research title bullying in school

• Research article
• Open access
• 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 ].

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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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The open science movement has developed out of growing concerns over the scientific standard of published academic research and a perception that science is in crisis (the “replication crisis”). Bullying research sits within this scientific family and without taking a full part in discussions risks falling behind. Open science practices can inform and support a range of research goals while increasing the transparency and trustworthiness of the research process. In this paper, we aim to explain the relevance of open science for bullying research and discuss some of the questionable research practices which challenge the replicability and integrity of research. We also consider how open science practices can be of benefit to research on school bullying. In doing so, we discuss how open science practices, such as pre-registration, can benefit a range of methodologies including quantitative and qualitative research and studies employing a participatory research methods approach. To support researchers in adopting more open practices, we also highlight a range of relevant resources and set out a series of recommendations to the bullying research community.

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Bullying in school is a common experience for many children and adolescents. Such experiences relate to a range of adverse outcomes, including poor mental health, poorer academic achievement, and anti-social behaviour (Gini et al., 2018 ; Nakamoto & Schwartz, 2010 ; Valdebenito et al., 2017 ). Bullying research has increased substantially over the past 60 years, with over 5000 articles published between 2010 and 2016 alone (Volk et al., 2017 ). Much of this research focuses on the prevalence and antecedents of bullying, correlates of bullying, and the development and evaluation of anti-bullying interventions (Volk et al., 2017 ). The outcomes of this work for children and young people can therefore be life changing, and researchers should strive to ensure that their work is trustworthy, reliable, and accessible to a wide range of stakeholders both inside and outside of academia.

In recent years, the replication crisis has led to growing concern regarding the standard of research practices in the social sciences (Munafò et al., 2017 ). To address this, open science practices, such as openly sharing publications and data, conducting replication studies, and the pre-registration of research protocols, have provided the opportunity to increase the transparency and trustworthiness of the research process. In this paper, we aim to discuss the replication crisis and highlight the risks that questionable research practices pose for bullying research. We also aim to summarise open science practices and outline how these can benefit the broad spectrum of bullying research as well as to researchers themselves. Specifically, we aim to highlight how such practices can benefit both quantitative and qualitative research and studies employing a participatory research methods approach.

The Replication Crisis

In 2015, the Open Science Collaboration (Open Science Collaboration, 2015 ) conducted a large-scale replication of 100 published studies from three journals. The results questioned the replicability of research findings in psychology. In the original 100 studies, 97 reported a significant effect compared to only 35 of the replications. Furthermore, the effect sizes reported in the original studies were typically much larger than those found in the replications. The findings of the Open Science Collaboration received significant academic and mainstream media attention, which concluded that psychological research is in crisis (Wiggins & Chrisopherson, 2019 ). While these findings are based on the analysis of psychological research, challenges in replicating research findings have been reported in a range of disciplines including sociology (Freese & Peterson, 2017 ) and education studies (Makel & Pluker, 2014 ). Shrout and Rodgers ( 2018 ) suggest that the notion that science is in crisis is further supported by (1) the number of serious cases of academic misconduct such as that of Diederick Stapel (Nelson et al., 2018 ) and (2) the prevalence of questionable research practices and misuse of inferential statistics and hypothesis testing (see Ioannidis, 2005 ). The replication crisis has called into question the degree to which research across the social sciences accurately describes the world that we live in or whether this literature is overwhelmingly populated by misleading claims based on weak and error-strewn findings.

The trustworthiness of research reflects the quality of the method, rigour of the design, and the extent to which results are reliable and valid (Cook et al., 2018 ). Research on school bullying has grown exponentially in recent years (Smith & Berkkun, 2020 ) and typically focuses on understanding the nature, prevalence, and consequences of bullying to inform prevention and intervention efforts. If our research is not trustworthy, this can impede theory development and call into question the reliability of our research and meta-analytic findings (Friese & Frankenbach, 2020 ). Ultimately, if our research findings are untrustworthy, this undermines our efforts to prevent bullying and help and support young people. Bullying research exists within a broader academic research culture, which facilitates and incentivises the ways that research is undertaken and shared. As such, the issues that have been identified have direct relevance to those working in bullying.

The Incentive Culture in Academia

“The relentless drive for research excellence has created a culture in modern science that cares exclusively about what is achieved and not about how it is achieved.”

Jeremy Farrar, Director of the Wellcome Trust (Farrar, 2019 ).

In academia, career progression is closely tied to publication record. As such, academics feel under considerable pressure to publish frequently in high-quality journals to advance their careers (Grimes et al., 2018 ; Munafò et al., 2017 ). Yet, the publication process itself is biased toward accepting novel or statistically significant findings for publication (Renkewitz & Heene, 2019 ). This bias fuels a perception that non-significant results will not be published (the “file drawer problem”: Rosenthal, 1979 ). This can result in researchers employing a range of questionable research practices to achieve a statistically significant finding in order to increase the likelihood that a study will be accepted for publication. Taken together, this can lead to a perverse “scientific process” where achieving statistical significance is more important than the quality of the research itself (Frankenhuis & Nettle, 2018 ).

Questionable Research Practices

Questionable research practices (QRPs) can occur at all stages of the research process (Munafò et al., 2017 ). These practices differ from research misconduct in that they do not typically involve the deliberate intent to deceive or engage in fraudulent research practices (Stricker & Günther, 2019 ). Instead, QRPs are characterised by misrepresentation, inaccuracy, and bias (Steneck, 2006 ). All are of direct relevance to the work of scholars in the bullying field since each weakens our ability to achieve meaningful change for children and young people. QRPs emerge directly from “researcher degrees of freedom” that occur at all stages of the research process and which simply reflect the many decisions that researchers make with regard to their hypotheses, methodological design, data analyses, and reporting of results (see Wicherts et al., 2016 for an extensive list of researcher degrees of freedom). These decisions pose fundamental threats to how robust a study is as each compromises the likelihood that findings accurately model a psychological or social process (Munafò et al., 2017 ). QRPs include p -hacking; hypothesising after the result is known (HARKing); conducting studies with low statistical power; and the misuse of p values (Chambers et al., 2014 ). Such QRPs may reflect a misunderstanding of inferential statistics (Sijtsma, 2016 ). A misunderstanding of statistical theory can also lead to a lack of awareness regarding the nature and impact of QRPs (Sijtsma, 2016 ). This includes the prevailing approach to quantitative data analysis, Null Hypothesis Significance Testing (NHST) (Lyu et al., 2018 ; Travers et al., 2017 ), which is overwhelmingly the approach used in the bullying field. QRPs can fundamentally threaten the degree to which research in bullying can be trusted, replicated, and effective in efforts to implement successful and impactful intervention or prevention programs.

P -hacking (or data-dredging) reflects methods of re-analysing data in different ways to find a significant result (Raj et al., 2018 ). Such methods can include the selective deletion of outliers, selectively controlling for variables, recoding variables in different ways, or selectively reporting the results of structural equation models (Simonsohn et al., 2014 ). While there are various methods of p -hacking, the end goal is the same: to find a significant result in a data set, often when initial analyses fail to do so (Friese & Frankenbach, 2020 ).

There are no available data on the degree to which p -hacking is a problem in bullying research per se, but the nature of the methods commonly used mean it is a clear and present danger. For example, the inclusion of multiple outcome measures (allowing those with the “best” results to be cherry-picked for publication), measures of involvement in bullying that can be scored or analysed in multiple ways (e.g. as a continuous measure or as a method to categorise participants as involved or not), and the presence of a diverse selection of demographic variables (which can be selectively included or excluded from analyses) all provide researchers with an array of possible analytic approaches. Such options pose a risk for p -hacking as decisions can be made on the results of statistical fishing (i.e. hunting to find significant effects) rather than on any underpinning theoretical rationale.

P -hacking need not be driven by a desire to deceive; rather, it can be used by well-meaning researchers and their wish to honestly identify useful or interesting findings (Wicherts et al., 2016 ). Sadly, even in this case, the impact of p- hacking remains profoundly problematic for the field. The p- hacking process biases the literature towards erroneous significant results and inflated effect sizes, impacting on our understanding of any issue that we seek to understand better, and biasing effect size estimates reported in meta-analyses (Friese & Frankenbach, 2020 ). While such effects may seem remote or of only academic interest, they compromise all that we in the bullying field seek to accomplish because they make it much less likely that effective, impactful, and meaningful intervention and prevention strategies can be identified and implemented.

Typically, quantitative research follows the hypothetico-deductive model (Popper, 1959 ). From this perspective, hypotheses are formulated based on appropriate theory and previous research (Rubin, 2017 ). Once written, the study is designed, and data are collected and analysed (Rubin, 2017 ). Hypothesising after the result is known, or HARKing (Kerr, 1998 ), occurs when researchers amend their hypotheses to reflect their completed data analysis (Kerr, 1998 ). HARKing results in confusion between confirmatory and exploratory data analysis (Shrout & Rodgers, 2018 ), creating a literature where hypotheses are always confirmed and never falsified. This inhibits theory development (Rubin, 2017 ) in part because “progress” is, in fact, the accumulation of type 1 errors.

Low Statistical Power

Statistical power reflects the power in a statistical test to find an effect if there is one to find (Cohen, 2013 ). There are concerns regarding the sample sizes used in bullying research, as experiences of bullying are typically of a low frequency and positively skewed (Vessey et al., 2014 ; Volk et al., 2017 ). Low statistical power is problematic in two ways. First, it increases the type II error rate (the probability of falsely rejecting the null hypothesis), meaning that researchers may fail to report important and meaningful effects. Statistically significant effects can still be found under the conditions of low statistical power; however, the size of these effects is likely to be exaggerated due to a lower positive predictive value (the probability of a statistically significant result being genuine) (Button et al., 2013 ). In this case, researchers may find significant effects even in small samples, but those effects are at risk of being inflated.

QRPs in Qualitative Research

Apart from the previously discussed issues, there are also QRPs in qualitative work. Mainly, these involve issues pertaining to trustworthiness such as credibility, transferability, dependability, and confirmability (See Shenton, 2004 ). One factor that can influence perceptions about qualitative work is the possibility of subjectivity or different interpretations of the same data (Haven & Van Grootel, 2019 ). Additionally, the idea that the researcher will be biased and that their experiences, beliefs, and personal history will all influence how they both collect and interpret data has also been discussed (Berger, 2015 ). Clearly stating the positionality of the researcher and how their experiences informed their current research (the process of reflexivity) can help others better understand their interpretation of the data (Berger, 2015 ). Finally, one decision that qualitative researchers should consider when thinking about their designs is their stopping criteria. This might imply code or meaning saturation (see Hennink et al., 2017 , for more detail on how these two types are different from one another). Thus, making it clear in the conceptualisation process when and how the data collection will stop is important to assure transparency and high-quality research. This is not a complete list of QRPs in qualitative research, but these seem to be the most urgent when it comes to bullying research when thinking about open science.

The Prevalence and Impact of QRPs

Identifying the prevalence of QRPs and academic misconduct is challenging as this is reliant on self-reports. In their survey of 2155 psychologists, John et al. ( 2012 ) identified that 78% of participants had not reported all dependent measures, 72% had collected more data after finding their statistical effects were not statistically significant, 67% reported selective reporting of studies that “worked” (yielded a significant effect), and 9% reported falsifying data. Such problematic practices have serious implications for the reliability of effects reported in the research literature (John et al., 2012 ), which can impact interventions and treatments such evidence may inform. Furthermore, De Vries et al. ( 2018 ) have highlighted how biases in the publication process threaten the validity of treatment results reported in the literature. Although focused on the treatment of depression, their work has clear lessons for the bullying research community. They demonstrate how the bias towards reporting more positive, significant effects, distorts a literature in favour of treatments that appear efficacious but are much less so in practice (Box 1 ).

Box 1 The Replication Crisis

Munafò et al. ( 2017 ) outline a manifesto for reproducible research, highlighting problems with current research practices.

Shrout and Rodgers  ( 2018 ) provide an overview of the replication crisis and questionable research practices.

Steneck ( 2006 ) provides a detailed overview of definitions of academic misconduct, questionable research practices, and academic integrity.

Open Science

Confronting these challenges can be daunting, but open science offers several strategies that researchers in the bullying field can use to increase the transparency, reproducibility, and openness of their research. The most common practices include openly sharing publications and data, encouraging replication, pre-registration, and open peer-review. Below, we provide an overview of open science practices, with a particular focus on pre-registration and replication studies. We recommend that researchers begin by using those practices that they can most easily integrate into their work, building their repertoire of open science actions over time. We provide a series of recommendations for the school bullying research community alongside summaries of useful supporting resources (Box 2 ).

Box 2 Key Reading on Open Science

Banks et al. ( 2019 ) discuss frequently asked questions about open science providing a good overview of open science practices and contemporary debates.

