research paper on high school 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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Preventing Bullying Through Science, Policy, and Practice (2016)

Chapter: 1 introduction, 1 introduction.

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

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

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

STUDY CHARGE

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

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

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

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

CONTEXT FOR THE STUDY

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

Historical Context

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

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

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

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

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

Federal Efforts to Address Bullying and Related Topics

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

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

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

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

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

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

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

The above are examples of federal initiatives aimed at promoting the

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

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

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

Definitional Context

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

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

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

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

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

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

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

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

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

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

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

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

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

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

THE COMMITTEE’S APPROACH

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

Information Gathering

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

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

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

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

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

Terminology

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

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

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

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

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

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

ORGANIZATION OF THE REPORT

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

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

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

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

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

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

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

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

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

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

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Open Access

Peer-reviewed

Research Article

The relationship between teachers’ disciplinary practices and school bullying and students’ satisfaction with school: The moderated mediation effects of sex and school belonging

Roles Conceptualization, Methodology, Project administration, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Institute for Educational Research, Belgrade, Serbia

Roles Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing

Roles Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Affiliation University of Belgrade, Faculty of Special Education and Rehabilitation, Belgrade, Serbia

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Project administration

Roles Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Investigation

Affiliation Institute of Criminological and Sociological Research, Belgrade, Serbia

Roles Formal analysis, Software, Visualization

• Marina Kovacevic Lepojevic, 
• Marija Trajkovic, 
• Luka Mijatovic, 
• Branislava Popovic-Citic, 
• Lidija Bukvic, 
• Milica Kovacevic, 
• Ana Parausic Marinkovic, 
• Mladen Radulovic

• Published: May 28, 2024
• https://doi.org/10.1371/journal.pone.0303466
• Reader Comments

An authoritative school climate, along with greater teacher support and warm relations among peers are frequently connected with less school bullying. The main aim of this paper is to examine the direct link as perceived by students between teachers’ disciplinary practices and bullying in school and students’ satisfaction with school. The indirect relationships are explored via the mediation of school belonging and the moderation of sex. High school students (N = 860, 40.4% male students) completed the Delaware School Climate Survey, the Multidimensional Students’ Life Satisfaction Scale, and the Psychological Sense of School Membership Scale at a single time point. In general, teachers’ disciplinary practices have significant direct effects on perceptions of bullying and satisfaction with school. Positive disciplinary (direct effect = .28, SE = .04) and SEL techniques (direct effect = .22, SE = .04) are related to bullying only among males, while punitive techniques are directly linked to school bullying unrelated to sex (b = .03, SE = .05). Similarly, the effect of positive disciplinary (direct effect = .27, SE = .08) and SEL (direct effect = .21, SE = .08) techniques on satisfaction with school was significant only among males. A direct relationship between punitive disciplinary techniques and satisfaction with school was not recognized. The mediation analysis revealed the indirect effects of teachers’ disciplinary practices on the dependent variables via school belonging to be stronger among females. Teachers’ negative modeling through punitive disciplinary practices leads to more bullying. School belonging may serve as a protective factor related to the negative impact of teachers’ disciplinary practices on school bullying as well as satisfaction with school, especially among females. Interventions should be focused on fostering school belonging along with the development of positive sex-specific disciplinary practices.

Citation: Kovacevic Lepojevic M, Trajkovic M, Mijatovic L, Popovic-Citic B, Bukvic L, Kovacevic M, et al. (2024) The relationship between teachers’ disciplinary practices and school bullying and students’ satisfaction with school: The moderated mediation effects of sex and school belonging. PLoS ONE 19(5): e0303466. https://doi.org/10.1371/journal.pone.0303466

Editor: Gianpiero Greco, University of Study of Bari Aldo Moro, ITALY

Received: September 15, 2023; Accepted: April 25, 2024; Published: May 28, 2024

Copyright: © 2024 Kovacevic Lepojevic et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The data collection was funded by the Council of Europe and the European Union within the project Promotion of Diversity and Equality in Serbia, Horizontal Facility for the Western Balkans and Turkey (Horizontal Facility II, 2019-2022), BH4674/2021/7, and preparation of the manuscript was funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (Contract No. 451-03-47/2023-01/200018 and No. 451-03-66/2024-03/200039). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: NO: The authors have declared that no competing interests exist.

