research questions on cyberbullying

Qualitative Methods in School Bullying and Cyberbullying Research: An Introduction to the Special Issue

• Published: 12 August 2022
• Volume 4 , pages 175–179, ( 2022 )

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• Paul Horton 1 &
• Selma Therese Lyng 2  

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Introduction

School bullying research has a long history, stretching all the way back to a questionnaire study undertaken in the USA in the late 1800s (Burk, 1897 ). However, systematic school bullying research began in earnest in Scandinavia in the early 1970s with the work of Heinemann ( 1972 ) and Olweus ( 1978 ). Highlighting the extent to which research on bullying has grown exponentially since then, Smith et al. ( 2021 ) found that there were only 83 articles with the term “bully” in the title or abstract published in the Web of Science database prior to 1989. The numbers of articles found in the following decades were 458 (1990–1999), 1,996 (2000–2009), and 9,333 (2010–2019). Considering cyberbullying more specifically, Smith and Berkkun ( 2017 , cited in Smith et al., 2021 ) conducted a search of Web of Science with the terms “cyber* and bully*; cyber and victim*; electronic bullying; Internet bullying; and online harassment” until the year 2015 and found that while there were no articles published prior to 2000, 538 articles were published between 2000 and 2015, with the number of articles increasing every year (p. 49).

Numerous authors have pointed out that research into school bullying and cyberbullying has predominantly been conducted using quantitative methods, with much less use of qualitative or mixed methods (Hong & Espelage, 2012 ; Hutson, 2018 ; Maran & Begotti, 2021 ; Smith et al., 2021 ). In their recent analysis of articles published between 1976 and 2019 (in WoS, with the search terms “bully*; victim*; cyberbullying; electronic bullying; internet bullying; and online harassment”), Smith et al. ( 2021 , pp. 50–51) found that of the empirical articles selected, more than three-quarters (76.3%) were based on quantitative data, 15.4% were based on a combination of quantitative and qualitative data, and less than one-tenth (8.4%) were based on qualitative data alone. What is more, they found that the proportion of articles based on qualitative or mixed methods has been decreasing over the past 15 years (Smith et al., 2021 ). While the search criteria excluded certain types of qualitative studies (e.g., those published in books, doctoral theses, and non-English languages), this nonetheless highlights the extent to which qualitative research findings risk being overlooked in the vast sea of quantitative research.

School bullying and cyberbullying are complex phenomena, and a range of methodological approaches is thus needed to understand their complexity (Pellegrini & Bartini, 2000 ; Thornberg, 2011 ). Indeed, over-relying on quantitative methods limits understanding of the contexts and experiences of bullying (Hong & Espelage, 2012 ; Patton et al., 2017 ). Qualitative methods are particularly useful for better understanding the social contexts, processes, interactions, experiences, motivations, and perspectives of those involved (Hutson, 2018 ; Patton et al., 2017 ; Thornberg, 2011 ; Torrance, 2000 ).

Smith et al. ( 2021 ) suggest that the “continued emphasis on quantitative studies may be due to increasingly sophisticated methods such as structural equation modeling … network analysis … time trend analyses … latent profile analyses … and multi-polygenic score approaches” (p. 56). However, the authors make no mention of the range or sophistication of methods used in qualitative studies. Although there are still proportionately few qualitative studies of school bullying and cyberbullying in relation to quantitative studies, and this gap appears to be increasing, qualitative studies have utilized a range of qualitative data collection methods. These methods have included but are not limited to ethnographic fieldwork and participant observations (e.g., Eriksen & Lyng, 2018 ; Gumpel et al., 2014 ; Horton, 2019 ), digital ethnography (e.g., Rachoene & Oyedemi, 2015 ; Sylwander, 2019 ), meta-ethnography (e.g., Dennehy et al., 2020 ; Moretti & Herkovits, 2021 ), focus group interviews (e.g., Odenbring, 2022 ; Oliver & Candappa, 2007 ; Ybarra et al., 2019 ), semi-structured group and individual interviews (e.g., Forsberg & Thornberg, 2016 ; Lyng, 2018 ; Mishna et al., 2005 ; Varjas et al., 2013 ), vignettes (e.g., Jennifer & Cowie, 2012 ; Khanolainen & Semenova, 2020 ; Strindberg et al., 2020 ), memory work (e.g., Johnson et al., 2014 ; Malaby, 2009 ), literature studies (e.g., Lopez-Ropero, 2012 ; Wiseman et al., 2019 ), photo elicitation (e.g., Ganbaatar et al., 2021 ; Newman et al., 2006 ; Walton & Niblett, 2013 ), photostory method (e.g., Skrzypiec et al., 2015 ), and other visual works produced by children and young people (e.g., Bosacki et al., 2006 ; Gillies-Rezo & Bosacki, 2003 ).

This body of research has also included a variety of qualitative data analysis methods, such as grounded theory (e.g., Allen, 2015 ; Bjereld, 2018 ; Thornberg, 2018 ), thematic analysis (e.g., Cunningham et al., 2016 ; Forsberg & Horton, 2022 ), content analysis (e.g., Temko, 2019 ; Wiseman & Jones, 2018 ), conversation analysis (e.g., Evaldsson & Svahn, 2012 ; Tholander, 2019 ), narrative analysis (e.g., Haines-Saah et al., 2018 ), interpretative phenomenological analysis (e.g., Hutchinson, 2012 ; Tholander et al., 2020 ), various forms of discourse analysis (e.g., Ellwood & Davies, 2010 ; Hepburn, 1997 ; Ringrose & Renold, 2010 ), including discursive psychological analysis (e.g., Clarke et al., 2004 ), and critical discourse analysis (e.g., Barrett & Bound, 2015 ; Bethune & Gonick, 2017 ; Horton, 2021 ), as well as theoretically informed analyses from an array of research traditions (e.g., Davies, 2011 ; Jacobson, 2010 ; Søndergaard, 2012 ; Walton, 2005 ).

In light of the growing volume and variety of qualitative studies during the past two decades, we invited researchers to discuss and explore methodological issues related to their qualitative school bullying and cyberbullying research. The articles included in this special issue of the International Journal of Bullying Prevention discuss different qualitative methods, reflect on strengths and limitations — possibilities and challenges, and suggest implications for future qualitative and mixed-methods research.

Included Articles

Qualitative studies — focusing on social, relational, contextual, processual, structural, and/or societal factors and mechanisms — have formed the basis for several contributions during the last two decades that have sought to expand approaches to understanding and theorizing the causes of cyber/bullying. Some have also argued the need for expanding the commonly used definition of bullying, based on Olweus ( 1993 ) (e.g., Allen, 2015 ; Ellwood & Davies, 2010 Goldsmid & Howie, 2014 ; Ringrose & Rawlings,  2015 ; Søndergaard, 2012 ; Walton, 2011 ). In the first article of the special issue, Using qualitative methods to measure and understand key features of adolescent bullying: A call to action , Natalie Spadafora, Anthony Volk, and Andrew Dane instead discuss the usefulness of qualitative methods for improving measures and bettering our understanding of three specific key definitional features of bullying. Focusing on the definition put forward by Volk et al. ( 2014 ), they discuss the definitional features of power imbalance , goal directedness (replacing “intent to harm” in order not to assume conscious awareness, and to include a wide spectrum of goals that are intentionally and strategically pursued by bullies), and harmful impact (replacing “negative actions” in order to focus on the consequences for the victim, as well as circumventing difficult issues related to “repetition” in the traditional definition).

