hypothesis about bullying

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Published: 14 December 2021

Bullying at school and mental health problems among adolescents: a repeated cross-sectional study

Håkan Källmén 1 &
Mats Hallgren ORCID: orcid.org/0000-0002-0599-2403 2

Child and Adolescent Psychiatry and Mental Health volume 15 , Article number: 74 ( 2021 ) Cite this article

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To examine recent trends in bullying and mental health problems among adolescents and the association between them.

A questionnaire measuring mental health problems, bullying at school, socio-economic status, and the school environment was distributed to all secondary school students aged 15 (school-year 9) and 18 (school-year 11) in Stockholm during 2014, 2018, and 2020 (n = 32,722). Associations between bullying and mental health problems were assessed using logistic regression analyses adjusting for relevant demographic, socio-economic, and school-related factors.

The prevalence of bullying remained stable and was highest among girls in year 9; range = 4.9% to 16.9%. Mental health problems increased; range = + 1.2% (year 9 boys) to + 4.6% (year 11 girls) and were consistently higher among girls (17.2% in year 11, 2020). In adjusted models, having been bullied was detrimentally associated with mental health (OR = 2.57 [2.24–2.96]). Reports of mental health problems were four times higher among boys who had been bullied compared to those not bullied. The corresponding figure for girls was 2.4 times higher.

Conclusions

Exposure to bullying at school was associated with higher odds of mental health problems. Boys appear to be more vulnerable to the deleterious effects of bullying than girls.

Introduction

Bullying involves repeated hurtful actions between peers where an imbalance of power exists [ 1 ]. Arseneault et al. [ 2 ] conducted a review of the mental health consequences of bullying for children and adolescents and found that bullying is associated with severe symptoms of mental health problems, including self-harm and suicidality. Bullying was shown to have detrimental effects that persist into late adolescence and contribute independently to mental health problems. Updated reviews have presented evidence indicating that bullying is causative of mental illness in many adolescents [ 3 , 4 ].

There are indications that mental health problems are increasing among adolescents in some Nordic countries. Hagquist et al. [ 5 ] examined trends in mental health among Scandinavian adolescents (n = 116, 531) aged 11–15 years between 1993 and 2014. Mental health problems were operationalized as difficulty concentrating, sleep disorders, headache, stomach pain, feeling tense, sad and/or dizzy. The study revealed increasing rates of adolescent mental health problems in all four counties (Finland, Sweden, Norway, and Denmark), with Sweden experiencing the sharpest increase among older adolescents, particularly girls. Worsening adolescent mental health has also been reported in the United Kingdom. A study of 28,100 school-aged adolescents in England found that two out of five young people scored above thresholds for emotional problems, conduct problems or hyperactivity [ 6 ]. Female gender, deprivation, high needs status (educational/social), ethnic background, and older age were all associated with higher odds of experiencing mental health difficulties.

Bullying is shown to increase the risk of poor mental health and may partly explain these detrimental changes. Le et al. [ 7 ] reported an inverse association between bullying and mental health among 11–16-year-olds in Vietnam. They also found that poor mental health can make some children and adolescents more vulnerable to bullying at school. Bayer et al. [ 8 ] examined links between bullying at school and mental health among 8–9-year-old children in Australia. Those who experienced bullying more than once a week had poorer mental health than children who experienced bullying less frequently. Friendships moderated this association, such that children with more friends experienced fewer mental health problems (protective effect). Hysing et al. [ 9 ] investigated the association between experiences of bullying (as a victim or perpetrator) and mental health, sleep disorders, and school performance among 16–19 year olds from Norway (n = 10,200). Participants were categorized as victims, bullies, or bully-victims (that is, victims who also bullied others). All three categories were associated with worse mental health, school performance, and sleeping difficulties. Those who had been bullied also reported more emotional problems, while those who bullied others reported more conduct disorders [ 9 ].

As most adolescents spend a considerable amount of time at school, the school environment has been a major focus of mental health research [ 10 , 11 ]. In a recent review, Saminathen et al. [ 12 ] concluded that school is a potential protective factor against mental health problems, as it provides a socially supportive context and prepares students for higher education and employment. However, it may also be the primary setting for protracted bullying and stress [ 13 ]. Another factor associated with adolescent mental health is parental socio-economic status (SES) [ 14 ]. A systematic review indicated that lower parental SES is associated with poorer adolescent mental health [ 15 ]. However, no previous studies have examined whether SES modifies or attenuates the association between bullying and mental health. Similarly, it remains unclear whether school related factors, such as school grades and the school environment, influence the relationship between bullying and mental health. This information could help to identify those adolescents most at risk of harm from bullying.

To address these issues, we investigated the prevalence of bullying at school and mental health problems among Swedish adolescents aged 15–18 years between 2014 and 2020 using a population-based school survey. We also examined associations between bullying at school and mental health problems adjusting for relevant demographic, socioeconomic, and school-related factors. We hypothesized that: (1) bullying and adolescent mental health problems have increased over time; (2) There is an association between bullying victimization and mental health, so that mental health problems are more prevalent among those who have been victims of bullying; and (3) that school-related factors would attenuate the association between bullying and mental health.

Participants

The Stockholm school survey is completed every other year by students in lower secondary school (year 9—compulsory) and upper secondary school (year 11). The survey is mandatory for public schools, but voluntary for private schools. The purpose of the survey is to help inform decision making by local authorities that will ultimately improve students’ wellbeing. The questions relate to life circumstances, including SES, schoolwork, bullying, drug use, health, and crime. Non-completers are those who were absent from school when the survey was completed (< 5%). Response rates vary from year to year but are typically around 75%. For the current study data were available for 2014, 2018 and 2020. In 2014; 5235 boys and 5761 girls responded, in 2018; 5017 boys and 5211 girls responded, and in 2020; 5633 boys and 5865 girls responded (total n = 32,722). Data for the exposure variable, bullied at school, were missing for 4159 students, leaving 28,563 participants in the crude model. The fully adjusted model (described below) included 15,985 participants. The mean age in grade 9 was 15.3 years (SD = 0.51) and in grade 11, 17.3 years (SD = 0.61). As the data are completely anonymous, the study was exempt from ethical approval according to an earlier decision from the Ethical Review Board in Stockholm (2010-241 31-5). Details of the survey are available via a website [ 16 ], and are described in a previous paper [ 17 ].

Students completed the questionnaire during a school lesson, placed it in a sealed envelope and handed it to their teacher. Student were permitted the entire lesson (about 40 min) to complete the questionnaire and were informed that participation was voluntary (and that they were free to cancel their participation at any time without consequences). Students were also informed that the Origo Group was responsible for collection of the data on behalf of the City of Stockholm.

Study outcome

Mental health problems were assessed by using a modified version of the Psychosomatic Problem Scale [ 18 ] shown to be appropriate for children and adolescents and invariant across gender and years. The scale was later modified [ 19 ]. In the modified version, items about difficulty concentrating and feeling giddy were deleted and an item about ‘life being great to live’ was added. Seven different symptoms or problems, such as headaches, depression, feeling fear, stomach problems, difficulty sleeping, believing it’s great to live (coded negatively as seldom or rarely) and poor appetite were used. Students who responded (on a 5-point scale) that any of these problems typically occurs ‘at least once a week’ were considered as having indicators of a mental health problem. Cronbach alpha was 0.69 across the whole sample. Adding these problem areas, a total index was created from 0 to 7 mental health symptoms. Those who scored between 0 and 4 points on the total symptoms index were considered to have a low indication of mental health problems (coded as 0); those who scored between 5 and 7 symptoms were considered as likely having mental health problems (coded as 1).

Primary exposure

Experiences of bullying were measured by the following two questions: Have you felt bullied or harassed during the past school year? Have you been involved in bullying or harassing other students during this school year? Alternatives for the first question were: yes or no with several options describing how the bullying had taken place (if yes). Alternatives indicating emotional bullying were feelings of being mocked, ridiculed, socially excluded, or teased. Alternatives indicating physical bullying were being beaten, kicked, forced to do something against their will, robbed, or locked away somewhere. The response alternatives for the second question gave an estimation of how often the respondent had participated in bullying others (from once to several times a week). Combining the answers to these two questions, five different categories of bullying were identified: (1) never been bullied and never bully others; (2) victims of emotional (verbal) bullying who have never bullied others; (3) victims of physical bullying who have never bullied others; (4) victims of bullying who have also bullied others; and (5) perpetrators of bullying, but not victims. As the number of positive cases in the last three categories was low (range = 3–15 cases) bully categories 2–4 were combined into one primary exposure variable: ‘bullied at school’.