Crüwell et al. ( 2019 ) provide an annotated reading list on important papers in open science.

Gehlbach and Robinson ( 2021 ) in their introduction to a special edition of the journal Educational Psychologist they discuss the adoption of open science practices in the context of what they term “old school” research practices.

Lindsay ( 2020 ) outlines a series of steps researchers can take to integrate open science practices into their research.

Open Publication, Open Data, and Reporting Standards

Open publication.

Ensuring research publications are openly available by providing access to pre-print versions of papers or paying for publishers to make articles openly available is now a widely adopted practice (Concannon et al., 2019 ; McKiernan et al., 2016 ). Articles can be hosted on websites such as ResearchGate and/or on institutional repositories, allowing a wider pool of potential stakeholders to access relevant bullying research and increasing the impact of research (Concannon et al., 2019 ). This process also supports access for the research and practice communities in low- and middle-income countries where even Universities may be unable to pay journal subscriptions. The authors can also share pre-print versions of their papers for comment and review before submitting them to a journal for review using an online digital repository, such as PsyArXiv. Sharing publications in this way can encourage both early feedback on articles and the faster dissemination of research findings (Chiarelli et al., 2019 ).

Making data and data analysis scripts openly available is also encouraged, can enable further data analysis (e.g. meta-analysis), and facilitates replication (Munafò et al., 2017 ; Nosek & Bar-Anan, 2012 ). It also enables the collation of larger data sets, and secondary data analyses to test different hypotheses. Several publications on bullying in school are based on the secondary analysis of openly shared data (e.g. Dantchev & Wolke, 2019 ; Przybylski & Bowes, 2017 ) and highlight the benefits of such analyses. Furthermore, although limited in number, examples of papers on school bullying where data, research materials, and data analysis scripts are openly shared are emerging (e.g. Przybylski, 2019 ).

Bullying data often includes detailed personal accounts of experiences and the impact of bullying. Such data are highly sensitive, and there may be a risk that individuals can be identified. To address such sensitivities, Meyer ( 2018 ) (see box 3 ) proposes a tiered approach to the consent process, where participants are actively involved in decisions around what parts of their data and where their data are shared. Meyer ( 2018 ) also highlights the importance of selecting the right repository for your data. Some repositories are entirely open, whereas others only provide access to suitably qualified researchers. While bullying data pose particular ethical challenges, the sharing of all data is encouraged (Bishop, 2009 ; McLeod & O’Connor, 2020 ).

Reporting Standards

Reporting standards are standards for reporting a research study and provide useful guidance on what methodological and analytical information should be included in a research paper (Munafò et al., 2017 ). Such guidelines aim to ensure sufficient information is provided to enable replication and promote transparency (Munafò et al., 2017 ). Journal publishers are now beginning to outline what open science practices should be reported in articles. For example, from July 2021, when submitting a paper for review in one of the American Psychological Association journals, the authors are now required to state whether their data will be openly shared and whether or not their study was pre-registered. In a bullying context, Smith and Berkkun ( 2020 ) have highlighted that important contextual data is often missing from publications and recommend, for example, that the gender and age of participants alongside the country and date of data collection should be included as standard in papers on bullying in school.

Recommendations:

Researchers to start to share all research materials openly using an online repository. Box 3 provides some useful guidance on how to support the open sharing of research materials.

Journal editors and publishers to further promote the open sharing of research material.

Researchers to follow the recommendations set out by Smith and Berkkun ( 2020 ) and follow a set of reporting standards when reporting bullying studies.

Reviewers be mindful of Smith and Berkkun ( 2020 ) recommendations when reviewing bullying papers.

Box 3 Useful Resources on Openly Sharing Research Materials & Reporting Standards

Banks et al. ( 2019 ) provide a helpful overview of open science practices, alongside a set of recommendations for ensuring research is more open.

Meyer ( 2018 ) provides some useful guidance on managing the ethical issues of openly sharing data.

The Equator Network ( https://www.equator-network.org/reporting-guidelines/ ) is a useful resource for the sharing of different reporting standards, for example, the PRISMA guidelines for systematic reviews and STROBE standards for observational studies.

The Foster website is an online e-learning portal with a wealth of resources to help researchers develop open science practices https://www.fosteropenscience.eu/ , including sharing resources and pre-prints.

The Open Science Framework has resources to support open science practices and to use their platform https://www.cos.io/products/osf .

Smith and Berkkun ( 2020 ) provide a review of contextual information reported in bullying research papers and offer recommendations on what information to include.

The PsyArXiv https://psyarxiv.com and SocArXiv https://osf.io/preprints/socarxiv repositories accept pre-print publications in psychology and sociology.

Replication Studies

Replicated findings increase confidence in the reliability of that finding, ensuring research findings are robust and enabling science to self-correct (Cook et al., 2018 ; Drotar, 2010 ). Replication reflects the ability of a researcher to duplicate the results of a prior study with new data (Goodman et al., 2018 ). There are different forms of replication that can be broadly categorised into two: those that aim to recreate the exact conditions of an earlier study (exact/direct replication) and those that aim to test the same hypotheses again using a different method (conceptual replication) (Schmidt, 2009 ). Replication studies are considered fundamental in establishing whether study findings are consistent and trustworthy (Cook et al., 2018 ).

To date, few replication studies have been conducted on bullying in schools. A Web of Science search using the Boolean search term bully* alongside the search term “replication” identified two replication studies (Berdondini & Smith, 1996 ; Huitsing et al., 2020 ). Such a small number of replications may reflect concerns regarding the value of these and concerns about how to conduct such work when data collection is so time and resource-intensive. In addition, school gatekeepers are themselves interested in novelty and addressing their own problems and may be reluctant to participate in a study which has “already been done”. One possible solution to this challenge is to increase the number of large-scale collaborations among bullying researchers (e.g. multiple researchers across many sites collecting the same data). Munafò et al. ( 2017 ) highlight the benefits of collaboration and “team science” to build capacity in a research project. They argue that greater collaboration through team science would enable researchers to undertake higher-powered studies and relieve the pressure on single researchers. Such projects also have the benefit of increasing generalisability across settings and populations.

Undertake direct replications or, as a more manageable first step, include aspects of replication within larger studies.

Journal editors to actively promote the submission of replication studies on school bullying.

Journal editors, editorial panels, and reviewers to recognise the value of replication studies rather than favouring new or novel findings (Box 4 ).

Box 4 Useful Resources on Replication Studies

Brandt et al. ( 2014 ) provide a useful step by step guide on conducting replication studies, including a registration template form for pre-registering a replication study (available here: https://osf.io/4jd46/ ).

Coyne et al. ( 2016 ) discuss the benefits of replication to research in educational research (with a particular focus on special education).

Duncan et al. ( 2014 ) discuss the benefits of replication to research in developmental psychology.

Pre-Registration

Pre-registration requires researchers to set out, in advance of any data collection, their hypotheses, research design, and planned data analysis (van’t Veer & Giner-Sorolla, 2016 ). Pre-registering a study reduces the number of researcher degrees of freedom as all decisions are outlined at the start of a project. However, to date, there have been few pre-registered studies in bullying. There are two forms of pre-registration: the pre-registration of analysis plans and registered reports. In a pre-registered analysis plan, the hypotheses, research design, and analysis plan are registered in advance. These plans are then stored in an online repository (e.g. the Open Science Framework (OSF) or AsPredicted website), which is then time-stamped as a record of the planned research project (van’t Veer & Giner-Sorolla, 2016 ). Registered reports, however, integrate the pre-registration of methods and analyses into the publication process (Chambers et al., 2014 ). With a registered report, researchers can submit their introduction and proposed methods and analyses to a journal for peer review. This creates a two-tier peer-review process, where the registered reports can be accepted in principle or rejected in the first stage of review, based on the rigour of the proposed methods and analysis plans rather than on the findings of the study (Hardwicke & Ioannidis, 2018 ). In the second stage of the review process, the authors then submit the complete paper (at a later date after data have been collected and analyses completed), and this is also reviewed. The decision to accept a study is therefore explicitly based on the quality of the research process rather than the outcome (Frankenhuis & Nettle, 2018 ) and in practice, almost no work is ever rejected following an in-principal acceptance at stage 1 (C. Chambers, personal communication, December 11, 2020). At the time of writing, over 270 journals accept registered reports, many of which are directly relevant to bullying researchers (e.g. Developmental Science, British Journal of Educational Psychology, Journal of Educational Psychology).

Pre-registration offers one approach for improving the validity of bullying research. Employing greater use of pre-registration would complement other recommendations on how to improve research practices in bullying research. For example, Volk et al. ( 2017 ) propose a “bullying research checklist” (see Box 5 ).

Box 5 Volk et al. ( 2017 ) Bullying Research Checklist ( reproduced with permission )

State and justify your chosen definition of bullying.

Outline the theoretical logic underlying your hypotheses and how it pertains to your chosen definition and program of research/intervention.

Use one's logic model and theoretical predictions to determine which kind of measurements are most appropriate for testing one's hypotheses. There is no gold standard measure of bullying, but be aware of the strengths and weaknesses of the different types of measures. Where possible, use complementary forms of measurement and reporters to offset any weaknesses.

Implement an appropriate research or intervention design (longitudinal if possible) and recruit an appropriate sample.

Reflect upon the final product, its associations with the chosen logic model and theory, and explicitly discuss important pertinent limitations with a particular emphasis on issues concerning the theoretical validity of one's findings.

Volk et al.’s ( 2017 ) checklist highlights the importance of setting out in advance the definition of bullying, alongside the theoretical underpinnings for the hypotheses.

Pre-Registering Quantitative Studies

The pre-registration of quantitative studies requires researchers to state the hypotheses, method, and planned data analysis in advance of any data collection (van’t Veer & Giner-Sorolla, 2016 ). When outlining the hypotheses being tested, researchers are required to outline the background and theoretical underpinning of the study. This reflects the importance of theoretically led hypotheses (van’t Veer & Giner-Sorolla, 2016 ), which are more appropriately tested using NHST and inferential statistics in a confirmatory rather than exploratory design (Wagenmakers et al., 2012 ). Requiring researchers to state their hypotheses in advance of any data collection adheres to the confirmatory nature of inferential statistics and reduces the risk of HARKing (van’t Veer & Giner-Sorolla, 2016 ). Following a description of the hypotheses, researchers outline the details of the planned method, including the design of the study, the sample, the materials and measures, and the procedure. Information on the nature of the study and how materials and measures will be used and scored are outlined in full. Researchers are required to provide a justification for and an indication of the desired sample size.

The final stage of the pre-registration process requires researchers to consider and detail all steps of the data analysis process. The data analysis plan should be outlined in terms of what hypotheses are tested using what analyses and any plans for follow-up analysis (e.g. post hoc testing and any exploratory analyses). Despite concerns to the contrary (Banks et al., 2019 ; Gonzales & Cunningham, 2015 ), the aim of pre-registration is not to devalue exploratory research, but rather, to make more explicit what is exploratory and what is confirmatory (van’t Veer & Giner-Sorolla, 2016 ). While initially, the guidance on pre-registration focused more on confirmatory analyses, more recent guidance considers how researchers can pre-register exploratory studies (Dirnagl, 2020 ), and make a distinction between confirmatory versus exploratory research in the publication process (McIntosh, 2017 ). Irrespective of whether confirmatory or exploratory analyses are planned, pre-registering an analysis reduces the risk of p -hacking (van’t Veer & Giner-Sorolla, 2016 ). A final point, often a concern to those unfamiliar with open science practices, is that a pre-registration does not bind a researcher to a single way of analysing data. Changes to plans are entirely acceptable when they are deemed necessary and are described transparently.

Pre-Registering Qualitative Studies

Pre-registration of qualitative studies is still relatively new (e.g. Kern & Gleditsch, 2017a , b ; Piñeiro & Rosenblatt, 2016 ). This is because most of the work uses inductive and hypothesis-generating approaches. Coffman and Niederle ( 2015 ) argue that this hypothesis-generation is one of the most important reasons why pre-registering qualitative work is so important. This could help distinguish between what hypotheses are generated from the data and which were hypotheses conceptualised from the start. Therefore, it could even be argued that pre-registering qualitative research encourages exploratory work. Using pre-registration prior to a hypothesis-generating study will also help with the internal validity of this same study, as it will be possible to have a sense of how the research evolved from before to post data collection.