Acknowledging that these three features are challenging to capture using quantitative methods, Spadafora, Volk, and Dane point to existing qualitative studies that shed light on the features of power imbalance, goal directedness and harmful impact in bullying interactions — and put forward suggestions for future qualitative studies. More specifically, the authors argue that qualitative methods, such as focus groups, can be used to investigate the complexity of power relations at not only individual, but also social levels. They also highlight how qualitative methods, such as diaries and autoethnography, may help researchers gain a better understanding of the motives behind bullying behavior; from the perspectives of those engaging in it. Finally, the authors demonstrate how qualitative methods, such as ethnographic fieldwork and semi-structured interviews, can provide important insights into the harmful impact of bullying and how, for example, perceived harmfulness may be connected to perceived intention.

In the second article, Understanding bullying and cyberbullying through an ecological systems framework: The value of qualitative interviewing in a mixed methods approach , Faye Mishna, Arija Birze, and Andrea Greenblatt discuss the ways in which utilizing qualitative interviewing in mixed method approaches can facilitate greater understanding of bullying and cyberbullying. Based on a longitudinal and multi-perspective mixed methods study of cyberbullying, the authors demonstrate not only how qualitative interviewing can augment quantitative findings by examining process, context and meaning for those involved, but also how qualitative interviewing can lead to new insights and new areas of research. They also show how qualitative interviewing can help to capture nuances and complexity by allowing young people to express their perspectives and elaborate on their answers to questions. In line with this, the authors also raise the importance of qualitative interviewing for providing young people with space for self-reflection and learning.

In the third article, Q methodology as an innovative addition to bullying researchers’ methodological repertoire , Adrian Lundberg and Lisa Hellström focus on Q methodology as an inherently mixed methods approach, producing quantitative data from subjective viewpoints, and thus supplementing more mainstream quantitative and qualitative approaches. The authors outline and exemplify Q methodology as a research technique, focusing on the central feature of Q sorting. The authors further discuss the contribution of Q methodology to bullying research, highlighting the potential of Q methodology to address challenges related to gaining the perspectives of hard-to-reach populations who may either be unwilling or unable to share their personal experiences of bullying. As the authors point out, the use of card sorting activities allows participants to put forward their subjective perspectives, in less-intrusive settings for data collection and without disclosing their own personal experiences. The authors also illustrate how the flexibility of Q sorting can facilitate the participation of participants with limited verbal literacy and/or cognitive function through the use of images, objects or symbols. In the final part of the paper, Lundberg and Hellström discuss implications for practice and suggest future directions for using Q methodology in bullying and cyberbullying research, particularly with hard-to-reach populations.

In the fourth article, The importance of being attentive to social processes in school bullying research: Adopting a constructivist grounded theory approach , Camilla Forsberg discusses the use of constructivist grounded theory (CGT) in her research, focusing on social structures, norms, and processes. Forsberg first outlines CGT as a theory-methods package that is well suited to meet the call for more qualitative research on participants’ experiences and the social processes involved in school bullying. Forsberg emphasizes three key focal aspects of CGT, namely focus on participants’ main concerns; focus on meaning, actions, and processes; and focus on symbolic interactionism. She then provides examples and reflections from her own ethnographic and interview-based research, from different stages of the research process. In the last part of the article, Forsberg argues that prioritizing the perspectives of participants is an ethical stance, but one which comes with a number of ethical challenges, and points to ways in which CGT is helpful in dealing with these challenges.

In the fifth article, A qualitative meta-study of youth voice and co-participatory research practices: Informing cyber/bullying research methodologies , Deborah Green, Carmel Taddeo, Deborah Price, Foteini Pasenidou, and Barbara Spears discuss how qualitative meta-studies can be used to inform research methodologies for studying school bullying and cyberbullying. Drawing on the findings of five previous qualitative studies, and with a transdisciplinary and transformative approach, the authors illustrate and exemplify how previous qualitative research can be analyzed to gain a better understanding of the studies’ collective strengths and thus consider the findings and methods beyond the original settings where the research was conducted. In doing so, the authors highlight the progression of youth voice and co-participatory research practices, the centrality of children and young people to the research process and the enabling effect of technology — and discuss challenges related to ethical issues, resource and time demands, the role of gatekeepers, and common limitations of qualitative studies on youth voice and co-participatory research practices.

Taken together, the five articles illustrate the diversity of qualitative methods used to study school bullying and cyberbullying and highlight the need for further qualitative research. We hope that readers will find the collection of articles engaging and that the special issue not only gives impetus to increased qualitative focus on the complex phenomena of school bullying and cyberbullying but also to further discussions on both methodological and analytical approaches.

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Acknowledgements

We would like to thank the authors for sharing their work; Angela Mazzone, James O’Higgins Norman, and Sameer Hinduja for their editorial assistance; and Dorte Marie Søndergaard on the editorial board for suggesting a special issue on qualitative research in the journal.

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Horton, P., Lyng, S.T. Qualitative Methods in School Bullying and Cyberbullying Research: An Introduction to the Special Issue. Int Journal of Bullying Prevention 4 , 175–179 (2022). https://doi.org/10.1007/s42380-022-00139-5

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EDITORIAL article

Editorial: cyberbullying and mental health: an interdisciplinary perspective.

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

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

Introduction

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

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

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

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

Literature Review and Theoretical Contributions

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

Empirical Findings: Quantitative Data on Cyberbullying and Developmental Outcomes

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

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

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

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

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

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

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

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

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

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

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

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

Conclusions

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

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

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

Author Contributions

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

Conflict of Interest

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

Publisher's Note

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

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

PubMed Abstract | Google Scholar

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

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

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

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

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

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

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

Future Research Questions in Cyberbullying

Research output : Chapter in Book/Report/Conference proceeding › Chapter

In the last decade, research on cyberbullying has provided much needed knowledge about this relatively new form of bullying. Earlier studies documented prevalence and developmental patterns (e.g., age and gender) of cyberbullying among children (Kowalski & Limber, 2007; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Research findings also identified a number of correlates of cybervictimization, including depression (Patchin & Hinduja, 2006; Perren, Dooley, Shaw, & Cross, 2010), anxiety (Dempsey, Sulkowski, & Nichols, 2009), and suicidal ideation (Hinduja & Patchin, 2010). Along with cyberbullying cases that have been widely publicized by the popular media, these studies have alerted us to the significance of hostile, aggressive behaviors using communication technology among children and adolescents. As the field pushes this research area forward, researchers must address the many challenges in studying cyberbullying, as have been outlined throughout the other chapters of this book. This chapter explores possible research questions that would stimulate future research efforts and thus contribute to ongoing theory building and intervention/prevention efforts against cyberbullying.

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• Cyberbullying Medicine & Life Sciences 100%
• Bullying Medicine & Life Sciences 15%
• aggressive behavior Social Sciences 15%
• Suicidal Ideation Medicine & Life Sciences 14%
• communication technology Social Sciences 11%
• exclusion Social Sciences 10%
• Child Medicine & Life Sciences 10%
• anxiety Social Sciences 9%

T1 - Future Research Questions in Cyberbullying

AU - Yoon, Jina

N1 - Publisher Copyright: © 2013 by Taylor & Francis Group, LLC.

PY - 2012/1/1

Y1 - 2012/1/1

N2 - In the last decade, research on cyberbullying has provided much needed knowledge about this relatively new form of bullying. Earlier studies documented prevalence and developmental patterns (e.g., age and gender) of cyberbullying among children (Kowalski & Limber, 2007; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Research findings also identified a number of correlates of cybervictimization, including depression (Patchin & Hinduja, 2006; Perren, Dooley, Shaw, & Cross, 2010), anxiety (Dempsey, Sulkowski, & Nichols, 2009), and suicidal ideation (Hinduja & Patchin, 2010). Along with cyberbullying cases that have been widely publicized by the popular media, these studies have alerted us to the significance of hostile, aggressive behaviors using communication technology among children and adolescents. As the field pushes this research area forward, researchers must address the many challenges in studying cyberbullying, as have been outlined throughout the other chapters of this book. This chapter explores possible research questions that would stimulate future research efforts and thus contribute to ongoing theory building and intervention/prevention efforts against cyberbullying.

