys invisible” (Mishna et al., 2021b ). The qualitative interview data in this instance confirmed our quantitative findings on sexting among youth and allowed us to delve into the complex and nuanced ways participants articulated sexting behaviors along gender lines that both reinforced and were reinforced by gendered sociocultural norms and pressures. In student accounts, boys’ presence and participation in cyberbullying were frequently invisible, such as the non-consensual sharing of sexual images. Blamed for their poor choices, girls were spotlighted and their behavior problematized through negative characterizations. The participants’ focus on girls as responsible for the gendered cyberbullying and non-consensual sharing of images corresponds with how youth are typically educated about digital technologies through an “online safety model” with the focus on youth protecting themselves and avoiding “risky” activities (Johnson, 2015 ). As such, our findings provided context for this rapidly evolving environment that then allowed us to draw links between individual cyberbullying behaviors, understanding and articulation of these behaviors, and the broader influence of patriarchal structures (Mishna et al., 2021b ). The qualitative findings underscored the need to consider key factors that go beyond individual characteristics and behaviors and to develop education and prevention and intervention strategies that address sociocultural norms and values. The qualitative findings stimulated new research endeavors and collaborations with community organizations and academics.

Capturing Nuances and Complexity of Perspectives

Bullying and cyberbullying are exceedingly complex and must be studied within the contexts of the involved youth as well as within the larger social context of youth (Cross et al., 2015 ; Dennehy et al., 2020 ; Johnson & Puplampu, 2008 ; Sainju, 2020 ; Thornberg, 2011 ). An ecological systems framework is appropriate as it provides insight into the interconnected relationships among varying aspects and social layers of an individual’s world (Bronfenbrenner, 1979 ). While quantitative research considers and articulates context, qualitative interviews provide an occasion to engage with the richness of students’ perspectives, thoughts, and feelings about themselves and their social worlds (Mishna et al., 2004 ) and allow for a deeper understanding of youth culture and social processes from the vantage point of young people (Chaumba, 2013 ; Dennehy et al., 2020 ; Spears et al., 2009 ; Thornberg & Knutsen, 2011 ). Although qualitative studies are generally bound by a particular timeframe, participants bring their life histories and cumulative experiences to the research engagement (Phoenix et al., 2003 ), which can generate a fulsome and holistic understanding of cyberbullying, taking into consideration individual, family, peer, school, cyber, and sociocultural conditions over time.

Qualitative interview data allow for an interpretive approach that draws upon patterns of understanding, similarity, and contradiction, thereby teasing out underlying assumptions that shape how people define and assess experiences and phenomena such as bullying and cyberbullying (Mishna et al., 2020 , 2021a ). In our paper entitled “Looking Beyond Assumptions to Understand Relationship Dynamics in Bullying” Footnote 4 (Mishna et al., 2021a ), analysis of the qualitative interview data exposed persistent and pervasive assumptions about bullying linked to sociocultural norms and understanding of gender. These assumptions shaped participants’ understanding and conclusions of bullying and cyberbullying experiences, behavior, and motivations. Focusing on the visible hurt and injuries associated with physical bullying, participants tended to make comments such as “you’ll heal in a few days,” whereas they noted that with verbal bullying, the mental anguish “might stay for a long term.” This viewpoint that physical bullying was not a relationship problem appeared to be linked to gender stereotypes and social norms regarding the “natural” behavior of girls and boys. These gendered assumptions led participants to suggest that addressing bullying among girls was “complicated” and ongoing, whereas addressing physical bullying among boys was “simpler” and faster, a finding similar to that of Eriksen and Lyng ( 2018 ) who described participants’ descriptions of bullying among boys as “undramatic.” These assumptions appeared to preclude participants from discussing physical bullying among boys in a manner that acknowledged the physical bullying involvement as entrenched in relationship dynamics.

Qualitative interviewing provides an opportunity for participants to express their views and ideas when discussing the topic of interest which can elicit novel conclusions and nuances. As an example, at times, youth who claimed not to have involvement with cyberbullying may go on to describe situations that actually seemed to fit the definition of cyberbullying. In our Spotlighting Girls paper, many participant reports aligned with stereotypes regarding differences in how boys and girls bully others. These stereotypes were shared, however, even when they contradicted participants’ own experiences. For instance, similar to other research findings (Eriksen & Lyng, 2018 ), one participant described a boy as using “guilt trips” as a bullying tactic, yet described boys as only bullying physically. Consequently, relational aggression among boys often goes unnoticed and remains invisible. Similarly, the same behavior displayed by both girls and boys was discounted in boys and highlighted in girls. Boys’ behaviors were often not considered to be bullying because they were positioned as within the bounds of masculine gender norms. For example, one girl reported that “mostly girls, not boys,” bully “because boys would just go over and do some physical things... [Girls would] post embarrassing stuff about the person and do that kind of stuff” (p. 410). It is possible therefore that such actions by boys were not identified as bullying and thus underreported in the quantitative surveys while captured in the interviews. Discrepancies emerged in how cyberbullying had been reported in quantitative measures and how it was described in the interviews. This indicates that qualitative interviews can complement quantitative findings by revealing the complexities and ramifications of social experiences which are not reported in quantitative surveys.

