impact of cyberbullying research paper

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

Affiliations.

1 School of Political Science and Public Administration, Wuhan University, Wuhan, China.
2 School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
3 College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, United Kingdom.
PMID: 33791270
PMCID: PMC8006937
DOI: 10.3389/fpubh.2021.634909

Background: Cyberbullying is well-recognized as a severe public health issue which affects both adolescents and children. Most extant studies have focused on national and regional effects of cyberbullying, with few examining the global perspective of cyberbullying. This systematic review comprehensively examines the global situation, risk factors, and preventive measures taken worldwide to fight cyberbullying among adolescents and children. Methods: A systematic review of available literature was completed following PRISMA guidelines using the search themes "cyberbullying" and "adolescent or children"; the time frame was from January 1st, 2015 to December 31st, 2019. Eight academic databases pertaining to public health, and communication and psychology were consulted, namely: Web of Science, Science Direct, PubMed, Google Scholar, ProQuest, Communication & Mass Media Complete, CINAHL, and PsycArticles. Additional records identified through other sources included the references of reviews and two websites, Cyberbullying Research Center and United Nations Children's Fund. A total of 63 studies out of 2070 were included in our final review focusing on cyberbullying prevalence and risk factors. Results: The prevalence rates of cyberbullying preparation ranged from 6.0 to 46.3%, while the rates of cyberbullying victimization ranged from 13.99 to 57.5%, based on 63 references. Verbal violence was the most common type of cyberbullying. Fourteen risk factors and three protective factors were revealed in this study. At the personal level, variables associated with cyberbullying including age, gender, online behavior, race, health condition, past experience of victimization, and impulsiveness were reviewed as risk factors. Likewise, at the situational level, parent-child relationship, interpersonal relationships, and geographical location were also reviewed in relation to cyberbullying. As for protective factors, empathy and emotional intelligence, parent-child relationship, and school climate were frequently mentioned. Conclusion: The prevalence rate of cyberbullying has increased significantly in the observed 5-year period, and it is imperative that researchers from low and middle income countries focus sufficient attention on cyberbullying of children and adolescents. Despite a lack of scientific intervention research on cyberbullying, the review also identified several promising strategies for its prevention from the perspectives of youths, parents and schools. More research on cyberbullying is needed, especially on the issue of cross-national cyberbullying. International cooperation, multi-pronged and systematic approaches are highly encouraged to deal with cyberbullying.

Keywords: adolescents; children; cyberbullying; globalization; preventive measures; risk factors.

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Conflict of interest statement

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.

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The prevalence of cyberbullying perpetration of high quality studies.

Cyberbullying prevalence across types (2015–2019).

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> Journals
> BJPsych Bulletin
> The Psychiatrist
> Volume 37 Issue 5
> Cyberbullying and its impact on young people's emotional...

Article contents

The nature of cyberbullying, the impact of cyberbullying on emotional health and well-being, technological solutions, asking adults for help, cyberbullying and its impact on young people's emotional health and well-being.

Published online by Cambridge University Press: 02 January 2018

The upsurge of cyberbullying is a frequent cause of emotional disturbance in children and young people. The situation is complicated by the fact that these interpersonal safety issues are actually generated by the peer group and in contexts that are difficult for adults to control. This article examines the effectiveness of common responses to cyberbullying.

Whatever the value of technological tools for tackling cyberbullying, we cannot avoid the fact that this is an interpersonal problem grounded in a social context.

Practitioners should build on existing knowledge about preventing and reducing face-to-face bullying while taking account of the distinctive nature of cyberbullying. Furthermore, it is essential to take account of the values that young people are learning in society and at school.

Traditional face-to-face bullying has long been identified as a risk factor for the social and emotional adjustment of perpetrators, targets and bully victims during childhood and adolescence; Reference Almeida, Caurcel and Machado 1 - Reference Sourander, Brunstein, Ikomen, Lindroos, Luntamo and Koskelainen 6 bystanders are also known to be negatively affected. Reference Ahmed, Österman and Björkqvist 7 - Reference Salmivalli 9 The emergence of cyberbullying indicates that perpetrators have turned their attention to technology (including mobile telephones and the internet) as a powerful means of exerting their power and control over others. Reference Smith, Mahdavi, Carvalho, Fisher, Russell and Tippett 10 Cyberbullies have the power to reach their targets at any time of the day or night.

Cyberbullying takes a number of forms, to include:

• flaming: electronic transmission of angry or rude messages;

• harassment: repeatedly sending insulting or threatening messages;

• cyberstalking: threats of harm or intimidation;

• denigration: put-downs, spreading cruel rumours;

• masquerading: pretending to be someone else and sharing information to damage a person’s reputation;

• outing: revealing personal information about a person which was shared in confidence;

• exclusion: maliciously leaving a person out of a group online, such as a chat line or a game, ganging up on one individual. Reference Schenk and Fremouw 11

Cyberbullying often occurs in the context of relationship difficulties, such as the break-up of a friendship or romance, envy of a peer’s success, or in the context of prejudiced intolerance of particular groups on the grounds of gender, ethnicity, sexual orientation or disability. Reference Hoff and Mitchell 12

A survey of 23 420 children and young people across Europe found that, although the vast majority were never cyberbullied, 5% were being cyberbullied more than once a week, 4% once or twice a month and 10% less often. Reference Livingstone, Haddon, Anke Görzig and Ólafsson 13 Many studies indicate a significant overlap between traditional bullying and cyberbullying. Reference Perren, Dooley, Shaw and Cross 5 , Reference Sourander, Brunstein, Ikomen, Lindroos, Luntamo and Koskelainen 6 , Reference Kowalski and Limber 14 , Reference Ybarra and Mitchell 15 However, a note of caution is needed when interpreting the frequency and prevalence of cyberbullying. As yet, there is no uniform agreement on its definition and researchers differ in the ways they gather their data, with some, for example, asking participants whether they have ‘ever’ been cyberbullied and others being more specific, for example, ‘in the past 30 days’.

Research consistently identifies the consequences of bullying for the emotional health of children and young people. Victims experience lack of acceptance in their peer groups, which results in loneliness and social isolation. The young person’s consequent social withdrawal is likely to lead to low self-esteem and depression. Bullies too are at risk. They are more likely than non-bullies to engage in a range of maladaptive and antisocial behaviours, and they are at risk of alcohol and drugs dependency; like victims, they have an increased risk of depression and suicidal ideation. Studies among children Reference Escobar, Fernandez-Baen, Miranda, Trianes and Cowie 2 - Reference Kaltiala-Heino, Rimpalä, Rantanen and Rimpalä 4 , Reference Kumpulainen, Rasanen and Henttonen 16 and adolescents Reference Salmivalli, Lappalainen and Lagerspetz 17 , Reference Sourander, Helstela, Helenius and Piha 18 indicate moderate to strong relationships between being nominated by peers as a bully or a victim at different time points, suggesting a process of continuity. The effects of being bullied at school can persist into young adulthood. Reference Isaacs, Hodges and Salmivalli 19 , Reference Lappalainen, Meriläinen, Puhakka and Sinkkonen 20

Studies demonstrate that most young people who are cyberbullied are already being bullied by traditional, face-to-face methods. Reference Sourander, Brunstein, Ikomen, Lindroos, Luntamo and Koskelainen 6 , Reference Dooley, Pyzalski and Cross 21 - Reference Riebel, Jaeger and Fischer 23 Cyberbullying can extend into the target’s life at all times of the day and night and there is evidence for additional risks to the targets of cyberbullying, including damage to self-esteem, academic achievement and emotional well-being. For example, Schenk & Fremouw Reference Schenk and Fremouw 11 found that college student victims of cyberbullying scored higher than matched controls on measures of depression, anxiety, phobic anxiety and paranoia. Studies of school-age cyber victims indicate heightened risk of depression, Reference Perren, Dooley, Shaw and Cross 5 , Reference Gradinger, Strohmeier and Spiel 22 , Reference Juvonen and Gross 24 of psychosomatic symptoms such as headaches, abdominal pain and sleeplessness Reference Sourander, Brunstein, Ikomen, Lindroos, Luntamo and Koskelainen 6 and of behavioural difficulties including alcohol consumption. Reference Mitchell, Ybarra and Finkelhor 25 As found in studies of face-to-face bullying, cyber victims report feeling unsafe and isolated, both at school and at home. Similarly, cyberbullies report a range of social and emotional difficulties, including feeling unsafe at school, perceptions of being unsupported by school staff and a high incidence of headaches. Like traditional bullies, they too are engaged in a range of other antisocial behaviours, conduct disorders, and alcohol and drug misuse. Reference Sourander, Brunstein, Ikomen, Lindroos, Luntamo and Koskelainen 6 , Reference Hinduja and Patchin 26

The most fundamental way of dealing with cyberbullying is to attempt to prevent it in the first place, through whole-school e-safety policies Reference Campbell 27 - Reference Stacey 29 and through exposure to the wide range of informative websites that abound (e.g. UK Council for Child Internet Safety (UKCCIS; www.education.gov.uk/ukccis ), ChildLine ( www.childline.org.uk )). Many schools now train pupils in e-safety and ‘netiquette’ to equip them with the critical tools that they will need to understand the complexity of the digital world and become aware of its risks as well as its benefits. Techniques include blocking bullying behaviour online or creating panic buttons for cyber victims to use when under threat. Price & Dalgleish Reference Price and Dalgleish 30 found that blocking was considered as a most helpful online action by cyber victims and a number of other studies have additionally found that deleting nasty messages and stopping use of the internet were effective strategies. Reference Livingstone, Haddon, Anke Görzig and Ólafsson 13 , Reference Kowalski and Limber 14 , Reference Juvonen and Gross 24 However, recent research by Kumazaki et al Reference Kumazaki, Kanae, Katsura, Akira and Megumi 31 found that training young people in netiquette did not significantly reduce or prevent cyberbullying. Clearly there is a need for further research to evaluate the effectiveness of different types of technological intervention.

Parents play an important role in prevention by banning websites and setting age-appropriate limits of using the computer and internet. Reference Kowalski and Limber 14 Poor parental monitoring is consistently associated with a higher risk for young people to be involved in both traditional and cyberbullying, whether as perpetrator or target. Reference Ybarra and Mitchell 15 However, adults may be less effective in dealing with cyberbullying once it has occurred. Most studies confirm that it is essential to tell someone about the cyberbullying rather than suffer in silence and many students report that they would ask their parents for help in dealing with a cyberbullying incident. Reference Smith, Mahdavi, Carvalho, Fisher, Russell and Tippett 10 , Reference Stacey 29 , Reference Aricak, Siyahhan, Uzunhasanoglu, Saribeyoglu, Ciplak and Yilmaz 32 On the other hand, some adolescents recommend not consulting adults because they fear loss of privileges (e.g. having and using mobile telephones and their own internet access), and because they fear that their parents would simply advise them to ignore the situation or that they would not be able to help them as they are not accustomed to cyberspace. Reference Smith, Mahdavi, Carvalho, Fisher, Russell and Tippett 10 , Reference Hoff and Mitchell 12 , Reference Kowalski and Limber 14 , Reference Stacey 29 In a web-based survey of 12- to 17-year-olds, of whom most had experienced at least one cyberbullying incident in the past year, Juvonen & Gross Reference Juvonen and Gross 24 found that 90% of the victims did not tell their parents about their experiences and 50% of them justified it with ‘I need to learn to deal with it myself’.

Students also have a rather negative and critical attitude to teachers’ support and a large percentage consider telling a teacher or the school principal as rather ineffective. Reference Aricak, Siyahhan, Uzunhasanoglu, Saribeyoglu, Ciplak and Yilmaz 32 , Reference DiBasilio 33 Although 17% of students reported to a teacher after a cyberbullying incident, in 70% of the cases the school did not react to it. Reference Hoff and Mitchell 12

Involving peers

Young people are more likely to find it helpful to confide in peers. Reference Livingstone, Haddon, Anke Görzig and Ólafsson 13 , Reference Price and Dalgleish 30 , Reference DiBasilio 33 Additionally, it is essential to take account of the bystanders who usually play a critical role as audience to the cyberbullying in a range of participant roles, and who have the potential to be mobilised to take action against cyberbullying. Reference Salmivalli 9 , Reference Cowie 34 For example, a system of young cyber mentors, trained to monitor websites and offer emotional support to cyber victims, was positively evaluated by adolescents. Reference Banerjee, Robinson and Smalley 35 Similarly, DiBasilio Reference DiBasilio 33 showed that peer leaders in school played a part in prevention of cyberbullying by creating bullying awareness in the school, developing leadership skills among students, establishing bullying intervention practices and team-building initiatives in the student community, and encouraging students to behave proactively as bystanders. This intervention successfully led to a decline in cyberbullying, in that the number of students who participated in electronic bullying decreased, while students’ understanding of bullying widened.

Although recommended strategies for coping with cyberbullying abound, there remains a lack of evidence about what works best and in what circumstances in counteracting its negative effects. However, it would appear that if we are to solve the problem of cyberbullying, we must also understand the networks and social groups where this type of abuse occurs, including the importance that digital worlds play in the emotional lives of young people today, and the disturbing fact that cyber victims can be targeted at any time and wherever they are, so increasing their vulnerability.

There are some implications for professionals working with children and young people. Punitive methods tend on the whole not to be effective in reducing cyberbullying. In fact, as Shariff & Strong-Wilson Reference Shariff, Strong-Wilson and Kincheloe 36 found, zero-tolerance approaches are more likely to criminalise young people and add a burden to the criminal justice system. Interventions that work with peer-group relationships and with young people’s value systems have a greater likelihood of success. Professionals also need to focus on the values that are held within their organisations, in particular with regard to tolerance, acceptance and compassion for those in distress. The ethos of the schools where children and young people spend so much of their time is critical. Engagement with school is strongly linked to the development of positive relationships with adults and peers in an environment where care, respect and support are valued and where there is an emphasis on community. As Batson et al Reference Batson, Ahmad, Lishner, Tsang, Snyder and Lopez 37 argue, empathy-based socialisation practices encourage perspective-taking and enhance prosocial behaviour, leading to more satisfying relationships and greater tolerance of stigmatised outsider groups. This is particularly relevant to the discussion since researchers have consistently found that high-quality friendship is a protective factor against mental health difficulties among bullied children. Reference Skrzypiec, Slee, Askell-Williams and Lawson 38

Finally, research indicates the importance of tackling bullying early before it escalates into something much more serious. This affirms the need for schools to establish a whole-school approach with a range of systems and interventions in place for dealing with all forms of bullying and social exclusion. External controls have their place, but we also need to remember the interpersonal nature of cyberbullying. This suggests that action against cyberbullying should be part of a much wider concern within schools about the creation of an environment where relationships are valued and where conflicts are seen to be resolved in the spirit of justice and fairness.

Acknowledgement

I am grateful to the COST ACTION IS0801 for its support in preparing this article ( https://sites.google.com/site/costis0801 ).

Declaration of interest

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Volume 37, Issue 5
Helen Cowie (a1)
DOI: https://doi.org/10.1192/pb.bp.112.040840

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Open Access

Peer-reviewed

Research Article

How childhood psychological abuse affects adolescent cyberbullying: The chain mediating role of self-efficacy and psychological resilience

Roles Writing – review & editing

* E-mail: [email protected]

Affiliation School of Education Science, Nanjing Normal University, Jiangsu, China

Roles Investigation, Writing – original draft

Affiliation School of Computing, Nanjing University of Information Science & Technology, Jiangsu, China

Haihua Ying,

Published: September 9, 2024
https://doi.org/10.1371/journal.pone.0309959
Peer Review
Reader Comments

Despite the recognition of the impact of childhood psychological abuse, self-efficacy, and psychological resilience on cyberbullying, there is still a gap in understanding the specific mechanisms through which childhood psychological abuse impacts cyberbullying via self-efficacy and psychological resilience.