Using investigator triangulation, where multiple researchers share and discuss conclusions and findings of the data, and reach a common understanding, could improve the trustworthiness of a qualitative study (Carter et al., 2014 ). Similarly, where establishing intercoder reliability is appropriate, the procedures demonstrating how this is achieved can be communicated and recorded in advance. One example of this would be the use of code books. When analysing qualitative data, developing a code book that could be used by all the coders could help with intercoder reliability and overall trustworthiness (Guest et al., 2012 ). These are elements that could be considered in the pre-registration process by clearly outlining if intercoder reliability is used and, if so, how this is done. To improve the transparency of pre-registered qualitative work, it has also been suggested that researchers should clearly state whether, if something outside the scope of the interview comes to light, such novel experiences will also be explored with the participant (Haven & Van Grootel, 2019 ; Kern & Gleditsch, 2017a , b ). Issues of subjectivity, sometimes inherent to qualitative work, can be reduced as a result of pre-registering because it allows the researcher to clearly consider all the elements of the study and have a plan before data collection and analysis, which reduces levels of subjectivity.

Kern and Gleditsch ( 2017a , b ) provide some practical suggestions on how to use pre-registration with qualitative studies. For example, when using in-depth interviews, one should make the interview schedule and questions available to help others to comprehend what the participants were asked. Similarly, they suggest that all recruitment and sampling strategy plans should be included to improve transparency (Haven & Van Grootel, 2019 ; Kern & Gleditsch, 2017a , b ). Piñeiro and Rosenblatt ( 2016 ) provide an overview of how these pre-registrations could be achieved. They suggested three main elements: conceptualisation of the study, theory (inductive or deductive in nature), and design (working hypothesis, sampling, tools for data collection). More recently, Haven and Van Grootel ( 2019 ) highlighted a lack of flexibility in the existing pre-register templates to adapt to qualitative work, as such, they adapted an OSF template to a qualitative study.

Integrating Participatory Research Methods into Pre-Registration

Participatory research methods (PRMs) aim to address power imbalances within the research process and validate the local expertise and knowledge of marginalised groups (Morris, 2002 ). The key objective of PRM is to include individuals from the target population, also referred to as “local experts”, as meaningful partners and co-creators of knowledge. A scoping review of PRM in psychology recommends wider and more effective use (Levac et al., 2019 ). Researchers are calling specifically for youth involvement in bullying studies to offer their insight, avoid adult speculation, and assist in the development of appropriate support materials (O’Brien, 2019 ; O’Brien & Dadswell, 2020 ). PRM is particularly appropriate for research with children and young people who experience bullying behaviours given their explicit, defined powerlessness. Research has shown that engaging young people in bullying research, while relatively uncommon, provides lasting positive outcomes for both researchers and participants (Gibson et al., 2015 ; Lorion, 2004 ).

Pre-registration has rarely been used in research undertaking a PRM approach. It is a common misconception that pre-registration is inflexible and places constraints on the participant-driven nature of PRM (Frankenhuis & Nettle, 2018 ). However, pre-registration still allows for the exploratory and subjective nature of PRM but in a more transparent way, with clear rationale and reasoning. An appropriate pre-registration method for PRM can utilise a combination of both theoretical and iterative pre-registration. Using a pre-registration template, researchers should aim to document the research process highlighting the main contributing theoretical underpinnings of their research, with anticipatory hypotheses and complementary analyses (Haven & Van Grootel, 2019 ). This initial pre-registration can then be supported using iterative documentation detailing ongoing project development. This can include utilising workflow tools or online notebooks, which show insights into the procedure of co-researchers and collaborative decision making (Kern & Gleditsch, 2017a , b ). This creates an evidence trail of how the research evolved, providing transparency, reflexivity, and credibility to the research process.

The Perceived Challenges of Pre-Registration.

To date, there have been few pre-registered studies in bullying. A Web of Science search using the Boolean search terms bully* peer-vict*, pre-reg*, and preregist* identified four pre-registered studies on school bullying (Kaufman et al., 2022 ; Legate et al., 2019 ; Leung, 2021 ; Noret et al., 2021 ). The lack of pre-registrations may reflect concerns that it is a difficult, rigid, and time-consuming process. Reischer and Cowan ( 2020 ) note that pre-registration should not be seen as a singular time-stamped rigid plan but as an ongoing working model with modifications. Change is possible so long as this is clearly and transparently articulated, for example, in an associated publication or in an open lab notebook (Schapira et al., 2019 ). The move to pre-registering a study requires a change in workflow rather than more absolute work. However, this early and detailed planning (especially concerning analytical procedures) can improve the focus on the quality of the research process (Ioannidis, 2008 ; Munafò et al., 2017 ).

The Impact of Pre-Registration.

The impact of pre-registration on reported effects can be extensive. The pre-registration of funded clinical trials in medicine has been a requirement since 2000. In an analysis of randomised control trials examining the role of drugs or supplements for intervening in or treating cardiovascular disease, Kaplan and Irvin ( 2015 ) identified a substantial change in the number of significant effects reported once pre-registration was introduced (57% reported significant effects prior to the requirement but and only 8% after). More recently, Scheel et al. ( 2021 ) compared the results of 71 pre-registered studies in psychology with the results published in 152 studies that were not pre-registered. They found that only 44% of the pre-registered studies reported a significant effect, compared to 96% of studies that were not pre-registered. As a result, the introduction of pre-registration has increased the number of null effects reported in the literature and presents a more reliable picture of the effects of particular interventions.

When conducting your next research study on bullying, consider pre-registering the study.

Journal editors and publishers to actively encourage registered reports as a submission format.

The Benefits of Open Science for Researchers

Employing more open science practices can often be challenging, in part because they force us to reconsider methods that are already “successful” (often synonymous with “those which result in publication”). Based on our own experience, this takes time and is best approached by beginning small and building up to a wider application of the practices we have outlined in this article. Alongside increasing the reliability of research, open science practices are associated with several career benefits for the researcher. Articles which use open science practices are more likely to be accepted for publication, are more visible, and are cited more frequently (Allen & Mehler, 2019 ). Open science can also lead to the development of more supportive networks for collaboration (Allen & Mehler, 2019 ). In terms of career advancement, Universities are beginning to reward engagement with science principals in their promotion criteria. For example, the University of Bristol (UK) will consider open research practices such as data sharing and pre-registration in promotion cases in 2020–21. Given that formal recognition such as this has been recommended by the European Union for some time (O’Carroll et al., 2017 ), it is likely to be an increasingly important part of career progression in academia (Box 6 ).

Box 6 Pre-Registration

van't Veer and Giner-Sorolla ( 2016 ) provide a clear overview of the pre-registration process and provide a template for the pre-registration of studies.

Center for Open Science YouTube channel https://www.youtube.com/watch?v=PboPpcg6ik4 includes several webinars on pre-registration and the replication crisis. The OSF website also includes a number of pre-registration templates for researchers to use https://osf.io/zab38/wiki/home/?view , and provide a list of journals that accept registered reports https://www.cos.io/initiatives/registered-reports

Haven and Van Grootel ( 2019 ) review the issues around pre-registering of qualitative work and adapted an existing pre-registering OSF template to suit these types of studies.

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Noret, N., Hunter, S.C., Pimenta, S. et al. Open Science: Recommendations for Research on School Bullying. Int Journal of Bullying Prevention 5 , 319–330 (2023). https://doi.org/10.1007/s42380-022-00130-0

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Preventing Bullying Through Science, Policy, and Practice (2016)

Chapter: 1 introduction, 1 introduction.

Bullying, long tolerated by many as a rite of passage into adulthood, is now recognized as a major and preventable public health problem, one that can have long-lasting consequences ( McDougall and Vaillancourt, 2015 ; Wolke and Lereya, 2015 ). Those consequences—for those who are bullied, for the perpetrators of bullying, and for witnesses who are present during a bullying event—include poor school performance, anxiety, depression, and future delinquent and aggressive behavior. Federal, state, and local governments have responded by adopting laws and implementing programs to prevent bullying and deal with its consequences. However, many of these responses have been undertaken with little attention to what is known about bullying and its effects. Even the definition of bullying varies among both researchers and lawmakers, though it generally includes physical and verbal behavior, behavior leading to social isolation, and behavior that uses digital communications technology (cyberbullying). This report adopts the term “bullying behavior,” which is frequently used in the research field, to cover all of these behaviors.

Bullying behavior is evident as early as preschool, although it peaks during the middle school years ( Currie et al., 2012 ; Vaillancourt et al., 2010 ). It can occur in diverse social settings, including classrooms, school gyms and cafeterias, on school buses, and online. Bullying behavior affects not only the children and youth who are bullied, who bully, and who are both bullied and bully others but also bystanders to bullying incidents. Given the myriad situations in which bullying can occur and the many people who may be involved, identifying effective prevention programs and policies is challenging, and it is unlikely that any one approach will be ap-

propriate in all situations. Commonly used bullying prevention approaches include policies regarding acceptable behavior in schools and behavioral interventions to promote positive cultural norms.

STUDY CHARGE

Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, a group of federal agencies and private foundations asked the National Academies of Sciences, Engineering, and Medicine to undertake a study of what is known and what needs to be known to further the field of preventing bullying behavior. The Committee on the Biological and Psychosocial Effects of Peer Victimization:

Lessons for Bullying Prevention was created to carry out this task under the Academies’ Board on Children, Youth, and Families and the Committee on Law and Justice. The study received financial support from the Centers for Disease Control and Prevention (CDC), the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the Health Resources and Services Administration, the Highmark Foundation, the National Institute of Justice, the Robert Wood Johnson Foundation, Semi J. and Ruth W. Begun Foundation, and the Substance Abuse and Mental Health Services Administration. The full statement of task for the committee is presented in Box 1-1 .

Although the committee acknowledges the importance of this topic as it pertains to all children in the United States and in U.S. territories, this report focuses on the 50 states and the District of Columbia. Also, while the committee acknowledges that bullying behavior occurs in the school

environment for youth in foster care, in juvenile justice facilities, and in other residential treatment facilities, this report does not address bullying behavior in those environments because it is beyond the study charge.

CONTEXT FOR THE STUDY

This section of the report highlights relevant work in the field and, later in the chapter under “The Committee’s Approach,” presents the conceptual framework and corresponding definitions of terms that the committee has adopted.

Historical Context

Bullying behavior was first characterized in the scientific literature as part of the childhood experience more than 100 years ago in “Teasing and Bullying,” published in the Pedagogical Seminary ( Burk, 1897 ). The author described bullying behavior, attempted to delineate causes and cures for the tormenting of others, and called for additional research ( Koo, 2007 ). Nearly a century later, Dan Olweus, a Swedish research professor of psychology in Norway, conducted an intensive study on bullying ( Olweus, 1978 ). The efforts of Olweus brought awareness to the issue and motivated other professionals to conduct their own research, thereby expanding and contributing to knowledge of bullying behavior. Since Olweus’s early work, research on bullying has steadily increased (see Farrington and Ttofi, 2009 ; Hymel and Swearer, 2015 ).

Over the past few decades, venues where bullying behavior occurs have expanded with the advent of the Internet, chat rooms, instant messaging, social media, and other forms of digital electronic communication. These modes of communication have provided a new communal avenue for bullying. While the media reports linking bullying to suicide suggest a causal relationship, the available research suggests that there are often multiple factors that contribute to a youth’s suicide-related ideology and behavior. Several studies, however, have demonstrated an association between bullying involvement and suicide-related ideology and behavior (see, e.g., Holt et al., 2015 ; Kim and Leventhal, 2008 ; Sourander, 2010 ; van Geel et al., 2014 ).

In 2013, the Health Resources and Services Administration of the U.S. Department of Health and Human Services requested that the Institute of Medicine 1 and the National Research Council convene an ad hoc planning committee to plan and conduct a 2-day public workshop to highlight relevant information and knowledge that could inform a multidisciplinary

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1 Prior to 2015, the National Academy of Medicine was known as the Institute of Medicine.

road map on next steps for the field of bullying prevention. Content areas that were explored during the April 2014 workshop included the identification of conceptual models and interventions that have proven effective in decreasing bullying and the antecedents to bullying while increasing protective factors that mitigate the negative health impact of bullying. The discussions highlighted the need for a better understanding of the effectiveness of program interventions in realistic settings; the importance of understanding what works for whom and under what circumstances, as well as the influence of different mediators (i.e., what accounts for associations between variables) and moderators (i.e., what affects the direction or strength of associations between variables) in bullying prevention efforts; and the need for coordination among agencies to prevent and respond to bullying. The workshop summary ( Institute of Medicine and National Research Council, 2014c ) informs this committee’s work.

Federal Efforts to Address Bullying and Related Topics

Currently, there is no comprehensive federal statute that explicitly prohibits bullying among children and adolescents, including cyberbullying. However, in the wake of the growing concerns surrounding the implications of bullying, several federal initiatives do address bullying among children and adolescents, and although some of them do not primarily focus on bullying, they permit some funds to be used for bullying prevention purposes.

