hypothesis on bullying

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

111k Accesses

18 Citations

37 Altmetric

Metrics details

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

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

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

Conclusions

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

Introduction

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

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

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

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

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

Participants

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

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

Study outcome

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

Primary exposure

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

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

Statistical analyses

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

Prevalence of bullying at school and mental health problems

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

Associations between bullying at school and mental health problems

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

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

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

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

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

Strengths and limitations

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

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

Availability of data and materials

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

Code availability

Not applicable.

Olweus D. School bullying: development and some important challenges. Ann Rev Clin Psychol. 2013;9(9):751–80. https://doi.org/10.1146/annurev-clinpsy-050212-185516 .

Article Google Scholar

Arseneault L, Bowes L, Shakoor S. Bullying victimization in youths and mental health problems: “Much ado about nothing”? Psychol Med. 2010;40(5):717–29. https://doi.org/10.1017/S0033291709991383 .

Article CAS PubMed Google Scholar

Arseneault L. The long-term impact of bullying victimization on mental health. World Psychiatry. 2017;16(1):27–8. https://doi.org/10.1002/wps.20399 .

Article PubMed PubMed Central Google Scholar

Moore SE, Norman RE, Suetani S, Thomas HJ, Sly PD, Scott JG. Consequences of bullying victimization in childhood and adolescence: a systematic review and meta-analysis. World J Psychiatry. 2017;7(1):60–76. https://doi.org/10.5498/wjp.v7.i1.60 .

Hagquist C, Due P, Torsheim T, Valimaa R. Cross-country comparisons of trends in adolescent psychosomatic symptoms—a Rasch analysis of HBSC data from four Nordic countries. Health Qual Life Outcomes. 2019;17(1):27. https://doi.org/10.1186/s12955-019-1097-x .

Deighton J, Lereya ST, Casey P, Patalay P, Humphrey N, Wolpert M. Prevalence of mental health problems in schools: poverty and other risk factors among 28 000 adolescents in England. Br J Psychiatry. 2019;215(3):565–7. https://doi.org/10.1192/bjp.2019.19 .

Article PubMed Central Google Scholar

Le HTH, Tran N, Campbell MA, Gatton ML, Nguyen HT, Dunne MP. Mental health problems both precede and follow bullying among adolescents and the effects differ by gender: a cross-lagged panel analysis of school-based longitudinal data in Vietnam. Int J Ment Health Syst. 2019. https://doi.org/10.1186/s13033-019-0291-x .

Bayer JK, Mundy L, Stokes I, Hearps S, Allen N, Patton G. Bullying, mental health and friendship in Australian primary school children. Child Adolesc Ment Health. 2018;23(4):334–40. https://doi.org/10.1111/camh.12261 .

Article PubMed Google Scholar

Hysing M, Askeland KG, La Greca AM, Solberg ME, Breivik K, Sivertsen B. Bullying involvement in adolescence: implications for sleep, mental health, and academic outcomes. J Interpers Violence. 2019. https://doi.org/10.1177/0886260519853409 .

Hogberg B, Strandh M, Hagquist C. Gender and secular trends in adolescent mental health over 24 years—the role of school-related stress. Soc Sci Med. 2020. https://doi.org/10.1016/j.socscimed.2020.112890 .

Kidger J, Araya R, Donovan J, Gunnell D. The effect of the school environment on the emotional health of adolescents: a systematic review. Pediatrics. 2012;129(5):925–49. https://doi.org/10.1542/peds.2011-2248 .

Saminathen MG, Låftman SB, Modin B. En fungerande skola för alla: skolmiljön som skyddsfaktor för ungas psykiska välbefinnande. [A functioning school for all: the school environment as a protective factor for young people’s mental well-being]. Socialmedicinsk tidskrift [Soc Med]. 2020;97(5–6):804–16.

Google Scholar

Bibou-Nakou I, Tsiantis J, Assimopoulos H, Chatzilambou P, Giannakopoulou D. School factors related to bullying: a qualitative study of early adolescent students. Soc Psychol Educ. 2012;15(2):125–45. https://doi.org/10.1007/s11218-012-9179-1 .

Vukojevic M, Zovko A, Talic I, Tanovic M, Resic B, Vrdoljak I, Splavski B. Parental socioeconomic status as a predictor of physical and mental health outcomes in children—literature review. Acta Clin Croat. 2017;56(4):742–8. https://doi.org/10.20471/acc.2017.56.04.23 .

Reiss F. Socioeconomic inequalities and mental health problems in children and adolescents: a systematic review. Soc Sci Med. 2013;90:24–31. https://doi.org/10.1016/j.socscimed.2013.04.026 .

Stockholm City. Stockholmsenkät (The Stockholm Student Survey). 2021. https://start.stockholm/aktuellt/nyheter/2020/09/presstraff-stockholmsenkaten-2020/ . Accessed 19 Nov 2021.

Zeebari Z, Lundin A, Dickman PW, Hallgren M. Are changes in alcohol consumption among swedish youth really occurring “in concert”? A new perspective using quantile regression. Alc Alcohol. 2017;52(4):487–95. https://doi.org/10.1093/alcalc/agx020 .

Hagquist C. Psychometric properties of the PsychoSomatic Problems Scale: a Rasch analysis on adolescent data. Social Indicat Res. 2008;86(3):511–23. https://doi.org/10.1007/s11205-007-9186-3 .

Hagquist C. Ungas psykiska hälsa i Sverige–komplexa trender och stora kunskapsluckor [Young people’s mental health in Sweden—complex trends and large knowledge gaps]. Socialmedicinsk tidskrift [Soc Med]. 2013;90(5):671–83.

Wu W, West SG. Detecting misspecification in mean structures for growth curve models: performance of pseudo R(2)s and concordance correlation coefficients. Struct Equ Model. 2013;20(3):455–78. https://doi.org/10.1080/10705511.2013.797829 .

Holt MK, Espelage DL. Perceived social support among bullies, victims, and bully-victims. J Youth Adolscence. 2007;36(8):984–94. https://doi.org/10.1007/s10964-006-9153-3 .

Mark L, Varnik A, Sisask M. Who suffers most from being involved in bullying-bully, victim, or bully-victim? J Sch Health. 2019;89(2):136–44. https://doi.org/10.1111/josh.12720 .

Tsaousis I. The relationship of self-esteem to bullying perpetration and peer victimization among schoolchildren and adolescents: a meta-analytic review. Aggress Violent Behav. 2016;31:186–99. https://doi.org/10.1016/j.avb.2016.09.005 .

Veldkamp SAM, Boomsma DI, de Zeeuw EL, van Beijsterveldt CEM, Bartels M, Dolan CV, van Bergen E. Genetic and environmental influences on different forms of bullying perpetration, bullying victimization, and their co-occurrence. Behav Genet. 2019;49(5):432–43. https://doi.org/10.1007/s10519-019-09968-5 .

Janssen I, Craig WM, Boyce WF, Pickett W. Associations between overweight and obesity with bullying behaviors in school-aged children. Pediatrics. 2004;113(5):1187–94. https://doi.org/10.1542/peds.113.5.1187 .

Kelly EV, Newton NC, Stapinski LA, Conrod PJ, Barrett EL, Champion KE, Teesson M. A novel approach to tackling bullying in schools: personality-targeted intervention for adolescent victims and bullies in Australia. J Am Acad Child Adolesc Psychiatry. 2020;59(4):508. https://doi.org/10.1016/j.jaac.2019.04.010 .

Gunnell D, Kidger J, Elvidge H. Adolescent mental health in crisis. BMJ. 2018. https://doi.org/10.1136/bmj.k2608 .

O’Reilly M, Dogra N, Whiteman N, Hughes J, Eruyar S, Reilly P. Is social media bad for mental health and wellbeing? Exploring the perspectives of adolescents. Clin Child Psychol Psychiatry. 2018;23:601–13.

Unnever JD, Cornell DG. Middle school victims of bullying: who reports being bullied? Aggr Behav. 2004;30(5):373–88. https://doi.org/10.1002/ab.20030 .

Download references

Acknowledgements

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

Open access funding provided by Karolinska Institute. None to declare.

Author information

Authors and affiliations.

Stockholm Prevents Alcohol and Drug Problems (STAD), Center for Addiction Research and Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden

Håkan Källmén

Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Global Public Health, Karolinska Institutet, Level 6, Solnavägen 1e, Solna, Sweden

Mats Hallgren

You can also search for this author in PubMed Google Scholar

Contributions

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.

Corresponding author

Correspondence to Mats Hallgren .

Ethics declarations

Ethics approval and consent to participate.

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).

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1..

Principal factor analysis description.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

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

Download citation

Received : 05 October 2021

Accepted : 23 November 2021

Published : 14 December 2021

DOI : https://doi.org/10.1186/s13034-021-00425-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Mental health
Adolescents
School-related factors
Gender differences

Child and Adolescent Psychiatry and Mental Health

ISSN: 1753-2000

Submission enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

Search in PubMed
Search in NLM Catalog
Add to Search

Four decades of research on school bullying: An introduction

Affiliations.

1 Faculty of Education, Department of Educational and Counselling Psychology and Special Education.
2 Faculty of Education, Department of Educational Psychology, University of Nebraska-Lincoln.
PMID: 25961310
DOI: 10.1037/a0038928

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

PubMed Disclaimer

Publication types

Search in MeSH

Related information

Cited in Books

LinkOut - more resources

Full text sources.

American Psychological Association
Ovid Technologies, Inc.
MedlinePlus Health Information

Miscellaneous

NCI CPTAC Assay Portal
Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
Wiley Open Access Collection

Psychological processes in young bullies versus bully‐victims

Anouk van dijk.

1 Department of Psychology, Utrecht University, Utrecht, The Netherlands

Astrid M. G. Poorthuis

2 Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, The Netherlands

3 Department of Psychology, University of Toronto, Mississauga, Ontario, Canada

Associated Data

Additional Supporting Information may be found online in the supporting information tab for this article.

Some children who bully others are also victimized themselves (“bully‐victims”) whereas others are not victimized themselves (“bullies”). These subgroups have been shown to differ in their social functioning as early as in kindergarten. What is less clear are the motives that underlie the bullying behavior of young bullies and bully‐victims. The present study examined whether bullies have proactive motives for aggression and anticipate to feel happy after victimizing others, whereas bully‐victims have reactive motives for aggression, poor theory of mind skills, and attribute hostile intent to others. This “distinct processes hypothesis” was contrasted with the “shared processes hypothesis,” predicting that bullies and bully‐victims do not differ on these psychological processes. Children ( n = 283, age 4–9) were classified as bully, bully‐victim, or noninvolved using peer‐nominations. Theory of mind, hostile intent attributions, and happy victimizer emotions were assessed using standard vignettes and false‐belief tasks; reactive and proactive motives were assessed using teacher‐reports. We tested our hypotheses using Bayesian model selection, enabling us to directly compare the distinct processes model (predicting that bullies and bully‐victims deviate from noninvolved children on different psychological processes) against the shared processes model (predicting that bullies and bully‐victims deviate from noninvolved children on all psychological processes alike). Overall, the shared processes model received more support than the distinct processes model. These results suggest that in early childhood, bullies and bully‐victims have shared, rather than distinct psychological processes underlying their bullying behavior.

1. INTRODUCTION

Bullying among children occurs as early as in kindergarten and potentially has severe negative consequences (Vlachou, Andreou, Botsoglou, & Didaskalou, 2011 ). Young children who bully others are at risk of behavior problems, peer problems, and health problems (Wolke, Woods, Bloomfield, & Karstadt, 2000 , 2001 ). In later childhood, these children also are at risk of poor psychosocial adjustment, including low academic achievement, lack of friendships, and psychiatric symptoms (Kumpulainen et al., 1998 ; Nansel et al., 2001 ). Given the aversive outcomes associated with bullying, it is important to better understand underlying psychological processes of bullying at an early age, as to prevent escalation in later childhood.

About 10–14% of kindergartners bully others and are also victimized themselves (labeled “bully‐victims”), whereas about 4–17% of kindergartners bully others but are not victimized themselves (labeled “bullies”; Jansen et al., 2012 ; Wolke, Woods, Stanford, & Schulz, 2001 ). Young bullies and bully‐victims have been shown to differ in their social functioning. For example, research has shown that young bully‐victims have fewer friends than their noninvolved peers, are less likely to affiliate with noninvolved classmates, and are more likely to be rejected by their classmates. In contrast, young bullies have as many friends as their noninvolved peers are equally likely to affiliate with noninvolved classmates, and seem to have a controversial status in their class: they are more likely to be rejected, but are also more likely to be popular (Farmer et al., 2010 ; Perren & Alsaker, 2006 ). Thus, bullies appear to be well‐integrated in their class at an early age, whereas bully‐victims are typically marginalized (Griffin & Gross, 2004 ; Vlachou et al., 2011 ).

1.1. Distinct psychological processes in young bullies versus bully‐victims

The observation that young bullies and bully‐victims have different social positions in their class has led researchers to theorize that bullying behavior in these two subgroups may be driven by distinct motives. It has been proposed that bullies are more motivated by proactive reasons, such as gaining social status or getting their way, whereas bully‐victims are more motivated by reactive reasons, such as feeling angry or repelling perceived social threats (e.g., Griffin & Gross, 2004 ; Olweus, 1978 ; Rodkin, Espelage, & Hanish, 2015 ; Vlachou et al., 2011 ). In line with this argument, researchers have suggested that certain psychological processes may underlie the bullying behavior of bullies but not bully‐victims, or vice versa (e.g., Camodeca, Goossens, Schuengel, & Terwogt, 2003 ; Gasser & Keller, 2009 ). We here investigate this “distinct processes hypothesis,” focusing on three psychological processes that are related to bullying behavior in early childhood.

First, bully‐victims (but not bullies) may have poor theory of mind skills, or a limited ability to take another person's perspective. This notion is based on conflicting findings regarding theory of mind skills in aggressive children. On the one hand, research has shown that hard‐to‐manage preschoolers with poor theory of mind skills tend to behave more negatively towards their peers (i.e., they showed more insulting, whining, and controlling behavior while playing a game; Hughes, Cutting, & Dunn, 2001 ). This finding suggests that children may bully others because they insufficiently comprehend their peers’ mental states. On the other hand, research has shown that a subgroup of “ringleader” bullies have intact theory of mind skills and in fact may use these skills to manipulate others (Sutton, Smith, & Swettenham, 1999 ). Given the distinction in social functioning between bullies and bully‐victims, it has been proposed that these conflicting findings apply to different subgroups of bullies: Poor theory of mind skills may characterize bully‐victims, but not the subgroup of socially well‐integrated bullies (Gasser & Keller, 2009 ).

Second, bully‐victims (but not bullies) may tend to interpret their peers’ intentions as hostile. Such “hostile intent attributions” are uniquely related to reactive aggression (Arsenio, Adams, & Gold, 2009 ; Dodge & Coie, 1987 ) and as such may characterize bully‐victims, who engage in bullying as they respond to the perceived hostility of their peers’ behavior (Camodeca et al., 2003 ). In contrast, bullies who are not victimized themselves may be less inclined to perceive hostility in their peers’ behavior.

Third, bullies (but not bully‐victims) may tend to anticipate feeling positive emotions after victimizing others. Such “happy victimizer emotions” are uniquely related to proactive aggression (Arsenio et al., 2009 ; Dodge, Lochman, Harnish, Bates, & Pettit, 1997 ) and as such may characterize bullies, who tend to initiate aggressive behavior as they focus on their own gains rather than the victim's feelings (Gasser & Keller, 2009 ). In contrast, bully‐victims may not be characterized by happy victimizer emotions, as they are victimized themselves and thus may be more likely to empathize with the victim (Menesini et al., 2003 ).

In sum, the distinct processes hypothesis predicts that bullies and bully‐victims may have distinct psychological processes underlying their bullying behavior, where as bullies may have proactive motives for aggression and attribute happiness to themselves as victimizer, bully‐victims may have reactive motives for aggression, poor theory of mind skills, and a tendency to attribute hostile intent (Table 1 , left).

Two hypotheses on psychological processes in children involved in bullying (B) versus Bullying and Victimization (BV) as compared to noninvolved children (NC)

	H : Distinct processes	H : Shared processes
Theory of mind errors	BV > NC, B	B, BV > NC
Hostile intent attributions	BV > NC, B	B, BV > NC
Happy victimizer emotions	B > NC, BV	B, BV > NC
Reactive motives	BV > NC, B	B, BV > NC
Proactive motives	B > NC, BV	B, BV > NC

1.2. Empirical evidence for distinct psychological processes in bullies versus bully‐victims

Empirical research comparing psychological processes between bullies and bully‐victims is scarce, particularly in early childhood. Hence, we here discuss research from early childhood to adolescence. To this date, the evidence for the distinct processes hypothesis is mixed, with some studies finding differences between bullies and bully‐victims but others not. For theory of mind skills, the evidence is inconsistent: One study found that bully‐victims (age 7–8) had poorer theory of mind skills than bullies (Gasser & Keller, 2009 ) whereas another, longitudinal study found no differences in theory of mind skills at age 5 between children who were classified as either bully or bully‐victim at age 12 (Shakoor et al., 2012 ). For hostile intent attributions, the evidence is inconsistent as well: One study found that bully‐victims attributed more blame to hypothetical peers than bullies (Camodeca et al., 2003 ), whereas another study found that bullies and bully‐victims (age 13–14) both expected hostile behavior from hypothetical peers (Ziv, Leibovich, & Shechtman, 2013 ). For happy victimizer emotions, the evidence for the distinct processes hypothesis is very limited: The two studies that addressed this question did not find that bullies had more happy victimizer emotions than bully‐victims, at age 7–8 (Gasser & Keller, 2009 ) nor at age 12–18 (Perren, Gutzwiller‐Helfenfinger, Malti, & Hymel, 2012 ). Last, the evidence for distinct aggression motives in bullies and bully‐victims as well is very limited: Four studies found that bullies and bully‐victims both had reactive and proactive motives for aggression, at age 7–8 (Camodeca, Goossens, Terwogt, & Schuengel, 2002 ) as well as in adolescence (Bettencourt & Farrell, 2013 ; Ragatz, Anderson, Fremouw, & Schwartz, 2011 ; Salmivalli & Nieminen, 2002 ).

Importantly, all of the studies discussed (except Perren et al., 2012 ) did find distinctions in the discussed psychological processes between children involved in bullying (bullies and bully‐victims) and noninvolved children. Thus, these psychological processes do seem important in predicting whether children bully; however, it is unclear whether these processes distinguish bullies from bully‐victims.

1.3. Psychological processes in bullies versus bully‐victims: Distinct or shared?

One explanation for the limited empirical support may be that bullies and bully‐victims in fact do not have different, but rather have shared psychological processes underlying their bullying behavior (Table 1 , right). At first sight, this “shared processes hypothesis” may seem at odds with bullies’ and bully‐victims’ different social positions in their class: Why would the subgroup of well‐integrated bullies have similar psychological processes underlying their bullying behavior as the subgroup of marginalized bully‐victims? Note, however, that bullies and bully‐victims have one important similarity: They both engage in aggressive behavior towards their peers. This behavior markedly differentiates them from children noninvolved in bullying, who may rather use social strategies such as problem‐solving or avoidance to cope with peer problems. Thus, psychological processes may not so much predict from which social position children engage in bullying (i.e., bully or bully‐victim), but rather whether children engage in bullying.

An alternative explanation for the limited empirical support may be that previous research had limitations that hindered the detection of differences between bullies and bully‐victims. Hence, the present study addresses two key limitations of previous research.

First, the studies on reactive and proactive motives used questionnaires that may have been unsuited to detect distinct patterns of reactive and proactive motives in bullies versus bully‐victims. These questionnaires consisted of items that were fixed combinations of one motive with one form of aggressive behavior (e.g., “hurts others to dominate”). As a result, children's motives could have been confounded with their actual aggressive behavior: respondents may have given high ratings to children who frequently hurt others, even though these children did not have the motive to dominate. Illustrative of this confound, such questionnaires typically yield high relations between reactive and proactive motives ( r = .70 as found in a meta‐analysis; Polman, de Castro, Koops, van Boxtel, & Merk, 2007 ). To address this issue, the present study used a questionnaire that assesses children's motives independently of their actual aggressive behavior (Polman, de Castro, Thomaes, & van Aken, 2009 ).

