hypothesis on bullying

• Research article
• Open access
• Published: 14 December 2021

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

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

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

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

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

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

Conclusions

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

Introduction

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

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

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

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

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

Participants

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

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

Study outcome

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

Primary exposure

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

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

Statistical analyses

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

Prevalence of bullying at school and mental health problems

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

Associations between bullying at school and mental health problems

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

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

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

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

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

Strengths and limitations

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

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

Availability of data and materials

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

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Acknowledgements

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

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

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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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Is Adolescent Bullying an Evolutionary Adaptation? A 10-Year Review

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• Volume 34 , pages 2351–2378, ( 2022 )

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• Anthony A. Volk   ORCID: orcid.org/0000-0002-4475-8134 1 ,
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• Elizabeth Al-Jbouri 1  

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Bullying is a serious behavior that negatively impacts the lives of tens of millions of adolescents across the world every year. The ubiquity of bullying, and its stubborn resistance toward intervention effects, led us to propose in 2012 that adolescent bullying might be an evolutionary adaptation. In the intervening years, a substantial amount of research has arisen to address this question. Therefore, the goal of this review is to consider whether evidence continues to support an evolutionary perspective that bullying is an adaptation that remains adaptive for some individuals in favorable contexts. In addition, we consider new ideas related to this hypothesis, explore how an evolutionary theory of bullying intersects with other influential perspectives, including ecological and social learning theories, and discuss applied implications for interventions. Our review of the evidence published since our 2012 paper provides very consistent and strong support for the hypothesis that adolescent bullying is, at least in part, an evolutionary adaptation that is currently adaptive regarding at least five evolutionarily relevant functions (the Five “Rs”): Reputation, Resources, deteRrence, Recreation, and Reproduction. We note that bullying is a facultative adaptation that is conditionally adaptive, subject to cost–benefit analyses. Finally, we discuss how an evolutionary theory of bullying frequently complements alternative theories of adolescent bullying rather than conflicting or competing with them. An interdisciplinary approach to bullying that includes evolutionary theory is thus likely to afford stronger options for both research and prevention efforts.

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Volk, A.A., Dane, A.V. & Al-Jbouri, E. Is Adolescent Bullying an Evolutionary Adaptation? A 10-Year Review. Educ Psychol Rev 34 , 2351–2378 (2022). https://doi.org/10.1007/s10648-022-09703-3

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Is bullying in adolescence associated with the development of depressive symptoms in adulthood?: A longitudinal cohort study

• Trine Nøhr Winding 1 ,
• Lisbeth Astrid Skouenborg 1 ,
• Vibeke Lie Mortensen 1 &
• Johan Hviid Andersen 1  

BMC Psychology volume  8 , Article number:  122 ( 2020 ) Cite this article

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Being bullied in adolescence is linked to mental health problems like anxiety, depressive- and somatic symptoms and can have negative consequences on both an individual and a societal level. However, evidence regarding the long-term mental health consequences of bullying in adolescence is limited. The aim of this study was to examine whether being bullied at age 15 or 18 was associated with experiencing depressive symptoms at age 28, and to examine whether being bullied at both ages 15 and 18 increased the risk of experiencing depressive symptoms at age 28.

A prospective cohort study, which applied data from the West Jutland Cohort Study, was conducted. Bullying and depressive symptoms were measured on the basis of self-reported data from surveys in 2004, 2007 and 2017. Depressive symptoms were measured with the Center for Epidemiological Studies Depression Scale. A total of 1790 participants were included in the study, and analyzed by multiple logistic regressions.

The results showed associations between being bullied at age 15 or 18 and the reporting of depressive symptoms at age 28 when adjusted for potential confounders. An exposure–response relationship was seen in those who were bullied at both ages 15 and 18. This group had the highest risk of developing depressive symptoms at age 28.

Conclusions

Being bullied in adolescence was associated with developing depressive symptoms in adulthood and there was an exposure–response relationship between being bullied over time and the later reporting of depressive symptoms. The results highlight the need to provide more detailed information to schools and local communities about the negative consequences of bullying. Such increased awareness may help reduce the risk of young people developing depressive symptoms later in life.

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Introduction

Depression is one of the most common mental illnesses and the number of people with mental health problems is increasing worldwide. Over the past 20 years, the number of mental health problems among young people in particular has risen considerably and account for most of the burden of illness for this age group [ 1 ].

Characteristics of depression are sadness, a poor state of mind, feelings of guilt, decreased self-esteem and difficulty sleeping [ 1 ]. The causes of depression are a complex interplay of social, psychological and biological factors. In addition to the immediate individual consequences of mental health problems, there is also a growing recognition that these problems have a large compromising influence on the individual's ability to cope educationally, professionally and financially and thus reduce the individual's ability to contribute to society [ 2 , 3 ]. The prevention and treatment of mental health problems is therefore of great importance and interest on both an individual and a societal level.

The psychological well-being of children and young people in Denmark is declining. A recent report shows that levels of psychological satisfaction among young people, especially teenage girls, have decreased and that more children and young people are reporting conflicts with peers [ 4 ]. Today every fifth child in Denmark is exposed to bullying [ 5 ]. Bullying is a social phenomenon and in Denmark the proportion of people being subjected to bulling is highest among 11 year olds (11%) and falls to 4% among 15 year olds [ 6 ]. Although the incidence of bullying generally decreases from childhood to adolescence, bullying may be more targeted and persistent in adolescence [ 7 ]. Socializing with peers becomes more important during adolescence, which is a particularly sensitive life period, characterized by many and rapid social, emotional and physiological changes [ 8 ]. Bullying during this period may therefore have a particularly adverse effect on mental health extending into adult life [ 9 ]. Bullying is associated with several adverse outcomes later in life, such as reduced self-esteem, reduced desire to engage in social relations, and health problems such as anxiety, depression and psychosomatic disorders [ 10 , 11 , 12 , 13 , 14 ]. Several cross-sectional studies indicate that there is an association between bullying and mental health problems among children and adolescents [ 12 , 13 , 14 , 15 , 16 , 17 ], and longitudinal studies have linked bullying at school to depression and depressive symptoms in adolescence [ 7 , 17 , 18 , 19 ]. However, there is still a relatively limited amount of research that examines the long-term consequences of bullying in childhood and adolescents and most studies have limited follow-up periods that do not extend into adulthood [ 7 , 18 , 19 ]. A few longitudinal studies identify a link between childhood bullying and mental health problems in adult life [ 10 , 20 ]. A British longitudinal study, spanning five decades, found that children who were frequently bullied had a higher risk of anxiety disorders, depression and suicide at age 23 and 50 relative to peers who had not been bullied [ 10 ]. Sigurdson et al. [ 20 ] found that bullying among Norwegian adolescents at age 14/15 was associated with mental health problems at age 27 and that those who had been exposed to bullying had a significantly greater need for psychiatric help as adults compared with those who had not been bullied. In contrast, in a twin study, Singham et al. [ 21 ] showed that the negative effect of bullying on mental health diminished over time among children and adolescents, which Östberg et al. [ 22 ] also found, but only for males. The literature lacks information about the consequences of more persistent bullying during childhood and adolescence for mental health later in life. At the same time those being exposed to bullying report having fewer close friends and a poorer relation to their parents compared to those not exposed to bullying [ 16 , 21 ]. A study by Bjereld et al. [ 13 ] found that among children aged 4–16 from Nordic countries, those with many close friends had higher odds to be mentally healthy than children with fewer close friends.