AB - In the last decade, research on cyberbullying has provided much needed knowledge about this relatively new form of bullying. Earlier studies documented prevalence and developmental patterns (e.g., age and gender) of cyberbullying among children (Kowalski & Limber, 2007; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Research findings also identified a number of correlates of cybervictimization, including depression (Patchin & Hinduja, 2006; Perren, Dooley, Shaw, & Cross, 2010), anxiety (Dempsey, Sulkowski, & Nichols, 2009), and suicidal ideation (Hinduja & Patchin, 2010). Along with cyberbullying cases that have been widely publicized by the popular media, these studies have alerted us to the significance of hostile, aggressive behaviors using communication technology among children and adolescents. As the field pushes this research area forward, researchers must address the many challenges in studying cyberbullying, as have been outlined throughout the other chapters of this book. This chapter explores possible research questions that would stimulate future research efforts and thus contribute to ongoing theory building and intervention/prevention efforts against cyberbullying.

UR - http://www.scopus.com/inward/record.url?scp=85121889839&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85121889839&partnerID=8YFLogxK

U2 - 10.4324/9780203084601-37

DO - 10.4324/9780203084601-37

M3 - Chapter

AN - SCOPUS:85121889839

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BT - Principles of Cyberbullying Research

PB - Taylor and Francis

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Cyberbullying and Psychological Well-being in Young Adolescence: The Potential Protective Mediation Effects of Social Support from Family, Friends, and Teachers

Karin hellfeldt.

1 School of Law, Psychology and Social Work, Örebro University, SE-701 82 Örebro, Sweden; [email protected]

Laura López-Romero

2 Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; [email protected]

Henrik Andershed

In the current study, we tested the relations between cyberbullying roles and several psychological well-being outcomes, as well as the potential mediation effect of perceived social support from family, friends, and teachers in school. This was investigated in a cross-sectional sample of 1707 young adolescents (47.5% girls, aged 10–13 years, self-reporting via a web questionnaire) attending community and private schools in a mid-sized municipality in Sweden. We concluded from our results that the Cyberbully-victim group has the highest levels of depressive symptoms, and the lowest of subjective well-being and family support. We also observed higher levels of anxiety symptoms in both the Cyber-victims and the Cyberbully-victims. Moreover, we conclude that some types of social support seem protective in the way that it mediates the relationship between cyberbullying and psychological well-being. More specifically, perceived social support from family and from teachers reduce the probability of depressive and anxiety symptoms, and higher levels of social support from the family increase the probability of higher levels of subjective well-being among youths being a victim of cyberbullying (i.e., cyber-victim) and being both a perpetrator and a victim of cyber bullying (i.e., cyberbully-victim). Potential implications for prevention strategies are discussed.

1. Introduction

The negative consequences of school bullying have been relatively well established within research [ 1 , 2 , 3 ]. However, due to technology development, bullying is not only restricted to the physical and real-life school context. Cyberbullying refers to an intentional act of aggression, carried out to harm another individual using electronic forms of contacts or devices [ 4 ]. Previous studies have rather consistently linked cyberbullying with several negative psychosocial well-being outcomes in adolescence (for review, see Reference [ 5 ]). However, much more research is needed to more clearly establish how and to what extent the distinctive cyberbullying roles (i.e., being a cyberbully, cyber-victim, and cyberbully-victim) are related with various psychological well-being outcomes. More research investigating if and to what extent various types of social support can mediate these relations is also needed. Social support from family, friends, and teachers has proven to be able to mitigate the negative impacts of traditional bullying but have been scarcely studied in relation to cyberbullying [ 6 , 7 , 8 , 9 , 10 , 11 ]. Therefore, the aim of the present study is to examine the relations between cyberbullying and its different roles with several psychological well-being outcomes. In addition, and in order to identify potential variables that may influence these associations, we examine if and to what extent perceived social support from the family, friends, and teachers mediate the association between cyberbullying roles and psychological well-being outcomes.

1.1. The Association between Cyberbullying and Adolescent Psychological Well-Being

Some scholars suggest that cyberbullying is more stressful than traditional forms of school bullying [ 12 , 13 ]. Cyberbullying has emerged as a distinct form of bullying, with features such as publicity, permeability of online messages and pictures, anonymity of offender, and limitless boundaries, which distinguish it from traditional school bullying [ 4 ]. Hence, it is possible that cyberbullying renders other and more serious consequences as compared to traditional bullying. Although less studied than traditional bullying, involvement in cyberbullying has been linked to a range of psychological problems (for review, see Reference [ 5 ]). However, very few studies have compared psychological outcomes for the different cyberbullying roles. Youths may participate in cyberbullying either in the role of cyber victims, cyberbullies, or cyberbully-victims. Previous research has mostly focused on victims of cyberbullying and its potential consequences. A substantial amount of research has found associations between cyber-victimization and depressive symptoms ([ 13 , 14 , 15 , 16 ]; for reviews and meta-analyses, see Reference [ 17 ]). Fewer studies have studied other outcomes and found relations between cyber-victimization and anxiety symptoms [ 18 ] and between cyber-victimization and lower levels of subjective well-being [ 19 , 20 ].

Although less studied, research also indicates an association between cyberbullying (i.e., being in the role of the perpetrator of cyberbullying) and adverse outcomes. A majority of studies show that higher levels of cyberbullying relates to higher levels of depressive symptoms [ 14 , 18 ], anxiety symptoms [ 18 , 21 ], and lower levels of subjective well-being [ 19 ]. However, some studies indicate that cyberbullies might be better off than those who are victimized, also with examples of studies finding no relation between the role of cyberbullying and depressive symptoms [ 15 ].

Some studies suggest that children and adolescents who are both victims and perpetrators of cyberbullying, (i.e., cyberbully-victims), constitute a distinct group with the highest risk for psychosocial problems, such as depressive and anxiety symptoms, as well as for lower levels of well-being in general [ 22 , 23 , 24 , 25 ]. Nevertheless, a limited amount of research has focused on the relationship between cyberbully-victims and different well-being outcomes.

In sum, existing research suggests that children involved in any way in cyberbullying can be at increased risk for psychological distress, including depressive and anxiety symptoms, as well as lower subjective well-being. Existing studies are, however, not entirely consistent in these findings and more research is therefore clearly needed.

1.2. The Potential Positive and Protective Role of Social Support

Very little is known from research concerning how to prevent or ameliorate the potential negative consequences of cyberbullying. One such potential protective factor that could mediate the relationship between cyberbullying and negative well-being could be social support. Existing studies indicate that different types of social support could potentially buffer against negative consequences of traditional, non-cyber, bullying [ 6 , 7 , 8 , 9 , 10 , 11 ]. The term social support often refers to different kinds of supportive social relations or interactions that can increase or promote an individuals’ well-being by acting as a buffering factor against negative outcomes [ 26 , 27 , 28 ]. Social support can be defined as including both an emotional dimension, (i.e., the individuals’ perception of being valued and cared for by others in their social network), as well as an instrumental dimension, (i.e., the individuals’ perception of having access to practical help with different tasks or obstacles in life) [ 29 , 30 ]. Theoretically, the potential benefits of social support can be understood in terms of the stress-buffering model [ 26 ], that is, that social support works as a buffer in stressful situations by serving as an important coping mechanism on which youths can draw [ 31 ]. Ongoing involvement in cyberbullying can be seen as a chronic stressor. Hence, emotional and instrumental social support could serve as important resources when youths experience bullying, by both offering support when it occurs, but also to help stop bullying at an early stage [ 9 ]. For example, greater family support has been shown to be able to protect adolescents from being cyberbullied and cyber-victimized [ 32 ]. In addition, telling a friend about the bullying situation has been identified by adolescents themselves as the most helpful coping strategy when being cyberbullied [ 33 ].