Second, previous research used various methodologies to assess psychological processes and included various age groups, which makes it difficult to interpret the inconsistent findings. To address this issue, the present study tested several psychological processes within one sample, using standard paradigms to assess each process. By using such an integrative approach (Malti, 2016 ) we aimed to optimize the sensitivity of our research design to detect distinct psychological processes underlying the behavior of bullies versus bully‐victims.

1.4. The present study

In sum, previous work has supported two alternative hypotheses (Table 1 ). Theoretical work suggests that young bullies and bully‐victims have distinct psychological processes underlying their bullying behavior (H 1 ; e.g., Griffin & Gross, 2004 ; Olweus, 1978 ; Rodkin et al., 2015 ; Vlachou et al., 2011 ). However, empirical work to this date provides limited support for this hypothesis, which may imply that young bullies and bully‐victims in fact have shared psychological processes underlying their behavior (H 2 ). The present study aimed to test these contrasting hypotheses, assessing several psychological processes within one sample.

Children (age 4–9) were classified as bully, bully‐victim, or noninvolved using peer‐nominations. Children's theory of mind skills, hostile intent attributions, and happy victimizer emotions were assessed using standard vignettes and false‐belief tasks; and their reactive and proactive motives for aggression using teacher‐reports. Our hypotheses were tested using Bayesian model selection; an upcoming statistical approach that in recent years has increasingly been used by researchers in child psychology (Van de Schoot et al., 2014 ). The advantage of this approach is that it quantifies the amount of support from the data for each hypothesis as a coherent model (instead of testing group differences for each variable separately, as would be the case with multivariate analyses). Thus, Bayesian model selection enabled us to conduct a single test that indicates which of the two contrasting hypotheses receives most support from the data.

2. METHODS 1

2.1. participants.

Participants were 283 children aged 4–9, recruited from five primary schools in the Netherlands (59% boys; M age = 6.70, SD = 1.36; 92% European nationalities, 8% other nationalities, such as Moroccan, Surinam, and Turkish). All children received active written parental consent to participate in the study (61% consent, 32% no response, 7% no consent).

2.2. Procedure

Children were individually interviewed in a quiet room in their school. The session lasted 35–45 minutes and was conducted by the first author or one of eight trained research assistants (i.e., female undergraduate psychology students). Children completed three tasks in the following order: (1) hostile intent attributions; (2) theory of mind; and (3) happy victimizer emotions. Last, they completed a peer‐nomination interview to assess bullying and victimization. Teachers reported on children's reactive and proactive motives for aggression. Children received stickers to thank them for their participation; teachers received a gift card.

2.3. Measures

2.3.1. bully groups.

Bullying and victimization were assessed with a peer‐nomination interview developed for use with kindergartners (Perren & Alsaker, 2006 ). Starting the interview, experimenters explained the meaning of the term bullying to children, using four drawings of different types of bullying (i.e., physical, verbal, object‐related, and exclusion; Alsaker, Nägele, Valkanover, & Hauser, 2008 ) and emphasizing that repeated portrayal of these forms of behavior is called bullying. Next, children saw a grid with photographs of their classmates and were asked to identify them all. Using this grid with photographs, children nominated (1) classmates who bully others; and the (2) victims of these bullies.

Scores for bullying and victimization were calculated as the proportion of total possible nominations in the class. This total of nominations was lower than the total number of classmates, because not all children received consent to participate in the study and because we excluded nominations from children ( n = 10) who had poor comprehension of the interview according to experimenter‐ratings (scored on a 5‐point Likert scale after completion of the interview). We also excluded nomination data from five classes ( n = 46) that had participation rates lower than 50%. Bullying scores were significantly correlated with victimization scores ( r = .18, P = .005), and teacher‐rated aggression ( r = .49, P < .001).

Bully groups were created using the mean score in the class. “Bullies” scored above the mean on bullying and below the mean on victimization ( n = 31; 11%). “Bully‐victims” scored above the mean on both bullying and victimization ( n = 45; 16%). “Noninvolved children” scored below the mean on victimization and scored zero on bullying, creating a clear contrast between noninvolved children versus bullies and bully‐victims ( n = 67; 24%). The remaining children were excluded from the main analyses ( n = 140; 50%).

We conducted sensitivity analyses to investigate whether our results were affected by how we created the bully groups. First, we analyzed the data using stricter criteria to create the bully groups: that is, one standard deviation above the mean ( n = 17 bullies; n = 8 bully‐victims) or the 85th percentile ( n = 19 bullies; n = 7 bully‐victims). Second, we analyzed the data using nomination scores as continuous variables, enabling us to include data of all children. Using regression analyses, we tested whether the main effect of bullying on each psychological process was moderated by victimization, which would indicate that children who scored high on bullying and victimization (i.e., “bully‐victims”) had different scores than children who scored high on bullying but low on victimization (i.e., “bullies”). Third, we analyzed the data excluding classes with nomination rates lower than 60% (instead of 50%). All of these sensitivity analyses yielded the same conclusions as our main analysis (see supplementary material).

2.3.2. Theory of mind errors

Theory of mind errors were assessed using two variants of standard false‐belief tasks (for a detailed description see Hughes et al., 2000 ). The first task assessed first‐order false‐belief and belief‐emotion reasoning. Children were introduced to a plush rabbit that really liked smarties. Next, the rabbit left. Children were shown a smarties box and learned that this box actually contained grit instead of smarties. Upon the rabbit's return, children were asked what the rabbit would think was inside the box (first order false‐belief question) and what really was inside the box (reality control question). Next, the experimenter gave the box to the rabbit, and children were asked if the rabbit would feel happy or not happy upon getting the box (belief‐desire question); this question was repeated after the rabbit had opened the box (emotion control question).

The second task assessed first‐ and second‐order false‐belief, and was acted out by the experimenter using toy figurines and a toy house. Children saw a girl putting her ball into a red box. After she left the house, another girl changed the location of the ball from the red box to a blue box. Children were then asked where the girl who went outside would think her ball was (first‐order false‐belief question) and where the ball really was (reality control question). Next, the experimenter showed that the girl who went outside had looked through the window and had seen the other girl move her ball. The girl then returned into the house and children were asked in which box she would search according to the girl who moved the ball (second‐order false‐belief question) and where the ball really was (reality control question).

Children's responses on the four theory of mind questions were scored as correct (score = 0) if they answered both this question and the corresponding control question correctly, and as incorrect (score = 1) if they erred on this question but answered the control question correctly. Responses were coded as missing, if children erred on the control question. Scores were averaged to create a single theory of mind error score. We calculated Cronbach's α for categorical items using categorical principal components analysis (CATPCA; Meulman, Van Der Kooij, & Heiser, 2004 ). Reliability was sufficient ( α =.69).

2.3.3. Hostile intent attributions

Hostile intent attributions were assessed using four vignettes describing a hypothetical interaction between the child and a same‐sex protagonist. The vignettes described ambiguous provocations—that is the protagonist caused a bad outcome, but it was unclear whether this bad outcome was intended (Feshbach, 1989 ). Story themes were provocations familiar to young children: (1) being hurt; (2) a drawing being ruined; (3) being refused to join a game; and (4) a toy being taken. The stories were read aloud by the experimenter and each was accompanied by three 8 × 8 cm black‐and‐white line drawings. Following each vignette, children were asked two questions to assess their intent attributions. First, children were asked why the protagonist had caused the bad outcome. If their response did not reflect a hostile or a benign attribution, they were asked a forced‐choice question (37% of responses; e.g., “did the girl try to ruin your drawing or did she not pay attention?”). Second, children were asked whether the protagonist was trying to be mean or not mean .

Children's intent attributions were coded by two of the female research assistants into the following categories: (a) hostile intent , if children indicated that harm was caused on purpose (15%, e.g., “he was jealous of my drawing”); (b) benign intent , if children indicated that harm was caused by accident (58%, e.g., “I was sitting too close to her arm”); or (c) unclear , if children made both hostile and benign intent attributions, merely remarked upon the story, or did not answer (27%, e.g., “her arm slipped or she wanted to bump me,” “she is sad”). All responses were coded twice and inter‐coder reliability was good ( M κ =.84, range =.78–.90). Coding disagreements (8% of responses) were resolved by discussion, using children's scores on the forced‐choice probe question when available. Hostile intent and mean responses were coded as 1; benign intent and not mean responses were coded as 0. These scores were averaged over the eight questions to create a single hostile intent attribution score. Reliability for categorical items was sufficient: α =.71.

2.3.4. Happy victimizer emotions

Happy victimizer emotions were assessed using four vignettes describing moral transgressions between two same‐sex children of the target child's age (Malti, Gummerum, Keller, & Buchmann, 2009 ). Two stories described the omission of a prosocial duty (i.e., not sharing a pencil with another child; not helping another child who had fallen) and two stories described doing harm (i.e., stealing another child's chocolate; pushing another child off the swing). The stories were read aloud by the experimenter and each was accompanied by three 8 × 8 cm black‐and‐white drawings. Following each vignette, children were asked whether the transgressor's behavior was “okay or not okay?” In line with previous research, all children knew that it was not okay (99% of responses). Next, to assess children's anticipated emotions, they were asked how they would feel if they had been the transgressor in the vignette story. If their answer did not refer to emotions or described neutral or mixed emotions (23% of responses), they were asked a forced‐choice probe question: “would you feel happy or not happy?”

Children's anticipated emotions were coded by two of the research assistants (other than the assistants who coded children's intent attributions) into the following categories: (a) positive emotions (42%; e.g., “happy,” “good,” “fine”); (b) negative emotions (40%; e.g., “bad,” “guilty,” “ashamed”); or (c) other (18%; e.g., “just okay,” “cheeky”). All responses were coded twice and inter‐coder reliability was good ( M κ =.95, range =.93–.99). Coding disagreements (2% of responses) were resolved by discussion. For each vignette, children received a score of 1 if they anticipated positive emotions , and a score of 0 if they anticipated negative emotions . These scores were averaged over the four vignettes to create a single happy victimizer score. Reliability for categorical items was good: α =.87.

2.3.5. Reactive and proactive motives

Reactive and proactive motives were assessed using the Instrument for Reactive and Proactive Aggression (IRPA; Polman et al., 2009 ). Teachers rated the frequency of seven forms of aggressive behavior (i.e., kicking, pushing, hitting, name calling, arguing, gossiping, and doing sneaky things) within the last week, on a 5‐point Likert scale (0 = never , 1 = once , 2 = several times , 3 = every day , 4 = several times a day ). Next, for each form of aggressive behavior that occurred at least once (score > 0), teachers rated three items on reactive motives (e.g., “because this child was angry”) and three items on proactive motives (e.g., “because this child wanted to dominate others”) on a 5‐point Likert scale (0 = never , 1 = rarely , 2 = sometimes , 3 = most of the times , 4 = always ). Thus, both reactive and proactive motive scales had 21 items (i.e., three motive items for each of seven behavior items).

Scores for both on reactive and proactive motives were calculated as the average across the 21 items. Children who never showed any form of aggression received a score of 0 on both motive scales. The internal consistency of the scales was good (reactive motives: α = 85; proactive motives: α =.79). Scores on the frequency of aggressive behavior were calculated by averaging teachers’ ratings on the seven behavior items ( α =.79).

2.4. Data analysis strategy

We tested our two contrasting hypotheses using Bayesian Inequality and Equality constrained Model Selection (BIEMS), applying the software's default settings (i.e., objective priors; Mulder, Hoijtink, & de Leeuw, 2012 ). Using BIEMS enabled us to test our hypotheses as coherent models (instead of testing differences between bullies and bully‐victims for each psychological process separately). Thus, this statistical approach enabled us to conduct a single test that directly indicates which hypothesis receives most support from the data.

First, each hypothesis was translated into a model using inequality constraints on the means to specify the expected differences between the bully groups for each variable. For instance, the distinct processes hypothesis predicts that bully‐victims make more theory of mind errors than both bullies and noninvolved children, which was specified with the inequality constraints [ M bully‐victim > M bully] and [ M bully‐victim > M noninvolved]. In contrast, the shared processes hypothesis predicts that both bullies and bully‐victims make more theory of mind errors than noninvolved children, which was specified as [ M bully > M noninvolved] and [ M bully‐victim > M noninvolved].

Next, we evaluated these models. Bayesian model selection does not rely on significance testing or P‐ values but instead computes Bayes factors that quantify to what extent the data support one model compared to another. A Bayes factor of 1 indicates equal support for both models; a Bayes factor of >1 indicates support in favor of one model over another (e.g., a Bayes factor of BF modelA > B = 4 indicates that this model A received four times more support from the data than model B). Before testing our hypotheses, we first tested whether each model had a sufficient fit to the data by computing a Bayes factor of the model against the unconstrained (null) model. Next, we tested our two hypotheses against each other by computing the Bayes factor between the two models.

3.1. Preliminary analyses

3.1.1. correlations.

Zero‐order correlations between the study variables are shown in Table 2 . First, as expected, we found negative correlations of age with theory of mind errors, hostile intent attributions, and happy victimizer emotions. Second, most psychological processes were positively correlated to the bully or victim nomination scores—with the exception of happy victimizer emotions, which was related to neither. Third, the correlation between reactive and proactive motives was lower than typically reported in questionnaire studies (i.e., r = .43, compared to r =.70 as found in a meta‐analysis; Polman et al., 2007 ). This relatively low correlation enabled us to study distinct motives in bully and bully‐victim groups, beyond these children's shared tendency to aggress.

Zero‐order correlations between the study variables for the complete sample ( N = 283)

	Sex	Age	B	V	RE	PRO	TOM	HIA	HV
=	283	283	237	237	283	283	280	282	282
Bully nominations (B)	−.37***	.11	–
Victim nominations (V)	.04	−.21**	.18**	–
Reactive motives (RE)	−.22***	.05	.45***	.25***	–
Proactive motives (PRO)	−.08	−.06	.40***	.15*	.43***	–
Theory of mind errors (TOM)	−.00	−.56***	.02	.13*	−.04	.01	–
Hostile intent attributions (HIA)	−.11	−.24***	.13*	−.09	.02	.03	.24***	–
Happy victimizer emotions (HV)	.05	−.15*	−.06	−.02	−.05	−.05	.01	.05	–

Missing scores (i.e., n ≠ 283) indicate that children failed to complete a task (TOM, HIA, HV) or were in a class with <50% participation rate (B, V).

* P < .05, ** P < .01, *** P < .001.

3.1.2. Bully groups

Table 3 shows descriptive statistics for the three bully groups. As can be seen, boys were overrepresented in the bully and bully‐victim groups, whereas girls were overrepresented in the noninvolved group, χ 2 = 27.08, P < .001. There were no significant age differences between the bully groups, F (2, 140) = 1.68, P = .190. A MANOVA indicated that the three bully groups differed in teacher‐rated frequency of aggressive behavior, bully nominations, and victim nominations, F (6, 278) = 38.52, P < .001. Post‐hoc tests showed that bully‐victims received more victim nominations than bullies, but received similar numbers of bully nominations and aggression ratings (Table 3 ), indicating that bullies and bully‐victims were comparable in their levels of bullying and aggressive behavior.

Means (and standard deviations) for age, aggression ratings, bully and victim nominations, and the number (and %) of boys and girls nominated as bully, bully‐victim, or noninvolved

	Bully ( = 31)	Bully‐victim ( = 45)	Noninvolved ( = 67)
Boys	25 (26.3)	40 (42.1)	30 (31.6)
Girls	6 (12.5)	5 (10.4)	37 (77.1)
Age (in years)	6.76 (1.31)	7.21(1.23)	6.80(1.31)
Aggression ratings	0.59 (0.64)	0.49 (0.61)	0.11 (0.22)
Bully nominations	0.36 (0.21)	0.32 (0.18)	0.00 (0.00)
Victim nominations	0.17 (0.12)	0.37 (0.14)	0.12 (0.08)

Groups with different superscripts differ significantly at α < .01.

3.1.3. Sex and age differences

To explore whether the results for the primary analyses differed for boys and girls or by age, we analyzed interaction effects of sex and age with bully group for each psychological process. No moderation effects were found (all p s > .05).

3.2. Primary analyses

Table 4 shows means and standard deviations on the psychological process variables for children nominated as bully, bully‐victim, and noninvolved. The mean differences indicate that bullies and bully‐victims both had higher scores on reactive and proactive motives than noninvolved children; that bullies had higher scores on hostile intent than bully‐victims and noninvolved children; and that there were no differences between the bully groups on theory of mind errors and happy victimizer emotions.

Means (and standard deviations) of psychological process variables for children nominated as bully, bully‐victim, or noninvolved

	Bully ( = 31)	Bully‐victim ( = 45)	Noninvolved ( = 67)
Reactive motives	1.50 (0.94)	1.42 (1.09)	0.42 (0.75)
Proactive motives	1.02 (0.93)	0.89 (1.06)	0.22 (0.49)
Theory of mind errors	0.14 (0.20)	0.10 (0.17)	0.13 (0.24)
Hostile intent attributions	0.45 (0.30)	0.29 (0.26)	0.29 (0.23)
Happy victimizer emotions	0.43 (0.41)	0.43 (0.41)	0.57 (0.42)

To test whether these results—as a pattern—are more in line with the distinct processes hypothesis or the shared processes hypothesis, we used BIEMS to run these two models on the data. First, we assessed the fit of each model by comparing it to the unconstrained (null) model. This analysis yielded BF distinct < 0.01 and BF shared = 0.45. Both Bayes factors were below 1, so this result indicates that neither hypothesis received more support from the data than the unconstrained (null) model.

Next, we reran the analysis excluding happy victimizer emotions, as this variable was unrelated to both bully and victim nominations. This second analysis yielded BF distinct = 0.03 and BF shared = 7.46, indicating that the shared processes model received more support from the data than the unconstrained (null) model, whereas the distinct processes model did not. Last, we computed the evidence for the shared processes model over the distinct processes model by dividing these Bayes factors, yielding BF shared>disctinct = 248.67: the shared processes hypothesis received over two hundred times more support from the data than the distinct processes hypothesis.

4. DISCUSSION

The present study tested two contrasting hypotheses, examining whether young “bullies” and “bully‐victims” have distinct or shared psychological processes underlying their bullying behavior (Table 1 ). The “distinct processes hypothesis” predicts that bullies have proactive motives for aggression and anticipate happiness after victimizing others, whereas bully‐victims have reactive motives for aggression, poor theory of mind skills, and attribute hostile intent to others. In contrast, the “shared processes hypothesis” predicts that bullies and bully‐victims deviate on all psychological processes alike. We analyzed our results using Bayesian model selection, enabling us to conduct a single test to compare our two hypotheses. The data provided 249 times more support for the shared processes hypothesis than for the distinct processes hypothesis.

Taken together, these findings suggest that, at an early age bullies and bully‐victims have shared, rather than distinct, psychological processes underlying their bullying behavior. The support for the shared processes hypothesis implies that psychological processes may not so much predict from which social position children engage in bullying (i.e., bully or bully‐victim), but rather whether children engage in bullying at all. Notably, both bullies and bully‐victims resort to aggressive strategies when interacting with peers (rather than resorting to avoidant or prosocial strategies, for instance). But if bullies and bully‐victims have shared psychological processes, what then explains their different social positions (i.e., bullies are typically well‐integrated, whereas bully‐victims are typically marginalized; Farmer et al., 2010 ; Perren & Alsaker, 2006 )? Possibly, these different social positions are explained by young children's success with behaving aggressively: Bullies may be the children who have gained dominance by behaving aggressively, whereas bully‐victims may be the children who have evoked victimization by behaving aggressively (Perren & Alsaker, 2006 ). Thus, one potential explanation for our findings is that bullies and bully‐victims do not differ in their motives for aggression at this early age, but rather in the successfulness of their aggression.

It is important to note that this interpretation is limited to early childhood; it is possible that in later childhood bullies and bully‐victims do have distinct psychological processes underlying their bullying behavior. Throughout this paper, we have conceptualized psychological processes as antecedents of bullying behavior; however, many of the processes studied may as well be the consequences of bullying or victimization. For instance, children who are repeatedly victimized may over time develop a tendency to attribute hostile intent. Thus, it is possible that stable psychological characteristics predicting children's position as bully or bully‐victim may emerge later in childhood.

This study found that bullies and bully‐victims in early childhood are similar in their reactive and proactive motives for aggression, replicating previous research in adolescence (Bettencourt & Farrell, 2013 ; Ragatz et al., 2011 ; Salmivalli & Nieminen, 2002 ). This finding is important, because the notion of distinct motives for aggression is at the heart of current theorizing about other distinct psychological processes in bullies and bully‐victims. Instead, if the aggressive behavior of bullies and bully‐victims is similarly motivated, there is less reason to presume other differences—for instance, that bullies expect to feel happy after victimizing whereas bully‐victims expect their peers to have hostile intentions.