This altogether indicates a divergence in the results of the existing literature.

The sparse national and international evidence regarding the long-term mental health consequences of bullying in adolescence combined with the divergence in the results of the existing literature makes it highly relevant to examine the association between adolescent bullying and the development of depressive symptoms in early adult life.

The primary aim of the present study was to investigate whether exposure to bullying at ages 15 or 18 was associated with the development of depressive symptoms at age 28.

The secondary aim was to investigate whether exposure to bullying at both ages 15 and 18 increased the risk of developing depressive symptoms at age 28.

Design and population

This is a longitudinal study using questionnaire data gathered as part of the ongoing West Jutland Cohort Study (VestLiv), which aims to investigate aspects of inequality in health and social differences in welfare from a lifelong perspective [ 23 , 24 ]. Individuals born in 1989 who were living in the county of Ringkjoebing (West Denmark) in April 2004 (age 15) were invited to participate (N = 3681). Contact information for this complete regional cohort of young people was retrieved from the Central Office of Civil Registration and from public schools in the county of Ringkjoebing. Of the original source population, 3054 (83%) filled out the initial questionnaire at age 15 in 2004.

Information from two follow-up surveys were used at ages 18 and 28 with response rates of 65% (n = 2400) and 57% (n = 2102) respectively. Register information about the respondents was derived from national registers in Statistics Denmark using the personal identification number from the Central Office of Civil Registration (CPR number), which is given to every inhabitant in Denmark at birth (or upon entry for immigrants) [ 25 ]. To obtain information about parental educational level, gender and family type (split home), the respondents were also linked to their parents or guardians using the CPR number [ 25 ].

The study population consists of participants who provided information about depressive symptoms at age 28 and bullying at age 15 and/or age 18 (n = 1790). The response rates of the participants in years 2004, 2007 and 2017 are presented in Fig.  1 .

Inclusion into the study population

The outcome of the study was depressive symptoms, which was based on the participants' self-reporting at age 28. We included four items from The Center for Epidemiological Studies Depression Scale (CES-D). This scale is an abbreviated validated version of the original scale [ 26 , 27 ] and is designed to measure the current level of depressive symptoms in a general population, with emphasis on the affective component “depressed state”. The CES-D scale was developed for use in epidemiological studies [ 27 ] and has been translated into several languages and validated for both young people and adults [ 26 , 28 ]. Participants were asked the following 4 questions to assess their level of depressive symptoms: During the past week, how often have you had the following feelings?": (1) "I was happy", (2) "People were unfriendly", (3) "I felt sad", (4) "I could not get going" with the following response options: (1) "Not at all", (2) "A little", (3) "Some", (4) "A lot". The responses were subsequently awarded scores of 0–3 and generated into a sum-score ranging from 0–12, with high values corresponding to having more depressive symptoms. The scales were then dichotomized at 3 points and above into few depressive symptoms and more depressive symptoms, as suggested by Fendrich et al. [ 26 ], who found this cut-point relevant in relation to the prediction of major depressive disorders in the general population.

Questionnaire information about bullying was obtained by the participants' self-reporting at age 15 and 18. At age 15, the participants were asked: "How much have you been bullied at school during the last six months?". At age 18, the participants were asked about bullying in a slightly different way: "How much have you been bullied in an unpleasant way at school during the last six months?". At both ages, the response options were: (1) "Never", (2) “Once or twice”, (3) “A few times”, (4) “Once a week”, (5) "Several times a week". These options were combined into the following three categories: "Not bullied" if they had answered (1), "Bullied" if they had answered (2) or (3) and "Often bullied" if they had answered (4) or (5), as suggested by Andersen et al. [ 29 ].

Potential confounders

Information about potential confounders was obtained from the participants' questionnaire responses at age 15 and 18 and from register information.

Information about the highest level of education in the household in 2003 was obtained from the educational registers [ 30 ] and divided into the following 4 categories: (1) ≤ 10 years (primary school), (2) 10–13 years (secondary school), (3) 13–15 years (short/middle tertiary education), and (4) > 15 years of school (long tertiary education). If the participants’ parents were divorced, information was taken from the household at which the participants had their postal address.

Information about close friends was measured as a question, at age 15, about whether the participants had a friend in whom they could confide (yes vs. no).

Information about family functioning was based on the participants' responses to questions regarding the general functioning of the family at age 15. The General Functioning Scale consists of 12 items that assess the overall health or pathology of the family and is one of seven scales from the McMaster Family Assessment Device (FAD) [ 31 ]. In this study, the variable was dichotomized at a cut-off of ≥ 2, corresponding to the 75%-percentile, with high scores indicating a problematic family function [ 29 , 31 ].

Information about split home and gender was collected from registers [ 25 ]. The variable split home was dichotomized into whether the participant lived with one or both parents.

Statistical methods

The characteristics of the study population were presented by gender, and the distributions of the categorical variables were presented by number and proportion.

The distributions of being bullied at age 15 and 18 in relation to depressive symptoms at age 28 were presented by number (n) and proportion (%). Because only a limited number of participants reported that they were "often bullied" at age 18, the categories "Bullied" and "Often bullied" were collapsed into one category called "Bullied" in regard to all analyses using information about bullying at age 18.

The associations between being bullied at age 15 or 18 and the development of depressive symptoms at age 28 were analyzed using multiple logistic regression. Firstly, crude estimates between each exposure variable and outcome were performed. Secondly, estimates adjusted for parental educational level, close friends, family functioning, gender and split home were calculated. Thus, crude and adjusted odds ratios (ORs) were estimated with 95% confidence intervals (95% CI). As supplementary analyses, the associations between being bullied at age 15 or age 18 and depressive symptoms at age 28 was adjusted for depressive symptoms at age 15.