Social support may derive from a number of sources and can thus be of various types. Among youths, the two primary sources or types of support seem to be parents and friends [ 7 ]. However, which of these two types of social support that serves as the primary resource seem to differ with age during youth. Younger children receive their primary support from parents but as the child approaches and enters adolescence, the role of parents can become less prominent, and the support from friends can increase and become more important [ 34 ]. Turning to a friend for support has been shown to be more commonly used by cyberbullied children, as compared to other types of support [ 35 ]. Regarding youths’ social network in the context of the school, teachers could be expected to play an important role in offering support [ 36 ]. Although cyberbullying generally takes place outside the school, it has been shown that most of the victims know their perpetrator from school [ 37 ]. Hence, teachers can potentially serve as an important support system when children experience cyberbullying. Importantly, seeking support from parents, friends, or teachers have been shown to be quite common strategies used by adolescents to cope with cyberbullying experiences [ 35 ].

Although there are several studies on different programs aimed at preventing bullying, few studies have focused on factors that may help youths to handle cyberbullying [ 38 ]. Social support from parents, friends, or teachers has been indicated to be able to mitigate the consequence of being a victim of traditional bullying but studies concerning this topic have yielded mixed findings [ 6 , 9 , 10 ]. In one study, moderate levels of peer support were shown to buffer against anxiety/depression among bullies and victims, as well as bully-victims [ 7 ]. In contrast, others found that support from friends and family protected cyber-victims from poor academic achievement but not from mental health difficulties [ 9 ]. Also, little research has explicitly investigated various types of social support in relation to cyber-victimization in general, and different roles of cyberbullying more specifically. An exception is a study including 765 Swiss seventh-graders, which examined if certain coping strategies could moderate the relation between cyber-victimization and depressive symptoms [ 39 ]. In this study, seeking support from friends and family showed a significant buffering effect on depressive symptoms. In addition, in a study including 1416 adolescents living in Cyprus, family support protected both cyber-victims and cyberbullies from being cyber-victimized one year later [ 32 ]. These previous studies offer promising indications that social support can protect adolescents involved in cyberbullying from negative consequences. However, little empirical work has been done in this area and more research is needed to understand how the various cyberbullying roles among youths can benefit from different types of social support.

1.3. The Present Study

Even though more and more research has linked cyberbullying to different aspects of psychological distress, there is still a lack of studies focused on how distinctive cyberbullying roles (i.e., being a cyberbully, cyber-victim, and cyberbully-victim) are associated with various adverse outcomes [ 22 ]. Furthermore, few studies have examined processes that could mitigate the potential negative consequences of cyberbullying. Previous studies suggest that social support from family, friends, and teachers may mitigate the effect of traditional bullying [ 6 ] but this has not been thoroughly studied in relation to cyberbullying in general, nor more specifically in relation to distinctive cyberbullying roles.

Hence, in the current study, we examine the relations between cyberbullying and its different roles with symptoms of depression, anxiety, and levels of subjective well-being. In addition, and in order to identify potential variables that may mediate these associations, we test whether and to what extent youths’ perceived social support from the family, friends, and teachers mediate the association between cyberbullying roles and the three studied psychological well-being outcomes. This was examined using data from a cross-sectional study, in which 1707 youths aged 10–13 years in a mid-sized Swedish municipality responded to a questionnaire. The specific research questions we aimed to answer are:

• How are different cyberbullying roles (i.e., being a cyberbully, cyber-victim, and cyberbully-victim) associated with depressive and anxiety symptoms, as well as with subjective well-being?
• To what extent can youths´ perceived social support from family, friends, and teachers mediate the association between various cyberbullying roles and depressive and anxiety symptoms, as well as to subjective well-being?

In terms of hypotheses, previous research indicates a negative influence of cyberbullying on children’s psychological well-being [ 5 , 19 ]. Hence, we hypothesized higher levels of depressive and anxiety symptoms, and lower levels of subjective well-being for the cyber-victim and cyberbully-victim roles. We also expected protective mediation effects of social support in the way that social support from family, friends, and teachers will reduce the risk for depressive and anxiety symptoms and lower the levels of subjective well-being among those exposed to cyberbullying.

We also controlled for gender since prior research indicates that seeking support may be more beneficial for girls compared to boys [ 9 ], and also that different sources of support might be of different importance for bullied girls and boys [ 27 ].

2. Materials and Methods

This study uses cross-sectional self-report data from the fifth wave of data collections in an ongoing prospective longitudinal study, the SOFIA-study (Social and Physical Development, Interventions and Adaptation). The SOFIA-study aims to provide better understanding of children’s behavior, social adjustment, and psychological and physical health. The target population for the SOFIA-study was all children born in 2005, 2006, and 2007, attending preschools during the spring of 2010 (2542 children) in a midsized (approximately 85,000 citizens) Swedish municipality. In terms of demographics of the municipality (i.e., gender, age, educational level, and employment, and the mix of urban and rural areas), the municipality is proportional to the rest of Sweden. Wave 5 of the SOFIA-study used in the current study was conducted in the year 2018 when the children were in their young adolescent age of 10–13 years. In the first data collection, the parents of 2121 children (85.7% of target population; 47% girls) gave active consent to participate. The SOFIA-study uses parents’, teachers’, and (pre)schoolteachers’ reports for all five waves of data collections. In the fifth data collection, the children were themselves the respondents for the first time. In Wave 5, 1707 children (approximately 80% of the original sample) completed the self-report questionnaire. The current study used these cross-sectional youth self-reports from the fifth wave of data collection of the SOFIA-study.

2.1. Participants

The sample consisted of 1707 youths, which represent 80.4% of the original target sample (47.5% girls). The sample age ranged between 10 to 13 years ( Mean age = 11.89, Standard Deviation age = 0.86) and included 33.7% (n = 576) children born in 2005, 33.7% (n = 576) children born in 2006, and 32.5% (n = 554) children born in 2007. In addition, 16.7% of participants had at least one parent born in another country than Sweden.

Regarding non-participants, caregivers declined participation in the study for about 16% of the target population in 2010. The non-participants did not differ significantly from participants regarding relevant aspects, such as the children’s levels of conduct problems and internalizing problems, or the caregivers’ socio-economic status and origin [ 40 ].

2.2. Measurements

Cyberbullying/Cyber-victimization. Two items from the Revised Olweus’ Bully/Victim Questionnaire (OBVQ, [ 41 ]) were used to assess cyberbullying. Each participant was introduced with a detailed definition of bullying. The definition included three common criteria of bullying, i.e., intentionality, repetitiveness, and power imbalance between perpetrator(s) and a victim [ 41 , 42 ]. This definition was followed up by two cyberbullying questions, one on cyber-victimization, “How often have you been cyber-victimized during the past six months?”, and one on cyberbullying, “How often have you cyberbullied other students at school during the past six months?”. Items were rated as 1 (Never), 2 (1 or 2 times), 3 (2 or 3 times a month), 4 (Once a week), and 5 (Several times a week). The cyberbullying questions were preceded by the following definition: “Here are some questions about cyberbullying. When we say ‘cyberbullying’, we mean bullying through e-mail, instant messaging, in a chat room, on a website, or through a text message sent to a cell phone”. Following recommendations from previous studies, a cutoff point for frequent involvement in bullying is “two or three times a month”, and “only once or twice” for occasional involvement [ 43 ].