Indeed, we did not find the predicted differences between bullies and bully‐victims on theory of mind skills, hostile intent attributions, and happy victimizer emotions. However, we also did not find differences between noninvolved children versus bullies and bully‐victims, as predicted by both hypotheses. This was unexpected, because we selected our psychological processes for their known relevance to predict aggressive behavior in young children (de Castro, Veerman, Koops, Bosch, & Monshouwer, 2002 ; Malti & Krettenauer, 2013 ; Sutton et al., 1999 ). Moreover, these processes all correlated with age in expected directions (i.e., resonating with children's social and moral development in early childhood; Flavell, 1999 ; Malti & Ongley, 2014 ).

Concerning theory of mind skills, ours is not the first study to find no differences between bullies and noninvolved children in early childhood (e.g., Gini, 2006 ; Monks, Smith, & Swettenham, 2005 ; Sutton et al., 1999 ). Yet, one longitudinal study did find evidence for poorer theory of mind skills at age 5 in children subsequently identified as bully or bully‐victim age 12 (Shakoor et al., 2012 ). These findings suggest that the detrimental effects of poor theory of mind skills may build up during years of peer interactions and may only manifest themselves in bullying behavior in later childhood.

Concerning hostile intent attributions, our results were puzzling. We found that bullies make more hostile intent attributions than bully‐victims, whereas the distinct processes hypothesis predicts the opposite pattern: that bully‐victims make more hostile intent attributions than bullies. As bullies and bully‐victims were equally aggressive according to teachers, this finding cannot be explained by bullies showing more severe behavior. Rather, these results may be a chance finding: There were three children who had the highest possible score on hostile intent attributions and these children were all categorized as bully. Indeed, if we excluded data of these children from the multivariate analysis, the difference between bullies and bully‐victims became nonsignificant. It is possible that these children's extreme scores were outliers or stemmed from home experiences such as harsh parenting (Weiss, Dodge, Bates, & Pettit, 1992 ). However, these interpretations are quite speculative and further research seems warranted.

The variable happy victimizer emotions was unrelated to both bullying and victimization and was removed from the analyses in order to obtain adequate model fit. One explanation for this finding is that happy victimizer emotions are not as relevant for predicting bullying (Gini, 2006 ; Menesini & Camodeca, 2008 ) as they are for predicting aggressive behavior (Malti & Krettenauer, 2013 ). Alternatively, happy victimizer emotions may be relevant for predicting bullying behavior but only when assessed in a more fine‐grained manner: Some bullies may attribute negative emotions merely because they expect to be sanctioned, but would attribute happiness if they expected their victimization to remain undetected (as is often the case for bullying behavior). Research that additionally assesses children's reasoning behind their anticipated emotions may be more sensitive to detect subtle differences in children's motivations for bullying (Nunner‐Winkler, 2007 ). In addition, research that directly compares different ages may provide further information about developmental differences and similarities in relations between happy victimizer emotions and bullying behavior.

Collectively, the results show the advantage of using an integrative approach to study several psychological processes in bullies and bully‐victims (Malti, 2016 ). When considering each process separately, the results yielded mixed evidence; however, when using Bayesian model selection to compare our two hypotheses as coherent models, the data clearly favored the shared processes hypothesis. This is one important illustration of why researchers in social science have recommended the use of Bayesian statistics (Van de Schoot et al., 2014 ).

Our findings are based on comparisons between bully groups and so it is important to carefully consider how these groups were created. First, we assigned children to a bully group if they received more nominations than the mean of their classroom. This approach yielded sufficient group sizes, but lower severity of bullying and victimization problems within the groups. However, our results do not seem to be affected by this approach: we found similar results using different criteria to create groups. Second, we used victim nominations to discriminate bullies from bully‐victims. A previous study found that kindergarteners gave more victim nominations to their friends, casting some doubt regarding the validity of such nominations (Monks, Smith, & Swettenham, 2003 ). In our study, however, it seems unlikely that victim nominations reflected friendship because they were correlated with several variables indicative of low social competence (i.e., poor theory of mind, and reactive and proactive motives for aggression). Third, we based our groups solely on peer‐nominations. We refrained from using combined peer‐ and teacher‐report to avoid shared informant bias: Teachers’ perceptions of bullying and victimization may generalize to their report of reactive and proactive motives, and vice versa. To enhance the reliability of our peer‐nomination assessment, we used an interview developed for use with kindergarteners; including pictures to explain the definition of bullying, and photographs of classmates to help children with recognition (Alsaker et al., 2008 ). We have indications this worked out sufficiently: there were meaningful associations between the peer‐nomination scores and psychological process variables, and the bully groups corroborated with teacher‐ratings of aggression.

In sum, we find that young bullies and bully‐victims have shared psychological processes underlying their bullying behavior. These findings raise new questions concerning what exactly differentiates bullies from bully‐victims: Is their behavior differently motivated, or do they differ in the successfulness of their aggression? Should psychological processes be regarded as the antecedents of children's position as bully or bully‐victim, as the consequences, or both (but in different developmental stages)? Thus, the present study has set a starting point for future research by clarifying that, in early childhood, bullies and bully‐victims have shared rather than distinct psychological processes underlying their behavior.

Supporting information

Supporting Information S1.

van Dijk A, Poorthuis AMG, Malti T. Psychological processes in young bullies versus bully‐victims . Aggressive Behavior . 2017; 43: 430–439. https://doi.org/10.1002/ab.21701 [ PMC free article ] [ PubMed ] [ Google Scholar ]

1 Raw data, analysis code, and relevant study materials are available at: https://osf.io/tzjwk

Alsaker, F. D. , Nägele, C. , Valkanover, S. , & Hauser, D . (2008). Pathways to victimization and a multisetting intervention: Project documentation . Bern: University of Bern. [ Google Scholar ]
Arsenio, W. F. , Adams, E. , & Gold, J . (2009). Social information processing, moral reasoning, and emotion attributions: Relations with adolescents’ reactive and proactive aggression . Child Development , 80 , 1739–1755. https://doi.org/10.1111/j.1467‐8624.2009.01365.x [ PubMed ] [ Google Scholar ]
Bettencourt, A. F. , & Farrell, A. D . (2013). Individual and contextual factors associated with patterns of aggression and peer victimization during middle school . Journal of Youth and Adolescence , 42 , 285–302. https://doi.org/10.1007/s10964‐012‐9854‐8 [ PubMed ] [ Google Scholar ]
Camodeca, M. , Goossens, F. A. , Schuengel, C. , & Terwogt, M. M . (2003). Links between social information processing in middle childhood and involvement in bullying . Aggressive Behavior , 29 , 116–127. https://doi.org/10.1002/ab.10043 [ Google Scholar ]
Camodeca, M. , Goossens, F. A. , Terwogt, M. M. , & Schuengel, C . (2002). Bullying and victimization among school‐age children: Stability and links to proactive and reactive aggression . Social Development , 11 , 332–345. https://doi.org/10.1111/1467‐9507.00203 [ Google Scholar ]
De Castro, B. O. , Veerman, J. W. , Koops, W. , Bosch, J. D. , & Monshouwer, H. J . (2002). Hostile attribution of intent and aggressive behavior: A meta‐analysis . Child Development , 73 , 916–934. https://doi.org/10.1111/1467‐8624.00447 [ PubMed ] [ Google Scholar ]
Dodge, K. A. , & Coie, J. D . (1987). Social‐information‐processing factors in reactive and proactive aggression in children's peer groups . Journal of Personality and Social Psychology , 53 , 1146–1158. https://doi.org/10.1037/0022‐3514.53.6.1146 [ PubMed ] [ Google Scholar ]
Dodge, K. A. , Lochman, J. E. , Harnish, J. D. , Bates, J. E. , & Pettit, G. S . (1997). Reactive and proactive aggression in school children and psychiatrically impaired chronically assaultive youth . Journal of Abnormal Psychology , 106 , 37–51. https://doi.org/10.1037/0021‐843X.106.1.37 [ PubMed ] [ Google Scholar ]
Farmer, T. W. , Petrin, R. A. , Robertson, D. L. , Fraser, M. W. , Hall, C. M. , Day, S. H. , & Dadisman, K . (2010). Peer relations of bullies, bully‐victims, and victims: The two social worlds of bullying in second‐grade classrooms . The Elementary School Journal , 110 , 364–392. https://doi.org/10.1086/648983 [ Google Scholar ]
Feshbach, L. E . (1989). Aggression‐conduct problems, attention‐deficits hyperactivity, play, and social cognition in four‐year‐old boys (Unpublished doctoral dissertation). University of Washington. [ Google Scholar ]
Flavell, J. H . (1999). Cognitive development: Children's knowledge about the mind . Annual Review of Psychology , 50 , 21–45. https://doi.org/10.1146/annurev.psych.50.1.21 [ PubMed ] [ Google Scholar ]
Gasser, L. , & Keller, M . (2009). Are the competent the morally good? Perspective taking and moral motivation of children involved in bullying . Social Development , 18 , 798–816. https://doi.org/10.1111/j.1467‐9507.2008.00516.x [ Google Scholar ]
Gini, G . (2006). Social cognition and moral cognition in bullying: What's wrong ? Aggressive Behavior , 32 , 528–539. https://doi.org/10.1002/ab.20153 [ Google Scholar ]
Griffin, R. S. , & Gross, A. M . (2004). Childhood bullying: Current empirical findings and future directions for research . Aggression and Violent Behavior , 9 , 379–400. https://doi.org/10.1016/S1359‐1789(03)00033‐8 [ Google Scholar ]
Hughes, C. , Adlam, A. , Happe, F. , Jackson, J. , Taylor, A. , & Caspi, A . (2000). Good test—retest reliability for standard and advanced false‐belief tasks across a wide range of abilities . Journal of Child Psychology and Psychiatry , 41 , 483–490. [ PubMed ] [ Google Scholar ]
Hughes, C. , Cutting, A. L. , & Dunn, J . (2001). Acting nasty in the face of failure? Longitudinal observations of “hard‐to‐manage” children playing a rigged competitive game with a friend . Journal of Abnormal Child Psychology , 29 , 403–416. https://doi.org/10.1023/A:1010495319182 [ PubMed ] [ Google Scholar ]
Jansen, P. W. , Verlinden, M. , Dommisse‐van Berkel, A. , Mieloo, C. , van der Ende, J. , Veenstra, R. , & Tiemeier, H . (2012). Prevalence of bullying and victimization among children in early elementary school: Do family and school neighbourhood socioeconomic status matter ? BMC Public Health , 12 https://doi.org/10.1186/1471‐2458‐12‐494 [ PMC free article ] [ PubMed ] [ Google Scholar ]
Kumpulainen, K. , Räsänen, E. , Henttonen, I. , Almqvist, F. , Kresanov, K. , Linna, S. L., , & Tamminen, T . (1998). Bullying and psychiatric symptoms among elementary school‐age children . Child Abuse & Neglect , 22 , 705–717. https://doi.org/10.1016/S0145‐2134(98)00049‐0 [ PubMed ] [ Google Scholar ]
Malti, T . (2016). Toward an integrated clinical‐developmental model of guilt . Developmental Review . https://doi.org/10.1016/j.dr.2015.11.001 [ Google Scholar ]
Malti, T. , Gummerum, M. , Keller, M. , & Buchmann, M . (2009). Children's moral motivation, sympathy, and prosocial behavior . Child Development , 80 , 442–460. https://doi.org/10.1111/j.1467‐8624.2009.01271.x [ PubMed ] [ Google Scholar ]
Malti, T. , & Krettenauer, T . (2013). The relation of moral emotion attributions to prosocial and antisocial behavior: A meta‐analysis . Child Development , 84 , 397–412. https://doi.org/10.1111/j.1467‐8624.2012.01851.x [ PubMed ] [ Google Scholar ]
Malti, T. , & Ongley, S. F . (2014). The development of moral emotions and moral reasoning In Killen M., & Smetana J. (Eds.), Handbook of moral development . (pp. 163–183). New York, NY: Psychology Press. [ Google Scholar ]
Menesini, E. , & Camodeca, M . (2008). Shame and guilt as behaviour regulators: Relationships with bullying, victimization and prosocial behaviour . British Journal of Developmental Psychology , 26 , 183–196. https://doi.org/10.1348/026151007×205281 [ Google Scholar ]
Menesini, E. , Sánchez, V. , Fonzi, A. , Ortega, R. , Costabile, A. , & Lo Feudo, G . (2003). Moral emotions and bullying: A cross‐national comparison of differences between bullies, victims and outsiders . Aggressive Behavior , 29 , 515–530. https://doi.org/10.1002/ab.10060 [ Google Scholar ]
Meulman, J. J. , Van Der Kooij, A. J. , & Heiser, W. J . (2004). Principal components analysis with nonlinear optimal scaling transformations for ordinal and nominal data The Sage handbook of quantitative methodology for the social sciences . (pp. 49–70). Thousand Oaks, CA: Sage. [ Google Scholar ]
Monks, C. P. , Smith, P. K. , & Swettenham, J . (2003). Aggressors, victims, and defenders in preschool: Peer, self‐, and teacher reports . Merrill‐Palmer Quarterly , 49 , 453–469. https://doi.org/10.1353/mpq.2003.0024 [ Google Scholar ]
Monks, C. P. , Smith, P. K. , & Swettenham, J . (2005). Psychological correlates of peer victimisation in preschool: Social cognitive skills, executive function and attachment profiles . Aggressive Behavior , 31 , 571–588. https://doi.org/10.1002/ab.20099 [ Google Scholar ]
Mulder, J. , Hoijtink, H. , & de Leeuw, C . (2012). BIEMS: A Fortran 90 program for calculating Bayes factors for inequality and equality constrained models . Journal of Statistical Software , 46 , 1–39. [ Google Scholar ]
Nansel, T. R. , Overpeck, M. , Pilla, R. S. , Ruan, W. J. , Simons‐Morton, B. , & Scheidt, P . (2001). Bullying behaviors among US youth: Prevalence and association with psychosocial adjustment . The Journal of the American Medical Association , 285 , 2094–2100. https://doi.org/10.1001/jama.285.16.2094 [ PMC free article ] [ PubMed ] [ Google Scholar ]
Nunner‐Winkler, G. (2007). Development of moral motivation from childhood to early adulthood . Journal of Moral Education , 36 , 399–414. https://doi.org/10.1080/03057240701687970 [ Google Scholar ]
Olweus, D . (1978). Aggression in the schools: Bullies and whipping boys . Washington, DC: Hemisphere. [ Google Scholar ]
Perren, S. , & Alsaker, F. D . (2006). Social behavior and peer relationships of victims, bully‐victims, and bullies in kindergarten . Journal of Child Psychology and Psychiatry , 47 , 45–57. https://doi.org/10.1111/j.1469‐7610.2005.01445.x [ PubMed ] [ Google Scholar ]
Perren, S. , Gutzwiller‐Helfenfinger, E. , Malti, T. , & Hymel, S . (2012). Moral reasoning and emotion attributions of adolescent bullies, victims, and bully‐victims . British Journal of Developmental Psychology , 30 , 511–530. https://doi.org/10.1111/j.2044‐835X.2011.02059.x [ PubMed ] [ Google Scholar ]
Polman, H. , de Castro, B. O. , Thomaes, S. , & van Aken, M . (2009). New directions in measuring reactive and proactive aggression: Validation of a teacher questionnaire . Journal of Abnormal Child Psychology , 37 , 183–193. https://doi.org/10.1007/s10802‐008‐9266‐0 [ PubMed ] [ Google Scholar ]
Polman, H. , de Castro, B. O. , Koops, W. , van Boxtel, H. W. , & Merk, W. W . (2007). A meta‐analysis of the distinction between reactive and proactive aggression in children and adolescents . Journal of Abnormal Child Psychology , 35 , 522–535. https://doi.org/10.1007/s10802‐007‐9109‐4 [ PubMed ] [ Google Scholar ]
Ragatz, L. L. , Anderson, R. J. , Fremouw, W. , & Schwartz, R . (2011). Criminal thinking patterns, aggression styles, and the psychopathic traits of late high school bullies and bully‐victims . Aggressive Behavior , 37 , 145–160. https://doi.org/10.1002/ab.20377 [ PubMed ] [ Google Scholar ]
Rodkin, P. C. , Espelage, D. L. , & Hanish, L. D . (2015). A relational framework for understanding bullying: Developmental antecedents and outcomes . American Psychologist , 70 , 311–321. https://doi.org/10.1037/a0038658 [ PubMed ] [ Google Scholar ]
Salmivalli, C. , & Nieminen, E . (2002). Proactive and reactive aggression among school bullies, victims, and bully‐victims . Aggressive Behavior , 28 , 30–44. https://doi.org/10.1002/ab.90004 [ Google Scholar ]
Shakoor, S. , Jaffee, S. R. , Bowes, L. , Ouellet‐Morin, I. , Andreou, P. , Happé, F. , & Arseneault, L . (2012). A prospective longitudinal study of children's theory of mind and adolescent involvement in bullying . Journal of Child Psychology and Psychiatry, , 53 , 254–261. https://doi.org/10.1111/j.1469‐7610.2011.02488.x [ PMC free article ] [ PubMed ] [ Google Scholar ]
Sutton, J. , Smith, P. K. , & Swettenham, J . (1999). Social cognition and bullying: Social inadequacy or skilled manipulation ? British Journal of Developmental Psychology , 17 , 435–450. https://doi.org/10.1348/026151099165384 [ Google Scholar ]
Van de Schoot, R. , Kaplan, D. , Denissen, J. , Asendorpf, J. B. , Neyer, F. J. , & Aken, M. A . (2014). A gentle introduction to Bayesian analysis: Applications to developmental research . Child Development , 85 , 842–860. https://doi.org/10.1111/cdev.12169 [ PMC free article ] [ PubMed ] [ Google Scholar ]
Vlachou, M. , Andreou, E. , Botsoglou, K. , & Didaskalou, E . (2011). Bully/victim problems among preschool children: A review of current research evidence . Educational Psychology Review , 23 , 329–358. https://doi.org/10.1007/s10648‐011‐9153‐z [ Google Scholar ]
Weiss, B. , Dodge, K. A. , Bates, J. E. , & Pettit, G. S . (1992). Some consequences of early harsh discipline: Child aggression and a maladaptive social information processing style . Child Development , 63 , 1321–1335. https://doi.org/10.1111/j.1467‐8624.1992.tb01697.x [ PubMed ] [ Google Scholar ]
Wolke, D. , Woods, S. , Bloomfield, L. , & Karstadt, L . (2000). The association between direct and relational bullying and behaviour problems among primary school children . Journal of Child Psychology and Psychiatry , 41 , 989–1002. https://doi.org/10.1111/1469‐7610.00687 [ PubMed ] [ Google Scholar ]
Wolke, D. , Woods, S. , Bloomfield, L. , & Karstadt, L . (2001). Bullying involvement in primary school and common health problems . Archives of Disease in Childhood , 85 , 197–201. https://doi.org/10.1136/adc.85.3.197 [ PMC free article ] [ PubMed ] [ Google Scholar ]
Wolke, D. , Woods, S. , Stanford, K. , & Schulz, H . (2001). Bullying and victimization of primary school children in England and Germany: Prevalence and school factors . British Journal of Psychology , 92 , 673–696. https://doi.org/10.1348/000712601162419 [ PubMed ] [ Google Scholar ]
Ziv, Y. , Leibovich, I. , & Shechtman, Z . (2013). Bullying and victimization in early adolescence: Relations to social information processing patterns . Aggressive Behavior , 39 , 482–492. https://doi.org/10.1002/ab.21494 [ PubMed ] [ Google Scholar ]

ORIGINAL RESEARCH article

Bullying history and mental health in university students: the mediator roles of social support, personal resilience, and self-efficacy.