The earliest federal initiative was in 1999, when three agencies collaborated to establish the Safe Schools/Healthy Students initiative in response to a series of deadly school shootings in the late 1990s. The program is administered by the U.S. Departments of Education, Health and Human Services, and Justice to prevent youth violence and promote the healthy development of youth. It is jointly funded by the Department of Education and by the Department of Health and Human Services’ Substance Abuse and Mental Health Services Administration. The program has provided grantees with both the opportunity to benefit from collaboration and the tools to sustain it through deliberate planning, more cost-effective service delivery, and a broader funding base ( Substance Abuse and Mental Health Services Administration, 2015 ).

The next major effort was in 2010, when the Department of Education awarded $38.8 million in grants under the Safe and Supportive Schools (S3) Program to 11 states to support statewide measurement of conditions for learning and targeted programmatic interventions to improve conditions for learning, in order to help schools improve safety and reduce substance use. The S3 Program was administered by the Safe and Supportive Schools Group, which also administered the Safe and Drug-Free Schools and Communities Act State and Local Grants Program, authorized by the

1994 Elementary and Secondary Education Act. 2 It was one of several programs related to developing and maintaining safe, disciplined, and drug-free schools. In addition to the S3 grants program, the group administered a number of interagency agreements with a focus on (but not limited to) bullying, school recovery research, data collection, and drug and violence prevention activities ( U.S. Department of Education, 2015 ).

A collaborative effort among the U.S. Departments of Agriculture, Defense, Education, Health and Human Services, Interior, and Justice; the Federal Trade Commission; and the White House Initiative on Asian Americans and Pacific Islanders created the Federal Partners in Bullying Prevention (FPBP) Steering Committee. Led by the U.S. Department of Education, the FPBP works to coordinate policy, research, and communications on bullying topics. The FPBP Website provides extensive resources on bullying behavior, including information on what bullying is, its risk factors, its warning signs, and its effects. 3 The FPBP Steering Committee also plans to provide details on how to get help for those who have been bullied. It also was involved in creating the “Be More than a Bystander” Public Service Announcement campaign with the Ad Council to engage students in bullying prevention. To improve school climate and reduce rates of bullying nationwide, FPBP has sponsored four bullying prevention summits attended by education practitioners, policy makers, researchers, and federal officials.

In 2014, the National Institute of Justice—the scientific research arm of the U.S. Department of Justice—launched the Comprehensive School Safety Initiative with a congressional appropriation of $75 million. The funds are to be used for rigorous research to produce practical knowledge that can improve the safety of schools and students, including bullying prevention. The initiative is carried out through partnerships among researchers, educators, and other stakeholders, including law enforcement, behavioral and mental health professionals, courts, and other justice system professionals ( National Institute of Justice, 2015 ).

In 2015, the Every Student Succeeds Act was signed by President Obama, reauthorizing the 50-year-old Elementary and Secondary Education Act, which is committed to providing equal opportunities for all students. Although bullying is neither defined nor prohibited in this act, it is explicitly mentioned in regard to applicability of safe school funding, which it had not been in previous iterations of the Elementary and Secondary Education Act.

The above are examples of federal initiatives aimed at promoting the

2 The Safe and Drug-Free Schools and Communities Act was included as Title IV, Part A, of the 1994 Elementary and Secondary Education Act. See http://www.ojjdp.gov/pubs/gun_violence/sect08-i.html [October 2015].

3 For details, see http://www.stopbullying.gov/ [October 2015].

healthy development of youth, improving the safety of schools and students, and reducing rates of bullying behavior. There are several other federal initiatives that address student bullying directly or allow funds to be used for bullying prevention activities.

Definitional Context

The terms “bullying,” “harassment,” and “peer victimization” have been used in the scientific literature to refer to behavior that is aggressive, is carried out repeatedly and over time, and occurs in an interpersonal relationship where a power imbalance exists ( Eisenberg and Aalsma, 2005 ). Although some of these terms have been used interchangeably in the literature, peer victimization is targeted aggressive behavior of one child against another that causes physical, emotional, social, or psychological harm. While conflict and bullying among siblings are important in their own right ( Tanrikulu and Campbell, 2015 ), this area falls outside of the scope of the committee’s charge. Sibling conflict and aggression falls under the broader concept of interpersonal aggression, which includes dating violence, sexual assault, and sibling violence, in addition to bullying as defined for this report. Olweus (1993) noted that bullying, unlike other forms of peer victimization where the children involved are equally matched, involves a power imbalance between the perpetrator and the target, where the target has difficulty defending him or herself and feels helpless against the aggressor. This power imbalance is typically considered a defining feature of bullying, which distinguishes this particular form of aggression from other forms, and is typically repeated in multiple bullying incidents involving the same individuals over time ( Olweus, 1993 ).

Bullying and violence are subcategories of aggressive behavior that overlap ( Olweus, 1996 ). There are situations in which violence is used in the context of bullying. However, not all forms of bullying (e.g., rumor spreading) involve violent behavior. The committee also acknowledges that perspective about intentions can matter and that in many situations, there may be at least two plausible perceptions involved in the bullying behavior.

A number of factors may influence one’s perception of the term “bullying” ( Smith and Monks, 2008 ). Children and adolescents’ understanding of the term “bullying” may be subject to cultural interpretations or translations of the term ( Hopkins et al., 2013 ). Studies have also shown that influences on children’s understanding of bullying include the child’s experiences as he or she matures and whether the child witnesses the bullying behavior of others ( Hellström et al., 2015 ; Monks and Smith, 2006 ; Smith and Monks, 2008 ).

In 2010, the FPBP Steering Committee convened its first summit, which brought together more than 150 nonprofit and corporate leaders,

researchers, practitioners, parents, and youths to identify challenges in bullying prevention. Discussions at the summit revealed inconsistencies in the definition of bullying behavior and the need to create a uniform definition of bullying. Subsequently, a review of the 2011 CDC publication of assessment tools used to measure bullying among youth ( Hamburger et al., 2011 ) revealed inconsistent definitions of bullying and diverse measurement strategies. Those inconsistencies and diverse measurements make it difficult to compare the prevalence of bullying across studies ( Vivolo et al., 2011 ) and complicate the task of distinguishing bullying from other types of aggression between youths. A uniform definition can support the consistent tracking of bullying behavior over time, facilitate the comparison of bullying prevalence rates and associated risk and protective factors across different data collection systems, and enable the collection of comparable information on the performance of bullying intervention and prevention programs across contexts ( Gladden et al., 2014 ). The CDC and U.S. Department of Education collaborated on the creation of the following uniform definition of bullying (quoted in Gladden et al., 2014, p. 7 ):

Bullying is any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated. Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm.

This report noted that the definition includes school-age individuals ages 5-18 and explicitly excludes sibling violence and violence that occurs in the context of a dating or intimate relationship ( Gladden et al., 2014 ). This definition also highlighted that there are direct and indirect modes of bullying, as well as different types of bullying. Direct bullying involves “aggressive behavior(s) that occur in the presence of the targeted youth”; indirect bullying includes “aggressive behavior(s) that are not directly communicated to the targeted youth” ( Gladden et al., 2014, p. 7 ). The direct forms of violence (e.g., sibling violence, teen dating violence, intimate partner violence) can include aggression that is physical, sexual, or psychological, but the context and uniquely dynamic nature of the relationship between the target and the perpetrator in which these acts occur is different from that of peer bullying. Examples of direct bullying include pushing, hitting, verbal taunting, or direct written communication. A common form of indirect bullying is spreading rumors. Four different types of bullying are commonly identified—physical, verbal, relational, and damage to property. Some observational studies have shown that the different forms of bullying that youths commonly experience may overlap ( Bradshaw et al., 2015 ;

Godleski et al., 2015 ). The four types of bullying are defined as follows ( Gladden et al., 2014 ):

• Physical bullying involves the use of physical force (e.g., shoving, hitting, spitting, pushing, and tripping).
• Verbal bullying involves oral or written communication that causes harm (e.g., taunting, name calling, offensive notes or hand gestures, verbal threats).
• Relational bullying is behavior “designed to harm the reputation and relationships of the targeted youth (e.g., social isolation, rumor spreading, posting derogatory comments or pictures online).”
• Damage to property is “theft, alteration, or damaging of the target youth’s property by the perpetrator to cause harm.”

In recent years, a new form of aggression or bullying has emerged, labeled “cyberbullying,” in which the aggression occurs through modern technological devices, specifically mobile phones or the Internet ( Slonje and Smith, 2008 ). Cyberbullying may take the form of mean or nasty messages or comments, rumor spreading through posts or creation of groups, and exclusion by groups of peers online.

While the CDC definition identifies bullying that occurs using technology as electronic bullying and views that as a context or location where bullying occurs, one of the major challenges in the field is how to conceptualize and define cyberbullying ( Tokunaga, 2010 ). The extent to which the CDC definition can be applied to cyberbullying is unclear, particularly with respect to several key concepts within the CDC definition. First, whether determination of an interaction as “wanted” or “unwanted” or whether communication was intended to be harmful can be challenging to assess in the absence of important in-person socioemotional cues (e.g., vocal tone, facial expressions). Second, assessing “repetition” is challenging in that a single harmful act on the Internet has the potential to be shared or viewed multiple times ( Sticca and Perren, 2013 ). Third, cyberbullying can involve a less powerful peer using technological tools to bully a peer who is perceived to have more power. In this manner, technology may provide the tools that create a power imbalance, in contrast to traditional bullying, which typically involves an existing power imbalance.

A study that used focus groups with college students to discuss whether the CDC definition applied to cyberbullying found that students were wary of applying the definition due to their perception that cyberbullying often involves less emphasis on aggression, intention, and repetition than other forms of bullying ( Kota et al., 2014 ). Many researchers have responded to this lack of conceptual and definitional clarity by creating their own measures to assess cyberbullying. It is noteworthy that very few of these

definitions and measures include the components of traditional bullying—i.e., repetition, power imbalance, and intent ( Berne et al., 2013 ). A more recent study argues that the term “cyberbullying” should be reserved for incidents that involve key aspects of bullying such as repetition and differential power ( Ybarra et al., 2014 ).

Although the formulation of a uniform definition of bullying appears to be a step in the right direction for the field of bullying prevention, there are some limitations of the CDC definition. For example, some researchers find the focus on school-age youth as well as the repeated nature of bullying to be rather limiting; similarly the exclusion of bullying in the context of sibling relationships or dating relationships may preclude full appreciation of the range of aggressive behaviors that may co-occur with or constitute bullying behavior. As noted above, other researchers have raised concerns about whether cyberbullying should be considered a particular form or mode under the broader heading of bullying as suggested in the CDC definition, or whether a separate defintion is needed. Furthermore, the measurement of bullying prevalence using such a definiton of bullying is rather complex and does not lend itself well to large-scale survey research. The CDC definition was intended to inform public health surveillance efforts, rather than to serve as a definition for policy. However, increased alignment between bullying definitions used by policy makers and researchers would greatly advance the field. Much of the extant research on bullying has not applied a consistent definition or one that aligns with the CDC definition. As a result of these and other challenges to the CDC definition, thus far there has been inconsistent adoption of this particular definition by researchers, practitioners, or policy makers; however, as the definition was created in 2014, less than 2 years is not a sufficient amount of time to assess whether it has been successfully adopted or will be in the future.

THE COMMITTEE’S APPROACH

This report builds on the April 2014 workshop, summarized in Building Capacity to Reduce Bullying: Workshop Summary ( Institute of Medicine and National Research Council, 2014c ). The committee’s work was accomplished over an 18-month period that began in October 2014, after the workshop was held and the formal summary of it had been released. The study committee members represented expertise in communication technology, criminology, developmental and clinical psychology, education, mental health, neurobiological development, pediatrics, public health, school administration, school district policy, and state law and policy. (See Appendix E for biographical sketches of the committee members and staff.) The committee met three times in person and conducted other meetings by teleconferences and electronic communication.

Information Gathering

The committee conducted an extensive review of the literature pertaining to peer victimization and bullying. In some instances, the committee drew upon the broader literature on aggression and violence. The review began with an English-language literature search of online databases, including ERIC, Google Scholar, Lexis Law Reviews Database, Medline, PubMed, Scopus, PsycInfo, and Web of Science, and was expanded as literature and resources from other countries were identified by committee members and project staff as relevant. The committee drew upon the early childhood literature since there is substantial evidence indicating that bullying involvement happens as early as preschool (see Vlachou et al., 2011 ). The committee also drew on the literature on late adolescence and looked at related areas of research such as maltreatment for insights into this emerging field.