Depressive symptoms. To assess Depressive symptoms, items from The Youth Self-Report (YSR) was used, an instrument based on the Achenbach System of Empirically Based Assessment [ 44 ]. The subscale used in this study, i.e., Affective problems (used to measure depressive symptoms) reflects DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th) problem dimensions, which comprise items that experienced psychiatrists and psychologists from 16 cultures have rated as being very consistent with DSM-IV diagnostic categories [ 45 ]. We included all items from the Affective problems subscale but one (i.e., “Thinks about suicide”), resulting in 11 items (e.g., “I am unhappy, sad, or depressed”; α = 0.79; mean inter item correlation (MIC) = 0.44). Participants rated each of the 11 included items on a three-point scale ranging from 1 (Not true) to 3 (Very true or often true). Respondents were requested to base their ratings on the preceding 6 months.

Anxiety Symptoms. Anxiety symptoms were assessed with items from the Spence Children´s Anxiety Scale (SCAS [ 46 ]). The SCAS corresponds to DSM-IV anxiety disorder categories, and the scale has shown good psychometric properties with empirical support for test–retest reliability and internal consistency [ 47 ]. In the current study, we used the subscale for general anxiety, in total 6 items (e.g., “I worry that something awful will happen to me”; α = 0.81, MIC = 0.58). Participants rated each item on a four-point scale ranging from 1 (Never) to 4 (Always). Respondents were requested to base their ratings on the preceding 6 months.

Subjective well-being. Subjective well-being was assessed using one item (“I enjoy life very much”), using a response scale ranging from 1 (Does not apply at all) to 4 (Applies very well). Respondents were requested to base their ratings on the preceding 6 months.

Perceived social support. Social support was assessed with The Multidimensional Scale of Perceived Social Support [ 48 ]. This scale consists of 12 items intended to assess perceived social support from Family (four items; e.g., “My family is willing to help me making decisions”; α = 0.81, MIC = 0.63), Friends (four items, e.g., “I can talk about my problems with my friends”; α = 0.87, MIC = 0.72), and Teachers (four items; e.g., “My teachers help me solve problems in a good way”; α = 0.91, MIC = 0.80). Participants rated each item in a response scale ranging from 1 (Does not apply at all) to 4 (Applies very well). Respondents were requested to base their ratings on the preceding 6 months.

2.3. Procedure

Initially, the decision makers in the Child and Adolescent Department at the municipality, decided on the participation of all municipal preschools. Private preschool principals were contacted separately. In 2010, at the first wave of data collection, all concerned preschool teachers received written information about the study, who in turn, passed on this information to parents who gave active informed consent. In the fifth wave of data collection carried out in the year of 2018 (used in current study), the youths answered a web-based questionnaire during school hours. They did not receive any compensation for their participation. The web-questionnaire took approximately 20 minutes to complete. Each school was responsible for administrating the questionnaire, i.e., giving the children the possibility to answer the questionnaire via a secure web-based questionnaire. The youths received information about the purpose of the study, that their participation was voluntary, etc.

The SOFIA-study has been evaluated by a regional ethics committee (First three waves 2010–2012; Dnr #2009/429. Fourth wave 2015; Dnr #2015/024. Fifth wave 2018; Dnr #2017/486). The study has followed all stipulated ethical research principles by the Swedish Research Council and the Swedish Ethics Authority.

2.4. Statistical Analyses

First, descriptive statistics were computed for all study variables, with additional tests for differences due to gender and age performed through Student’s t -test and zero-order correlations, respectively. Second, correlations among study variables were explored with zero-order and partial correlations, controlling for gender and age. Third, cyberbullying role variables (i.e., No cyberbully/cyber-victim, Cyberbully, Cyber-victim, Cyberbully-victim) were created by computing low/high groups from the cyberbullying and cyber-victimization items. These groups were then compared on psychological well-being outcomes (i.e., depressive symptoms, anxiety symptoms, and subjective well-being) and perceived social support (i.e., social support from family, friends, and teachers) through analysis of variance (ANOVA) and including the Bonferroni correction for multiple comparisons ( p < 0.008). The strength of differences was assessed with the partial effect size statistic ( ƞ ² ), and interpreted as small (>0.05), medium (0.06 to 0.14), and large (<0.14). Both correlation analyses and comparisons across groups were replicated using non-parametric analytic approaches (i.e., Spearman rho and Kruskal–Wallis tests, respectively), with no relevant changes in main results (further information is available upon request). Descriptive statistics, correlation analyses, and ANOVAs were computed in IBM SPSS 20 (IBM, Armonk, NY, USA).

Finally, a series of mediation models were examined via structural equation modeling (SEM) in Mplus 7.4 (Muthén & Muthén, Los Angeles, CA, USA). The estimated models tested the effects of cyberbullying roles (i.e., Cyberbully, Cyber-victim, and Cyberbully-victim), coded as dummy variables (0 = No, 1 = Yes), on depressive and anxiety symptoms, and subjective well-being through the potential mediation effect of perceived family, friends, and teachers support, controlling for age and gender. The mean- and variance-adjusted maximum likelihood test statistic (MLMV) was used as the estimator, since it is robust to non-normal data, and yields the best combination of accurate standard errors and Type I error [ 49 ]. Goodness-of-fit was assessed using the root-mean-square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). According to suggestions by Hu and Bentler [ 50 ], RMSEA and SRMR values lower or equal to 0.06 and 0.05 respectively, and CFI values of 0.95 or higher are considered indicators of good model fit, whereas a RMSEA and SRMR smaller than 0.08, and CFI larger than 0.90 indicate adequate model fit.

3.1. Descriptive Statistics and Correlations between Main Study Variables

Descriptive statistics and gender comparisons are presented in Table 1 . As expected given the characteristics of the sample, participants showed low levels of cyberbullying and cyber-victimization, depression, and anxiety symptoms, and high levels of subjective well-being, as well as high levels of perceived social support. Gender comparisons revealed differences across gender groups in cyberbullying, anxiety, subjective well-being, and peer support, with effect sizes ranging from low to moderate. Results showed higher levels of cyberbullying and subjective well-being among boys, and higher levels of anxiety and social support from friends among girls. Significant differences were also observed in terms of age for all study variables (r s = 0.05 to −0.26; p < 0.05). More specifically, results revealed higher levels of cyberbullying and cyber-victimization, depressive, and anxiety symptoms among the older adolescents, whereas higher levels of subjective well-being and perceived social support were observed among the younger adolescents.

Descriptive statistics for the main study variables with tests for gender differences.

Note. Min = Minimum score; Max = Maximum score; SD = Standard deviation. * p < 0.05. ** p < 0.01. *** p < 0.001.

Zero-order correlation results between the main study variables are displayed in Table 2 . All variables were significantly correlated with each other, except cyberbullying and anxiety symptoms. Results from partial correlations controlling for age and gender yielded basically the same results, with similar values for all the analyzed variables. The only larger difference was observed for the correlation between cyberbullying and friends’ support, which was no longer significant when controlling for age and gender (results available upon request).

Zero-order correlations between the main study variables.

* p < 0.05. ** p < 0.01. *** p < 0.001.

