hypothesis 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

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

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

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

Conclusions

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

Introduction

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

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

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

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

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

Participants

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

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

Study outcome

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

Primary exposure

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

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

Statistical analyses

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

Prevalence of bullying at school and mental health problems

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

Associations between bullying at school and mental health problems

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

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

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

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

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

Strengths and limitations

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

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

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Acknowledgements

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

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Håkan Källmén

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

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Additional file 1..

Principal factor analysis description.

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

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3 Theories That Help to Understand Bullying

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

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Bullying Increases Risk of Developing Mental Health Problems and Vice Versa

A new study by researchers at Columbia University Mailman School of Public Health suggests there is a two-way relationship between bullying perpetration and mental health problems among American youth. Bullying perpetration increased the risk of developing internalizing problems—such as depression, withdrawal, anxiety, and loneliness—and having internalizing problems increased the probability of bullying others. While previous research has focused on the causes and consequences of bullying victimization, this is the first study to comprehensively explore the time sequence between bullying perpetration and mental health problems. The results are published online in the Journal of Adolescent Health .

Bullying is defined as any unwanted aggressive behavior by youth or group of youths who are not siblings or dating partners that is repeated multiple times or highly likely to be repeated. In the U.S., it has been estimated that between 18-31 percent of youths are involved in bullying.

“While it is well documented that bullying victimization is associated with immediate and lifelong mental health problems, no studies to date have examined the hypothesis that the relationship between bullying perpetration and mental health problems may be bidirectional,” said Marine Azevedo Da Silva, PhD, a postdoctoral researcher at the Columbia Mailman School.

The researchers analyzed data from 13,200 youths aged 12 to 17 years in the nationally representative Population Assessment of Tobacco and Health survey to study the bidirectional association between bullying perpetration and internalizing problems. Among them, 79 percent reported that they never bullied others, 11 percent reported having bullied others over a year ago, and 10 percent reported having bullied others in the past year. When bullying perpetration was considered as a past month measure, 16 percent reported having bullied others over a month ago, and 5 percent reported having bullied others in the past month.

When the researchers examined the relationship between bullying perpetration as a predictor of internalizing problems, they found that youths who reported being the perpetrators of bullying were more likely to develop a moderate to high incidence of mental health problems compared to those who reported not perpetrating bullying. They also found that adolescents who experienced moderate to high internalizing problems had increased risk of bullying others compared to those who reported no or low incidence of having mental health problems.

“The study we designed allowed us to show that the association is likely to be bidirectional between bullying perpetration and internalizing problem. However, it is important to point out that the methods of assessment—including definitions, question-wording, and self-report—could overestimate or underestimate the prevalence of bullying and in turn, influence the strength of association between bullying perpetration and internalizing problems,” observed Azevedo Da Silva.

“Our findings provide an important extension to previous literature, and indicate that bullying behaviors prevention and intervention strategies among youth should consider how to take into account and handle negative feelings and mental health problems,” said Silvia Martins , MD, PhD, director of the Substance Abuse Epidemiology Unit of the Department of Epidemiology and senior author.

Co-authors are Jasmin Gonzalez, University of California, Berkeley; and Gregory Person, Xavier University of Louisiana.

The study was supported by NIDA-Inserm Drug Abuse Research Fellowship from the National Institute on Drug Abuse and the French National Institute of Health and Medical Research.

The Social Cognitions of Victims of Bullying: A Systematic Review

• Systematic Review
• Open access
• Published: 22 February 2022
• Volume 7 , pages 287–334, ( 2022 )

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• Sanne Kellij   ORCID: orcid.org/0000-0001-5952-4499 1 , 2 , 4 ,
• Gerine M. A. Lodder 3 ,
• Neeltje van den Bedem 2 ,
• Berna Güroğlu 2 , 4   na1 &
• René Veenstra 1   na1  

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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 hypothesis predicts that victims become increasingly insensitive to social cues because of a numbing effect. This systematic review examines evidence for these three hypotheses on the relation between victimization and social information processing. The focus is on two phases of social information processing: encoding of social information (attending to and registration of social cues) and interpreting social information (making sense of multiple social cues simultaneously). These phases are important prerequisites for behavioral responses. The systematic search led to the inclusion of 142 articles, which were published between 1998 and 2021 and received quality assessment. The studies included on average about 1600 participants (range: 14–25,684), who were on average 11.4 years old (range: 4.1–17.0). The topics covered in the literature included attention to and accurate registration of social cues, peer perception, attribution of situations, empathy, and theory of mind. The results were most often in line with the prevention hypothesis and suggested that victimization is related to a negative social-cognitive style, as shown by a more negative perception of peers in general and more negative situational attribution. Victimization seemed unrelated to abilities to empathize or understand others, which contradicted the desensitization hypothesis. However, desensitization may only occur after prolonged and persistent victimization, which to date has been sparsely studied. The reaffiliation hypothesis could not be thoroughly examined, because most studies did not include positive social cues. In bullying prevention, it is important to consider the negative social information processing style related to victimization, because this style may impede the development of positive social interactions.

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Introduction

Seeing is believing, or so is the expression. People can see the same things but interpret them differently. In social situations, this can lead to misunderstandings and may, in the case of bullying, lead to unwanted negative spirals. Social cognition refers to how individuals construct their (subjective) social reality. It involves psychological and cognitive processes of how a person processes, stores, and applies information about the social world (Ostrom, 1984 ). When children are the victim of repeated, intentionally aggressive, or hurtful behavior from a powerful perpetrator, such as in bullying (Olweus, 1993 ), it is likely to affect how they experience their social world and may affect their general social cognitive tendencies. This may have long lasting consequences, even into adulthood, as victims report more mental health problems, lower levels of academic achievement, and poorer social relationships (Arseneault, 2018 ). A better understanding of the effects of victimization on social cognition of victims is needed, as social cognition likely influences (the perception of) new social interactions, and thus play a role in the victimization process. To date, it is unclear how victimization relates to different aspects of social cognition, as many studies only examine a subcomponent of this highly complex construct. Therefore, this systematic review provides an overview of the literature on the relation between victimization and different aspects of social cognition.

Bullying is a social process (Salmivalli, 2010 ). Both bullies and victims influence social interactions by sending and interpreting social messages. The past experiences and the social-cognitive thinking style of children influence how these social messages are received. According to the social information processing (SIP) model (Crick & Dodge, 1994 ), the social-cognitive processes can be organized in six subsequent steps or phases. The first two phases refer to the selection and interpretation of social cues: encoding (which cues are registered) and interpretation (interpreting the combined meaning of all registered cues). For example, perceiving someone’s facial expression without any interpretation is part of the encoding phase, whereas thinking about why someone is laughing contains a subjective component and is therefore an interpretation. A feedback loop exists between encoding and interpretation, such that interpretation can influence encoding of subsequent social cues. The last four SIP-phases refer to cognitive processes which enable an individual to form a behavioral response: goal selection , construction of possible responses , response choice , and the execution of the chosen response (Crick & Dodge, 1994 ). Finally, each person has a database which includes memories, schemas, and social knowledge that influence each SIP-phase (Crick & Dodge, 1994 ). For example, if people get to know each other (knowledge and memories), the interpretation of the other’s intentions will improve. While the database concurrently influences the SIP-phases, it is also simultaneously updated with new experiences. The updated database, in turn, influences future encoding, interpretation, and behavioral responses, possibly leading to the development of negative spirals. Victims are likely to have difficulties in sending and interpreting social information, as they seem to have poorer social cognition and social skills (Fox & Boulton, 2005 ).

No matter whether it is a precursor or consequence of victimization, having difficulties in social cognition (or social intelligence, see Kaukiainen et al., 2002 ) may relate to being victimized. Based on the SIP-model, prior victimization experiences likely affect how victims encode, interpret, and respond to social cues as their past experiences color the interpretation of new social situations. First, victims may have a positive social-cognitive style and focus on positive social cues and interpretations to facilitate reaffiliation (Bernstein, 2003 ; Pickett & Gardner, 2005 ), called the reaffiliation hypothesis in this review. In line with this hypothesis, socially excluded people tend to focus more on positive social cues (Buckner et al., 2010 ) and have better memory recall for positive events (DeWall et al., 2011 ). Second, instead of focusing on positive social cues, victims may develop a negative social-cognitive style and focus more on negative social cues or threat, and detect such stimuli more rapidly, to prevent subsequent negative interactions (Rapee & Heimberg, 1997 ), the prevention hypothesis . In line with this, previous studies have found that anxious individuals tend to focus on negative information (Bar-Haim et al., 2007 ), lonely individuals expect more rejection by others (Spithoven et al., 2017 ), and victims of all types of events (e.g., natural disasters and crime) are prone to interpret hostile intent (van Reemst et al., 2016 ). Third, victims may become increasingly insensitive to social information, the desensitization hypothesis , as repeated victimization might lead to an insensitivity to all kinds of social information (Bernstein, 2003 ). However, to date, it is unclear what the nature of this relation is.

Current Study

The aim of the present study was to examine the relation between victimization and social cognition (encoding and interpretation) in children and adolescents through a systematic literature review. The results were interpreted in light of hypotheses that were formed on the relation between victimization and social cognition: the reaffiliation (focus on positive social cues to reaffiliate), prevention (focus on negative social cues to avoid future victimization), and desensitization (numbing or insensitivity to social cues) hypotheses .

Search Strategy

The systematic review was carried out in line with the PRISMA guidelines (Moher et al., 2009 ). Search terms were included for victimization and social cognition in three databases (PsycInfo, Web of Science, ERIC), see the identification block in Fig.  1 and Online Source 1. The literature search was executed in July 2018 and updated in February 2021.

Flow diagram of the selection process of the articles. In the first box you read the utilized search term and the hits per database. In the following blocks you can see the other article selection phases (title deselection, abstract reading, diagonal reading & full-text reading)

Study Selection

The presented results are of the combined initial search and update. The search resulted in 7628 hits (PsycInfo: 3477, Web of Science (WoS): 3232, ERIC: 919). 1890 hits were excluded, if they had titles unrelated to the topic (e.g., other victimization types, such as gang violence), were not peer-reviewed publications (to warrant study quality), or were not written in English. After removal of 1334 duplicates, 4404 articles were left (PsycInfo: 2611, WoS: 2521, ERIC: 706). In round two, the abstracts were read and articles were selected only when they referred to victimization of bullying or social cognition. This round resulted in 1227 articles (PsycInfo: 772, WoS: 767, ERIC: 213). In round three, diagonal reading, the articles were scanned for relevant information and selected articles that examined the relation between social cognition and victimization and had a particular focus on either encoding or interpretation. Articles were excluded if they included participants older than 18 years, or if they examined coping, attribution style (internal/external, stable/unstable, controllable/uncontrollable), general social skills, or if they examined the last four phases of the SIP-model (behavioral response). During the first search in 2018, two researchers independently did round three, the diagonal reading. Inter-rater reliability for selection in this round was 89.9% (79.3% for the first 100 and 91.5% for the remaining articles). In case of disagreement, the researchers discussed the article and respective arguments, to come to an agreement. During the search update in 2021 one researcher read the articles because of the high inter-rater reliability obtained during the first search. Diagonal reading resulted in 198 included articles (PsycInfo: 135, WoS: 151, ERIC: 37).

These 198 articles were read thoroughly by the first author. An additional 56 articles (15 first search, 42 search update) were excluded (e.g., focus on rejection instead of victimization or because of participant age either being younger than 4 or older than 18). This led to an inclusion of 142 articles in the review (PsycInfo: 101, WoS: 110, ERIC: 25), published between 1998 and 2021. Studies included on average about 1600 participants ( Median  = 390, range: 14–25,684), who were on average 11.4 years old (range: 4.1–17.0). Figure  1 provides the selection flow diagram. Online Source 1 contains details on the selection process.