Finally, the association between being bullied both at age 15 and age 18 and developing depressive symptoms at age 28 was investigated by constructing the following three categories:

"Not bullied", if not bullied at age 15 or 18

"Bullied at one age point", if Bullied or Often bullied at either age 15 or 18,

"Bullied at two age points", if Bullied or Often bullied at both age 15 and 18

We furthermore carried out a sensitivity analysis using a multiple imputation chained model with 100 imputations. Seven chains, either logit or ologit dependent on the categorization of the variables, were constructed in order to impute missing data on the following variables: depressive symptoms at age 28, bullying at age 15 or 18, family functioning and close friends at age 15, split home and household educational level in year 2003. Information on gender was complete. Besides the above mentioned variables some additional were included: (1) depressive symptoms at age 15 and 18 were included when imputing depressive symptoms at age 28, (2) being bullied at age 28 was included when imputing bullying at age 15 and 18, respectively, The final estimates were found as the average of the m sets of estimates and the standard errors by applying a simple formula called Rubin’s rule (results not shown) [ 32 ]. All statistical analyses were carried out in STATA statistical package (V.15.0; State, College Station, TX).

Ethical considerations

This study is in accordance with the 1975 Declaration of Helsinki [ 33 ]. The study is approved by the Danish Data Protection Agency. According to Danish law at the time point of data collection, questionnaire and register-based studies did not need written informed consent nor approval by ethical or scientific committees [ 34 ].

Characteristics of the study population are presented in Table 1 .

Table 1 shows that more females than males participated in the study. Slightly more females than males reported more depressive symptoms. There was a decrease in the prevalence of bullying from age 15 to age 18 in both females and males. 26% of males were bullied ("bullied" or "often bullied") at age 15 and this level dropped to 13% at age 18. 25% of females were bullied ("bullied" or "often bullied") at age 15 and this level dropped to 10% at age 18. The prevalence of males who did not have any close friends at age 15 was higher compared with the females and the prevalence of males who were living with both parents was higher compared with the females.

Table 2 shows that more participants who had been "bullied" or "often bullied" at ages 15 or 18, reported more depressive symptoms at age 28 than those who had not been bullied.

Table 3 shows OR in the range of 1.6 to 2.1 between being bullied at age 15 or age 18 and the reporting of depressive symptoms at age 28, when adjusted for potential confounders.

Being bullied at age 15 increased the risk of reporting depressive symptoms by 1.6 and reporting being often bullied at age 15 increased the risk by 1.8, though statistical insignificant, when adjusted for potential confounders. Being bullied or often bullied (one category) at age 18 increased the risk of reporting depressive symptoms at age 28 by around 2 compared with those who had not experienced bullying.

Adjusting the association between being bullied at age 15 and depressive symptoms at age 28 for depressive symptoms at age 15 changed the adjusted OR to 1.6 (1.2; 2.0) in "bullied" and to 1.4 (1.1; 1.8) in "often bullied", and the adjusted OR between "bullied" age 18 and depressive symptoms age 28 changed to 2.0 (1.4; 3.0).

Table 4 shows a clear exposure–response relationship between the extents of bulling over time.

Those who were bullied at one age point (age 15 or 18) had a 1.8-fold increased risk of reporting depressive symptoms at age 28, whereas those who were bullied at both age points (15 and 18) had a 2.7-fold increased risk of reporting depressive symptoms at age 28 compared with those who had not experienced bullying at either of the two age points. Both adjusted ORs decreased by 0.2 when also adjusting for depressive symptoms at age 15.

In this study we found that those who were bullied at ages 15 or 18 had an increased risk of developing depressive symptoms at age 28 compared with those who were not bullied. An association between being bullied and developing depressive symptoms already began to emerge among those who reported being bullied “once or twice” or “a few times” during the previous 6 months at age 15. However, the strongest association was seen among those who reported being bullied at both age 15 and 18.

Previous studies have documented an association between being bullied as a child and developing subsequent mental health problems [ 9 , 16 , 35 , 36 ]. However, these studies vary greatly in their study design, follow-up periods, and definitions and categorizations of exposure and outcome. Moreover, studies investigating persistent bullying during childhood and adolescence are limited and only a handful of studies examine the long-term health consequences of bullying, which makes a direct comparison with the results of this study difficult. In the following discussion, the results of this study will therefore be compared with the longitudinal studies considered most relevant.

In line with our findings Takizawa el al [ 10 ] demonstrated that a high frequency of bullying had a negative impact on mental health. Likewise, Sourander et al. found that exposure to frequent bullying at age 8 was associated with severe psychiatric problems, including depression, as an adult [ 36 ]. However, the present study found that even infrequent bullying—“once or twice” or “a few times” during the previous 6 months—had a negative effect on the participants’ mental health.

Zwiezynska et al. [ 7 ] documented an exposure–response relationship between being bullied both at age 8 and 10 and symptoms of depression. These findings are in line with the findings of this study, which demonstrates an association between being exposed to bullying both in early and late adolescence and developing depressive symptoms in early adulthood.

Sigurdson et al. [ 20 ] showed an association between bullying and depressive symptoms, when adjusting for baseline depressive symptoms. The latter finding is consistent with the results of the present study, as adjustment for baseline depressive symptoms did not change the results significantly. By contrast, Zwiezynska et al. [ 7 ] found that depression at baseline had a significant effect on the development of depressive symptoms as an adult.

Previous studies have shown that more females than males experience depressive symptoms [ 7 ] and studies also reveal that both friendship and the type of friendship are important in relation to bullying and depressive symptoms. Skrzyipec et al. found that the likelihood of a person experiencing mental health problems decreased the more close friends he/she had [ 37 ]. This is supported by Bjereld et al. who found that bullied children who had more than 3 close friends were more likely to enjoy good mental health than bullied children with fewer close friends [ 13 ]. In this study, we made adjustments for background characteristics, gender, and social relations to family and peers, but these factors only explained a minor part of the association between being bullied during adolescence and reporting depressive symptoms as an adult.

Strength and limitations

This study benefitted from a prospective design and a relatively large sample size. Information about bullying was collected from two separate age points, ages 15 and 18, which allowed us to examine the course of bullying throughout adolescence.

However, it is also important to note some limitations of the study. A main limitation was that both exposures and outcome were based on self-reporting, which increases the risk of common methods bias [ 38 ]. It is possible that participants who were bullied were also more likely to report depressive symptoms due to their mental state. This increases the risk of overestimating the associations between the exposures and the outcome and hence bias away from the null-hypothesis.

However, adjustments for depressive symptoms at age 15 did not change the estimates considerably, with a maximum change in OR of 0.4, why we believe that the risk of bias was minor.

Although the study showed significant associations between being bullied and experiencing depressive symptoms, is it important to be cautious of causal inference. Firstly, it could be argued that a 10-year gap between the latest exposure measurement of bullying and the measurement of depressive symptoms is too long. However, a certain amount of time between baseline and follow-up data is necessary as a main criterion of the definition of being bullied is the prolonged nature of the negative experience [ 39 ], and negative acts often develop over a long time span [ 40 ].