Assessment year was operationalized as the year when data was collected: 2014, 2018, and 2020. Age was operationalized as school grade 9 (15–16 years) or 11 (17–18 years). Gender was self-reported (boy or girl). The school situation To assess experiences of the school situation, students responded to 18 statements about well-being in school, participation in important school matters, perceptions of their teachers, and teaching quality. Responses were given on a four-point Likert scale ranging from ‘do not agree at all’ to ‘fully agree’. To reduce the 18-items down to their essential factors, we performed a principal axis factor analysis. Results showed that the 18 statements formed five factors which, according to the Kaiser criterion (eigen values > 1) explained 56% of the covariance in the student’s experience of the school situation. The five factors identified were: (1) Participation in school; (2) Interesting and meaningful work; (3) Feeling well at school; (4) Structured school lessons; and (5) Praise for achievements. For each factor, an index was created that was dichotomised (poor versus good circumstance) using the median-split and dummy coded with ‘good circumstance’ as reference. A description of the items included in each factor is available as Additional file 1 . Socio-economic status (SES) was assessed with three questions about the education level of the student’s mother and father (dichotomized as university degree versus not), and the amount of spending money the student typically received for entertainment each month (> SEK 1000 [approximately $120] versus less). Higher parental education and more spending money were used as reference categories. School grades in Swedish, English, and mathematics were measured separately on a 7-point scale and dichotomized as high (grades A, B, and C) versus low (grades D, E, and F). High school grades were used as the reference category.

Statistical analyses

The prevalence of mental health problems and bullying at school are presented using descriptive statistics, stratified by survey year (2014, 2018, 2020), gender, and school year (9 versus 11). As noted, we reduced the 18-item questionnaire assessing school function down to five essential factors by conducting a principal axis factor analysis (see Additional file 1 ). We then calculated the association between bullying at school (defined above) and mental health problems using multivariable logistic regression. Results are presented as odds ratios (OR) with 95% confidence intervals (Cis). To assess the contribution of SES and school-related factors to this association, three models are presented: Crude, Model 1 adjusted for demographic factors: age, gender, and assessment year; Model 2 adjusted for Model 1 plus SES (parental education and student spending money), and Model 3 adjusted for Model 2 plus school-related factors (school grades and the five factors identified in the principal factor analysis). These covariates were entered into the regression models in three blocks, where the final model represents the fully adjusted analyses. In all models, the category ‘not bullied at school’ was used as the reference. Pseudo R-square was calculated to estimate what proportion of the variance in mental health problems was explained by each model. Unlike the R-square statistic derived from linear regression, the Pseudo R-square statistic derived from logistic regression gives an indicator of the explained variance, as opposed to an exact estimate, and is considered informative in identifying the relative contribution of each model to the outcome [ 20 ]. All analyses were performed using SPSS v. 26.0.

Prevalence of bullying at school and mental health problems

Estimates of the prevalence of bullying at school and mental health problems across the 12 strata of data (3 years × 2 school grades × 2 genders) are shown in Table 1 . The prevalence of bullying at school increased minimally (< 1%) between 2014 and 2020, except among girls in grade 11 (2.5% increase). Mental health problems increased between 2014 and 2020 (range = 1.2% [boys in year 11] to 4.6% [girls in year 11]); were three to four times more prevalent among girls (range = 11.6% to 17.2%) compared to boys (range = 2.6% to 4.9%); and were more prevalent among older adolescents compared to younger adolescents (range = 1% to 3.1% higher). Pooling all data, reports of mental health problems were four times more prevalent among boys who had been victims of bullying compared to those who reported no experiences with bullying. The corresponding figure for girls was two and a half times as prevalent.

Associations between bullying at school and mental health problems

Table 2 shows the association between bullying at school and mental health problems after adjustment for relevant covariates. Demographic factors, including female gender (OR = 3.87; CI 3.48–4.29), older age (OR = 1.38, CI 1.26–1.50), and more recent assessment year (OR = 1.18, CI 1.13–1.25) were associated with higher odds of mental health problems. In Model 2, none of the included SES variables (parental education and student spending money) were associated with mental health problems. In Model 3 (fully adjusted), the following school-related factors were associated with higher odds of mental health problems: lower grades in Swedish (OR = 1.42, CI 1.22–1.67); uninteresting or meaningless schoolwork (OR = 2.44, CI 2.13–2.78); feeling unwell at school (OR = 1.64, CI 1.34–1.85); unstructured school lessons (OR = 1.31, CI = 1.16–1.47); and no praise for achievements (OR = 1.19, CI 1.06–1.34). After adjustment for all covariates, being bullied at school remained associated with higher odds of mental health problems (OR = 2.57; CI 2.24–2.96). Demographic and school-related factors explained 12% and 6% of the variance in mental health problems, respectively (Pseudo R-Square). The inclusion of socioeconomic factors did not alter the variance explained.

Our findings indicate that mental health problems increased among Swedish adolescents between 2014 and 2020, while the prevalence of bullying at school remained stable (< 1% increase), except among girls in year 11, where the prevalence increased by 2.5%. As previously reported [ 5 , 6 ], mental health problems were more common among girls and older adolescents. These findings align with previous studies showing that adolescents who are bullied at school are more likely to experience mental health problems compared to those who are not bullied [ 3 , 4 , 9 ]. This detrimental relationship was observed after adjustment for school-related factors shown to be associated with adolescent mental health [ 10 ].

A novel finding was that boys who had been bullied at school reported a four-times higher prevalence of mental health problems compared to non-bullied boys. The corresponding figure for girls was 2.5 times higher for those who were bullied compared to non-bullied girls, which could indicate that boys are more vulnerable to the deleterious effects of bullying than girls. Alternatively, it may indicate that boys are (on average) bullied more frequently or more intensely than girls, leading to worse mental health. Social support could also play a role; adolescent girls often have stronger social networks than boys and could be more inclined to voice concerns about bullying to significant others, who in turn may offer supports which are protective [ 21 ]. Related studies partly confirm this speculative explanation. An Estonian study involving 2048 children and adolescents aged 10–16 years found that, compared to girls, boys who had been bullied were more likely to report severe distress, measured by poor mental health and feelings of hopelessness [ 22 ].

Other studies suggest that heritable traits, such as the tendency to internalize problems and having low self-esteem are associated with being a bully-victim [ 23 ]. Genetics are understood to explain a large proportion of bullying-related behaviors among adolescents. A study from the Netherlands involving 8215 primary school children found that genetics explained approximately 65% of the risk of being a bully-victim [ 24 ]. This proportion was similar for boys and girls. Higher than average body mass index (BMI) is another recognized risk factor [ 25 ]. A recent Australian trial involving 13 schools and 1087 students (mean age = 13 years) targeted adolescents with high-risk personality traits (hopelessness, anxiety sensitivity, impulsivity, sensation seeking) to reduce bullying at school; both as victims and perpetrators [ 26 ]. There was no significant intervention effect for bullying victimization or perpetration in the total sample. In a secondary analysis, compared to the control schools, intervention school students showed greater reductions in victimization, suicidal ideation, and emotional symptoms. These findings potentially support targeting high-risk personality traits in bullying prevention [ 26 ].

The relative stability of bullying at school between 2014 and 2020 suggests that other factors may better explain the increase in mental health problems seen here. Many factors could be contributing to these changes, including the increasingly competitive labour market, higher demands for education, and the rapid expansion of social media [ 19 , 27 , 28 ]. A recent Swedish study involving 29,199 students aged between 11 and 16 years found that the effects of school stress on psychosomatic symptoms have become stronger over time (1993–2017) and have increased more among girls than among boys [ 10 ]. Research is needed examining possible gender differences in perceived school stress and how these differences moderate associations between bullying and mental health.

Strengths and limitations

Strengths of the current study include the large participant sample from diverse schools; public and private, theoretical and practical orientations. The survey included items measuring diverse aspects of the school environment; factors previously linked to adolescent mental health but rarely included as covariates in studies of bullying and mental health. Some limitations are also acknowledged. These data are cross-sectional which means that the direction of the associations cannot be determined. Moreover, all the variables measured were self-reported. Previous studies indicate that students tend to under-report bullying and mental health problems [ 29 ]; thus, our results may underestimate the prevalence of these behaviors.

In conclusion, consistent with our stated hypotheses, we observed an increase in self-reported mental health problems among Swedish adolescents, and a detrimental association between bullying at school and mental health problems. Although bullying at school does not appear to be the primary explanation for these changes, bullying was detrimentally associated with mental health after adjustment for relevant demographic, socio-economic, and school-related factors, confirming our third hypothesis. The finding that boys are potentially more vulnerable than girls to the deleterious effects of bullying should be replicated in future studies, and the mechanisms investigated. Future studies should examine the longitudinal association between bullying and mental health, including which factors mediate/moderate this relationship. Epigenetic studies are also required to better understand the complex interaction between environmental and biological risk factors for adolescent mental health [ 24 ].

Availability of data and materials

Data requests will be considered on a case-by-case basis; please email the corresponding author.

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Acknowledgements

Authors are grateful to the Department for Social Affairs, Stockholm, for permission to use data from the Stockholm School Survey.

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HK conceived the study and analyzed the data (with input from MH). HK and MH interpreted the data and jointly wrote the manuscript. All authors read and approved the final manuscript.

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Additional file 1..

Principal factor analysis description.