Quality Assessment

The commonly used Newcastle–Ottawa Scale for study quality assessment (Wells et al., 2000 ) was adjusted for the purposes of this systematic review. Studies were evaluated on sample, measures, and method in relation to our aim: examining the relation between social cognition and victimization of bullying. Sample referred to the representativeness of the sample, the appropriateness of the sample size, the non-response, and the participant characteristics. Measures referred to the measurement of victimization as well as social cognition, and the use of control variables. Method referred to the type of study (longitudinal/cross-sectional), pre-registration, the use of descriptives, and the use of statistics. The first author assessed the quality, which was replicated by the third author for 10% of the studies. The interrater reliability for this subset was satisfactory ( r  = 0.84, p  < 0.001; ICC = 0.89, p  < 0.001).The included studies received between 4 and 13 points out of the possible 16 ( M  = 8.50, SD  = 1.82), with a notable exception of one receiving 1 point (see Online Source 2a Table S3 for the quality assessment per study and Online Source 2b for details). Studies most often lost points on not including effect sizes and response rates, using non-validated measures, not having a longitudinal design, and not pre-registering the study. Generally, the overall quality of the studies seems unsatisfactory, which demonstrates possible improvements for research designs.

The results are organized based on the two aspects of social cognition: encoding and interpretation (first two SIP-phases) in relation to victimization of bullying. Within each SIP-phase, results are categorized in subdomains, based on topics addressed in the articles. Results were interpreted in light of the reaffiliation, prevention, and desensitization hypotheses.

Victimization and the Encoding of Social Information

The articles on encoding, the first SIP-phase, examined which cues were attended to (selection) and whether cues were registered as what they objectively were (accurate registration).

Selection of Social Cues

Selection of social cues, or attention, refers to how perceptual, motor, and cognitive systems are allocated to potentially competing information-processing demands. It involves both conscious and unconscious selection to different social cues (Anderson, 2015 ).

Only four studies examined victimization in relation to attention (see Table 1 ); therefore, conclusions are preliminary. Based on the reaffiliation hypothesis, it was expected that victims would attend predominantly to positive social cues, in order to identify possibilities to restore social relationships. However, most studies focused exclusively on negative social information. One study examined differences in the attention to emotions between victims and non-victims, but neither specified valence of emotions nor found support for victims differing in attention to others’ emotions compared with peers (Hussein, 2013 ). Therefore, no conclusions could be drawn for the reaffiliation hypothesis .

Based on the prevention hypothesis, it was expected that victims would attend predominantly to negative social cues, to prevent further negative interactions. There was support for this hypothesis, as frequent victimization was associated with a higher likelihood to notice bullying events in real life (Jenkins & Nickerson, 2017 ). Another study examined visual attention to bullying scenarios, and showed that all children spent most time looking at bullies and second most time looking at victims (Troop-Gordon et al., 2019 ). Thus, children focused attention mostly on the immediate threat, the bully, and not, for example, on bystanders who could possibly help. For victims, the attended social cues might affect behavior, as heightened attention for bullies by victimized children related to more aggressive behavior (Troop-Gordon et al., 2019 ). These findings provided indirect support for the role of threat prevention in attention to social cues in general.

A focus on threat not only became apparent in studies employing tasks with visual social cues, but also in a study examining interference of word valence on the ability to name the color of the word (emotional Stroop effect: Williams et al., 1996 ). Victimization experiences related to faster responses to victimization related words (Rosen et al., 2007 ). Faster responses to victimization related words indicate faster attendance to these social cues, which could imply that victims focus on threatening social cues. Alternatively, these results can also be interpreted in line with the desensitization hypothesis , from which it was expected that victims would attend less to social cues in general. Frequently victimized children may be more insensitive toward negative valence words, so that the valence of these words interferes less, resulting in faster reaction times. As such, whether this study provides more support for the prevention or the desensitization hypothesis remains unclear.

Taken together, the studies on attention and victimization suggest that victims may have a heightened focus on negative or threatening social cues, as two studies gave indirect support and one study out of four clearly indicated that victims might notice social threatening events more often. Across time, this focus on negative social cues may result in numbness for negative social information, but the conclusion regarding the desensitization hypothesis is tentative, as no study investigated prolonged (persistent) victimization. So far, studies have not examined heightened attention to positive information, which means that there is not enough evidence to assess the reaffiliation hypothesis properly. Although the (scarce) evidence so far seems most in line with the prevention hypothesis , it is possible that victims use different social-cognitive styles depending on the situation and that the situations invoking reaffiliation have been omitted. For instance, situations with unknown peers might invoke reaffiliation strategies, whereas situations with familiar peers might invoke prevention or desensitization strategies.

Accurate Registration

Accurate registration of social cues is crucial for effective social interactions. Inaccurate registration of important information can lead to less adequate responses, which can come across as odd, rendering one vulnerable for victimization. Below, the general accurate registration of social cues (6 studies) and emotion recognition (12 studies) are discussed separately.

Table 2 displays the research on accurate registration of social cues and emotion recognition. Some evidence for general accurate registration points toward the desensitization hypothesis (1 of 6 studies) , which predicts that victims would focus less on social events in general, and therefore have lower accuracy in perceiving social cues, regardless of their valence. One of the five studies indicated that victimization related to a less accurate registration of social cues in general. Children who, according to their teachers, had more victimization experiences were less accurate in telling what they saw in a picture of a social situation (Ogelman & Seven, 2012 ).

Other research was in line with the prevention hypothesis (3 out of 6 studies) , which predicts that victims would focus on negative social cues and therefore would register more cues as negative, leading to a lower registration accuracy of positive social cues. These studies showed that victims register cues with a negative bias. They underestimated the number of balls they received from other players in a digital ball tossing game (Cyberball) and overestimated the times they were excluded from the ball tossing interaction, regardless of being in- or excluded in the game (Lansu et al., 2017 ). Overestimation also occurred in rejection perceptions. Overt victimization, and not relational victimization, related to increased perceptions (overestimation) of peer rejection (Zimmer-Gembeck et al., 2013 ). Moreover, being victimized related to lower overestimation of one’s own likeability (Garandeau & Lansu, 2019 ). These general tendencies pointed to a negative social-cognitive style, in line with the prevention hypothesis .

One study provided some support for the reaffiliation hypothesis , which predicts that victims, in pursuit of reaffiliation, would register ambiguous social cues more positively, leading to lower registration accuracy of negative social cues. In a study where children had to identify children as being part of their own or another team, victims tended to be better at recalling their own rather than opposite team members, when they had seen pictures of the others only once before (Telzer et al., 2020 ). By remembering team member’s identities better, they may optimize social opportunities, as they have something (although minimal) in common. In a last study peer-reported victims were compared with bullies, followers, defenders, outsiders, and non-involved children. This study provided no support for any of the hypotheses, as victims did not differ from others in their ability to recall and retell vignettes of social provocation and ambiguous scenarios (Camodeca & Goossens, 2005 ). The differences between these studies might be because of the assessment of registration accuracy, as the type of task (e.g., recalling or describing) and the level of language skills needed to complete it, differed between the studies, possibly leading to diverse results.

In sum, results on accurate registration are limited and mixed, and much remains unknown, but there are first indications that victims differ in registration accuracy of social cues.

Emotion recognition is the ability to label facial expressions of others correctly. Twelve studies on accurate registration were found, of which two studies examined recognition of specific emotions, eight studies overall emotion recognition, and two studies both overall and specific emotion recognition. Most evidence indicated no significant relation between victimization and overall emotion recognition (8 out of 10 studies, of which 1 had mixed results depending on the task used), see Table 2 . There was no evidence for tasks with basic emotion recognition that victimization among young children (4–6 years old) related significantly to overall emotion recognition: neither for matching emotional pictures (Heinze et al., 2015 ; Laurent et al., 2018 ) nor when choosing a facial picture of how a person in a story feels (Belacchi & Farina, 2010 ; Garner & Lemerise, 2007 ; Heinze et al., 2015 ; Laurent et al., 2018 ). These results contradict the desensitization hypothesis , which predicts that victims are worse overall in emotion recognition, because of desensitization to others’ emotions. However, the results are also not in line with the prevention and reaffiliation hypothesis , which similarly predict worse overall emotion recognition: victims focusing more on negative social cues could be more open to register more expressions as negative ( prevention ) and vice versa, victims focusing more on positive social cues could be more open to register more expressions as positive ( reaffiliation ). However, the non-significant results might be due to the use of tasks that were too simple and thus unable to catch subtle differences between children or show ceiling effects. Indeed, the use of more complex measures provided different outcomes (study quality did not clearly differ between the simple and more complex tasks studies). Results on a more intricate task (labeling emotions of puppets giving visual and audio cues), indicated a positive relation between victimization and accurate labeling of emotions (Heinze et al., 2015 ). Additionally, physical victimization (but not relational) related to better overall emotion recognition (Garner & Lemerise, 2007 ). However, victimization was related to making more mistakes in labeling ten different emotions in pictures (Miller et al., 2005 ). Thus, the findings were mixed and also often based on relatively small sample sizes.

Among the studies on older children (10–15 years old), there were a few with larger sample sizes. The study with the largest sample size ( N  = 6233) provided evidence that victimization related negatively to self-reports of emotion recognition abilities (Hsieh et al., 2019 ), whereas the second study ( N  = 757) using a task (reading the mind in the eyes) did not (Guy et al., 2017 ). Both studies had higher quality levels in the quality assessment (9 and 11 points respectively). Furthermore, most other studies did not provide evidence that victimization related to overall emotion recognition (Baird et al., 2010 ; Baroncelli & Ciucci, 2014 ; Ciucci et al., 2014 ), except for cyber-victimization which related to lower general emotion recognition abilities (Ciucci et al., 2014 ). Overall, the relation between victimization and overall emotion recognition seems not significant.

Although overall differences in emotion recognition do not seem apparent, victims may have worse abilities in emotion recognition of specific emotions. For example, emotions like fear or sadness may be recognized as anger to prevent (possible) assault ( prevention hypothesis ), or contrarily, emotions such as contempt may be recognized as positive and social opportunities ( reaffiliation hypothesis ). Four articles examined separate emotions. One study focused on younger children (4–6 years old) and found that physical and not relational victimization, related to worse recognition of angry expressions (Garner & Lemerise, 2007 ). Another study on victimization type found that cyber-victimization related to making more mistakes on recognizing anger and fear (Ciucci et al., 2014 ), yet found no evidence for a relation with traditional victimization. A small study ( N  = 43 girls), found that female victims were less accurate in labeling negative emotions, especially if they were sensitive to rejection, but no significant effects were found for labeling positive emotions (Rudolph et al., 2021 ). There might be gender differences, as a last study found that boys’ victimization related to making more errors on recognizing fear and sadness, whereas for girls, victimization related to errors on recognizing sadness, disgust, and surprise and to less mistakes on recognizing happiness (Pozzoli et al., 2017 ). These studies indicate that victims might have trouble recognizing negative rather than positive emotions.

In sum, findings on registration accuracy suggest that across different types of social cues there are indications that negative social cues might be registered less accurately, which would be in line with the prevention hypothesis . If true, such misrepresentations of negative social cues would set victims at a disadvantage for appropriate responding, possibly leading to misunderstanding by others and yielding them even more vulnerable for rejection or victimization. However, the conclusions are tentative because of the small number of studies examining registration of social cues and lack of longitudinal studies investigating these links.

Interpretation of Social Information

After the selection and registration of social cues, the next step in the SIP model is the interpretation of social cues. Interpretation comprises assigning meaning to the (combination of) registered cues. For example, when you attend to and accurately register a face as happy, interpretation involves attributing a reason to why this person is smiling given the other social cues in that situation. The topics related to interpretation in the selected articles involve attribution of situations, peer perception, and the ability to understand others, which includes empathy and theory of mind (ToM).