Another limitation of this study is missing information about bullying at age 18. Participating in surveys may be prone to selection bias if non-participation is associated with both exposures and outcomes. In this study, we found more participants were females, had higher educated parents and more often lived with both parents compared with the non-participants. However, non-participants and drop-outs in the same cohort were examined in a previous study and results showed that neither non-participants nor drop-outs influenced the size of the associations significantly [ 41 ]. We furthermore conducted a sensitivity analysis using a multiple imputation model (results not shown). These results showed none or small deviations of the adjusted estimates in both directions. The OR between bullying age 15 and depressive symptoms age 28 decreased in "bullied" from 1.6 to 1.5 (1.2; 1.9) and increased in "often bullied" from 1.8 to 2.2 (1.2; 4.2), whereas the adjusted estimate related to bullying at age 18 did not change. The adjusted estimate between being "bullied at one age point (age 15 or 18)" decreased from 1.8 to 1.7 (1.3;2.2), whereas the adjusted estimate related to "bullied at both age points (15 and 18)" decreased from 2.7 to 2.6 (1.5; 4.3). However, the assumptions of missing at random cannot be fulfilled with the imputation model, as the mechanism behind loss to follow-up in this study is unknown and may be related to unmeasured factors not included in the model. Furthermore, it is also worth noting that the measurement of bullying consisted of a single item, which allowed the individual participant to define the concept of bullying. An initial definition of bullying could have been beneficial, since the perception of what bullying is may be individual. Using such a definition could have increased the validity of the measuring tool. In relation to measuring exposure, it would have been beneficial to use a more in-depth questionnaire to determine the degree and nature of bullying but also to establish whether the participant was a victim or a perpetrator of bullying, since some studies show that both the bullied and the bully have a greater risk of mental health problems later in life [ 35 , 36 , 42 ].

In this study, there were few participants who were "often bullied" at age 18. This made it necessary to collapse the two bullied categories into one. This favored anonymity and increased the statistical strength, but it also made it more difficult to examine the exposure–response relationship between the amount of bullying at age 18 and depressive symptoms at age 28.

The questions used to measure depressive symptoms were derived from the CES-DC questionnaire [ 26 ]. We chose to dichotomize the scale in order to simplify the interpretation and increase the comprehensibility of the results. Although the proportion of young people with depressive symptoms seemed high, it does not differ much from findings in other populations [ 43 , 44 ].

It is important to emphasize that this questionnaire measures symptoms and is not a well-established diagnosis of depression. The high proportion of young people presenting with depressive symptoms could reflect that early adulthood is a challenging period of life due to leaving home and starting working life or further education. We used a cut point of 3, but changing this cut point to 2 or 4 did not change the size of the estimates significantly.

The potential confounders were selected a priori based on a literature review. Additional potential confounders for the association between bullying and depressive symptoms could be ethnicity and personality type, which it would have been beneficial to adjust for in the current study.

The fact that the study is based on a complete regional cohort of young people and contains a considerable number of responders strengthens the generalizability of the results to the rest of the country.

Despite the methodological limitations of the study, we think it is likely that the results can be transferred to similar populations in other countries with similar societal, cultural and social conditions.

The current study found that being bullied in early or late adolescence was related to depressive symptoms in adulthood, especially among those being bullied frequently and those who reported being bullied at both ages 15 and 18. This study adds to a growing body of research showing that being bullied in childhood can have potential serious mental health consequences in the longer run. Bullying should therefore be considered an important public health risk. Providing more detailed information to schools and local communities about the negative consequences of bullying and developing interventions to reduce bullying may help reduce the development of depressive symptoms later in life.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Winding, T.N., Skouenborg, L.A., Mortensen, V.L. et al. Is bullying in adolescence associated with the development of depressive symptoms in adulthood?: A longitudinal cohort study. BMC Psychol 8 , 122 (2020). https://doi.org/10.1186/s40359-020-00491-5

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Introduction, discussions, conclusions, funding information, disclosure statement, data availability statement, framing bullying as a health risk: null effects on young adults’ support for anti-bullying policies.

Subject: Psychology and Psychiatry

Published online by Cambridge University Press:  19 August 2020

• Peer reviews

Given extensive research underscoring the deleterious effects of bullying on youth adjustment, anti-bullying policies and programming are critical public health priorities. However, strategies that increase public support for anti-bullying causes are not well understood. This experiment assessed the influence of “bullying messaging” on support for anti-bullying policies. Specifically, I investigated whether learning about the health consequences of bullying, as opposed to its prevalence or educational impact, increased individuals’ support of anti-bullying policies. Participants ( n  = 329) were randomly assigned to one of four conditions where they read a brief summary about bullying research; conditions varied by whether the research documented the: a) prevalence of bullying b) mental health consequences of bullying c) physical health consequences of bullying or d) academic consequences of bullying. Results indicated that participants endorsed high levels of support for anti-bullying policies, regardless of experimental condition, and that policies aimed at increasing K-12 mental health resources were most supported.

Approximately one in every five youth are bullied by their peers (U.S. Department of Education, 2016 ), and extensive research highlights the deleterious effects of bullying on victims’ mental health, physical health, and academic outcomes (Juvonen & Graham, Reference Juvonen and Graham 2014 ; Wolke & Lereya, Reference Wolke and Lereya 2015 ). Communicating the severe consequences of bullying to the public may be essential for the promotion of appropriate policy changes and program development. Indeed, framing scientific findings in ways that engage key public stakeholders can catalyze important translational efforts (Bubela et al., Reference Bubela, Nisbet, Borchelt, Brunger, Critchley, Einsiedel and Jandciu 2009 ), and past research suggests that people are more supportive of public action towards pressing social issues ( e.g. , childhood obesity) if they are framed in terms of their health consequences (Gollust et al., Reference Gollust, Niederdeppe and Barry 2013 ). However, very little is known about public perceptions of bullying or whether framing bullying as a health risk promotes greater support for the development and implementation of anti-bullying policies. Learning about the health burden of bullying on victims may be one powerful method of highlighting its severity and garnering greater support for anti-bullying initiatives.

The goal of the present study was to evaluate the influence of “bullying messaging” on young adults’ support for anti-bullying policies. Understanding whether certain framing strategies promote greater anti-bullying support is important for translational efforts seeking to bridge bullying research and policy. Specifically, the study tests whether emphasizing the negative health consequences of bullying—as opposed to underscoring its prevalence or educational impact—promotes greater support of programs and policies designed to reduce bullying among youth. As an exploratory aim, this study also examines young adults’ relative levels of support for different types of anti-bullying policies ( e.g. , federal laws versus school-based interventions).