Based on the Social Cognitive Theory, this study aims to investigate the link between childhood psychological abuse and cyberbullying in adolescents, mediated by the sequential roles of self-efficacy and psychological resilience. The sample consisted of 891 students ( M = 15.40, SD = 1.698) selected from four public secondary schools in Jiangsu Province, Eastern China. All the participants filled in the structured self-report questionnaires on childhood psychological abuse, self-efficacy, psychological resilience, and cyberbullying. The data were analyzed using SPSS 24.0 and structural equation modeling (SEM) in AMOS 24.0.

The findings of this study are as follows: (1) Childhood psychological abuse is positively associated with adolescent cyberbullying; (2) Self-efficacy plays a mediating role between childhood psychological abuse and adolescent cyberbullying; (3) Psychological resilience plays a mediating role between childhood psychological abuse and adolescent cyberbullying; (4) Self-efficacy and psychological resilience play a chain mediation role between childhood psychological abuse and adolescent cyberbullying.

This study contributes to a deeper understanding of the underlying mechanisms linking childhood psychological abuse to adolescent cyberbullying, shedding light on potential pathways for targeted interventions and support programs to promote the well-being of adolescents in the face of early adversity.

Citation: Ying H, Han Y (2024) How childhood psychological abuse affects adolescent cyberbullying: The chain mediating role of self-efficacy and psychological resilience. PLoS ONE 19(9): e0309959. https://doi.org/10.1371/journal.pone.0309959

Editor: Amgad Muneer, The University of Texas, MD Anderson Cancer Center, UNITED STATES OF AMERICA

Received: February 6, 2024; Accepted: August 21, 2024; Published: September 9, 2024

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

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The rapid development of the internet has brought many conveniences to our lives, but it has also brought numerous negative impacts, such as internet addiction [ 1 ], online fraud [ 2 ], and cyberbullying [ 3 ]. Among these, cyberbullying has been referred to as an “invisible fist”, with its harm being greater than traditional bullying and having a wider impact [ 4 ]. Cyberbullying is characterized by deliberate, repetitive, and malicious acts which are carried out using modern communication technologies, aimed at causing harm to others [ 5 , 6 ]. It comprises two dimensions: cyberbullying victimization and cyberbullying perpetration [ 7 ]. This pervasive issue is recognized globally [ 8 ], as evidenced by data from 2019, which revealed that one-third of young people from 30 countries consistently reported being victims of cyberbullying [ 9 ]. In China, the number of underage internet users reached 183 million in 2020, with 24.3% of minors reporting experiencing cyber violence, according to the “Research Report on Internet Usage among Minors in China in 2020” [ 10 ]. Adolescents are particularly vulnerable to cyberbullying [ 11 ]. The survey results indicate that approximately 52.2% of adolescents in China have experienced at least one incident of cyberbullying in the past year [ 12 ]. Cyberbullying not only impacts the psychological well-being of adolescents, but also lead to their difficulties in social adaptation and potentially tragic outcomes [ 13 ]. Therefore, it is of great significance to explore the factors influencing adolescent cyberbullying for prevention and intervention.

Cyberbullying is influenced by both environmental factors and individual factors [ 14 ]. Childhood psychological abuse is an important environmental factor influencing cyberbullying [ 15 ]. Child psychological abuse refers to the series of inappropriate fostering methods that are repeatedly and continuously adopted by the fosterer during the process of children’s growth, including intimidation, neglect, disparagement, interference, and indulgence [ 16 ]. Previous research has established a positive correlation between childhood psychological abuse and adolescent cyberbullying [ 17 , 18 ]. High levels of childhood psychological abuse have been associated with higher levels of cyberbullying, while low levels of childhood psychological abuse can hinder adolescent cyberbullying [ 19 ]. Self-efficacy and psychological resilience are two individual factors that have been extensively explored in relation to cyberbullying [ 20 ]. Self-efficacy refers to an individual’s confidence and expectation in their ability to take effective action and accomplish tasks in specific situations [ 21 ]. Psychological resilience is defined as the adaptive ability to maintain an active life despite adversity and stressful events [ 22 ]. They have been found to exhibit a negative correlation with adolescent cyberbullying. For example, Özdemir and Bektaş suggested that self-efficacy plays a negative role in cyberbullying [ 23 ]. Similarly, Clark and Bussey observed a noteworthy negative association between self-efficacy and cyberbullying among adolescents [ 24 ]. Güçlü-Aydogan et al. posited that psychological resilience has a negative impact on cyberbullying [ 20 ]. The findings highlight the importance of considering both self-efficacy and psychological resilience in understanding adolescent cyberbullying.

Despite scholars proposing the influence of these factors on adolescent cyberbullying, the specific mechanisms through which childhood psychological abuse affects adolescent cyberbullying via self-efficacy and psychological resilience remain understudied. To address this research gap, this study aims to investigate the interactive effects of childhood psychological abuse, self-efficacy, psychological resilience on adolescent cyberbullying, thereby providing a holistic understanding of the relationship between these factors. Furthermore, the study endeavors to investigate the impact of childhood psychological abuse on adolescent cyberbullying, with a specific focus on the mediating roles of self-efficacy and psychological resilience. This study seeks to address the following questions: First, what is the relationship between childhood psychological abuse and adolescent cyberbullying? Second, does self-efficacy mediate the relationship between childhood psychological abuse and adolescent cyberbullying? Third, does psychological resilience mediate the relationship between childhood psychological abuse and adolescent cyberbullying? Fourth, is there a serial mediation effect of self-efficacy and psychological resilience between childhood psychological abuse and adolescent cyberbullying? This study is significant as it addresses a gap in the existing literature and provides insights into the determinants of adolescent cyberbullying. Moreover, by exploring the mediating mechanisms through which childhood psychological abuse impacts adolescent cyberbullying, this study provides valuable guidance for educators and parents seeking to reduce adolescent cyberbullying.

The structure of the remaining sections of this article is as follows. Section 2 provides an overview of the theoretical background and hypothesis development. Section 3 details the materials and methods, encompassing participants, the research process, research instruments, and statistical analysis. Section 4 covers common method variance, descriptive statistics, correlation analysis, examination of the model, and testing for mediation effects. Section 6 presents the findings, limitations, and implications.

2. Theoretical background and hypothesis development

2.1 theoretical background.

Social Cognitive Theory (SCT), originally proposed by Bandura [ 21 ], provides a robust theoretical framework for this study. The theory includes three elements: environment, personal factors, and behavior [ 25 ]. Environment is defined as the external influences that affect an individual’s behavior, such as social norms, cultural values, and physical surroundings, while personal factors refer to an individual’s cognitive, affective, and biological characteristics, including beliefs, emotions, and genetic predispositions [ 26 ]. Behavior encompasses the actions and responses exhibited by an individual in various situations [ 21 ]. Unlike some other theories that focus solely on either environmental or personal determinants of behavior, SCT emphasizes the dynamic interaction between environment, personal factors, and behavior. It posits that individuals are not simply passive recipients of environmental influences, but rather they actively engage with and interpret their surroundings. Personal factors, such as cognitive processes and emotional states, play a crucial role in mediating the impact of the environment on behavior. Similarly, an individual’s behavior can also influence and modify their environment and personal factors. In this study, childhood psychological abuse is considered an environmental factor, while self-efficacy and psychological resilience as two personal factors. Cyberbullying, heralded as individuals’ social behavior, can also be explained by environmental and personal factors [ 27 ]. Childhood psychological abuse has a significant impact on the development of individuals’ self-efficacy. An enhanced sense of self-efficacy enables individuals to effectively cope with academic and social challenges, engage actively in demanding learning tasks, and develop psychological resilience [ 28 ]. Moreover, self-efficacy significantly reduces the occurrence of cyberbullying by bolstering individuals’ confidence and coping abilities, while psychological resilience lowers the risk of becoming a victim of cyberbullying by improving individuals’ adaptability to adversity [ 20 ]. By employing this theoretical framework, we can gain a comprehensive understanding of the association between childhood psychological abuse and cyberbullying, elucidating the mediating roles of self-efficacy and psychological resilience. This theoretical model in the study is visually represented in Fig 1 .

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https://doi.org/10.1371/journal.pone.0309959.g001

2.2 Hypothesis development

2.2.1 childhood psychological abuse and cyberbullying..

Numerous studies have provided compelling evidence of the link between childhood psychological abuse and subsequent engagement in cyberbullying behaviors [ 15 , 29 , 30 ]. Research has proposed that adverse experiences of psychological abuse in childhood can impact brain function states, such as persistent stress and heightened neurotic anxiety, prompting individuals to suppress and bury these feelings in their subconscious, ultimately leading to engaging in cyberbullying behavior [ 31 ]. Research has also proposed that childhood psychological abuse can have an impact on psychological development, thus leading to cyberbullying [ 19 , 32 ]. For instance, Xu and Zheng demonstrated that childhood emotional abuse can damage an individual’s self-esteem and self-confidence, making them seek to control and gain a sense of power through cyberbullying [ 33 ]. Moreover, Li et al. identified that childhood psychological abuse may lead to inner feelings of anger in individuals, causing them to seek comfort and escape from reality in online environments, ultimately leading them to release these negative emotions by bullying others online [ 34 ]. Based on the evidence presented in the literature, it is hypothesized:

H1: Childhood psychological abuse is positively associated with adolescent cyberbullying.

2.2.2 Self-efficacy as a mediator.

There is a well-established negative relationship between childhood psychological abuse and self-efficacy [ 35 ]. For example, Soffer et al. conducted a study that revealed individuals who experienced childhood psychological abuse reported lower levels of self-efficacy in various domains, such as academic, social, and personal domains [ 36 ]. This suggests that the negative experiences associated with abuse can undermine an individual’s belief in their capabilities. Supporting this notion, Hosey emphasized the detrimental effects of childhood psychological abuse on an individual’s self-efficacy beliefs [ 37 ]. Their research highlighted the long-lasting impact of abuse on self-efficacy. Furthermore, Bentley and Zamir conducted a longitudinal study that found the negative relationship between childhood psychological abuse and self-efficacy persisted over time [ 38 ]. This suggests that the effects of abuse on self-efficacy may endure throughout adolescence and beyond. Taken together, these studies provide compelling evidence that childhood psychological abuse can significantly impact an individual’s self-efficacy.

Studies have explored the relationship between self-efficacy and cyberbullying [ 23 , 39 ]. Clark and Bussey conducted a study examining the relationship between self-efficacy and cyberbullying victimization and revealed that higher levels of self-efficacy were associated with higher rates of defending behavior during cyberbullying episodes [ 24 ]. Similarly, Bussey et al. investigated the relationship between self-efficacy and cyberbullying defending and indicated that individuals with a high level of self-efficacy were more likely to defend cyberbullying [ 40 ]. Ferreira et al. surveyed 676 students from the fifth to twelfth grade and found that self-efficacy significantly impacted cyberbullying behavior, with students exhibiting higher self-efficacy demonstrating more proactive problem-solving behavior, thereby reducing instances of cyberbullying [ 41 ]. Additionally, Ybarra and Mitchell found that self-efficacy plays a crucial role in moderating the negative effects of cyberbullying [ 42 ]. Their studies revealed that individuals with higher self-efficacy were better able to cope with and overcome the negative consequences of cyberbullying.

The above views indicate that childhood psychological abuse may negatively affect individuals’ self-efficacy, which in turn, may contribute to an increased likelihood of engaging in cyberbullying behavior. Based on these, the following assumption is proposed:

H2: Self-efficacy may play a mediating role in the association between childhood psychological abuse and adolescent cyberbullying.

2.2.3 Psychological resilience as a mediator.

It has been found that psychological resilience can be influenced by childhood psychological abuse [ 43 ]. Yang et al. carried out a cross-sectional survey among 1607 adolescents and proposed that childhood psychological abuse may contribute to the development of psychological resilience during the learning process [ 44 ]. Additionally, Arslan conducted a survey involving 937 adolescents from various high schools and emphasized that childhood psychological abuse was a consistent predictor of psychological resilience [ 45 ]. These findings collectively support the notion that childhood psychological abuse may have a positive impact on the psychological resilience of adolescents.

Studies have shown that psychological resilience can influence cyberbullying [ 46 , 47 ]. Students with higher levels of resilience were less likely to engage in cyberbullying behaviors [ 48 ]. Hinduja and Patchin have argued that students with more psychological resilience were less likely to report being online victims, and among those who did report being victims, their psychological resilience worked as a “buffer,” preventing negative effects at school [ 49 ]. Similarly, Güçlü-Aydogan et al. investigated the role of psychological resilience in mitigating the impact of cyberbullying and found adolescents who exhibit higher levels of psychological resilience are capable of surviving adversity and uncertainty through the use of healthy, effective, and adaptable coping mechanisms, which may result in reduced cyber victimization [ 20 ]. Zhang et al. have demonstrated that students who experienced more childhood psychological abuse have lower psychological resilience, which plays a crucial role in bullying victimization [ 50 ]. Therefore, this study speculates that there is a positive relationship between adolescents’ psychological resilience and their cyberbullying, and psychological resilience may play an intermediary role between childhood psychological abuse and cyberbullying.

Psychological resilience is believed to be influenced by self-efficacy [ 51 ]. Bandura proposed a comprehensive framework for understanding the role of self-efficacy in promoting psychological resilience [ 21 ]. Individuals with higher levels of self-efficacy are better equipped to navigate and overcome challenges, leading to greater psychological resilience [ 52 ]. Sabouripour et al. [ 28 ] revealed that individuals with higher levels of self-efficacy demonstrated greater psychological resilience when facing health challenges. Therefore, it is believed that childhood psychological abuse may influence cyberbullying via the serial variables of self-efficacy and psychological resilience. Given this, the following hypotheses are proposed:

H3: Psychological resilience plays a mediating role in the association between childhood psychological abuse and adolescents’ cyberbullying.
H4: Self-efficacy and psychological resilience play a chain mediating role in the association between childhood psychological abuse and adolescent cyberbullying.

Based on Social Cognitive Theory and the above hypotheses, this study aims to apply SCT to explore the relationship between childhood psychological abuse and adolescents’ cyberbullying. Specifically, we will examine the mediating roles of self-efficacy and psychological resilience. A theoretical model ( Fig 1 ) will be constructed to investigate these relationships.

3. Materials and methods

3.1 participants.

This study utilized G*power 3.1 software [ 53 ] to calculate the required sample size, with an effect size set at 0.3 and α set at 0.05. The results indicated that in order to achieve a statistical power of 0.95, a total of 145 participants were needed. Furthermore, based on the requirement of Structural Equation Modeling (SEM) [ 54 ] that the appropriate sample size should be at least ten times the total observed variables, it was determined that a minimum of 800 participants would be necessary. The survey initially identified schools for sample collection based on convenience sampling principles. However, to ensure representativeness, cluster sampling was subsequently employed at the class level to select the 1,000 samples from 4 secondary schools (2 public junior high schools and 2 public senior high schools) in Jiangsu province, China. The selected public schools for this study exhibit diversity in terms of student backgrounds, academic achievements, and socio-economic statuses, thereby approximating the overall student population in the region. A total of the 1000 questionnaires were distributed, and after excluding the invalid questionnaires with missing answers or consistent responses, 891 valid questionnaires were collected, resulting in an effective response rate of 89.1%. Participants were aged 13 to 18 years old (M = 15.40, SD = 1.698), with 408 (45.8%) being boys, and 483 (54.2%) being girls. In terms of grade, the participants included 152 (17.1%) in the 7th grade, 167 (18.7%) in the 8th grade, 148 (16.6%) in the 9th grade, and 164 (18.4%) in the 10th grade, 113 (12.7%) in the 11th grade, 147 (16.5%) in the 12th grade.

3.2 Procedure

The study was conducted in accordance with the approved guidelines from the Ethical Review Committee of Hohai University (Protocol Number: Hhu10294-240125). Additionally, consent was obtained from the principals, students, and their parents in the participating schools. Before the survey, students were informed about the confidentiality of the survey results and their intended use solely for research purposes in class. They were also assured that measures had been implemented to safeguard their privacy. The questionnaires were then distributed and thoroughly explained to the participants. After 15 minutes, the trained research assistants collected the questionnaires on the spot, and subsequently, the data from the questionnaires were meticulously sorted and analyzed to derive meaningful conclusions.