Attribution of Situations

Attribution of situations was a popular topic in research on social cognition of victims (49 studies). Examples were interpretation of others’ intentions and expectations of what would happen. Most evidence favored the prevention hypothesis, which predicts that victims have more negative interpretations of social cues because of their focus on threatening information (33 studies, of which two found it only for a specific victimization type and one only for a certain nationality), see Table 3 . With respect to attributions about bullying, victimization related to thinking that bullying is a serious problem at one’s school (Choi & Park, 2018 ), interpreting ambiguous scenarios more often as bullying (Calleja & Rapee, 2020 ) and thinking they were being bullied more often because of their personality instead of their behavior (Morrow et al., 2019 ), but not to a more negative attitude toward the concept of bullying (Caravita et al., 2019 ; Pouwels et al., 2017 ).

Other research, on non-bullying situations, found that victimization related to expecting threat (Balan et al., 2018 ; González-Díez et al., 2017 ; Hunter et al., 2010 ; Röder & Müller, 2020 ), being rejection sensitive (Ding et al., 2020 ; Rowe et al., 2015 ; Zimmer-Gembeck, 2015 ; Zimmer-Gembeck & Duffy, 2014 ; Zimmer-Gembeck et al., 2013 , 2014 ), worrying about negative evaluations (Estévez et al., 2019 ; Giannotta et al., 2012 ; Gómez-Ortiz et al., 2018 ; Taylor et al., 2013 ; Zimmer-Gembeck & Duffy, 2014 ), feeling rejected when receiving few likes in a social media task (Lee et al., 2020 ), and being more sensitive to aversive stimuli (Rudolph et al., 2016 ). Moreover, a longitudinal study found that adolescents with victimization experiences adopted rejection schemas more often. These maladaptive schemas, in turn, predicted later victimization (Calvete et al., 2018 ). Not only perceived threats of rejection, but also of hostility have been examined. Victimization experiences related to hostile intent attributions in ambiguous situations (Camodeca & Goossens, 2005 ; Camodeca et al., 2003 ; Guy et al., 2017 ; Hoglund & Leadbeater, 2007 ; Hung et al., 2017 ; Kokkinos & Voulgaridou, 2018 ; Ogelman & Seven, 2012 ; Perren et al., 2013 ; Pornari & Wood, 2010 ; Schwartz et al., 1998 ; Yeung & Leadbeater, 2007 ), as well as in provocative situations (Ziv et al., 2013 ). In other words, children with more victimization experiences seemed to interpret situations more often as threatening, consistent with the prevention hypothesis . In more positive situations, victims did not interpret more hostile intent (Smorti & Ciucci, 2000 ). Thus, the situation (positive, ambiguous, or negative) might influence the adopted social-cognitive style.

Findings from three other studies painted a more complex picture. The specific bully-role might be important, as one study indicated that only bully-victims, but not pure victims, interpreted video fragments of ambiguous social interactions (abstract figures, animals, and humans) more often as bullying compared to non-involved children. Additionally, bully-victims interpreted even positive interactions of apes in a zoo more often as bullying compared to non-involved children (Pouwels 2016 ). A second study found that only relational victimization, and not physical victimization, related to interpreting situations as more negative and social threatening (Calleja & Rapee, 2020 ).

However, there were several contradictory findings (14 studies). First, some studies did not find significant associations between victimization and hostile interpretation tendencies (Leff et al., 2014 ; Mathieson et al., 2011 ; Prinstein et al., 2005 ; Smalley & Banerjee, 2014 ; Smorti & Ciucci, 2000 ; van Dijk et al., 2017 ; Warden & Mackinnon, 2003 ) or being more upset after hypothetical, ambiguous provocations (McQuade et al., 2019 ), or only found evidence of this association for Japanese but not for American children (Kawabata et al., 2013 ). Other studies found no association between victimization and fearing negative evaluation (Kiekens et al., 2020 ; Pabian, 2019 ) or expecting and interpreting rejection (Rudolph et al., 2021 ; Stubbs-Richardson & May, 2020 ). In addition, one study found no evidence that victims interpret situations more often as emergencies when they were also asked whether they would intervene that particular situation (Jenkins & Nickerson, 2017 ). Notably, the average study quality of these studies ( M  = 7.21 points, SD  = 1.42) is lower than the study quality of all studies on situation attribution ( M  = 8.69, SD  = 2.02), slightly suggesting that the results that were more common and in line with the prevention hypothesis might be more valid.

With regards to the reaffiliation hypothesis , in the seven studies that examined positive attributions separately from negative attributions, no evidence was found that victims interpret situations more positively or attribute less hostile intent (Garner & Lemerise, 2007 ; Hung et al., 2017 ; Smorti & Ciucci, 2000 ; Warden & Mackinnon, 2003 ), nor that victims perceive more social opportunities amid school transitions (Röder & Müller, 2020 ), nor judge bullying conceptually right (Caravita et al., 2019 ). Victims might even interpret intentions less positive compared with non-involved children (Camodeca et al., 2003 ; Ziv et al., 2013 ).

In sum, strongest evidence was found in line with the prevention hypothesis (33 out of 49 studies): victims interpreted situations and intentions of others more negatively, hostile, or dangerous, and were more sensitive to rejection. Moreover, this negative attribution style seems to include both more negative and less positive interpretations.

Peer Perception

There were many studies that examined how victims generally perceived their peers, see Table 4 (35 studies). In line with the prevention hypothesis , most research (26 studies, of which three with partial support) indicated that victimization related to negative peer perception (Hong et al., 2019 , 2021 ; Ladd & Troop-Gordon, 2003 ; Purcell et al., 2021 ; Rudolph et al., 2009 ; Sainio et al., 2013 ; Salmivalli & Isaacs, 2005 ; Schacter & Juvonen, 2018 ; Troop-Gordon & Ladd, 2005 ), less trust in peers (Betts et al., 2017 ), negative expectations of peer interactions (Audley et al., 2020 ), and negative perceptions of the social climate and interpersonal relationships (Barzeva et al., 2020 ; Berg & Aber, 2015 ; Elsaesser et al., 2013 ; Gini, 2008 ; Harks & Hannover, 2020 ; Holfeld & Baitz, 2020 ; Lázaro-Visa et al., 2019 ; Leadbeater et al., 2015 ; Mertens et al., 2021 ; Moyano et al., 2019 ). Some longitudinal studies also provided evidence in this direction: Increased victimization led to increases in negative peer perception (Elsaesser et al., 2013 ; Troop-Gordon & Ladd, 2005 ), and negative peer perception predicted subsequent victimization for girls (Sainio et al., 2013 ). However, cyber-victimization did not explain negative peer perception over and above traditional victimization (DePaolis & Williford, 2019 ). In addition, a second study also did not find a concurrent relation between victimization and peer connectedness perceptions (Aldridge et al., 2020 ).

Several studies indicated that it is important to examine to which peers the perception refers. Victims attributed less favorable characteristics to non-friends than they did to friends (van Noorden et al., 2014 ), even more strongly than non-involved peers (van Noorden et al., 2016 ). This might be partially based on sympathy, as victims judged non-involved peers more positively than they judged bullies and bully-victims (van Noorden et al., 2016 ), again in line with the prevention hypothesis. Though victims themselves might think less of bullies, they do not necessarily think that others have similar thoughts. Being victimized was not related to thinking that hypothetical victims and classmates would dislike a hypothetical bully (Garandeau & Lansu, 2019 ). However, victims themselves judged known bullies and followers more positively than unknown bullies and followers ( reaffiliation hypothesis ), whereas known defenders are judged less positively than unknown defenders ( prevention hypothesis ) (Pouwels et al., 2017 ). Possibly, judgements occur in reference to standards that are hold for specific peers.

Additionally, two studies indicated that the general peer perception of victims might be rigid. They found that victimization related positively to holding an entity rather than an incremental perspective on peer relationships (Rudolph, 2010 ) and on peers’ personalities (Kaufman et al., 2020 ). In other words, victims seem to think that peers and relationships are set and cannot change. As victims also hold more negative perceptions of peers, it is likely that such rigid perceptions might influence how they engage in future interactions with peers.

Three studies compared victimization types. Cyber-victims were less positive about peers than non-involved peers, but cyber-bully-victims were not (Guo et al., 2021 ). This finding was corroborated by Ding et al. ( 2020 )), who found no differences on perceived social climate for non-involved, traditional bully-victims and cyber-bully-victims. A last study found that bully-victims, but not pure victims, perceived their school social climate less positive than non-involved children, whereas both victims and bully-victims perceived their peers less positive compared with bullies and non-involved peers (Bayar & Uçanok, 2012 ).

Only one study was fully consistent with the reaffiliation hypothesis , and found that victimization related to believing that others keep secrets and keep promises (Rotenberg & Boulton, 2013 ), contrasting the study of Betts and colleagues ( 2017 ). Although trust is usually a strength in social interactions, trust might lead to more opportunities to being bullied, for example when a victim tells others their secrets. These opportunities might be especially utilized if there is a motive, such as being perceived as untrustworthy (which was how others perceived victims, Rotenberg & Boulton, 2013 ). Contrasting the reaffiliation hypothesis , it seems unlikely that victims more readily like peers for superficial reasons, because participants did not like previously unknown teammates better than non-teammates (Telzer et al., 2020 ).

One study seemed in line with the desensitization hypothesis, as persistent victimization did not relate to peer perception (Ladd & Troop-Gordon, 2003 ). A finding that did not fit any of the hypotheses was that victimization, especially for girls, related to thinking one’s friends are susceptible to peer influence (Goldstein et al., 2020 ). Speculatively, this perception might relate to negative peer experiences where friends do not stand up for victimized youth and join in on negative behaviors of others in the peer group.

In conclusion, victims adopt more negative views of both their peers and relationships in general (26 studies in favor, 5 studies with nonsignificant results), though this tendency is less pronounced for friends and defenders. In addition, victims possibly think that peers cannot change (2 studies).

Understanding others

For successful interpretation, the ability to understand others is crucial. An important aspect is empathy, the ability to experience (affective empathy) and understand (cognitive empathy) feelings of others (Decety et al., 2012 ; Mehrabian & Epstein, 1972 ). Related to cognitive empathy is theory of mind (ToM). ToM involves the technical ability to ascribe mental states to others, such as feelings, intentions and thoughts, and specifically the understanding that people can have different information available and thus differ in mental states (Astington, 2001 ). Although victims might be trying hard to understand others (to anticipate social opportunities or threats), based on the reaffiliation and the prevention hypothesis , they actually might have less abilities to experience and understand emotions and (mental) states of others. Furthermore, based on the desensitization hypothesis , persistent victimization might lead to an even lower ability to experience and understand emotions and (mental) states of others, because of desensitization. Even more, it was expected that these victims would have a deficit in the ability to understand the mental states of others, as similar to rejected peers, they might have had fewer social opportunities to develop these abilities (Banerjee et al., 2011 ).

In contrast with all three hypotheses, reaffiliation, prevention and desensitization , Table 5 reveals that most studies (29 out of 44, of which 8 studies found some significant results for either affective, cognitive or general empathy) provide no evidence for an association between victimization and empathy (e.g., Berg & Aber, 2015 , see Online Source 3 for the 29 references). Moreover, a longitudinal study found no effect of within-person changes in empathy over time on victimization (Espelage et al., 2018 b ). Another study examined empathy (cognitive, affective, and somatic) separately for negative and positive feelings of others, and found mixed results (Chen et al., 2021 ). It must be noted, however, that these significant results (7 of 11 correlations), were only very small in size ( r ’s all < 0.07).