1 Department of Clinical Psychology and Psychotherapy, Mental Health Research & Treatment Center, Ruhr-Universität Bochum, Bochum, Germany
2 Department of Psychology and Warwick Medical School, University of Warwick, Coventry, United Kingdom
3 Department of Clinical Child and Adolescent Psychology of the Faculty of Psychology, Mental Health Research & Treatment Center, Ruhr-Universität Bochum, Bochum, Germany

Bullying victimization by peers is highly prevalent in childhood and adolescence. There is convincing evidence that victimization is associated with adverse mental health consequences. In contrast, it has been found that perpetrators suffer no adverse mental health consequences. These findings originate from Western countries such as Germany but have rarely been investigated in collectivistic societies such as China. Furthermore, it has been rarely studied whether positive intrapersonal characteristics (e.g., personal resilience and self-efficacy) and interpersonal positive resources (e.g., social support) may mediate the impact of bullying on mental health. The current study used a path analytic model to examine, firstly, whether previous bullying experiences (both victimization and perpetration) are associated with current positive and negative mental health in university students and, secondly, whether these influences are mediated by social support, resilience, and self-efficacy. The model was tested in 5,912 Chinese and 1,935 German university students. It was found that in both countries, higher victimization frequency was associated with lower levels of social support, personal resilience, and self-efficacy, which in turn predicted poorer mental health. Moreover, and only in China, perpetration was negatively associated with social support and personal resilience but not self-efficacy. In contrast, in the German sample, perpetration experience was found to enhance one's self-efficacy, and the later was associated with better mental health. The results support a mediation model in which social support, personal resilience, and self-efficacy partially mediate the influence of victimization on mental health in both countries. For the relationship between perpetration and mental health, self-efficacy was the only full mediator in Germany, whereas in China, both social support and personal resilience were partial mediators. In conclusion, peer victimization has adverse effects on mental health in both Germany and China. Only in China, however, is perpetration also associated with adverse mental health outcomes. In contrast, getting ahead by bullying in an individualistic society such as Germany is associated with increased self-efficacy and mental health. The differences found between an individualistic country and a collectivistic country have important implications for understanding and planning interventions to reduce bullying.

Introduction

Peer bullying at school is highly prevalent and has become an international concern (e.g., 1 , 2 ). Victimization has been universally found to be associated with cross-sectional and long-term adverse mental health consequences, including more severe depression and anxiety symptoms (e.g., 3 – 5 ) and lower levels of positive mental health (e.g., 4 ).

In contrast, the relationships between bullying perpetration and health problems are not consistent across countries ( 2 ). In some countries such as Germany, Austria, the UK, the USA, and Denmark, bullies appear to be as healthy as non-involved peers, in terms of adult mental and general health ( 5 , 6 ), except for a higher risk for antisocial personality ( 7 ) and alcohol use ( 2 ). However, in other countries such as China, Greece, or Israel, perpetrators have reported worse health problems and emotional adjustment ( 2 , 8 ). Furthermore, bullies may perceive less social support than non-involved students in the USA and China ( 8 , 9 ). The differences between bullies in different countries indicate that the same behavior may have different consequences depending on context and societal norms. Thus, a cross-national study that applies the same measures in different cultures may help to clarify the relationship between perpetration and mental health.

Only recently has research focused on factors that may help to explain how being bullied may be associated with adverse mental health outcomes (e.g., 10 , 11 ). An increasing amount of urecharacteristics (e.g., personal resilience and self-efficacy) can promote mental well-being ( 12 – 14 ). These may be protective factors that mitigate the negative impact of bullying experience on mental health, meanwhile, they may also be influenced by the bullying experiences.

As one of the most prominent protective factors, perceived social support plays an essential part in preventing mental illness (e.g., 12 , 13 , 15 ). It has a remarkably consistent positive association with positive mental health (e.g., 16 , 17 ). Perceived social support refers to an individual's feeling or evaluation of whether the social network is supportive enough to facilitate the individual's coping with tasks and stress or to achieve personal goals ( 18 , 19 ). The link between social support and bullying has been well established, with poor social support highly associated with victimization by peers (e.g. 20 , 21 ). Stress may erode the perception or effectiveness of social support ( 22 ). For instance, longitudinal evidence has shown that “continuous victims of bullying” had worse school attendance rates, which further isolated them from peers and undermined a healthy peer relationship ( 23 ). Furthermore, social support has been shown to mediate the negative effect of workplace or school bullying on positive or negative well-being ( 24 , 25 ).

While some use friendships and family as protective buffers, others may rely on their resilience to overcome the adversity of victimization ( 10 ). Resilience can manifest in several ways. Personal resilience refers to the capacity to adapt, recover, and avoid potential deleterious effects after facing overwhelming adversity ( 14 ). Children and adolescents are in a constant process of development. Thus, their resilience trait is more likely to be influenced by situational factors such as bullying involvement during primary or secondary school periods. For example, negative life events negatively predict resilience in students ( 26 ) and parental HIV longitudinally affected resilience in children ( 27 ). Indeed, research has shown that resilience trait mediates the relationships between workspace bullying and physical strain ( 28 ) and between primary school bullying and depressive symptoms ( 29 ).

Another essential positive factors in stress regulation is self-efficacy. The perception of self-efficacy is the belief that one can perform novel or challenging tasks and attain desired outcomes, indicating a self-confident view of one's own capability to deal with stressors in life [see Social Cognitive Theory, ( 30 , 31 )]. High self-efficacy is associated with higher levels of optimism and life satisfaction ( 28 , 33 ) and lower anxiety and depression ( 34 ). Meanwhile, prior experience is one of the most influential factors that shape self-efficacy ( 35 ). It is likely that a negative peer experience (i.e., victimization) or a mastery experience (i.e., perpetration) influence one's self-efficacy appraisal. For instance, previous research indicates that self-efficacy mediates the effect of stressful life events or daily stressors on both positive and negative mental health in samples from different cultures ( 36 , 37 ).

Unlike social support and personal resilience, results on the relationship between self-efficacy and bullying involvement are mixed. In some research, both victimization and perpetration were found to be negatively associated with overall self-efficacy [Greek elementary school children: 38 ; Turkish middle school students: ( 39 )]. In some cases, it has been found that victims have lower self-efficacy than bullies and those not involved in Chinese primary and German secondary school bullying. Bullies, on the other hand, do not tend to differ from not-involved peers in self-efficacy ( 8 ). There are also studies indicating that firmer self-efficacy beliefs are positively correlated to high levels of self-reported cyberbullying behaviors ( 40 ). A possible explanation for the mixed results regarding self-efficacy may be that a substantial number of persons are involved in both bullying perpetration and victimization (i.e., so-called bully-victims). Therefore, in the current study, the correlations between perpetration and victimization were controlled.

In sum, there is some consistency in the findings when it comes to social support and personal resilience as single mediators in the relationship between victimization and mental health. The role of self-efficacy has not yet been established. Thus social support, personal resilience, and self-efficacy may be considered potential factors that protect against being bullied and may explain the impact of previous bullying severity on mental health. Therefore, the current study aimed to explore the role of perceived social support, personal resilience, and self-efficacy in the relationship between previous peer bullying experience (both victimization and perpetration) and current mental health (both positive mental health and mental illness symptoms) in university students using a mediation model (see Figure 1 for a hypothesized model). Bullying experience was measured with a retrospective inventory regarding victimization and perpetration frequency from primary schools to current universities. Our work aims to add insight into the relationship between school bullying and its long-term consequences during university. Both perpetration and victimization experiences were examined in one model in order to control for the correlation between them. Adding perpetration into the model was also predicted to expand our knowledge of how bullying behaviors impact one's mental health. Moreover, in order to expand on previous works that typically focused on only the mental illness, both the positive and negative aspects of mental health were outcome variables [measured by the Positive Mental Health scale, PMH; ( 41 ); and the Depression, Anxiety, and Stress Scale, DASS; ( 42 )].

Figure 1 A hypothesized mediation model for bullying and mental health.

Furthermore, as reviewed above, there appear to be cultural differences in the effects of bullying perpetration on well-being and mental health. So far, our knowledge of bullying consequences is primarily based on studies carried out in western, individualistic societies. In more collectivistic cultures such as China, however, bullying and its mechanisms have rarely been investigated. There is evidence that bullies in China also suffer from concurrent or long-term problems such as poor life satisfaction, depression, suicide ideation, or psychoticism (e.g., 8 , 43 , 44 ), unlike the phenomena found in western countries where bullies typically do well ( 2 , 5 , 6 ). Therefore, the hypothesized model was tested within two separate samples: university students in China, a country that fosters Eastern Asian group-oriented culture (e.g., 45 , 46 ); and students in Germany, a West European individualistic country, where the ties between individuals are relatively loose ( 45 ).

Based on the research regarding bullying and its aversive consequences on mental health and the protective role of social support, personal resilience, and self-efficacy (e.g., 3 , 4 , 10 , 12 , 32 ), it is hypothesized that in both countries, (a) social support, personal resilience, and self-efficacy would be positively related to PMH and negatively related to DASS; (b) victimization experience would be positively related to DASS and negatively related to PMH and (c) social support, personal resilience, and self-efficacy would mediate the relationship between victimization and mental health. Giving that bullies reported different mental health levels across various countries ( 2 , 5 , 8 ), we further hypothesized cross-cultural differences regarding the paths on perpetration.

Participants

This study is part of the Bochum Optimism and Mental Health (BOOM) research project, which is a large-scale cross-cultural longitudinal investigation in mental health. The Ethics Committee of the Faculty of Psychology at Ruhr University Bochum approved the project. Chinese data were collected either by paper-pencil survey or online questionnaires, while German data were all collected via an online survey.

In total, 5,912 Chinese students from Capital Normal University (Beijing city), Shanghai Normal University (Shanghai city), Nanjing University (Nanjing city), Hebei United University (Tangshan city), and Guizhou University of Finance and Economics (Guiyang city) participated in the 2015 survey. All participants were in the fourth year of bachelor degree studies (age: 21.54 ± 1.20). Among them, 3,301 (60.0%) were female and 2,202 (40.0%) were male; 3,403 (60.1%) came from low affluent families, 1,687 (29.8%) from medium affluent families, and 573 (10.1%) from high affluent families. Family affluence was measured and classified based on the scores on the 4-item Family Affluence Scale-II ( 47 ).

The German sample consists of 1,935 students (age: 21.73 ± 4.93) of Ruhr University Bochum (Bochum city) who took the survey at least once between 2015 and 2017. Among them, 1166 (61.7%) were female while 725 (38.3%) were male; 242 (15.7%) came from low affluent families, 812 (52.5%) from medium, and 492 (31.8%) from high affluent families; 1156 were in the freshman year, 105 in the sophomore year, 53 in the junior year, 99 in the senior year, 352 in the fifth year or higher, and 68 were in Ph.D. programs.

Questionnaires

Bullying history.

Peer victimization and perpetration experiences at primary school, secondary school, and currently at university were collected with the Retrospective Bullying Questionnaire [modified from ( 48 )]. Behaviors of direct, relational and cyberbullying were first described. Participants rated how frequently they perpetrated or received (victimization) the described behavior during each school period (primary school, secondary school, current university) from 1 ( never ), 2 ( once or twice ), 3 ( occasionally ), 4 ( about once a week ), to 5 ( several times a week ). The three victimization questions across all periods were summed for a total victimization score, while the three perpetration questions were summed for a total perpetration score. The Retrospective Bullying Questionnaire was test-retested in 287 German students with a one-year gap. The one-year test-retest reliability was.81 for school victimization and ranged from.55 to.60 for school perpetration.

Depression, Anxiety, and Stress Scale (DASS)

The 21-item DASS ( 42 ) assesses depression, anxiety, and stress symptoms (seven items for each) from the last seven days. Participants checked agreement on a four-point Likert scale from 0 ( did not apply to me at all ) to 3 ( applied to me very much or most of the time ). A higher score indicates severer mental illness symptoms. Cronbach's alpha was.93 in the German sample and.96 in the Chinese sample.

Positive Mental Health Scale (PMH)

The 9-item PMH ( 41 ) measures positive aspects of emotional well-being and health on 4-point Likert scales ranging from 0 ( do not agree ) to 3 ( agree ). A higher score indicates better general positive mental health. Cronbach's alpha was.91 in the German sample and.96 in the Chinese sample.

Resilience Scale

The 11-item Resilience Scale ( 49 ) is a short unidimensional version of the 25-item Resilience Scale from ( 14 ), which measures psychosocial stress-resistance (e.g., personal competence and acceptance of self and life) on scales ranging from 1 (disagree) to 7 (agree). Higher scores indicate a higher level of resilience. Internal consistency was.87 in the German sample and.90 in the Chinese sample.

Brief Perceived Social Support Questionnaire (F-SozU K-6)

The 6-item F-SozU ( 50 ) assesses general support that one perceives from the social network. Participants indicated agreement on 5-point Likert scales ranging from 1 ( not true at all ) to 5 ( very true ). Higher scores indicate a higher level of perceived social support. Cronbach's alpha was.87 in the German sample and.90 in the Chinese sample.

General Self-Efficacy Scale (GSE)

The 10-item GSE ( 51 ) was used to assess a general sense of one's ability to cope when facing unexpected situations. Items are rated on a 4-point likely scale ranging from 1 ( not agree ) to 4 ( totally agree ). Higher sum scores indicate a greater sense of self-efficacy. In the German sample, Cronbach's alpha was.88, and in the Chinese sample, .93.

Data Analysis

Multivariate analysis of variance (MANOVA) was used to examine the difference in bullying frequency (victimization and perpetration) at each school period between China and Germany. In order to define the relationship between bullying experience, positive factors, and mental well-being, Mplus [version 7.4, ( 52 )] was used to test the path analytic model. Full information maximum likelihood (FIML) estimation was used. The hypothesized model was defined with two correlated predictors (victimization and perpetration), three inter-correlated mediators (social support, personal resilience, and self-efficacy), and two correlated dependent variables (DASS and PMH). Sum scores of all the scales were entered into the model. Bias-corrected bootstrapping (5000 times) was applied for testing the significance of indirect effects ( 53 ). Then, insignificant paths were removed one by one to simplify the model. Final models contained only significant paths. An adequate model fit was determined by a nonsignificant chi-square statistic, a root mean square error of approximation (RMSEA) <.06, a comparative fit index (CFI) >.95, and a standardized root-mean-square residual (SRMR) <.08 ( 54 ). The effect size of the standardized regression coefficient was interpreted as small (.14), medium (.39), and large (.59) based on Cohen ( 55 ); while the effect size of standardized indirect effects was interpreted as small (.01), medium (.09), and large (.25) as suggested by Kenny and Judd ( 56 ). The datasets for this study can be found in the online Supplementary Material .

Bullying Frequency in Both Countries

Table 1 presents the self-reported bullying frequency at primary, secondary school, and university. Results from MANOVA showed that both countries differed significantly for all periods; however, the effect size of bullying at university was trivial (η 2 part. <.01). German students reported more frequently being bullied and bullying others than Chinese students during primary and secondary school.

Table 1 Means (M) and standardized deviations (SD) of bullying frequency in each school period.

Correlation Table

Table 2 presents the correlations between the variables. All variables were found to be significantly correlated with each other ( p <.05), except for perpetration, which was not correlated with personal resilience and self-efficacy in the German sample. As expected, in both countries, victimization was positively related to perpetration and DASS, and negatively related to social support, personal resilience, self-efficacy, and PMH. Moreover, the three positive factors were positively inter-correlated with each other and with the two outcome measures. Additionally, in China, the effect sizes between perpetration and other variables were small to modest, whereas the same correlation in Germany had only trivial to small effects.

Table 2 Means (M) and standardized deviations (SD) of measures and correlation table.

Mediated Path Analytic Model Within the German Sample

The results of the final mediated path model in the German sample indicate an excellent fit of the data, RMSEA <.0001 (90% confidence interval from <.0001 to.027), CFI = 1, SRMR =.004. The standardized path coefficients ( p <.001) of the final model are shown in Figure 2 . Victimization experience was negatively linked with all three mediators and the two dependent variables, and the three mediators further associated negatively with DASS and positively with PMH, suggesting that social support, personal resilience, and self-efficacy partially mediated the effect of victimization on the two mental health measures. Perpetration experience was significantly linked only with self-efficacy, the later further regressed positively on PMH and negatively on DASS, suggesting that self-efficacy fully mediated the effect of perpetration on mental health. The correlations between the two predictors, the three mediators, and the two dependent variables were all significant at.001 level. The effect sizes of the direct and indirect effects from the bootstrapping are presented in Table 3 . In addition, the final model explained 58.1% of the variance in PMH, 37.0% in DASS, 3.0% in personal resilience, 3.9% in self-efficacy, and 6.4% in social support.

Figure 2 Final path mediated model for the effects of bullying, social support, personal resilience, and self-efficacy on positive and negative well-being in the German sample. Regression paths (single-arrow) and correlation paths (curved double-arrow) were all significant on at least.05 level. Standardized coefficients are shown. DASS, Depression, Anxiety, and Stress Scale. PMH, Positive Mental Health Scale.

Table 3 Standardized total indirect, specific indirect, and direct effects and their 95% confidence intervals (C.I.).

Mediated Path Analytic Model in the Chinese Sample

The results of the final mediated path model in the Chinese sample also indicate an excellent fit of the data, RMSEA <.0001 (90% confidence interval from <.0001 to.024), CFI = 1, SRMR =.002. The standardized path coefficients are shown in Figure 3 . Victimization experience was negatively linked with all three mediators and the two dependent variables, while perpetration frequency was negatively linked with personal resilience and social support and the two dependent variables but not with self-efficacy. All three positive factors were positively associated with PMH, while only social support and personal resilience further regressed on DASS. The results indicate that social support, personal resilience, and self-efficacy partially mediated the effect of victimization on mental health and that only social support and personal resilience partially mediated the effect of perpetration on mental health. The direct and indirect effects of the mediation are presented in Table 3 . Moreover, all the correlations were significant at.001 level. In addition, the final model explained 49.0% of the variance in PMH, 20.8% in DASS, 2.6% in personal resilience and self-efficacy, and 3.9% in social support.

Figure 3 Final path mediated model for the effects of bullying, social support, personal resilience, and self-efficacy on positive and negative well-being in the Chinese sample. Regression paths (single-arrow) and correlation paths (curved double-arrow) were all significant on at least.05 level. Standardized coefficients are shown. DASS, Depression, Anxiety, and Stress Scale. PMH, Positive Mental Health Scale.

The main aim of this study was to test the mediators of previous bullying experience regarding the outcomes of both positive and negative mental health in university students in China and Germany. For both countries, it was found that social support, personal resilience, and self-efficacy partially mediate the effect of previous victimization experience on current well-being and mental illness. In contrast, cultural differences were observed for the relationship between perpetration and positive and mental health. For Germany, only self-efficacy fully mediated the effect of perpetration on mental health: more frequent perpetration promoted higher mental health status via a higher level of self-efficacy. Conversely, for students in China, social support and partially resilience partially mediated the effect of perpetration on mental health. More specifically, more frequent bullying perpetration was linked with a lower level of social support perception and lower personal resilience, which in turn was found to be associated with worse mental health.

In both countries, social support, personal resilience, and self-efficacy partially mediated the negative effect of victimization on mental health, with medium-sized total indirect effects. The results replicate previous findings on similar social resources and positive traits (e.g., 24 , 28 , 29 , 38 , 57 ) and indicate that the long-term adverse emotional consequences of being bullied are partly explained by less social support, lower personal resilience and lower self-efficacy levels. The current results further provide some initial evidence of an important role for self-efficacy, which revealed the strongest indirect mediating effect in our data. Bullying interventions may consider promoting the social resources and the self-efficacy of the victims in order to reduce the negative impact of victimization. However, there was also a direct effect of bullying victimization, indicating that even if social support, personal resilience or self-efficacy is high, a negative effect of being excluded and beaten may not be avoided.

The relationships between perpetration, positive factors, and mental well-being were different across countries. In China, bullying others more frequently, like being bullied, was associated with a lower level of personal resilience and support perception; whereas in Germany, bullying others was unrelated to the level of social support or personal resilience, but instead even weakly increased one's self-efficacy. The results indicate that bullies from two different cultures, Germany and China, face different psychological consequences of their perpetration behavior. The associations of perpetration with positive factors were different as well. Those involved in bullying in China were less personally resilient and socially supported and had more severe mental illness symptoms ( 8 ). Thus, providing social support and strengthening personal resilience may reduce bullying perpetration in China. In contrast, in Germany, bullies were as socially supported and personally resilient but even more self-efficient than those not involved in any bullying. This is consistent with previous findings that bullying is little socially sanctioned and conducted by students who are competent social manipulators with good emotional well-being (e.g., 5 , 6 , 58 , 59 ).