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Källmén, H., Hallgren, M. Bullying at school and mental health problems among adolescents: a repeated cross-sectional study. Child Adolesc Psychiatry Ment Health 15 , 74 (2021). https://doi.org/10.1186/s13034-021-00425-y

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Four decades of research on school bullying: An introduction

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1 Faculty of Education, Department of Educational and Counselling Psychology and Special Education.
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This article provides an introductory overview of findings from the past 40 years of research on bullying among school-aged children and youth. Research on definitional and assessment issues in studying bullying and victimization is reviewed, and data on prevalence rates, stability, and forms of bullying behavior are summarized, setting the stage for the 5 articles that comprise this American Psychologist special issue on bullying and victimization. These articles address bullying, victimization, psychological sequela and consequences, ethical, legal, and theoretical issues facing educators, researchers, and practitioners, and effective prevention and intervention efforts. The goal of this special issue is to provide psychologists with a comprehensive review that documents our current understanding of the complexity of bullying among school-aged youth and directions for future research and intervention efforts.

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Bullying is an epidemic that is not showing signs of improvement.
Evidence-based bullying prevention programs can be effective, but school adoption is inconsistent.

According to the U.S. federal government website StopBullying.gov :

There is no federal law that specifically applies to bullying . In some cases, when bullying is based on race or ethnicity , color, national origin, sex, disability, or religion, bullying overlaps with harassment and schools are legally obligated to address it.

The National Bullying Prevention Center reports data suggesting that one in five children have been bullied. There are many risk factors for being targeted, including being seen as weak, being different from peers including being LGBT or having learning differences or visible disabilities, being depressed or anxious, and having few friends. It's hard to measure how many engage in bullying, but estimates range from one in twenty, to much higher .

The American Association of University Women reports that in grades 7-12, 48 percent of students (56 percent of girls and 40 percent of boys) are sexually harassed. In college, rates of sexual harassment rise to 66 percent. Eleven percent are raped or sexually assaulted.

Silence facilitates traumatization

Only 20 percent of attacked young women report sexual assault . And 89 percent of undergraduate schools report zero sexual harassment. This means that children, adolescents, young adults and their friends are at high risk for being victimized. It means that many kids know what is happening, and don't do anything.

This may be from fear of retaliation and socialization into a trauma-permissive culture, and it may be from lack of proper education and training. Institutional betrayal , when organizations fail to uphold their promises and responsibilities, adds to the problem.

In some states such as New York, laws like “ the Dignity for All Students Act ” (DASA) apply only to public schools. Private, religious, and denominational schools are not included, leaving 20 percent of students in NYC and 10 percent throughout the state unprotected. Research shows that over the last decade, bullying in U.S. high schools has held steady around 20 percent, and 15 percent for cyberbullying.

The impact of bullying

While there is much research on how bullying affects mental health, social function, and academics, the results are scattered across dozens of papers. A recent paper in the Journal of School Violence (Halliday et al., 2021) presents a needed systematic literature review on bullying’s impact in children aged 10-18.

1. Psychological: Being a victim of bullying was associated with increased depression , anxiety , and psychosis . Victims of bullying reported more suicidal thinking and engaged in greater self-harming behaviors. They were more likely to experience social anxiety , body-image issues, and negative conduct. Simultaneous cyberbullying and conventional bullying were associated with more severe depression.

2. Social: Bullying victims reported greater problems in relationships with family, friends and in day-to-day social interactions. They reported they enjoyed time with family and friends less, felt they were being treated unfairly more easily, and liked less where they lived. Victimized children were less popular and likeable, and experienced more social rejection. They tended to be friends with other victims, potentially heightening problems while also providing social support.

3. Academic achievement: Victimized kids on average had lower grades. Over time, they did worse especially in math. They tended to be more proficient readers, perhaps as a result of turning to books for comfort in isolation (something people with a history of being bullied commonly report in therapy ).

4. School attitudes: Bullied children and adolescents were less engaged in education, had poorer attendance, felt less belonging, and felt more negatively about school.

5. What happens with age? Researchers studied adult psychiatric outcomes of bullying, looking at both victims and bullies, reported in the Journal of the American Medical Association (JAMA) Psychiatry (Copeland et al., 2013). After controlling for other childhood hardships, researchers found that young adults experience increased rates of agoraphobia (fear of leaving the house), generalized anxiety, panic disorder, and increased depression risk. Men had higher suicide risk.

The impact of bullying does not stop in early adulthood. Research in the Journals of Gerontology (Hu, 2021) found that people over the age of 60 who were bullied as children had more severe depression and had lower life satisfaction.

6. Bullying and the brain: Work reported in Frontiers in Psychiatry (Muetzel et al., 2019) found that victims of bullying had thickening of the fusiform gyrus, an area of the cerebral cortex involved with facial recognition, and sensing emotions from facial expressions. 1 For those with posttraumatic stress disorder, brain changes may be extensive.

7. Bystanders are affected: Research also shows that bystanders have higher rates of anxiety and depression (Midgett et al., 2019). The problem is magnified for bystanders who are also victims. It is likely that taking appropriate action is protective.

Given that victims of bullying are at risk for posttraumatic stress disorder ( PTSD ; Idsoe et al., 2012), it’s important to understand that many of the reported psychiatric findings may be better explained by PTSD than as a handful of overlapping but separate diagnoses. Trauma often goes unrecognized.

What can be done?

The psychosocial and academic costs of unmitigated bullying are astronomical, to say nothing of the considerable economic cost. Change is needed, but resistance to change, as with racism, gender bias, and other forms of discrimination , is built into how we see things.

Legislation: There is no federal antibullying legislation, and state laws may be weak and inconsistently applied. Given that bullying rates are no longer falling, it’s important for lawmakers and advocates to seek immediate changes.

Bullying prevention: Schools can adopt antibullying programs, though they are not universally effective and sometimes may backfire. Overall, however, research in JAMA Pediatrics (Fraguas et al., 2021) shows that antibullying programs reduce bullying, improve mental health outcomes, and stay effective over time. 2

Trauma-informed education creates an environment in which all participants are aware of the impact of childhood trauma and the need for specific modifications given how trauma is common among children and how it affects development.

According to the National Child Traumatic Stress Network (NCTSN):

"The primary mission of schools is to support students in educational achievement. To reach this goal, children must feel safe, supported, and ready to learn. Children exposed to violence and trauma may not feel safe or ready to learn. Not only are individual children affected by traumatic experiences, but other students, the adults on campus, and the school community can be impacted by interacting or working with a child who has experienced trauma. Thus, as schools maintain their critical focus on education and achievement, they must also acknowledge that mental health and wellness are innately connected to students’ success in the classroom and to a thriving school environment."

Parenting makes a difference. Certain parenting styles may set kids up for emotional abuse in relationships , while others may be protective. A 2019 study reported in Frontiers in Public Health (Plexousakis et al.) found that children with anxious, overprotective mothers were more likely to be victims.

Those with cold or detached mothers were more likely to become bullies. Overprotective fathering was associated with worse PTSD symptoms, likely by getting in the way of socialization. The children of overprotective fathers were also more likely to be aggressive.

Quality parental bonding, however, appeared to help protect children from PTSD symptoms. A healthy home environment is essential both for helping victims of bullying and preventing bullying in at-risk children.

Parents who recognize the need to learn more positive approaches can help buffer again the all-too-common cycle of passing trauma from generation to generation, building resilience and nurturing secure attachment to enjoy better family experiences and equip children to thrive.

State-by-state legislation

Bullying prevention programs (the KiVA program is also notable)

Measuring Bullying Victimization, Perpetration and Bystander Experiences , Centers for Disease Control

Trauma-informed teaching

US Government Stop Bullying

1. Such differences could both result from being bullied (e.g. needing to scan faces for threat) and could also make being bullied more likely (e.g. misreading social cues leading to increased risk of being targeted).

2. Such programs focus on reducing negative messaging in order to keep stakeholders engaged, monitor and respond quickly to bullying, involve students in bullying prevention and detection in positive ways (e.g. being an “upstander” instead of a bystander), monitor more closely for bullying when the risk is higher (e.g. after anti-bullying trainings), respond fairly with the understanding that bullies often have problems of their own and need help, involved parents and teachers in anti-bullying education, and devote specific resources for anti-bullying.