Nonetheless, some studies reported consistent associations between victimization and empathy. In studies examining specific bully-roles, traditional victims and not cyber-victims might have slightly higher levels of affective empathy, whereas only cyber-victims might have slightly higher levels of cognitive empathy when compared to outsiders or non-involved peers (Arató et al., 2020 ; Martínez et al., 2020 ). A third study, however, found that victims, compared to non-involved peers, had lower self-reported empathy (Mendoza-González et al., 2020 ). Some studies (9 out of 44), not comparing bullying roles, found that victimization related to less affective empathy (Chan & Wong, 2015 ), less cognitive empathy (Nasaescu et al., 2018 ; Williford et al., 2016 ) and less general empathy (Farrell et al., 2018 ; Jenkins et al., 2016 , 2017 ; Malti et al., 2010 ; Pistella et al., 2020 ; Yudes et al., 2020 ). Nevertheless, other research reported a positive association of victimization (13 out of 44, of which 5 also reported some ns associations with (subtypes of) empathy), with affective empathy (Hood & Duffy, 2018 ; Kokkinos & Kipritsi, 2012 ; Nasaescu et al., 2018 ; Rodríguez-Hidalgo et al., 2018 , 2019 ; van Noorden et al., 2016 ), cognitive empathy (Arató et al., 2020 ; Lázaro-Visa et al., 2019 ; Rodríguez-Hidalgo et al., 2018 ; van der Ploeg et al., 2017 ), and general empathy (Donat et al., 2020 ; Yang et al., 2020 ). Furthermore, one study found a between-person effect for general empathy and victimization (Espelage et al., 2018 b ). It is possible that the contradicting findings happened because of capitalization of chance. Studies with significant associations mostly utilized small samples or found small to very small effect sizes. The quality of studies with non-significant and significant findings was quite similar ( M ns  = 8.11, SD  = 1.89 versus M sig  = 8.91, SD  = 1.54), providing support for the expectation that these results were a capitalization of chance. Furthermore, the studies with positive associations also did not differ from the studies finding negative associations, with respect to quality assessment ( M pos  = 8.85, SD  = 1.46; M neg  = 8.90, SD  = 1.66). The studies with more power provided no or little evidence that victimization related to empathic abilities. However, there is a difference between empathic abilities and motivation to use empathic abilities. Only one study investigated motivation-related aspects and found that, although victims did not differ from non-victims in empathic abilities, they showed less cognitive and affective empathy for bullies and bully-victims than for non-involved peers (van Noorden et al., 2017 ). In other words, victims might be able to empathize with others, but not willing to do so with everyone.

Theory of Mind

Table 6 shows that the few studies (9) examining victimization in relation to ToM skills (i.e., the ability to ascribe mental states to others) showed diverse results. Some studies found no evidence for an association between victimization and ToM skills (4 out of 9), either first or second order false belief (Caravita et al., 2010 ; Espelage et al., 2018 ; Monks et al., 2005 ; Renouf et al., 2010 ), which is in line with the findings on empathy. Two studies found mixed results, showing evidence that victims score worse than bullies and non-involved children on cognitive, but not emotional ToM aspects (Gasser & Keller, 2009 ; Gini, 2006 ). Furthermore, three other studies indicated that victimization related to ToM skills negatively (Hsieh et al., 2019 ; van Dijk et al., 2017 ), with some evidence that a relative ToM deficit leads to future victimization (Shakoor et al., 2012 ). Overall, the association between ToM skills and victimization seems either absent or (negative and) small in magnitude.

Social cognition, and hence how victims experience their social world, is likely affected by bullying, but the nature of this relation was unclear. Victims may become more sensitive to threat attempting to prevent or counteract new bullying situations ( prevention hypothesis ). However, children may also become more sensitive to positive cues while they try to restore their social situation ( reaffiliation hypothesis ). Finally, persistent victimization may cause a numbing effect on social cue processing to prevent the negative experience of victimization ( desensitization hypothesis ). The results of this systematic review on the literature on social cognition of victims across childhood and adolescence, mostly align with the prevention hypothesis . The review suggests that victims might have heightened attention to negative or threatening social cues, a less accurate registration of cues, and worse negative emotion recognition (encoding). Furthermore, victims perceived peers more negatively, attributed more hostile intent, and were more sensitive for rejection (interpretation). However, they did not differ in empathic skills. These results indicate that, regardless of whether the social-cognitive style is a precursor or consequence of victimization (or both), there might be a risk for negative spirals, in which negative interpretations may affect future experiences. According to SIP theory, encoding and interpretation of information and previous experiences have consequences for the displayed behavior (Table 7 ). As victims seem to have a negative social-cognitive style, they likely align their behavior accordingly. Indeed, victims’ social-cognitive style seems related to later aggressive behavior (Troop-Gordon et al., 2019 ; Yeung & Leadbeater, 2007 ). If victims display more negative and perhaps unexpected behavior, it could lead to a downward spiral of victimization, as such behaviors may evoke bullying (Thornberg, 2010 ).

Although most evidence (56.3% of all articles, and 71.4% of articles only on peer perception and attribution of situations) was in favor of the prevention hypothesis , a considerable number of studies found insignificant or mixed results. Specifically, most studies indicated that victims did not differ from non-victims in their ability to recognize emotions in general, understand others’ mental states and empathize with others’ emotions. Some methodological issues in these studies should be considered. First, the utilized tasks might be improved. Emotion recognition tasks adopted by researchers are usually quite simple, for example, using basic emotions such as anger, happiness, sadness, and surprise that can be easily differentiated, or using long presentation and response times. Moreover, the questionnaires on empathy were often self-reported. Therefore, they required considerable self-reflection on one’s own empathic abilities and possibly assessed whether children try to empathize with others instead of the ability to empathize. Last on the used tasks, ToM tasks were often quite simple, measuring first and second order ToM, which skills are usually mastered by most 5-year-olds (Perner & Wimmer, 1985 ), whereas the studies examined 7- to 9-year-olds. If severe problems arise in basic emotion recognition, basic empathy, or basic ToM skills, this may affect social functioning, as, for example, has been found for people with autism spectrum disorders (Trevisan & Birmingham, 2016 ). When no differences are found in basic or easy tasks, it does not guarantee that victims have no trouble with emotion recognition of short-lived or complex emotions, when different cues are shown simultaneously, or when people try to hide their emotions, such as in real life. A second possible methodological issue involves that in real life registration of social cues happens automatically. Having to report and explicitly think about it, might lead to different results in the lab compared with real-life social situations. Simple designs might thus not capture relevant (ecological valid) differences in victims. A last methodological issue relates to assessments of having versus using skills. The literature mostly focusses on having skills to understand others and not on whether these skills are used in social interactions. One study reported that victims did not differ from non-victims in empathic abilities, but reported lower levels of empathy for bullies and bully-victims than for non-involved peers (van Noorden et al., 2017 ). This finding is important as it indicates a difference between motivation and ability. Therefore, the motivational aspect should be considered when examining empathy, ToM, or social skills in further research.

While most evidence favored the prevention hypothesis , there was little evidence in favor of the reaffiliation hypothesis . To some extent this may be a consequence of few studies examining more positive aspects of SIP. Researchers examining the interpretation SIP-phase focus mainly on negative interpretations, leaving the reaffiliation hypothesis understudied. Examining positive SIP aspects can help changing toward a more positive framework, with factors for personal growth to improve victims’ resiliency, instead of focusing on (SIP) tendencies that may be detrimental. Similar to the reaffiliation hypothesis , the desensitization hypothesis is also understudied. Only two studies explicitly examined persistency of victimization. One study found that differences in longevity of victimization over five years did not relate significantly to positive peer beliefs, whereas the most recent victimization level related to less positive peer beliefs (Ladd & Troop-Gordon, 2003 ). The second study found that persistent victims were more sensitive to aversive stimuli than non-victims (Rudolph et al., 2016 ). Given the (limited) results, it cannot be discerned whether victimization recency or persistency is most influential on SIP. Studies on differences between recency and persistency of victimization in relation to SIP can also help unraveling the timing that SIP-styles take to change. Furthermore, it can help unravel whether victims perhaps move through different social-cognitive-styles as victimization persists. Initially, victims may try to reaffiliate , but when victimization does not cease, they may switch to the prevention style and if victimization persists for even longer periods, they may yet switch to the desensitization style.

Theoretical and Practical Implications

The prevention hypothesis was best supported in this review and stated that victims focus more on negative events or interpretations to be able to better prevent future negative experiences. These negative interpretations may be a precursor of initial victimization or play a role in maintaining victimization when one responds defensive or aggressive after such interpretations. Alternatively, these interpretations may be a result of previous victimization and thus be very realistic. It can be beneficial in ambiguous social situations, as this allows victims to avoid the situation and thus prevent social exclusion. Longitudinal studies examining victimization and intent attribution may provide more clarity on the causality of this relation.

Anti-bullying interventions can benefit from these insights, as social-cognitive factors are not commonly addressed in interventions (Ttofi & Farrington, 2011 ). Raising awareness about social-cognitive styles may break the downward spiral of victimization and result in changes in behavioral responses, as making automatic thoughts explicit is a core principle of cognitive behavioral therapy (Leahy & Rego, 2012 ). Moreover, as bullying is a social process and multiple parties are involved (Salmivalli, 2010 ), it could be beneficial to teach children how to use perspective taking skills and to acknowledge differences in perspectives (Imuta et al., 2016 ). This might lead to a better understanding of and more sympathy for one another, and to more prosocial behavior (Allen & Kinsey, 2013 ). For victims this could help to reevaluate their focus of attention, interpretations, and behavioral responses. Such changes in SIP of victims might reduce vulnerabilities or risk factors for future victimization. For non-involved peers, it could lead to better understanding of victims and higher levels of empathy, which likely leads them to respond differently.

Limitations of the Literature and Future Directions

A first limitation of the current review involves the examined victims in the included studies. Most of the time victims of bullying were examined as a homogeneous group. However, the victim group is quite heterogeneous with respect to whether victims also bully others (Lereya et al., 2015 ) and whether the victimization is long- or short-term (Kaufman et al., 2018 ). The conclusions might not hold for all types of victims, as there might be different processes at play for the different types of victims. There is some research investigating the interpretation SIP-phase of bully-victims. Some studies found that bully-victims had more negative interpretations of ambiguous scenarios than victims (Camodeca et al., 2003 ; Pouwels et al., 2016 ), whereas other studies found no evidence for a difference between victims and bully-victims (Bayar & Uçanok, 2012 ; Guy et al., 2017 ), and a last study found that it depended on the situation whether bully-victims had more negative interpretations (Ziv et al., 2013 ). Such studies typically did not address victimization duration, nor individual differences over time. Long-term victimization merits more attention, as it is related to indicators of both biological (Giletta et al., 2018 ) and mental stress (Hong et al., 2018 ). Moreover, long-term victims in schools with low levels of bullying (healthy context) have increased levels of mental health problems compared with long-term victims in schools with high levels of bullying (Huitsing et al., 2019 ). With increasingly more schools employing anti-bullying interventions, there is a strong and urgent need to identify factors that will improve interventions for long-term victims.

A second limitation of this review is that the role of development in social-cognitive abilities is hardly examined. As experience is used throughout all SIP-phases, it is expected that younger children have less experience in processing social information, and with more experience they will develop more advanced social-cognitive abilities. Consequences of victimization on the development of social-cognitive abilities can also be expected based on the desensitization hypothesis. With persistent victimization, social cognition of victims may become less focused on social cues, which may have consequences for the further development of social-cognitive abilities. The development of social-cognitive abilities is backed by research findings such as that three year-olds do not pass ToM tasks on false belief, whereas five to six year-olds do (Wellman & Peterson, 2013 ). In other words, perspective-taking abilities, as well as other social-cognitive abilities, such as language skills, develop with age. However, to date most research on social cognition and victims of bullying is cross-sectional, limiting the conclusions regarding causality or developmental trajectories of social-cognitive styles of (long-term) victims. Possibly, victims with a reaffiliation style can break negative spirals of sustained victimization, whereas victims with a prevention style may not be able to do so, and they might eventually develop a desensitization style over time. Without longitudinal studies such developmental patterns cannot be discerned. Similarly, without longitudinal studies it cannot be determined whether certain aspects of social cognition are precursors, consequences or both precursor and consequence of victimization. Knowledge on whether social-cognitive aspects adopted by victims result in subsequent (long-term) victimization is highly valuable for interventions that aim to increase resilience of victims. Whereas this systematic review provided evidence for a social-cognitive style that is in line with the prevention hypothesis , based on the desensitization hypothesis , long-term victims are expected to have a social-cognitive style marked by insensitivity to social cues.