Procedures were preregistered as part of a larger study protocol on the Open Science Framework ( https://osf.io/75vng ), and data analyzed for the current study can be found at https://osf.io/t5fzv/ . Participants (n = 350) between the ages of 18 and 25 were recruited via online advertisements from an undergraduate psychology subject pool at a large, urban university in the midwestern United States and received course credit for participating. All procedures were approved by the university’s Institutional Review Board. The current study focuses on an analytic sample of 329 participants (82% female; 45% White/European American, 22% Middle Eastern/North African, 13% South Asian, 7% Black/African American, 6% Multiethnic/Biracial, 3% Latinx, 5% Other) who completed the full experimental procedure. At the end of an online survey, participants were randomly assigned to one of four conditions in which they read a brief passage summarizing findings from an ostensible large-scale research study on bullying that was made up for the experiment (see Table 1 ). After reading the research summary, participants rated how much they supported six different anti-bullying policies (items adapted from Gollust et al., Reference Gollust, Niederdeppe and Barry 2013 ) using a Likert-scale ranging from 1 (strongly oppose) to 5 (strongly support). Ratings from the six items were averaged to create a mean score of anti-bullying policy support, with higher scores indicating greater support for anti-bullying programming (α = 80).

Table 1. Experimental conditions varying in bullying messaging.

Table 2. Results from one-way between-subjects ANOVA comparing average levels of anti-bullying policy support by experimental condition.

Confirmatory analyses ( i.e. , testing preregistered hypotheses) were conducted using a one-way between-subjects ANOVA to compare average levels of anti-bullying policy support by experimental condition. There were no significant differences in policy support across conditions (see Table 2 ). Average support for anti-bullying policies was relatively high, regardless of whether the article emphasized prevalence ( M  = 4.40, SD  = .54), mental health effects ( M  = 4.30, SD  = .69), physical health effects ( M  = 4.37, SD  = .52), or academic effects ( M  = 4.31, SD  = .64).

Table 3. Results from one-way repeated-measures ANOVA comparing item-level mean differences for each type of anti-bullying policy collapsed across conditions.

Note. Values reflect results with a Greenhouse–Geisser correction.

Exploratory analyses ( i.e. , testing non-preregistered hypotheses) were conducted using a repeated measures ANOVA to examine item-level mean differences for each type of anti-bullying policy collapsed across experimental conditions. Results indicated significant within-person differences in endorsement of the six policies (see Table 3 ). Pairwise comparisons with a Bonferonni correction showed that participants endorsed the highest levels of support for making mental health resources available to students in K-12 schools and the lowest levels of support for creating a federal law against bullying (see Table 4 ).

Table 4. Item-level means and standard deviations for anti-bullying policy support.

Note. Non-shared subscripts indicate significant mean-level differences between items. All denoted differences significant at p  < .001 after Bonferroni correction.

The results suggest that strategically framing messages about bullying around health risk, as opposed to prevalence or academic impact, does not increase young adults’ support for anti-bullying policies. Results from exploratory analyses also highlighted young adults’ perceived importance of K-12 mental health resources for bullied youth, regardless of messaging type. Limitations include the reliance on a convenience sample of predominantly female college students, restricting the generalizability of the results. For example, the null findings may reflect some degree of developmental specificity (Bradshaw et al., Reference Bradshaw, Sawyer and O’Brennan 2007 ) and corresponding ceiling effects. The current sample of young adults have grown up in a world where bullying is more widely recognized as a serious public health issue (National Academies of Sciences, Engineering, and Medicine, 2016 ), and, across conditions, most participants agreed or strongly agreed with all six policy suggestions. Bullying messaging type could have stronger effects on the policy opinions of older adults, who may exhibit greater variability in their perceptions of bullying and its broader societal significance. Replication of results among a nationally representative sample would provide important insights into the robustness of the current findings.

The current results did not support the hypothesis that health-related bullying messages would resonate more than non-health-related bullying messages. However, the findings also provide some encouragement by revealing high overall support for anti-bullying policies, at least as endorsed among young adults. Future research should consider whether there are differences in bullying framing effects among different age groups ( e.g. , younger versus older adults) and as a function of individuals’ peer histories.

None to report.

The author declares that there are no conflicts of interest.

The data used in this study are available from https://osf.io/t5fzv/

Review 1: Framing bullying as a health issue: Does it increase public support of antibullying efforts?

Conflict of interest statement.

Comments to the Author: Although the paper offers a novel insight into the implications of how bullying is framed, there is greater depth required to justify the importance of this within the article. My advice to the author is to build the real world application/importance of framing bullying from a health perspective and embed this specifically within the population under study. The author would also benefit from building theoretical content in the introduction section for which to explore in the discussion section of the report. There is a disjoint between the theoretical discussion points raised and the material provided in the introduction. The title would benefit from reflecting the study outcomes, despite non-significant results as opposed to opening a question – this is misleading. In addition, the abstract should clearly state the aims in the opening section. It is not until the introduction section that I was clear about the aims of the research.

Presentation

Review 2: framing bullying as a health issue: does it increase public support of antibullying efforts.

Comments to the Author:

-Introduction

–The author nicely summarizes the purpose of the study and grounds it in some literature in a concise manner.

–How were participants recruited?

–If permitted by Gollust et al., (2013), please make sure that the exact wording of the survey items are available to the reader either by including in an appendix or an online repository.

–Is it possible to provide some item-level descriptive statistics for each item on the scale? I think this should be included.

–In reading the first sentence of this section “Confirmatory analyses…” I started to assume you had conducted a factor analysis, but that’s not the analysis you chose. Please revise this first sentence so that it reads “Analyses were conducted…”

–For the second paragraph in this section, I would also advise against starting with “Exploratory analyses…” Instead consider, “Analyses were conducted using a repeated measures ANOVA to explore item-level mean differences…”

-Discussion

–You must include some mention of study limitations. For example, how were participants recruited? Could this affect the generalizability of the findings?

-Tables/Figures

–Tables 2 and 3 are not ANOVA tables and should not be captioned or referred to as such. These tables show what appears to be the scale score descriptives (mean and standard deviation). This must be revised. You should still report the scale score descriptives (perhaps in the text) and ought to show the actual ANOVA table (look up an APA example template of this on the Internet).

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ORIGINAL RESEARCH article

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

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

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

Introduction

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

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

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

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

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

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

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

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

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

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

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

Participants

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

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

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

Questionnaires

Bullying history.