Sarah Halliday, Tess Gregory, Amanda Taylor, Christianna Digenis & Deborah Turnbull (2021): The Impact of Bullying Victimization in Early Adolescence on Subsequent Psychosocial and Academic Outcomes across the Adolescent Period: A Systematic Review, Journal of School Violence, DOI: 10.1080/15388220.2021.1913598

Copeland WE, Wolke D, Angold A, Costello EJ. Adult Psychiatric Outcomes of Bullying and Being Bullied by Peers in Childhood and Adolescence. JAMA Psychiatry. 2013;70(4):419–426. doi:10.1001/jamapsychiatry.2013.504

Bo Hu, PhD, Is Bullying Victimization in Childhood Associated With Mental Health in Old Age, The Journals of Gerontology: Series B, Volume 76, Issue 1, January 2021, Pages 161–172, https://doi.org/10.1093/geronb/gbz115

Muetzel RL, Mulder RH, Lamballais S, Cortes Hidalgo AP, Jansen P, Güroğlu B, Vernooiji MW, Hillegers M, White T, El Marroun H and Tiemeier H (2019) Frequent Bullying Involvement and Brain Morphology in Children. Front. Psychiatry 10:696. doi: 10.3389/fpsyt.2019.00696

Midgett, A., Doumas, D.M. Witnessing Bullying at School: The Association Between Being a Bystander and Anxiety and Depressive Symptoms. School Mental Health 11, 454–463 (2019). https://doi.org/10.1007/s12310-019-09312-6

Idsoe, T., Dyregrov, A. & Idsoe, E.C. Bullying and PTSD Symptoms. J Abnorm Child Psychol 40, 901–911 (2012). https://doi.org/10.1007/s10802-012-9620-0

Fraguas D, Díaz-Caneja CM, Ayora M, Durán-Cutilla M, Abregú-Crespo R, Ezquiaga-Bravo I, Martín-Babarro J, Arango C. Assessment of School Anti-Bullying Interventions: A Meta-analysis of Randomized Clinical Trials. JAMA Pediatr. 2021 Jan 1;175(1):44-55. doi: 10.1001/jamapediatrics.2020.3541. PMID: 33136156; PMCID: PMC7607493.

Plexousakis SS, Kourkoutas E, Giovazolias T, Chatira K and Nikolopoulos D (2019) School Bullying and Post-traumatic Stress Disorder Symptoms: The Role of Parental Bonding. Front. Public Health 7:75. doi: 10.3389/fpubh.2019.00075

Note: An ExperiMentations Blog Post ("Our Blog Post") is not intended to be a substitute for professional advice. We will not be liable for any loss or damage caused by your reliance on information obtained through Our Blog Post. Please seek the advice of professionals, as appropriate, regarding the evaluation of any specific information, opinion, advice, or other content. We are not responsible and will not be held liable for third-party comments on Our Blog Post. Any user comment on Our Blog Post that in our sole discretion restricts or inhibits any other user from using or enjoying Our Blog Post is prohibited and may be reported to Sussex Publishers/Psychology Today. Grant H. Brenner. All rights reserved.

Grant Hilary Brenner, M.D., a psychiatrist and psychoanalyst, helps adults with mood and anxiety conditions, and works on many levels to help unleash their full capacities and live and love well.

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Bullying: What We Know Based On 40 Years of Research

APA journal examines science aimed at understanding causes, prevention

WASHINGTON — A special issue of American Psychologist ® provides a comprehensive review of over 40 years of research on bullying among school age youth, documenting the current understanding of the complexity of the issue and suggesting directions for future research.

“The lore of bullies has long permeated literature and popular culture. Yet bullying as a distinct form of interpersonal aggression was not systematically studied until the 1970s. Attention to the topic has since grown exponentially,” said Shelley Hymel, PhD, professor of human development, learning and culture at the University of British Columbia, a scholarly lead on the special issue along with Susan M. Swearer, PhD, professor of school psychology at the University of Nebraska-Lincoln. “Inspired by the 2011 U.S. White House Conference on Bullying Prevention, this collection of articles documents current understanding of school bullying.”

The special issue consists of an introductory overview (PDF, 90KB) by Hymel and Swearer, co-directors of the Bullying Research Network, and five articles on various research areas of bullying including the long-term effects of bullying into adulthood, reasons children bully others, the effects of anti-bullying laws and ways of translating research into anti-bullying practice.

Articles in the issue:

Long-Term Adult Outcomes of Peer Victimization in Childhood and Adolescence: Pathways to Adjustment and Maladjustment (PDF, 122KB) by Patricia McDougall, PhD, University of Saskatchewan, and Tracy Vaillancourt, PhD, University of Ottawa.

The experience of being bullied is painful and difficult. Its negative impact — on academic functioning, physical and mental health, social relationships and self-perceptions — can endure across the school years. But not every victimized child develops into a maladjusted adult. In this article, the authors provide an overview of the negative outcomes experienced by victims through childhood and adolescence and sometimes into adulthood. They then analyze findings from prospective studies to identify factors that lead to different outcomes in different people, including in their biology, timing, support systems and self-perception.

Patricia McDougall can be contacted by email or by phone at (306) 966-6203.

A Relational Framework for Understanding Bullying: Developmental Antecedents and Outcomes (PDF, 151KB) by Philip Rodkin, PhD, and Dorothy Espelage, PhD, University of Illinois, Urbana-Champaign, and Laura Hanish, PhD, Arizona State University.

How do you distinguish bullying from aggression in general? In this review, the authors describe bullying from a relationship perspective. In order for bullying to be distinguished from other forms of aggression, a relationship must exist between the bully and the victim, there must be an imbalance of power between the two and it must take place over a period of time. “Bullying is perpetrated within a relationship, albeit a coercive, unequal, asymmetric relationship characterized by aggression,” wrote the authors. Within that perspective, the image of bullies as socially incompetent youth who rely on physical coercion to resolve conflicts is nothing more than a stereotype. While this type of “bully-victim” does exist and is primarily male, the authors describe another type of bully who is more socially integrated and has surprisingly high levels of popularity among his or her peers. As for the gender of victims, bullying is just as likely to occur between boys and girls as it is to occur in same-gender groups.

Dorothy Espelage can be contacted by email or by phone at (217) 333-9139.

Translating Research to Practice in Bullying Prevention (PDF, 157KB) by Catherine Bradshaw, PhD, University of Virginia.

This paper reviews the research and related science to develop a set of recommendations for effective bullying prevention programs. From mixed findings on existing programs, the author identifies core elements of promising prevention approaches (e.g., close playground supervision, family involvement, and consistent classroom management strategies) and recommends a three-tiered public health approach that can attend to students at all risk levels. However, the author notes, prevention efforts must be sustained and integrated to effect change.

Catherine Bradshaw can be contacted by email or by phone at (434) 924-8121.

Law and Policy on the Concept of Bullying at School (PDF, 126KB) by Dewey Cornell, PhD, University of Virginia, and Susan Limber, PhD, Clemson University.

Since the shooting at Columbine High School in 1999, all states but one have passed anti-bullying laws, and multiple court decisions have made schools more accountable for peer victimization. Unfortunately, current legal and policy approaches, which are strongly rooted in laws regarding harassment and discrimination, do not provide adequate protection for all bullied students. In this article, the authors provide a review of the legal framework underpinning many anti-bullying laws and make recommendations on best practices for legislation and school policies to effectively address the problem of bullying.

Dewey Cornell can be contacted by email or by phone at (434) 924-0793.

Understanding the Psychology of Bullying: Moving Toward a Social-Ecological Diathesis-Stress Model by Susan Swearer, PhD, University of Nebraska-Lincoln, and Shelley Hymel, PhD, University of British Columbia.

Children’s involvement in bullying varies across roles and over time. A student may be victimized by classmates but bully a sibling at home. Bullying is a complex form of interpersonal aggression that can be both a one-on-one process and a group phenomenon. It negatively affects not only the victim, but the bully and witnesses as well. In this paper, the authors suggest an integrated model for examining bullying and victimization that recognizes the complex and dynamic nature of bullying across multiple settings over time.

Susan Swearer can be contacted by email or by phone at (402) 472-1741. Shelley Hymel can be contacted by email or by phone at (604) 822-6022.

Copies of articles are also available from APA Public Affairs , (202) 336-5700.

The American Psychological Association, in Washington, D.C., is the largest scientific and professional organization representing psychology in the United States. APA's membership includes more than 122,500 researchers, educators, clinicians, consultants and students. Through its divisions in 54 subfields of psychology and affiliations with 60 state, territorial and Canadian provincial associations, APA works to advance the creation, communication and application of psychological knowledge to benefit society and improve people's lives.

Jim Sliwa (202) 336-5707

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Bullying: A Guide to Research, Intervention, and Prevention

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3 Theories That Help to Understand Bullying

Published: May 2012
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This chapter will entail a review of theoretical frameworks that are typically utilized to understand and address bullying, including an ecological systems framework, social learning, cognitive behavioural, attribution, lifestyles exposure and resilience frameworks. The complexity of bullying demands that more than one theoretical lens be used to help understand this phenomenon and to inform effective prevention and intervention strategies and programs. An ecological systems theoretical framework serves as an overarching umbrella within which the complex factors and interactions that influence bullying behavior can be examined and addressed. Innumerable theories can be applied within an ecological systems framework—at different times, sequentially or simultaneously.

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Child Adolesc Psychiatry Ment Health

Bullying in school and cyberspace: Associations with depressive symptoms in Swiss and Australian adolescents

Sonja perren.

1 Jacobs Center for Productive Youth Development, University of Zürich, Culmannstrasse 1, 8001 Zürich, Switzerland

Julian Dooley

2 Child Health Promotion Research Centre, Edith Cowan University, WA, Australia

Thérèse Shaw

Donna cross.