The critical role of witnessing in bullying and cyberbullying is well documented (Salmivalli, 2010 , 2014 ; Spadafora et al., 2020 ; Volk et al., 2014 ). Social experiences related to witnessing are also complex, and bystander decision-making and responses impact both the process and outcomes of bullying incidents (Salmivalli et al., 2011 ). Qualitative research can offer youth the opportunity to explore and explain the motivations and factors they consider in determining whether to intervene, specifically the social costs and benefits of intervening (Spadafora et al., 2020 ). Our qualitative interviews similarly added youth voices concerning the dilemmas they faced in considering whether and how to respond based on emotional and contextual factors (Mishna et al., 2021b ), thus providing nuanced perspectives that serve to augment the quantitative findings related to bystander responses.

Providing Moments for Self-reflection and Opportunities for Learning

Qualitative methodologies are recognized as providing participants opportunities to self-reflect in the context of being listened to empathically (Birch & Miller, 2000 ; Wolgemuth et al., 2015 ). According to a systematic review of quantitative, qualitative, and mixed-methods studies conducted with children and adolescents, participation was mainly considered to be beneficial (Crane & Broome, 2017 ). Negative responses to participating in the research included feeling anxious and upset (Crane & Broome, 2017 ). Research indicates that despite describing negative effects of participating, children and youth reported that overall it was more positive to participate in the research (Crane & Broome, 2017 ) or described the emotional pain they experienced as beneficial in various ways, for example, as “emotionally cleansing” (Wolgemuth et al., 2015 , p. 366). The qualitative research process offers participants the opportunity to come to new understandings and can reveal evolving thoughts within participant narratives (Birch & Miller, 2000 ; Wolgemuth et al., 2015 ). Qualitative processes are iterative and involve probing questions that can prompt dynamic reflection by participants (Wolgemuth et al., 2015 ). Birch and Miller ( 2000 ) explain that they “use the term therapeutic to represent a process by which an individual reflects on, and comes to understand previous experiences in different—sometimes more positive—ways that promote a changed sense of self” (p. 190).

Recognizing the potential risks in research with children and youth (Mishna et al., 2004 ; Crane & Broome, 2017 ), we informed the students in our study of the possible risks should they decide to participate, such as the possibility that they would become upset as we were asking them about hurtful matters, and the limits to confidentiality. Anticipating that some of the questions could lead to a participant becoming distressed or disclosing potentially sensitive or upsetting information, we put in place a protocol (approved by the university and school board research ethics boards) to identify and offer support for students in distress (Mishna et al., 2016 ).

Corresponding with previous research, the reflexivity of sharing their narratives and views seemed to contribute to some participants coming to a different understanding of their experiences. Such reflection was evident in our interviews with students and their parents and teachers. When asked whether he had witnessed cyberbullying, for example, a boy reflected that only in being asked about cyberbullying in the interview did he recognize the behavior as cyberbullying: “When I think about it now, I actually did a few times. I didn’t feel that it’s cyber bullying, I wasn’t thinking that it’s a huge deal. It’s basically a few arguments between people on Facebook, like writing things about each other in public, not in private, chats.”

In another example, a parent reconsidered her views during the interview. This parent first commented that girls and women are “more vindictive” than boys and men, who, she explained, have “your spat, you get over it, and you move on.” After reflecting on her assumptions, she wondered how much of this widely held view of the behavior “is just media driven because I guess the victims that we see on the news, at least in Canada, have been girls, right?… but that doesn’t say that boys aren’t also being bullied.” Similarly, a girl contemplated her assumptions after first casting boys in a favorable light in contrast to girls. In commenting that girls bully each other because of appearance, she praised boys, “because usually they don’t tend to worry about those things...They’re proud of themselves, and they don’t pick on other people. They’re good with what they have.” After pondering these stated differences between boys and girls, this girl surmised, “I think it’s from when we were little because those Barbie dolls are super skinny. We wanted to have blonde hair, blue eyes, and be like Barbie. I think it’s just how maybe we were raised.” Another girl, who asserted that while cyberbullying occurred with equal frequency among boys and girls, added that it was not “a big thing” for boys, in contrast to girls who, “would show it off more, be like oh yah, blah, blah, blah.” Rather than concluding that this difference indicated that cyberbullying was not a big deal for boys, however, this girl attributed the difference between boys and girls to dominant masculinity norms. She asserted that “guys kind of hide it in more” and explained that “they don’t want to show that they’re weak because guys tend to be, they think that they’re very strong, kind of thing.” The evolving perspectives throughout this and the previous exchanges demonstrate the process of deepened understanding that can occur because of qualitative interviewing.