3.3 Research instrument

3.3.1 childhood psychological abuse scale..

The measurement of childhood psychological abuse was conducted using Pan et al.’s scale [ 16 ], which comprises 23 items capturing five dimensions: intimidation, neglect, disparagement, interference, and indulgence. For example, one item on the scale is “My parents interrogate me about the details of my interactions with friends.” A 5-point Likert scale was employed, with scores ranging from 0 to 4, indicating “none” to “always”, and higher scores reflecting higher childhood psychological abuse. The scale has been demonstrated to possess good reliability and validity [ 55 ].

3.3.2 Self-efficacy scale.

Self-efficacy was measured using the scale developed by Wang et al. [ 56 ], which is based on Schwarzer and Jerusalem’s General Self-Efficacy Scale [ 57 ]. This scale consists of 10 items, presented in a single structure, with statements such as “I can calmly face challenges because I trust my ability to handle problems.” A 4-point Likert scale was utilized, with scores ranging from 1–4, representing “strongly disagree” to “strongly agree” respectively. Higher scores indicate higher levels of self-efficacy. The scale has good reliability and validity in previous study [ 58 ].

3.3.3 Psychological resilience scale.

The psychological resilience scale, developed by Hu and Gan [ 59 ], was utilized to evaluate the psychological resilience levels of adolescents. This scale comprises 27 items, encompassing five dimensions: goal focus, emotional control, positive cognition, interpersonal assistance, and family support. For example, one item states, “I believe that everything has its positive aspects”. The scale is rated on a 5-point Likert scale, with scores ranging from 1(strongly disagree) to 5(strongly agree), and higher scores indicating a stronger sense of psychological resilience. The scale demonstrates good reliability and validity, which has been validated by Xiao et al. [ 60 ].

3.3.4 Cyberbullying scale.

The measurement of adolescents’ cyberbullying was carried out using the revised Chinese version of the Cyberbullying Scale by You [ 7 ]. This scale comprises two subscales: the cyberbullying victimization scale (12 items, such as “Someone has shared or used my photos or videos online without my consent”) and the cyberbullying perpetration scale (8 items, such as “When conversing with someone online and things don’t go my way, I may resort to using offensive language to insult them”). The scale utilizes a 4-point rating, ranging from 1 (Never happened) to 4 (Frequently happened), with higher scores indicating a higher frequency of cyberbullying. Studies have demonstrated good reliability and validity among Chinese adolescents [ 61 , 62 ].

3.4 Statistical analysis

The collected data were analyzed using SPSS 24.0 and AMOS 24.0. Initially, the Harman single-factor test was conducted in SPSS 24.0 to assess common method variance. Subsequently, correlation analysis was performed on the variables of childhood psychological abuse, self-efficacy, psychological resilience, and cyberbullying in SPSS 24.0. Then, the measurement model and structural model were assessed using factor loadings, Cronbach’s α, CR, AVE, and goodness-of-fit. Finally, the mediation test was conducted utilizing AMOS 24.0. To ascertain the statistical significance of the mediating effects posited by the hypotheses, a bootstrapping method was employed, with the generation of 95% confidence intervals to provide a robust evaluation of these effects.

4.1 Common method bias analysis

To mitigate the influence of common method bias, in addition to ensuring anonymous responses during the survey, Harman’s single-factor test was conducted [ 63 ]. Exploratory factor analysis was performed on the 80 items of the questionnaire, and an unrotated principal component analysis revealed the presence of 11 factors with eigenvalues greater than 1. However, the first factor accounted for only 32.534% of the variance, which is below the critical threshold of 40% [ 64 ], indicating that there is no significant evidence of common method bias.

4.2 Correlation analyses

Table 1 shows the results of the correlation analysis. Specifically, there is a significant positive correlation between childhood psychological abuse and cyberbullying (r = 0.398, p < 0.01); There is a significant negative correlation between childhood psychological abuse and both self-efficacy (r = -0.162, p < 0.01); Childhood psychological abuse and psychological resilience established a significant negative relationship (r = -0.445, p < 0.01); Self-efficacy was significantly and negatively related to adolescent psychological resilience (r = 0.459, p < 0.01); Self-efficacy was significantly and negatively related to adolescent cyberbullying(r = -0.309, p < 0.01); Psychological resilience was significantly and negatively related to adolescent cyberbullying(r = -0.490, p < 0.01). Among these correlations, the highest correlation is observed between psychological resilience and cyberbullying, while the lowest correlation is observed between childhood psychological abuse and self-efficacy.

https://doi.org/10.1371/journal.pone.0309959.t001

4.3 Measurement model

The fit indices for the measurement model were assessed to examine how well the model fits the data. Jackson et al. have suggested that a model fits the data when the goodness-of-fit index is between 1 and 3 for x 2 / df, greater than 0.9 for GFI, AGFI, NFI, TLI, and CFI, less than 0.08 for SMSEA [ 54 ]. Childhood psychological abuse showed a good model fit: χ2/df = 2.939 (X 2 = 567.167 df = 193), RMSEA = 0.047, TLI = 0.970, NFI = 0.966, CFI = 0.977, GFI = 0.946, AGFI = 0.923. Self-efficacy showed a good model fit: χ2/df = 2.847 (X 2 = 54.093, df = 19), RMSEA = 0.046, TLI = 0.986, NFI = 0.991, CFI = 0.994, GFI = 0.988, AGFI = 0.964). Psychological resilience also meets the requirement with χ2/df = 3.097 (X 2 = 607.072, df = 196), RMSEA = 0.049, TLI = 0.962, NFI = 0.969, CFI = 0.979, GFI = 0.951, AGFI = 0.905, together with cyberbullying (χ2/df = 2.996, X2 = 245.708, df = 82, RMSEA = 0.047, TLI = 0.983, NFI = 0.989, CFI = 0.993, GFI = 0.974, AGFI = 0.933). All the data support the robustness of the measurement model.

Additionally, in the measurement model, the standardized factor loadings are significant and ideally above 0.50, indicating that the items are good indicators of their respective constructs [ 65 ]. The values of Cronbach’s α and CR are over 0.7, indicating the acceptable reliability [ 66 ]. The AVE values surpassed the recommended threshold of 0.5, signifying satisfactory convergent validity, and the AVE value reaching 0.36 shows acceptable convergent validity [ 67 ]. The square root of the AVE should be greater than the correlations with other constructs, indicating that the constructs have discriminant validity [ 68 ].

As presented in Table 2 , the value of Cronbach’s α ranged from 0.931 to 0.974, indicating high reliability. The standardized factor loadings covered a range between 0.528 and 0.890 ( p < .001), while the values of CR and AVE ranged from 0.932 to 0.975 and from 0.482 to 0.660 respectively, indicating acceptable convergent validity. In Table 3 , the square root of AVE for each construct was greater than the correlation with other constructs, indicating acceptable levels of discriminant validity.

https://doi.org/10.1371/journal.pone.0309959.t002

https://doi.org/10.1371/journal.pone.0309959.t003

4.4 Structural model

The structural model was evaluated using the goodness-of-fit indices and path coefficients. The fit indices for the structural model are as follows: X 2 / df = 1.403 (X 2 = 1135.419, df = 809), GFI = 0.913, AGFI = 0.901, CFI = 0.973, TII = 0.971, NFI = 0.913, RMSEA = 0.033. All the values met the recommended thresholds [ 54 ], indicating a good fit for the structural model. Additionally, as shown in Fig 2 , all the path coefficients were statistically significant (P < 0.01) by performing a bootstrap procedure with 5000 resamplings. Therefore, the structural model was supported by these empirical data.

https://doi.org/10.1371/journal.pone.0309959.g002

4.5 Testing for mediation effect

The study employed structural equation modeling to examine the mediating effects among the four variables. The bootstrap proposed by MacKinnon [ 69 ] was used for significance testing, with a sample size of 5000 and a confidence level of 95%. A mediating effect is considered statistically significant when the bootstrap 95% confidence interval of the indirect effects estimated by the bias-corrected percentile method does not include zero [ 69 ]. Data analysis was performed using Amos 24.0 software. The results of the mediation analysis for the mediating effect of self-efficacy and psychological resilience on the relationship between childhood psychological abuse and cyberbullying are presented in Table 4 . The direct effect of childhood psychological abuse on adolescent cyberbullying is significant ( β = 0.296, P < 0.001), supporting the acceptance of H1. Self-efficacy and psychological resilience mediate the relationship between childhood psychological abuse and cyberbullying, with a total indirect effect of 0.214 ( P < 0.001). Specifically, the indirect effect is composed of three pathways: The pathway of childhood psychological abuse → self-efficacy→ cyberbullying had an indirect effect of 0.025 with a 95% confidence interval of [0.007, 0.053]; The pathway of childhood psychological abuse → self-efficacy→ psychological resilience → cyberbullying had an indirect effect of 0.028 with a 95% confidence interval of [0.013, 0.049]; The pathway of childhood psychological abuse → psychological resilience → cyberbullying had an indirect effect of 0.162 with a 95% confidence interval of [0.112, 0.227]. The Bootstrap 95% confidence intervals for all three indirect effects do not include zero, indicating that all three indirect effects are statistically significant. These results provide support for H 2, H3, and H4.

https://doi.org/10.1371/journal.pone.0309959.t004

In addition, the indirect effect percentage of self-efficacy and psychological resilience as partial mediators were examined. As indicated in Table 4 , among the three significant indirect mediators, the indirect effect of self-efficacy accounts for 11.5% of the total indirect effect, while the indirect effect of psychological resilience accounts for 75.7% of the total indirect effect. Besides, the indirect effect of self-efficacy and psychological resilience accounts for 12.8% of the total indirect effect. This indicates that the indirect effect of psychological resilience is the greatest. The specific pathways of childhood psychological abuse acting on cyberbullying through self-efficacy and psychological resilience are detailed in Fig 2 .

5. Discussion

Empirical evidence suggests that childhood psychological abuse, self-efficacy, and psychological resilience have an impact on cyberbullying. However, there is still a gap in understanding the specific mechanisms through which childhood psychological abuse impacts cyberbullying via self-efficacy and psychological resilience. This research aimed to construct a mediation model to investigate whether childhood psychological abuse would be indirectly correlated with adolescents’ cyberbullying through self-efficacy and psychological resilience. The findings, limitations and implications are presented as follows.

5.1 Findings

The results of the study revealed a direct and positive link between childhood psychological abuse and adolescents’ cyberbullying. This not only corroborates Kircaburun et al.’s research [ 70 ], which identified a positive correlation between childhood psychological abuse and adolescents’ cyberbullying but also aligns with the notion proposed by Zhang et al. [ 30 ] that psychological abuse contributes to the occurrence of cyberbullying. One potential explanation is that individuals who have experienced abuse may struggle to regulate their emotions, increasing the likelihood of displaying aggressive behavior in online settings. Adolescents who experienced greater psychological abuse during childhood are more inclined to exhibit negative online behaviors [ 19 ]. This study further underscores the significance of childhood psychological abuse as a predictive factor for cyberbullying.

The results of the study identified self- efficacy as one significant partial mediating role between childhood psychological abuse and adolescents’ cyberbullying. This finding is consistent with previous research suggesting a negative association between childhood psychological abuse and self-efficacy [ 35 , 38 ], as well as a negative association between self-efficacy and cyberbullying [ 23 , 24 ]. These findings provide support for the idea that childhood psychological abuse plays a crucial role in shaping the perception of self-efficacy, which subsequently influences adolescents’ engagement in cyberbullying behaviors. This finding adds further evidence to the understanding of the role of self-efficacy in the link between childhood psychological abuse and cyberbullying.

The results of the study demonstrated that psychological resilience plays a significant partial mediating role between childhood psychological abuse and adolescents’ cyberbullying. This finding is consistent with previous research suggesting a negative association between childhood psychological abuse and psychological resilience [ 44 , 45 ], as well as a negative association between psychological resilience and cyberbullying [ 20 , 48 ]. One potential reason is that childhood psychological abuse can lead to a sense of helplessness, frustration, and negative emotions in children, hindering the development of psychological resilience. Individuals with lower psychological resilience may have difficulty seeking help when facing adversity and may resort to negative behaviors to avoid problems, leading to an increase in cyberbullying. These findings provide support for the idea that childhood psychological abuse plays a crucial role in shaping the perception of psychological resilience, which subsequently influence adolescents’ engagement in cyberbullying behaviors.

The results of the study further showed that both self-efficacy and psychological resilience functioned as a chain mediating role between childhood psychological abuse and adolescents’ cyberbullying. In other words, adolescents with high childhood psychological abuse scores tend to perceive lower self-efficacy, leading to an overall lower belief in their ability to effectively cope with and overcome challenges. This, in turn, is associated with lower levels of psychological resilience, resulting in increased engagement in cyberbullying behaviors. This finding further elucidates the mechanisms by which environmental systems and individual factors influence adolescents’ cyberbullying and advances the previous research by shedding light on how childhood psychological abuse can increase adolescents’ cyberbullying. It is worth noting that although both serial mediation and self-efficacy as mediators were established, their percentages were only 12.8% and 11.5%, respectively, which were lower than the mediating effect of psychological resilience. This indicates that psychological resilience has a more significant impact on cyberbullying behaviors. This suggests that when intervening in adolescent cyberbullying behaviors at the family level, cultivating their perception of psychological resilience should be given greater priority compared to enhancing their self-efficacy.

5.2 Implications

The findings of this study have significant implications for both theory and practice in understanding and addressing adolescents’ cyberbullying.

From a theoretical perspective, this study contributes to the existing literature by unravelling the intricate relationship between childhood psychological abuse and adolescent cyberbullying with the application of the Social Cognitive Theory. By identifying self-efficacy and psychological resilience as pivotal mediators, the study provides a conceptual framework that enhances our comprehension of the psychological processes underpinning cyberbullying behaviors. This understanding is crucial for developing psychological interventions and educational programs aimed at bolstering self-efficacy and fostering resilience among adolescents. Moreover, the findings of the study offer insights into the buffering effects of positive psychological attributes against the adverse outcomes of childhood maltreatment, enriching the existing literature on the subject and guiding future research endeavors in the field of developmental psychology and educational studies.

On a practical level, these findings offer valuable insights for designing effective interventions to prevent and address cyberbullying among adolescents. Specifically, by addressing childhood psychological abuse, enhancing self-efficacy, and fostering psychological resilience, we can reduce the likelihood of adolescents engaging in or being affected by cyberbullying. To address childhood psychological abuse, parents need to increase self-awareness and understand the impact of their emotions and behaviors on their children. They can learn positive parenting techniques such as active listening, respect, and expressing love. Additionally, establishing a positive parent-child relationship, including positive communication and emotional support, as well as clear rules and boundaries, can help reduce the occurrence of psychological abuse [ 71 ]. In enhancing self-efficacy, both schools and parents play crucial roles. Schools can design tasks that are challenging yet fair, enabling adolescents to experience success and bolster their sense of self-efficacy. Teachers should complement this by offering timely recognition and encouragement, nurturing greater confidence in their abilities. Meanwhile, parents should lead by example, exhibiting positive and proactive attitudes and behaviors. By doing so, they create an environment that allows adolescents to observe and imitate these behaviors, providing them with opportunities to practice and excel in various tasks, thereby, contributing to the development of their self-efficacy. To foster psychological resilience, parents should assist children in cultivating positive values and building self-confidence. Schools should prioritize student growth and development by establishing appropriate evaluation systems and avoiding excessive competition. Students themselves should strive to establish positive interpersonal relationships with their peers, fostering mutual support and respect.

5.3 Limitations

It is important to recognize several limitations inherent in this study. Firstly, the use of a cross-sectional design precludes the establishment of causal relationships between variables. It is recommended that future research employ longitudinal or experimental designs to validate the causal hypotheses. Secondly, the reliance on self-reported data from middle school students introduces the possibility of biases, such as social desirability. Future studies should consider gathering data from multiple sources, such as parents or peers, to enhance the robustness of findings. Lastly, there are other unexplored factors in this study, such as self-control and self-esteem, which could potentially mediate the relationship. Future studies should focus on investigating the role of these factors in developing targeted interventions to reduce the occurrence of cyberbullying among adolescents.