Cultural differences were also found in the relationship between positive and negative mental health. For instance, the effect size of the correlation between PMH and DASS was smaller in China than that in Germany. Moreover, self-efficacy had a stronger association, as indicated by the path coefficient in Figure 3 , with PMH than with DASS in Germany. This phenomenon is more pronounced in the China sample, where self-efficacy had a significant association with PMH but not with DASS. On the one hand, these results are in line with Karademas ( 60 ), who proposed that the buffering effect of self-efficacy is greater for positive than for negative mental health. On the other hand, it may be that self-efficacy may not be related to depression or anxiety in China. In China, many people believe that uncontrollable or unexpected events or “fate” ( Tianming ) may sometimes impact the outcome of ones' best endeavors. Thus, those having high self-efficacy may face greater disappointment, while having low self-efficacy may also link to a greater sense of powerlessness. In Germany, in contrast, having higher self-efficacy not only promoted PMH but also prevented mental illness at a certain level. Taken together, it appears that the difference between the latent constructs measured by PMH and DASS was greater in China than in Germany.

While the large sample size, cross-cultural design (allowing for direct comparison of bullying involvement in Germany and China), and the inclusion of mediators are major strengths of the current study, there are also limitations. The measure of bullying history was retrospective and self-reported. However, test–retest showed high reliability over one year. Nevertheless, reported associations need to be interpreted cautiously and require replication in prospective studies. The large sample size did allow us to detect small effects. Thus, when interpreting our results, not only the significance of paths but also the effect sizes should be considered, especially regarding the effects between perpetration and other variables ( 56 ). In addition, the current study chose three representative positive factors as a start of the coping/recourse model of bullying; however, there may be more critical mediators, especially for perpetration, that were not tested in our study. Further studies may consider other protective or buffering factors and expand the model upon the three mediators examined in the current study.

In sum, the current study found that social support, personal resilience, and self-efficacy play essential roles in regulating the influences of victimization on later mental well-being across countries considered as individualistic or collectivistic. Thus strengthening social support, personal resilience and self-efficacy are likely to help to mitigate the ill effects of peer victimization. In contrast, mechanisms of how bullying perpetration associates with mental health differ between individualistic and collectivistic cultures. In Germany, bullying increases self-efficacy and has even small positive effects on mental well-being. In contrast, in a collectivistic society such as China, bullying others is associated with reduced social support and decreased personal resilience and negative mental health. Bullying may be seen as breaking the social norms of caring for others. The model proposed here needs to be explored longitudinally and applied to the development of strategies that build psychological personal resilience and resource in bullying victims.

Data Availability Statement

All datasets generated for this study are included in the article/ Supplementary Material .

Ethics Statement

This study is part of the Bochum Optimism and Mental Health (BOOM) research project, which is a large-scale cross-cultural longitudinal investigation in mental health. The project was approved by the Ethics Committee of the Faculty of Psychology at Ruhr University Bochum.

Author Contributions

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

This study was supported by Alexander von Humboldt Professorship awarded to the last author by the Alexander von Humboldt-Foundation.

Conflict of Interest

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

Acknowledgments

The authors would like to acknowledge Dr. Xiao Chi Zhang and Dr. Kristen Lavallee for their support in results discussion, manuscript proofreading, and data collection management.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2019.00960/full#supplementary-material

1. Fleming LC, Jacobsen KH. Bullying among middle-school students in low and middle income countries. Health Promot Int (2010) 25(1):73–84. doi: 10.1093/heapro/dap046

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Nansel TR, Craig W, Overpeck MD, Saluja G, Ruan WJ. Cross-national consistency in the relationship between bullying behaviors and psychosocial adjustment. Arch Pediatr Adolesc Med (2004) 158(8):730–6. doi: 10.1001/archpedi.158.8.730

3. Arseneault L. Annual research review: the persistent and pervasive impact of being bullied in childhood and adolescence: implications for policy and practice. J Child Psychol Psychiatry (2018) 59(4):405–21. doi: 10.1111/jcpp.12841

4. Moore SE, Norman RE, Suetani S, Thomas HJ, Sly PD, Scott JG. Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis. World J Psychiatry (2017) 7(1):60. doi: 10.5498/wjp.v7.i1.60

5. Wolke D, Lereya ST. Long-term effects of bullying. Arch Dis Child (2015) 100(9):879–85. doi: 10.1136/archdischild-2014-306667

6. Wolke D, Copeland WE, Angold A, Costello EJ. Impact of bullying in childhood on adult health, wealth, crime, and social outcomes. Psychol Sci (2013) 24(10):1958–70. doi: 10.1177/0956797613481608

7. Copeland WE, Wolke D, Angold A, Costello EJ. Adult psychiatric outcomes of bullying and being bullied by peers in childhood and adolescence. JAMA Psychiatry (2013) 70(4):419–426. doi: 10.1001/jamapsychiatry.2013.504

8. Lin M, Wolke D, Schneider S, Margraf J. (under review). Bullies Get Away with It – But Only in Western Cultures?

Google Scholar

9. Holt MK, Espelage DL. Perceived social support among bullies, victims, and bully-victims. J Youth Adolesc (2007) 36(8):984–94. doi: 10.1007/s10964-006-9153-3

CrossRef Full Text | Google Scholar

10. Bowes L, Maughan B, Caspi A, Moffitt TE, Arseneault L. Families promote emotional and behavioural resilience to bullying: evidence of an environmental effect. J Child Psychol Psychiatry (2010) 51(7):809–17. doi: 10.1111/j.1469-7610.2010.02216.x

11. Sapouna M, Wolke D. Resilience to bullying victimization: the role of individual, family and peer characteristics. Child Abuse Negl (2013) 37(11):997–1006. doi: 10.1016/j.chiabu.2013.05.009

12. Brailovskaia J, Teismann T, Margraf J. Cyberbullying, positive mental health and suicide ideation/behavior. Psychiatry Res (2018) 267:240–2. doi: 10.1016/j.psychres.2018.05.074

13. Lakey B, Orehek E. Relational regulation theory: A new approach to explain the link between perceived social support and mental health. Psychol Rev (2011) 118(3):482. doi: 10.1037/a0023477

14. Wagnild G, Young H. Development and psychometric evaluation of the Resilience Scale. J Nurs Meas (1993) 1(2):165–17847.

PubMed Abstract | Google Scholar

15. Rueger SY, Malecki CK, Demaray MK. Relationship between multiple sources of perceived social support and psychological and academic adjustment in early adolescence: comparisons across gender. J Youth Adolesc (2010) 39(1):47. doi: 10.1007/s10964-008-9368-6

16. Kumar S, Calvo R, Avendano M, Sivaramakrishnan K, Berkman LF. Social support, volunteering and health around the world: cross-national evidence from 139 countries. Soc Sci Med (2012) 74(5):696–706. doi: 10.1016/j.socscimed.2011.11.017

17. Tian L, Liu B, Huang S, Huebner ES. Perceived social support and school well-being among Chinese early and middle adolescents: the mediational role of self-esteem. Soc Indic Res (2013) 113(3):991–1008. doi: 10.1007/s11205-012-0123-8

18. Fydrich T, Geyer M, Hessel A, Sommer G, Brähler E. Fragebogen zur sozialen unterstützung (F-SozU): Normierung an einer repräsentativen Stichprobe. [Social support questionnaire (F-SozU): Standardization on a representative sample]. Diagnostica (1999) 45:212–6. doi: 10.1026//0012-1924.45.4.212

19. Fydrich T, Sommer G, Tydecks S, Brähler E. Fragebogen zur sozialen unterstützung (F-SozU): Normierung der Kurzform (K-14). [Social support questionnaire (F-SozU): Standardization of the short form (K-14)]. Z für Med Psychol (2009) 18(1):43–8.

20. Cui S, Cheng Y, Xu Z, Chen D, Wang Y. Peer relationships and suicide ideation and attempts among Chinese adolescents. Child: Care Health Dev (2011) 37(5):692–702. doi: 10.1111/j.1365-2214.2010.01181.x

21. Evans CB, Smokowski PR, Cotter KL. Cumulative bullying victimization: an investigation of the dose–response relationship between victimization and the associated mental health outcomes, social supports, and school experiences of rural adolescents. Children Youth Serv Rev (2014) 44:256–64. doi: 10.1016/j.childyouth.2014.06.021

22. Barrera M Jr.. Distinctions between social support concepts, measures, and models. Am J Community Psychol (1986) 14(4):413–45. doi: 10.1007/BF00922627

23. Smith PK, Talamelli L, Cowie H, Naylor P, Chauhan P. Profiles of non‐victims, escaped victims, continuing victims and new victims of school bullying. Br J Educ Psychol (2004) 74(4):565–81. doi: 10.1348/0007099042376427

24. Cassidy T, McLaughlin M, McDowell E. Bullying and health at work: the mediating roles of psychological capital and social support. Work Stress (2014) 28(3):255–69. doi: 10.1080/02678373.2014.927020

25. Seeds PM, Harkness KL, Quilty LC. Parental maltreatment, bullying, and adolescent depression: evidence for the mediating role of perceived social support. J Clin Child Adolesc Psychol (2010) 39(5):681–92. doi: 10.1080/15374416.2010.501289

26. Liu C, Zhao Y, Tian X, Zou G, Li P. Negative life events and school adjustment among Chinese nursing students: The mediating role of psychological capital. Nurse Education Today (2015) 35(6):754–59. doi: 10.1016/j.nedt.2015.02.002

27. Chi P, Li X, Du H, Tam CC, Zhao J, Zhao G. Does stigmatization wear down resilience? A longitudinal study among children affected by parental HIV. Pers Individ Dif (2016) 96:159–63. doi: 10.1016/j.paid.2016.03.001

28. Maidaniuc-Chirilă T. The mediation role of resilience on the relationship between workplace bullying and Romanian employees' strain. Rev Cercet şi Interv Soc (2015)(48), 120–33.

29. Zhou ZK, Liu QQ, Niu GF, Sun XJ, Fan CY. Bullying victimization and depression in Chinese children: a moderated mediation model of resilience and mindfulness. Pers Individ Dif (2017) 104:137–42. doi: 10.1016/j.paid.2016.07.040

30. Bandura A. Self-efficacy: The exercise of control . Freeman: New York (1997).

31. Schwarzer R, Warner LM. Perceived self-efficacy and its relationship to resilience. In: Resilience in children, adolescents, and adults . Springer: New York, NY (2013). p. 139–50. doi: 10.1007/978-1-4614-4939-3_10

32. Azizli N, Atkinson BE, Baughman HM, Giammarco EA. Relationships between general self-efficacy, planning for the future, and life satisfaction. Pers Individ Dif (2015) 82:58–60. doi: 10.1016/j.paid.2015.03.006

33. Luszczynska A, Gutiérrez-Doña B, Schwarzer R. General self-efficacy in various domains of human functioning: evidence from five countries. Int J Psychol (2005) 40(2):80–9. doi: 10.1080/00207590444000041

34. Kwasky AN, Groh CJ. Vitamin D, depression and coping self-efficacy in young women: Longitudinal study. Arch Psychiatr Nurs (2014) 28(6):362–7. doi: 10.1016/j.apnu.2014.08.010

35. Bong M, Skaalvik EM. Academic self-concept and self-efficacy: how different are they really? Educ Psychol Rev (2003) 15(1):1–40. doi: 10.1023/A:1021302408382

36. Maciejewski PK, Prigerson HG, Mazure CM. Self-efficacy as a mediator between stressful life events and depressive symptoms: differences based on history of prior depression. Br J Psychiatry (2000) 176(4):373–8. doi: 10.1192/bjp.176.4.373

37. Schönfeld P, Brailovskaia J, Bieda A, Zhang XC, Margraf J. The effects of daily stress on positive and negative mental health: mediation through self-efficacy. Int J Clin Health Psychol (2016) 16(1):1–10. doi: 10.1016/j.ijchp.2015.08.005

38. Kokkinos CM, Kipritsi E. The relationship between bullying, victimization, trait emotional intelligence, self-efficacy and empathy among preadolescents. Soc Psychol Educ (2012) 15(1):41–58. doi: 10.1007/s11218-011-9168-9

39. Özer A, Totan T, Atik G. Individual correlates of bullying behaviour in Turkish middle schools. J Psychol Counsellors Schools (2011) 21(2):186–202. doi: 10.1375/ajgc.21.2.186

40. Bussey K, Fitzpatrick S, Raman A. The role of moral disengagement and self-efficacy in cyberbullying. J School Violence (2015) 14(1):30–46. doi: 10.1080/15388220.2014.954045

41. Lukat J, Margraf J, Lutz R, van der Veld WM, Becker ES. Psychometric properties of the Positive Mental Health Scale (PMH-scale). BMC Psychol (2016) 4, 8. doi: 10.1186/s40359-016-0111-x

42. Henry JD, Crawford JR. The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. Br J Clin Psychol (2005) 44(2):227–39. doi: 10.1348/014466505X29657

43. Gu CH, Zhang WX. A survey on the relations of the bullying problem among primary school children to their personality. Acta Psychol Sin (2003) 35:101–5.

44. Hong L, Guo L, Wu H, Li P, Xu Y, Gao X, et al. Bullying, depression, and suicidal ideation among adolescents in the fujian province of china: a cross-sectional study. Medicine (2016) 95(5):e2530. doi: 10.1097/MD.0000000000002530

45. Hofstede G. Culture's consequences: Comparing values, behaviors, institutions and organizations across nations (2 nd Ed.) . Sage publications: Thousand Oaks (2001).

46. Huang LL. Interpersonal Harmony and Conflict for Chinese People: A Yin–Yang Perspective. Front Psychol (2016) 7:847. doi: 10.3389/fpsyg.2016.00847

47. Boyce W, Torsheim T, Currie C, Zambon A. The family affluence scale as a measure of national wealth: Validation of an adolescent self-report measure. Soc Indic Res (2006) 78:473–87. doi: 10.1007/s11205-005-1607-6

48. Wolke D, Sapouna M. Big men feeling small: Childhood bullying experience, muscle dysmorphia and other mental health problems in bodybuilders. Psychol Sport Exercise (2008) 9(5):595–604. doi: 10.1016/j.psychsport.2007.10.002

49. Schumacher J, Leppert K, Gunzelmann T, Strauß B, Brähler E. Die resilienzskala–ein fragebogen zur erfassung der psychischen widerstandsfähigkeit als personmerkmal. Z Klin Psychol Psychiatr Psychother (2005) 53(1):16–39.

50. Kliem S, Mößle T, Rehbein F, Hellmann DF, Zenger M, Brähler E. A brief form of the Perceived Social Support Questionnaire (F-SozU) was developed, validated, and standardized. J Clin Epidemiol (2015) 68(5):551–62. doi: 10.1016/j.jclinepi.2014.11.003

51. Schwarzer R, Jerusalem M. Generalized Self-Efficacy scale. In: Weinman J, Wright S, Johnston M, editors . Measures in health psychology: A user's portfolio. Causal and control beliefs . NFER-NELSON: Windsor, UK (1995). p. 35–7.

52. Muthén LK, Muthén BO. Mplus User’s Guide . Seventh Edition. Los Angeles, CA: Muthén & Muthén (1998–2015).

53. Hayes AF. Beyond Baron and Kenny: Statistical mediation analysis in the new millenium. Commun Monogr (2009) 76:408–20. doi: 10.1080/03637750903310360

54. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model (1999) 6(1):1–55. doi: 10.1080/10705519909540118

55. Cohen J. The effect size. Stat Power Anal Behav Sci (1988), 77–83. doi: 10.1001/jamapsychiatry.2013.504

56. Kenny DA, Judd CM. Power anomalies in testing mediation. Psychol Sci (2014) 25(2):334–9. doi: 10.1177/0956797613502676

57. Pouwelse M, Bolman C, Lodewijkx H, Spaa M. Gender differences and social support: Mediators or moderators between peer victimization and depressive feelings? Psychol Schools (2011) 48(8):800–14. doi: 10.1002/pits.20589

58. Guy A, Lee K, Wolke D. Differences in the early stages of social information processing for adolescents involved in bullying. Aggress Behav (2017) 43(6), 578–87. doi: 10.1002/ab.21716

59. Sutton J, Smith PK, Swettenham J. Social cognition and bullying: Social inadequacy or skilled manipulation? Br J Dev Psychol (1999) 17:435–50. doi: 10.1348/026151099165384

60. Karademas EC. Positive and negative aspects of well-being: Common and speciﬁc predictors. Pers Individ Dif (2007) 43:277–87. doi: 10.1016/j.paid.2006.11.031

Keywords: bullying, perpetrators, social support, self-efficacy, resilience, cross-cultural differences, positive mental health, mental illness

Citation: Lin M, Wolke D, Schneider S and Margraf J (2020) Bullying History and Mental Health In University Students: The Mediator Roles of Social Support, Personal Resilience, and Self-Efficacy. Front. Psychiatry 10:960. doi: 10.3389/fpsyt.2019.00960

Received: 15 April 2019; Accepted: 04 December 2019; Published: 14 January 2020.

Reviewed by:

Copyright © 2020 Lin, Wolke, Schneider and Margraf. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jürgen Margraf, [email protected]

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

The Many Faces of Bullying

Listening when kids talk about peer interactions helps parents detect bullying..

Posted August 30, 2024 | Reviewed by Tyler Woods

How to Handle Bullying
Take our Anger Management Test
Find counselling to support kids or teens
Kids can work some problems out, but young kids need parents' guidance on how to resolve social challenges.
Actively listening when children talk about peer interactions helps parents detect bullying.
Gordon Allport's contact hypothesis can help explain why being around an excluded peer can halt bullying.
If parents learn that their child has bullied others, they benefit in the long term by correcting their child.

In an age of parents tending to stick up for their kids before really thinking about right and wrong, the parents who slow down and consider what's best for everyone will ultimately win by raising the best kids. Leslie Blanchard wrote an essay on this exact topic entitled: “I’m Raising a Bully.” Rather than candy-coating the situation of her daughter leaving a well-meaning peer out “just because,” this mother of five called her daughter out for bullying and then publicly admitted to it on social media . While she recognized her daughter and other classmates’ actions were not overtly cruel, she understood that avoiding a peer who was attempting to become a friend is a more covert form of bullying. This mother’s ability to empathize with another child rather than protect her own “at all costs” proved to be quite valuable. Instead of sympathizing with "how annoying" her daughter’s classmate probably was, she gave her daughter a task to get to know the other girl. It was not a suggestion, not a choice, but a requirement to come home the next day and “report three cool things she found out” about the other child.

Blanchard’s resolve to cut her daughter’s exclusion of a peer off at the pass was a brave and brilliant act of parenting . She taught her daughter and the other girl a very important lesson. She also warded off the chance of her daughter’s actions escalating over the years into more overt bullying by accepting, quietly consenting, or even encouraging her actions.

In addition to making a plan with her daughter to get to know the other child and checking in about how it went, this conscientious mother went a step further and risked her own precious pride to check in with the other girl’s mother. To admit that her daughter was not “perfect” (thereby, she was not a “perfect” parent) was brave. Blanchard rightly points out that other parents’ attempts to stay out of their children’s peer interactions and let them handle it on their own is wrong. Fourth graders do not have the life experience or the brain development to just “know” how to handle such complicated social interactions. They need guidance. They need support. They need parents to follow up with them and with each other. They need to understand how values of inclusion and non- prejudice play into their lives with clear, concrete examples from their own lives.

It is important for parents to see the forest for the trees. In this age of “helicopter parents” who hover, fixating on the details of their children’s lives, there can be many missed opportunities to teach children how to become good humans. Speaking frankly and collaboratively with children about how to solve problems and modeling examples of challenges that parents have to overcome themselves (without sharing too many details!) can help children start to think independently about how to solve problems. Children who are popular and well-liked, as Blanchard’s daughter is, have the somewhat unique opportunity to serve as an example of inclusion and open-mindedness. These children’s peers look up to them. They can model behavior that helps everyone act more kindly and inclusively and breaks down prejudice in young friend groups. Or they can lead the bully charge. Who do you want your child to become?

Daniela Owen, Ph.D., is a clinical psychologist and children's book author who uses evidence-based strategies to help children live mentally healthier lives.

Find a Therapist
Find a Treatment Center
Find a Psychiatrist
Find a Support Group
Find Online Therapy
International
New Zealand
South Africa
Switzerland
Asperger's
Bipolar Disorder
Chronic Pain
Eating Disorders
Passive Aggression
Personality
Goal Setting
Positive Psychology
Stopping Smoking
Low Sexual Desire
Relationships
Child Development
Self Tests NEW
Therapy Center
Diagnosis Dictionary
Types of Therapy

Sticking up for yourself is no easy task. But there are concrete skills you can use to hone your assertiveness and advocate for yourself.