Such new understanding can inspire a desire to act and make change through community engagement. A girl explained that the research was the first time she had spoken with anyone about cyberbullying. This girl’s appraisal of her participation is consistent with findings in which participants may be motivated to take part in research for the opportunity to effect and advocate for change and help others (Cutcliffe & Ramcharan, 2002 ; Wolgemuth et al., 2015 ). She remarked that participating had been a helpful process which led her to,

think of different ways that I could help someone else if I see it happening… Just talking about it makes you think about what could cause it, what could make someone bully someone else. It makes you realize how it could make someone feel. Also, talking about how there isn’t really a support system at school. It makes me want to go and talk to someone to organize it, because it does happen a lot and I know it affects a lot of people

The inclusion of qualitative interviews in mixed methods research brings forth new information about content, process, and meaning that is otherwise not visible. By engaging youth voices as well as adult perspectives through both quantitative measures and qualitative interviews in the mixed methods study discussed in this manuscript, entitled Motivations for Cyberbullying, understanding of bullying and cyberbullying was advanced, thus enriching the quantitative methodology. The findings of the interviews extended knowledge related to bullying and cyberbullying in the following ways, which can inform “bottom-up research and intervention efforts” (Dennehy et al., 2020 , p. 10): augmenting quantitative findings, contextualizing new or rapidly evolving areas of research, capturing nuances and complexity of perspectives, and providing moments for self-reflection and opportunities for learning.

Qualitative research constitutes a significant venue through which to amplify the voices of children and youth (Dennehy et al., 2020 ) and ensures that children and youth’s experiences of the world are represented in understanding social phenomena (Mishna et al., 2004 ; Carroll & Twomey, 2020 ; Chaumba, 2013 ; Dennehy et al., 2020 ; Patton et al., 2017 ). According to Dennehy and colleagues ( 2020 ), engaging youth as co-researchers in cyberbullying research may enhance efforts to ethically and earnestly amplify youth voices. A synthesis by Elsaesser et al. ( 2017 ) supports the view that focusing on collaboratively working with youth to understand and safely navigate the cyber world through education and empowerment is more effective than interventions aimed at restricting ICT use without involving youth. Through quantitative measures and qualitative interviews, our mixed methods study examined participant perspectives regarding bullying and cyberbullying on the various ecological systems levels across the students’ lives. The use of mixed methods facilitated a dialogue between the participant responses to both methodologies, thus highlighting the salience of the overlapping influence and interactions among the systems levels. Such complex and nuanced understanding is necessary to inform meaningful prevention and intervention strategies to address bullying and cyberbullying.

According to the United Nations Convention on the Rights of the Child (Assembly UG, 1989 ), children and youth have the right to discuss their views and experiences. The Convention states that all children have the right to protections, provisions, participation, and non-discrimination (Assembly UG, 1989 ). Participation entails the right for children to express themselves and have a voice in situations that have to do with and affect them. The importance of listening to children’s voices underscores the limits of adult proxies in representing children’s emotional and social worlds (O’Farrelly, 2021 ). Bullying and cyberbullying fundamentally violate these protections, silence children’s voices, and compromise their healthy development (Greene, 2006 ). Our mixed methods study through quantitative measures and qualitative interviews facilitated a dialogue between the participant responses in both methodologies. This interaction of data types maximizes the voices of and collaboration with participants as well as knowledge generation.

Data Availability

Not applicable.

Code Availability

Different terms are used to describe the same approach (e.g., social-ecological framework, ecological systems framework, ecological theory, ecological perspectives). For the purposes of this paper, the term ecological systems framework is used.

All additional references to this research study will be shortened to “Motivations for Cyberbullying.”

All additional references to this paper will be shortened to “Benchmarks and Bellwethers paper.”

All additional references to the paper will be shortened to “Relationship Dynamics paper.”

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Acknowledgements

We would like to acknowledge first and foremost the Toronto District School Board for their utmost commitment to participating in the study, as well as each school for their dedication to both data collection and ensuring that the mental health needs of students that were identified through the study were addressed. We would like to thank the students, parents, and teachers for sharing their experiences with us. We would like to thank the research assistants, without whom we could not have completed this study.

This research was supported by a grant from the Social Sciences and Humanities Research Council of Canada: Grant Account Number: 410–2011-1001.

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Mishna, F., Birze, A. & Greenblatt, A. Understanding Bullying and Cyberbullying Through an Ecological Systems Framework: the Value of Qualitative Interviewing in a Mixed Methods Approach. Int Journal of Bullying Prevention 4 , 220–229 (2022). https://doi.org/10.1007/s42380-022-00126-w

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Accepted : 25 April 2022

Published : 10 May 2022

Issue Date : September 2022

DOI : https://doi.org/10.1007/s42380-022-00126-w

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