A third limitation involves the examination of encoding. Studies on encoding often rely on recall and are therefore vulnerable for memory biases (alternations, enhancements, or impairments). Negative social events might be more emotionally impactful for victims than positive ones, and thus, have more leverage in recall (LaBar & Cabeza, 2006 ; Roozendaal & Mcgaugh, 2012 ). First, this might bias these results in favor of the prevention hypothesis . Second, the results might be more indicative of differences in the database and not of encoding.

A last limitation is related to the studies examining interpretation. Peer perception and attribution of situations are often examined in relation to school- or classmates, meaning that these studies examine the school-context and therefore the context in which victims are commonly bullied. Due to the limited number of studies on peer perception and situational attribution over different contexts (e.g., sport clubs, and new places), it is currently unknown whether victims also have a more negative social-cognitive style when they interact with unknown peers, are in other contexts, and whether it has consequences for future interactions (e.g., being able to trust others and invest in new relationships).

The underlying neurobiological processes of social cognition are a relevant aspect not examined in this review. Prior research shows that victims had blunted cortisol responses to stress compared with non-victims (Vaillancourt et al., 2013 ). Because of such altered stress responses, victims might be more sensitive to threats and therefore adopt a prevention style. Along similar lines, neuroimaging studies showed that victimized or chronically rejected children had heightened neural responses to social exclusion, compared with non-victimized (McIver et al., 2018 ) or non-rejected children (Will et al., 2016 ), suggesting stronger neural sensitivity to negative social interactions (see for an overview: Güroǧlu & Veenstra, 2021 ). Moreover, evidence exists that the strength of these neural responses is more strongly related to internalizing symptoms for long-term victims compared with non-victimized adolescents (Rudolph et al., 2016 ). In a recent large-scale study, it was found that bullying involvement related to brain structure. Victims differed in cortical thickness of the fusiform gyrus, a brain region involved in visual processing, from bullies, bully-victims and uninvolved children (Muetzel et al., 2019 ). Finally, it was shown that victimization experiences in childhood may modulate the relation between stress sensitivity and adolescent brain structure (Du Plessis et al., 2019 ), suggesting more complex relations between how early victimization experiences might influence future development. Despite evidence that victims have altered neural responses to social exclusion experiences, how these responses generalize across various processes of social cognition and differ for temporary versus long-term victims is largely unknown. Moreover, studies on neural processes of social cognition might inform on underlying motivational (Apps et al., 2016 ; Telzer, 2016 ) or regulatory processes (Sebastian et al., 2010 ), which might be difficult to assess using self-reports or observations of behavior. An example of possible underlying motivational processes is that victims were more empathetic toward non-involved children and friends compared with bullies and non-friends (van Noorden et al., 2017 ). Although motivation is hard to measure behaviorally, neural measurements might prove fruitful. Furthermore, given existing evidence on the role of neurobiological processes in atypical social cognition (e.g., seen in persons with autism spectrum disorder), a developmental neuroscience perspective is an important avenue for further research (Happé & Frith, 2014 ).

It had been unclear how victimization relates to social cognition, as many researchers only examined subcomponents of this complex construct. This systematic review reveals that victimization during childhood and adolescence relates to a stronger emphasis on negative events and a negative social-cognitive style, mostly in line with the prevention hypothesis . Victims appeared to have a heightened focus on negative or threatening social cues and represent social cues less accurately. Furthermore, they perceived peers more negatively, attributed more hostile intent and were more sensitive to rejection than non-victimized children. However, they did not differ in empathic or ToM skills. Further research is needed on the (neurobiological) development of social-cognitive styles and in particular on persistent victims and whether they, in line with the desensitization hypothesis, become insensitive to social cues because of the long period of victimization. For now, researchers and practitioners (e.g., who develop anti-bullying interventions) should realize that, in line with the prevention hypothesis, victims focus on negative social cues.

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We would like to thank Anssi Bwalya for helping to update the search term and summarizing literature, and Ymke G. Riemersma for her help as second reader for the article selection.

This work was supported by The Netherlands Organization for Scientific Research (NWA Startimpuls 400.17.602 to BG and RV; 016.Veni.195.186 to GL).

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Kellij, S., Lodder, G.M.A., van den Bedem, N. et al. The Social Cognitions of Victims of Bullying: A Systematic Review. Adolescent Res Rev 7 , 287–334 (2022). https://doi.org/10.1007/s40894-022-00183-8

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Adult Bullying Is a Thing, Too

Seven tips for how to deal with being bullied as an adult..

Posted February 19, 2021 | Reviewed by Ekua Hagan

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Curiously, while adult bullying is fairly common (some studies say it’s as common as childhood bullying), it doesn't make its way into our conversations as frequently as childhood and adolescent bullying. Furthermore, there are more online resources when it comes to childhood bullying. While there is research on adult bullying that mostly focuses on bullying in the workplace and higher education , it’s not something that we often talk about. Why isn’t adult bullying more a part of our casual conversations?

While I don’t have the answer as to why there seems to be a shortage of both material and conversation surrounding adult bullying despite its pervasiveness, I’d like to offer a hypothesis: We talk less about bullying in adulthood because it carries a greater stigma with potentially higher consequences than it does in childhood.

Because adult bullying is often sneakier and more masked, the person being bullied carries shame and self-doubt—wondering if it’s all "in their head" and they are misinterpreting what is happening. Furthermore, the person getting bullied may likely be worried about real-life outcomes that can have long-ranging and devastating effects — loss of their job, relationships, or reputation. Because of this, adult bullying feels taboo and carries more weight.

Therefore, it’s easy to see why being bullied as an adult can be a lonely experience.

Only, it’s not. In one article found with quantitative data about the rates of adult bullying, a poll derived from The Harris Poll done on behalf of the American Osteopathic Association surveyed 2000 United States adults and found that 31 percent of them reported being bullied as an adult, rates that are surprisingly on par with the levels reported in adolescence . Bullying as an adult was related to significant mental and physical consequences, just as it is when it happens in childhood and adolescence. These numbers were corroborated in other studies done from the early 2000s, where the authors found 30 percent of Americans will be bullied over the course of their careers.

To be honest, this is a topic that feels personal to me, as I have had two experiences of being bullied as an adult, including one fairly recent incident. It’s interesting for me to reflect on the self-doubt that came up for me as I considered writing about my experiences on a public forum. And if there’s something that I’ve learned over the years, it’s that many (if not all?) of our experiences are shared with other humans. If I feel something, then there is a strong likelihood that many others do, too. We are just not that unique. There is something comforting in this awareness of our implicit kinship. It reminds me of the old advice we got back in grade school about speaking up and asking questions: If you have the question, you can assume so do others. Generalizing this to our experiences : If I have this experience, I can assume so do many others. We are more similar than different, and our brain processes mirror one another’s in several important ways.

Both times that I was bullied as an adult, it was by someone older than myself who held greater perceived power. The first time was years ago when I was a graduate student, and the second time was in a cyberbullying incident.

In my recent online bullying encounter, I had the gumption I lacked in my first bullying experience. This time I dealt with it in a proactive and empowered way. I took a stand. I spoke up. I set boundaries and reached out to my social support. I noticed shame as it arose and worked through it. I got information. I regrouped and figured out a new path for myself that limited interaction with the person doing the bullying. In contrast, I responded quite differently years ago when I was bullied in graduate school, where I suffered a hellish year of social isolation , abuse of power, and misconduct perpetrated by someone who held more power than I. It’s nice to notice our growth when we are put back in a similar position for a second time.

Propelled by my own experiences, I feel compelled to spread awareness around adult bullying. It happens, and not infrequently. It’s more insidious and passive-aggressive than childhood bullying, because adults are, well…more sophisticated in how they attack their prey. Bullying behavior is pervasive. It’s perpetuated by smart executives and people in high-ranking positions. It’s executed by people claiming to want to help you and build you up. There is often a power dynamic — but there doesn’t need to be. And the recipient of the bullying often feels very much alone, carrying big shame on top of all the other costs of getting bullied.

Shortly after the above-mentioned cyberbullying incident, I created an adult bullying-themed week on Instagram where I discussed different facets of adult bullying. It was both heartbreaking and illuminating how many people said that they were bullied as an adult. Many women wrote to me that they were bullied by other women. In an era of “women supporting women,” this reality can carry an extra sting and be more painful. It may leave the victim wondering, “there must be something wrong with me to be the target of another woman. Why does she seem to be supporting other women but not me? What’s wrong with me?” and often because the individual doing the bullying is supportive in other ways, or claims to support the voices of women, there is additional doubt and fear of not being believed.

If you find yourself in the position of being bullied as an adult, here are some ideas that might be useful to help you ride, and ultimately thrive and grow from, this very difficult experience. The following are some strategies you might want to try to help yourself if you are being bullied:

1. Take a stand . People who bully find their strength and power in fear. If you show fear or let your shame dictate your next moves and cower, this gives more fodder for the bully’s fire. By speaking up either directly, using calm and assertive techniques, or to a superior who can help (if you feel like you would benefit from more support), you are letting the bully know that they chose the wrong target.

2. Document everything . Save emails, screenshot messages on social media , and write down incidents that occur. This will help you if the bullying persists and you need more support down the line.

3. Use your social support. Don’t stay quiet and carry this burden in silence. If you don’t talk about it, you may be reinforcing your belief that there is something wrong or shameful about you. Talking about it not only enables you to receive emotional support, but it can help you gain perspective, and step out of the shame spiral. Take a deep breath and reach out to people whom you trust and can rely on. These people can offer you reassurance and advice, and remind you that this bullying incident is just one small facet of your life.

4. Validate your experience. Because adult bullying is sneakier and often encourages you to "get in your head," you may find yourself diminishing or not fully acknowledging the extreme hurt of the situation. Try asking yourself this question— if a friend came to you with this exact problem, how would you respond? Turn that empathy inward. Validate the awfulness of what it feels like to be bullied. You’re not making it up, your feelings are justified and reflect that you are going through something real and hard.

5. Set clear boundaries. Physical boundaries are those concrete boundaries where you decide how often and in what circumstance you will have contact with the bully. Unfriend or block the bully on social media if you can. Decide what events you will participate in, and how. Emotional boundaries are not receiving the emotional baggage the bully is wanting to offload onto you. I think of it as a game of volleyball — when the bully tosses the ball over the net (whether that is their anger , insecurity, or shame) ask yourself, is this mine to hold? Are these feelings stemming from something within me- or are they being evoked by the bully’s behaviors? If the answer is these feelings are not mine — volley that ball back over the net. Send those feelings back into the hands of the person doing the bullying. Life quickly becomes exhausting when we hold emotional baggage that is not ours to claim.

6. Practice compassion. Hurt people hurt people. Sadly, people who bully often have had their share of trauma and earlier difficulties leading to the development of a fragile ego and the need to rise up by pushing others down. Looking at it from this angle, while not condoning their behavior in any way, helps to minimize any intimidation you might feel from the bully. Maybe even try imagining them as a little child. This can help evoke feelings of compassion towards an injured human who is still hurting. Looking at it from this angle, we can feel both quite sad for the bully while being liberated from their perceived power at the same time.

