Due to increasing internet and mobile penetration, children in India are at risk of cyberbullying. A survey of 174 middle graders in Delhi showed that, of total, 8% indulged in cyberbullying and 17% reported being victimized by such acts. However, prevalence of in-person bullying, fighting and victimization by either was 16%, 12% and 17% respectively. Males were more likely to bully and fight in-person than females. They were also more likely to be victims of both online and offline aggression. Interwoven modes of bullying along with safe use of technology need to be understood.

Background

Violence has far broader health consequences than death and injuries ( Hemphill et al., 2011 ). Still, children are exposed every day to violence in their homes, schools and communities causing significant physical, mental, and emotional harm with long-term effects lasting well into adulthood ( Finkelhor et al., 2009 ). Aggressive behaviors like verbal violence and kicking, hitting etc. have been found precursors to more serious forms of violence (Moffitt, 1993 ). Such peer mediated interpersonal violence or bullying is common in schools.

India showed an impressive growth in active internet users against the global average (90% vs 19%, 2015–16) (Kemp, 2016 ). Presently, 35% of Indian population has internet access with 12% having active social media accounts led by Facebook with one-tenth users being 13–17 years old ( Kemp, 2016 ).

This transformed landscape of children's social lives includes Internet bullying as a new and growing form of social cruelty. It allows children and youth to say and do things with a certain degree of anonymity and limited oversight by adult monitors ( William and Guerra, 2007 ).

The world over, studies on electronic aggression suggest that 9–35% of young people are victims, 4–21% perpetrators, with 7–14% both ( David-Ferdon and Hertz, 2009 ). Females prefer online bullying ( Li, 2006;Marcum et al., 2012a,b;[3] ).

Researchers have also looked at the risk and protective factors for electronic aggression and its effects on victims. Like traditional forms of youth violence, it is associated with emotional distress and conduct problems at school (Mitchell et al., 2011 ). The victims tend to use alcohol and other drugs, receive school detention/suspension, skip school, and experience in-person victimization. Those who experience cyberbullying (bullies or victims) are likelier to have suicidal thoughts ( Hinduja and Patchin, 2010;Time Staff, 2016;O'Keefee and Clarke-Pearson, 2011 ). Given the rapid increase in Internet and mobile penetration, children in India are equally at risk.

Given the scarcity of studies in this area, we undertook the present study to assess the prevalence of cyber-bullying and its relation with in-person bullying and thus tried to fill this knowledge gap.

Methods

We conducted a cross-sectional study in English-medium public schools located in Central district of New Delhi on students of 8th standard (aged 11–15 years) who completed a self-report survey during July–Sept 2013.

With estimated prevalence of ‘victimization by cyber violence’ at 9%, absolute precision 5% and 95% confidence interval, the sample size came out to be 125. Considering non-response, we studied a bigger sample (n = 200) (Venkataraghavan, 2015 ).

The study adhered to the guidelines of the Declaration of Helsinki. Written informed consent of the parents and school administration and assent from the students was sought before the study. Approval was obtained from the Institutional Ethical Committee of Maulana Azad Medical College. The participants filled questionnaires in the presence of researchers; queries were answered as they appeared.

2.1

Measures

We used a self-administered, pre-tested questionnaire about socio-demographic information, violence parameters and electronic aggression.

2.1.1

Face-to-face violence

Illinois bully scale is an 18-item scale with 3 sub-scales measuring frequency of bullying behaviour (perpetration of emotional violence), fighting (perpetration of physical violence), and victimization (by both physical and emotional means of violence), over past 30 days ( Hamburger et al., 2011 ).

2.1.2

Electronic aggression

Cyber Harassment Student survey, a 15-item measure, assesses respondents' awareness of cyber-harassment, their experience with cyber-harassment as both the victim and perpetrator and the emotional/behavioural impact of being cyber-harassed ( Hamburger et al., 2011 ).

2.2

Statistical analysis

Difference between sub-groups was assessed using Wilcoxon rank sum test. To explore the relationships among the various experiences of bullying, Spearman’s rho coefficients for ordinal data were calculated. Chi-square test was used to analyze difference between sub-groups for nominal variables.