6. Conclusion

The findings of this study can be summarized as follows: (1) Childhood psychological abuse, self-efficacy, psychological resilience, and cyberbullying are significantly correlated with each other. Specifically, childhood psychological abuse is significantly positively correlated with cyberbullying, while self-efficacy and psychological resilience are significantly negatively correlated with cyberbullying; (2) Childhood psychological abuse influences cyberbullying indirectly through self-efficacy and psychological resilience respectively; (3) Childhood psychological abuse can affect cyberbullying through the mediating chain role of self-efficacy and psychological resilience.

Supporting information

https://doi.org/10.1371/journal.pone.0309959.s001

Acknowledgments

The authors wish to thank Jingtao Wu for providing technical support in data analysis for this research.

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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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Published: 14 January 2023

Prevalence and related risks of cyberbullying and its effects on adolescent

Gassem Gohal 1 ,
Ahmad Alqassim 2 ,
Ebtihal Eltyeb 1 ,
Ahmed Rayyani 3 ,
Bassam Hakami 3 ,
Abdullah Al Faqih 3 ,
Abdullah Hakami 3 ,
Almuhannad Qadri 3 &
Mohamed Mahfouz 2

BMC Psychiatry volume 23 , Article number: 39 ( 2023 ) Cite this article

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Cyberbullying is becoming common in inflicting harm on others, especially among adolescents. This study aims to assess the prevalence of cyberbullying, determine the risk factors, and assess the association between cyberbullying and the psychological status of adolescents facing this problem in the Jazan region, Saudi Arabia.

A cross-sectional study was conducted on 355 students, aged between 12–18 years, through a validated online questionnaire to investigate the prevalence and risk factors of cyberbullying and assess psychological effects based on cyberbullying questionnaire and Mental Health Inventory-5 (MHI-5) questions.

The participants in this study numbered 355; 68% of participants were females compared to 32% were males. Approximately 20% of the participants spend more than 12 h daily on the Internet, and the estimated overall prevalence of cyberbullying was 42.8%, with the male prevalence slightly higher than females. In addition, 26.3% of the participants were significantly affected in their academic Performance due to cyberbullying. Approximately 20% of all participants considered leaving their schools, 19.7% considered ceasing their Internet use, and 21.1% considered harming themselves due to the consequences of cyberbullying. There are essential links between the frequency of harassment, the effect on academic Performance, and being a cyber victim.

Conclusions

Cyberbullying showed a high prevalence among adolescents in the Jazan region with significant associated psychological effects. There is an urgency for collaboration between the authorities and the community to protect adolescents from this harmful occurrence.

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Introduction

Cyberbullying is an intentional, repeated act of harm toward others through electronic tools; however, there is no consensus to define it [ 1 , 2 , 3 ]. With the surge in information and data sharing in the emerging digital world, a new era of socialization through digital tools, and the popularization of social media, cyberbullying has become more frequent than ever and occurs when there is inadequate adult supervision [ 4 , 5 ]. A large study that looked at the incidence of cyberbullying among adolescents in England found a prevalence of 17.9%, while one study conducted in Saudi Arabia found a prevalence of 20.97% [ 6 , 7 ]. Cyberbullying can take many forms, including sending angry, rude, or offensive messages; intimidating, cruel, and possibly false information about a person to others; sharing sensitive or private information (outing); and exclusion, which involves purposefully leaving someone out of an online group [ 8 ]. Cyberbullying is influenced by age, sex, parent–child relationships, and time spent on the Internet [ 9 , 10 ]. Although some studies have found that cyberbullying continues to increase in late adolescence, others found that cyberbullying tends to peak at 14 and 15 years old before decreasing through the remaining years of adolescence [ 11 , 12 , 13 ].

The COVID-19 epidemic has impacted the prevalence of cyberbullying since social isolation regulations have reduced face-to-face interaction, leading to a significant rise in the use of social networking sites and online activity. As a result, there was a higher chance of experiencing cyberbullying [ 14 ].

Unlike traditional Bullying, which usually only occurs in school and is mitigated at home, victims of cyberbullying can be contacted anytime and anywhere. Parents and teachers are seen as saviors in cases of traditional Bullying. Simultaneously, in cyberbullying, children tend to be reluctant to tell adults for fear of losing access to their phones and computers, so they usually hide the cyberbullying incident [ 15 ]. Reports show that cyberbullying is a form of harm not easily avoided by the victim. In addition, in the cyber form of Bullying, identification of the victim and the perpetrator is generally challenging compared to traditional Bullying; this makes an accurate estimation of the problem widely contested [ 16 , 17 ].

There is growing evidence that is cyberbullying causes more significant levels of depression, anxiety, and loneliness than traditional forms of Bullying. A meta-analysis examining the association between peer victimization, cyberbullying, and suicide in children and adolescents indicates that cyberbullying is more intensely related to suicidal ideation than traditional Bullying [ 18 ]. Moreover, the significant problem is that cyberbullying impacts adolescent due to its persistence and recurrence. A recent report in Saudi Arabia indicated a growing rise in cyberbullying in secondary schools and higher education, from 18% to approximately 27% [ 19 ]. In primary schools and kindergartens in Saudi Arabia, we were not surprised to find evidence that children were unaware that cyberbullying is illegal. Although the study showed an adequate awareness of the problem in our country, Saudi Arabia, there were relatively significant misconceptions [ 20 ].

Adolescents' emotional responses to cyberbullying vary in severity and quality. However, anger, sadness, concern, anxiety, fear, and depression are most common among adolescent cyber victims [ 21 ]. Moreover, cyberbullying may limit students' academic Performance and cause higher absenteeism rates [ 22 ]. Consequently, this study aims to assess the prevalence of cyberbullying, determine the risk factors, and establish the association between cyberbullying and the psychological status of adolescents. We believe our study will be an extension of and significantly add to the literature regarding the nature and extent of cyberbullying in the Jazan region of Saudi Arabia.

A descriptive cross-sectional study was carried out in the Jazan region, a province of the Kingdom of Saudi Arabia. It is located on the tropical Red Sea coast of southwestern Saudi Arabia.

Design and participants

A descriptive cross-sectional study was carried out in the Jazan region, a province of the Kingdom of Saudi Arabia. It is located on the tropical Red Sea coast of southwestern Saudi Arabia. The study targeted adolescents (12–18 years old) who use the Internet to communicate in the Jazan region. The main inclusion criteria are adolescents between 12–18 years who use the Internet and agree to participate; however, it excludes adolescents not matching the inclusion criteria or those refusing to participate in the study. If participants were under 16, the parent and/or legal guardian should be notified. A sample of participants was estimated for this study, and the ideal sample size was calculated to be 385 using the Cochran formula, n = (z) 2 p (1 – p) / d 2 . Where: p = prevalence of cyberbullying 50%, z = a 95% confidence interval, d = error of not more than 5%. A convenience sample was used to recruit the study participants. A self-administrated online questionnaire was used to collect the study information from May to December 2021.

The ethical approval for this study was obtained from The Institute Review Board (IRB) of Jazan University (Letter v.1 2019 dated 08/04/2021). Informed consent was acquired from all participants and was attached to the beginning of the form and mandatory to be read and checked before the participant proceeded to the first part of the questionnaire. For the participants under 16, informed consent was obtained from a parent and legal guardian.

Procedure of data collection and study measures

An Arabic self-administrated online questionnaire was used for this research. This anonymous online survey instrument was based on (Google Forms). The study team distributed the questionnaire to the participants through school teachers. The research team prepared the study questionnaire and chose the relevant cyberbullying scale questions from similar studies [ 5 , 6 ]. The questionnaire was translated by two bilingual professionals to ensure the accuracy and appropriateness of the instrument wording. A panel of experts then discussed and assessed the validity and suitability of the instrument for use on adolescents. The panel also added and edited a few questions to accommodate the local culture of Saudi students. It was validated with a pilot study that included 20 participants. The questionnaire was divided into three main sections. The first part of the questionnaire contains the basic participant information, including gender, age, nationality, school grade, residence, and information about family members and the mother's occupation and education. The mother's level of education was considered as it found that mothers' low levels of education specifically had a detrimental impact on the cyberbullying process [ 23 ]. The second section explores the participant's definition of cyberbullying, questions regarding exposure to cyberbullying as a victim or by bullying another person, and questions considering the possible risk factors behind cyberbullying. The last section explores how cyberbullying affects adolescents psychologically based on the standardized questionnaire Mental Health Inventory-5 (MHI-5). MHI-5 is a well-known, valid, reliable, and brief international instrument for assessing mental health in children and adolescents (such as satisfaction, interest in, and enjoyment of life) and negative aspects (such as anxiety and depression) [ 24 ]. It is composed of five questions, as shown in Table 1 . There are six options available for each question, ranging from "all the time" (1 point) to "none of the time" (6 points); therefore, the adolescent's score varies between five and 30. These questions assess both negative and positive qualities of mental health, as well as questions about anxiety and depression. By adding all the item scores and converting this score to a scale ranging from 0 to 100, the final MHI-5 score is determined, with lower scores indicating more severe depressive symptoms. The value for which the sum of sensitivity and specificity was utilized to establish the ideal cut-off score for MHI-5 in many similar studies was reviewed to reach an optimal conclusion. Therefore, we considered all cut-off values with associated sensitivities and specificities of various MHI-5 cut-off points previously employed among adolescents in similar studies and compared them to conclude that MHI-5 = 70 as our cut points. So the presence of depressive symptoms is considered with an MHI-5 cut-off score of ≤ 70 [ 25 ].

The Questionnaires were initially prepared in English and then translated into Arabic. A native speaker with fluency in English (with experience in translation) converted the questionnaire from the initial English version into Arabic. Then, we performed a pilot study among 20 participants to ensure the readability and understandability of the questionnaire questions. We also assessed the internal consistency of the questionnaire based on Cronbach’s alpha, which produced an acceptable value of 0.672. The internal consistency for Mental Health Inventory-5 (MHI-5) was reported at 0.557. In order to assess the factor structure of the Arabic-translated version of the (MHI-5) questionnaire, a factor analysis was conducted. The factor loading of the instrument is shown in Table 1 . Using principal component analysis and the varimax rotation method, we found a one-component solution explaining 56.766% of the total variance. All items loaded on the first factor ranged from (0.688 to 0.824), which confirms that a single factor has explained all the items of the scale. In addition, Bartlett’s test of sphericity was found significant ( p < 0.001).

Data presentation & statistical analysis

Simple tabulation frequencies were used to give a general overview of the data. The prevalence of cyberbullying was presented using 95% C.I.s, and the Chi-squared test was performed to determine the associations between individual categorical variables and Mental Health. The univariate and multivariate logistic regression model was derived, and unadjusted and adjusted odds ratios (OR) and their 95% confidence intervals (C.I.s) were calculated. A P -value of 0.05 or less was used as the cut-off level for statistical significance. The statistical analysis was completed using SPSS ver. 25.0 (SPSS Inc. Chicago, IL, USA) software.

The distributed survey targeted approximately 385 students, but the precise number of respondents to the questionnaire was 355 (92% response rate), with 68% of female students responding, compared to 32% of male students. More than half of the respondents were secondary school students, with a nearly equal mix of respondents living in cities and rural areas. Table 2 demonstrates that 20% of the participants spend more than 12 h daily on the Internet and electronic gadgets, while only 13% spend less than two hours.

As demonstrated in Table 3 , the total prevalence of cyberbullying was estimated to be 42.8%, with male prevalence somewhat higher than female prevalence. Additional variables, such as the number of hours spent on the Internet, did not affect the prevalence. Table 4 shows the pattern and experience of being cyberbullied across mental health levels, as measured by the MHI-5.

Academic Performance was significantly affected due to cyberbullying in 26.3% of the participants. Furthermore, approximately 20% of all participants considered leaving their schools for this reason. Moreover, 19.7% of the participants thought of stopping using the Internet and electronic devices, while 21.1% considered harming themselves due to the effects of cyberbullying. Regarding associations between various variables and psychological effects using the MHI-5, there are significant associations between whether the participant has been a cyber victim before (cOR 2.8), the frequency of harassment (cOR 1.9), academic Performance (cOR 6.5), and considering leaving school as a result of being a cyber victim (cOR 3.0). In addition, by using univariate logistic regression analysis, there are significant associations between the psychological effects and the participant's thoughts of getting rid of a bully (cOR 2.8), thinking to stop using electronic devices (cOR 3.0), and considering hurting themselves as the result of cyberbullying (cOR 6.4). In addition, the use of the multivariate logistic regression analysis showed that frequency of harassment was the only statistically significant predictor of mental health among adolescents (aOR 2.8). Other variables continue to have higher (aORs) but without statistical significance. All these results are demonstrated in Table 4 .

Cyberbullying prevalence rates among adolescents vary widely worldwide, ranging from 10% to more than 70% in many studies. This variation results from certain factors, specifically gender involvement, as a decisive influencing factor [ 26 , 27 ]. Our study found a prevalence of 42.8% (95% confidence interval (CI): 37.7–48), which is higher than the median reported prevalence of cyberbullying of 23.0% in a scoping review that included 36 studies conducted in the United States in adolescents aged 12 to 18 years old [ 28 ]. A systematic review found that cyberbullying ranged from 6.5% to 35.4% [ 3 ]. These two studies gathered data before the COVID-19 pandemic. When compared to recent studies, it was found that cyberbullying increased dramatically during the COVID-19 era [ 29 , 30 ]. Subsequently, with the massive mandate of world online communication in teaching and learning, young adolescents faced a large amount of cyberspace exposure with all risk-related inquiries. Psychological distress due to COVID-19 and spending far more time on the Internet are vital factors in this problem, which might be a reasonable explanation for our results.

There is insufficient data to compare our findings to the Arab world context, notably Saudi Arabia. Although, according to one study done among Saudi Arabian university students, the prevalence was 17.6%. [ 31 ]. we discovered a considerable discrepancy between this prevalence and our findings, and the decisive explanation is the difference in the target age group studied. Age is a crucial risk factor for cyberbullying, and according to one study, cyberbullying peaks at around 14 and 15 years of age and then declines in late adolescence. Thus, a U-inverted relation exists between prevalence and age [ 11 , 12 , 13 , 32 ].

In our study, males reported being more vulnerable to cyberbullying despite there being more female participants; this inconsistent finding with previous literature requires further investigation. A strong, but not recent, meta-analysis in 2014 reported that, in general, males are likely to cyberbully more than females. Females were more likely to report cyberbullying during early to mid-adolescence than males [ 11 ]. This finding presents a concern for males reporting lower than females’ results in our data and raises some questions about whether cultural or religious conservative values play a role.

Increased Internet hours are another risk factor in this study and were significantly associated with cyberbullying. Specifically, it was likely to be with heavy Internet users (> 12 h/day); a similar result was well documented in one equivalent study [ 3 ]. Notably, while some studies have reported that those living in city areas are more likely to be cyberbullying victims than their counterparts from suburban areas [ 3 ], our observations reported no significant influence of this factor on the prevalence of cyberbullying.

According to a population-based study on cyberbullying and teenage well-being in England, which included 110,000 pupils, traditional Bullying accounted for more significant variability in mental well-being than cyberbullying. It did, however, conclude that both types of Bullying carry a risk of affecting mental health [ 33 ]. We confirmed in this study that multiple occurrences of cyberbullying and the potential for being a victim are risk factors influencing mental health ( P < 0.001). Moreover, the frequency of harassment also shows a significant, influential effect. The victim's desire to be free from the perpetrator carrying out the cyberbullying is probably an alarming sign and a precursor factor for suicidal ideation; we reported that nearly half of the participants wished they could get rid of the perpetrators. Furthermore, more than 20% of participants considered harming themselves due to cyberbullying; this result is consistent with many studies that linked cyberbullying and self-harm and suicidal thoughts [ 34 , 35 , 36 ].