The committee used a variety of sources to supplement its review of the literature. The committee held two public information-gathering sessions, one with the study sponsors and the second with experts on the neurobiology of bullying; bullying as a group phenomenon and the role of bystanders; the role of media in bullying prevention; and the intersection of social science, the law, and bullying and peer victimization. See Appendix A for the agendas for these two sessions. To explore different facets of bullying and give perspectives from the field, a subgroup of the committee and study staff also conducted a site visit to a northeastern city, where they convened four stakeholder groups comprised, respectively, of local practitioners, school personnel, private foundation representatives, and young adults. The site visit provided the committee with an opportunity for place-based learning about bullying prevention programs and best practices. Each focus group was transcribed and summarized thematically in accordance with this report’s chapter considerations. Themes related to the chapters are displayed throughout the report in boxes titled “Perspectives from the Field”; these boxes reflect responses synthesized from all four focus groups. See Appendix B for the site visit’s agenda and for summaries of the focus groups.

The committee also benefited from earlier reports by the National Academies of Sciences, Engineering, and Medicine through its Division of Behavioral and Social Sciences and Education and the Institute of Medicine, most notably:

• Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research ( Institute of Medicine, 1994 )
• Community Programs to Promote Youth Development ( National Research Council and Institute of Medicine, 2002 )
• Deadly Lessons: Understanding Lethal School Violence ( National Research Council and Institute of Medicine, 2003 )
• Preventing Mental, Emotional, and Behavioral Disorders Among Young People: Progress and Possibilities ( National Research Council and Institute of Medicine, 2009 )
• The Science of Adolescent Risk-Taking: Workshop Report ( Institute of Medicine and National Research Council, 2011 )
• Communications and Technology for Violence Prevention: Workshop Summary ( Institute of Medicine and National Research Council, 2012 )
• Building Capacity to Reduce Bullying: Workshop Summary ( Institute of Medicine and National Research Council, 2014c )
• The Evidence for Violence Prevention across the Lifespan and Around the World: Workshop Summary ( Institute of Medicine and National Research Council, 2014a )
• Strategies for Scaling Effective Family-Focused Preventive Interventions to Promote Children’s Cognitive, Affective, and Behavioral Health: Workshop Summary ( Institute of Medicine and National Research Council, 2014b )
• Investing in the Health and Well-Being of Young Adults ( Institute of Medicine and National Research Council, 2015 )

Although these past reports and workshop summaries address various forms of violence and victimization, this report is the first consensus study by the National Academies of Sciences, Engineering, and Medicine on the state of the science on the biological and psychosocial consequences of bullying and the risk and protective factors that either increase or decrease bullying behavior and its consequences.

Terminology

Given the variable use of the terms “bullying” and “peer victimization” in both the research-based and practice-based literature, the committee chose to use the current CDC definition quoted above ( Gladden et al., 2014, p. 7 ). While the committee determined that this was the best definition to use, it acknowledges that this definition is not necessarily the most user-friendly definition for students and has the potential to cause problems for students reporting bullying. Not only does this definition provide detail on the common elements of bullying behavior but it also was developed with input from a panel of researchers and practitioners. The committee also followed the CDC in focusing primarily on individuals between the ages of 5 and 18. The committee recognizes that children’s development occurs on a continuum, and so while it relied primarily on the CDC defini-

tion, its work and this report acknowledge the importance of addressing bullying in both early childhood and emerging adulthood. For purposes of this report, the committee used the terms “early childhood” to refer to ages 1-4, “middle childhood” for ages 5 to 10, “early adolescence” for ages 11-14, “middle adolescence” for ages 15-17, and “late adolescence” for ages 18-21. This terminology and the associated age ranges are consistent with the Bright Futures and American Academy of Pediatrics definition of the stages of development. 4

A given instance of bullying behavior involves at least two unequal roles: one or more individuals who perpetrate the behavior (the perpetrator in this instance) and at least one individual who is bullied (the target in this instance). To avoid labeling and potentially further stigmatizing individuals with the terms “bully” and “victim,” which are sometimes viewed as traits of persons rather than role descriptions in a particular instance of behavior, the committee decided to use “individual who is bullied” to refer to the target of a bullying instance or pattern and “individual who bullies” to refer to the perpetrator of a bullying instance or pattern. Thus, “individual who is bullied and bullies others” can refer to one who is either perpetrating a bullying behavior or a target of bullying behavior, depending on the incident. This terminology is consistent with the approach used by the FPBP (see above). Also, bullying is a dynamic social interaction ( Espelage and Swearer, 2003 ) where individuals can play different roles in bullying interactions based on both individual and contextual factors.

The committee used “cyberbullying” to refer to bullying that takes place using technology or digital electronic means. “Digital electronic forms of contact” comprise a broad category that may include e-mail, blogs, social networking Websites, online games, chat rooms, forums, instant messaging, Skype, text messaging, and mobile phone pictures. The committee uses the term “traditional bullying” to refer to bullying behavior that is not cyberbullying (to aid in comparisons), recognizing that the term has been used at times in slightly different senses in the literature.

Where accurate reporting of study findings requires use of the above terms but with senses different from those specified here, the committee has noted the sense in which the source used the term. Similarly, accurate reporting has at times required use of terms such as “victimization” or “victim” that the committee has chosen to avoid in its own statements.

4 For details on these stages of adolescence, see https://brightfutures.aap.org/Bright%20Futures%20Documents/3-Promoting_Child_Development.pdf [October 2015].

ORGANIZATION OF THE REPORT

This report is organized into seven chapters. After this introductory chapter, Chapter 2 provides a broad overview of the scope of the problem.

Chapter 3 focuses on the conceptual frameworks for the study and the developmental trajectory of the child who is bullied, the child who bullies, and the child who is bullied and also bullies. It explores processes that can explain heterogeneity in bullying outcomes by focusing on contextual processes that moderate the effect of individual characteristics on bullying behavior.

Chapter 4 discusses the cyclical nature of bullying and the consequences of bullying behavior. It summarizes what is known about the psychosocial, physical health, neurobiological, academic-performance, and population-level consequences of bullying.

Chapter 5 provides an overview of the landscape in bullying prevention programming. This chapter describes in detail the context for preventive interventions and the specific actions that various stakeholders can take to achieve a coordinated response to bullying behavior. The chapter uses the Institute of Medicine’s multi-tiered framework ( National Research Council and Institute of Medicine, 2009 ) to present the different levels of approaches to preventing bullying behavior.

Chapter 6 reviews what is known about federal, state, and local laws and policies and their impact on bullying.

After a critical review of the relevant research and practice-based literatures, Chapter 7 discusses the committee conclusions and recommendations and provides a path forward for bullying prevention.

The report includes a number of appendixes. Appendix A includes meeting agendas of the committee’s public information-gathering meetings. Appendix B includes the agenda and summaries of the site visit. Appendix C includes summaries of bullying prevalence data from the national surveys discussed in Chapter 2 . Appendix D provides a list of selected federal resources on bullying for parents and teachers. Appendix E provides biographical sketches of the committee members and project staff.

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Vivolo, A.M., Holt, M.K., and Massetti, G.M. (2011). Individual and contextual factors for bullying and peer victimization: Implications for prevention. Journal of School Violence, 10 (2), 201-212.

Vlachou, M., Andreou, E., Botsoglou, K., and Didaskalou, E. (2011). Bully/victim problems among preschool children: A review of current research evidence. Educational Psychology Review, 23 (3), 329-358.

Wolke, D., and Lereya, S.T. (2015). Long-term effects of bullying. Archives of Disease in Childhood, 100 (9), 879-885.

Ybarra, M.L., Espelage, D.L., and Mitchell, K.J. (2014). Differentiating youth who are bullied from other victims of peer-aggression: The importance of differential power and repetition. Journal of Adolescent Health, 55 (2), 293-300.

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Bullying has long been tolerated as a rite of passage among children and adolescents. There is an implication that individuals who are bullied must have "asked for" this type of treatment, or deserved it. Sometimes, even the child who is bullied begins to internalize this idea. For many years, there has been a general acceptance and collective shrug when it comes to a child or adolescent with greater social capital or power pushing around a child perceived as subordinate. But bullying is not developmentally appropriate; it should not be considered a normal part of the typical social grouping that occurs throughout a child's life.

Although bullying behavior endures through generations, the milieu is changing. Historically, bulling has occurred at school, the physical setting in which most of childhood is centered and the primary source for peer group formation. In recent years, however, the physical setting is not the only place bullying is occurring. Technology allows for an entirely new type of digital electronic aggression, cyberbullying, which takes place through chat rooms, instant messaging, social media, and other forms of digital electronic communication.

Composition of peer groups, shifting demographics, changing societal norms, and modern technology are contextual factors that must be considered to understand and effectively react to bullying in the United States. Youth are embedded in multiple contexts and each of these contexts interacts with individual characteristics of youth in ways that either exacerbate or attenuate the association between these individual characteristics and bullying perpetration or victimization. Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, this report evaluates the state of the science on biological and psychosocial consequences of peer victimization and the risk and protective factors that either increase or decrease peer victimization behavior and consequences.

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124 Bullying Essay Topics

🏆 best essay topics on bullying, ✍️ bullying essay topics for college, 👍 good bullying research topics & essay examples, 🎓 most interesting bullying research titles, ❓ bullying research questions.