Interventions on Bullying and Cyberbullying in Schools: A Systematic Review

Elisa Cantone ,1,* Anna P Piras ,1 Marcello Vellante,1 Antonello Preti ,1 Sigrun Daníelsdóttir,2 Ernesto D’Aloja ,1 Sigita Lesinskiene ,3 Mathhias C Angermeyer,1,4 Mauro G Carta ,2 and Dinesh Bhugra5

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Abstract

Background : bullying (and cyberbullying) is a widespread phenomenon among young people and it is used to describe interpersonal relationships characterized by an imbalance of power. In this relationships often show aggressive behavior and intentional "harm doing" repeated over time. The prevalence of bullying among youth has been reported to vary widely among countries (5.1%-41.4%) and this behavior seems generally higher among student boys than girls. Several school interventions have been developed to reduce bullying, but reported inconsistent results possibly related to limitations in the study design or to other methodological shortcomings. Aims : evaluating randomized-controlled trials (RTCs) conducted between 2000 and 2013 to assess the effectiveness of school interventions on bullying and cyberbullying. Methods : a systematic search of the scientific literature was conducted on Pubmed/Medline and Ebsco online databases. We also contacted experts in the field of preventive bullying research. Results : 17 studies met the inclusion criteria. The majority of studies did not show positive effects in the long term; the interventions focused on the whole school were more effective in reducing bullying than interventions delivered through classroom curricula or social skills training alone. Conclusion : while there is evidence that programs aimed at reducing bullying can be effective in the short term, their long-term effectiveness has not been established, and there are important differences in the results based on gender, age and socio-economic status of participants. Internal inconsistency in the findings of some studies, together with the wide variability of experimental designs and lack of common standardized measures in outcome evaluation, are important limitations in this field of research.

Keywords: Bullying, cyber bullying, randomized controlled trials, school

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INTRODUCTION

Bullying is a significant problem in schools [ 1 ]. It is defined as intentional aggressive behaviour by a single person or a group against a peer who cannot easily defend himself/herself. Its nature is repetitive over time, lasting weeks and, at times, even months or years. Bullying can take on the following forms: physical (punching or kicking, seizing or damaging other people's belongings); verbal (ridiculing, insulting, repeatedly mocking someone, making racist remarks); relational (leaving one or more peers out of aggregation groups) and indirect (spreading rumours or gossip about a student) [ 2 ].

In recent years, as a result of the widespread use of smart phones and Internet access among youth, another phenomenon has surfaced: cyberbullying. Cyberbullying is characterized by the use of electronic forms of contact (e.g., phone calls, text messages, picture/video clips, e-mails, chat rooms, instant messaging, websites) [ 3 ], that allow the perpetrator toremain anonymous and intensify feelings of discomfort in the victim [ 4 ]. Cyberbullying can take on the following forms: flaming (online fights using electronic messages with angry and vulgar language); harassment (repeatedly sending mean, insulting messages); cyberstalking (repeated, intense harassment and denigration that includes threats or creates significant fear); denigration (spreading rumours online; sending or posting gossip about a person to damage his/her reputation or friendships); impersonation (pretending to be someone else and sending or posting material to get that person in trouble or danger, or damage that person’s reputation or friendships); outing (sharing someone’s secrets or embarrassing information or images online); trickery (tricking someone into revealing secrets or embarrassing information, then sharing it online); and exclusion (intentionally and cruelly excluding someone from an online group) [ 5 ].

Three main roles have been identified within the bullying cycle: the bully, the victim, and bystanders [ 6 ]. Usually the bully is the strongest among peers and has a strong need for power. In fact, the main purpose of bullying behaviours is to undermine the social status of the victim and his/her sense of personal security, while at the same time raising the bully's self-esteem and social status. As a consequence, bullying actions usually take place in front of an audience. Bystanders can support the bully, defend the victim, or serve as passive onlookers. In the majority of cases bystanders attend without intervening but still they are considered an integral part of the bullying situation. The victims are of lower status than their aggressors and tend to isolate themselves due to bullying appearing unable to defend themselves and in need of protection.

The school has been identified as a context where bullying behaviours frequently occur [ 1 ]. Sometimes persecution also occurs on the way to and from school but cyber-bullying, by definition, can occur anywhere. Finally, the prevalence of victimization and bullying changes in different age groups. Dake and collaborators [ 7 ] have shown that the incidence of victimization and bullying in primary school (grades 1-5) is higher than in middle (grades 6-8) and secondary school (grades 9-12). While, as mentioned in the report of Ttofi [ 8 ], the incidence of bullying is more prevalent among males versus female.