Adolescence is a particularly vulnerable age for the effects of cyberbullying on mental health. In one Saudi Arabian study, parents felt that cyberbullying is more detrimental than Bullying in the schoolyard and more harmful to their children's mental health. According to them, video games were the most popular social platform for cyberbullying [ 37 ]. Both cross-sectional and longitudinal research shows a significant link between cyberbullying and emotional symptoms, including anxiety and depression [ 38 , 39 ]. Therefore, we employed the MHI-5 to measure the mental impact of cyberbullying on adolescents in this study. Overall, the MHI-5 questionnaire showed relatively high sensitivity in detecting anxiety and depression disorders for general health and quality of life assessments. The questions listed happy times, peacefulness, and sensations of calmness, in addition to episodes of anxiousness, downheartedness, and feelings of depression, as given in Table 1 .

Cyberbullying has been well-documented to affect the academic achievement of the victim adolescents. Therefore, bullied adolescents are likelier to miss school, have higher absence rates, dislike school, and report receiving lower grades. According to one meta-analysis, peer victimization has a significant negative link with academic achievement, as measured by grades, student performance, or instructor ratings of academic achievement [ 40 ]. In our investigation, we reported that up to 20% of participants considered leaving their schools due to the adverse effects of cyberbullying (cOR 3.0) and wished they could stop using the Internet; 26% of participants felt that their school performance was affected due to being cyber victims (cOR 6.5). The results of the univariate analysis showed a high odd ratio related to school performance and a willingness to leave school. This conclusion indicates the likelihood of these impacts specifically with a significant p-value, as shown in Table 5 .

In this study, approximately 88% of the participants were cyber victims compared to only 11% of cyberbullying perpetrators who committed this act on their peers. Mental health affection is well-reported in many studies on cyber victims with higher depression rates than cyberbullying perpetrators [ 41 , 42 ]. However, other studies indicate that cyberbullying victims are not the only ones affected; harm is also extended to involve perpetrators. Cyberbullying perpetrators have high-stress levels, poor school performance, and an increased risk of depression and alcohol misuse. Furthermore, research shows that adolescents who were victims or perpetrators of cyberbullying in their adolescence continue to engage in similar behavior into early adulthood [ 43 , 44 ].

Limitations of the study

Although the current study found a high prevalence and positive connections among variables, it should be emphasized that it was conducted on a determinate sample of respondents, 11 to 18 years old. Therefore, the results could not be generalized for other samples, age groups, and communities from other cultures and contexts. In addition, it was limited to adolescent survey responses, did not include parents' and caretakers' viewpoints, and failed to include other risk factors such as divorce and financial status. We believe future studies should consider parents' perspectives and more analysis of perpetrators' characteristics. Moreover, self-reported tools are susceptible to social desirability bias, which can influence test item responses. As a result, future research should employ a variety of monitoring and evaluation metrics and larger potential populations and age ranges. Another limitation of this analysis is that we cannot make conclusive inferences regarding gender and exact prevalence because male adolescents had a lower response rate than female adolescents, suggesting that males might be more sensitive to disclosing these issues.

Even though experts in the social sciences typically research cyberbullying, it is crucial to investigate it from a clinical perspective because it significantly affects mental health. Adolescents' lives have grown increasingly centered on online communication, which provides several possibilities for psychological outcomes and aggressive actions such as cyberbullying. Stress, anxiety, depressive symptoms, suicidal ideation, and deterioration in school performance are all linked to cyberbullying. Therefore, we emphasize the need for parents and educators to be conscious of these dangers and be the first line of protection for the adolescent by recognizing, addressing, and solving this problem. Furthermore, we urge the responsibility of pediatricians, physicians, and psychiatric consultants to create a comfortable atmosphere for adolescents to disclose and report this problem early and raise awareness of the problem in their communities. Furthermore, practical strategies for dealing with such occurrences involving health, education, and law authorities, should be supported to tackle this problem, which can affect the adolescent mentally and academically. Lastly, to decide how to intervene most effectively, more research must be done on the many methods to assess how schools, communities, and healthcare providers tackle cyberbullying.

Availability of data and materials

The authors ensure that the data supporting the results of this study are available within the article. The raw data for the study will be obtainable from the corresponding author upon reasonable demand.

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Gohal, G., Alqassim, A., Eltyeb, E. et al. Prevalence and related risks of cyberbullying and its effects on adolescent. BMC Psychiatry 23 , 39 (2023). https://doi.org/10.1186/s12888-023-04542-0

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Cyberbullying and Adolescents

Vidhya lakshmi kumar.

MassGeneral Hospital for Children, Department of Pediatrics, Harvard Medical School

Mark A. Goldstein

Division of Adolescent and Young Adult Medicine, MassGeneral Hospital for Children, Department of Pediatrics, Harvard Medical School, 175 Cambridge Street, Room 508, Boston, MA 02114

Purpose of Review

Cyberbullying is an aggressive behavior involving a type of electronic communication intending to harm a victim that can have profound effects on adolescents. This review examines the epidemiology, issues from cyberbullying, presentation to care of its victims and proposed interventions to this behavior.

Recent Findings

There are a variety of physical and psychological effects on victims of cyberbullying that can include recurrent abdominal pain, headaches and difficulty with sleep. In addition, victims have higher rates of anxiety, depression, suicidal ideation and a lower level of well-being. Unfortunately, victims may remain silent, so screening for cyberbullying is encouraged in a variety of settings. Interventions can be designed at the level of the victim (and perpetrator), family, school and other support networks. Prevention of cyberbullying can be a focus for providers of healthcare.

Cyberbullying can have profound biopsychosocial effects on its victims. There are strategies currently in use and under development to identify and intervene on behalf of those affected by these behaviors.

Introduction

Michelle Carter, age 20, was convicted of involuntary manslaughter and sentenced in 2017 to prison for her role in the 2014 suicide of her then 18-year-old boyfriend, Conrad Roy Jr. The case against Carter, according to prosecutors, rested on text messages that she sent to Roy that encouraged him to end his life which he did by carbon monoxide poisoning. Phoebe Prince, a 15-year-old immigrant from Ireland, committed suicide in 2010 by hanging after bullying online and in school by her peers.

Bullying has been a well-documented phenomenon across the United States and internationally as well. Within Massachusetts, the stories of Michelle Carter, Conrad Roy Jr and Phoebe Prince serve as powerful reminders of the impact of cyberbullying, verbal bullying and intimidation.

Though there is not one standard definition, in the state of Massachusetts, bullying is defined by the Department of Education as “ the severe or repeated use by one or more students of a written, verbal, or electronic expression, or a physical act or gesture, or any combination thereof, directed at another student that has the effect of: (i) causing physical or emotional harm to the other student or damage to the other student’s property; (ii) placing the other student in reasonable fear of harm to himself or of damage to his property; (iii) creating a hostile environment at school for the other student; (iv) infringing on the rights of the other student at school; or (v) materially and substantially disrupting the education process or the orderly operation of a school” ( 1 ). It is this electronic expression, in particular, that has catapulted in recent years with the advancement in technology, the ease of communication via social media, as well as the dissemination and access to technology among grade school children and beyond.

Definition of Cyberbullying

Cyberbullying has evolved in many forms, which has created difficulty in establishing a unified definition that is widely accepted by clinicians. The definition of bullying itself does not easily translate to the cyber arena, but at its core, primarily refers to “an intentional act of aggression, carried out to harm another individual using electronic forms of contacts or devices” ( 2 ). Though initially limited to electronic mail, cyberbullying has slowly begun to incorporate a wider array of forms of electronic communication, ranging from personal blogs, text messaging, video content posted to streaming websites, such as You Tube, and more recently, social media formats including Instagram, SnapChat and TikTok.

Further exacerbating the potential for a severe impact of cyberbullying is access to smartphone technology, the audience involved in cyberbullying efforts, the opportunity for “anonymity by perpetrators,” the “permanency of bullying displays on the internet,” as well as the ability of bullying to occur regardless of distance from the victim and with “minimal constraints on time ( 3 ).” Cyberbullying can take on the following forms: flaming (online fights using electronic messages with angry and vulgar language), harassment, cyber stalking, denigration, impersonation, outing, trickery and exclusion ( 4 ). In the case of Michelle Carter, she used text messages to Conrad Roy to encourage him to end his life.

Epidemiology

Given the lack of consensus on a definition for cyberbullying, it has been difficult to easily quantify its true prevalence in the United States and the global arena. In a small sample of global studies, prevalence of middle and high school cyberbullying ranged from 1–30% for suspected perpetrators, and from 3–72% for suspected victims ( 3 ). The prevalence has been thought to vary due to a multitude of factors including varying definitions for what constitutes an act of cyberbullying, cross-cultural differences in victim reporting, as well as access to technology, which could limit the ability to participate in cyberbullying. Studies available across the U.S. and internationally identify vulnerable populations of adolescents for whom special attention should be made, including females, LGBTQ youth, younger adolescents and youth with disabilities ( 5 , 6 ).

Studies have also demonstrated gender differences in the prevalance of cyberbullying vicitimization, with female adolescents reporting a higher prevalence of victimization (9.4% for single encounter, 13.3% with two or more encounters) than their male counterparts (8.3% for single encounter, 7.8% with two more encounters) ( 7 ). Being bullied is further associated with increased suicidal ideation, delinquency and global psychological distress among both male and female adolescents, though more marked in females and more pronounced with repeated cyberbullying encounters or incidences ( 7 ).

Surveys of cyberbullying victims population further identify a large proportion of youth who identified as a part of the LGBTQ community, as well as youth with disabilities. In a Taiwanese study reviewing 500 homosexual or bisexual men between the ages of 20 and 25, there were reported significant associations between low family support, early coming out and traditional bullying victimization with cyberbullying ( 8 ).

In addition, adolescents and young adults with mental health needs or disabilities have often been targets of cyberbullying efforts. A Chinese study examining associations between cyberbullying and social impairment, attention-deficit-hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) in adolescents with high functioning autism spectrum disorder demonstrated that older adolescents and those with more severe ODD symptoms were more likely to be victims of cyberbullying. The victims of cyberbullying in this population were more likely to report symptoms associated with depression, anxiety and suicidality ( 9 ).

Issues from Cyberbullying

Cyberbullying has been associated with a variety of psychological and physical effects on its victims ( Table 1 ) ( 10 – 12 ). Victims of cyberbullying have higher rates of depression when compared to other forms of traditional bullying. In addition, victims may have more anxiety and suicidal ideation compared to peers who do not face victimization ( 3 , 8 ). A varying percentage of cyberbullying victims pursue suicide. Some studies suggest that children and adolescents who are both victims and perpetrators of cyberbullying 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. Victims of cyberbullying have also shown impacts in their family dynamics and relationships with friends, with many demonstrating increasing isolation and loneliness as well as decreased trust in their support groups ( 13 ). Some studies have indicated that reactions to cyberbullying may depend on the form of media (video vs. text conversation vs. phone calls) with some suggestion that pictures and video were the most negatively impactful on adolescents ( 14 ).

Signs and Symptoms of Cyberbullying ( 10 – 12 )

• Decreased self-esteem or feelings of helplessness

• Increased depression and/or anxiety

• Sudden loss of friends, isolation from peers or withdrawal at home

• Reported health problems (e.g., stomach aches, headaches) for which adolescent wants to stay at home or fake illnesses

• Increased truancy or school absences

• Decline in academic performance or loss of interest in school work

• Changes in eating habits or appetite

• Difficulty sleeping or frequent nightmares

• Sudden anger, rage or other emotional swings

• Self-harm behaviors, such as cutting or suicidal ideation

There have been relatively few studies examining the effect of cyberbullying on adolescents’ physical health. Grade school adolescent cyberbullying victims are often more likely to report somatic symptoms including difficulty sleeping, recurrent non-specific abdominal pain and frequent headaches ( 3 ). However, certain studies indicate that cyberbullies might be better off than victims with some studies finding no relation between the role of perpetrator and depressive symptoms ( 2 ). Other studies have focused on health impact as opposed to specific health problems by examining self-reported health-related quality of life (HRQOL). Survey data collected from college students have demonstrated long term impacts on physical health due to pre-college bullying experiences with lower HRQOL, likely mediated through depression ( 15 ). Furthermore, the study proposed that precollege exposure to cyberbullying might have latent effects that could be triggered by future bullying-related traumatization, including reduced confidence in social situations as well as isolation ( 15 ).

In addition, there have been links between cyberbullying and increased risky behaviors including substance abuse across a variety of substances. In a study examining a population of Greek national undergraduates, both male and female late adolescents who were victims of bullying during middle and high school were less likely to use condoms during college years when compared to non-victimized students ( 16 ). Furthermore, men who were bullies or victims of bullying were twice as likely to experience excessive drunkness and three times as likely to pay for sex. In addition, for males, cyberbullies and cybervictims were more likely to report smoking ( 16 ). Compared with traditional bullying, cyberbullying may have a stronger link to substance abuse, with one longitudinal study demonstrating that cyberbullying victimization predicted depression and substance abuse six months later ( 17 ). In addition, both victims and perpetrators of cyberbullying have been linked with increased use of marijuana with an implication that this may be indicative of a larger substance abuse problem among this population ( 18 ). This highlights the emergence of gender specific risks and behaviors associated with cyberbullying that require further evaluation.

The relationship between cyberbullying and an adolescent’s use of the internet has also been explored. A study of 845 adolescents with a median age of 15 years demonstrated that cyberbullying victims were at increased risk for having problematic internet use (PUI), which included a preoccupation with the internet, an inability to control their use of the internet, as well as continued use despite negative consequences ( 19 ). However, it remains unclear whether the increased time spent on the internet is deleterious or protective, as victims may be using the internet as an escape mechanism to mitigate anxiety and reduce negative feelings of isolation. Nevertheless, increased time on the internet by cyberbullying victims does place them at risk for harassment, invasion of privacy and exploitation ( 19 ).

Presentation to Care

Unfortunately, despite the deleterious effects of cyberbullying on a victim’s mental and physical health, many victims remain silent and hesitate to reach out for help. The onus, therefore, remains on others: educators, providers, family members and social supports to recognize common signs and symptoms of cyberbullying. Most often, individuals will notice that such victims begin to avoid school, a primary setting in which they face the effects of cyberbullying. In addition, a large majority of perpetrators may be members of the victim’s school community.

Accordingly, the victim may have increased school absenteeism due to somatic symptoms (frequent stomachaches, headaches, sleeping disruption or nightmares) or academic difficulties due to lack of school attendance or problems with concentration. Victims may demonstrate lower self-esteem, increased depressive symptoms and anxiety with detachment from friends or sudden withdrawal at home or school. On the contrary, these affected youth may show sudden bursts of anger or demonstrate increased self-destructive behaviors, such as cutting, or acts of truancy ( 10 – 12 ). Ultimately, since a victim may not come forward to seek help, it is important that support groups bring the individual to care.

The ability to prevent or intervene in cyberbullying most effectively hinges upon screening to detect and identify victims, as well as perpetrators. There is difficulty in determining the best method to screen for bullying in the medical setting, whether this is in the emergency department or at a primary care visit. Though direct questioning may be effective, studies have posited that it may be more effective to use a questionnaire to elicit accurate responses from patients. The “Guidelines for Adolescent Preventive Services” form includes screening across a variety of health behaviors and experiences, including bullying ( 20 ). Couching inquiries about bullying in the setting of assessing adolescent behavior may serve to normalize questioning about bullying and in turn allow adolescents to open up to providers about their experiences. These screens can focus on questions such as ( 21 ):

- How often do you get bullied or bully others?

- How long have you been bullied or bullied others?

- Where are you bullied or bully others?

- How are you bullied or how do you bully others?

Screening for cyberbullying should be an important element of adolescent care. Furthermore, screening should not be limited to non-urgent scenarios. Studies have shown that adolescents report exposure to cyberbullying and violence in a variety of urgent medical situations as well, including emergency rooms, inpatient hospital stays and school-based clinics. This underscores the importance screening for cyberbullying during any patient interaction.