Introduction

By its definition school bullying involves the repeated intent to harm and an imbalance of power between the aggressor and the victim [ 1 ]. Such an imbalance of power may stem from physical strength, social status within the group, or a certain vulnerability (e.g. appearance, learning difficulties, family situation, personality characteristics) [ 2 ]. Less school bullying is frequently connected with an authoritative school climate, and more teacher, peer and parental support [ 3 – 5 ]. Scientific results imply that instead of being considered in terms of the individual’s behaviour, bullying should be considered as a structural issue [ 6 ]. Harsh discipline in schools is generally directly related to more experiences of bullying as a consequence of negative teacher-student modeling [ 7 ]. Punishment is often used in traditionally oriented schools and reflects a policy of zero tolerance and the frequent use of suspensions and exclusions from school. Research results indicate that a supportive disciplinary framework is recognized in effective bullying prevention programmes [ 8 ], and even punitive discipline may be successful in achieving the short-term effects of managing student behaviour [ 9 ]. Teachers’ SEL disciplinary practices are the most effective in developing students’ self-discipline and long-term positive developmental changes [ 10 ]. The results of evaluation studies show that SEL in combination with positive disciplinary techniques achieves better results than without them [ 11 , 12 ]. Certain authors stress that in an authoritative school climate, both responsiveness (support) and demandingness (structure) are equally valued, and together are viewed as instrumental for effective discipline in both the short and long term [ 13 ]. There has been a notable shift in school programmes from bullying prevention to the systemic integration of the evidence-based practices of social and emotional learning (SEL) [ 14 ]

One of the frequently examined indicators of positive youth developmental outcomes is student life satisfaction [ 15 ]. Subjective well-being is most often interpreted as experiencing a high level of positive affect, a low level of negative affect, and a high degree of satisfaction with one’s life [ 16 ]. The concept of subjective well-being has frequently been used synonymously with ‘‘happiness”, meaning that maximising one’s well-being has been viewed as maximising one’s feelings of happiness [ 16 ]. However, self- reports of being happy do not necessarily mean that people are psychologically well [ 16 ]. As represented in the Eudaimonic Activity Model, eudaimonic and hedonic aspects of well-being are closely related [ 17 ]. Life satisfaction is one of the most important indicators of youth well-being and represents their cognitive evaluation of their quality of life [ 18 ]). This might be conceptualized as a general life satisfaction assessment or within specific life domains (e.g. satisfaction with friends, family, and school experiences) [ 19 , 20 ]. The author suggests the variability in satisfaction ratings across life domains, with adolescents reporting the greatest dissatisfaction with their school experiences [ 21 ]. Creating a balance between responsiveness and demandingness in the classroom is connected to higher student satisfaction with school [ 22 ]. The interpersonal relations between students and teachers and among peers has been found to be the most important school climate factor which affects student satisfaction with school [ 22 ]. The research results suggest that teachers should focus more on positive disciplinary practices as they are linked to improved outcomes for both students and teachers [ 23 ]. Monitoring the effects of the RULER program–an evidence-based approach to social and emotional learning, significant improvements in multiple dimensions of the school climate, including disciplinary practice, were found to be related to satisfaction with school [ 24 ].