Research also indicates that being the victim of bullying contributes independently to children's mental health problems [ 9 ]. The persistence of the phenomenon for prolonged periods of time may cause the development of low self esteem and depressive symptoms that can persist into adulthood [ 2 , 10 ]. Bullying victims have reported various forms of psychological, physical and social suffering, such as sleep disturbances, enuresis, abdominal pain, headache, self-destructive behaviour, feeling sad, and feeling socially rejected or isolated [ 11 - 13 ]. They experience greater social marginalization and lower social status and the effects of the bullying experience appear to last over time [ 14 ]. In fact, along with their bullies, victims have a significantly amplified risk of anxiety, depressive symptoms and suicidal ideation than children who are not bullied or bully [ 15 , 16 ]. A recent meta-analysis [ 17 ] has confirmed the strong correlation between being bullied and psychosomatic disorders in adolescents and children. Bullies are also more frequently involved in delinquency and substance abuse than other children and adolescents. Studies in school settings reported that victims showed problems of adjustment and bonding as well as difficulties in the completion of homework, while bullies showed increased school absenteeism [ 18 ].

Thus, it seems particularly important in this context to analyse how the different variables involved in the process of victimization and bullying influence each other, and to take into account that some studies have only looked at bullying and victimization outcomes, while others have also assessed associated mental health and social outcomes. We also consider it relevant to understand how many treatments were able to reduce the principal components of bullying (bullying, victimization and bystanders behaviour).

To our knowledge, only few prior systematic reviews have been conducted on school-based interventions to reduce bullying [ 19 , 10 ]. These reviews though included several kinds of study and experimental design, making it difficult to compare and evaluate the outcomes. This work tries to avoid some of these difficulties by selecting RCT designs only. Finally, this work is part of a collection of reviews on several aspects of children’s and adolescents’ well-being. They concern, for example, the promotion of health and well-being in schools through focused intervention programs [ 20 ], the development of physical activity interventions within schools to support and improve general mental health [ 21 ], and the expansion of school-based programs targeting children with mental disorders [ 22 ].

Taking the above into consideration, the objective of this specific study is to systematically review the international research in this field and critically analyze the results of school-based interventions to reduce or prevent bullying and cyber-bullying.

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METHODOLOGY

Bullying is of interest to researchers and clinicians as those who are bullied can develop problems later on in life, thus that public mental health perspective and interventions become important for a greater understanding of the phenomenon. The work group made a first search of all the studies available on the theme in an online medical database (PubMed/Medline) with some highly comprehensive keywords (“school”, “mental health”, “education context”) in the time interval of 2000-2013. From over 17,000 items, and after double-blind selection on title and abstract, 1051 papers were selected concerning actions or promotion programs. Most actions focused on the promotion of general or psychological well-being, on the management of emotions or the identification of mental health needs, the prevention of conduct disorders, the prevention of school dropout or improvement in academic performance.

Considering the extent of the results, we focused on the specific topic of bullying and cyberbullying. We expanded the systematic research using more specific keywords (“bullying”, “cyberbullying”, “school based”) always in the time interval from 2000 to 2013 in an online medical database (PubMed/Medline) and, specifically, in an online psychological and social database (Ebsco). Additionally, we contacted the experts in the field of action and preventive bullying research and asked them whether they knew about relevant studies not published in peer-reviewed journals or other relevant literature.

This search yielded 2058 articles; 2020 were excluded because they were present in both databases or were described as quasi-experimental study designs. We also considered it relevant to confine the study design to experimental research and we selected Randomized Control Trial (RCT).

The decision to include only RCT studies limits the effect selection and helps to determine the effectiveness and the repetitiveness of the actions.

Subject recruitment for school-based interventions can be done on several levels in randomized controlled trials, but we did not make further selections based on this criterion. Additionally, we used another criterion to analyze the selected documents: the focus of the study had to be on the operative and preventive school interventions against bullying and cyberbullying. The language used to describe the work and papers’ translations and transcriptions into English were also taken into account. Each article was analyzed to determine the study method, the intervention components, the measured outcomes, and the results.

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RESULTS

We conducted a systematic review of 17 studies that met the inclusion criteria. The selection steps are illustrated in the flow diagram in Fig. ( 11 ). Overall, the studies are distributed globally with a prevalence in extra-European countries: 8 studies on the efficacy of anti-bullying intervention programs took place in the USA and 3 were conducted in Australia. The remaining 6 took place in Europe and, as shown in Table 11 , in Northern countries mostly.

Associations between Cyberbullying and School Bullying Victimization and Suicidal Ideation, Plans and Attempts among Canadian Schoolchildren

Sampasa-Kanyinga, Hugues; Roumeliotis, Paul; Xu, Hao. PLoS One; San Francisco Vol. 9, Iss. 7, (Jul 2014): e102145. DOI:10.1371/journal.pone.0102145

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Abstract

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Purpose

The negative effects of peer aggression on mental health are key issues for public health. The purpose of this study was to examine the associations between cyberbullying and school bullying victimization with suicidal ideation, plans and attempts among middle and high school students, and to test whether these relationships were mediated by reports of depression.