Though victims may present to their pediatrician’s office for assistance, often these youth present to the emergency department. These encounters may be due to mental health needs, in the setting of suicidal ideation or attempts at self-harm, previously identified as significant symptomatology in cyberbullying victims. Studies demonstrate that over three quarters of victims of cyberbullying will present to the emergency department with a mental health need as their chief complaint and that more than three quarters of adolescents presenting with suicidal ideation as their chief complaint have endorsed previous incidences of cyberbullying ( 22 ). Cyberbullying was also found to be the strongest predictor of suicidal ideation, while controlling for other important factors, such as age, gender and psychiatric diagnosis ( 22 ). Therefore, it remains important that providers caring for adolescents and young adults presenting with suicidal ideation pointedly ask about bullying and cyberbullying in the patient’s life. In a Canadian population of adolescents, cyberbullying victims were more likely to attempt, or complete suicide compared to those who had not been bullied ( 18 ). It is further postulated that cyberbullying victims may seek help less frequently or underreport incidences compared to those who have been traditionally bullied and that increases their risk of suicidal ideation ( 22 ).

Types of Interventions

Interventions designed to target and mitigate cyberbullying remain as important as attempts to intervene and provide support for victims. These efforts should not solely focus on victims; they should also work with perpetrators. Programs need to reinforce positive values in school age children to reduce the number of cyberbullying perpetrators.

Though these interventions may occur in a multitude of settings, many studies have primarily focused on school-based interventions. This seems appropriate given that a large proportion of cyberbullying incidents take place amongst school classmates. Social support has been shown to be an important buffer when adolescents experience cyberbullying ( 23 ). As previously suggested by the efficacy of school-based interventions, perceived social support from family and teachers has been shown to potentially ameliorate the association between cyberbullying and several outcomes at the psychosocial level. A study of 131 pupils with developmental disorders who had received social support from parents and teachers demonstrated reduced depressive symptoms one year after a cyberbullying experience ( 24 ).

A viable intervention program and cyberbullying prevention mechanism may rely on specific strategies such as improved access to resources, as well as efforts to increase the potential protective effects of social support figures in an adolescent’s life, including family members, friends and teachers ( 2 ). This study in particular suggested that there may be differences between male and female victims as to which form of social support is more efficacious with an implication that girls may benefit more from social supports than their male counterparts ( 2 ). However, the efficacy of social support in preventing cyberbullying or supporting its victims is often contingent upon adolescents seeking help or divulging their victim status.

Some studies suggest that effective interventions focus on enhancing an adolescent’s empathy, promoting positive social relationships with family and decreasing screen time ( 13 ). In particular, given the lack of nonverbal cues inherent in the nature of cyberbullying, it is postulated that adolescents who serve as cyberbullying perpetrators may demonstrate little empathy for their cyber victims. Furthermore, given that poor self-esteem has been shown to be a significant factor among victims and perpetrators alike, both educators and health care providers should focus on an adolescent’s emotional status, particularly with those who seem to demonstrate not only a decline in their self-esteem but also who are showing more troublesome behaviors such as truancy and substance use ( 18 ).

Another potential focus of intervention may hinge on coping strategies for adolescents ( 25 ). Coping strategies are divided into two types: emotion-focused and problem-focused. There are two emotion-based strategies that victims of cyberbullying can utilize: self-control and escape-avoidance. The self-control strategy employs inhibitions of emotional expressions and spontaneous behavior ( 26 ). The desire to regulate emotions brought on by a stressful situation is usually carried out when there is a belief that nothing can be done to change the unfavorable conditions ( 27 ). This may lead to increased avoidance and depression-based coping in a cyberbullying victim’s day-to-day activities with increased depressive symptoms and health complaints.

Problem-focused strategies may be particularly helpful to cyberbullying victims, as they often cannot face (or identify) their aggressor or stand up to the bully ( 28 ). As a result, coping strategies that attempt to either manage or solve the problem may be more beneficial to victims of cyberbullying, motivating them to implement changes, both internally and environmentally. Although there is no one right way to cope, adolescents employing “more approach and problem solving” as opposed to avoidance strategies, and assessing a stressor to be a challenge were shown to have more adaptive outcomes ( 29 ). Such strategies teach the importance of standing up for oneself as well as using methods to not only deal with cyberbullying but manage the daily stress ( 30 ).

A validated tool, such as the Utrecht Coping List for Adolescents, has been a long-standing tool used to help adolescents work through their current emotional coping-based mechanisms and transition to thinking in a more pro-active problem-based fashion. This underscores the importance of both social skills and assertiveness training which inspire victims to adopt more active problem-based strategies, such as telling someone about their bullying or making new friends ( 31 ). These coping strategies, in conjunction with school, peer group and teacher-based efforts to prevent bullying, may bolster the prevention and resiliency efforts currently underway.

Prevention of cyberbullying should be a focus for healthcare providers. Anticipatory guidance remains a cornerstone of the well child and well adolescent visit, and should include strategies conveyed to both patients and their parents on how to identify signs of cyberbullying, In addition, discussion of stigma and myths about cyberbullying should occur. This could include discussions about the use of technology in the home, as well as the best and safest social media practices for the adolescent. Furthermore, taking a history about the signs and symptoms of cyberbullying from caregivers independently of the adolescent may be helpful in determining the patient’s source of distress and to appropriately plan interventions.

A variety of screening tools have been developed ( Table 2 ) that represent the potential to identify victimization as well as serve as an opportunity to respond and intervene ( 32 ). However, these tools address the larger umbrella phenomenon of bullying and are not specific to cyberbullying. Therefore, instruments and tools that can be used adequately to identify victims and aggressors of cyberbullying still remain a large area of need.

Current Bullying Assessment Tools ( 32 )

Current Bullying Assessment Tools
The Bully Survey
Gatehouse Bullying Scale
Olweus Bullying Questionnaire
The Peer Relations Assessment Questionnaires
Peer Relationship Survey
“My Life in School” Checklist
The Personal Experiences Checklist
California Bullying Victimization Scale

Many states have responded to the surge of cyberbullying with legislation focusing on prevention, intervention and consequences. In Massachusetts, as a response to the deaths of Phoebe Prince and others, legislation was enacted so that all school staff (including educators, nurses, custodians, athletic coaches, advisors to extracurricular activities, administrators, cafeteria workers, bus drivers, and paraprofessionals) must report bullying to the school administration ( 1 ). These individuals are also required to receive training on bullying prevention and intervention ( 1 ). That stated, effective interventions to prevent cyberbullying-related suicide or suicidal ideation have not yet been identified or vetted through research.

Currently, there are a variety of school-based interventions focused on adolescent suicide awareness, typically presented between the ages of 12 and 18. Preventative interventions focus on suicide awareness campaigns or screening as primary preventative measures, or secondary approaches to provide support to those affected by suspected suicides. Some schools have implemented psychologic interventions in those who have already demonstrated attempts at self-harm, including cognitive behavioral therapy (CBT), dialectic behavioral therapy (DBT) and home-based family interventions ( 33 ). However, these services are not routinely available in school systems and their efficacy in identifying cyberbullying victims and pro-actively preventing attempts at suicide are not well understood. Ultimately, though there are school-based interventions in place for suicide awareness, only a few are evidenced-based and there is little to demonstrate the true efficacy of these interventions for preventing suicide and suicide attempts in the adolescent population. Therefore, the adolescent population serves as an untapped area of research into evidence-based interventions and policies, potentially to be extrapolated from other high-risk populations and proven efficacious efforts.

Much of the current literature focuses on an older adolescent population (i.e. high school and undergraduate). It may, therefore, behoove the community to understand the effects of cyberbullying in younger adolescents (less than 12 years of age) and how this may inform prevention efforts. This is a particularly important focus given the ubiquity of technology and internet access in a young child’s life. The large majority of children regularly use the internet ( 17 ). Some studies have demonstrated similarly negative effects on psychological well-being of younger adolescents secondary to cyberbullying victimization, poor self-esteem and decreased peer socialization ( 34 ). The ability to identify these negative effects at a younger age may allow us to build more effective programs and coping strategies at an earlier age to ultimately foster a population of adolescents with increased resiliency and skills to face the stressors of life.

Ultimately, the prevention of cyberbullying rests not only on the shoulders of victims and their families, but on educators, providers and researchers. More focused studies and evaluations of interventions may not only reduce the prevalence of cyberbullying but also lower the mental health sequelae seen in the short and long term. The serious consequences of cyberbullying, particularly surrounding mental health issues and suicidal ideation, underscore the importance of effective and evidence-based bullying prevention programs and support groups in school-based settings. In addition, the multitude of factors associated with victimization in cyber sexuality-related bullying as well should be factored into developing prevention and intervention strategies.

Acknowledgments

Funding information : This paper was funded in part by NIH grant 5 R01 MH103402.

The authors wish to thank Dr. Karen Sadler for reviewing their manuscript.

Compliance with Ethics Guidelines

Conflict of Interest

The authors declare no conflict of interest.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of a an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

Contributor Information

Vidhya Lakshmi Kumar, MassGeneral Hospital for Children, Department of Pediatrics, Harvard Medical School.

Mark A. Goldstein, Division of Adolescent and Young Adult Medicine, MassGeneral Hospital for Children, Department of Pediatrics, Harvard Medical School, 175 Cambridge Street, Room 508, Boston, MA 02114.

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Early Recognition and Intervention of Bullying and Cyberbullying: Strategies, Challenges, and Solutions

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Bullying and cyberbullying remain pervasive issues affecting children and adolescents worldwide, with significant psychological, social, and academic consequences. Despite increased awareness, many cases of bullying go unrecognized or are addressed too late, exacerbating the negative impacts on both bullies and victims. Early recognition and intervention are crucial in mitigating these effects and promoting a safer, healthier environment for youth. This Research Topic delves into the multifaceted aspects of bullying and cyberbullying, aiming to uncover effective strategies, identify challenges, and propose comprehensive solutions to enhance early detection and improve prevention and intervention efforts. The primary goal of this Research Topic is to explore current research on the early recognition, prevention, and intervention of bullying and cyberbullying. By identifying barriers and examining innovative methods for detecting, preventing, and intervening, we aim to provide a robust framework for educators, healthcare professionals, policymakers, and researchers to effectively address bullying and cyberbullying. This Research Topic invites contributions that explore various aspects of bullying and cyberbullying, with a focus on early recognition, prevention, and intervention. The collection welcomes papers targeting the following subthemes: - Examination of early recognition and intervention strategies for bullying and cyberbullying in diverse settings. - Investigation of novel methods for early disclosure of bullying and cyberbullying, including emerging technologies and digital platforms. - Analysis of the challenges faced in the recognition of bullying behaviors, including bias-based bullying (race, gender, religion, etc.), across different cultural and social contexts. - Exploration of the psychological, social, and academic consequences of late recognition of bullying and cyberbullying. - Examination of the role of educators, parents, peers, and the broader school environment in the early detection and intervention of bullying and cyberbullying. - Evaluation of the effectiveness of anonymous reporting systems and digital platforms in early disclosure of bullying and cyberbullying incidents. - Research into the utilization of artificial intelligence and machine learning for identifying, predicting, and addressing cyberbullying. This collection seeks to foster collaboration and inspire new research directions, ultimately contributing to the reduction of bullying and its adverse effects on children and adolescents.

Keywords : Bullying, Cyberbullying, Early recognition, Artificial intelligence, Victimization, Intervention strategies

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Published: 13 September 2024

Relationship between physical exercise, bullying, and being bullied among junior high school students: the multiple mediating effects of emotional management and interpersonal relationship distress

Qiang Zhang 1 &
Wenjing Deng 2

BMC Public Health volume 24 , Article number: 2503 ( 2024 ) Cite this article

Metrics details

This paper investigates the relationships between physical activity (PA), school bullying, emotion regulation self-efficacy (ERS), and interpersonal relationship distress (IRD) among junior high school students. It also examines the underlying mechanisms of school bullying to provide insights into reducing adolescent bullying and to lay the groundwork for preventing and controlling aggressive behaviors.

A survey was conducted on 484 students (240 males, 12.18 ± 0.8 years) from 4 secondary schools using the Physical Activity Rating Scale (PARS), Emotional Management Self-Efficacy Scale (EMSS), Interpersonal Relationship Distress Scale (IRDS), and Campus Bullying Scale (CBS) to examine the effects among the variables. A stratified random sampling method was used to select the sample, and data were collected with a structured questionnaire. The data were analyzed using SPSS 24.0 and AMOS 24.0 statistical software. The analysis included Pearson correlation analysis, structural equation modeling, and bias-corrected percentile Bootstrap methods.

(1) PA negatively predicts IRD, which in turn has an indirect effect on bullying (PA → IRD → Bullying), ES = -0.063. Additionally, EM and IRD act as mediators between PA and school bullying (PA → EM → IRD → Bullying), ES = 0.025. (2) PA negatively predicts IRD, which has an indirect effect on being bullied (PA → IRD → Being bullied), ES = -0.044. EM and IRD serve as chain mediators between PA and being bullied (PA → EM → IRD → Being bullied), ES = -0.071.

PA can positively predict bullying, but it can be mitigated through EM to reduce IRD, thereby decreasing the occurrence of campus bullying and being bullied.

Peer Review reports

School bullying is considered an aggressive, intentional, and repetitive behavior, occurring without clear motivation, inflicted by one or more students on others. It not only causes physical harm to the victims but also negatively affects their mental health [ 1 , 2 ]. School bullying is prevalent in some East Asian countries [ 3 ], having profound and lasting effects on the health and well-being of the victims [ 4 , 5 ]. In children and adolescents, school bullying is closely associated with depression, anxiety, and insomnia [ 6 ]. Severe bullying can lead to self-harm [ 7 ]. Bullying peaks between the ages of 11 and 13, during the transition from primary to secondary school [ 8 ]. Given the potential harm of bullying to mental health, it is necessary to explore the mechanisms of bullying and victimization to provide a theoretical basis for preventing bullying among middle school students.

Physical activity (PA) has demonstrated significant mental health benefits, including strong anti-depressive and anti-anxiety effects, improved self-efficacy, and enhanced mood regulation [ 7 , 9 ]. PA has also proven to be an effective intervention in anti-bullying programs for special populations with mental disorders, overweight, or obesity [ 10 , 11 ]. As a vital component of public health strategies against bullying, PA positively influences the psychological well-being of both perpetrators and victims. Studies abroad have confirmed a close relationship between school bullying, victimization, and the frequency and type of PA. Students who engage in PA at least four times a week show higher aggression scores than those with lower exercise frequencies [ 9 ]. Studies suggest that regularly exercising adolescents are more likely to become bullies and exhibit higher aggression compared to their non-exercising peers [ 12 ]. Nikolaou’s study suggests that individuals who frequently participate in competitive sports are more likely to become bullies but are less likely to be victimized [ 13 ]. It recommends increasing opportunities for adolescents to exercise while enhancing supervision of exercise content and venues. Other studies confirm that physical education classes protect against bullying, with regularly exercising girls showing lower levels of victimization [ 14 ]. Waasdor used binary logistic regression to examine the relationship between health-related behaviors and bullying, finding that PA significantly reduces the likelihood of students becoming victims [ 15 ]. Pacífico et al. systematically reviewed the relationship between bullying victimization, aggressive behavior, and participation in physical activities and sedentary behaviors, finding that victims are associated with reduced PA and increased sedentary time [ 11 ]. Based on these findings, we hypothesize that H1a: PA can increase the likelihood of bullying behavior. H1b: PA can decrease the likelihood of being bullied.