Cyber-bullying (i.e., bullying via electronic means) has emerged as a new form of bullying that presents unique challenges to those victimised. Recent studies have demonstrated that there is a significant conceptual and practical overlap between both types of bullying such that most young people who are cyber-bullied also tend to be bullied by more traditional methods. Despite the overlap between traditional and cyber forms of bullying, it remains unclear if being a victim of cyber-bullying has the same negative consequences as being a victim of traditional bullying.

The current study investigated associations between cyber versus traditional bullying and depressive symptoms in 374 and 1320 students from Switzerland and Australia respectively (52% female; Age: M = 13.8, SD = 1.0). All participants completed a bullying questionnaire (assessing perpetration and victimisation of traditional and cyber forms of bullying behaviour) in addition to scales on depressive symptoms.

Across both samples, traditional victims and bully-victims reported more depressive symptoms than bullies and non-involved children. Importantly, victims of cyber-bullying reported significantly higher levels of depressive symptoms, even when controlling for the involvement in traditional bullying/victimisation.

Conclusions

Overall, cyber-victimisation emerged as an additional risk factor for depressive symptoms in adolescents involved in bullying.

It is well established that students who are bullied by their peers are at higher risk for internalizing problems. Recently, a new form of bullying behaviour has come to the attention of school staff, clinicians, researchers and the general public, namely cyber-bullying. Although several definitions are proposed, cyber-bullying is generally considered to be bullying using technology such as the Internet and mobile phones [ 1 - 3 ]. Recent studies have demonstrated that there is a significant conceptual and practical overlap between both types of bullying such that most young people who are cyber-bullied also tend to be bullied by more traditional methods [ 4 - 6 ]. Despite the overlap between traditional and cyber forms of bullying, it remains unclear if being a victim of cyber-bullying has the same negative consequences as being a victim of traditional bullying. Therefore, to investigate this we differentiate between two types of bullying: traditional bullying , including physical or verbal harassment, exclusion, relational aggression and cyber-bullying , involving the use of some kind of electronic media (i.e., Internet or mobile phone) to engage in bullying behaviour. The aim of the current study was to investigate the associations between both types of bullying and depressive symptoms in adolescents from two different countries.

Consequences and correlates of peer victimisation

As children develop, the peer context acquires increasing importance for health and well-being [ 7 ]. Peer problems during childhood and adolescence can often result in disruptions to healthy functioning both for those who engage in disruptive behaviours as well as those who are victimised.

It is well established that being a victim of bullying has negative short- and long-term consequences. Furthermore, it is reported that negative peer relations such as lack of acceptance in the peer group and peer victimisation are associated with loneliness, social dissatisfaction and social withdrawal [ 8 ] and emotional and behavioural symptoms [ 9 ]. Importantly, evidence from several longitudinal studies has demonstrated that peer victimisation and exclusion may also increase children's depressive symptoms [ 10 - 13 ]. These findings indicate that peer rejection and victimisation may play a causal role in the development of depressive symptoms. Consistently, the causal influence of peer victimisation on symptoms of depression was supported by the results of a recent twin study [ 14 ].

A meta-analytic review of cross-sectional associations between peer victimisation and psychosocial maladjustment provided clear evidence that peer victimisation is most strongly related to symptoms of depression and least strongly to anxiety [ 15 ]. Peer victimisation is also associated with low self-esteem, health problems, suicidality, and poor school adjustment [ 16 - 20 ].

Consequences and correlates of bullying behaviours

Young people who bully others also often experience negative consequences related to their behaviour, some of which are not immediately apparent [ 21 ]. For example, primary and middle school students who bully others often seem unscathed, as their social standing and self-concept are similar to that of observers and markedly better than those who are bullied. Early on, these young people are seen as positive leaders with a good sense of humour, high self-esteem qualities and positive early friendship qualities and popularity [ 22 , 23 ].

Nevertheless, as children grow older bullying behaviours become increasingly maladaptive. Whereas young children solve disputes by fighting, adolescents and adults prefer negotiation to solve a conflict [ 24 ]. Children who bully others often do not learn to interact and communicate in socially appropriate ways and therefore have difficulty in interacting adequately with their older peers. This often results in persistent maladaptive behavioural patterns [ 25 ], as well as representing an elevated risk for serious injury [ 26 ], alcohol dependency [ 27 ], and delinquency [ 28 ]. These findings suggest that children and adolescents who bully others, frequently also show other forms of antisocial behaviour and that some of those students show a pattern of life-course persistent antisocial behaviour [ 29 ].

Furthermore, adolescents who bully others are found to have more psychological and physical problems than their peers [ 30 ], and have an increased risk for depression and suicidal ideation [ 31 ]. Bullying research traditionally differentiates between children or adolescents who are only victims, only bullies or both [ 28 ]. Regarding potential outcomes of bullying, it has been shown that those who both bully others and are victimised (i.e. bully-victims) report the highest levels of externalizing and internalizing symptoms [ 31 , 32 ].

In sum, bullying perpetration and victimisation may have highly negative consequences for children's and adolescents' mental health and well-being. In general, bullying others is most strongly associated with externalizing problems, while being a victim of bullying is strongly associated with internalizing symptoms.

Consequences and correlates of cyber-bullying and cyber-victimisation

The existing (albeit limited) literature on cyber-bullying suggests that the consequences of cyber-bullying may be similar to traditional bullying. Cyber-bullying, like traditional bullying, correlates significantly with physical and psychological problems [ 33 ]. A large scale Australian-based bullying study also demonstrated that cyber-victimisation is associated with higher levels of stress symptoms [ 4 ]. Moreover, adolescent victims of cyber-bullying not only reported higher depressive symptoms but also that they engage in other types of problematic behaviour, such as increased alcohol consumption, a tendency to smoke and poor school grades [ 34 ]. Cross-sectional studies showed that aggressors are at increased risk for school problems, assaultive behaviours, and substance use [ 35 ]. These findings suggest that cyber-victimisation, like traditional victimisation, increases the risk of internalizing (and externalizing) problems.

However, as traditional and cyber-bullying forms are strongly associated and frequently co-occur within the same individuals [ 1 , 36 - 39 ] it is important to investigate both forms of bullying simultaneously. Few studies have systematically analysed the impact of cyber versus traditional bullying on adolescents' adjustment and mental health.

In a recent study with 761 adolescents from Austria the combined victim group (cyber and traditional victimisation) showed the highest level of internalizing problems [ 6 ]. In this study, combined bully-victims showed the most maladjusted pattern. Similarly, a Swedish study found that cyber-victimisation contributed over and above traditional victimisation to adolescents' social anxiety [ 40 ]. Cyber-victimisation is also associated with a range of negative emotions [ 41 ]. Qualitative data suggest that in comparison with traditional bullying forms, cyber-bullying evoked stronger negative feelings, fear and a clear sense of helplessness [ 42 ]. Therefore, being a victim of cyber-bullying might be even more strongly associated with depressive symptoms than traditional victimisation.

Research questions

This paper describes the relationship between traditional and cyber forms of bullying/victimisation and psychological outcomes. Several hypotheses were generated: (1) there is an overlap between traditional bullying/victimisation and cyber-bullying/victimisation; (2) traditional victims and bully-victims experience higher levels of depressive symptoms than those who bully others and non-involved students; and (3) cyber-victimisation represents an independent risk factor - over and above traditional victimisation - for higher levels of symptoms of depression.

In addition to the three main hypotheses, we examined the influence of culture on the relationship between perpetration/victimisation and outcome. Eslea and colleagues showed in a large dataset from seven different countries that victims of traditional bullying were significantly more disadvantaged on all measures (e.g., mental health, friendships) in all samples, whereas bullies did not differ consistently in all samples. The authors concluded that traditional bullying is a universal phenomenon with many negative correlates for victims and few (if any) for bullies [ 43 ]. The consequences associated with cyber-victimisation are not as well established as associations with traditional bullying/victimisation. Moreover, no cross-national comparison has been conducted regarding cyber-bullying so far. Given this, we investigated if the outcomes associated with traditional and cyber forms of bullying were similar for young people in Switzerland and Australia, i.e. we tested whether the results were replicated in both countries (Switzerland versus Australia).

Participants

Australia . Data for the Australian sample were taken from a cross-sectional study (the Cyber Friendly Schools study) to determine the prevalence of cyber-bullying behaviours in Western Australia (WA) conducted in 2008 by the Child Health Promotion Research Centre (CHPRC) at Edith Cowan University. Schools were randomly selected within strata defined by geographic location and school sector. Non-mainstream and smaller schools as well as those already involved in intervention projects conducted by the CHPRC were excluded, as were students with disabilities which prevented them from completing hard copy self-report surveys. Surveys were administered by school staff within classrooms to those students who consented to participate and for whom written consent was provided by their parents. The Australian students each received a small gift (less than a dollar in value) as thanks for participating in the study. Schools received a $50 voucher for a stationary/educational store and a report detailing study results. All students were provided with contact information for youth support agencies should they have experienced difficulties as a result of participating in the survey. The study was approved by the Edith Cowan University Human Research Ethics Committee.