• School Bullying: Causes and Effects
• Bullying in Schools: Essay Example
• The Problem of Bullying in School
• Chronicles of Bullying: An Editorial Article
• Bullying at School and Impact on Mental Health
• School Bullying and Student’s Development
• Bullying in Schools: Anti-Bullying Programs
• The Cognitive Behavioural Therapy on Victims of Bullying This paper will be able to ascertain that Cognitive Behavioural Therapy is a very effective therapy that defies the ugly trend of bullying in schools.
• Bullying: A Serious Social Problem Bullying is undesirable behavior that society must deter at all costs. In schools, teachers, parents, and other stakeholders should have working knowledge on managing the vice.
• Teenagers’ Contemporary Issues: Bullying at School Bullying can be caused by differences between students, and the existing assessment and support options contribute to improving the situation.
• Workplace Bullying and Its Implications on Organizations Discrimination is one of the major challenges that organizational leaders face within the workplace. Workplace bullying refers to any acts intended to intimidate a colleague.
• Negative Bullying Outcomes: A Persuasive Speech Bullying has adverse effects on both victims and perpetrators. Bullying should be prevented, or should it occur, reported, and taken care of as soon as possible.
• Why Bullying Is Wrong and Methods of Resolving Disputes Without Violence Such methods of conflict resolution as mediation, communication, and listening may eliminate the harmful impact of such behavior without violence.
• Prevention of Bullying in Schools School bullying is a relevant and critical global issue, and while it affects all children, some groups may experience various disparities and increased exposure to bullying.
• Online Bullying Takes Over the World In the context of a rapidly and highly digitized global environment, online bullying, otherwise known as cyberbullying, has become a prevalent issue.
• Bullying Behavior and Its Negative Effects on Children Bullying behavior is a severe issue among school-age children. This essay addresses the negative effects of bullying on children and the ways of overcoming the problem.
• Bullying in Poverty and Child Development Context The aim of the present paper is to investigate how Bullying, as a factor associated with poverty, affects child development.
• Bullying Effects on Health and Life Quality When children are subject to bullying by their peers, it affects their feelings and evokes negative emotions in the first place.
• Reducing Bullying in Schools by Involving Stakeholders Schools should raise awareness among educators, instructors, and community members about their roles and responsibilities in the battle against bullying.
• Bullying and Parenting Styles There are many positive and negative outcomes of parenting on children. This paper aims at investigating the connection between several types of parenting and bullying behaviors.
• School Bullying and Problems in Adult Life Bullying is aggressive behavior that can be seen in different children, teenagers, and adults. In this paper, the causes of bullying and the effects of it will be presented and discussed.
• Fear Appeal in the Stop Bullying Public Campaign In the video “Stop bullying,” the subject matter is presented shockingly. The 47-second clip shows a high school girl receiving an aggressive text message from her peers.
• The Problem of Workplace Bullying: Literature Review The purpose of this paper is to provide a review of the relevant literature on the topic of workplace bullying.
• Deterring Juvenile Crime. Bullying and Delinquency Delinquency can be defined as a crime committed by a minor; in the recent few years, cases of juvenile delinquency have been on the rise.
• Addressing Bullying in Elementary and Middle School Classrooms The study mainly focuses on teachers’ lack of knowledge on how to deal with the issue of bullying in the classroom in an effective manner.
• Bullying Problem in School Bullying is caused by genetic predisposition, relations with peers, and as a reaction to the situation in school or at home.
• The Long-Term Consequences of Being Bullied or Bullying Others in Childhood This study attempts to discuss the main consequences on the mental and physical health of victims, bully-victims, and bullies themselves, and comment on the prevalent patterns.
• Anti Bullying Prevention Program The standards for anti-bullying program aims to prevent not only the behavior of bullying but also behavior representing the full spectrum of inter-student cruelty.
• Causes of Bullying in Nursing The relationship between medical staff is an important aspect that determines the quality of work in a particular institution and the healthcare system as a whole.
• Cyber-Bullying and Ways to Solve the Problem The primary goal of the given study is the investigation of cyber-bullying, which is nowadays one of the integral parts of social media and the Internet.
• Cyber Bullying Messages in Communication Networks Bullying can come in different forms, but it always causes injury or even worse. Bullying victims may carry the psychological wounds of their ordeal for the rest of their life.
• Bullying and Work-Related Stress in the Irish Workplace One of the best analyses of relationships between workplace stress and bullying has been done in the research study called “Bullying and Work-Related Stress in the Irish Workplace.”
• Bullying and School Drop Out Rate Relationship Analysis Bullying is rife in schools where physical and verbal abuse occurs among pupils/students. There is “a close relationship between bullying, school involvement, and literacy”.
• Organization Conflicts and Bullying Workplace bullying is a serious problem with huge costs attached to it in terms of loss of working days. The topic requires academic attention to ascertain the factors that induce such behavior.
• Bullying at Pre-School and Preventive Measures This paper provides five tips for pre-school bullying prevention, the first of which is to give opportunities for children to show kindness and respect.
• The Relation Between the Teen Suicide and Bullying During the teenage years, bullying and harassment represent cases of social animosity that make suicide an option.
• Parenting Style and Bullying Among Children The investigation of parenting styles is highly essential to understand how they affect the bullying behavior of children to prevent it.
• Bullying and Sexual Harassment at Work Place According to Safety and Health Assessment and Research for Prevention, workplace bullying occurs when an individual direct irrational actions repeatedly towards their fellow worker.
• High School Bullying: Psychological Aspects The study discusses the psychology behind bullying, the effects of bullying on all the involved parties, and emergent patterns.
• The Workplace Bullying Prevention Policy The problem of bullying creates a severe issue for the atmosphere of the workplace environment, the mental health of workers, and their performance.
• The Issue of High School Bullying Bullying cases among high school students have been on the rise in modern society. High school bullying is mainly caused by media exposure.
• The Consequences of High School Bullying This annotated bibliography includes summaries of four academic studies that explore the effects of bullying on high school students.
• Bullying of Learners with Disabilities The problem of bullying remains one of the predicaments learners with disabilities encounter in their learning environments.
• Bullying and Methods of Solving This Problem The article is devoted to the causes of bullying which develops in almost any closed community among children and adolescents.
• Harsher Laws for Cyber Bullying The number of people using social networks is growing but they do not see the danger in remote communication and are subjected to cyberbullying.
• The Social Problem of Bullying and the School System The present paper focuses on the connection between the social problem of bullying and the school system, describing each of these concepts.
• Bullying During Orientations in the Universities In order to address the issue related to bullying during orientations, only the most empathetic senior students should be allowed to participate in orientations.
• Bullying Among Adolescents Problem Studying the problem of bullying, its factors of influence, and the application of developmental theories are critical for finding ways to combat it effectively.
• Bullying: A Guide for the Parents The first way for parents to assist the kid in coming up with bullies is to teach them a set of responses, which they can use in case someone is picking on them.
• Problem Scenario: Workplace Bullying in Teaching When the word “bullying” is used in the context of education, one often presumes the situation in which one student systematically mistreats another.
• Bullying and Patient Safety in Clinical Settings Besides damaging the atmosphere in clinical settings and negatively affecting the personnel, bullying can lower the quality of healthcare services and harm patient safety.
• Bullying as Managerial Issue in Nursing Sector Bullying is a significant nursing issue due to the negative impact caused on the performance level among the employees.
• Problem of Bullying Overview and Analysis Bullying can have harmful impacts on everyone involved, including bullies, the bullied, and bystanders. It can be prevented through the use of selective preventive programs.
• Nurse Bullying: Unprofessional Conduct Bullying can be exhibited in the form of physical and verbal threats, social seclusion, aggressive behaviors, and suppression of applicable care information.
• Bullying: A Concern for Modern Communities and Educational Establishments Parents can educate their children to create safe environment for healthy development, both physical and mental, guaranteeing the absence of abusive behavior or victimization.
• Bullying and Its Impact on My Life In this essay, the author talks about the impact of bullying on his life and how he managed to cope with the problem.
• Workplace Bullying and Its Impact on People’s Mental Health Workplace bullying turns out to be a serious theme for discussion because of a variety of reasons, and one of them is its impact on people’s mental health.
• “Nurse Exposure to Physical and Nonphysical Violence, Bullying…” by Spector This paper is a critique of the article titled “Nurse Exposure to Physical and Nonphysical Violence, Bullying, and Sexual Harassment: A Quantitative Review”.
• Anti-bullying Practices in Criminal Prosecution Anti-bullying practices have proceeded past only encouraging an individual to avoid ill-treatment of their peers to the establishment of laws.
• Workplace Bullying: Dealing With the Office Bully The psychological stress caused by bullying can be so severe that in the worst case, it can lead to depression and quitting.
• Bullying in the Modern Society: Review Bullying is one of the major concerns of modern society. Following the statistics, about 40% of all individuals have experienced being bullied at least once.
• The Dumfries and Galloway Council’s Policy Against Bullying This paper discusses the analysis of the bullying in general and its understanding in the works of Dumfries and Galloway Council.
• The Meaning of Cyber Bullying The work reveals the meaning and purpose of cyberbullying, what signs characterize it and the solution to cyberbullying.
• Workplace Bullying in the Nursing Areas The paper is aimed to tell about the importance of overcoming workplace bullying in the example of a nursing collective.
• Exploring Workplace Bullying in Nursing This paper critiques Etienne’s 2013 study of workplace bullying in nursing and highlights the strengths and weaknesses of the research.
• Bullying Among Nursing Staff The bullying in health care is still present, and health practitioners’ mental health, motivation, and ability to uphold precision and self-composure are compromised.
• Nurse Bullying and Legal Interventions Nurse bullying has to be addressed by healthcare establishments and national agencies to ensure proper work culture and adequate environment for patient care.
• Horizontal Violence and Bullying in Nursing There is a direct correlation between horizontal violence and job satisfaction among nurses, which affects the efforts of individuals who choose this profession.
• The Issue of Cyber-Bullying in Education Field Bullying has been recognized as a pervasive and a severe problem as well as a significant concern, mostly in the educational field.
• Bullying and Laws in American Schools Researchers distinguish two major kinds of bullying that take place in the academic setting: direct and indirect.
• School Bullying and Legal Responsibility The following paper will discuss and cover the rate of school bullies’ legally unregulated actions and the detriment that they constantly cause to other children who surround them.
• Cyber-Bullying and Cyber-Stalking as Crimes Cyber-bullying and cyber-stalking are relatively close in meaning, but there is a slight difference in the definition of these terms.
• School Bullying and Teacher Professional Development
• Bullying and Its Effect on Our American Society
• Physical, Emotional, and Social Bullying
• The Government Should Put Laws in Place To Prevent Bullying
• Childhood Bullying and Social Relationships
• Bullying and Its Effects on Individual’s Education
• The Emotional and Physical Aspects of Bullying
• Bullying and Its Effects on the Person Who Is Being Hurt
• Childhood Bullying and Its Effects on Children
• Cyber Bullying Affects People‘s Lives More Than One Might Think
• Managing Bullying and Harassment in the Workplace
• Bullying Affects the Social Learning Theory
• How Has Bullying Changed Our Modern World?
• Bullying and the Workplace and Affect Morale
• The Bible Belt and Its Beliefs on the Problem of Bullying
• Cyber-bullying Through Anonymous Social Media
• The Difference Between Bullying and Harassment
• Racial Bullying and Its Effects on the Middle of the Twenty
• Bullying Among Children With Autism Spectrum Disorder
• Social Media Bullying and Cyberbullying
• Bullying Prevention and School Safety
• Physical and Verbal Bullying in Schools
• What Are Schools and Parents Doing for Bullying Prevention?
• What Are the Effects of Bullying in Public Schools?
• What Strategies Might You Employ to Encourage Pupils to Prevent Bullying?
• How to Talk to Your Children About Bullying?
• What Are the Six Types of Bullying Parents Should Know About?
• Which American State Has the Toughest Bullying Laws?
• Who Started and Invented Anti-Bullying Day?
• What Countries Have Anti-Bullying Laws?
• Which American State Is the Only One to Not Have an Anti-Bullying Law?
• What Is the Meaning of Anti-Bullying Law?
• What Is the Number One Determinant of Bullying Will Occur?
• When Was the First Anti-Bullying Law Passed?
• Is Bullying a Social Determinant of Health?
• What Should Be in an Anti-Bullying Policy?
• Why Is the Anti-Bullying Policy Important?
• Why Should We Be Aware of the Anti-Bullying Act of 2013?
• What Is the Meaning of Emotional Bullying?
• What Is the Punishment for Anti-Bullying Act?
• Is Bullying a Social Phenomena?
• Who Is the Father of Bullying Research?
• What Is a Good Slogan for Stop Bullying?
• Why Do the Bullying Programs not Work?
• Why Students Engage in Bullying?
• Why Are Workplace Bullying and Violence Important Issues for Organizations?
• Why Should Bullying Not Be Harsh?
• What Is the Most Important Strategy for Bullying Prevention?
• Why Do We Need to Conduct a Study About Bullying?
• Are Bullying Prevention Programs Effective?
• Who Should Universities Have the Ability to Punish Students for Cyber Bullying?
• Are Neoliberalist Behaviours Reflective of Bullying?

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This essay topic collection was updated on December 27, 2023 .

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Cyberbullying and its influence on academic, social, and emotional development of undergraduate students

This study investigated the influence of cyberbullying on the academic, social, and emotional development of undergraduate students. It's objective is to provides additional data and understanding of the influence of cyberbullying on various variables affecting undergraduate students. The survey sample consisted of 638 Israeli undergraduate students. The data were collected using the Revised Cyber Bullying Survey, which evaluates the frequency and media used to perpetrate cyberbullying, and the College Adjustment Scales, which evaluate three aspects of development in college students. It was found that 57% of the students had experienced cyberbullying at least once or twice through different types of media. Three variables were found to have significant influences on the research variables: gender, religion and sexual preferences. Correlation analyses were conducted and confirmed significant relationships between cyberbullying, mainly through instant messaging, and the academic, social and emotional development of undergraduate students. Instant messaging (IM) was found to be the most common means of cyberbullying among the students.

The main conclusions are that although cyberbullying existence has been proven, studies of cyberbullying among undergraduate students have not been fully developed. This particular population needs special attention in future research. The results of this study indicate that cyberbullying has an influence on the academic, social, and emotional development of undergraduate students. Additional Implications of the findings are discussed.

1. Introduction

Cyberbullying is defined as the electronic posting of mean-spirited messages about a person (such as a student) often done anonymously ( Merriam-Webster, 2017 ). Most of the investigations of cyberbullying have been conducted with students in elementary, middle and high school who were between 9 and 18 years old. Those studies focused on examining the prevalence and frequency of cyberbullying. Using “cyberbullying” and “higher-education” as key words in Google scholar (January, 2019) (all in title) yields only twenty one articles. In 2009, 2012 and 2013 one article appeared each year, since 2014 each year there were few publications. Of these articles only seven relates to effect of cyberbullying on the students, thus a gap in the literature exists in that it only minimally reports on studies involving undergraduate students. Given their relationship and access to technology, it is likely that cyberbullying occurs frequently among undergraduates. The purpose of this study is to examine the frequency and media used to perpetrate cyberbullying, as well as the relationship that it has with the academic, social and emotional development of undergraduate students.

Undergraduate students use the Internet for a wide variety of purposes. Those purposes include recreation, such as communicating in online groups or playing games; academics, such as doing assignments, researching scholarships or completing online applications; and practical, such as preparing for job interviews by researching companies. Students also use the Internet for social communication with increasing frequency.

The literature suggests that cyberbullied victims generally manifest psychological problems such as depression, loneliness, low self-esteem, school phobias and social anxiety ( Grene, 2003 ; Juvonen et al., 2003 ; Akcil, 2018 ). Moreover, research findings have shown that cyberbullying causes emotional and physiological damage to defenseless victims ( Akbulut and Eristi, 2011 ) as well as psychosocial difficulties including behavior problems ( Ybarra and Mitchell, 2007 ), drinking alcohol ( Selkie et al., 2015 ), smoking, depression, and low commitment to academics ( Ybarra and Mitchell, 2007 ).

Under great emotional stress, victims of cyberbullying are unable to concentrate on their studies, and thus their academic progress is adversely affected ( Akcil, 2018 ). Since the victims are often hurt psychologically, the depressive effect of cyberbullying prevents students from excelling in their studies ( Faryadi, 2011 ). The overall presence of cyberbullying victimization among undergraduate college students was found to be significantly related to the experience of anxiety, depression, substance abuse, low self-esteem, interpersonal problems, family tensions and academic underperformance ( Beebe, 2010 ).