Recent studies have found that emotion regulation self-efficacy (ERS) and interpersonal relationship distress (IRD) are crucial in preventing school bullying. Muris defines ERS as an individual’s perceived ability to manage negative emotions, including the belief in one’s capacity to avoid or recover from such states [ 16 ]. Effective ERS is essential for mental and physical health and is considered a protective factor against negative emotions. For instance, self-talk can help regain a positive attitude or calm oneself during fear and anxiety. Bandura, in his self-efficacy and social cognitive theories [ 17 , 18 ], emphasizes that self-efficacy and self-regulation strategies are crucial for behavior change. Regular PA promotes both physical and psychological health, including a healthy lifestyle, body awareness, and confidence in physical skills. It also enhances safety, responsibility, patience, courage, and psychological balance [ 19 ]. Valois et al. surveyed over 3,800 students and found that PA is related to ERS [ 20 ]. Continuous PA can enhance self-efficacy, which, if not managed, can lead to decreased academic performance, social adaptation disorders, emotional depression, and an increased likelihood of deviant behavior. Moreover, regular physical activity offers multiple psychological benefits, such as enhanced self-control and self-esteem, both of which are closely linked to a decrease in bullying behaviors [ 21 ]. Participation in sports can mitigate the effects of bullying and is an effective strategy for promoting positive peer interactions and emotional regulation among adolescents.

IRD refers to the inability to establish and maintain meaningful relationships, lack of stable personal identity and self-awareness, and the use of avoidance strategies to manage strong emotions [ 22 ]. Méndez et al. found that poor relationships among students can result in bullying [ 9 ]. School bullying, a negative social interaction among adolescents, can be predicted by negative relationships with parents, teachers, and peers [ 23 ]. Gross’s emotion regulation self-efficacy theory emphasizes the impact of emotion management on social interactions and relationships [ 24 ]. PA can serve as an ERS strategy, improving emotion management through stress relief and emotional state enhancement, thereby improving interpersonal relationships.

In recent years, research has increasingly focused on how PA can improve adolescents’ emotion management and interpersonal relationships, thereby reducing bullying and victimization. González’s study confirmed that adolescents’ participation in group sports brings joy, improves poor interpersonal relationships, and promotes harmonious peer relationships [ 25 ]. Further research found that non-competitive physical activities convey values, promote prosocial attitudes, prevent bullying and victimization, and reduce the risk of aggressive incidents [ 26 ].

Based on these findings, we hypothesize H2a: PA can improve individuals’ ERS abilities, thereby reducing the occurrence of school bullying behaviors. H2b: PA can indirectly decrease the likelihood of individuals becoming victims of bullying by enhancing their ERS abilities. H3a: PA can alleviate IRD, thereby reducing the frequency of bullying behaviors. H3b: PA can further lower the risk of students being bullied by mitigating IRD.

According to Sullivan’s interpersonal theory [ 27 ], individuals seek interpersonal interactions during their adolescence. If they cannot effectively control their emotions, it may lead to psychological stress and social interaction difficulties [ 28 ]. Jun et al., in a cross-sectional survey study of 207 medical students, found that appropriate expression of anger can enhance their ERS ability, thereby improving interpersonal interaction skills [ 29 ]. ERS ability is a cognitive variable that influences behavioral and emotional processes [ 30 ]. Individuals with high levels of ERS ability believe they can achieve desired outcomes through their efforts, thus choosing effective coping strategies. Moreover, they exhibit more patience in the process of achieving their goals [ 30 , 31 ]. Therefore, the ability to manage emotions may enhance individuals’ confidence, stimulate motivation for communication with others, and enable them to handle interpersonal relationships more effectively, avoiding disharmony in relationships.

Based on the above, the hypotheses are proposed: H4a: PA can enhance ERS, thereby alleviating IRD and preventing school bullying. H4b: PA can enhance ERS, thereby reducing IRD and decreasing the risk of being bullied.

This study employed PA as the independent variable, school bullying and being bullied as the dependent variables, and ERS and IRD as mediating variables to develop a chain mediation model (Fig. 1 ). The model aims to elucidate how PA reduces IRD through the enhancement of ERS, thereby preventing school bullying. This theoretical framework clarifies the research objectives and provides direction for subsequent analysis.

Multiple mediation model of school bullying

Materials and methods

Participants.

From March to May 2023, we utilized a multi-stage cluster random sampling method to select two key junior high schools and two regular junior high schools in Shandong Province. Within each school, 1–2 classes from grades 6 through 9 were randomly chosen to participate in the survey, which was administered via the Wenjuanxing platform. Ultimately, 15 classes took part, and we issued 529 questionnaires, each taking an average of 8 min to complete. After excluding responses with repetitive patterns or completion times under 3 min, 45 invalid responses were discarded, resulting in 484 valid responses and a response rate of 91.5%. The sample included 240 male and 244 female students; 171 were only children, while 313 had siblings. The breakdown by grade was as follows: 87 students in grade 6, 137 in grade 7, 134 in grade 8, and 126 in grade 9. The average age of the participants was 12.18 years with a standard deviation of 0.8 years. Detailed demographic information is presented in Table 1 .

This study utilized a cross-sectional design and structured questionnaires to collect the necessary data. The questionnaires used in this study were revised in China, widely utilized, and demonstrated high reliability and validity. To further ensure their reliability and validity, we conducted additional reliability analysis and exploratory factor analysis. The study followed these procedures: Approval was first obtained from the Human Research Ethics Committee of Capital University of Physical Education and Sports. Afterward, researchers received consent from the principals of the selected schools and coordinated with grade-level directors to select the participating classes. Class teachers then distributed informed consent forms to students and their parents, explaining that participation was voluntary and confidentiality was assured. They also confirmed the number of participants. Finally, during physical education classes, teachers organized students to complete the questionnaires anonymously using the Wenjuanxing platform in the school information room. Researchers were present on-site to address any participant questions.

Instruments

Physical activity rating scale (pars).

The PARS revised by Liang (1994) [ 32 ], was employed to assess the PA levels of middle school students and investigate their exercise habits. This scale evaluates the intensity (e.g., “light exercise”), duration (e.g., “less than 10 minutes”), and frequency (e.g., “less than once a month”) of PA, with each dimension rated on a 5-point scale from 1 (low) to 5 (high). The amount of PA is calculated using the formula: PA = Intensity × Duration × Frequency. Both intensity and frequency are rated on a scale from 1 to 5, while duration is rated from 0 to 4. The possible scores range from 0 to 100 points. The activity levels are categorized as follows: 0–19 points indicate low activity, 20–42 points indicate moderate activity, and 43–100 points indicate high activity. In this study, Cronbach’s alpha for the scale was 0.807.

Emotion regulation self-efficacy scale (ERSS)

The ERSS, developed by Li [ 33 ], was used. This scale contains 17 items, covering four dimensions: Expressing Positive Emotions (EPM) with 4 items (e.g., “showing joy when something good happens”), Regulating Anger (AM) with 3 items, Regulating Depression (RD) with 4 items (e.g., “not feeling dejected when strongly criticized”), and Regulating Fear (RF) with 6 items (e.g., “not feeling scared in the dark”). In this study, Cronbach’s alpha for the total scale was 0.955, with the four dimensions being 0.911, 0.822, 0.907, and 0.889 respectively. The overall confirmatory factor analysis fit indices for the scale were: χ2/ df = 5.03, CFI = 0.96, TLI = 0.92, RMSEA = 0.06, and SRMR = 0.05.

Interpersonal relationship distress scale (IRDS)

The IRDS developed by Deng & Zheng [ 34 ] was used. This questionnaire consists of 28 questions, with a binary response format (“Yes” or “No”). Higher scores indicate more severe IRD. The scale includes four dimensions, each with 7 items: Conversation Trouble (CT) (e.g., “finding it difficult to talk about personal troubles”), Interaction Trouble (IT) (e.g., “feeling uncomfortable when meeting strangers”), Trouble Treating Others (TTO) (e.g., “feeling excessive envy and jealousy towards others”), and Exposure to Heterosexual Distress (EHD) (e.g., “feeling unnatural when interacting with the opposite sex”). In this study, the Cronbach’s alpha for the questionnaire was 0.889. The confirmatory factor analysis fit indices were: χ2 /df = 2.603, CFI = 0.89, TLI = 0.87, RMSEA = 0.05, and SRMR = 0.04.

Campus bullying scale (CBS)

The bullying subscale of the Olweus Bullying Questionnaire [ 35 ], revised by Zhang & Wu [ 36 ], consists of 12 items. It uses a 5-point Likert scale to measure the frequency of bullying behaviors. Six items assess bullying (BULLY) (e.g., “I spread rumors about some classmates to make others dislike them”), and six items assess victimization (VIC) (e.g., “others call me unpleasant nicknames, insult me, or mock me”). The frequency of occurrence is rated from 0 to 4, ranging from “never happened” to “several times a week”. In this study, the Cronbach’s alpha for the questionnaire was 0.843. Confirmatory factor analysis indicated good structural validity, with fit indices as follows: χ2/ df = 2.94, CFI = 0.97, TLI = 0.98, RMSEA = 0.05, and SRMR = 0.03.

Data analysis

The social statistical analysis software SPSS 24.0 was used for internal consistency testing and Pearson correlation analysis of PA, ERS, IRD, and school bullying. The AMOS 24.0 software was used for confirmatory factor analysis, mediation analysis, and Bootstrap analysis for difference testing. A significance level of α = 0.05 was set for statistical significance.

Control and testing for common method bias

All data in this study were self-reported by adolescents, which may be affected by common method bias. Therefore, in the study design and data collection process, measures were taken such as making the questionnaire anonymous, separating different questionnaires, reverse scoring some items, and emphasizing the confidentiality of the data for pre-program control. In addition, confirmatory factor analysis was used to test for common method bias in all self-reported items. The results showed a poor model fit, with χ2/ df = 29.44, CFI = 0.47, GFI = 0.55, AGFI = 0.39, NFI = 0.46, and RMSEA = 0.24. This indicates that there is no serious common method bias issue in this study.

Means, standard deviations, and correlation analysis of variables

Descriptive statistics and correlation analysis (Table 2 ) reveal significant relationships: gender is significantly related to PA and interpersonal relationships ( r =-0.272, P < 0.01; r = 0.107, P < 0.05). ERS is significantly related to bullying and IRD ( r =-0.134, P <0.01) ( r =-0.316, P <0.01), and ERS is positively correlated with PA ( r = 0.161, P <0.01). IRD is negatively correlated with PA ( r =-0.132, P <0.01), and positively correlated with bullying and being bullied ( r = 0.306, P <0.01) ( r = 0.207, P <0.01). Given that the relationship between gender and bullying was not significant, subsequent analyses did not differentiate between male and female students.

Chain mediating mechanism analysis between PA and school bullying

To effectively control measurement errors, this study used structural equation modeling to test for multiple mediating effects. First, based on the hypothesized model, PA was used as the predictor variable, bullying as the outcome variable, and ERS and IRD as mediating variables for path analysis. Figure 2 presents the data fit results: χ2/ df = 3.001, CFI = 0.96, GFI = 0.953, RMSEA = 0.064, and SRMR = 0.041. All fit indices fall within acceptable ranges, confirming the validity of the initially proposed model.

Chain mediations between PA and bullying. Note: BULLY = school bullying. Dash lines indicate an insignificant relationship

The path coefficients and significance levels are illustrated in the diagram. PA significantly affects ERS and IRD, with standardized path coefficients of 0.23 and − 0.19, respectively. ERS negatively impacts IRD, with a standardized path coefficient of -0.33. IRD positively affects bullying, with a standardized path coefficient of 0.33. Additionally, PA positively affects bullying, with a standardized path coefficient of 0.16. However, ERS does not significantly impact bullying.

This study used the Bootstrap procedure to test the significance of the mediating effects, drawing 5000 samples with a 95% confidence interval. A mediating effect is considered significant if the 95% confidence interval for the path coefficients does not include 0. According to the results in Table 3 , the path from PA to bullying is significant ( P = 0.025), supporting hypothesis H1a. In contrast, the path from ERS to bullying is not significant ( P = 0.103), which does not support hypothesis H2a.

Following Wen et al. [ 37 ], the interpretation of mediating effects depends on the signs of ab and c’. If ab and c’ have the same sign, the mediating effect is considered valid. This study found that both IRD and ERS act as suppressor variables in the relationship between PA and school bullying among adolescents: (1) PA reduces IRD, which indirectly decreases bullying (PA → IRD → Bullying), with a suppressor effect value of -0.063 (95% CI: -0.179, -0.028), supporting hypothesis H3a. (2) ERS and IRD also act as suppressors in the relationship between PA and school bullying (PA → ERS → IRD → Bullying), with a suppressor effect value of 0.025 (95% CI: -0.375, -0.037), supporting hypothesis H4a.

Path analysis of the chain mediation mechanism of PA and school bullying

In this analysis, PA is treated as the predictor variable, and being bullied is the outcome variable. ERS and IRD serve as mediating variables. The model’s fit indices are within acceptable ranges: χ2 /df = 2.704, CFI = 0.965, GFI = 0.957, RMSEA = 0.059, and SRMR = 0.039, as illustrated in Fig. 3 . These results support the validity of the initially proposed model.

Chain mediations between PA and being bullied. Note: VIC = being bullied. Dash lines indicate an insignificant relationship

The figure illustrates the path coefficients and significance levels. PA significantly impacts ERS and IRD, with standardized path coefficients of 0.22 and − 0.19, respectively. ERS significantly negatively impacts IRD, with a standardized path coefficient of -0.33. IRD significantly positively affects being bullied, with a standardized path coefficient of 0.23. However, the effects of ERS and PA on being bullied are not significant.

Table 4 reveals that the paths from PA and ERS to being bullied are not significant ( P = 0.054, 0.445), thus hypotheses H1b and H2b are not supported. The lack of a significant direct effect from PA to being bullied indicates that IRD and ERS fully mediate this relationship. This complete mediation consists of two pathways: (1) PA negatively affects IRD, which then indirectly impacts being bullied (PA → IRD → Being bullied), with a mediation effect of -0.044 (95% CI: -0.179, -0.028), supporting hypothesis H3b; (2) ERS and IRD mediate the relationship between PA and being bullied in a chain mediation model (PA → ERS → IRD → Being bullied), with a mediation effect of -0.071 (95% CI: -0.375, -0.037), supporting hypothesis H4b.

This study examines the predictive effects of PA on bullying and victimization, as well as the role of emotional management and interpersonal relationship issues in mediating this relationship. It reveals the mechanism by which PA predicts bullying and victimization through its influence on emotional management and interpersonal relationships.

Direct effects analysis of PA on bullying and being bullied

The study found that PA can positively predict school bullying, but its predictive effect on victimization is not significant. Empirical studies on the relationship between PA and bullying/victimization in China are relatively scarce. The results of this study are consistent with most related studies both domestically and internationally, indicating that higher levels of PA may be associated with the occurrence of school bullying. Upon entering middle school, adolescents face the challenge of re-establishing peer relationships. During this period, active physical activities may lead to more frequent participation in various social activities on campus, thereby increasing the risk of exposure to potential conflicts. Without adequate supervision, these conflicts may escalate into bullying behaviors. However, some studies do not distinguish between bullying and victimization, suggesting that the higher the level of physical participation, the less frequent the occurrence of school bullying. These studies suggest that physical participation can enhance cognitive functions, reduce sensitivity to hostile information, and decrease attention to dangerous behaviors. Haney Aguirre-Loaiza et al. first confirmed through experimental intervention the positive effects of PA on inhibitory control and emotional situation recognition [ 38 ]. Additionally, physical participation can improve the quality of peer relationships, further reducing the occurrence of school bullying. PA may also enhance the cognitive flexibility and emotional regulation abilities of victims, helping them better cope with the negative impacts of bullying experiences. This study found that the direct predictive effect of PA on bullying may be related to the personality changes of adolescents during puberty and the high level of activity brought by PA. In this context, although the positive effects of PA may not be as significant as expected, it still helps in understanding the role of PA in school bullying.