To increase comparability between the two countries' data and due to different requirements for obtaining consent and subsequent low consent rates in government schools, only results from secondary non-government co-educational schools are reported below.

Relative to the schools included in these analyses, the parent consent rate was 94% with 73% of students returning completed usable questionnaires. Six percent of cases did not indicate gender on the questionnaire and are excluded from the analyses. A total of 22 participants did not indicate their age and those missing values were replaced with the mean age of their respective grade level. This sample comprised 1320 adolescents (Mean age = 13.7, SD = 0.92) from four religious-affiliated average socio-economic status schools (two metropolitan, two rural). The final sample was fairly evenly distributed between year levels (Australian Grade 8: 33.8%, Grade 9: 37.2%, Grade 10: 29.0%), by area (48.5% metropolitan) and by gender (52.8% female). Students' access to technology was high: 95% had access to the internet at home and about 92% had their own mobile phone.

Switzerland . Nineteen school classes (Grades 7 to 9 in the city of St. Gallen) participated in the study [ 44 ]. Schools and participating classrooms were selected to represent all city districts (Schulkreise) and to represent all three school types at the secondary level in Switzerland: Realschule with basic classes (low achievement level school, N = 7 classes), Sekundarschule with broader classes (average achievement level school, N = 6 classes) and Kantonschule with advanced classes (high achievement level school, N = 6 classes).

Following Swiss legislation, permission from the respective school councils to conduct the study was first obtained. Second, teachers from the selected schools volunteered. The survey procedure and the goal of the study were explained to the students who then had the opportunity to refrain from participation without negative consequences (informed oral consent). Students who did not want to participate were offered another activity during the respective school hour. Participating school classes received a voucher for books and media worth 50 Swiss Franks. Teachers and students received general feedback about the occurrence of bully/victim behaviours in their classes and an information flyer that provided contact information for students who may require help following completion of the survey.

Eight students were absent on the day of assessments and did not participate. Although no student actively refused to participate in the study, 6 questionnaires were not included in the study due to missing or incomplete information. The final study sample comprised 374 participants (53.2% female; mean age = 14.3 years, SD = 1.13). In total, 17 participants did not indicate their age and these missing values were replaced with the mean age of their respective school class. The sample was fairly evenly distributed between year levels: Swiss Grade 7: 31.8%, Grade 8: 31.8%, Grade 9: 36.6%. Half (51%) of participants reported a foreign-language or migration background, 28% spoke (Swiss) German and at least one other language at home and 23% did not speak (Swiss) German within their families. Students' access to technology was high: 97% had access to the internet at home and about 95% had their own mobile phone.

Assessment of traditional bullying and victimisation

In the following we differentiate between bullying (= perpetration) and victimisation (being a victim of bullying).

Australia . Participants reported on the frequency of traditional bullying and victimisation in the last 3 months (0 = never to 4 = most days this term). The 6 items address specific negative behaviours (was ignored/excluded; teased in nasty ways; physically hurt; frightened by what someone said they would do; hurtful rumours spread; property stolen, damaged or destroyed).

Switzerland . Participants reported on the frequency of traditional bullying and victimisation in the last 3 months (0 = never to 4 = several times a day). The 6 items were used to measure specific negative behaviours (verbal aggression, physical aggression, exclusion, indirect aggression, threat and property-related behaviours).

Both samples . Each of the 6 items described above were chosen from a larger item pool of items to make the assessments as similar as possible. Students' self-reports regarding the frequency of being a perpetrator or victim of different forms of traditional bullying were used for categorization into four mutually exclusive categories as bully-victims, victims, bullies, and non-involved students. The same cut-off was used in both samples (at least once a week on at least one item) to denote frequent bullying perpetration/victimisation.

Assessment of cyber-bullying and -victimisation

Australia . The frequency of cyber-bullying and cyber-victimisation were assessed in the same way as described for the traditional bullying (same time period and response options). Each scale encompassed 5 items (sent nasty or threatening emails, nasty messages on the Internet/to mobile phone and mean or nasty comments or pictures sent to websites/other students' mobile phones). Composite scores were calculated for the cyber-bullying behaviours by applying confirmatory factor analysis (see below).

Switzerland . Students also reported on the frequency of cyber-bullying and cyber-victimisation (same time period and response options as above). Each scale encompassed 2 items: being bullied through the use of mobile phones (calls, SMS, pictures, films); being bullied through the use of Internet (e-mail, social networking sites, chat). A mean score was computed to establish the scales.

Both samples . Due to the nature of cyber-bullying, repetition as a defining feature of this bullying behaviour may be hard to assess [ 5 ]. Therefore, no established cut-offs for being a cyber-bully or cyber-victim exist. In addition, dichotomising these scores would have led to an unnecessary loss of information with regard to various degrees of perpetration/victimisation. Thus, cyber-victimisation and cyber-bullying were analysed as linear variables. Whilst the response categories varied between the studies, this was mostly at the upper end of the scale where there were relatively few responses.

Assessment of depressive symptoms

Australia . Students completed a 14-item depression subscale of the Depression Anxiety Stress Scales (DASS) [ 45 ].

Switzerland . Students completed an 8-item scale addressing depressive symptoms. The scale has been validated in a longitudinal study [ 46 , 47 ].

Both samples . Both scales tap the same constructs: sad/depressed feelings, lack of positive feeling, lack of motivation/energy, worthlessness of life. Composite scores were calculated for the depressive symptoms by applying confirmatory factor analysis fitting a single-factor measurement model using weighted least squares estimation based on polychoric correlation matrices. This approach appropriately accounts for the skewed item distributions and measurement error in the items. To maximize data available for analyses, when 20% or less of the items were missing, values were imputed for the missing items based on observed items using the EM (expectation-maximization) algorithm prior to the factor analysis.

Data analyses

Data analyses accounted for the skew of the dependent variables through the use of tobit regressions, the data were log transformed to meet the requirement of normality of the non-censored scores as recommended by Osgood [ 48 ]. Our analyses also accounted for non-independence of the data resulting from the clustered sampling, which can lead to inflated Type I error rates, through the inclusion of a random intercept in the models. Clustering in the Australian data was by school (where secondary students within a year level move between classes for different subjects) and by class in the Swiss sample.

For the statistical analyses, a significance level of p < 0.05 was used.

Descriptive statistics

Table Table1 1 shows means and standard deviations of all study variables by sample and gender.

Descriptive statistics of all study variables


	Female	Male	Female	Male
Being a bully-victim	19 (2.8%)	27 (4.4%)	5 (2.5%)	9 (5.2%)
Being a victim	66 (9.6%)	55 (9.1%)	22 (11.1%)	24 (13.8%)
Being a bully	29 (4.2%)	70 (11.5%)	23 (11.6%)	31 (17.8%)
Cyber-bullying (range 0-4)	Mean = .14 SD = .406 Median = 0	Mean = .14 SD = .446 Median = 0	Mean = .03 SD = .152 Median = 0	Mean = .10 SD = .320 Median = 0
Cyber-victimisation (range 0-4)	Mean = .18 SD = .485 Median = 0	Mean = .12 SD = .452 Median = 0	Mean = .08 SD = .218 Median = 0	Mean = .08 SD = .289 Median = 0
Depressive symptoms (range 0-3)	Mean = .34 SD = .630 Median = .05	Mean = .35 SD = .670 Median = .04	Mean = .59 SD = .637 Median = .37	Mean = .34 SD = .449 Median = .13

a Numbers (percentages) of students within each country, (traditional bully-victim categories defined according to involvement in bullying behaviours once a week or more often in the past 3 months).

Traditional bully/victim categorization

Across both samples, students' self-reported frequency of traditional bullying perpetration/victimisation were used to categorize participants (cut-off: at least once a week): traditional victims (10.0%), bully-victim (3.6%), perpetrators (9.2%), and non-involved (77.2%). In addition, significant gender differences were found with more boys reporting they were frequently perpetrators (12.9%) than girls (5.9%), χ 2 = 31.1, N = 1666, p < .001. When country specific frequencies were examined (Table (Table1), 1 ), significantly more Swiss participants reported bullying others than did their Australian counterparts (14.5% versus 7.7%), χ 2 = 20.9, N = 1666, p < .001.

Country and gender differences regarding the other variables are reported in the multivariable analyses below.

Bivariate associations

Both types of bullying and victimisation were significantly associated with each other (see Table Table2 2 and Table Table3). 3 ). These relationships remained statistically significant (all p < .01) when examined by country, with stronger associations observed in the Australian sample. When comparing the traditional bully-victim categories, 41% of (traditional) bullies, 59% of bully-victims, 30% of victims and 16% of non-involved students reported perpetrating cyber-bullying behaviours at least once or twice. Thirty-nine percent of (traditional) victims, 50% of bully-victims, 22% of bullies and 17% of non-involved students were exposed to cyber-bullying behaviours at least once or twice. The association between bullying behaviour and mental health revealed some interesting results with depressive symptoms being most strongly correlated with traditional victimisation (Spearman's rho = .26 Australian sample, rho = .24 Swiss sample) and cyber-victimisation (rho = .22 Australian sample, rho = .12 Swiss sample).