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

Depression, Anxiety, and Stress Scale (DASS)

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

Positive Mental Health Scale (PMH)

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

Resilience Scale

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

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

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

General Self-Efficacy Scale (GSE)

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

Data Analysis

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

Bullying Frequency in Both Countries

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

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

Correlation Table

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

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

Mediated Path Analytic Model Within the German Sample

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

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

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

Mediated Path Analytic Model in the Chinese Sample

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

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

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

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

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

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

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

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

Data Availability Statement

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

Ethics Statement

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

Author Contributions

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

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

Conflict of Interest

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

Acknowledgments

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

Supplementary Material

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

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

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

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

Reviewed by:

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

*Correspondence: Jürgen Margraf, [email protected]

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

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A Case Study with an Identified Bully: Policy and Practice Implications

Bullying is a serious public health problem that may include verbal or physical injury as well as social isolation or exclusion. As a result, research is needed to establish a database for policies and interventions designed to prevent bullying and its negative effects. This paper presents a case study that contributes to the literature by describing an intervention for bullies that has implications for practice and related policies regarding bullying.

An individualized intervention for an identified bully was implemented using the Participatory Culture-Specific Intervention Model (PCSIM; Nastasi, Moore, & Varjas, 2004) with a seventh-grade middle school student. Ecological and culture-specific perspectives were used to develop and implement the intervention that included psychoeducational sessions with the student and consultation with the parent and school personnel. A mixed methods intervention design was used with the following informants: the target student, the mother of the student, a teacher and the school counselor. Qualitative data included semi-structured interviews with the parent, teacher and student, narrative classroom observations and evaluation/feedback forms filled out by the student and interventionist. Quantitative data included the following quantitative surveys (i.e., Child Self Report Post Traumatic Stress Reaction Index and the Behavior Assessment Scale for Children). Both qualitative and quantitative data were used to evaluate the acceptability, integrity and efficacy of this intervention.

The process of intervention design, implementation and evaluation are described through an illustrative case study. Qualitative and quantitative findings indicated a decrease in internalizing, externalizing and bullying behaviors as reported by the teacher and the mother, and a high degree of acceptability and treatment integrity as reported by multiple stakeholders.

Conclusion:

This case study makes important contributions by describing an intervention that is targeted to specific needs of the bully by designing culture specific interventions and working with the student’s unique environmental contexts. Contributions also are made by illustrating the use of mixed methods to document acceptability, integrity and efficacy of an intervention with documented positive effects in these areas. In addition, implications for policy and practice related to the treatment of students identified as bullies and future research needs are discussed.

INTRODUCTION

Bullying is one of the most significant school problems experienced by children and adolescents and affects approximately 30% of students in U.S. public schools. 1 This included 13% as bullies, 10.6% as victims and 6.3% as bully-victims. 2 Bullying has been defined as repeated exposure to negative events within the context of an imbalanced power relationship. 3 Bullying is a serious public health problem that may include verbal or physical injury, as well as social isolation or exclusion. 3 – 4 As a result, research is needed to establish a database for interventions designed to prevent bullying and its negative effects within the context of school policies. 4

Researchers have found that bullying may have deleterious effects for both perpetrators and victims, including social, emotional, mental health and academic concerns, as well as loss of instructional time. 5 – 12 For example, a relationship has been found between bullying behavior and internalizing problems (i.e., depression and anxiety), as well as externalizing problems (i.e., aggression and hyperactivity). 11 – 12 Further, bullies have been found to have more conduct problems and less favorable views of school than their non-bullying peers, which may lead to academic disengagement. 5

Rationale for the Case Study

The purpose of this case study is to describe the implementation of an individualized psychoeducational intervention with an identified bully and to report the outcomes of the intervention in terms of acceptability, integrity and efficacy. 13 This case study was unique because we used mixed methods (i.e., both qualitative and quantitative methods) to contribute to the database on acceptability, integrity and efficacy by providing a rich description of the cultural and contextual variables that may influence the implementation and outcomes of the intervention. 14 This case study was distinctive because it used the Participatory Culture-Specific Intervention Model (PCSIM) to design, implement, and evaluate the intervention. 15 Based on an ecological-developmental stance, PCSIM addresses individual and cultural factors related to mental health and promotes cultural competence using culturally valued resources and coping skills. 16 – 18 PCSIM uses an iterative data collection process that incorporates feedback from stakeholders to promote treatment acceptability and cultural validity, treatment integrity and efficacy. 15 The research questions were: (1) What was the nature of acceptability from the perspectives of stakeholders? (2) What was the treatment integrity of intervention implementation? (3) Was there a reduction in this student’s: (a) externalizing symptoms, (b) internalizing symptoms and (c) bullying behaviors?

Context and Informants

We conducted this study in a southeastern urban public school district with 2,484 students and 499 students at the target middle school. The population was diverse with respect to ethnicity (approximately 40% African American, 52% Caucasian, 2% Asian, 2% Hispanic and 4% multiracial) and socioeconomic status (30% free and reduced lunch). The research team had an ongoing collaborative relationship with this school district for eight years. 19 Bullying behavior was addressed in the district discipline policies, which were distributed to students at all grade levels. The school response to bullying depended on severity and could include: student participation in a conference with school personnel, assignment to alternative lunch area, partial or full day in-school suspension (ISS), out of school suspension, financial restitution for the repair of any damage, or consideration of an alternative placement for up to 10 school days.

The informants included the mother of the target student, the interventionist, a classroom teacher, the seventh-grade school counselor and the target student. The target student’s mother, Ms. S., was an African-American woman who worked in the education field. The interventionist was an African-American female doctoral-level school psychology graduate student who was certified as a school psychologist and had 10 years of classroom teaching experience. The seventh grade counselor was an African-American female masters-level school counselor who had been employed by the district for many years. Based on the tenets of PCSIM, stakeholders participated as informants by providing data to develop intervention goals and to assess intervention acceptability, integrity and efficacy. 15

Qualitative Data

All interviews were semi-structured and produced qualitative data. Interviews were conducted with the mother, teacher and the target student. Interviews were conducted with all informants prior to intervention to facilitate development of the intervention sessions. The pre-intervention student interview was audio taped, transcribed and coded for major themes. The interventionist took ethnographic notes during all other interviews. Teacher and parent interviews were conducted post-intervention to enhance outcome data. Parent interview questions included a focus on the target student’s behavior at home and school, parent concerns related to his behavior, and the results of previously employed strategies. The course instructor, which this student received the lowest conduct grade, participated in data collection (i.e., interviews, observations, and surveys). Examples of the questions from the student, teacher and parent interviews are reported in Table 1 .

Sample interview questions asked of the bullying student, his parent and teacher.

Behavioral observations

The referred student was observed in structured (classroom) and less structured settings (hallway, lunch) to determine the frequency and nature of bullying behaviors and to aid in intervention development. We used a narrative approach (i.e., rich description) for conducting behavioral observations to gain information regarding peer and teacher interactions.