Emotional Intelligence
Gaslighting
Affective Forecasting
Neuroscience

Research article
Open access
Published: 22 November 2021

Bullying in schools: prevalence, bystanders’ reaction and associations with sex and relationships

Temesgen Demissie Eijigu ORCID: orcid.org/0000-0001-8846-8844 1 &
Seleshi Zeleke Teketel 2

BMC Psychology volume 9 , Article number: 183 ( 2021 ) Cite this article

10k Accesses

5 Citations

1 Altmetric

Metrics details

Bullying and peer victimization are the most pressing social problems affecting the wellbeing of children and adolescents. This study attempts to estimate the prevalence and examine the association of bystander’s sex, her/his relationship with the victim and with the bully, and bystander’s reaction to school bullying in East Gojjam Administrative Zone, Ethiopia.

This study followed an explanatory mixed-method study design. For the quantitative phase, 612 participants were selected using multistage cluster sampling techniques and for qualitative phase, 18 participants were selected using purposive sampling technique. We used self-reported questionnaires and semi-structured interviews to collect data from students attending grades 7, 8, 9, and 10.

This study revealed that 55% of bystanders remained passive while 38% of them defended the victim upon witnessing bullying incidents. Pearson Chi-Square test for independence indicated a significant association between bystanders’ relationship with the victim and/or bully, and bystanders’ reaction. In contrast, sex has no significant association with bystanders’ reaction. The semi-structured interview data also suggested that large number of bystanders most often stood by passively while some of them defended the victim.

The practice of defending among students attending their education in governmental primary and secondary schools in East Gojjam Administrative Zone was low. Close social relationships (being close friends, relatives, and classmates) with the victim and bully were significantly associated with the practice of defending.

Peer Review reports

Bullying and peer victimization are the most pressing social problems affecting the wellbeing of children and adolescents [ 1 ]. Although bullying occurs in many contexts [ 2 ], it is predominantly prevalent within a school setting [ 3 , 4 ]. For instance, over 90% of primary and secondary school students in Australia witnessed verbal bullying, and more than 60% witnessed physical bullying in their schools [ 5 ]. Moreover, a study on the prevalence of being bullied in South Australian schools depicted that approximately one of every two secondary school students experienced victimization by peers while at school [ 3 ].

The problem of violence and bullying is also prevalent in Ethiopia [ 6 , 7 , 8 , 9 , 10 ]. A study in Addis Ababa revealed that 84% of teachers and directors confirmed that violence is a problem in and around primary and secondary schools, mainly targeting girls and smaller children [ 7 ]. Similarly, a national study in Ethiopia revealed that 13.1% and 16.7% of children have been left out and hit by other children, respectively, in their class [ 10 ].

The situation of school bullying in the East Gojjam Zone does not seem an exception. For example, in the 2014 academic year, more than 57% of students in Menkorer High School at Debre Markos Town, the capital of East Gojjam Administrative Zone, experienced physical and sexual violence [ 11 ].

School bullying is viewed as a group phenomenon that, in addition to bullies and victims, involves a large number of bystanders who witness bullying [ 12 , 13 , 14 ]. For instance, two studies in Canada illustrated that peer bystanders were present in more than five out of six bullying episodes [ 13 , 14 ]. Another natural observational research also reported that peers were present closely in nine out of ten bullying episodes [ 13 ]. Although bullying often occurs in the presence of large bystanders who have a high potential to reduce it, most do not intervene to stop it [ 13 , 14 ].

In bullying situations, bystanders may take the following four roles: (1) assistants, who join in the bully’s side (2) reinforcers, who encourage bullies (3) passive bystanders, who merely watch what is happening and (4) defenders, who stand up on behalf of victims [ 12 ]. Recent studies proposed three forms of bystander roles as passive bystanders, defenders, and pro-bully/bully supporters/by combining the roles of assistant and reinforcers [ 15 ].

A study in 1220 elementary school children from grades four to six found that low scores on the anti-bullying attitude scale were associated with bullying, assisting the bully, and reinforcing the bully. In contrast, high scores on that scale were related to defending the victim and remaining passive in bullying situations [ 16 ]. Since passive bystanders scored high in anti-bullying attitude and moral disapproval scores of bullying, it is easier to change them to the defenders than assistants and reinforcers. Thus, passive bystanders were the focus of this study. Besides, passive bystanders and defenders account for more than half of the bystanders who could play a key role in reducing bullying. To our knowledge, no previous studies in Ethiopia estimated the extent of defenders and passive bystanders during bullying in primary and general secondary school students. Thus, one of the focuses of this study was to estimate the extent of defending and passive bystanding behaviors during school bullying.

Empirical findings reported gender differences in defending and passive bystanding behavior [ 5 , 17 , 18 , 19 , 20 ]. Several studies revealed that girls are more involved in defending the victim [ 16 , 17 , 20 , 21 , 22 ] and remaining passive in bullying situations than boys, whereas boys were more involved in supporting bullies as assistants and reinforcers than girls [ 16 , 17 , 20 , 23 ]. In addition, some studies have shown a significant association between the gender of the bystander, the gender of the bully, and the victim [ 13 ]. Their findings suggest that boys are more likely to defend when the bully or victim is male, whereas girls are more likely to defend when the bully or victim is female. Likewise, some studies [ 24 , 25 ] documented that students were more likely to defend their same-sex peers than opposite-sex peers. This shows that previous studies emphasized sex differences and how bystanders are more likely to help the same sex victim [ 17 , 18 , 19 ]. They did not answer the question, “To what extent do female and/or male bystanders defend or remain passive upon witnessing a girl victimizing a boy, a boy victimizing a boy, a boy victimizing a girl, and a girl victimizing a girl. Thus, further research is needed to fill these knowledge gaps.

Furthermore, bystanders’ relationships with the victim or bully may also influence defending or passive bystanding behavior [ 26 , 27 ]. These studies revealed that bystanders who had a close relationship with the victim are more likely to help the victim, whereas those who had a close relationship with the perpetrator and no relationship with the victim are more likely to remain passive; sometimes it may even initiate co-bullying [ 26 ]. The motives for co-bullying or non-intervention, were reported to come from fear of friendship loss, perceived peer pressure, or to not disprove the actions of friends.

In the culture of Amhara, when one's close relative or friend is attacked, he/she will not watch the incident passively. At least, he/she is expected to separate the bully and the victim. This strong social bond among Amhara society [ 28 ] makes it reasonable to include bystanders’ relationship with the bully and victim in the study.

Research question

This research planned to answer the following questions:

To what extent do students defend or remain passive during bullying incidents in primary and secondary schools in East Gojjam Administrative Zone?

To what extent do male and female bystanders defend or remain passive upon witnessing a boy victimizing a boy, a boy victimizing a girl, a girl victimizing a girl, and a girl victimizing a boy?

Does the relationship between the bystander and the victim or the bystander and the bully make a difference in the bystander’s reaction?

This study aimed to estimate the prevalence and examine the association between bystander’s sex, her/his relationship with the victim and with the bully, and bystander’s reaction to school bullying in East Gojjam Administrative Zone, Ethiopia.

Study design

This study followed an explanatory sequential mixed methods design [ 29 , 30 ] with quantitative data collection and analysis in the first phase and qualitative data collection and analysis in the second phase. Mixed methods design was selected to other designs since the complex nature of bystanding behaviors during school bullying requires an investigation from multiple ways.

The study was conducted in primary and general secondary schools from Aneded, Debre Markos, Enebesie Sar Medir, Enemay, and Machakel Woredas of East Gojjam Administrative Zone, Amhara National Regional State, Ethiopia. These five Woredas consists of 181 second cycle primary schools (Grades 5–8) and 19 secondary schools (grades 9 and 10). Primary and general secondary schools from Woredas in East Gojjam Administrative Zone were selected due to bullying prevalence and its serious consequences. In addition to familiarity with the language and culture, the researcher works in the study area that may contribute to the study.

Participants and sampling techniques

The quantitative data were drawn from 612 students aged 12–16 years attending five primary schools in grades 7and 8 and five general secondary schools in grades 9 and 10 (see Table 1 ). To select participants for this study, we used a multistage cluster sampling procedure. In the first stage, we subdivided the 19 Woredas of East Gojjam Administrative Zone into five groups based on the number of students’ population from grades 7–10. From each group, we selected one woreda randomly. Then, from each woreda, one general secondary school was chosen randomly. Next, for accessibility and comparison purposes, from all primary schools in the area where the selected general secondary schools were situated, one primary school from each woreda was selected by using lottery method. Then, one class from each grade in each school was selected by applying lottery method. Accordingly, 20 classes of students from both primary and general secondary schools (10 classes each) were invited to participate in the study.

On the other hand, the qualitative data were drawn from 18 participants (9 boys and 9 girls) who witnessed bullying incidents. To select participants, a purposive sampling technique was employed. With the help of school principals, homeroom teachers, and classroom representatives, students who usually defend or passively watch when witnessing bullying incidents were selected. Participants’ age ranged from 14 to 16 years, and more than 22% were from rural areas. Concerning grade level, five students were from grade seven, four students from grade eight, five students from grade nine, and four students from grade ten.

Inclusion and exclusion criteria

All students who were attending grades 7–10 education in 20 classes were included in the study. Those students who witnessed bullying were also included in the study. Those students outside the age range of 12–16 years, who did not witness bullying, and absent from class during data collection were excluded from the study.

Data collection instruments

Questionnaire.

To collect quantitative data, self-report questionnaires have been adapted from previous sources [ 17 ]. To estimate the prevalence and examine the association between bystander’s sex, her/his relationship with the victim and with the bully, and bystander’s reaction to school bullying, participants were asked to recall one particular incident where they witnessed a student/s bullying another student since the beginning of this semester. The items included in the questionnaire were: “Describe in brief the nature of the bullying incident you witnessed,” “When and where the bullying incident happened,” “Describe the characteristics of the victim and the bully (sex, grade, bystander’s relationship with the victim/bully such as close relative, close friend, classmate, a person that I knew but have no close relationship, or person that I did not know),” and “What did you do when you witnessed bullying incident?”.

A bystander was placed into categories of defender, passive bystander, and bully supporter based on his/her reactions to the bullying incident in the school:

If a student answers, “I joined in the bullying when the bully had started it,” “I assisted the bullying by doing something for the bully”, and/or “I giggled, laughed, shouted, or made similar reactions,” s/he is categorized under “bully supporter.”

If a student answers, “I kept looking at the bullying without siding anyone,” “Nothing, I went away from the situation,” and/or “Nothing, I pretended not to notice what was happening,” s/he is categorized under “passive bystander.”

If a student answers, “I tried to help in some way but was not successful,” and/or I tried to help in some way and was successful,” s/he is categorized under “defender.”

The English version of the instrument was translated into the Amharic language by three language experts who have Ph.D. in Teaching Amharic, Linguistic, and Teaching English as a Foreign Language and whose mother tongue was Amharic. The principal investigator of this study synthesized a single version by combining the best cultural translation of each item. The appropriateness of the synthesized translated version was judged by three language experts (two Amharic, one English) and two psychologists. By taking into account the feedback offered by professionals, in view of the study's objectives and reviewed literature, the researcher of this study revised the synthesized translated version of the instrument. An expert from Debre Markos University who had a doctoral degree in Teaching English as a Foreign Language back-translated the synthesized version from Amharic into English. Moreover, the Amharic version of the instrument was submitted to seven psychology instructors of Debre Markos University to assess the instruments' content validity. Based on comments of experts, some items were modified. Finally, the questionnaire was administered to the participants during the period 01–31 January 2019.

Semi-structure interview

The interviews were conducted face to face by the principal investigator from 01 April to 02 May 2019 using semi-structured open-ended items with probing questions. Interviews were conducted at the offices of the counselor, or school director lasted between 30 and 45 min. Students were alone (not accompanied by guardians/parents) when interviews were administered. All interviews were audio-recorded, transcribed, and notes were taken properly. Items in the interview guide include: “If you have witnessed someone being bullied by another student, tell me what happened?”, “How did you feel when you saw bullying happening?”, “What did you do when you witnessed bullying happening? Why?”, “Who else witnessed the bullying situations besides you?”, “What did they do when this was happening?”, “Why do you think they reacted this way?”, “Why do you think that some students defend and others remain silent in bullying incidents?” and “How do you describe boys and girls' engagement in defending or passive bystanding behaviors?”.

Data analysis techniques

Researchers employed percentage to describe the rate of defending and passive bystanding behavior during bullying incidents for data analysis. Chi-square test of independence was used to check the association between bystanders’ sex, their relationship with the victim and with the bully, and their reaction to the bullying incident. Thematic analysis [ 31 ] was used to analyze the qualitative data.

Ethical considerations

Addis Ababa University School of Psychology Ethical Review Committee exempted the study from requiring ethical clearance and suggested collecting letter of permission from the school of Psychology. Accordingly, a letter of permission was collected from the School of Psychology, Addis Ababa University.

Permission letters were submitted to East Gojjam Administrative Zone Education Office. The office itself wrote a letter of permission to school directors. After receiving permission from school directors, students were also asked their willingness to participate in the study. Before data collection, informed assent and passive consent were secured from students and parents, respectively. Students were also informed that they would be free to omit any questions they did not want to answer. The participants were also informed that their identity would not be disclosed to any third party, and the information they provided would be kept confidential.

The extent of defenders, passive bystanders, and bully supporters

Out of 511 participants who reported witnessing a single bullying incident, 55% of bystanders reported being passive bystanders, and 38% of them reported being defenders (see Table 2 ). The Chi-Square test revealed significant differences between the three percentages, x 2 (2, N = 511) = 181.131, p = 0.000.

In the semi-structured interview, all of the participants agreed that most of the students did not want to defend the victims when witnessing school bullying. For instance, One interviewee stated, “Those who stand and watch victimization were larger than those who defend because they have the interest to see the fight and to know who wins at the end.”

The extent of students involved in defending, passive bystanding, and bully supporting by bully-victim sex

As shown in Table 3 , 39.3% of bystanders witnessed male victimizing male, 33.1% witnessed male victimizing female, 20.2% witnessed female victimizing female, and 7.4% witnessed female victimizing male.

Since the bully support role expected frequencies were less than 5 in more than 8% of the cells [ 32 ], and the purpose of the study focused on defending and passive bystanding behaviors, the bully support role was removed from further analysis (see Table 4 ).

The Chi-Square test revealed no significant association between bully-victim sex and bystander’s reaction, χ 2 (3, N = 475) = 1.956, p = 0.58, Cramer’s V = 0.06.

The extent to which male and female bystanders defend, or remain passive upon witnessing victimization across bully-victim sex

Tables 5 , 6 , 7 and 8 summarizes that 67.2% of males and 32.8% females had witnessed male victimizing male, 31.2% males, and 68.8% females witnessed male victimizing femalel, 14.4% males and 85.6% females witnessed female victimizing female, and 63.9% males and 36.1% females witnessed female victimizing male.

Among students who witnessed male victimizing male, 40.2% of boys and 38.7% of girls defended victims. Besides, 36% of boys and 49.1% of girls who witnessed male victimizing female helped victims in some way. Regarding students who saw female victimizing female, 46.2% of boys and 35.1% of girls defended victims. Moreover, 30.4% of boys and 53.8% of girls helped victims when witnessing female victimizing male.

The Chi-Square test revealed no significant association between bystander’s sex with victimization across bully-victim sex and bystander’s reaction. The Chi-Square test values were χ 2 (1, N = 189) = 0.001, p = 0.974, phi = − 0.014, for students witnessing male victimizing male; χ 2 (1, N = 160) = 1.881, p = 0.170, phi = − 0.122, for students witnessing male victimizing female; and χ 2 (1, N = 36) = 1.057, p = 0.304, phi = − 0.231, for students witnessing female victimizing male.

The interview data revealed that boys and girls intervened when witnessing school bullying. For instance, Hermela noted, “When male victimizes female, mostly girls hold girls and boys hold boys.” Kidist, a ninth-grade student, also indicated, “When female victimizes female, both boys and girls may intervene.”

The qualitative data demonstrated a dissimilar intervention approach between girls and boys when witnessing male physically victimizing male. Male students, most of the time, defend directly when witnessing male physically victimizing male. On the other hand, girls can participate in defending indirectly by screaming or calling other students or reporting the case to the school authority. For instance, Hermela says, “When male physically attacks male, mostly boys and teachers directly intervene.” Debasu, an eighth-grade student said “If a girl directly intervenes when male is victimized, rumors will spread which show the girl has love affair with the victim.”

The extent of students’ participation in defending and passive bystanding behavior by relationship with the victim or bully

As indicated in Tables 9 and 10 , bystanders were asked to report their relationship with victims and bullies. Among those who reported their relationship with victims and bullies, 3.6% and 3.8% reported to be relatives, 26.7% and 11.6% close friends, 24.6% and 24.2% classmates, 24.6% and 26.3% knew the victim/bully, but have no close relationships, and 20.4% and 34.1% did not know the victim and bully, respectively. Among those who reported their relationship with the victim, 52.9% of relatives, 60.6% of close friends, and 47.8% of classmates defended the victim. Similarly, among those who reported their relationship with the bully, 61.1% of relatives, 49.1% of close friends, and 47% of classmates defended the victim.

The Chi-Square test revealed that there is a significant association between the relationship with the victim and bystander’s reaction, χ 2 (4, 475) = 32.79, p < 0.001, phi = − 0.263; and between relationship with the bully and bystander’s reaction, χ 2 (4, N = 475) = 9.847, p = 0.043, phi = − 0.114.

The qualitative data through interview indicated that bystanders’ close relationship with the victim or/and bully as key determinant of defending upon witnessing school bullying. For instance, Debasu said “I have entered (involved in defending) because both the perpetrators and the victims were my friends.” A grade eight student named Binyam stated, “Students who are relative or close friends…to the victim/bully would not have any role other than separating the bully and the victim.” Hermela also noted that relatives, friends, and teachers are defenders during victimization.

On the other hand, not being a friend of the bully or the victim was reported as a possible reason for bystanders’ passive bystanding. For instance, Hermela mentioned “bystanders’ not being the friend of the bully or the victim as one reason for bystanders to surround and watch bullying events. Had the bystanders been friends of the victim/bully, they would have intervened or they would have called a teacher.”

The extent to which students defend or passively watch during bullying incidents

The findings of this study revealed that a larger proportion of students remained passive upon witnessing school bullying. Fifty five percent of bystanders were involved in passive bystanding behavior, and 38% of them involved in defending behavior.

The interview data also supported the findings of the quantitative data. All participants of the interview reported that many bystanders most often stood by passively, and only some of them defended the victim. Many participants concisely stated that when students in school witness bullying incidents, most of them often stand and observe while a small number of others decide to defend.

These findings are consistent with prior studies [ 14 , 17 ]. For instance, a study conducted on college students who recalled bullying events occurring in junior high school and high school students with the same method reported that 59% of bystanders chose to remain passive upon witnessing bullying situations, and 31% of them were involved in defending on behalf of the victims [ 17 ]. Similar findings were also reported in an observational study conducted in two Toronto school children in Canada [ 14 ]. Even the percentages are very close to the ones this study found.

There are various explanations attributed to the surpassing of passive bystanders to defenders in East Gojjam Administrative Zone. One reason for passivity of bystanders during bullying incidents may involve the gradual decline of helping relationships due to urbanization. In the past, people do not often standby and watch when one individual victimized another. Findings in Yetmen, East Gojjam, revealed that when conflicts arise within and between households, they were usually resolved by neighbors. If neighbors cannot solve the problem, relatives of the two parties consider the problem and try to address it. If this level of conflict resolution fails, the elder of the community get involved [ 28 ]. So, helping each other during an emergency was the norm. Due to urbanization, the norms of helping relationships are changing somehow in the current East Gojjam. Another possible explanation for more passive bystanders to defenders involves fear of revenge. If the perpetrator is older and/or physically stronger than the bystander, the bystanders are more likely to remain passive. Student bystanders may believe that defending on behalf of the victim could lead the older/or stronger bully to attack the defender later. Many other personal and situational factors (e.g., lower level of bystander’s self-efficacy, empathy, lower number of close friends, bullying experiences, high moral disengagement) may also be used to explain greater proportions of passive bystanders to defenders in bullying situations [ 17 , 20 , 22 , 26 , 33 ].

The quantitative findings demonstrated that there were no significant difference between boys and girls in defending and passive bystanding behaviors upon witnessing a boy victimizing a boy, a boy victimizing a girl, and a girl victimizing a boy.