3.2. Cyberbullying Roles: Comparisons across Groups on Psychological Well-Being

In order to examine the associations between distinctive cyberbullying roles and psychological well-being, we identified groups low and high from the cyberbullying and cyber-victimization continuous items. Based on prior recommendations, those participants who reported being cyberbullying/bullied “two or three times a month” or more often [ 42 ] were classified as cyberbullies (n = 11; 0.6% of the sample) and cyber-victims (n = 55; 3.2%), respectively. By combining these groups, four mutually exclusive groups representing distinctive cyberbullying roles were identified: No Cyberbully/cyber-victim (n = 1640; 96.5%), Cyberbully (n = 5; 0.3%), Cyber-victim (n = 49; 2.8%), and Cyberbully-victim (n = 6; 0.4%). Given the low prevalence rates in the Cyberbully, Cyber-victim, and Cyberbully-victim groups, and in order to ensure enough participants within each group for subsequent analyses, new cyberbullying groups were created using a less stringent cut-off. The less strict cutoff follows recommendations from previous studies, resulting in groups with youths more occasionally involved in cyberbullying [ 43 ]. Hence, those participants who reported being cyberbullying/bullied “one or two times” or more often were classified as cyberbullies (n = 42; 2.5%) and cyber-victims (n = 218; 12.8%). The combination of these groups yielded four different groups representing the following cyberbullying roles: No Cyberbully/cyber-victim (n = 1469; 86.4%), Cyberbully (n = 13; 0.8%), Cyber-victim (n = 191; 11.2%), and Cyberbully-victim (n = 27; 1.6%). Comparisons across groups revealed no differences in terms of gender, χ² (3) = 7.39; p = 0.060, nor age, F = 1.73; p = 0.158 in the distribution across these groups.

Results of comparisons between these groups showed significant differences on all three of the psychological well-being outcomes as well as on all types of perceived social support, even after applying the Bonferroni correction (see Table 3 ). More specifically, the Cyberbully-victim group showed the highest levels of depressive symptoms, and the lowest levels of subjective well-being, and family support. Higher levels of anxiety symptoms were observed for both the cyber-victim and the cyberbully-victim groups. There were no significant differences between the three cyberbullying roles (i.e., cyberbully, cyber-victim, and cyberbully-victim) in social support from friends and teachers. Effect sizes were small for all the analyzed variables except depressive symptoms, which showed a medium effect size.

Comparisons between cyberbullying roles on psychological well-being and social support variables.

Note. ƞ² = partial effect size statistic. Means with different subscripts (a, b, c) were significantly different ( p < 0.05) in post hoc pairwise comparisons (subscript a represents the lowest score/s in the analyzed variable). * Significant value after applying the Bonferroni correction ( p < 0.008).

3.3. Cyberbullying Roles and Psychological Well-Being: The Potential Mediational Role of Perceived Social Support

In order to include cyberbullying roles as independent variables in the mediation models, three dummy variables were created: Cyberbully (No (0) = 1687; Yes (1) = 13), Cyber-victim (No (0) = 1509; Yes (1) = 191), and Cyberbully-victim (No (0) = 1673; Yes (1) = 27). Three independent models were initially estimated, examining the effects of cyberbullying roles and social support variables on depression (RMSEA = 0.04, CFI = 0.93, SRMR = 0.04), anxiety (RMSEA = 0.04, CFI = 0.95, SRMR = 0.03), and subjective well-being (RMSEA = 0.04, CFI = 0.96, SRMR = 0.03), respectively. Because similar results were observed across models, and considering the covariance between depressive symptoms, anxiety symptoms, and subjective well-being, the final model tested the effects of cyberbullying roles and perceived social support on all three psychological well-being outcomes simultaneously.

As can be seen in Figure 1 , model fit indices ranged from acceptable (CFI = 0.92) to good (RMSEA = 0.03; SRMR = 0.04). Regarding direct effects, both Cyber-victim and Cyberbully-victim roles showed a positive and significant association with depressive and anxiety symptoms and negative associations with subjective well-being. Similarly, the Cyber-victim group was significantly and negatively related with all perceived types of social support (i.e., from family, friends, and teachers), whereas the Cyberbully-victim showed negative significant associations with family and teachers support. Finally, family, friends’, and teachers’ support showed negative associations with both depressive and anxiety symptoms. Only family and teachers’ support showed a positive and significant association with subjective well-being.

Mediation model of cyberbullying roles on psychological well-being through perceived social support. Root-Mean-Square Error of Approximation (RMSEA) = 0.03; Comparative Fit Index (CFI) = 0.92; Standardize Root Square Residual (SRMR) = 0.04. The model shows the standardized estimates for direct effects, covariance between mediators and dependent variables, and controlled effects for age and gender (in grey). Only statistically significant relationships are shown in the figure. * p < 0.05. ** p < 0.01. *** p < 0.001.

Of note, being a Cyberbully did not show direct associations with any of the analyzed variables. Therefore, mediation effects were only examined for Cyber-victim and Cyberbully-victim roles (see Table 4 ). Indirect effects, although small, showed that the association between the Cyber-victim and Cyberbully-victim groups with all three psychological well-being outcomes were partially mediated by family and teachers support, except for Cyberbully-victim on subjective well-being through teacher support, which was non-significant. More specifically, for Cyber-victims and Cyberbully-victims, higher levels of family and teachers’ support reduce the probability of showing depressive and anxiety symptoms, whereas higher levels of family support increase the probability of reporting higher levels of subjective well-being.

Standardized indirect effects of cyberbullying roles (Cyber-victim and Cyberbully-Victim) on psychological well-being outcomes through family, friends’, and teachers’ support.

Note. CI = Confidence interval. * p < 0.05. ** p < 0.001. *** p < 0.001.

4. Discussion

In this study, we examined the relations between cyberbullying and its different roles with symptoms of depression, anxiety, and levels of subjective well-being. In addition, and in order to identify potential variables that may mediate these associations, we tested whether and to what extent youths’ perceived social support from family, friends, and teachers mediate the association between different cyberbullying roles and the three studied psychological well-being outcomes. We conclude from our results that the Cyberbully-victim group has the highest levels of depressive symptoms, and the lowest levels of subjective well-being and family support. We also observed higher levels of anxiety symptoms in both the Cyber-victim and the Cyberbully-victim roles. Moreover, we conclude that some types of social support seem protective in the way that it mediates the relationship between cyberbullying and psychological well-being. More specifically, perceived social support from family and from teachers reduce the probability of depressive and anxiety symptoms, and higher levels of social support from the family increase the probability of higher levels of subjective well-being among youths being a victim of cyberbullying (i.e., Cyber-victim) and being both a perpetrator and a victim of cyber bullying (i.e., Cyberbully-victim).

In current study, the prevalence of involvement in cyberbullying was very low according to the self-reports of the young adolescents in this study. This is of course a positive sign since it indicates low levels of victimization and perpetration of cyberbullying. In comparison to other studies, our results are in line with others who show relative low levels of prevalence’s of involvement in cyberbullying, but not with those who report much higher numbers (for meta-review of prevalence, see Reference [ 51 ]). Due to the lack of consensus regarding the definition of cyberbullying and hence difficulties in the operationalization of the concept, multiple instruments are used in the field to estimate cyberbullying [ 52 ], making comparisons across studies problematic. In our study, we used a single item to estimate involvement in cyberbullying. Even though the use of such a single item has been argued to be both an economical, valid, and reliable estimate of bullying [ 42 ], it also comes with some limitations that perhaps explain the low prevalence of cyberbullying involvement reported in the current study. By using the word bullying/bully/victim in the questions, there is always a risk of biased perception or stigma [ 53 ]. In addition, single-item rather than multiple-item scales also run the risk of missing the complexity of a phenomenon such as cyberbullying, hence rendering lower prevalence than multiple-item scales [ 51 , 54 ]. Also, relying on self-report as the single strategy to collect information about bullying behavior may be problematic and some argue for the use of multiple reporters and methods to assess bullying [ 51 , 55 ]. As an example, peer and teacher nominations can be important additions to youth self-reports, as previous studies indicate higher agreement between peers and teachers in identifying both bullies and victims, than in relation to youth self-report [ 55 ]. Hence, future studies could benefit from combining multiple sources of reports when estimating cyberbullying involvement.