Evaluation/Feedback Forms

We used qualitative student evaluation and interventionist feedback forms to gather narrative information related to intervention implementation, including acceptability and integrity of the intervention. The student feedback forms were completed at the end of each intervention session and were used to determine what the participant liked about the session, as well as what he would change about the session. The interventionist feedback form was completed following each session and provided documentation about culture-specific modifications as well as treatment acceptability and self-assessment of the interventionist’s performance.

Quantitative Measures

Behavior assessment scale for children: second edition.

The Behavior Assessment Scale for Children (BASC-2) was administered to the teacher, parent and student pre- and post-intervention. 23 These data from the student were not considered because of observations indicating that the student did not read the items carefully and, instead, provided invalid responses. The BASC-2 is a behavior rating scale that was designed to evaluate personality characteristics, emotions, self-perceptions or parent/teacher perceptions of adolescents. At-risk T-scores range from 60 to 69 while T-scores of 70 or above are considered clinically significant. This instrument has high test-retest reliability ( r = .91) and internal consistency ( α = .89). 23 We used the internalizing, externalizing and bullying scales for this case study.

Child Self Report Post Traumatic Stress Reaction Index

The Child Self Report Post Traumatic Stress Reaction Index (CPTS-RI) was administered before and after the intervention to determine change in symptoms related to post-traumatic stress experienced by the target student. 20 The CPTS-RI was used to supplement information provided by the BASC-2 regarding internalizing problems. The CPTS-RI has high internal consistency ( α = .86) and test-retest reliability ( r = .84). Although the CPTS-RI does not yield standard scores, raw scores of 38 and above have been described as clinically significant in previous research. 21 , 22

Qualitative Data Analysis Procedures

The qualitative data (interviews, observations, & evaluation feedback forms) were subject to thematic analysis by having one coder read through each piece of data to create a list of themes that were reflected by these data. 24 We employed a deductive approach to coding in which the coder identified information regarding externalizing, internalizing and bullying behaviors in the data. 17 After the first coder had read through all data to generate a list of themes, a group of three coders read through all of the data again and used a consensus-based approach to confirm or modify each theme. This team also selected quotes illustrating these themes. 25

Quantitative Data Analysis Procedures

We analyzed the pre/post quantitative data (internalizing and externalizing from the BASC-2) using a two-step process that included calculation of the Reliable Change Index (RCI) and determination of whether an observed change was clinically significant. 26 – 28 We calculated the RCI based on the standard error of measurement or reliability of the instrument and the student’s pre- and post-scores for each instrument. We used the following formula based on Jacobson & Truax (RCI = X 2 − X 1 /S diff ). S diff is calculated by taking the square root of 2(S E ) 2 , where S E is the test’s standard error of measurement. 27 RCI scores of 1.96 or greater are considered to be statistically significant. Mean scores from the CPTS-RI and bullying content scales were analyzed descriptively. We did not calculate RCI scores for these two variables because standard scores are not reported for the CPTS-RI and there are insufficient data about reliability and standard error of measurement for these two instruments.

Background of the Case Study

The target student for the intervention was David, a 12-year-old African-American student in the seventh grade. David’s mother (Ms. S.) provided background and medical information. David lived with his mother and nine-year-old sister. His family history included a recent martial separation. However, regular contact with his father was maintained through weekend and extended holiday visitation. David’s medical history included a diagnosis of Attention Deficit Hyperactive Disorder, which was managed through medication and counseling.

Reason for referral

David was referred for the bullying intervention by members of the administrative and counseling staff and was described as a “provocative bully” by administrators and teachers. An administrator indicated that David had a tendency to “annoy” his peers verbally until they “reach[ed] their limit” and as a result became physically aggressive with him. The administrator described David’s behavior as verbal bullying. The school counselor expressed concerns about his limited ability to engage in prosocial interactions with peers and school personnel, as David appeared to “ignore the comments of adults” and seemed unaware of how his actions or remarks were perceived by peers. Ms. S. (David’s mother) expressed concern that her son was becoming verbally aggressive in reaction to being bullied at school. She cited school reports of inappropriate comments to teachers and peers as evidence of David’s verbal aggression and indicated that his bullying behaviors persisted or escalated irrespective of school and home interventions. Ms. S. and the school personnel stated that they were interested in determining the best ways to intervene.

INTERVENTION

Data obtained from interviews, surveys, review of records and observations were used to develop an individualized eight session intervention to address David’s bullying behavior. 29 Intervention sessions are described in Table 2 including the sessions, the goals, and cultural modifications that resulted in the individualization of the curriculum. 29

Sessions, goals, and cultural modifications used to individualize the curriculum.

Note. Adapted with permission of the authors.29 Please contact second author for more details regarding the curriculum.

Consistent with the PCSIM, we evaluated this case by examining both the process and the outcomes of the intervention that was implemented with a student who had been identified as a bully-victim. We answered the acceptability, integrity, and efficacy of the intervention for this case study. 15 , 30 – 32

Acceptability: Research Question 1

We defined acceptability as the extent to which stakeholders (e.g., mental health professionals, parents, teachers and students) find a particular treatment or intervention to be fair, appropriate, reasonable and consistent with their expectations of treatment. 31 We collected acceptability data through parent, facilitator, student and teacher report and used data to modify the curriculum in an effort to increase acceptability and efficacy. 15 For example, David reported in the session evaluation that activities that were less contingent upon verbal interaction were more acceptable than those that required him to discuss emotions. Through the recursive process of the PCSIM, subsequent sessions were adapted to allow for choice between various less verbally demanding tasks, such as those that allowed David to respond to the curriculum by creating artwork such as drawings or collages. 16

Examples of high acceptability also were revealed through post-intervention data obtained from all stakeholders. For example, Ms. S. indicated that she viewed the intervention as an important resource to address her son’s social deficits related to interpersonal relationships with peers and family members. David’s teacher acknowledged the value of the intervention as a reinforcement tool by informing David of her ongoing communication with the interventionist to encourage him to behave appropriately in order to have positive remarks relayed about his behavior. We also obtained measures of acceptability from the interventionist after each session, suggesting that initial sessions were less acceptable due to the resistance encountered and the slow development of rapport between the interventionist and the target student. However, treatment acceptability increased during subsequent sessions as rapport developed due to curriculum modifications made based on student feedback (i.e., less verbal input was required).