Methods

Data for this study are from the 2011 Eastern Ontario Youth Risk Behaviour Survey, which is a cross-sectional regional school-based survey that was conducted among students in selected Grade 7 to 12 classes (1658 girls, 1341 boys; mean±SD age: 14.3±1.8 years).

Results

Victims of cyberbullying and school bullying incurred a significantly higher risk of suicidal ideation (cyberbullying: crude odds ratio, 95% confidence interval = 3.31, 2.16–5.07; school bullying: 3.48, 2.48–4.89), plans (cyberbullying: 2.79, 1.63–4.77; school bullying: 2.76, 2.20–3.45) and attempts (cyberbullying: 1.73, 1.26–2.38; school bullying: 1.64, 1.18–2.27) compared to those who had not encountered such threats. Results were similar when adjusting for sociodemographic characteristics, substance use, and sedentary activities. Mediation analyses indicated that depression fully mediated the relationship between cyberbullying victimization and each of the outcomes of suicidal ideation, plans and attempts. Depression also fully mediated the relationship between school bullying victimization and suicide attempts, but partially mediated the relationship between school bullying victimization and both suicidal ideation and plans.

Conclusion

These findings support an association between both cyberbullying and school bullying victimization and risk of suicidal ideation, plans and attempts. The mediating role of depression on these links justifies the need for addressing depression among victims of both forms of bullying to prevent the risk of subsequent suicidal behaviours.

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About the Authors:

Hugues Sampasa-Kanyinga

* E-mail: [email protected]

Affiliation: Eastern Ontario Health Unit, Cornwall, Ontario, Canada

Paul Roumeliotis

Affiliations Eastern Ontario Health Unit, Cornwall, Ontario, Canada, Department of Pediatrics, McGill University, Montreal, Quebec, Canada

Hao Xu

Affiliation: Eastern Ontario Health Unit, Cornwall, Ontario, Canada

Introduction

Suicide is a significant public health problem worldwide. It is the second leading cause of death for Canadian youth aged 10–24. Each year, on average, 294 youths die from suicide [1]. A recent report indicated that Eastern Ontario has a suicide attempt rate two times greater than the provincial average (6.78 vs. 2.96 per 1,000) [2]. Females aged 15 to 19 years in Eastern Ontario have a 50 per cent higher rate of suicide than the rest of the province. These alarming data support the crucial need for research data to understand the determinants of suicide and suicidal behaviour among children and adolescents. Experience of bullying victimization is one of many possible determinants of suicidal ideation and suicide-related behaviours.

Bullying – an aggressive behaviour that is intentional, repeated, and involves a power imbalance [3] – is a major public health concern. Despite the efforts of schools to prevent or stop bullying, bullying is still highly prevalent worldwide [4], [5]. Information and communication technology (ICT) has emerged as a recent vehicle for peer aggression worldwide. Cyberbullying has been defined as the use of email, cell phones, text messages, and Internet sites to threaten, harass, embarrass, or socially exclude [6], [7]. That is, cyberbullying provides to perpetrators the benefit of lack of face-to-face contact. It is more pervasive than traditional bullying, as it can happen anytime and anywhere. Consequently, bullying which usually takes place in school is now also occurring at home [8], [9], [10]. Among features that may distinguish cyberbullying from traditional bullying, the anonymity afforded to perpetrators and the limitless potential audience consisting of bystanders and observers are even more redoubtable [8], [11]. The inability for victims to have any control over acts of cyberbullying may result in feelings of powerlessness in the person being bullied [12]. As a result, the damage experienced in cyberbullying may be largely social and emotional in nature and is exacerbated by the intensity of the threats inflicted [12].

The growing number of cyberbullying victims over the past decade and the deleterious effects of cyberbullying on victims are of great concern. Several studies have shown that traditional bullying among youths is associated with depression, suicidal ideation and non-fatal suicidal behaviour [13], [14]. However, the psychological outcomes of cyberbullying remain inconsistent and unclear, probably because of its recent development. While some authors think that the consequences of cyberbullying tend to parallel those of traditional bullying [4], [11], others believe that cyberbullying may be even more psychologically distressing than regular school bullying [12]. An emerging body of research has begun to identify an association between cyberbullying and mental health problems. Several correlates have been identified among victims of cyberbullying, such as increased depression, suicidal ideation, and non-fatal suicidal behaviour (suicide attempts) [4], [15], [16].