7. Depersonalize. I heard beautiful words recently from Bonnie Duran on the Ten Percent Happier podcast hosted by Dan Harris. In it, she said the words “nothing is personal , nothing is permanent , and nothing is perfect .” I think we can use these words to reassure ourselves if we ever find ourselves in the midst of a bullying episode. While it is often difficult to depersonalize, it is an important reminder that the bullying behavior is not about you. It’s about some unresolved difficulties on the part of the person doing the bullying. It’s really not personal. But more than that, ‘ it’s not about you’ reminds us that in this life, nothing is ever uniquely about us- even the things that feel deeply personal. Everything that happens to us- for us- reflects nature: human nature or the nature of this world. The bullying phenomenon is timeless. This power dynamic is written about in some of our oldest stories (read: Cain/Able or Jacob/Esau). Unfortunately, it's how humans have been treating each other for generations and generations. It’s a painful part of the nature of things, and not your story alone. There is something deeply comforting when we frame it in this way. And why has it existed for years and years and years? Because adult bullying is indeed a thing .

Leah Katz, Ph.D., is a clinical psychologist practicing in Portland, Oregon. She specializes in working with teenage girls and women, with a focus on treating anxiety and depression.

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Bullying in Primary School Children: The Relationship between Victimization and Perception of Being a Victim

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Georgina Perpiñà

Robinson ortiz, carles rostan.

This study aims to investigate victimization of bullying in primary school children, as well as its relationship with children’s perception of being a victim. In a sample of 4646 students from 3rd to 6th grade, we evaluated children’s victimization and cybervictimization behaviors, and children were also asked whether they had been victims of bullying or cyberbullying. From the participants, 36.7% were victims, and 4.4% cybervictims. In addition, 24.2% had a perception of being a victim, and 4.9% a perception of being a cybervictim. On the other hand, 56.9% of victims of traditional bullying had no perception of being a victim. The victimization behaviors of traditional bullying associated with a higher perception of being a victim were threats, while physical and direct verbal aggression implied a lower perception of being a victim. The results suggest the most frequent victimization behaviors may be normalized.

1. Introduction

Bullying is a type of aggressive behavior that implies intentionality, repetition and an imbalance of power between the aggressor and the victim, in a way that the victim is incapable of defending against the aggressor [ 1 ]. Cyberbullying occurs when bullying behaviors are carried out using electronic devices [ 2 ], situation in which the repetition, the imbalance of power and the roles of the participants are not as obvious as in traditional bullying [ 3 ]. For example, one aggression with electronic devices may be multiplied with only one intervention of the perpetrator [ 4 ]. Bullying may be divided into different types (physical, verbal and relational) each including direct and indirect forms of aggression, depending on whether the aggressor is concealed (indirect) or not (direct) [ 5 , 6 ]. In the present article we focus on the role of victims of bullying and cyberbullying, which implies notable negative consequences in their psychosocial adjustment [ 7 ]. To analyze this role we considered, on the one side, children’s perception of being a victim (the child admits to having been a victim or not), and on the other side, the victimization behaviors the child informs to have received. In this way, we intend to analyze victimization behaviors in primary school students as a function of sex and grade, as well as the relationship between victimization behaviors and the perception of having been a victim.

1.1. Experience of Bullying and Cyberbullying

An international report of UNESCO [ 8 ] informs of a global percentage of bullying of 32% at the age of 11 years. However, bullying prevalence varies as a function of the instruments used to measure it (which differ in crucial aspects such as the frequency criterion or the time reference period they use), the definition of the concept, the sex, school grade or country of the participants, among other variables [ 9 , 10 , 11 ]. Precisely, an extensive systematic review about cyberbullying in Spain concludes that it is of great importance to unify criteria and choose evaluation strategies appropriately [ 2 ]. For primary school, the study by Juvonen and Graham [ 12 ] suggests that between 9% and 25% of students are victims of school bullying, and these percentages could be even higher than in older children [ 13 ]. This represents an important health problem, as victims of bullying present depressive symptoms, suicidal ideation and suicide attempts (in some cases consummate), anxiety, school dropout and poor academic performance [ 14 ]. It has been reported that victims of bullying in primary school tend to experience more health problems (headache, dizziness, restlessness, nervousness and sleeping problems, among others) [ 15 ]. In relation to the different forms of bullying, as children grow old there is a change from direct bullying to indirect and relational bullying [ 6 ].

Regarding sex differences in traditional bullying, UNESCO [ 8 ] reports a higher prevalence of global victimization in boys than in girls. Specifically, it mentions the Global School-based Student Health Survey (GSHS) study, which finds a global prevalence of 34.8% in boys and 30.4% in girls (13 to 15 years old). The Health Behaviour in School-aged Children (HBSC) study for 2018 in Spain [ 16 ] also reports a higher a prevalence for boys (at the age of 11–12: 14.1% among girls and 17.1% among boys, and at the age of 13–14: 12.1% among girls and 15.7% among boys). Furthermore, a recent systematic review of studies about victimization in primary school found that in most of the studies boys are more likely to be victims of bullying than girls [ 14 ]. Sex differences may be due in part to the fact that boys tend to be involved in physical forms of aggression that are easier to identify, while girls tend to be involved in indirect forms of bullying in relational contexts [ 10 ]. On the other hand, research suggests that children in primary school have higher rates of victimization compared to older children [ 14 ].

In cyberbullying there are also important differences depending on the study [ 17 ], and UNESCO [ 8 ] reports a global cybervictimization of about 10%. In addition, the global report of the HBSC study in 2018 [ 18 ] found that girls were more likely than boys to be victims of cyberbullying (14% for girls and 12% for boys), especially at the age of 13. These sex differences were found in more than half of the countries/regions considered in the study. In Spain, the study by Romera et al. [ 19 ] reports a prevalence of cybervictimization in the last grades of primary school between 7.5% and 10%, and a higher cybervictimization in girls than in boys, both in secondary and primary school. Specifically for primary school, Navarro et al. [ 20 , 21 , 22 ] have found a prevalence of bullying cybervictimization between 4.6% and around 24%, differences that could be explained at least partially by methodological reasons such as the cut-off point for classifying a child as a victim.

Regarding the relationship between cyberbullying and age, the results of the literature seem quite inconsistent; while some studies have found an increase in cybervictimization as students grow old, others have found a decrease, but the majority reports a negligible association [ 23 ].

1.2. Perception of Being a Victim

Some students may receive different victimization behaviors with a certain frequency and still not consider themselves as being victims. Juvonen et al. [ 24 ] explain that those students who had a victim perception were evaluated worse in psychological well-being than those who did not consider themselves victimized. In another study [ 25 ], they found that victims were not conscious of the rejection they suffer from other children. In this sense, it is important that studies consider not only the victimization behaviors that children receive, but also whether children have the perception of being victimized, as it is useful for professionals and families to raise awareness and to alert about the danger of bullying behaviors [ 26 ]. Even so, only a few studies on harassment have taken into account the perception of the victims when identifying them. One of those is the study by Schuster [ 27 ], who found that, among 22 students (11–13 years old) who according to their classmates and teachers suffered bullying only 7 identified themselves as victims (32%). Another study, by Hwang et al. [ 28 ], found that in students aged 12 to 15 the percentage of victims (according to their classmates) who had a perception of being a victim was 16.2% (42 out of 259). Therefore, some studies have examined the perception of being a victim from the perspective of the victim compared to the view of the classmates, but we are unaware of studies exploring the perception of being a victim in relation to the victimization behaviors reported by the same child. This analysis could allow us to understand better how the different types of victimization behaviors are related to the perception of being a victim. On the other hand, Solberg and Olweus [ 29 ] argue that young children could have a more extensive conception of bullying than older children (including actions that are not intentional or not repeated), while other authors defend that younger students exclude indirect types of bullying [ 5 , 6 ]. In any case, the results of Solberg and Olweus suggest that boys and girls with low frequencies of bullying are less likely to consider that they are victims of bullying.

1.3. The Present Study

Although being bullied in primary school might have consequences in secondary school, and even adulthood [ 30 ], only a few studies on bullying and cyberbullying are focused on primary education, and they usually cover just the last cycle of this educational stage (5th and 6th grade). The present research also intends to provide data about bullying and cyberbullying in the middle cycle (3rd and 4th grade). Moreover, few studies have focused on the relationship between victimization behaviors and the perception of being a victim, which is important because the perception of being a victim plays an important role in the recognition of the bullying experience as well as in its consequences [ 28 ].

The present study has two main objectives: First, to study bullying and cyberbullying victimization behaviors in primary school students, and to analyze possible grade and sex differences, including the less studied 3rd and 4th grades; second, to examine the relationship between victimization behaviors and the students’ perception of being a victim.

In relation to the first objective, and according to the scientific literature reviewed above, we can formulate the following hypotheses for the sample of children from 3rd to 6th grade of primary school: (a) Boys will have higher victimization rates in traditional bullying compared to girls [ 14 , 16 ]; (b) Victimization rates in traditional bullying will decrease according to age [ 13 , 14 ]; (c) Girls will have higher cybervictimization rates compared to boys [ 18 , 19 ]; Finally, it was not possible to establish a clear hypothesis relating cyberbullying and age.

Regarding the second objective, we could not make a hypothesis, as we are not aware of prior research studying the relationship between self-reported victimization behaviors and having a perception of being a victim. Therefore, this part will be exploratory.

2. Materials and Methods

2.1. participants.

A total of 4646 students from 3rd to 6th grade of primary school in Catalonia, in northeastern Spain, participated in the study (49% girls). The age ranged between 7.33 and 13.42 years (M = 10.16; SD = 1.17). By grades, there were 1123 third-graders (49% girls; age: M = 8.62 years; SD = 0.37), 1167 fourth-graders (48.8% girls; age: M = 9.65 years; SD = 0.42), 1176 fifth-graders (49.1% girls; age: M = 10.59 years; SD = 0.40), and 1180 sixth-graders (49.4% girls; age: M = 11.61 years; SD = 0.44). Some participants did not respond the question about their sex (65 at 3rd, 55 at 4th, 56 at 5th and 59 at 6th), so results were calculated according to the available data.

With regard to the socioeconomic status, as we collected data on a representative sample of the students from 3rd to 6th grade of primary school in Catalonia, that took into account the type of school of the children as well as the school area (see Procedure section), we believe the sample is representative of the different socioeconomic statuses that exist in this area of Spain.

In order to ensure that our sample size was sufficient to detect an adequate effect, we computed a post hoc power analyses using G * Power 3.1 Software [ 31 ]. Results revealed that our total sample size of 4646 participants was sufficient, in the case of the ANOVA test, to detect with a 0.99 power a medium effect size (f = 0.25).

2.2. Instruments

It is worth noting that right before the administration of the questionnaires, a definition of bullying and cyberbullying was provided to the children by the researchers of the project. Children also had the opportunity to ask questions. Moreover, a definition was also written at the beginning of the questionnaires. The following instruments were administered to the participants, by order of presentation.

• (a) Bullying Questionnaire

The European Bullying Intervention Project Questionnaire (EBIPQ) [ 32 ] was used. It is an instrument of 14 items (7 for victimization and 7 for aggression) in which children are asked what situations they have lived in the last two months, evaluated on a Likert scale with 5 response options: 0 = No; 1 = Yes, once or twice; 2 = Yes, once or twice a month; 3 = Yes, about once a week; 4 = Yes, more than once a week. In the present study, only the victimization scale has been taken into account. Reliability, assessed through Chronbach’s Alpha was 0.81 on the victimization scale.

• (b) Cyberbullying Questionnaire

A reduced version of the European Cyberbullying Intervention Project Questionnaire (ECIPQ) [ 32 ] was used. The original instrument consists of 22 items (11 for cybervictimization and 11 for cyberaggression) evaluated on the same Likert scale mentioned for the bullying questionnaire. In our version for primary education (see Appendix A ), some items were eliminated or merged, while others were maintained, finally using 12 items (6 cybervictimization and 6 cyberaggression). In this study, only cybervictimization items were taken into account. Reliability, assessed through Chronbach’s Alpha on the cybervictimization scale, was 0.75.

• (c) Perception of being a victim and cybervictim

We asked children whether they have been a victim, aggressor or observer of bullying or cyberbullying. In relation to the perception of being a victim, we asked “Have you been a victim of bullying?” and “Have you been a victim of cyberbullying?” Children had to mark yes or no in each question.