For victimization, this study did not find a significant direct effect between PA and being bullied, which is consistent with the findings of Ortega [ 39 ]. Some studies suggest that regular participation in PA can reduce the likelihood of becoming a victim of bullying. PA is not only an important way to convey values but also enhances communication skills and promotes prosocial attitudes. Therefore, students’ physical activities are considered a health-promoting practice, and physically active students are generally believed to be more capable of protecting themselves. Hermoso and his team explored the relationship between PA, sedentary behavior, and the experience of bullying among children and adolescents [ 40 ]. They found that not meeting PA guidelines and excessive sedentary behavior are risk factors for being bullied, while at least 60 min of moderate-to-vigorous PA per day leads to better health and quality of life. Previous cross-sectional studies have also shown that not meeting these PA guidelines significantly increases the risk of bullying among children and adolescents. Therefore, PA is seen as an effective tool for preventing and reducing the occurrence of bullying. Hermoso et al. believe that students lacking PA are more likely to be bullied due to factors such as insufficient motor skills, poor physical fitness, and lack of confidence in participating in physical activities [ 40 ]. Nevertheless, this study did not find a significant direct effect between PA and being bullied. The occurrence of school bullying is influenced by various factors, including family background, cultural adaptation, bullying experience, and parental educational background. For example, Jang et al. pointed out that long-term bullying victimization is a potential risk factor for the mental health of children from multicultural families, particularly among adolescents whose mothers are from Southeast Asia [ 58 ]. The study by Kim and Fong explored the relationship between the bullying victimization experiences of children from multicultural families and their cultural adaptation and life satisfaction [ 41 ]. They found that entering bullying victimization is associated with reduced emotional cultural adaptation, and both entering and exiting bullying victimization are related to life satisfaction. Park used an asymmetric fixed effects model to evaluate the effects of entering and exiting bullying victimization [ 42 ]. He found that the mother’s college education level enhances the psychological health benefits of exiting bullying victimization but does not mitigate the harmful effects of entering it. The protective effect of the mother’s college education level is particularly significant for girls.

In summary, the direct predictive effects of PA on school bullying and victimization have not yet reached a consensus. Due to the complexity of the direct predictive effects of PA on bullying and victimization, more research is needed to further confirm this relationship and consider other potential influencing factors.

Indirect effects Analysis of ERS and IRD

PA has a significant positive predictive effect on emotional management, consistent with most related studies [ 43 ]. Regular and sustained PA plays a crucial role in regulating emotions. When individuals are in an uncomfortable state, excellent emotional regulation abilities often lead to a reevaluation of existing cognitive elements related to interpersonal perception, memory, and thinking. This approach helps quickly find flexible and effective ways to avoid conflicts and contradictions in interpersonal interactions, aiding individuals in better integrating into groups [ 44 ].

According to the general aggression model, negative emotions such as anxiety, depression, and anger can bring negative experiences to adolescents, who may bully others to vent these unpleasant feelings [ 45 ]. However, this study did not confirm the hypothesis that emotional management negatively predicts bullying and victimization. Additionally, the effects of emotional regulation strategies vary in different contexts, and individuals can flexibly deploy these strategies according to changing situational demands [ 46 ]. Emotional regulation encompasses various strategies, such as cognitive reappraisal and emotional suppression. Individuals may use different strategies to cope with emotions, but this study did not distinguish between them, potentially obscuring the predictive role of emotional regulation self-efficacy on bullying and victimization. Additionally, differences in emotional regulation abilities among individuals and the ways male and female students handle positive and negative emotions may contribute to the non-significant relationship between emotional management and bullying/victimization.

The hypothesis that PA negatively predicts interpersonal relationship issues was confirmed in this study. Regular participation in PA increases opportunities for interaction among students, especially in group activities [ 47 ]. It promotes mutual interactions while reducing the occurrence of some negative emotions. Adolescents usually do not prefer to communicate with guardians such as family and teachers, leading to relatively less social support and help, which weakens their interpersonal communication skills during this period. When conflicts and disputes arise among students, they tend to use simple and rough methods to cope, leading to deteriorating peer relationships and escalating conflicts, which may trigger school bullying. The conclusion that interpersonal relationship issues positively predict school bullying and victimization was also confirmed in this study, consistent with most research results [ 25 , 47 , 48 ]. Negative interpersonal relationships among adolescents can directly predict aggressive behaviors. Previous studies have shown that poor conflict management skills in interpersonal relationships are a risk factor for bullying [ 49 ]. Longitudinal studies also show that reducing negative emotions like anxiety and depression and fostering positive peer perceptions can predict a reduction in victimization [ 50 ]. Adolescents with interpersonal relationship issues often experience frustration in real-life interactions. The widespread use of the internet and the development of mobile media lead them to escape reality, feel alienated from society, and seek fulfillment in the virtual world [ 51 ]. Adolescents during this period may view bullying as a reasonable way to solve problems and may become bullies in certain situations. Meanwhile, the excessive use of mobile phones, the internet, and other media takes up a lot of students’ time, making those who lack PA and are sedentary more likely to become victims of bullying [ 15 ].

This study also found that emotional management negatively predicts interpersonal relationship issues, similar to most domestic and international studies [ 52 , 53 , 54 ]. Liu proposed that emotional self-management ability, psychological resilience, and adolescent PA mutually promote each other, enhancing adolescents’ social communication skills [ 52 ]. With good emotional management strategies, individuals can transform negative emotions, stressful events, and disharmony into conditions that motivate self-development, reduce the experience of negative emotions, and handle interpersonal relationships more rationally, effectively alleviating awkwardness and discomfort in interactions [ 53 ]. Emotional management is closely related to the development of individual social cognitive characteristics and social communication skills [ 54 ]. Adolescents who frequently exhibit negative emotions may experience social withdrawal, lack of activity, and a lack of sports skills, leading to lower acceptance among peers, such as being less talkative or not fitting in. In contrast, good emotional management can help adolescents better handle various issues related to self-development and social interactions.

In summary, this study confirmed the positive predictive effect of PA on emotional management and its negative predictive effect on alleviating interpersonal relationship issues. This provides important guidance for the application of PA in preventing school bullying. By incorporating the challenges and stress of activity into daily physical education classes, students can learn and experience the effectiveness of emotional regulation during physical activities. Some studies have shown that participating in relaxation activities such as yoga [ 55 ] and meditation [ 56 ] can significantly promote emotional stability and enhance self-regulation abilities, helping students better control and adjust their emotions during exercise, thus more effectively coping with school pressures and conflicts. Additionally, encouraging participation in group activities [ 57 ] can significantly enhance students’ social skills, increase peer interactions, and reduce feelings of isolation and interpersonal conflicts. Implementing these strategies can help schools effectively reduce the impact of interpersonal relationship issues on bullying and victimization, and improve students’ social environment. Ultimately, this will help create a positive and healthy living environment for students, promoting their overall well-being and healthy development.

Strengths and limitations

This study, grounded in the theories of self-efficacy and interpersonal relationships, incorporates ERS and IRD as mediating variables. It separately models and explores the relationships and underlying mechanisms between physical activity (PA), bullying behavior, and being bullied. The findings provide empirical evidence and intervention recommendations for addressing school bullying, assisting educators and society in effectively tackling issues that impact students’ physical and mental health.

However, this study has some limitations. Firstly, as a cross-sectional study, it cannot infer causal relationships between variables. Future research could employ longitudinal tracking or experimental intervention designs to better explain the impact of PA on school bullying. Secondly, while this study considered the mediating roles of self-efficacy and IRD, other potential moderating factors such as cultural adaptation [ 41 ] and parental education level [ 58 ] might also influence the research outcomes. Future research could incorporate these factors to achieve a more comprehensive understanding of the complex relationship between bullying victimization and mental health. Additionally, the study’s participants were junior high school students from Eastern China, which may limit the generalizability of the findings. Future research should expand the sample to include students from more countries and regions. Lastly, this study explored the predictive mechanism of bullying based on students’ PA levels, but the practical implications of the findings need further strengthening. Future research should examine the effects of different forms, intensities, and types of PA on school bullying.

In the model predicting school bullying, PA significantly predicts bullying, ERS, and IRD. ERS negatively predicts IRD but does not significantly predict bullying. Additionally, IRD significantly predicts bullying. The prediction of school bullying by PA includes masking effects, with two primary pathways: (1) PA → IRD → bullying, and (2) PA → ERS → IRD → bullying. In the model predicting being bullied at school, PA does not significantly predict this outcome. However, PA significantly positively predicts ERS and negatively predicts IRD. ERS significantly negatively predicts IRD but does not significantly predict being bullied. IRD significantly predicts being bullied. PA fully mediates the prediction of being bullied, with the pathways being: (1) PA → IRD → being bullied, and (2) PA → ERS → IRD → being bullied.

Based on the results of this study, we conclude that PA is an effective way to improve students’ emotional regulation and interpersonal relationships, significantly reducing both bullying and victimization. Given the prevalence of school bullying and its negative impact on mental health, public health policies should prioritize increasing adolescent participation in moderate-to-vigorous physical activity. This not only enhances physical health but also effectively improves emotional regulation and develops students’ social interaction skills. Additionally, it is recommended that structured physical activity be incorporated into school curricula to create a relaxed and enjoyable learning environment, improving peer relationships and maximizing the prevention of school bullying.

Data availability

The datasets of this study are available from the corresponding author on reasonable request.

Abbreviations

Campus Bullying Scale

Comparative Fit Index

Conversation Trouble

Emotional Management Self-Efficacy Scale

Emotion Regulation Self-Efficacy

Expressing Positive Emotions

Exposure to Heterosexual Distress

Goodness of Fit Index

Interpersonal Relationship Distress Scale

Interpersonal Relationship Distress

Interaction Trouble

Moderate-to-Vigorous Physical Activity

Physical Activity

Physical Activity Rating Scale

Root Mean Square Error of Approximation

Regulating Fear

Regulating Stress

Standardized Root Mean Square Residual

Tucker-Lewis Index

Trouble Treating Others

Victimization

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Acknowledgements

We are grateful to the schools for approving our baseline survey and the intervention study and thank all the students who participated in our study.

This work was supported by the Key Project of Chongqing Academy of Educational Science (Grant No. 2021-16-238). The funding agency had no role in the design of the study, data collection, analysis, interpretation of data, writing of the manuscript, or the decision to publish.

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Zhang, Q., Deng, W. Relationship between physical exercise, bullying, and being bullied among junior high school students: the multiple mediating effects of emotional management and interpersonal relationship distress. BMC Public Health 24 , 2503 (2024). https://doi.org/10.1186/s12889-024-20012-y

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PDF Cyberbullying: A Review of the Literature
A review of literature is provided and results and analysis of the survey are discussed as well as recommendations for future research. Erdur-Baker's (2010) study revealed that 32% of the students were victims of both cyberbullying and traditional bullying, while 26% of the students bullied others in both cyberspace and physical environments ...
Full article: Bullying and cyberbullying: a bibliometric analysis of
A comprehensive review of the literature on bullying and cyberbullying in education, covering the trends, topics, and methods of three decades of research.
Cyberbullying research
Our study aims to provide a bibliometric overview of Cyberbullying research between 2010 and 2021, including a new analysis through the lens of sustainable development and the impact of COVID-19. We introduce altmetrics to assess the social media attention of publications.
Cyberbullying and its impact on young people's emotional health and
The impact of cyberbullying on emotional health and well-being Research consistently identifies the consequences of bullying for the emotional health of children and young people. Victims experience lack of acceptance in their peer groups, which results in loneliness and social isolation.
PDF The Effect of Cyber Bullying on Students Performance in the Exam ...
ABSTRACT This research investigates the emotional and physiological effects of cyber bullying on the university students. The primary objective of this investigation is to identify the victims of cyber bullying and critically analyze their emotional state and frame of mind in order to provide them with a workable and feasible intervention in fighting cyber bullying. In this research a ...
How childhood psychological abuse affects adolescent cyberbullying: The
Background Despite the recognition of the impact of childhood psychological abuse, self-efficacy, and psychological resilience on cyberbullying, there is still a gap in understanding the specific mechanisms through which childhood psychological abuse impacts cyberbullying via self-efficacy and psychological resilience. Methods Based on the Social Cognitive Theory, this study aims to ...
Cyberbullying Prevention and Intervention Efforts: Current Knowledge
This article reviews the current status of cyberbullying prevention and intervention efforts and provides suggestions for future research and implications for health care providers in Canada. Research on cyberbullying is relatively recent in comparison to the 4 decades of research on face-to-face bullying.
CYBER BULLYING: CAUSES, PSYCHOLOGICAL IMPACT AND REMEDIES
PDF | Cyberbullying has been analysed as a critical problem amongst youngsters in these years. The article addresses some common issues in... | Find, read and cite all the research you need on ...
Impacts of Cyberbullying and Its Solutions
The harmful effects of cyberbullying on teenagerssuch as sadness, anxiety, low self-esteem, suicidal behavior, eating disorders and gastrointestinal problemsare explored in the paper.
Qualitative Methods in School Bullying and Cyberbullying Research: An
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 ...
Prevalence and related risks of cyberbullying and its effects on
Background Cyberbullying is becoming common in inflicting harm on others, especially among adolescents. This study aims to assess the prevalence of cyberbullying, determine the risk factors, and assess the association between cyberbullying and the psychological status of adolescents facing this problem in the Jazan region, Saudi Arabia. Methods A cross-sectional study was conducted on 355 ...
Frontiers
Background: Cyberbullying is well-recognized as a severe public health issue which affects both adolescents and children. Most extant studies have focused on national and regional effects of cyberbullying, with few examining the global perspective of cyberbullying.
Cyberbullying and Adolescents
Cyberbullying is an aggressive behavior involving a type of electronic communication intending to harm a victim that can have profound effects on adolescents. This review examines the epidemiology, issues from cyberbullying, presentation to care of its ...
Early Recognition and Intervention of Bullying and Cyberbullying
Bullying and cyberbullying remain pervasive issues affecting children and adolescents worldwide, with significant psychological, social, and academic consequences. Despite increased awareness, many cases of bullying go unrecognized or are addressed too late, exacerbating the negative impacts on both bullies and victims. Early recognition and intervention are crucial in mitigating these effects ...
Cyberbullying in High Schools: A Study of Students' Behaviors and
This study explores high school students' beliefs and behaviors associated with cyberbullying. Specifically, it examines this new phenomenon from the following four perspectives: (a) What happens a...
Effects of cyberbullying
The impact of cyberbullying goes beyond the screen. It can lead to serious mental health issues, increased stress and anxiety, depression, violent behavior and low self-esteem. KCU's Dr. Ken Stewart speaks on the effects of cyberbullying and what we can do to stop it.
Cyberbullying on social media platforms among university students in
Previous research has found different correlates and consequences associated with specific forms of cyberbullying (Waasdorp & Bradshaw, 2011). Physical and psychological health-related and academic performance-related impacts have been cited as major correlations in both traditional and cyberbullying (Kowalski & Limber, 2013).
Relationship between physical exercise, bullying, and being bullied
Objective This paper investigates the relationships between physical activity (PA), school bullying, emotion regulation self-efficacy (ERS), and interpersonal relationship distress (IRD) among junior high school students. It also examines the underlying mechanisms of school bullying to provide insights into reducing adolescent bullying and to lay the groundwork for preventing and controlling ...
Bullying in schools: the state of knowledge and effective interventions
This article reviews the current research on bullying in schools, its causes, consequences, and prevention strategies, and provides practical guidance for educators and practitioners.

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How childhood psychological abuse affects adolescent cyberbullying: The chain mediating role of self-efficacy and psychological resilience

1. Introduction

2. Theoretical background and hypothesis development

2.2 Hypothesis development

2.2.2 Self-efficacy as a mediator.

2.2.3 Psychological resilience as a mediator.

3. Materials and methods

3.2 Procedure

3.3 Research instrument

3.3.2 Self-efficacy scale.

3.3.3 Psychological resilience scale.

3.3.4 Cyberbullying scale.

3.4 Statistical analysis

4.1 Common method bias analysis

4.2 Correlation analyses

4.3 Measurement model

4.4 Structural model

4.5 Testing for mediation effect

5. Discussion

5.1 Findings

5.2 Implications

5.3 Limitations

6. Conclusion

Supporting information

Acknowledgments

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

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Prevalence and related risks of cyberbullying and its effects on adolescent

Conclusions

Introduction

Design and participants

Procedure of data collection and study measures

Data presentation & statistical analysis

Limitations of the study

Availability of data and materials

Acknowledgements

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BMC Psychiatry

Cyberbullying and Adolescents

Mark A. Goldstein

Purpose of Review