The psychological mechanisms underlying the association between bullying victimization and suicidal ideation and suicide-related behaviours are less well understood. According to Agnew's social psychological strain theory of deviance, strained social relationships and events pressure individuals into committing deviant acts [17]. Bullying is known to be a source of strain [18], [19]. It makes victims feel angry and frustrated, therefore putting them more at risk to engage in deviant behaviours. From this, it can be reasoned that bullying victims are at an increased risk of suicidal ideation, plans and attempts as coping responses to their victimization. Since depression is a well known risk factor for suicidal behaviour [20], it may therefore be accounted for in these causal chains as victims may first endure episodes of depression before progressing to suicidal ideation, plans and attempts (Figure 1). Based on the nature and intensity of threats and individual vulnerability of the victim, cyberbullying and school bullying may directly result in suicidal ideation, plans and attempts (Path C, Figure 1).

[Figure omitted. See PDF.]

Figure 1. Mediational model for study of the relationship between cyberbullying and school bullying victimization and suicidal ideation, plans and attempts.

https://doi.org/10.1371/journal.pone.0102145.g001

Bauman et al. [21] have recently documented the mediating role of depression on the association between bullying victimization and suicide attempts among American high school student girls using data from the 2009 Youth Risk Behaviour Survey (YRBS). However, their analyses were not adjusted for covariates and potential confounders reported in the literature to be associated with experience of bullying victimization and/or report of suicide attempts such as substance use [20], [22], [23], sedentary activities [24], and also importantly the amount of time spent on a computer [25], inasmuch as the experience of cyberbullying depends, at least in part, on the use of Internet. Thus, the independent effects (direct or indirect pathways) of bullying victimization on suicidal ideation and non-fatal suicidal behaviour controlling for other risks behaviours are not clear.

The purpose of the current study was to (1) examine the association between cyberbullying and school bullying victimization with suicidal ideation, plans and attempts among middle and high school students, as well as (2) test whether the presence of depression mediates these associations. We hypothesized that cyberbullying and school bullying victimization results in higher likelihood of suicidal ideation, plans and attempts, and that depression would mediate these relationships, while controlling for sociodemographic variables, substance use, sedentary activities, and the amount of time spent on the computer.

Methods

The Eastern Ontario Youth Risk Behavior Survey (YRBS) is a regional cross-sectional school-based survey that has been conducted by the Eastern Ontario Health Unit (EOHU) for several years, and this paper uses the most recent data that was collected between November 2010 and March 2011 [26]. The survey was modeled after the Centers for Disease Control's (CDC) YRBS which monitors health-risk behaviours that contribute to death and disability among youths and adults [27].

Ethical Statement

The study was approved by the Queen's University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board. Signed consent forms from school principals and parents were verified prior to administering survey questionnaires.

Participants

Youths in Grades 7 to 12 were the target population of the survey. Thus, all four school boards of the region were invited to join in the survey, and all schools within the boards that accepted the invitation were eligible for participation. Of 79 existing middle and high schools falling under EOHU jurisdiction in 2010, a total of 49 schools (62%) participated in the survey. This group of participating schools did not significantly differ from those that did not participate in the survey with respect to geographical location, school board (Catholic versus Public) or school type (middle versus high).

For each school that participated, a list of classes taking place during a certain time of the day was generated. The chosen time period varied by school and staff schedule. A random sample of two classes from each grade was selected in each school, unless only one grade was available for survey administration to all students who consented to participate. In this way, all students in Grades 7 to 12 had the same opportunity to be selected for participation and were not at risk of being selected to participate twice. The only exception was that students who had a spare period during the selected time slot were not eligible for participation. In the event of a teacher's refusal to participate, a second class for that grade was selected from the same time period. Students in selected classes were eligible to participate voluntarily and anonymously. The student response rate was 68%, for a total of 3,509 students aged 11 to 20 years (14.5±1.8 years), with 54.9% females. A School Liaison (Public Health Nurse or Health Educator Promoter) remained in the classroom while students responded to the survey to address questionnaire-related issues. If students did not understand a question, the Liaison would re-read the question without leading them in any particular direction.

Measures

Bullying.