In line with previous cross-sectional studies, our results show how involvement in bullying is related to both depressive and anxiety symptoms, as well as to lower levels of subjective well-being [ 5 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. These results are consistent with previous research indicating the harm that cyberbullying may have on youths irrespectively of being a bully or a victim [ 5 ]. In addition, our results show that Cyberbully-victims reported the highest levels of depressive symptoms, as well as the lowest levels of subjective well-being. This is also in line with previous research indicating that this group of children may be at an extra risk for adverse outcomes [ 24 , 25 ]. Also, Cyberbully-victims also showed the lowest levels of perceived family support. This is important knowledge, since there is a lack of research on this particular group in general, and more specifically, in relation to sources of perceived support.

Expanding on previous research, our results show that higher levels of family and teacher social support are related to lower levels of depressive and anxiety symptoms among both Cyber-victims and Cyberbully-victims. Similar results have been found in relation to traditional non-cyber bullying, where parent and teacher support has been found to buffer against internalizing problems [ 27 ]. More specifically, using a longitudinal design, cyber-victimized adolescents who sought support from family reported lower levels of depression one year later [ 39 ]. In addition to this, our results expand on this knowledge, showing that positive social support can be beneficial, not only for Cyber-victims but also for Cyberbully-victims. There are numbers of ways that family and teacher support might translate into less negative outcomes for youth involved in cyberbullying. Parents and teachers could offer emotional support to handle the distress of being involved in cyberbullying [ 27 ]. The adult perspective in offering support is important, since others argue that peers might not see cyberbullying as problematic as adults and hence, not offer the support needed by youths involved in cyberbullying [ 35 ]. Also, parents and teachers might be able to intervene earlier to decrease or even stop the bullying. The potential role of parents as protectors has also been shown by others in that parental support has been related to less cyber-victimization one year later [ 32 ]. Our results add important new knowledge to the field by identifying social support factors that might mitigate the potential negative consequences of cyberbullying. However, it is important to note that the effect sizes were small.

In contrast to family and teacher support, perceived support from friends was not shown to buffer against psychological impairment from involvement in cyberbullying, regardless of being a Cyber-victim, Cyberbully, or Cyberbully-victim. These results are partially in line with previous studies on traditional non-cyberbullying; however, it is important to note that previous studies on social support as a mitigating factor have yielded mixed results. Our results are in line with those previous studies in which perceived social support from friends was not shown to protect children involved in traditional bullying from adverse outcomes such as depression [ 9 ], or internalizing problems [ 6 ]. However, in other studies on traditional bullying, perceived support from friends was demonstrated to mitigate the impact of bullying on the quality of lives of victims [ 32 ], as well as on anxiety/depression [ 7 ]. In relation to cyberbullying, our results contradict one of the few studies that have examined the issue and in which seeking support from friends had a buffering effect on depressive symptoms among cyber-victims [ 39 ]. However, our study expands this knowledge since they in their study, unlike we in ours, did not include Cyber-bullies nor Cyberbully-victim roles. The lack of studies, and the mixed results within the field, emphasizes the importance of more studies on friends’ support and its potential buffering function. This might be of particular importance since other studies indicate that seeking help or telling a friend is a commonly used coping strategy by youth who experience cyber-victimization [ 35 ]. However, our results indicate that seeking support from friends might not be the best way of coping with cyberbullying. One explanation could be that friends do not see cyberbullying as problematic as adults do [ 35 ], and hence do not offer the support that cyber-involved youths need. It could also be the case that friends are not able to help stop the bullying in the same way as parents or teachers could, since they have other resources to intervene in the situation. Regardless, since prior research indicates that youths commonly use and recommend others to use friends as support when experience cyberbullying [ 37 , 56 ], the role of friends’ support should be an important question for future studies.

In relation to the current studies results on the potential positive aspects of social support, there seems to be a positive bias towards adult support for cyberbullying-involved youths, i.e., youths who are involved in bullying and perceive higher levels of support from adults (i.e., family or teachers) may have less adverse outcomes than those who report less. Similar results on the positive aspects of parent/family and teacher support for cyberbullied children have been found in previous research [ 32 , 39 ]. These results are important, especially since studies indicate that adolescents generally do not tell a teacher or a parent when they are cyberbullied [ 33 , 35 , 56 , 57 ]. In fact, adolescents report that telling a teacher is rather ineffective [ 33 ] and that seeking support from a parent might be related to the loss of privileges such as free and unsupervised use of the Internet [ 57 ]. Hence, as argued by other scholars, adults should take a proactive approach in taking responsibility for building a supportive relationship with the youth [ 5 , 58 ].

Notwithstanding the prior contributions, the results of the present study should be interpreted in the light of the following limitations. First, the reliance on self-reports for all measures could have inflated some results due to shared method variance. Future research would benefit from using multiple sources of information, such as teacher and parent reports. However, a strength of this study is its use of well-validated scales to measure the majority of the included concepts. However, subjective well-being is a self-developed item, but can be argued to have high face-validity, although there were no other ways to validate this item. Second, the cross-sectional design did not allow for testing prospective associations and, therefore, conclusions of direction or stability of effects could not be established. Hence, future research should apply a longitudinal design in order to understand how cyberbullying may affect adolescents´ psychological well-being over time, and also, which role different sources of social support might play in such relations. This is of great importance since it is not clear from previous research if aspects of psychological well-being such as depressive and anxiety symptoms, as well as perceived support, are antecedents or consequences of involvement in cyberbullying [ 5 ]. In fact, it could be that there is a bidirectional link between studied variables. For example, psychological problems such as depressive symptoms could result in less social skills, and a tendency for youths to withdraw themselves from others, making them less attractive to peers, hence increasing the likelihood of becoming a victim of bullying [ 15 ]. Also, social support may work as a protective factor for children not to become involved in cyberbullying. In fact, youths may be interpersonally at risk (having fewer friends or being rejected by peer) for future victimization [ 59 ]. Also, family support has been proven to decrease the risk for cyber-victimization one year later [ 32 ]. Hence, more research should use a longitudinal approach to further clarify the potential causal relationships between psychological well-being, social support, and involvement in cyberbullying. Third, although the current study included a relatively large sample, the prevalence rates for both cyberbullying and cyber-victimization were relatively low, leading to small groups when testing the cyberbullying roles. Related to this, the small size of the groups did not allow for further tests by gender, an issue that should be addressed in future research. Hence, research using larger samples is needed to increase our understanding of how factors such as gender may moderate the association between cyberbullying roles, psychological well-being, and different sources of social support. This is of great importance since prior research indicates that seeking support may be more beneficial for girls compared to boys [ 5 ], and also that different sources of support might be of different importance for bullied girls and boys [ 6 ]. Lastly, the effect sizes for the indirect effects were small. Since we excluded the suicide item from the depressive symptoms scale due to ethical considerations, i.e., the setting for the answering of questionnaire and the age of respondents, this could have potentially attenuated the strength of the statistical relationships. Hence, including suicide ideation in the depressive symptoms scale could potentially have helped to differentiate between the groups and outcomes.