Integrity: Research Question 2

We defined integrity as the degree to which core program elements are implemented and cultural adaptations are documented. 15 This study employed a partnership model to maintain treatment integrity, by focusing on collaboration with stakeholders in order to be culturally responsive while maintaining the essential components and content of the intervention. 30 We obtained integrity data through the interventionist feedback forms to evaluate the ways in which session goals were met. Based on a thematic analysis of these forms, treatment integrity was high as session goals were met in all of the intervention sessions (meeting the threshold of greater than 80% implementation of intervention components). 31

Efficacy: Research Question 3a –Externalization

We collected qualitative and quantitative results related to David’s externalizing behaviors from the teacher and parent report. The teacher reported in an exit interview that David no longer engaged in disruptive activities after completing assignments but instead chose to read. David’s mother reported a decrease in the number of phone calls received regarding disciplinary concerns from the school during and after the intervention. There was a clinically significant difference in the teacher pre- and post-intervention BASC-2 scores reflecting reduced externalizing behaviors (RCI = − 3.74). There was no change indicated by the parent pre- and post-test BASC-2 scores on externalizing behaviors ( Table 3 ).

Pre-post scores for internalizing, externalizing and bullying.

Efficacy: Research Question 3b- Internalization

The school counselor reported that David was less withdrawn at the end of the intervention. For example, she indicated that he made eye contact and acknowledged the statements or requests of school personnel, which were skills addressed in sessions related to empathy and perspective taking. Although David’s CPTS-RI raw score of 20 did not meet the threshold of clinical significance (i.e., 38 and higher), his post-intervention score of seven suggested a lower perception of internalizing symptoms associated with post-traumatic stress after the intervention. Specifically, he indicated that he had fewer bad dreams and was better able to concentrate at school. Quantitative findings from the BASC -2 included a clinically significant decrease in Internalizing Behaviors based on Teacher report (RCI = −3.79). However, there was no change related to internalizing symptoms based on parent report.

Efficacy: Research Question 3c- Bullying

The results of the BASC-2 completed by his teacher revealed that David’s bullying behavior decreased based on pre-post test data. His score on the bullying content scale from the teacher BASC-2 decreased from the at-risk range (SS = 66) to within normal limits (SS = 59) for students his age. Ms. S. reported no change on the parent BASC-2 from pre- (SS= 62) to post-test (SS = 62) in regards to David’s bullying behavior. However, as mentioned earlier, she reported the number of discipline referrals decreased during and after the intervention. Further, qualitative findings from school personnel also suggested improvement in David’s behavior after the intervention. Additional support for positive change in this area is that there were no additional counseling or disciplinary referrals for the remainder of the school year ( Table 3 ).

This case study contributes to the literature related to intervention with bullies by providing an in-depth description of a promising intervention model and by using mixed methods resulting in evidence that this intervention had high acceptability, integrity and efficacy. 13 Using the PCSIM, this intervention successfully integrated data about the culture of bullying within the target school, as well as using knowledge gained through collaboration with parents, teachers and school personnel. 15 , 20 This psychoeducational intervention engaged multiple stakeholders, including school personnel, the mother, and the target student, to facilitate intervention acceptability and integrity and thereby increased the likelihood that the desired outcomes would be achieved. 15 , 30 Further, the use of mixed methods and multiple informants strengthened validity of the intervention and evaluation by examining findings across multiple informants and multiple sources of data. 14

An important finding in this case study was related to the efficacy of this intervention. Based on prior literature, the referral concerns and the pre-intervention data, the intervention was designed to reduce behaviors and symptoms associated with externalization, internalization, and bullying. 11 – 12 Predicted reductions in externalizing behaviors and bullying were partially confirmed with quantitative findings reflected by the RCI for externalization and clinical significance on the bullying scale from the BASC-2. 26 – 28 Additional support was provided by qualitative data from interviews and observations. Similarly, the predicted reductions for internalization were partially confirmed based on the RCI for internalization on the BASC-2 as well as by descriptive data from the CPTS-RI. These quantitative findings were confirmed by qualitative data obtained from school personnel. However, it is noted that the findings for internalizing were not supported by parent report.

The participatory approach to problem identification and intervention development incorporated in the PCSIM was successful in several ways. 15 For example, school personnel and the target student’s mother identified ongoing communication with the interventionist as a strength of the intervention. This enabled teachers to provide insight into the daily interactions of the students, the previous intervention efforts of school personnel, and an overview of the student’s social, emotional and academic strengths and challenges. Further, collaboration with the interventionist provided teachers with an opportunity to experience the target student in a different light by examining the influence of family context on the student’s behavior. This interaction between stakeholders and the interventionist exemplified the recursive nature of the PCSIM and illustrated the potential importance of mental health consultation in facilitating positive outcomes when intervening with bullies. 15 , 33

LIMITATIONS AND FUTURE RESEARCH

Since this case study was conducted with a single participant, more research is clearly needed to demonstrate the acceptability, integrity and effectiveness of this individualized intervention with identified bullies. In addition, given the range of findings from both the parent and teacher, future efforts should be designed to include input over time from multiple participants and to use these data for recursive revision of intervention plans. School-based (e.g., school counselors, school psychologists, school nurses) and mental health practitioners are uniquely qualified to design and implement culture-specific interventions for bullies in schools by using their relationships with stakeholders, along with ongoing data collection, to increase intervention acceptability, integrity and efficacy. 15 Future research may include a greater emphasis on systematic evaluation of the processes used to consult with educators and parents, particularly since educators and parents can have different views, while also having great potential to influence children. Based on information gained through the iterative process of the PCSIM, the intervention might be used as a method of primary prevention by extending it to younger students. 15 Further, research is needed to examine the range of ways that this intervention may need to be modified to address the characteristics of other bullies and their unique cultural and ecological circumstances. Such modifications might include multiple sessions per week, meeting with members of the target student’s peer group, and a greater focus on behavior management strategies.

POLICY AND PRACTICE IMPLICATIONS

This case study has important implications for practice in the context of public policy. While the ideas discussed in this paper may have the potential to create meaningful change in some bullies, it requires intense levels of data collection and analysis to address the acceptability, integrity and efficacy of this type of intervention. This requires a public commitment to the expense needed to carry out such intervention effectively. It also may require research based on public health models that seek less expensive methods of intervention and that emphasize a full range of preventive interventions, including primary prevention. 4 In this context, it is noted that policies in place within a school, school district and/or community may play a role in strengthening intervention efforts. 4 For example, the intervention described in this paper was implemented in the context of school policies that did not tolerate bullying and that had clear guidelines for school responses to bullying. Also, schools policies of service delivery referred to as response to intervention that include a simultaneous focus on a range of services including primary prevention, risk reduction, secondary prevention and tertiary prevention. 34 Research is needed to develop an understanding about the impact of such policies on the efficacy of individualized interventions such as this.

Acknowledgments

We would like to thank the student, parent, and school personnel who participated in this intervention. Funding for this work was supported by the American International Group, Inc. Additional funding was provided by the Center for School Safety, School Climate, and Classroom Management and the College of Education Dean’s Office at Georgia State University.

Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. The authors disclosed none.

Reprints available through open access at http://scholarship.org/uc/uciem_westjem .