2.3. Procedure

First, the Department of Education of the Catalan Government was contacted, who gave permission to conduct the study. To select the educational centers, a representative random sample of students from 3rd to 6th grade of primary school in Catalonia was carried out, stratified according to the type of school (public vs. private or concerted), and size (fewer than one class per grade, one class per grade, or more than one class per grade). Furthermore, in the case of public schools, the territorial area of the Department of Education was also considered as a criterion of representativeness. The school management teams were contacted to explain the project and request participation based on: (a) an explanatory letter of the study; (b) a letter of support from the Department of Education; and (c) consent from the school to confirm participation. A total of 41 schools participated in the study (data were collected between December 2018 and April 2019).

The questionnaires were administered mostly in paper, and only 10 group classes responded to it online. The families were informed of the objectives of the study and their informed consent was obtained. The researchers from the project administered the questionnaires in most cases, but five schools preferred to administer them on their own. After being provided with an explanation of bullying and cyberbullying, children chose to respond the questionnaires in Catalan or Spanish. Researchers from the project monitored that children answered correctly the questionnaires, and gave support to those who asked for help. At no time were the children asked for their names. After completing the questionnaires, children put them in a sealed envelope to preserve anonymity.

This study was approved by the Ethical and Biosecurity Research Committee of the University of Girona (code: CEBRU0016-2018).

2.4. Data Analysis

Data were analyzed using the SPSS 25 statistical program. To classify the participants into victims or cyber victims, the criteria by Romera et al. [ 19 ] was used, who considered as victims those participants with a minimum frequency of “Once or twice a month” in any of the EBIPQ or ECIPQ victimization items. On the other hand, in the line of García-Fernández et al. [ 33 ], participants with a minimum frequency of “More than once a week” in some item have also been considered as frequent victims or frequent cybervictims. Finally, the items of the EBIPQ questionnaire were classified into direct aggressive behaviors (items 1, 2 and 4) or indirect/relational behaviors (items 3, 5–7).

In order to compare victimization behaviors as a function of sex and grade, the mean scores of each type of behavior were used and an ANOVA of grade (4) × sex (2) was performed, also analyzing the simple effects of sex and grade. The partial eta squared (η p 2 ) was taken as a measure of the effect.

To analyze the effects of grade and sex on the perception of the victim, the chi-square test was used, using Cramer’s V as a measure of the effect. The same test was used to analyze the relationship between victimization behaviors and perception of being a victim.

3.1. Victims of Bullying and Cyberbullying

From the participants, 36.7% met the criteria established for victims of traditional bullying and 4.4% the criteria for cybervictims. On the other side, 17.4% of the participants were frequent victims of traditional bullying, while 1.7% of them were frequent cybervictims. Table 1 shows the victims of bullying and cyberbullying according to sex and grade. Table 2 shows the mean scores for victimization and cybervictimization items, so they represent for each sex and grade the mean frequency of the victimization and cybervictimization behaviors.

Percentages of victims and cybervictims as a function of grade and sex.

Percentages represent number of victims or cybervictims for each sex within each grade.

Means (and SD) of bullying and cyberbullying victimization frequency as a function of grade and sex.

Descriptive data represent the mean scores of the frequencies in all victimization/cybervictimization items (range: 0 to 4).

The results showed that 10.3% of victims of traditional bullying were also victims of cyberbullying. The prevalence of cyberbullying was much lower (of only 1%) among those participants who were not victims of traditional bullying. On the other hand, among the victims of cyberbullying, 85.8% were also victims of traditional bullying, while the prevalence of traditional bullying among participants who were not cybervictims was 34.1%.

The results in traditional bullying (means of victimization scores) showed a significant effect of sex (see Table 2 ), with boys reporting more frequent bullying, and a significant decrease according to grade ( F (3, 4127) = 16.96; p < 0.001; η p 2 = 0.012), there being no interaction between both variables ( p = 0.445). The analysis of the simple effects of sex in each of the grades indicated no sex differences in 6th grade, but significant differences existed in the other grades. On the other hand, the analysis of the simple effects of the grade separated by sex presented a significant effect of grade both for boys ( F (3, 4127) = 22.76; p <.001; η p 2 = 0.016) and girls ( F (3, 4127) = 38.71 p < 0.001; η p 2 = 0.027), with a decrease in these behaviors in higher grades.

The results of the 2-way ANOVA for cyberbullying behaviors (mean scores) showed a significant effect of sex with higher scores for boys (see Table 2 ), a significant effect of grade ( F (3, 4196) = 5.96; p < 0.001; η p 2 = 0.004), and also an interaction between both variables ( F (3, 4196) = 4.90, p = 0.002; η p 2 = 0.003). When analyzing the simple effects of sex in each of the grades, differences were observed between boys and girls at 3rd and 4th, but not at 5th or 6th grade (see Table 2 ). The analysis of the simple effects of grade for each sex indicated a grade effect for girls ( F (3, 4196) = 8.38; p < 0.001, η p 2 = 0.006) but not for boys ( p = 0.063). Therefore, cybervictimization remained stable in boys throughout primary school, while increased in girls in the last years of this stage.

3.2. Victimization Behaviors

Table 3 shows the percentage of victims as a function of the number of victimization behaviors. From the total amount of victims of traditional bullying, more than half were victims in more than one item (60.5%). Similarly, 44.3% were frequent victims in more than one item. Most of the cybervictims and frequent cybervictims reported victimization behaviors just in one item (56.8% and 58.1% respectively).

Percentages of victims and frequent victims as a function of the number of victimization behaviors.

Percentages were calculated according to the total: (a) victims of traditional bullying; (b) frequent victims of traditional bullying; (c) cybervictims; and (d) frequent cybervictims.

Table 4 shows direct and indirect victimization behaviors. A two-way ANOVA of grade (4) × sex (2) was performed to analyze the effects of those variables. For direct victimization, there was an effect of sex and grade ( F (3, 4309) = 34.55; p < 0. 001, η p 2 = 0.023). The analysis of simple effects showed sex differences in each grade (see Table 2 ), and the analysis of the simple effects of the grade for boys and girls separately showed a decrease in direct victimization (as the grade increases) in both sexes (Girls: F (3, 4309) = 15.25, p < 0.001, η p 2 = 0.011; Boys: F (3, 4309) = 20.77, p < 0.001, η p 2 = 0.014). The interaction between the sex and grade variables was not statistically significant ( p = 0.237). In summary, boys showed more direct victimization behaviors than girls, and in both sexes these behaviors tended to decrease from 3rd to 6th grade.

Direct and indirect victimization behaviors in traditional bullying according to grade and sex.

Scores ranged from 0 to 4.

For indirect victimization (see Table 4 ), a sex effect was also found with higher scores for girls (see Table 4 ). Similarly, a grade effect was found ( F (3, 4186) = 29.97, p < 0.001, η p 2 = 0.021), but there was no interaction between sex and grade ( p = 0.607). When analyzing the simple effects of grade for each sex, differences were found both in girls ( F (1, 4186) = 13.38, p < 0.001, η p 2 = 0.009) and boys ( F (1, 4186) = 17.27, p < 0.001, η p 2 = 0.012), with a decrease in both. Finally, the analysis of simple sex effects in each grade showed that sex differences in indirect victimization occurred only in 6th grade, with higher scores for girls. In Appendix B ( Table A1 ) we show the descriptive statistics for each of the victimization and cybervictimization behaviors as a function of grade and sex. For the total sample, the most frequent victimization behaviors (of traditional bullying) were physical aggression (M = 0.77; SD = 1.10) and direct verbal aggression (M = 1.07; SD = 1.23).

3.3. Perception of Being a Victim

From all participants, 24.2% had the perception of having been a victim of traditional bullying, and 4.9% reported having been victims of cyberbullying. Table 5 shows the participants with a perception of being a victim as a function of grade and sex.

Percentages and frequencies of participants with a perception of being a victim or cybervictim according to grade and sex.

Percentages represent number of children with a perception of being a victim or cybervictim for each sex.

We did not find a relationship between sex and the perception of being a victim of traditional bullying (using the Chi-square test) in the total sample ( p = 0.355), and only at 5th grade when dividing it by grades (3rd: p = 0.903; 4th: p = 0.536; 5th: χ 2 (1, n = 1102) = 7.71, p = 0.006; Cramer’s V = 0.084; 6th: p = 0.818). However, there was a relationship between perception of being a victim and grade (χ 2 (3, n = 4574) = 31.18, p < 0.001; Cramer’s V = 0.083). This relationship was significant both for boys (χ 2 (3, n = 2209) = 19.75, p < 0.001; Cramer’s V = 0.095) and girls (χ 2 (3, n = 2144) = 16.66, p = 0.001; Cramer’s V = 0.088), with a reduction in the perception of being a victims as the grade increased.

There was a relationship close to significant (χ 2 (1, n = 4243) = 3.73, p = 0.053; Cramer’s V = 0.030) between the perception of being a cybervictim and sex (see Table 5 ). This relationship was significant at 3rd (χ 2 (1, n = 993) = 8.83, p = 0.003; Cramer’s V = 0.094) and 4th grade (χ 2 (1, n = 1063) = 5.71, p = 0.017; Cramer’s V = 0.073), with a higher perception of being a cybervictim in boys; it was not significant at 5th grade ( p = 0.378), and it was significant again at 6th grade (χ 2 (1, n = 1095) = 4.81, p = 0.028; Cramer’s V = 0.066), with a higher perception of being a cybervictim in girls. Besides, the perception of being a cybervictim was not significantly related to grade (p = 0.305), although when separating it by sex, grade differences in the perception of being a cybervictim were found both in boys and girls, with a reduction as the grade increases in boys (χ 2 (3, n = 2149) = 8.93, p = 0.030; Cramer’s V = 0.064) and an increase in girls (χ 2 (3, n = 2094) = 11.44, p = 0.010; Cramer’s V = 0.074).

3.4. Relation between Victimization and Perception of Being a Victim

When analyzing the relationship between the victimization behaviors reported in the EBIPQ questionnaire (on traditional bullying) and the perception of being a victim, a significant relationship was found between both variables (See Table 6 ), although the majority of victims (56.9%) according to the EBIPQ do not have the perception of having been a victim of bullying. This relationship remained stable throughout the different grades; the percentages of victims who did not have a perception of being a victim were 55.6% at 3rd, 61.5% at 4th, 54.5% at 5th, and 56.12% at 6th grade. Regarding the relationship between frequent victimization in traditional bullying and the perception of the victim, it was also statistically significant (See Table 6 ). In this case, frequent victims who did not have a perception of being a cybervictim were 44.6%, being quite stable throughout the grades (46.6% at 3rd, 51.7% at 4th, 43.3% at 5th, and 40.1% at 6th).

Relationship between victimization and perception of being a victim.

When analyzing the relationship between victimization and the perception of the victim as a function of the type of victimization behavior (see Table 7 ), we observed that the type of victimization behavior where the subjects had a greater perception of being a victim was being threatened, followed by exclusion/being ignored. On the other side, the behavior with the lowest perception of the victim was direct verbal aggression, and the second with the lowest perception was physical aggression, which are among the behaviors with a highest frequency (See Appendix Table A1 ).

Percentages of victims who have a perception of being a victim as a function of the type of behavior.

The analysis of the relationship between the perception of being a victim of traditional bullying and the number of items in which participants had a suffered victimization (see Table 8 ) showed that the more items in which children reported victimization, the more likely they had a perception of being a victim.

Percentage of victims with a perception of being a victim according to the number of victimization behaviors.

3.5. Relation between Cybervictimization and Perception of Being a Cybervictim

Table 9 shows the relationship between cybervictims (according to the ECIPQ) and the perception of being a cybervictim. The Chi-square test shows a relationship between both variables. Even so, 67% of the cybervictims did not have the perception of being a cybervictim. Besides, a significant relationship was also found between being a frequent cybervictim and having the perception of being a cybervictim. The percentage of frequent cybervictims who did not have a perception of being a cybervictim was of 58.9%.