Students were asked about school bullying and cyberbullying victimization in the past 12 months. The subject was introduced as follows: “The next questions are about bullying. Bullying is when one or more students tease, threaten, spread rumors about, hit, shove, or hurt another student over and over again. It is not bullying when two students of about the same strength or power argue or fight or tease each other in a friendly way.” School bullying and cyberbullying victimization were measured by the following questions: “During the past 12 months, have you ever been bullied or threatened by someone while on school property?” and “During the past 12 months, have you ever experienced cyberbullying, that is, being bullied by email, text messaging, instant messaging, social networking or another website?” Responses included “Yes” (coded as 1) or “No” (coded as 0).

Mental health.

Items measuring mental health variables including depression, suicidal ideation, plans and attempts were taken from the Standard High School questionnaires of the CDC 2009 YRBS [27]. All yes-no response options were coded 1 for “Yes” and 0 for “No”. Depression was assessed by the following question: “During the past 12 months, did you ever feel so sad or hopeless almost every day for 2 weeks or more in a row that you stopped doing some usual activities?” (Yes or No). Suicidal ideation, plans and attempts were measured by the following questions, asked of all students: (1) “During the past 12 months, did you ever seriously consider attempting suicide?” (Yes or No); (2) “During the past 12 months, did you make a plan about how you would attempt suicide?” (Yes or No); and (3) “If you attempted suicide during the past 12 months, did any attempt result in injury, poisoning, or overdose that had to be treated by a doctor or nurse?” Response options included “I did not attempt suicide during the past 12 months” (coded as 0), Yes (equates to “attempted suicide that required medical attention”; coded as 1) or No (equates to “attempted suicide that did not require medical attention”; coded as 1). Combination of yes and no responses equates to “attempted suicide” (coded as 1).

Covariables.

Demographic variables included age, sex (coded as 1 for girls and 0 for boys), and grade.Tobacco and alcohol use were measured by the following questions: “Have you ever smoked a whole cigarette?” and “Have you ever had at least one drink of alcohol, other than a few sips?” Responses included “Yes” (coded as 1) or “No” (coded as 0). Marijuana use was measured by two items: “During your life, how many times have you used marijuana?” Response options included: “0 times”, “1 to 2 times”, “3 to 5 times”, “6 to 9 times”, “10 to 19 times”, “20 or more times”. 0 times was coded 0 and rest of options were combined and coded “1”. Participants who responded having used marijuana at least once (coded as 1) answered to the following question: “what kind of marijuana user do you consider yourself?” Response options included: “A regular marijuana user” (coded as 1), “an occasional marijuana user” (coded as 2), “a non-user (but ever tried) (coded as 3). Sedentary activities were assessed by four items. In a typical day, how much time do you usually spend (1) using a computer, including playing computer games and using the Internet? (2) Playing video games, such as XBOX, Nintendo and/or PlayStation? (3) Watching television or movies? (4) Reading (not counting reading at school or at work)? For each item, participants were asked to provide an average number of hours and/or minutes spent per day.

Three categories were generated including: “less than 1 hour per day” (coded as 0), “one to three hours per day” (coded as 1) and “more than three hours per day” (coded as 2).

Statistical analysis

Statistical analyses were conducted on individuals with no missing values for any of the variables studied. Of the 3509 students, 2999 (85.5% of the sample) were included in the analyses. With-and-without analyses showed that excluded missing data from the analyses did not have significant impact on the results. All data were analyzed with STATA (version 12.0, Stata Corp., College Station, Texas) using the svy commands to take account of the complex sampling design in variance estimates. Descriptive statistics on socio-demographic and risk behaviour correlates were calculated and stratified by cyberbullying and school bullying victimization status. Chi-square tests of significance were used to identify bivariate relationships between these characteristics and report of bullying victimization. There were no significant sex-by-cyberbullying victimization and sex-by-school bullying victimization interactions for any of the outcome variables of suicidal ideation, plans or attempts. As a result, all analyses were combined in order to maximize statistical power. Univariate and multivariate logistic regression analysis were performed to determine the associations between cyberbullying and school bullying victimization and each of the three outcomes of suicidal ideation, plans and attempts. Potential confounders included in the analysis were grade, gender, smoking, sedentary activities (including playing video games, such as XBOX, Nintendo and/or PlayStation, watching television or movies, and reading, not counting reading at school or at work), alcohol consumption, marijuana use, and the amount of time spent on the computer. All crude and adjusted odds ratios and 95% confidence interval (CI) are presented.