According to the interview data, both boys and girls can intervene when a boy victimizes a boy. But, their style of intervention may differ. Boys may intervene directly when witnessing physical bullying, whereas girls may intervene indirectly. Many participants said that boys, teachers, and adults directly intervene when a boy physically victimizes a boy. One possible reason for the direct intervention of more boys than girls was that if a girl intervenes directly when a boy victimizes a boy, rumors of love between the girl and the victim will spread. In the culture of the study area, having a boyfriend for a girl and a girlfriend for a boy is not a commonly accepted norm at that age level. If they establish such kinds of friendship, they do not disclose it to others. If other students know the relationship, they become the target of the rumor. So as to avoid being the target of the rumor, the girl will decide to use indirect strategies to help the victim.

Another possible explanation for more direct defending of boys than girls in physical bullying was that boys were more often socialized and culturally expected to defend directly than girls. Let alone defending on behalf of the victim, boys are expected to be a winner in any fight by their families and are not accepted by families if beaten up by anyone. If they fail to win the fight, their parents could further beat them. Though girls’ involvement in separating the bully and the victim is less direct, they frequently call defenders by screaming.

The finding also indicated that when a boy victimizes a girl, a girl victimizes a girl, and a girl victimizes a boy, most of the interview participants reported that both boys and girls are engaged in defending. This finding partly contradicts some other findings [ 24 , 25 ]. To explain these findings further, future researches are needed.

The current study revealed that students who were reported to be close friends, classmates, and relatives of the victims appear to defend the victim more than persons who either knew the victim or did not know them. Consistent with the current study, five studies included in one systematic review have examined the association between friendship with students involved in bullying situations and defending [ 33 ]. The studies revealed that youth were more likely to defend when the victimized youth was their friend, relative to a neutral peer. Similarly, some studies [ 26 , 27 ] revealed the association between bystanders’ close relationship with the victim and helping. For example, suppose a bystander is watching one’s own friend being bullied. In that case, the situation evokes more distressing emotions of empathy, sympathy, guilt, or anger and a stronger moral obligation and responsibility to intervene to help one’s friend [ 27 ].

The findings from the interview data also corroborated the quantitative results. The study showed that after bystanders witnessed bullying incidents, they evaluate their relationships (friendship, kinship, and disliking) with the bully, victim, or both before deciding to defend or passively watch the bullying incident. If bystanders witness victims with intimate relationships (friendship and blood relationship), they are more likely to defend the victim. Participants mentioned being close friends, relatives, and teachers with the victim as contributing factors to defending.

The finding that students who were reported to be relatives, close friends, and classmates of the bully appear to defend the victim more than persons who know and those who did not know the bully was unexpected. The qualitative interview also supported this finding. Some interview participants disclosed that having a close relationship with the bully would motivate the bystander to assist the victim. If bystanders are close friends or relatives of the bully, they can enter with confidence to protect the victim believing that the bully will not attack them later. Another possible reason for bystanders who have close relationships with the bully to stop the bully could be the belief that the problem will worsen and affect the whole family and its relatives. However, one participant reported that if bystanders have a close relationship with the bully, they might assist the bully to harm the victim further. Thus, further studies are needed.

Limitations of the study

The current study has some limitations. First, the study participants were limited to young and middle adolescents in East Gojjam Administrative Zone. This could reduce the diversity of the sample and the generalizability of the findings. Had I included adults as well, the findings could have been more generalizable. Second, the quantitative and qualitative findings on defending and passive bystanding behaviors were based on self-report measures. In self-reporting data, study participants may not always provide honest evidences. Third, the current research was cross-sectional, where cause and effect relationships could not be inferred.

Fourth, it is expected that if the perpetrator is older and/or physically stronger than the bystander, the bystander is more likely to remain passive during the incident of bullying. However, the current study did not collect information on age and/or physical differences between bully and bystander. If future studies include age and physical differences between the bystander and the bully, it would have more insights into school bullying literature.

Practice of defending among students attending their education in governmental primary and secondary schools in East Gojjam Administrative Zone was low. Close social relationships (being close friends, relatives, and classmates) with the victim and bully were significantly associated with the practice of defending. The findings of our qualitative study also showed that the number of passive bystanders was larger than defenders during witnessing school bullying; and bystanders’ close relationship with the victim, or/and bully as key determinants of defending.

High prevalence of passive bystanding behavior demand prevention programs that can discourage bullying in schools among bystanders in bullying situations through encouraging defending behavior irrespective of bully-victim sex, and helping bystanders establish close social relationships with the victim or/and bully.

Availability of data and materials

The datasets that support the findings of this study are not publically available at present. The authors need to use the data for further works before data could be made available. Besides, we have not received consent from participants to share the data on the web but, will be available from the corresponding author on reasonable request.

Hong JS, Espelage DL. A review of research on bullying and peer victimization in school: an ecological system analysis. Aggress Violent Behav. 2012;17:311–22.

Article Google Scholar

Smith PK, Sharp S, editors. The problem of school bullying. New York: USA Routledge; 1994.

Google Scholar

Delfabbro P, Winefield T, Trainor S, Dollard M, Anderson S, Metzer J, et al. Peer and teacher bullying/victimization of South Australian secondary school students: prevalence and psychosocial profiles. Br J Educ Psychol. 2006;76:71–90.

Harris S, Petrie GF. Bullying: the bullies, the victims, the bystanders. Lanham: The Scarecrow Press, Inc.; 2003.

Rigby K, Johnson B. Expressed readiness of Australian Schoolchildren to act as bystanders in support of children who are being bullied. Educ Psychol. 2006;26(3):425–40.

Amogne A. Indiscipline problems of high school students: the case of Ethio-Japan Hidasse Secondary School (Addis Ababa, Ethiopia). J Educ Pract. 2014;5(37):23–8.

Dereje T, Derese M, editors. Violence in Ethiopian schools: a study of some schools in Addis Ababa. Lausanne: United Nations Educational, Scientific and Cultural Organization; 1997.

Habtamu W. Interpersonal violence in Addis Ababa secondary schools: an iceberg of challenges to the democratization of education in Ethiopia. Addis Ababa: IER/AAU; 1998.

Kinde G, Meknnen S. Types, magnitude, predictors, and controlling mechanisms of aggression in secondary schools of Jimma zone. Ethiop J Educ Sci. 2007;2(2):39–61.

Yehualashet M, Negussie D. Children’s worlds national report Ethiopia. Addis Ababa: The African Child Policy Forum; 2015.

Getachew M, Ayu G, Desalegne A, Animut A, Fasil W, Chalachew T, et al. Prevalence of gender based violence and associated factors among female students of Menkorer high school in Debre Markos town. Northwest Ethiop Sci J Public Health. 2015;3(1):67–74.

Salmivalli C, Lagerspetz K, Bjorkqvist K, Osterman K, Kaukiainen A. Bullying as a group process: participant roles and their relations to social status within the group. Aggress Behav. 1996;22:1–15.

Hawkins DL, Pepler DJ, Craig WM. Naturalistic observations of peer interventions in bullying. Soc Dev. 2001;10(4):512–27.

O’Connell P, Pepler D, Craig W. Peer involvement in bullying: insights and challenges for intervention. J Adolesc. 1999;22:437–52.

Thornberg R, Jungert T. Bystander behavior in bullying situations: basic moral sensitivity, moral disengagement and defender self-efficacy. J Adolesc. 2013;36(3):475–83.

Salmivalli C, Voeten M. Connections between attitudes, group norms, and behavior in bullying situations. Int J Behav Dev. 2004;28(3):246–58.

Oh I, Hazler RJ. Contributions of personal and situational factors to bystanders’ reactions to school bullying. Sch Psychol Int. 2009;30(3):291–310.

Gini G, Albiero P, Benelli B, Altoe G. Does empathy predict adolescents’ bullying and defending behavior? Aggress Behav. 2007;33:467–76.

Pronk J, Olthof T, Goossens FA. Factors influencing interventions on behalf of victims of bullying: a counterfactual approach to the social cognitions of outsiders and defenders. J Early Adolesc. 2014;36(2):267–91.

Pöyhönen V, Juvonen J, Salmivalli C. What does it take to stand up for the victim of bullying? The interplay between personal and social factors. Merrill-Palmer Q. 2010;56(2):143–63.

Obermann M. Moral disengagement in self-reported and peer-nominated school bullying. Aggress Behav. 2011;37:133–44.

Gini G, Pozzoli T, Bussey K. The role of individual and collective moral disengagement in peer aggression and bystanding: a multilevel analysis. J Abnorm Child Psychol. 2015;43:441–52.

Pouwels JL, Lansu TAM, Cillessen AHN. Participant roles of bullying in adolescence: status characteristics, social behavior, and assignment criteria. Aggress Behav. 2016;42:239–53.

Fox CL, Jones SE, Stiff CE, Sayers J. Does the gender of the bully/victim dyad and the type of bullying influence children’s responses to a bullying incident? Aggress Behav. 2014;40:359–68.

Sainio M. Same- and other-sex victimization: risk factors, consequences, and protection by peers. Turku: University of Turku; 2013.

Thornberg R, Tenenbaum L, Varjas K, Meyers J, Jungert T, Vanegas G. Bystander motivation in bullying incidents: To intervene or not to intervene? West J Emerg Med. 2012;13(3):247–52.

Forsberg C, Thornberg R, Samuelsson M. Bystanders to bullying: fourth- to seventh-grade students’ perspectives on their reactions. Res Pap Educ. 2014;29(5):557–76.

WIDE1. research done 1994/5. 1994/5.

Creswell JW. Educational research: planning, conducting, and evaluating quantitative and qualitative research. 4th ed. Boston: Pearson Education, Inc.; 2012.

Creswell JW. Research design: qualitative, quantitative, and mixed methods approach. 3rd ed. Los Angeles: SAGE Publications, Inc.; 2009.

Braun V, Clarke V. Successful qualitative research a practical guide for beginners. Los Angeles: SAGE Publications Ltd; 2013.

Ho R. Handbook of univariate and multivariate data analysis and interpretation with SPSS. Boca Raton: Chapman & Hall; 2006.

Book Google Scholar

Lambe LJ, Cioppa VD, Hong IK, Craig WM. Standing up to bullying: A social ecological review of peer defending in offline and online contexts. Aggress Violent Behav. 2019;45:51–74.

Download references

Acknowledgements

The authors would like to thank Addis Ababa University for its financial support. We would also like to thank teachers at primary and secondary schools in East Gojjam Administrative Zone for their invaluable assistance in collecting data. Finally, we would like to acknowledge principals for facilitating the data collection and all participants of this study for their time and patience in responding to our interviews and questionnaires.

Addis Ababa University financially supported this study. However, the University did not have any role in the design of the study, data collection, and analysis, as well as in the interpretation of data and writing this manuscript.

Author information

Authors and affiliations.

Department of Psychology, Institute of Educational and Behavioral Sciences, Debre Markos University, Debre Markos, Ethiopia

Temesgen Demissie Eijigu

School of Psychology, Addis Ababa University, Addis Ababa, Ethiopia

Seleshi Zeleke Teketel

You can also search for this author in PubMed Google Scholar

Contributions

TDE has been involved in the study concept and design, data acquisition, drafting the manuscript, administrative, statistical analysis, and interpretation of the data and final proof of the manuscript. SZT has been involved in the study concept and design, technical and study supervision, and manuscript revision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Temesgen Demissie Eijigu .

Ethics declarations

Ethics approval and consent to participate.

The Department of Psychology at Addis Ababa University approved the study procedures for the dissertation, of which this manuscript is part of the dissertation. Psychology Department Ethical Committee exempted from requiring ethical clearance since this study collected data from schools with no physical or psychological harm on participants. Written informed consent was obtained from parents, and informed assent was obtained from student participants. The questionnaires were anonymous and fictitious names were assigned to interviewees. No payment was made to all participants, and interviews were conducted individually by the corresponding author.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Eijigu, T.D., Teketel, S.Z. Bullying in schools: prevalence, bystanders’ reaction and associations with sex and relationships. BMC Psychol 9 , 183 (2021). https://doi.org/10.1186/s40359-021-00685-5

Download citation

Received : 13 November 2020

Accepted : 09 November 2021

Published : 22 November 2021

DOI : https://doi.org/10.1186/s40359-021-00685-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Passive bystanding
Bystander reaction

BMC Psychology

ISSN: 2050-7283

General enquiries: [email protected]

Information

Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

Active Journals
Find a Journal
Proceedings Series
For Authors
For Reviewers
For Editors
For Librarians
For Publishers
For Societies
For Conference Organizers
Open Access Policy
Institutional Open Access Program
Special Issues Guidelines
Editorial Process
Research and Publication Ethics
Article Processing Charges
Testimonials
Preprints.org
SciProfiles
Encyclopedia

Article Menu

Subscribe SciFeed
Recommended Articles
Google Scholar
on Google Scholar
Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Imbalance between employees and the organisational context: a catalyst for workplace bullying behaviours in both targets and perpetrators.

1. Introduction

1.1. theoretical approaches—the three-way model, 1.2. theoretical approaches—job demands and resources model, 1.3. theoretical approaches combined—the dimensions of imbalances created by organisations triggering wb, 1.3.1. organisational focus, 1.3.2. organisational atmosphere, 1.3.3. organisational hierarchy, 1.3.4. research hypotheses, 2.1. participants, 2.2. measures, 2.3. procedure, 2.4. data analysis, 3.1. descriptive statistics, 3.2. correspondence analysis on hypothesis, 3.3. correspondence analysis of wb experiences, 4. discussion, 4.1. limitations and future research, 4.2. theoretical and practical implications, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

Ashforth, B.E.; Gioia, D.A.; Robinson, S.L.; Treviño, L.K. Introduction to special topic forum: Reviewing organisational corruption. Acad. Manag. Rev. 2008 , 33 , 670–684. [ Google Scholar ] [ CrossRef ]
Kessler, S.R.; Spector, P.E.; Chang, C.-H.; Parr, A.D. Organisational violence and aggression: Development of the three-factor Violence Climate Survey. Work Stress 2008 , 22 , 108–124. [ Google Scholar ] [ CrossRef ]
Skogstad, A.; Torsheim, T.; Einarsen, S.; Hauge, L.J. Testing the work environment hypothesis of bullying on a group level of analysis: Psychosocial factors as precursors of observed workplace bullying. Appl. Psychol. Int. Rev. 2011 , 60 , 475–495. [ Google Scholar ] [ CrossRef ]
Einarsen, S.; Hoel, H.; Zapf, D.; Cooper, C.L. (Eds.) Workplace Bullying: Developments in Theory, Research and Practice ; Taylor & Francis: Oxfordshire, UK, 2011. [ Google Scholar ]
Salin, D. Organisational responses to workplace harassment. Pers. Rev. 2009 , 38 , 26–44. [ Google Scholar ] [ CrossRef ]
Samnani, A.; Singh, P. 20 Years of workplace bullying research: A review of the antecedents and consequences of bullying in the workplace. Aggress. Violent Behav. 2012 , 17 , 581–589. [ Google Scholar ] [ CrossRef ]
Tuckey, M.; Dollard, M.; Hosking, P.; Winefield, A. Workplace bullying: The role of psychosocial work environment factors. Int. J. Stress Manag. 2009 , 16 , 215–232. [ Google Scholar ] [ CrossRef ]
Demerouti, E.; Bakker, A.B.; Nachreiner, F.; Schaufeli, W.B. The job demands–resources model of burnout. J. Appl. Psychol. 2001 , 86 , 499–512. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Baillien, E.; Rodriguez-Muñoz, A.; Van den Broeck, A.; De Witte, H. Do demands and resources affect victim’s and perpetrators’ reports of workplace bullying? A two-wave cross-lagged study. Work Stress 2011 , 25 , 128–146. [ Google Scholar ] [ CrossRef ]
Balducci, C.; Cecchin, M.; Fraccaroli, F. The impact of role stressors on workplace bullying in both victims and perpetrators, controlling for personal vulnerability factors: A longitudinal analysis. Work Stress 2012 , 26 , 195–212. [ Google Scholar ] [ CrossRef ]
Özer, G.; Escartín, J. The making and breaking of workplace bullying perpetration: A systematic review on the antecedents, moderators, mediators, outcomes of perpetration and suggestions for organisations. Aggress. Violent Behav. 2023 , 69 , 101823. [ Google Scholar ] [ CrossRef ]
Bakker, A.B.; Demerouti, E. The Job Demands-Resources model: State of the art. J. Manag. Psychol. 2007 , 22 , 309–328. [ Google Scholar ] [ CrossRef ]
Hart, P.M.; Cooper, C.L. Occupational stress: Toward a more integrated framework. In Handbook of Industrial, Work and Organizational Psychology ; SAGE: Thousand Oaks, CA, USA, 2001; Volume 2, pp. 93–114. [ Google Scholar ]
Baillien, E.; Neyens, I.; De Witte, H.; De Cuyper, N. A qualitative study on the development of workplace bullying: Towards a three-way model. J. Community Appl. Soc. Psychol. 2009 , 19 , 1–16. [ Google Scholar ] [ CrossRef ]
Berkowitz, L. The frustration-aggression hypothesis: An examination and reformulation. Psychol. Bull. 1989 , 106 , 59–73. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Felson, R.B.; Tedeschi, J.T. Aggression and Violence: Social Interactionists’ Perspectives ; American Psychological Association: Worcester, MA, USA, 1993. [ Google Scholar ]
Salanova, M.; Agut, S.; Peiró, J.M. Linking organisational resources and work engagement to employee performance and customer loyalty: The mediating role of service climate. J. Appl. Psychol. 2005 , 90 , 1217–1227. [ Google Scholar ] [ CrossRef ]
Demerouti, E.; Bakker, A.B. The Job Demands–Resources model: Challenges for future research. SA J. Ind. Psychol. 2011 , 37 , 974–983. [ Google Scholar ] [ CrossRef ]
Schaufeli, W.B.; Bakker, A.B.; Van Rhenen, W. How changes in job demands and resources predict burnout, work engagement, and sickness absenteeism. J. Organ. Behav. 2009 , 30 , 893–917. [ Google Scholar ] [ CrossRef ]
Xanthopoulou, D.; Bakker, A.B.; Demerouti, E.; Schaufeli, W.B. The role of personal resources in the job demands-resources model. Int. J. Stress Manag. 2007 , 14 , 121–141. [ Google Scholar ] [ CrossRef ]
Deci, E.L.; Ryan, R.M. Intrinsic Motivation and Self-Determination in Human Behavior ; Plenum Press: New York, NY, USA, 1985. [ Google Scholar ]
Bakker, A.B.; Van Veldhoven, M.J.P.M.; Xanthopoulou, D. Beyond the Demand-Control model: Thriving on high job demands and resources. J. Pers. Psychol. 2010 , 9 , 3–16. [ Google Scholar ] [ CrossRef ]
Bruursema, K.; Kessler, S.R.; Spector, P.E. Bored employees misbehaving: The relationship between boredom and counterproductive work behavior. Work Stress 2011 , 5 , 93–107. [ Google Scholar ] [ CrossRef ]
Karasek, R.A. Job demands, job decision latitude, and mental strain: Implications for job redesign. Adm. Sci. Q. 1979 , 24 , 285–308. [ Google Scholar ] [ CrossRef ]
Meijman, T.F.; Mulder, G. Psychological aspects of workload. In Handbook of Work and Organisational Psychology , 2nd ed.; Drenth, P.J., Thierry, H., de Wolff, C.J., Eds.; Erlbaum: Mahwah, NJ, USA, 1998; pp. 5–33. [ Google Scholar ]
Van den Broeck, A.; Baillien, E.; De Witte, H. Workplace bullying: A perspective from the job demands-resources model. Scand. J. Ind. Psychol. 2011 , 37 , 1–12. [ Google Scholar ] [ CrossRef ]
Ceja, L.; Escartín, J.; Rodríguez-Carballeira, A. Organisational contexts that foster positive behaviour and well-being: A comparison between family-owned firms and non-family businesses. Rev. De Psicol. Soc. 2012 , 27 , 69–84. [ Google Scholar ] [ CrossRef ]
Parzefall, M.R.; Salin, D. Perceptions of and reactions to workplace bullying: A social exchange perspective. Hum. Relat. 2010 , 63 , 761–780. [ Google Scholar ] [ CrossRef ]
VanOudenhoven, J.P. Do organisations reflect national cultures? A 10-nation study. Int. J. Intercult. Relat. 2001 , 25 , 89–107. [ Google Scholar ] [ CrossRef ]
Gioia, D.A.; Schultz, M.; Corley, K.G. Organisational identity, image, and adaptative instability. Acad. Manag. J. 2000 , 25 , 63–81. [ Google Scholar ]
Stiles, D.R. Pictorial representation. In Essential Guide to Qualitative Methods in Organizational Research ; Cassell, C., Symon, G., Eds.; SAGE Publications: Thousand Oaks, CA, USA, 2004; pp. 127–139. [ Google Scholar ]
Escartín, J.; Sora, B.; Rodríguez-Muñoz, A.; Rodríguez-Carballeira, A. Adaptación y validación de la versión Española de la escala de conductas negativas en el trabajo realizadas por acosadores: NAQ-Perpetrators. Rev. Psicol. Trab. Organ. 2012 , 28 , 157–170. [ Google Scholar ] [ CrossRef ]
Escartín, J.; Rodríguez-Carballeira, A.; Gómez-Benito, J.; Zapf, D. Development and validation of the workplace bullying scale “EAPA-T. Int. J. Clin. Health Psychol. 2010 , 10 , 519–539. [ Google Scholar ]
Landis, J.R.; Koch, G.G. The measurement of observer agreement for categorical data. Biometrics 1977 , 33 , 159–174. [ Google Scholar ] [ CrossRef ]
Leymann, H. The content and development of mobbing at work. Eur. J. Work Organ. Psychol. 1996 , 5 , 165–184. [ Google Scholar ] [ CrossRef ]
van de Velden, M.; van den Heuvel, W.; Galy, H.; Groenen, P.J. Retrieving a contingency table from a correspondence analysis solution. Eur. J. Oper. Res. 2020 , 283 , 541–548. [ Google Scholar ] [ CrossRef ]
Fernández-del-Río, E.; Ramos-Villagrasa, P.J.; Escartín, J. The incremental effect of Dark personality over the Big Five in workplace bullying: Evidence from perpetrators and targets. Personal. Individ. Differ. 2021 , 168 , 110291. [ Google Scholar ] [ CrossRef ]
George, D.; Mallery, P. IBM SPSS Statistics 26 Step by Step. In Routledge eBooks ; Routledge: Oxfordshire, UK, 2019. [ Google Scholar ] [ CrossRef ]
Rayner, C.; Cooper, C.L. The black hole in “bullying at work research”. Int. J. Manag. Decis. Mak. 2003 , 4 , 47–64. [ Google Scholar ] [ CrossRef ]
Bakker, A.B.; Demerouti, E.; Sanz-Vergel, A. Job Demands–Resources Theory: Ten years later. Annu. Rev. Organ. Psychol. Organ. Behav. 2023 , 10 , 25–53. [ Google Scholar ] [ CrossRef ]
Özer, G.; Griep, Y.; Escartín, J. The relationship between organisational environment and perpetrators’ physical and psychological State: A three-wave of longitudinal study. Int. J. Environ. Res. Public Health 2022 , 19 , 3699. [ Google Scholar ] [ CrossRef ]
Jenkins, M.F.; Zapf, D.; Winefield, H.; Sarris, A. bullying allegations from the accused bully’s perspective. Br. J. Manag. 2011 , 23 , 489–501. [ Google Scholar ] [ CrossRef ]
Vranjes, I.; Elst, T.V.; Griep, Y.; De Witte, H.; Baillien, E. What goes around comes around: How perpetrators of workplace bullying become targets themselves. Group Organ. Manag. 2022 , 48 , 1135–1172. [ Google Scholar ] [ CrossRef ]
O’Neill, R.E.; Vandenberghe, C.; Stroink, M.L. Implicit reciprocity norms between employees and their employers: A psychological contract perspective. J. Organ. Behav. 2009 , 30 , 203–221. [ Google Scholar ] [ CrossRef ]
Csikszentmihalyi, M. Flow: The Psychology of Optimal Experience ; Harper & Row: Manhattan, NY, USA, 1990. [ Google Scholar ]
Csikszentmihalyi, M. Finding Flow: The Psychology of Engagement with Everyday Life ; Basic Books; Hachette: London, UK, 1997. [ Google Scholar ]
Glambek, M.; Skogstad, A.; Einarsen, S.V. Do the bullies survive? A five-year, three-wave prospective study of indicators of expulsion in working life among perpetrators of workplace bullying. Ind. Health 1997 , 54 , 68–73. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Özer, G.; Griep, Y.; Escartín, J. A matter of health? A 24-week daily and weekly diary study on workplace bullying perpetrators’ psychological and physical health. Int. J. Environ. Res. Public Health 2023 , 20 , 479. [ Google Scholar ] [ CrossRef ]
Salin, D.; Hoel, H. Organisational causes of workplace bullying. In Workplace Bullying: Development in Theory, Research and Practice ; Einarsen, S., Hoel, H., Zapf, D., Cooper, C., Eds.; Taylor & Francis: Oxfordshire, UK, 2011. [ Google Scholar ]
Salin, D. Ways of explaining workplace bullying: A review of enabling, motivating and precipitating structures and processes in the work environment. Hum. Relat. 2003 , 56 , 1213–1232. [ Google Scholar ] [ CrossRef ]
Escartín, J.; Dollard, M.; Zapf, D.; Kozlowski, S. Multilevel emotional exhaustion: Psychosocial safety climate and workplace bullying as higher level contextual and individual explanatory factors. Eur. J. Work Organ. Psychol. 2021 , 30 , 742–752. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Baseline Characteristics	n	%		n	%
Gender			Supervisor
Males	404	38.7	Not a supervisor	872	83.5
Females	640	61.3	Supervisor	172	16.5
Sector			Civil Status
Education	257	24.6	Single	431	41.3
Industry	96	9.2	Married/Living together	523	50.1
Trade	151	14.5	Separated/divorced	80	7.7
Services	540	51.7	Widowed	10	1.0
Education			Income
No studies	14	1.3	Equal or less than €10k	221	21.2
Basic	123	11.8	€10,001–€20,000	338	32.4
Secondary	409	39.2	€20,001–€30,000	303	29.0
Diploma	211	20.2	€30,001–€40,000	117	11.2
Undergraduate	219	21.0	€40,001–€50,000	32	3.1
Postgraduate	68	6.5	More than €50,000	33	3.2
Contract
No permanent contract	304	29.1
Permanent contract	740	70.9