Bivariate associations between study variables: Complete sample


Gender (female)	.00	-.04	-.13**	.09*	.01	.07**
Age	--	.00	.13**	.02	.14**	.14**
Being a victim		--	.16**	.24**	.18**	.26**
Being a bully			--	.10**	.28**	.12**
Cyber-victimisation				--	.35**	.18**
Cyber-bullying					--	.24**

Note: Spearman's rho calculated for correlations involving cyber-victimization, cyber-bullying and depressive symptoms, Pearson's correlation calculated for all others

*p < .05, **p < .01

Bivariate associations between study variables: Australian versus Swiss sample


Gender	--	.06	-.07	-.12*	.00	-.16**	.24**
Age	-.03	--	-.15**	.07	-.06	.04	.09
Being a victim	-.03	.05	--	.06	.14**	.07	.24**
Being a bully	-.14**	.13**	.20**	--	.00	.19**	.05
Cyber-victimisation	.06*	.08**	.27**	.14**	--	.35**	.12*
Cyber-bullying	.00	.06*	.21**	.32**	.46**	--	.02
Depressive symptoms	-.01	.10	.26**	.11**	.22**	.24**	--

Note: Spearman's rho calculated for correlations involving cyber-victimisation, cyber-bullying and depressive symptoms, Pearson's correlation calculated for all others

*p < .05, **p < .01 two sided tests

Overlap of bullying/victimisation forms: Multivariable analyses

Next, two tobit regression analyses were conducted to analyse differences between those who use traditional methods to bully, those who are victimised, the combined group (hereafter bully-victims for brevity) and non-involved students in terms of their tendency to cyber-bully others and be cyber-victimised (as log-transformed linear dependent variables). Age and gender and country were entered as control variables. As we were interested in whether country moderates the associations, location (i.e., Switzerland or Australia) was entered as an interaction effect in a first model.

Cyber-victimisation

The bully/victim categorization interaction effect with country was found not to be significant (χ 2 [3]= 6.3, p = .098) and was thus dropped from the model The subsequent analysis yielded significant main effects for the bully/victim categorization, gender and country (see Table Table4). 4 ). As is evidenced by the positive sign for the Z statistic, girls reported higher levels of cyber-victimisation than boys (z = 4.75, p < .001). The Australian students reported being more frequently cyber-victimised than the Swiss students (z = 4.46, p < .001). All of the traditional bully/victim behaviour categories differed significantly from each other (see also Table Table5). 5 ). Bully-victims and victims reported higher levels of cyber-victimisation than non-involved students and bullies, of these victims had lower scores on cyber-victimisation than the bully-victims. Students who indicated they bullied others by traditional means reported higher levels of being cyber-victimised than those non-involved in traditional bullying behaviours.

Results of the tobit regression predicting cyber-victimisation and cyber-bullying


	Z	Sig	Z	Sig	Z	Sig	Z	Sig
Gender - female	4.75	< .001	1.02	.307	3.14	.002	2.79	.005
Age	1.48	.138	.67	.502	3.58	< .001	3.31	.001
Country - Australia	4.46	< .001	4.11	< .001	-3.46	.001	-4.36	< .001
Trad. bully/victim behaviors
Bullies vs non-involved	2.50	.012	9.32	< .001	2.47	.014	1.86	.063
Victims vs non-involved	8.31	< .001	4.79	< .001	9.89	< .001	8.38	< .001
Bully-victims vs non-involved	8.96	< .001	10.6	< .001	8.89	< .001	5.60	< .001
Bullies vs victims	-3.83	< .001	3.64	< .001	-5.18	< .001	-4.53	< .001
Bullies vs bully-victims	-5.88	< .001	-3.48	.001	-6.18	< .001	-4.00	< .001
Victims vs bully-victims	-3.02	.002	-6.31	< .001	-2.33	.020	-0.68	.496
Cyber-victimisation							4.83	< .001
Cyber-bullying							1.52	.127

Note: Cyber-victimisation: R 2 = 14.0%; Cyber-bullying: R 2 = 16.5%; Depressive symptoms (M1): R 2 = 12.8%; Depressive symptoms (M2): R 2 = 16.1%

Summary statistics for cyber-victimisation, cyber-bullying and depressive symptoms by traditional bully/victim categorization



Bully-victims	0.86	1.309	0.86	1.174	1.09	1.040
Victims	0.37	0.716	0.14	0.328	0.79	0.894
Bullies	0.10	0.250	0.37	0.705	0.42	0.647
Non-involved	0.07	0.215	0.06	0.171	0.28	0.507

Cyber-bullying others

A non-significant interaction was also found for cyber-bullying between country and bully/victim categorization (χ 2 [3] = 4.7, p = .192) Further analysis yielded significant effects for the bully/victim categorization (with all comparisons between categories significant) and country (see Table Table4). 4 ). Those who bullied using traditional methods (bullies and bully-victims) reported higher levels of cyber-bullying than those victimised or not involved, with bully-victims reporting higher frequencies than bullies (see also Table Table5). 5 ). Additionally, the Australian students tended to report more frequently engaging in cyber-bullying behaviours than the Swiss students.

(Cyber)bullying/victimisation and depressive symptoms (multivariable analyses)

To analyse differences between traditional bullies, victims, and bully-victims in relation to depressive symptoms, the same modelling procedure as described above was used. In the first analysis, only traditional bully/victim categorization was used (including a test of the interaction with country) with age and gender entered as control variables. In the second analysis, cyber-bullying and cyber-victimisation (as well as their interactions with country) were entered as additional independent variables.

Traditional bullying/victimisation

The analysis found that the effect of bully-victim categorization was not moderated by country (χ 2 [3] = 6.0, p = .113). The interaction term was dropped from the analyses. However, bully-victim categorization was a significant predictor of depressive symptoms. In addition, significant gender and country effects emerged (see Table Table4). 4 ). Female students reported higher levels of depressive symptoms (z = 3.14, p = .002) whilst the Australian students had lower scores on average than the Swiss (z = -3.46, p = .001). When comparing the traditional bully-victim categories, all were significantly different from each other, with bully-victims having the highest levels of symptoms, followed by victims, then bullies; non-involved students had the least depressive symptoms (see also Table Table5 5 ).

Cyber-bullying/victimisation as additional risk factor

First, the interactions between each of cyber-bullying and cyber-victimisation and country were tested to assess whether their association with depressive symptoms differed in Australia and Switzerland. As neither of these interaction effects reached significance (cyber-victimisation*country: z = .39, p = .697; cyber-bullying*country: z = 1.76, p = .078), they were dropped from the final model. Upon entering cyber-bullying and cyber-victimisation as additional independent variables, the main effects of traditional bully-victim behaviours remained the same (see Table Table4), 4 ), except that the comparison between bullies and non-involved students and the comparison between victims and bully-victims were no longer significant. In addition, cyber-victimisation was a significant predictor of depressive symptoms, the more frequent the victimisation the higher the level of depressive symptoms (z = 4.83, p < .001).

This study examined the relationship between bullying and victimisation and symptoms of depression in adolescents from two different countries, Switzerland and Australia. Particular attention was paid to different forms of bullying behaviour - specifically traditional forms of bullying (including physical or verbal harassment) and cyber-bullying (using the Internet and/or mobile phone). While the association between traditional and cyber forms of bullying is established [ 49 ], to date it remains unclear if being cyber-victimised (over and above traditional victimisation) is associated with increased symptom endorsement.

Although in its relative infancy, the emergent research literature describing the outcomes associated with cyber-bullying/cyber-victimisation is largely consistent with the traditional bullying literature illustrating the robust negative relationship between all forms of bullying/victimisation and mental health. However, what has not yet been clearly described is the cumulative effect of being bullied via traditional and cyber means on the mental health of young people [ 6 ]. Thus, the third aim of this study was to investigate whether in adolescents, cyber-victimisation is an independent predictor of depressive symptoms, after accounting for self-reported traditional bullying victimisation and to determine the influence of study location (i.e., country) on this association.

Overlap between traditional and cyber-bullying/victimisation

The first hypothesis, which proposed a relationship between traditional and cyber forms of bullying and victimisation, was supported with statistically significant relationships between traditional and cyber forms of bullying perpetration and victimisation in the expected direction. Importantly, significant correlations were found between cyber-victimisation and gender (female), age, traditional bullying perpetration and victimisation. Furthermore, as participants aged, their self-reported bullying perpetration (traditional and cyber) increased, a relationship that remained significant only in the Australian sample when country-specific report was examined. Overall, all associations were stronger in the Australian sample.

These results add to the theoretical [ 5 ] and other empirical evidence [ 1 , 4 , 36 - 39 ] demonstrating the relationship between traditional and cyber forms of bullying perpetration and victimisation. In accordance with other studies, our findings suggest that traditional and cyber-bullying form part of the same cluster of socially inappropriate behaviours and argue for a behavioural versus technical approach to intervention programs.