The mediating role of depression on the associations of bullying victimization (cyberbullying and school bullying) with suicidal ideation, plans and attempts was examined using the Baron and Kenny's approach [28] via a series of multivariate logistic models adjusted for grade, gender, smoking, sedentary activities, alcohol consumption, marijuana use, and time usually spent on the computer. The conditions necessary to demonstrate such a mediating relationship require: (1) a significant relationship between the independent (bullying victimization) and the dependent (suicidal ideation, plans and attempts) variables (Path C); (2) a significant association between independent (bullying victimization) and presumed mediator (depression) (Path A); (3) a significant association between presumed mediator (depression) and dependent (suicidal ideation, plans and attempts) variables (Path B). In the fourth and final regression model (4), after controlling the mediator (depression), the previously significant relationship between independent (bullying victimization) and dependent (suicidal ideation, plans and attempts) variables decreased or became non-significant. The Sobel test was used to statistically evaluate whether the indirect effect of bullying victimization on suicidal ideation, plans and attempts through depression was significant [29].

Results

Table 1 reports the distribution of socio-demographic data and risk behaviour correlates for the whole sample and among cyberbullying and school bullying victims. Of the 2999 participants included in the analyses, 55.3% were female, and students in lower grades were oversampled. A total of 17.4% of students were victims of cyberbullying and 25.2% were victims of school bullying. There was a significant difference in the gender ratio of cyberbullying victims. Girls were twice as likely (22.3% vs. 11.4%, p<0.001) to experience cyberbullying victimization as boys (data not shown). Students who were in lower grades were more likely to be victims of school bullying. Participants who reported spending a lot of time on the computer or in other sedentary activities reported cyberbullying victimization more often than those who used computers for less time or spent less time in sedentary activities.

[Figure omitted. See PDF.]

Table 1. Sample Characteristics.

https://doi.org/10.1371/journal.pone.0102145.t001

Table 2 presents the prevalence of suicidal ideation and suicide-related behaviours. Overall, the prevalence of suicidal ideation, plans and attempts was 10.5%, 10.7%, and 10.9%, respectively. Girls were more likely to report suicidal ideation and plan than boys. Among ideators, the conditional probability of making a plan was 64.6% and attempt was 49.7%. The probability of making an attempt among ideators with a plan was 58.3%, and 33.9% in ideators with no plan.

[Figure omitted. See PDF.]

Table 2. Prevalence of suicidal ideation and suicide-related behaviour among Canadian middle and high school students.

https://doi.org/10.1371/journal.pone.0102145.t002

Association between bullying victimization and suicidal behaviour

Table 3 presents the crude associations between cyberbullying and school bullying victimization and suicidal ideation, plans and attempts. Victims of cyberbullying and school bullying incurred a significantly higher risk of suicidal ideation (cyberbullying: crude odds ratio, 95% confidence interval = 3.31, 2.16–5.07; school bullying: 3.48, 2.48–4.89), plans (cyberbullying: 2.79, 1.63–4.77; school bullying: 2.76, 2.20–3.45) and attempts (cyberbullying: 1.73, 1.26–2.38; school bullying: 1.64, 1.18–2.27) compared to those who had not encountered such threats. Results were similar after controlling for grade, gender, sedentary activities, smoking, alcohol consumption, marijuana use, and the amount of time spent on a the computer (Table 4).

[Figure omitted. See PDF.]

Table 3. Associations between cyberbullying and school bullying victimization and suicidal ideation, plans and attempts.

https://doi.org/10.1371/journal.pone.0102145.t003

[Figure omitted. See PDF.]

Table 4. Results of the mediational analyses on the relationship between cyberbullying and school bullying victimization and suicidal ideation, plans and attempts.

https://doi.org/10.1371/journal.pone.0102145.t004

Mediation analysis

A series of multivariate logistic regression analyses were conducted and the results are summarized in Table 3. The regression coefficients of the three paths among the independent variables (cyberbullying victimization or school bullying), presumed mediator (depression), and each of the dependent variables (suicidal ideation, plans and attempts) were all significant. Entering depression into the equation of cyberbullying victimization rendered the main effect nonsignificant for all suicidal ideation, plans and attempts, whereas only the main effect of school bullying victimization on suicide attempts was rendered nonsignificant after controlling for depression.

Baron and Kenny's approach revealed therefore that the effects of cyberbullying victimization on suicidal ideation, plans and attempts were fully mediated by depression, and that depression also fully mediated the relationship between school bullying victimization and suicide attempts, but partially mediated the relationship between school bullying victimization and both suicidal ideation and plans. The Sobel test further showed evidence of the mediating role of depression in the relationship between cyberbullying and school bullying victimization and each of the suicidal ideation, plans and attempts outcomes among schoolchildren (p<0.001).