Previous research recognized school belonging as a good mediator in explaining the link between different aspects of the school climate and various positive and negative student outcomes such as problematic internet use [ 25 ]; academic success [ 26 ]; bullying, and symptoms of depression [ 27 ], etc. School belonging is defined as the extent to which students feel personally accepted, respected, included, and supported by others in the school social environment [ 28 ]. The research results indicate that school belonging is closely related to many positive developmental outcomes such as higher student cognitive and behavioural engagement, higher motivation and academic success [ 29 , 30 ]; fewer problems and higher prosocial behaviour [ 31 , 32 ], and higher life satisfaction [ 33 ]. The results show that students in positive school climates report higher levels of school belonging and fewer physical, emotional, and cyberbullying behaviours [ 27 , 34 ]. School belonging mediates certain school climate aspects (e.g. teacher-student relationships, and a sense of fairness) in relation to students’ life satisfaction [ 35 ]. School belonging may not be relevant for negative disciplinary practices. Supportive teaching practices are closely linked to school connectedness, while punitive disciplinary practice has no significant correlation with school connectedness [ 36 ]. Class level path analysis showed that the effect of the student-teacher relationship on bullying behaviour is mediated by the student-student relationship [ 37 ].

Numerous differences in peer socialization and variances between males and females have been recognized to date, starting from girls’ relational orientation, a tendency to build more meaningful relationships, interpersonal sensitivity and prosocial orientation [ 38 ], suggesting greater male engagement in bullying [ 5 , 39 ], less connectedness with school [ 40 ], and less positive relationships with teachers [ 41 , 42 ]. To our knowledge, sex moderation of the mediation of school belonging in examining the relationship between teacher disciplinary practices and school bullying behaviour and satisfaction with school has not yet been explored.

The main aim of this paper is to examine the links between teachers’ disciplinary practices perceived by students with bullying in school and with students’ satisfaction with school. The indirect relationships are explored via the mediation of school belonging and the moderating role of sex. The proposed model includes how (the mediating effect), when (the moderating effect), and when and how (moderated mediating effect) teachers’ disciplinary practices affect both bullying and students’ school satisfaction ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0303466.g001

Based on authoritative discipline theory [ 43 , 44 ] and Stockard and Mayberry’s [ 45 ] theoretical framework for the school climate which imply that a healthy balance between responsiveness (support) and demandingness (structure) lead to more self-discipline [ 46 ] we hypothesized that: punitive discipline is negatively related to satisfaction with school and positively to bullying; teachers’ socio-emotional techniques as well positive disciplinary techniques are negatively related to school bullying and positively to students’ satisfaction with school. School belonging is expected to have mediating potential in the explanation of the relationship between disciplinary practices and bullying in schools and disciplinary practices and students’ satisfaction with school. Additionally, we expect to find that the proposed interactions differ by sex We hypothesized that socioemotional learning and positive disciplinary techniques can help to develop school belonging, especially at females. Also, we expect that teachers’ negative modeling via the use of punitive discipline is expected to affect males more directly. We consider that further exploring of the sex moderation between teacher practices and school belonging can help to the developing of school belonging, greater satisfaction of students and prevention of school bullying.