Traditional victimisation and depressive symptoms

It was also hypothesized that those victimised using traditional methods (victims and bully-victims) would endorse more symptoms of depression than those who only reported bullying perpetration. Support for this hypothesis was found demonstrating that students who reported being victimised and bullying others as well as those only victimised were more likely to report depressive symptoms than were those who reported bullying perpetration only. This result was not moderated by country, indicating that the associations were comparable in both countries.

Cyber-victimisation and depressive symptoms

Finally, it was hypothesized that cyber-victimisation would represent an additional risk factor - independent of traditional victimisation - for the development of symptoms of depression. Strong support was found for the independent association that cyber-victimisation has with symptoms of depression over and above traditional bullying victimisation i.e. cyber-victimisation accounts for a significant amount of the variation in depressive symptoms even after controlling for possible effects of traditional victimisation. Importantly, this association was not moderated by country, which suggests that the relationship is not culturally dependent.

However, several differences between countries were found. For example, while Swiss students were more likely to report bullying others, the Australian students who bully others were more likely to report also using cyber-strategies. Despite these differences, it was demonstrated that cyber-victimisation was a significant predictor of depressive symptoms - a result that was culturally independent. This result suggests an additional negative mental health status associated with being exposed to bullying via technology, over and above that of being victimised by traditional means. Although fewer students reported being cyber-bullied via technology than traditional methods in both countries, clearly the inclusion of technology represents a risk factor for significantly higher rates of internalizing disorders for those victimised using both cyber and traditional methods.

Practical implications

The implications of these findings are important (e.g., for intervention programs) and demonstrate the scope of negative impact associated with cyber-victimisation. It is suggested that certain features of cyber-bullying (e.g., anonymity of perpetrator, accessibility of victim) present additional and difficult challenges for young people who are victimised [ 49 ]. It is often assumed that these challenges could contribute to a worsened mental health state for those victimised and the results of this study provide evidence in support of this.

Furthermore, some of the cyber-bullying strategies employed (e.g., nasty comments on SNS profiles) [ 4 ] mean that the audience potentially aware of the harassment is significantly larger. For example, if mean and nasty comments are posted on a SNS profile (social networking sites) or if an embarrassing picture is posted and the victim is identified in the picture by name (i.e., being tagged ), all people in their network, in addition to other networks, can potentially see that humiliating content. Therefore, strategies against cyber-bullying should also include educating students about privacy settings and safe internet/mobile practices. Given the difficulty in removing comments or pictures from the Internet and the permanence of information shared online, it is not surprising that cyber-victimisation represent an additional and independent risk factor for the development of depressive symptomatology. Further investigation is needed to clarify if specific elements of cyber-victimisation that are associated with poorer mental health outcomes for young people. For example, what is the impact of bullying via social networking sites given comments, pictures, and video can be viewed by a larger network (i.e., more students). Nonetheless, the results of this study raise important questions, as well as concerns, for those young people experiencing mental health issues in addition to bullying via traditional and cyber methods.

Strengths and Limitations

There were a number of strengths to this study. This was the first study to describe cultural similarities in relation to the impact of cyber-victimisation on depressive symptom endorsement. Despite some cultural differences (e.g., more Australian students reported using multiple strategies to bully (traditional and cyber) compared to Swiss students), the evidence demonstrating the additive effect of cyber-victimisation on mental health is an important result. Furthermore, the (culturally independent) predictive nature of cyber-victimisation on depressive symptoms provides an important insight into the influence of technology on young people.

Overall, there were some limitations with this study. For example, some items that assessed bullying and victimisation were worded differently between the two data collection countries. Moreover, there were certain differences in the wording of response categories and number of items in both samples. Regarding cyber-bullying/victimisation, we found a significant difference between Swiss and Australian students regarding their use of cyberstrategies to bully others (Australians reporting higher levels of cyber-bullying/victimisation). This finding has important methodological implications. Swiss students reported on two rather global items on cyber-bullying, whereas Australian students reported on five different behavioural descriptors of cyber-bullying. This might have lead to an underreporting of cyber-bullying in Swiss students. Studies in traditional bullying research have shown that global items result in lower prevalence rates of bullying than specific behavioural items [ 50 ].

Regarding depressive symptoms, it is important to know that although Australian students reported on more items than Swiss students, the same number of symptoms were assessed (i.e. the Australian students reported on two items for each symptom, Swiss students on 1-2 items). Nevertheless, we found a significant country effect on depressive symptoms. We assume that these country differences are mainly due to methodological differences. It is unlikely that the differences are culturally-based given the similarities between Switzerland and Australia in relation to the prevalence of depressive symptomatology [ 51 , 52 ].

There were some sample limitations (Swiss sample comprised students whose teachers volunteered while the Australian sample is comprised of students at religious-affiliated schools only), however, we do not anticipate that the associations examined would differ markedly from those in the general student population. Although there were some differences in sample demographics (e.g. age), these did not have an impact on the relationship between cyber-victimisation and self-reported depressive symptoms. Moreover, samples were highly similar regarding their access to technology. Other limitations concern the nature of the data collected. First, all measures were self-reports. Second, as with all cross-sectional studies the causal direction of the relationships cannot be determined, and thus our focus has been on associations between the variables involved.

In conclusion, this study provided evidence of a significant association between traditional and cyber forms of bullying behaviours. We demonstrated that, although several cultural differences exist between Swiss and Australian participants in relation to bullying and victimisation, the relationship between cyber-victimisation and increased endorsement of depression symptoms was culturally independent.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

SP and JD were responsible for the conceptual background of the paper, analyzed and interpreted the data and drafted the manuscript. TS analysed and interpreted the data. DC is grant-holder, conceived and directed the Australian study, and was actively involved in writing up the manuscript. All authors read and approved the final manuscript.

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Bullying experiences in childhood and health outcomes in adulthood

Peer bullying and Internet addiction among Chinese adolescents: a moderated mediation model

Published: 22 August 2024

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Chengkai Feng 1 ,
Zhenguo Shi 1 ,
Yuge Tian 1 &
Chao Ma 1

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This study aims to investigate the mechanism of peer bullying on adolescent Internet addiction and to verify the mediating role of loneliness and the moderating role of physical activity. The results of this study are utilized to propose theoretical references for the mitigation of adolescent Internet addiction. Adolescent peer bullying, loneliness, Internet addiction and physical activity were measured by scales. A total of 618 valid questionnaires were collected from eight primary and secondary schools in Shandong Province. Mediated and moderated modeling was performed using the PROCESS plug-in for SPSS. Peer bullying directly and positively predicted Internet addiction (β = 0.023, t = 4.412, p < 0.001). Peer bullying had a significant effect on loneliness (β = 0.022, p < 0.001), and loneliness had a significant effect on Internet addiction (β = 0.017, p < 0.001), establishing the mediating role of loneliness. Meanwhile, physical activity moderated the effect of peer bullying on loneliness (β = 0.033, p < 0.001) and loneliness on internet addiction (β = 0.026, p < 0.001), in addition to moderating the effect of peer bullying on internet addiction (β = 0.034, p < 0.001), establishing the moderating role of physical activity. Loneliness mediates the relationship between adolescent peer bullying and Internet addiction, while physical activity moderates the direct and indirect pathways of adolescent peer bullying and Internet addiction.

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How peer victimization predicts mental well-being and disruptive behaviors: exploring serial mediating mechanisms in the digital age

Peer Relationship Problems, Fear of Missing Out, Family Affective Responsiveness, and Internet Addiction among Chinese Adolescents: A Moderated Mediation Model

Correlation among psychological resilience, loneliness, and internet addiction among left-behind children in China: A cross-sectional study

Data availability.

The dataset used and analyzed during the current study are available from the corresponding author on reasonable request.

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Not Applicable.

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Bullying at school and mental health problems among adolescents: a repeated cross-sectional study

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Prevalence of bullying at school and mental health problems

Associations between bullying at school and mental health problems

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Bullying in school and cyberspace: Associations with depressive symptoms in Swiss and Australian adolescents

Julian Dooley

Thérèse Shaw

Conclusions

Consequences and correlates of peer victimisation

Consequences and correlates of bullying behaviours

Consequences and correlates of cyber-bullying and cyber-victimisation

Research questions

Participants

Assessment of traditional bullying and victimisation

Assessment of cyber-bullying and -victimisation

Assessment of depressive symptoms

Data analyses

Descriptive statistics

Traditional bully/victim categorization

Bivariate associations

Overlap of bullying/victimisation forms: Multivariable analyses

Cyber-victimisation

Cyber-bullying others

(Cyber)bullying/victimisation and depressive symptoms (multivariable analyses)

Traditional bullying/victimisation

Cyber-bullying/victimisation as additional risk factor

Overlap between traditional and cyber-bullying/victimisation

Traditional victimisation and depressive symptoms

Cyber-victimisation and depressive symptoms

Practical implications

Strengths and Limitations

Competing interests

Authors' contributions

Bullying experiences in childhood and health outcomes in adulthood

Peer bullying and Internet addiction among Chinese adolescents: a moderated mediation model

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