Discussion

This regional school-based survey provided supporting evidence for the association among cyberbullying and school bullying victimization, suicidal ideation, plans and attempts among Canadian middle and high school students. Mediation analysis further indicated that depression fully mediated the relationship between cyberbullying victimization and each of the outcomes of suicidal ideation, plans and attempts. Depression also fully mediated the relationship between school bullying victimization and suicide attempts, but partially mediated the relationship between school bullying victimization and both suicidal ideation and plans. These findings corroborate and extend those from previous cross-sectional studies [4], [15], [16], and indicate that cyberbullying and school bullying victims are at risk of psychological distress, suicidal ideation and non-fatal suicidal behaviour. This evidence also supports the fact that bullying-related psychological distress and suicidal behaviour are associated with both online and off-line bullying victimization [4], [11]. However, since cyberbullying is an emerging phenomenon, lack of youth's awareness and psychological preparedness to deal with such issues might increase their vulnerability. Mishna et al. [30] reported a significant lack of knowledge regarding Internet safety among youths. Enhancing awareness among schoolchildren is therefore a crucial step towards preventing cyberbullying victimization. This could be tackled by parents and schools discussing Internet safety and cyberbullying with children. On the other hand, there is a need to strengthen ongoing bullying prevention to make school environment a safe and happy place.

The prevalence of bullying and cyberbullying in high school: a 2011 survey Abstract Background: Bullying is common among young students, and cyberbullying has increased due to the use of technology. This study investigates the prevalence of bullying and cyberbullying among high school students and the emotional effects of bullying on students. Methods: Students at East Chapel Hill High School, Chapel Hill, North Carolina completed the Gatehouse Bullying Scale and the Peer Relations Questionnaire. They answered questions regarding how often they had experienced certain types of bullying in school and the emotional effects the bullying had on them. Results: The combined results from both surveys indicated that the prevalence of bullying was 55% with 18% of respondents reporting cyberbullying. Teasing and name-calling were the most common types of bullying, as 40% of students reported having been teased or called names. The most serious type of bullying, being threatened with harm, hit, or kicked, occurred in 20% of boys and 8% of girls, with 25% of respondents reported “quite upset” by the experience. The majority (79%) of students who had been bullied did not share with anyone about being bullied, and of those who did, only 50% were taken seriously. Conclusions: Bullying is still prevalent among high school students, and cyberbullying is becoming more widespread. Most victims do not share their bullying experience, and if they did, only half believe they are taken seriously. Both bullying among students in school and cyberbullying deserve attention due to their potentially devastating effects on victims. Keywords: bullying; child and adolescent health; cyberbullying; emotional health; schools. *Corresponding author: Sophie S. Gan, East Chapel Hill High School, 500 Weaver Dairy Road, Chapel Hill, NC 27514, USA, E-mail: [email protected] Connie Zhong, Shreya Das, Julia S. Gan and Eileen Tully: East Chapel Hill High School, Chapel Hill, NC, USA Stephanie Willis: Chapel Hill-Carrboro City Schools, Chapel Hill, NC, USA Introduction Bullying is common among young people in school (1–3) and is becoming increasingly prevalent. With the widespread use of the Internet, cell phones, and instant messaging (4), cyberbullying has recently emerged as a threat among students. Bullying involves the display of power and aggression over time by a bully to harm a target, who is a less dominant person than the bully (5–7). Actions that are considered bullying include physical aggression such as hitting, kicking, or threatening and other actions such as name-calling, teasing (but excluding giving dirty looks), or spreading rumors (8). As it is difficult to measure bullying because there is no commonly accepted definition (9–13), and young students and researchers may have different opinions regarding what defines bullying (9, 14), the true incidence of bullying has been difficult to ascertain. In addition, different survey instruments used in research studies made it difficult to compare results across the studies. A 2008 study of bullying in middle schools indicated that 45.1% of middle school students have been bullied and that 81.6% of students felt that bullying was a problem at their schools (15). Gossiping and rumors were the most common type of bullying among middle school students, as 60.7% reported that this type of bullying occurs all the time (15). Kowalski and Limber (16), in a 2007 study, found a 7% incidence of cyberbullying. A study performed in 2006 indicated that cyberbullying has increased 50% among preteens within the last 5 years (4). However, there is a paucity of more recent data if the incidence of bullying and cyberbullying has changed. In this study, we investigate the prevalence of bullying among high school students and examine how frequently certain types of bullying occur. We also examine the effects of bullying on students, the extent of cyberbullying that occurs in high school, and the emotional effects of cyberbullying on the victims.