5. Conclusions

In conclusion, the current study suggest that youths involved in cyberbullying, as victims, bullies, and bully-victims, are at increased risk for anxiety and depressive symptoms, as well as less well-being in general. Since cyberbullying has been linked to adverse outcomes in adolescence, it is important that teachers and other practitioners have a good understanding of how children’s different involvement in bullying relates with psychosocial well-being outcomes, and which variables that may impact that relationship. As observed in previous research, both emotional and instrumental perceived social support could serve as important resources when youths experience bullying in its different roles (e.g., References [ 9 , 32 ]). In this regard, perceived social support, particularly from family and teachers at school, may ameliorate the potential link between cyberbullying and several distress outcomes at the psychosocial well-being level. Hence, prevention and intervention programs of cyberbullying could benefit from including specific strategies leading to an increase in both seeking and perception of functional social support from relevant figures in adolescence (i.e., family and teachers).

Acknowledgments

We are very grateful to Karlstad University and Karlstad municipality for their collaboration in the SOFIA-study.

Author Contributions

K.H., L.L.-R., and H.A., conceptualization, methodology and analytic plan; L.L.-R., formal analysis; K.H. and H.A. investigation, resources, project administration, funding acquisition; K.H., writing—original draft preparation, L.L.-R. and H.A., writing—review and editing; H.A., supervision. All authors have read and agreed to the published version of the manuscript.

Karin Hellfeldts’ contribution to this study was partially funded by Groschinsky’s Memory Foundation. Laura López-Romero’ contribution to this study was partially funded by Programa de Axudas á Etapa Posdoutoral da Xunta de Galicia (2017). Aside from this funding, this research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Frequently Asked Questions on Cyber Bullying

What is cyberbullying, how are people cyberbullied, why do people cyberbully others, do cyberbullying victims and perpetrators fit any stereotypical profile, how do people react to cyber bullying.

• How do I respond and prevent to cyberbullying?

How can I prevent cyberbullying and stay cyber-safe?

If a parent suspects their child is a cyberbully, what should they do.

• Do cyber bullying victims and perpetrators fit any stereotypical profile?

Online bullying, or cyberbullying, occurs frequently to teens using the Internet, cell phones or other devices. These teens often experience texts or images intended to hurt or embarrass them. Almost half of all American teens are victims of cyber bullying. Whether you’ve been a victim of cyberbullying or know someone who has been cyberbullied, there are steps you and your friends can take to stop cyberbullying and stay cyber-safe.

Cyberbullying occurs when an individual uses the Internet or another form of technology to harm other people, in a deliberate, repeated, and hostile manner. In some cases a person may pretend that they are another person online to trick others. They could spread lies and rumors about victims, trick people into revealing personal information, send or forward mean text messages, and post pictures of victims without their consent.

Is bullying the same as cyberbullying? What makes them different?

While bullying occurs as a face-to-face confrontation, cyberbullying occurs online and involves the use of technologies. Cyberbullying can be even more vicious than bullying since cyberbullying can occur repeatedly in front of a massive online audience, with the cyberbully’s identity unknown, while the victim feels helpless because the attacks can come from several different online sources day in and day out.

People who cyberbully others are often driven by feelings of anger, revenge, and frustration. In many cases, cyberbullies were once victims of bullying who weren’t guided in the proper direction. However, the power-hungry are the most nefarious; they cyberbully with the pure intent of tormenting others or bolstering their ego. Luckily, most cyberbullies do not fall into that category. In a recent poll, 81% of cyberbullies have stated that they cyberbully others because they think it’s “funny”. Many others don’t cyberbully others on purpose. It occurs by accident and the “cyberbully” either sends a message to the wrong recipient or act impulsively without realizing the consequences, thinking it’s not a big deal. Because their motives differ, the solutions and responses to each type of cyberbullying incident has to differ as well. Kids cyberbully primarily to replace the social skills that they were supposed to develop in grade school, middle school, and high school. As children go through their developmental stages, they should be finding ways of working out problems with their peers and getting along with other people, which includes learning how to read social situations, make friends, and understand their social environment. Bullies however, use aggression, violence, and verbal abuse to supplant these skills. They don’t have to learn how to work things out because they solve their problems through harassment and intimidation. Cyberbullies, in addition to using cruel methods, hide behind the anonymity of a computer or cell phone, and over time, bullying becomes a natural response to any situation where they feel socially awkward, insecure, frightened, or embarrassed.

Neither victims nor perpetrators fit into any stereotypical profile. The “good kids”, the “quiet kids”, as well as “troublesome kids” can be either bullies or victims. Due to the fact that online communication allows bullies to remain anonymous, people often become more emboldened and vicious in their attacks than they would be in a face-to-face encounter. Many cyberbullies have admitted that they wouldn’t have made the same choices if their identities had been known.

There are two types of reactions. People either react positively or negatively. Positive victim reaction involves blocking communication with the cyberbully, deleting messages without reading them, talking to a friend about the bullying, or reporting the problem to an internet service provider or website monitor. Negative victim reaction involves seeking revenge on the bully, avoiding friends and activities, and even cyberbullying others.

How do I respond and to cyberbullying?

In some scenarios, cyberbullying can be ignored if the case is an unthreatening act, a prank, or a mild tease. The bully may get bored waiting and moves on. Cyberbullies actually want you to respond to them so they can expose your response to their audience. Yet we strongly urge you to take preventive measures against cyberbullying, which can be done by restricting the people who can communicate with you. Restrict others from being able to freely add you to their buddy list. If someone seems aggressive or makes you uncomfortable and doesn’t respond to verbal pleas or formal warnings, he or she should be blocked. You can even warn the sender by reporting the cyberbullying case to an Internet monitor service or a website monitor. In serious cases, you can report incidents to the police if someone threatens you physically. If you feel that you or someone you know is in danger, contact the police immediately and cut off contact with this person or user. Stay offline if you cannot avoid this person.

You can refuse to pass along cyberbullying messages. Tell friends to stop cyberbullying, block communication with cyberbullies, and report cyberbullying to a trusted adult. To stay cyber-safe, never post or share your personal information online or your friends’ personal information (this includes your full name, address, telephone number, school name, parents’ names or credit card number). Never share your Internet passwords with anyone and never meet face-to-face with someone you only met online.

The parent can start by teaching the child about social responsibility. Have the child imagine the situation in reverse. Cyberbullying can spiral to a massive level, even though cyberbullies may have just sent a post or text that initially started off as a joke. It is also important to teach this same lesson to cyberbullying victims, because many victims in turn can become cyberbullies themselves.

Television and pop culture have painted an image in our minds of what a bully and a victim should look like. The bully is the tough, muscular teenager that threatens to beat up the scrawny kid with the duct-taped glasses unless he hands over his lunch money. However, the truth is that neither the victims nor the perpetrators of cyber bullying fit into any stereotypical profile. Even though kids are often targeted because of their appearance and the way they speak or dress, there is no way to characterize a victim, since virtually anyone can become a target. Similarly, cyberbullies cannot be identified by a specific stereotype. However, what researchers have found is that bullies are often insecure and emotionally immature individuals who compensate for their weaknesses and lack of confidence with aggression. Bullies have no regard for other people’s boundaries and never consider the potential consequences of their actions. They feel empowered by targeting others and draw strength from their victims’ misery.

Get in Touch. Get Involved.

ETCB is a rapidly expanding organization, and as such we welcome questions about the company and most importantly, about cyber bullying. Whether you are personally being cyberbullied or you know someone who is being cyberbullied, please feel free to contact us in the form below and we will be sure to provide further assistance. Also, if you are in need of any further information about our organization, such as how can you participate or how can you make a difference, leave a message below and ETCB will respond as soon as possible.

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9 facts about bullying in the U.S.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

• Online Harassment & Bullying

Katherine Schaeffer is a research analyst at Pew Research Center

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