Relationship between victimization and perception of being a cybervictim.

4. Discussion

This study aimed to analyze children’s victimization of bullying and cyberbullying in primary school (grades 3rd to 6th) as a function of grade and sex. Also, it intends to study the relationship between children’s victimization behaviors and their perception of being a victim.

4.1. Victimization in Traditional Bullying

We found 36.7% of victims of traditional bullying in children from 3rd to 6th grade (and 17.4% of frequent victims). These percentages are slightly higher than those indicated by UNESCO [ 8 ] globally at the age of 11 (32%), and also slightly higher than the report by Romera et al. [ 19 ] on 5th and 6th grade in Spain (around 30%). The traditional bullying victimization instruments and criteria in our study were equivalent to those of Romera et al., so the differences can possibly be explained by a greater victimization in our study in 3rd and 4th grades compared to 5th and 6th grades. Hence, our data point to a decrease in traditional bullying throughout primary school in both sexes, in line with other studies [ 8 , 11 , 14 ], and higher rates than in secondary school. Thus, our hypothesis about a decrease of victimization rates according to age has been supported. It is possible that bullying-related behaviors changes along primary school, but this change could also be explained by age-related changes in the conception of bullying [ 29 ].

Regarding sex differences, we found a higher victimization in traditional bullying in boys than in girls (except in 6th grade), similarly to other studies [ 8 , 14 , 16 , 34 ], placing the differences already from 3rd grade. Hence, although these data support our hypothesis of greater victimization in boys than in girls, this is not the case in 6th grade. Besides, the lack of sex differences in 6th grade could indicate a change in trend between primary and secondary education. In the study by Romera et al. [ 19 ], sex differences in traditional victimization were very low for primary education (girls showed 2% more victimization) but increased in secondary education (around 6–8% more for girls).

We found a greater direct victimization in boys than in girls, a difference that was significant in all grades. In contrast, girls showed more indirect victimization behaviors than boys, although these differences were only significant in 6th grade. These data are in line with some authors who suggest that boys are more involved in physical forms of aggression and girls in indirect forms [ 10 ]. Beyond these descriptive data, several questions emerge regarding the observed differences between boys and girls in the different grades and in relation to the different forms of bullying. Our study did not used the appropriate instruments to allow a discussion about this issue, but we consider that analyzing this phenomenon from a gender perspective would permit a better understanding of the issue [ 35 ].

4.2. Cybervictimization

We found 4.4% of prevalence of cybervictims (and 1.7% of frequent cybervictims), percentages lower than those found previously in other parts of Spain [ 21 , 22 ], and specifically in Andalusia, where the percentages in 5th and 6th of primary education varied from 7.5% to 10% [ 19 ]. On the other hand, while in our study the vast majority of cyberbullying victims were also victims of traditional bullying (85.8%), a very low percentage of victims of traditional bullying were also victims of cyberbullying (10.3%). Other studies already pointed out that in primary school cyberbullying is related to problems with traditional bullying [ 36 ], and in the present study we highlight the high probability of suffering traditional bullying among cybervictims. This might imply a lack of convenience of interventions only aimed at cybervictimization [ 37 ], especially in primary education.

With regard to sex differences in cybervictimization, our hypothesis has not been confirmed, as we did not observe more cybervictimization in girls compared to boys. Contrarily, we observed more cybervictimization in boys than in girls from 3rd and 4th grades. If we take into account both the effects of grade and sex, we found that cybervictimization remained stable in boys throughout primary education, while it increased from 4th grade in girls. So more cybervictimization was found for boys compared to girls in grades 3rd and 4th, but no sex differences existed in grades 5th or 6th, where an increase was found for girls, especially in grade 6. These results differ somewhat from other investigations in which a higher prevalence of cybervictimization was found for girls with older samples [ 8 , 16 , 19 ]. Thus, sex differences in cybervictimization could undergo a change in trend throughout primary and secondary education, going from being more frequent in boys first and in girls later. This suggests that teachers should be especially attentive to cybervictimization for boys in the earlier years of primary school, and according to what other studies suggest [ 38 ], it is important to implement prevention and intervention programs to help children understand the risks of communication technologies and to deal with cyberaggressions. Finally, in our study most cybervictims were victims of only one type of behavior, whereas most victims of traditional bullying were victims of more than one behavior.

4.3. Relation between Victimization and Perception of Being a Victim in Traditional Bullying

In our study we found that the perception of being a victim (of traditional bullying) is reduced as the grade increases, in line with previous results [ 39 , 40 ]. Considering that the question about perception of being a victim refers to any time point, this reduction is counterintuitive (because older participants have had a longer period for having suffered bullying), and might indicate that younger children have a broader conception of bullying than older children [ 41 ]. Nevertheless, it could also be interpreted as a greater reluctance in older children to accept that they have been a victim. In this sense, some school bullying prevention programs include public recognition of the prevalence of bullying, so that the victim does not attribute it so much to oneself and more to contextual conditions [ 24 ]. It is also possible that in the case of the youngest children (3rd grade), a different conception or understanding of bullying may have influenced the results.

Our results show that only 43.1% of victims of traditional bullying (according to children’s informed victimization behaviors) have a perception of being a victim (and 55.4% in the case of frequent victims). These percentages are higher than in the studies by Schuster [ 27 ] and Hwang et al. [ 28 ], so a greater congruence between the experience of victimization and the perception of being a victim appears when the victimization is evaluated through self-report (as in our case) than through peers (as in the other mentioned studies).

Our study highlights that the perception of being a victim is related to the type of victimization behaviors. Thus, the most frequent victimization behaviors (physical aggression and direct verbal aggression) had a lower perception of being a victim, perhaps indicating a normalization of those behaviors. In this direction, Cuadrado [ 42 ] states that many children and adolescents internalize and normalize many indirect verbal and physical abuses. Perhaps this could also explain why more than half of the victims in our study did not have a perception of being a victim, and only when the number of victimization behaviors increased, or if they suffered a more frequent victimization, this perception increased. Solberg and Olweus [ 29 ] also found that boys and girls with low frequencies of bullying were less likely to consider themselves as victims.

4.4. Relationship between Cybervictimization and Perception of Being a Cybervictim

The perception of being a cybervictim was higher in boys compared to girls at 3rd and 4th grades, but higher in girls at 6th grade, following a trend to decrease in boys throughout primary school and to increase in girls. These data are similar to our results on cybervictimization prevalence. Besides, we observed that only 33% of cybervictims (and 41.1% of frequent cybervictims) had a perception of being a cybervictim, which is lower than in perception of being a victim in traditional bullying. This is especially worrisome considering that attacks with electronic devices can multiply and lengthen over time with a single action by the aggressor [ 4 ]. Thus, it seems necessary to work in primary schools on the concept of being a victim of bullying, and especially of cyberbullying.

4.5. Limitations

Regarding the limitations of the study, when we asked about the perception of being a victim of bullying, we did not ask how long ago it happened, which could have helped to interpret our results more adequately. In addition, the instruments used to measure victimization (EBIQP) and cybervictimization (ECIPQ) do not directly address the issues of intentionality and imbalance of power inherent in the definition of bullying. Moreover, if we had used sociometric data, or measured the victimization perceived by the peers, our data would have been more comprehensive. Finally, as we commented earlier, we cannot discuss up to which point the observed sex differences are related to gender socialization—see Navarro [ 43 ] for a review of gender studies on cyberbullying.

5. Conclusions

In the present study we found a reduction with grade of both children’s victimization behaviors (of traditional bullying) and of children’s perception of (traditional) bullying. Future research should try to disentangle whether these age-related changes are an effect of behavioral or conceptual changes. It is possible that young children have a broader concept of bullying compared to older children, but also that older children are more reluctant to accept that they have been bullied. Regarding sex differences in traditional bullying, boys were more victimized than girls except in 6th grade. Also, in line with prior research, boys suffered more direct victimization (physical and verbal aggressions) than girls in all grades, while girls in 6th grade suffered more indirect victimization than boys. In any case, direct victimization was more frequent than indirect victimization in both sexes.

Cybervictimization was stable in boys but increased in girls along the primary school years. As it was more frequent in boys only at 3rd and 4th grade, and prior studies had found a higher prevalence for girls in older samples [ 8 , 19 ], cybervictimization could undergo a sex-related change of tendency from primary to secondary education. On the other hand, our results highlight that cybervictims in primary school have a high likelihood of suffering from traditional bullying, an aspect that should be considered in interventions designed to address cyberbullying.

We also found that the victimization behaviors of traditional bullying that were associated with a higher perception of being a victim were threats; on the other hand, physical and direct verbal aggression, which were among the behaviors with the highest frequency, were associated with a lower perception of being a victim. This might indicate a normalization of these aggressive behaviors in primary school children, which is an important finding. According to Thornberg [ 44 ], children often view bullying as a normal consequence of deviance related to the victim or fight for social status, and thus they might interpret it as ordinary and trivial and reduce their motives for intervention. Future studies could analyze further which factors contribute to the normalization of these behaviors, and also to understand its consequences on children. More effort must be made to understand how children perceive victimization so that education professionals and families can reduce the widespread tolerance and consequent normalization of bullying [ 26 ].

From the Theory of system justification [ 45 ] it is argued that it is painful to accept that one is living an injustice situation, which leads some people to interpret this situation less negatively; this might help them to feel better, but at the same time reduces the likelihood of taking action and rejecting injustice, especially if they view the situation as inevitable. This could (at least in part) explain why we found that only about half of frequent victims/cybervictims have the perception of having been a victim/cybervictim. Thornberg [ 44 ] suggests that bullying might create a victim career on the victim, which starts with a social construction of being deviant or marginalized, and which implies a social devaluation of the victim. In this regard, our results suggest the need for psychoeducational interventions to work on children’s conceptions of being a victim of bullying (e.g., to help valuing themselves) and against the acceptance and normalization of aggressive behaviors. This seems especially necessary in virtual contexts, where we found a lower perception of being a victim. School bullying represents an important health problem for the victims [ 14 , 15 ]. In this regard, educational centers should promote the rejection of these behaviors and offer explicit support for those who suffer victimization behaviors, as it would make it easier for them to seek help [ 46 ].

Acknowledgments

We thank all the schools for their participation in the study, as well as their students and teachers.

Items used in the cyberbullying questionnaire.

• Someone has said offensive words, insulted or threatened me using social networks or WhatsApp.
• Someone has spoken badly about me using social networks or WhatsApp.
• Someone has tried to impersonate me on social media or WhatsApp.
• Someone has posted personal information about me on the Internet without my permission.
• Someone has posted compromising videos or photos of me on the Internet.
• I have been excluded or ignored from a social network or chat.
• I have said offensive words to someone, I have insulted or threatened them using social networks or WhatsApp.
• I have spoken badly of someone using social networks or WhatsApp.
• I have tried to impersonate someone on social networks or WhatsApp to harm another person.
• I have posted someone’s personal information on the Internet without their permission.
• I have posted compromised videos or photos of someone on the Internet.
• I have excluded or ignored someone on a social network or chat.

Mean (and SD) of the different victimization and cybervictimization behaviors as a function of grade and sex.

Author Contributions

Conceptualization, F.S., C.R. and J.C.; methodology, F.S., C.R. and E.S.; data collection, F.S., E.S., J.C., G.P., R.O. and C.R.; data analysis, F.S.; writing—original draft preparation, F.S. and E.S.; writing—review and editing, F.S., E.S., J.C., G.P., R.O. and C.R.; supervision, F.S. and E.S. All authors have read and agreed to the published version of the manuscript.

This study was carried out thanks to the funding of BARÇA FOUNDATION.

Conflicts of Interest

The authors declare no conflict of interest. Responsibility for the information and views set out in this study lies entirely with the authors. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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