1.1. Cyberbullying and internet

The Internet has been the most useful technology of modern times, which has enabled entirely new forms of social interaction, activities, and organizing. This has been possible thanks to its basic features such as widespread usability and access. However, it also causes undesirable behaviors that are offensive or threatening to others, such as cyberbullying. This is a relatively new phenomenon.

According to Belsey (2006, p.1) , “Cyberbullying involves the use of information and communication technologies such as e-mail, cell-phone and pager text messages, instant messaging, defamatory personal web sites, blogs, online games and defamatory online personal polling web sites, to support deliberate, repeated, and hostile behavior by an individual or group that is intended to harm others.” Characteristics like anonymity, accessibility to electronic communication, and rapid audience spread, result in a limitless number of individuals that can be affected by cyberbullying.

Different studies suggest that undergraduate students' use of the Internet is more significant and frequent than any other demographic group. A 2014 survey of 1006 participants in the U.S. conducted by the Pew Research Center revealed that 97% of young adults aged from 18 to 29 years use the Internet, email, or access the Internet via a mobile device. Among them, 91% were college students.

1.2. Mediums to perpetrate cyberbullying

The most frequent and common media within which cyberbullying can occur are:

Electronic mail (email): a method of exchanging digital messages from an author to one or more recipients.

Instant messaging: a type of online chat that offers real-time text transmission between two parties.

Chat rooms: a real-time online interaction with strangers with a shared interest or other similar connection.

Text messaging (SMS): the act of composing and sending a brief electronic message between two or more mobile phones.

Social networking sites: a platform to build social networks or social relations among people who share interests, activities, backgrounds or real-life connections.

Web sites : a platform that provides service for personal, commercial, or government purpose.

Studies indicate that undergraduate students are cyberbullied most frequently through email, and least often in chat rooms ( Beebe, 2010 ). Other studies suggest that instant messaging is the most common electronic medium used to perpetrate cyberbullying ( Kowalski et al., 2018 ).

1.3. Types of cyberbullying

Watts et al. (2017) Describe 7 types of cyberbullying: flaming, online harassment, cyberstalking, denigration, masquerading, trickery and outing, and exclusion. Flaming involves sending angry, rude, or vulgar messages via text or email about a person either to that person privately or to an online group.

Harassment involves repeatedly sending offensive messages, and cyberstalking moves harassment online, with the offender sending threatening messages to his or her victim. Denigration occurs when the cyberbully sends untrue or hurtful messages about a person to others. Masquerading takes elements of harassment and denigration where the cyberbully pretends to be someone else and sends or posts threatening or harmful information about one person to other people. Trickery and outing occur when the cyberbully tricks an individual into providing embarrassing, private, or sensitive information and posts or sends the information for others to view. Exclusion is deliberately leaving individuals out of an online group, thereby automatically stigmatizing the excluded individuals.

Additional types of cyberbullying are: Fraping - where a person accesses the victim's social media account and impersonates them in an attempt to be funny or to ruin their reputation. Dissing - share or post cruel information online to ruin one's reputation or friendships with others. Trolling - is insulting an individual online to provoke them enough to get a response. Catfishing - steals one's online identity to re-creates social networking profiles for deceptive purposes. Such as signing up for services in the victim's name so that the victim receives emails or other offers for potentially embarrassing things such as gay-rights newsletters or incontinence treatment. Phishing - a tactic that requires tricking, persuading or manipulating the target into revealing personal and/or financial information about themselves and/or their loved ones. Stalking – Online stalking when a person shares her personal information publicly through social networking websites. With this information, stalkers can send them personal messages, send mysterious gifts to someone's home address and more. Blackmail – Anonymous e-mails, phone-calls and private messages are often done to a person who bear secrets. Photographs & video - Threaten to share them publicly unless the victim complies with a particular demand; Distribute them via text or email, making it impossible for the victim to control who sees the picture; Publish the pictures on the Internet for anyone to view. Shunning - persistently avoid, ignore, or reject someone mainly from participating in social networks. Sexting - send sexually explicit photographs or messages via mobile phone.

1.4. Prevalence of cyberbullying

Previous studies have found that cyberbullying incidents among college students can range from 9% to 34% ( Baldasare et al., 2012 ).

Beebe (2010) conducted a study with 202 college students in United States. Results indicated that 50.7% of the undergraduate students represented in the sample reported experiencing cyberbullying victimization once or twice during their time in college. Additionally, 36.3% reported cyberbullying victimization on a monthly basis while in college. According to Dılmaç (2009) , 22.5% of 666 students at Selcuk University in Turkey reported cyberbullying another person at least once and 55.35% reported being a victim of cyberbullying at least once in their lifetimes. In a study of 131 students from seven undergraduate classes in United States, 11% of the respondents indicated having experienced cyberbullying at the university ( Walker et al., 2011 ). Of those, Facebook (64%), cell phones (43%) and instant messaging (43%) were the most frequent technologies used. Students indicated that 50% of the cyberbullies were classmates, 57% were individuals outside of the university, and 43% did not know who was cyberbullying them.

Data from the last two years (2017–18) is similar to the above. A research, of 187 undergraduate students matriculated at a large U.S. Northeastern metropolitan Roman Catholic university ( Webber and Ovedovitz, 2018 ), found that 4.3% indicated that they were victims of cyberbullying at the university level and a total of 7.5% students acknowledged having participated in bullying at that level while A survey (N = 338) at a large midwestern university conducted by Varghese and Pistole (2017) , showed that frequency counts indicated that 15.1% undergraduate students were cyberbully victims during college, and 8.0% were cyberbully offenders during college.

A study of 201 students from sixteen different colleges across the United States found a prevalence rate of 85.2% for college students who reported being victims of cyberbullying out of the total 201 responses recorded. This ranged from only occasional incidents to almost daily experiences with cyberbullying victimization ( Poole, 2017 ).

In A research of international students, 20.7% reported that they have been cyberbullied in the last 30 days once to many times ( Akcil, 2018 ).

1.5. Psychological impact of cyberbullying

Cyberbullying literature suggests that victims generally manifest psychological problems such as depression, anxiety, loneliness, low self-esteem, social exclusion, school phobias and poor academic performance ( DeHue et al., 2008 ; Juvonen and Gross, 2008 ; Kowalski and Limber, 2007 ; Grene, 2003 ; Juvonen et al., 2003 ; Rivituso, 2012 ; Varghese and Pistole, 2017 ; Na, 2014 ; Akcil, 2018 ), low self-esteem, family problems, school violence and delinquent behavior ( Webber and Ovedovitz, 2018 ), which brings them to experience suicidal thoughts as a means of escaping the torture ( Ghadampour et al., 2017 ).

Moreover, research findings have shown that cyberbullying causes emotional and physiological damage to defenseless victims ( Faryadi, 2011 ) as well as psychosocial problems including inappropriate behaviors, drinking alcohol, smoking, depression and low commitment to academics ( Walker et al., 2011 ).

The victims of cyberbullying, under great emotional stress, are unable to concentrate on their studies, and thus their academic progress is adversely affected ( Faryadi, 2011 ). Since the victims are often hurt psychologically, the depressive effect of cyberbullying prevents students from excelling in their studies ( Faryadi, 2011 ).

In a Malaysian university study with 365 first year students, the majority of the participants (85%) interviewed indicated that cyberbullying affected their academic performance, specifically their grades ( Faryadi, 2011 ). Also, 85% of the respondents agreed that bullying caused a devastating impact on students' emotions and equally caused unimaginable psychological problems among the victims. Heiman and Olenik-Shemesh (2018) report that for students with learning disabilities, predictors of cybervictimization were low social support, low self-perception, and being female, whereas for students without learning disabilities, the predictors were low social support, low well-being, and low body perception.

1.6. Academic, social, and emotional development of undergraduate students

The transition to academic institutions is marked by complex challenges in emotional, social, and academic adjustment ( Gerdes and Mallinckrodt, 1994 ; Parker et al., 2004 ).

The adaptation to a new environment is an important factor in academic performance and future achievement. Undergraduate students are not only developing academically and intellectually, they are also establishing and maintaining personal relationships, developing an identity, deciding about a career and lifestyle, and maintaining personal health and wellness. Many students are interacting with people from diverse backgrounds who hold different values and making new friends. Some are also adapting to living away from home for the very first time ( Inkelas et al., 2007 ).

The concept of academic development involves not only academic abilities, but motivational factors, and institutional commitment. Motivation to learn, taking actions to meet academic demands, a clear sense of purpose, and general satisfaction with the academic environment are also important components of the academic field ( Lau, 2003 ).

A second dimension, the social field, may be as important as academic factors. Writers have emphasized integration into the social environment as a crucial element in commitment to a particular academic institution ( Tinto, 1975 ). Becoming integrated into the social life of college, forming a support network, and managing new social freedoms are some important elements of social development. Crises in the social field include conflict in a living situation, starting or maintaining relationships, interpersonal conflicts, family issues, and financial issues ( McGrath, 2005 ), which are manifested as feelings of loneliness ( Clark et al., 2015 ).

In the emotional field, students commonly question their relationships, direction in life, and self-worth ( Rey et al., 2011 ). A balanced personality is one which is emotionally adjusted. Emotional adjustment is essential for creating a sound personality. physical, intellectual mental and esthetical adjustments are possible when emotional adjustment is made ( Ziapour et al., 2018 ). Inner disorders may result from questions about identity and can sometimes lead to personal crises ( Gerdes and Mallinckrodt, 1994 ). Emotional problems may be manifested as global psychological distress, somatic distress, anxiety, low self-esteem, or depression. Impediments to success in emotional development include depression and anxiety, stress, substance abuse, and relationship problems ( Beebe, 2010 ).

The current study is designed to address two research questions: (1) does cyberbullying affect college students' emotional state, as measured by the nine factors of the College Adjustment Scales ( Anton and Reed, 1991 ); (2) which mode of cyberbullying most affects students' emotional state?

2.1. Research settings and participants

The present study is set in Israeli higher education colleges. These, function as: (1) institutions offering undergraduate programs in a limited number of disciplinary fields (mainly the social sciences), (2) centers for training studies (i.e.: teacher training curricula), as well as (3) as creators of access to higher education. The general student population is heterogeneous, coming from the Western Galilee. In this study, 638 Israeli undergraduate students participated. The sample is a representative of the population of the Western galilee in Israel. The sample was 76% female, 70% single, 51% Jewish, 27% Arabs, 7% Druze, and 15% other ethnicity. On the dimension of religiosity, 47% were secular, 37% traditional, 12% religious, 0.5% very religious, and 3.5% other. On the dimension of sexual orientation, 71% were straight women, 23.5% straight men, 4% bisexual, 1% lesbians, and 0.5% gay males (note: according to the Williams Institute, approximately 4% of the population in the US are LGBT, [ Gates, 2011 ], while 6% of the EU population are LGBT, [ Dalia, 2016 ]).

2.2. Instrumentation

Two instruments were used to collect data: The Revised Cyber Bullying Survey (RCBS), with a Cronbach's alpha ranging from .74 to .91 ( Kowalski and Limber, 2007 ), designed to measure incidence, frequency and medium used to perpetrate cyberbullying. The survey is a 32-item questionnaire. The frequency was investigated using a 5-item scale with anchors ranging from ‘it has never happened to me’ to ‘several times a week’. Five different media were explored: email, instant messaging, chat room, text messaging, and social networking sites. Each medium was examined with the same six questions related to cases of cyberbullying (see Table 1 ).

Description of the Revised Cyber Bullying Survey (RCBS) variables.

Note: the theoretical range is between zero to twenty-four.

Table 1 shows the five variables that composed the RCBS questionnaire (all of the variables are composed of 6 statements). The results indicate that the levels of all the variables is very low, which means that the respondents experienced cyberbullying once or twice. The internal consistency reliability estimate based on the current sample suggested that most of the variables have an adequate to high level of reliability, with a Cronbach's alpha of 0.68–0.87.

The College Adjustment Scales (CAS) ( Anton and Reed, 1991 ), evaluated the academic, social, and emotional development of college students. Values were standardized and validated for use with college students. The validity for each subscale ranged from .64 to .80, noting high correlations among scales. Reliability of the scales ranged from .80 to .92, with a mean of .86. The instrument included 128 items, divided into 10 scales: anxiety, depression, suicidal ideation, substance abuse, self-esteem problems, interpersonal problems, family problems, academic problems, career problems, and regular activities (see Table 2 ). Students responded to each item using a four-point scale.

Description of CAS variables.

Anxiety: A measure of clinical anxiety, focusing on common affective, cognitive, and physiological symptoms.

Depression: A measure of clinical depression, focusing on common affective, cognitive, and physiological symptoms.

Suicidal Ideation: A measure of the extent of recent ideation reflecting suicide, including thoughts of suicide, hopelessness, and resignation.