Organisational Dimensions	Continuum	Example Adjectives
1. Organisational Focus	Task-Focused	Exploitative, obsolete, statistical
	Balanced Focus	Organised, participative, supportive
	Employee-Focused	Unstructured, disorganised, chaotic
2. Organisational Atmosphere	Hostile or Negative	Controlling, manipulative, inhumane
	Balanced or Positive	Amiable, respectful, empathetic
	Too Informal	Overwhelmed, unmotivated, suffocating
3. Organisational Hierarchy	Too Much	Authoritarian, inefficient, dictatorial
	Balanced Hierarchy	Hierarchical, cheerful, coherent
	Too Little	Uncoordinated, little prepared, unclear

Variables		Mean	SD	1	2	3	4	5
1	Age	35.43	10.91	-
2	Gender	1.61	0.49	0.06	-
3	Supervisor	1.16	0.37	0.10 **	−0.08 *	-
4	WB Target Score	0.24	0.41	−0.07 *	−0.04	0.01	-
5	WB Perpetration Score	0.22	0.39	−0.06	−0.08 *	−0.00	0.52 **	-

	WB Perpetration Level
WB Target Level	No WBP	Low WBP	Medium WBP	High WBP	Total	No WBP	Low WBP	Medium WBP	High WBP	Total
No WBT	295	131	7	12	445	28.3%	12.5%	0.7%	1.1%	42.6%
Low WBT	173	228	19	15	435	16.6%	21.8%	1.8%	1.4%	41.7%
Medium WBT	12	43	17	4	76	1.1%	4.1%	1.6%	0.4%	7.3%
High WBT	26	28	21	13	88	2.5%	2.7%	2.0%	1.2%	8.4%
Total	506	430	64	44	1044	48.5%	41.2%	6.1%	4.2%	100.0%

Categories	N	%
Target not a perpetrator	211	20.2
Target perpetrator	388	37.2
Perpetrator not a target	150	14.4
Uninvolved	295	28.3
Total	1044	100.0

WB Categories	Task Focus	Balanced Focus	Employee Focus	Total	Task Focus	Balanced Focus	Employee Focus	Total
Target not a perpetrator	55	66	29	150	7.3%	8.8%	3.9%	20.0%
Target perpetrator	112	107	75	294	15.0%	14.3%	10.0%	39.3%
Perpetrator not a target	30	54	17	101	4.0%	7.2%	2.3%	13.5%
Uninvolved	52	125	27	204	6.9%	16.7%	3.6%	27.2%
Total	249	352	148	749	33.2%	47.0%	19.8%	100.0%

WB Categories	Negative A	Balanced A	Too Informal A	Total	Negative A	Balanced A	Too Informal A	Total
Target not a perpetrator	40	78	28	146	5.5%	10.6%	3.8%	19.9%
Target perpetrator	98	132	60	290	13.4%	18.0%	8.2%	39.6%
Perpetrator not a target	17	65	16	98	2.3%	8.9%	2.2%	13.4%
Uninvolved	24	153	22	199	3.3%	20.9%	3.0%	27.1%
Total	179	428	126	733	24.4%	58.4%	17.2%	100.0%

WB Categories	Too Little H	Balanced H	Too High H	Total	Too Little H	Balanced H	Too High H	Total
Target not a perpetrator	25	79	44	148	3.4%	10.8%	6.0%	20.2%
Target perpetrator	68	124	96	288	9.3%	16.9%	13.1%	39.3%
Perpetrator not a target	16	61	22	99	2.2%	8.3%	3.0%	13.5%
Uninvolved	17	143	38	198	2.3%	19.5%	5.2%	27.0%
Total	126	407	200	733	17.2%	55.5%	27%	100.0%

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

Özer, G.; Escartín, J. Imbalance between Employees and the Organisational Context: A Catalyst for Workplace Bullying Behaviours in Both Targets and Perpetrators. Behav. Sci. 2024 , 14 , 751. https://doi.org/10.3390/bs14090751

Özer G, Escartín J. Imbalance between Employees and the Organisational Context: A Catalyst for Workplace Bullying Behaviours in Both Targets and Perpetrators. Behavioral Sciences . 2024; 14(9):751. https://doi.org/10.3390/bs14090751

Özer, Gülüm, and Jordi Escartín. 2024. "Imbalance between Employees and the Organisational Context: A Catalyst for Workplace Bullying Behaviours in Both Targets and Perpetrators" Behavioral Sciences 14, no. 9: 751. https://doi.org/10.3390/bs14090751

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

COMMENTS

Bullying at school and mental health problems among adolescents: a
Bullying involves repeated hurtful actions between peers where an imbalance of power exists [].Arseneault et al. [] 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 ...
Benefits of Bullying? A Test of the Evolutionary Hypothesis in Three
Abstract. Recent work on bullying perpetration includes the hypothesis that bullying carries an evolutionary advantage for perpetrators in terms of health and reproductive success. We tested this hypothesis in the National Child Development Study ( n = 4998 male, n = 4831 female), British Cohort Study 1970 ( n = 4261 male, n = 4432 female), and ...
Bullying in schools: the state of knowledge and effective interventions
Abstract. During the school years, bullying is one of the most common expressions of violence in the peer context. Research on bullying started more than forty years ago, when the phenomenon was defined as 'aggressive, intentional acts carried out by a group or an individual repeatedly and over time against a victim who cannot easily defend him- or herself'.
Bullying: What We Know Based On 40 Years of Research
WASHINGTON — A special issue of American Psychologist ® provides a comprehensive review of over 40 years of research on bullying among school age youth, documenting the current understanding of the complexity of the issue and suggesting directions for future research. "The lore of bullies has long permeated literature and popular culture. Yet bullying as a distinct form of interpersonal ...
Hypotheses for Possible Iatrogenic Impacts of School Bullying
Most bullying prevention programs incorporate a range of strategies, but we know little about which strategies actively reduce bullying and whether some may have iatrogenic effects. Questions have been raised about programs that involve working with peer bystanders and whether some strategies stigmatize victims. In this article, I propose three ...
Theoretical Perspectives and Two Explanatory Models of School Bullying
Theoretical explanations of bullying may be categorized under three general headings: (1) the nature of the beast, an idiom that conveys the inherent or essential quality or character of something, which cannot be changed and must be accepted (see Anderson, 2022); (2) the nature of the environment, that is, the aggregate of external agents or conditions—physical, biological, social, and ...
Effects of Bullying Forms on Adolescent Mental Health and Protective
1. Introduction. Bullying is intentional and repeated aggressive behavior toward another person in which there is a real or perceived power imbalance, and the victim of bullying feels vulnerable and powerless to protect themselves [1,2,3].Bullying includes physical assault, verbal abuse, and neglect [].Globally, bullying is widespread among adolescents.
Four decades of research on school bullying: An introduction
This article provides an introductory overview of findings from the past 40 years of research on bullying among school-aged children and youth. Research on definitional and assessment issues in studying bullying and victimization is reviewed, and data on prevalence rates, stability, and forms of bullying behavior are summarized, setting the ...
(PDF) Reviewing school bullying research: Empirical findings and
Reviewing school bullying research: empirical. findings and methodical considerations. Hsi-Sheng W ei ∗ Chung-Kai Huang ∗∗. Abstract. This article provides a comprehensive review of previous ...
Theoretical Explanations for Bullying in School: How ...
Bullying is a complex social dynamic that can best be understood by using various theoretical frameworks. The current article uses social capital theory, dominance theory, the theory of humiliation, and organizational culture theory to better understand the motivations behind bullying behavior, bullying's negative effects on victims, and how school culture and climate play a role in the ...
Is Adolescent Bullying an Evolutionary Adaptation? A 10-Year Review
Bullying is a serious behavior that negatively impacts the lives of tens of millions of adolescents across the world every year. The ubiquity of bullying, and its stubborn resistance toward intervention effects, led us to propose in 2012 that adolescent bullying might be an evolutionary adaptation. In the intervening years, a substantial amount of research has arisen to address this question ...
School bullying from a sociocultural perspective
School bullying is an important concern. Whilst there is growing knowledge about the nature, extent and effects of school bullying, areas of complexity in research findings remain. In this paper we develop our thinking on school bullying using a sociocultural theoretical framework. We review existing literature around three main themes: 1) The ...
Psychological processes in young bullies versus bully‐victims
We here investigate this "distinct processes hypothesis," focusing on three psychological processes that are related to bullying behavior in early childhood. First, bully‐victims (but not bullies) may have poor theory of mind skills, or a limited ability to take another person's perspective.
Frontiers
Beliefs about bullying are also influenced by societal values. When examining the relationship between Belief in a Just World (BJW) Hypothesis and responses to bullying, researchers found that higher global BJW, instead of personal BJW, was correlated with minimization of perpetrator actions (Voss and Newman). Therefore, belief in a just world ...
Full article: Understanding bullying from young people's perspectives
With its negative consequences for wellbeing, bullying is a major public health concern affecting the lives of many children and adolescents (Holt et al. 2014; Liu et al. 2014 ). Bullying can take many different forms and include aggressive behaviours that are physical, verbal or psychological in nature (Wang, Iannotti, and Nansel 2009 ).
PDF Observing Bullying at School: The Mental Health Implications of Witness
This study explores the impact of bullying on the mental health of students who witness it. A representative sample of 2,002 students aged 12 to 16 years attending 14 schools in the United Kingdom were surveyed using a questionnaire that included measures of bullying at school, substance abuse, and mental health risk.
Theoretical proposals in bullying research: A review.
Four decades of research into peer bullying have produced an extensive body of knowledge. This work attempts to provide an integrative theoretical framework, which includes the specific theories and observations. The main aim is to organize the available knowledge in order to guide the development of effective interventions. To that end, several psychological theories are described that have ...
The Social Cognitions of Victims of Bullying: A Systematic Review
The nature of the relation between victimization of bullying and social information processing is unclear. The prevention hypothesis predicts that victims focus more on negative social cues to prevent further escalation. In contrast, the reaffiliation hypothesis predicts that victims focus more on positive social cues to restore the social situation. Alternatively, the desensitization ...
Theoretical Explanations for Bullying in School: How Ecological
Bullying is a complex social dynamic that can best be understood by using various theoretical frameworks. The current article uses social capital theory, dominance theory, the theory of ...
Is bullying in adolescence associated with the development of
Being bullied in adolescence is linked to mental health problems like anxiety, depressive- and somatic symptoms and can have negative consequences on both an individual and a societal level. However, evidence regarding the long-term mental health consequences of bullying in adolescence is limited. The aim of this study was to examine whether being bullied at age 15 or 18 was associated with ...
Frontiers
Introduction. Peer bullying at school is highly prevalent and has become an international concern (e.g., 1, 2).Victimization has been universally found to be associated with cross-sectional and long-term adverse mental health consequences, including more severe depression and anxiety symptoms (e.g., 3-5) and lower levels of positive mental health (e.g., 4).
The Many Faces of Bullying
Gordon Allport's contact hypothesis can help explain why being around an excluded peer can halt bullying. If parents learn that their child has bullied others, they benefit in the long term by ...
PDF Qualitative Methods in School Bullying and Cyberbullying ...
School bullying and cyberbullying are complex phenomena, and a range of methodological approaches is thus needed to understand their complexity (Pellegrini & Bartini, 2000; Thornberg, 2011). Indeed, over-relying on quantitative meth-ods limits understanding of the contexts and experiences of bullying (Hong & Espelage, 2012; Patton et al., 2017).
Bullying in schools: prevalence, bystanders' reaction and associations
Background Bullying and peer victimization are the most pressing social problems affecting the wellbeing of children and adolescents. This study attempts to estimate the prevalence and examine the association of bystander's sex, her/his relationship with the victim and with the bully, and bystander's reaction to school bullying in East Gojjam Administrative Zone, Ethiopia. Methods This ...
Behavioral Sciences
It aligns with the organisational environment hypothesis , which sees work conditions as a bullying trigger. Therefore, according to Salin's bullying framework , workplaces can give rise to enabling, motivating, and precipitating processes for bullying. Organisations with a balanced/positive organisational context are unlikely to provide ...

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

Conclusions

Introduction

Participants

Study outcome

Primary exposure

Statistical analyses

Prevalence of bullying at school and mental health problems

Associations between bullying at school and mental health problems

Strengths and limitations

Availability of data and materials

Code availability

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Consent for publication

Additional information

Supplementary Information

Rights and permissions

About this article

Share this article

Child and Adolescent Psychiatry and Mental Health

Save citation to file

Add to My Bibliography

Four decades of research on school bullying: An introduction

Similar articles

Publication types

Related information

LinkOut - more resources

Miscellaneous

Psychological processes in young bullies versus bully‐victims

Astrid M. G. Poorthuis

Associated Data

1. INTRODUCTION

1.1. Distinct psychological processes in young bullies versus bully‐victims

1.2. Empirical evidence for distinct psychological processes in bullies versus bully‐victims

1.3. Psychological processes in bullies versus bully‐victims: Distinct or shared?

1.4. The present study

2. METHODS 1

2.2. Procedure

2.3. Measures

2.3.2. Theory of mind errors

2.3.3. Hostile intent attributions

2.3.4. Happy victimizer emotions

2.3.5. Reactive and proactive motives

2.4. Data analysis strategy

3.1. Preliminary analyses

3.1.2. Bully groups

3.1.3. Sex and age differences

3.2. Primary analyses

4. DISCUSSION

Supporting information

ORIGINAL RESEARCH article

Introduction

Participants

Questionnaires

Depression, Anxiety, and Stress Scale (DASS)

Positive Mental Health Scale (PMH)

Resilience Scale

Brief Perceived Social Support Questionnaire (F-SozU K-6)

General Self-Efficacy Scale (GSE)

Data Analysis

Bullying Frequency in Both Countries

Correlation Table

Mediated Path Analytic Model Within the German Sample

Mediated Path Analytic Model in the Chinese Sample

Data Availability Statement

Ethics Statement

Author Contributions

Conflict of Interest

Acknowledgments

Supplementary Material

The Many Faces of Bullying

Bullying in schools: prevalence, bystanders’ reaction and associations with sex and relationships

Research question

Does the relationship between the bystander and the victim or the bystander and the bully make a difference in the bystander’s reaction?

Study design

Participants and sampling techniques