Substance Abuse: A measure of the extent of disruption in interpersonal, social, academic, and vocational functioning as a result of substance use and abuse.

Self-esteem Problems: A measure of global self-esteem which taps negative self-evaluations and dissatisfaction with personal achievement.

Interpersonal Problems: A measure of the extent of problems in relating to others in the campus environment.

Family Problems: A measure of difficulties experienced in relationships with family members.

Academic Problems: A measure of the extent of problems related to academic performance.

Career Problems: A measure of the extent of problems related to career choice.

Participants also responded to a demographic questionnaire that included items on gender, birth year, marital status, ethnicity, and sexual orientation. As sexual orientation is a major cause for bullying ( Pollock, 2006 ; Cahill and Makadon, 2014 ), it was included in the background information.

Convenience sampling and purposive sampling were used for this study. Surveys with written instructions were administered in classrooms, libraries and online via Google Docs at the end of the semester.

The surveys were translated to Hebrew and back translated four times until sufficient translation was achieved. The research was approved by the Western Galilee College Research and Ethic Committee.

A sizeable percentage, 57.4% (366), of the respondents reported being cyber bullied at least once and 3.4% (22) reported being cyber bullied at least once a week. The types of bullies can be seen in Fig. 1 .

Types of bullies.

Three variables were found to have significant influences on the research variables: (1) gender (see Table 3 ); (2) religion (see Table 4 ); and (3) sexual preferences (see Table 5 ).

Results of independent t-tests for research variables by gender.

Note: n male = 127, n female = 510, *p < .05.

Results of independent t-tests for research variables by level of religion.

Note: n religious = 345, n secular = 293, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Results of independent t-tests for research variables by sexual preference.

Note: n heterosexual = 596, n other = 42, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Independent t-tests between the CAS variables and gender show significant differences between females and males (see Table 3 ).

Independent t-tests between the CAS variables and level of religiosity show significant differences between secular and religious persons, i.e., observant believers (see Table 4 ).

Independent t-tests between the CAS variables and sexual preference show significant differences between heterosexual individuals and others (see Table 5 ).

The research population was divided into three age groups having five year intervals. One respondent who was 14 years old was removed from the population.

For the variable “career problems” it was found that there was a significant difference between the 26–30 year age group [p < .05, F(2,5815) = 3.49, M = 56.55] and the 31–35 (M = 56.07) as well as the 20–25 (M = 54.58) age groups.

For the variable "depression" it was found that there was a significant difference between the 20–25 year age group [p < .05, F(2,5815) = 3.84, M = 54.56] and the 31–35 (M = 51.61) as well as the 26–30 (M = 52.83) age groups.

For the variable “interpersonal problems” it was found that there was a significant difference between the 20–25 year age group [p < .06, F(2,5815) = 3.84, M = 53.85] and the 31–35 (M = 51.29) as well as the 26–30 (M = 52.19) age groups.

For the variable “suicidal ideation” it was found that there was a significant difference between the 20–25 year age group [p < .06, F(2,5815) = 3.84, M = 55.45] and the 31–35 (M = 49.71) as well as the 26–30 (M = 50.13) age groups (see Table 6 ).

Results of one way Anova for research variables by age.

Note: n 20-25 = 216, n 26-30 = 287, n 31-35 = 82, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

To confirm that there was no effect among the independent variables, a Pearson correlation analysis of cyberbullying with CAS variables was run. As the correlations between the independent variables are weak, no multicollinearity between them was noted (see Table 7 ).

Pearson correlation of cyberbullying with CAS variables.

Note: n = 638, ∼ p < .06, ∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001.

Regression analyses on the effect of the cyberbullying variables on the CAS variables (see Fig. 2 ) show that an increase in cyberbullying by social networking and IM increases the academic problems variable. The model explained 6.1% of the variance (F (13,585) = 2.94, p < .001) and shows an increase in the suicidal ideation variable. There is also a marginal effect of cyberbullying by SMS on suicidal ideation, revealing that an increase in cyberbullying by SMS causes a decrease in suicidal ideation. The explained variance of the model is 24.8% (F (11,584) = 14.80, p < .001). Higher cyberbullying by social networking results in an increase in the anxiety variable. The explained variance of the model is 8.8% (F (13,584) = 4.32, p < .001). An increase in cyberbullying by chat and IM shows an increase in the substance abuse variable. The model explains 13% of the variance (F (13,584) = 6.71, p < .001). Increasing cyberbullying by social networking and IM increases the self-esteem problems variable. The explained variance of the model is 9% (F (13,584) = 4.43, p < .001). An increase of cyberbullying by email increases the problems students have with regular activities. The explained variance of the model is 5.2% (F (13,575) = 2.44, p < .01). Heightened cyberbullying by social networking and IM increases students' interpersonal problems. There is also an effect of cyberbullying by IM on suicidal ideation, such that an increase in cyberbullying by IM causes a decrease in interpersonal problems. The explained variance of the model is 8% (F (13,584) = 3.89, p < .001). An increase in cyberbullying by SMS decreases the family problems variable. The explained variance of the model is 11.4% (F (13,584) = 5.76, p < .001). And finally, heightened cyberbullying by IM and social networking decreases the depression variable. The variance explained by the model is 11.9% (F (13,584) = 6.04, p < .001).

The influence of academic cyberbullying variables on the CAS variables.

4. Discussion

The objective of this study was to fill an existing gap in the literature regarding the influence of cyberbullying on the academic, social, and emotional development of undergraduate students.

As has been presented, cyberbullying continues to be a disturbing trend not only among adolescents but also undergraduate students. Cyberbullying exists in colleges and universities, and it has an influence on the development of students. Fifty seven percent of the undergraduate students who participated in this study had experienced cyberbullying at least once during their time in college. As previous studies have found that cyberbullying incidents among college students can range from 9% to 50% ( Baldasare et al., 2012 ; Beebe, 2010 ) it seems that 57% is high. Considering the effect of smartphone abundance on one hand and on the other the increasing use of online services and activities by young-adults can explain that percentage.

Considering the effect of such an encounter on the academic, social and emotional development of undergraduate students, policy makers face a formidable task to address the relevant issues and to take corrective action as Myers and Cowie (2017) point out that due to the fact that universities are in the business of education, it is a fine balancing act between addressing the problem, in this case cyberbullying, and maintaining a duty of care to both the victim and the perpetrator to ensure they get their degrees. There is a clear tension for university authorities between acknowledging that university students are independent young adults, each responsible for his or her own actions, on one hand, and providing supervision and monitoring to ensure students' safety in educational and leisure contexts.

Although there are increasing reports on connections between cyberbullying and social-networks (see: Gahagan et al., 2016 ), sending SMS or MMS messages through Internet gateways ensures anonymity, thus indirectly supporting cyberbullying. A lot of websites require only login or a phone number that can also be made up ( Gálik et al., 2018 ) which can explain the fact that instant-messaging (IM) was found to be the most common means of cyberbullying among undergraduate students with a negative influence on academic, family, and emotional development (depression, anxiety, and suicidal ideation). A possible interpretation of the higher frequency of cyberbullying through IM may be that young adults have a need to be connected.

This medium allows for being online in ‘real time’ with many peers or groups. With the possibility of remaining anonymous (by creating an avatar – a fake profile) and the possibility of exposing private information that remains recorded, students who use instant messaging become easy targets for cyberbullying. IM apps such as WhatsApp are extremely popular as they allow messages, photos, videos, and recordings to be shared and spread widely and in real time.

Students use the Internet as a medium and use it with great frequency in their everyday lives. As more aspects of students' lives and daily affairs are conducted online, coupled with the fact that excessive use may have consequences, it is important for researchers and academic policy makers to study the phenomenon of cyberbullying more deeply.

Sexual orientation is also a significant factor that increases the risk of victimization. Similarly, Rivers (2016) documented the rising incidence of homophobic and transphobic bullying at university and argues strongly for universities to be more active in promoting tolerance and inclusion on campus. It is worth noting that relationships and sexual orientation probably play a huge role in bullying among university students due to their age and the fact that the majority of students are away from home and experiencing different forms of relationships for the first time. Faucher et al. (2014) actually found that same sex cyberbullying was more common at university level than at school. Nonetheless, the research is just not there yet to make firm conclusions.

Finally, cyberbullying is not only an adolescent issue. Although its existence has been proven, studies of cyberbullying among undergraduate students have not been fully developed. This particular population needs special attention in future research.

The results of this study indicate that cyberbullying has an influence on the academic, social, and emotional development of undergraduate students.

In the academic field, findings revealed a statistically significant correlation between cyberbullying perpetrated by email and academic problems. Relationships between academic problems and cyberbullying perpetrated by other media were not found. This suggests that cyberbullying through instant messaging, chat room, text messaging, and social networking sites, have not influenced academic abilities, motivation to learn, and general satisfaction with the academic environment. However, cyberbullying perpetrated by email has an influence on academics, perhaps because of the high use of this medium among undergraduate students.

With regard to career problems, correlations with cyberbullying were not found. This indicates that cyberbullying has no influence on career problems, perhaps because these kinds of problems are related to future career inspirations, and not to the day-to-day aspects of a student's life.

In the social field, it was found that interpersonal problems such as integration into the social environment, forming a support network, and managing new social freedoms, were related to cyberbullying via social networking sites. This finding is consistent with the high use of social networking sites, the purpose of the medium, and the reported episodes of cyberbullying in that medium.

Family problems were also related to cyberbullying perpetrated by all kinds of media. This may indicate that as cyberbullying through the use of email, instant messaging, chat rooms, text messaging, and social networking sites increases, so do family problems. This could be due to the strong influence that cyberbullying generates in all the frameworks of students, including their families.

Finally, in the emotional field, correlations between cyberbullying perpetrated by all kinds of media and substance abuse were found. This may indicate that as cyberbullying through the use of email, instant messaging, chat rooms, text messaging, and social networking sites increases, so does substance abuse. This is important because cyberbullying may be another risk factor for increasing the probability of substance abuse.

Depression and suicidal ideation were significantly related to the same media – email instant messaging and chat cyberbullying – suggesting that depression may lead to a decision of suicide as a solution to the problem. Previous findings support the above that being an undergraduate student – a victim of cyberbullying emerges as an additional risk factor for the development of depressive symptoms ( Myers and Cowie, 2017 ). Also Selkie et al. (2015) reported among 265 female college students, being engaged in cyberbullying as bullies, victims, or both led to higher rates of depression and alcohol use.

Relationships between anxiety and cyberbullying, through all the media, were not found although Schenk and Fremouw (2012) found that college student victims of cyberbullying scored higher than matched controls on measures of depression, anxiety, phobic anxiety, and paranoia. This may be because it was demonstrated that anxiety is one of the most common reported mental health problems in all undergraduate students, cyberbullied or not.

Self-esteem problems were significantly related to cyberbullying via instant messaging, social networking sites, and text messaging. This may suggest that as cyberbullying through instant messaging, social networking sites, and text messaging increases, so do self-esteem problems. This is an important finding, given that these were the media with more reported episodes of cyberbullying.

5. Conclusions

This findings of this study revealed that cyberbullying exists in colleges and universities, and it has an influence on the academic, social, and emotional development of undergraduate students.

It was shown that cyberbullying is perpetrated through multiple electronic media such as email, instant messaging, chat rooms, text messaging, and social networking sites. Also, it was demonstrated that students exposed to cyberbullying experience academic problems, interpersonal problems, family problems, depression, substance abuse, suicidal ideation, and self-esteem problems.

Students have exhibited clear preferences towards using the Internet as a medium and utilize it with great frequency in their everyday lives. As more and more aspects of students' lives are conducted online, and with the knowledge that excessive use may have consequences for them, it is important to study the phenomenon of cyberbullying more deeply.

Because college students are preparing to enter the workforce, and several studies have indicated a trend of cyberbullying behavior and victimization throughout a person's lifetime ( Watts et al., 2017 ), the concern is these young adults are bringing these attitudes into the workplace.

Finally, cyberbullying is not only an adolescent issue. Given that studies of cyberbullying among undergraduate students are not fully developed, although existence of the phenomenon is proven, we conclude that the college and university population needs special attention in future areas of research. As it has been indicated by Peled et al. (2012) that firm policy in regard to academic cheating reduces its occurrence, colleges should draw clear guidelines to deal with the problem of cyberbullying, part of it should be a safe and if needed anonymous report system as well as clear punishing policy for perpetrators.

As there's very little research on the effect of cyberbullying on undergraduates students, especially in light of the availability of hand held devices (mainly smartphones) and the dependence on the internet for basically every and any activity, the additional data provided in this research adds to the understanding of the effect of cyberbullying on the welfare of undergraduate students.

Declarations

Author contribution statement.

Yehuda Peled: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Competing interest statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

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