Materials and methods

Students from 11 Belgrade (Serbia) high schools from the first to the fourth grade (N = 860, 40.4% male students) completed the Delaware School Climate Survey [ 47 ], the Multidimensional Students’ Life Satisfaction Scale [ 19 ], and the Psychological Sense of School Membership Scale [ 28 ] at a single time point from April 5 th to May 28 th 2021. Measures The Delaware Positive, Punitive, and SEL Techniques Scale [ 47 ] measures students’ perceptions of the extent to which three types of techniques are used in their school to manage student behaviour. The positive behaviour techniques consist of 4 items (e.g. Students are often praised), the use of punitive/corrective techniques of 4 items (e.g. Students are punished a lot), and the use of SEL techniques of 5 items (e.g. Students are taught to feel responsible for their behaviour). In the current study, Cronbach’s alpha coefficient ranged from 0.77 (Punitive Techniques), 0.83 (Positive Techniques) to 0.85 (SEL Techniques) and McDonald’s omega from 0.77 (Punitive Techniques), 0.84 (Positive Techniques) to 0.85 (SEL Techniques) for the student sample. The Bullying School-Wide subscale comprises 4 items which explore students’ perceptions of bullying in their schools (e.g. In this school, bullying is a problem). The rating response range was from 1 (strongly disagree) to 4 (strongly agree). The internal consistency measured by Cronbach’s alpha and McDonald’s omega coefficient is 0.76. The Multidimensional Students’ Life Satisfaction Scale (MSLSS) [ 19 ] is a 6-point Likert-type self-report scale (ranging from strongly disagree (1) to strongly agree (6)), designed for children aged 8 to 18. The MSLSS is designed to provide a holistic assessment of the wellbeing of young people. It has five subscales: family, friends, school, the living environment and self. The school domain items rep-resent satisfaction with school life (e.g. I enjoy school activities). The value of Cronbach’s alpha is 0.84 and McDonald’s omega is 0.85. The Psychological Sense of School Membership Scale (PSSM) comprises 18 items (e.g. Most teachers at this school are interested in me.) to be assessed on a 5-point Likert-type scale from 1 (strongly disagree) to 5 (strongly agree) [ 28 ]. The internal consistency is 0.84 measured by Cronbach’s alpha and 0.90 measured by McDonald’s omega.

Procedure . Verbal informed consent from participants is obtained. At first we presented the research and relevant procedures involve with data collection and usage, and ask to declare if someone doesn’t want to participate. It was witnessed by school psychologist. One school hour was necessary for completing the questionnaire. In the Republic of Serbia there is no regulation at all about parental consent for children participating in scientific research, but Family law, Official Gazette, no 18/2005, 72/11 and 6/2015,and Law about protection of the rights of the patients, Official Gazette, no 45/2013-19, 25/2019-3, respect privacy of children above 15 years (e.g. they make decisions about medical treatments by their own). This study was approved by the Research Ethics and Conduct Committee of the CEPORA–Center for Positive Youth Development (no. 12/2021 ES)

Descriptive statistics and the intercorrelations of the variables

Descriptive and correlation analyses were conducted using SPSS 21.0. PROCESS analyses were performed to test the mediating role of school belonging in predicting bullying and students’ school satisfaction by teachers’ disciplinary practices (positive, punitive and SEL techniques) along with the moderating role of sex. The entire model was previously tested in IBM AMOS version 25.

Table 1 presents the means and standard deviations of the study variables: positive, punitive and SEL techniques, school belonging, bullying and students’ school satisfaction and their intercorrelations.

https://doi.org/10.1371/journal.pone.0303466.t001

The correlation results indicated that bullying was negatively associated with SEL techniques, school belonging and students’ school satisfaction (p < 0.01) and positively with punitive techniques (p < 0.01). Students’ school satisfaction was negatively related to punitive techniques, bullying and age (p < 0.01) and positively to the other study variables. The correlations of age with positive techniques, SEL techniques, school be-longing and students’ school satisfaction were negative and weak (p < 0.01).

Moderated mediation analyses results

The entire model was previously tested in IBM AMOS version 25. Results suggested the model can be considered unsatisfactory: Chi-square value was significant (χ2 = 780.396, p < .001), the TLI and CFI values were below the recommended threshold of 0.90, while the RMSEA was far above the prescribed value of 0.08 (TLI =.-.111, CFI = .704, RMSEA = .339). For that reason, direct and indirect effects were separately tested using the SPSS macro PROCESS suggested by Hayes [ 48 ]. Using proposed model number 59, six PROCESS analyses were conducted–one for each pair of predictor and dependent variables. In this way the independent contribution of the predictors and their relations with the mediator were examined with sex as the moderator. Age was treated as a covariate and its role will not be presented within the results or discussed. A full information maximum likelihood estimator was used which could also handle missing values. The direct, indirect, and total effects were calculated. 5000 bootstrap samples were used. Bootstrapping is a non-parametric method which bypasses the is-sue of non-normality distribution [ 49 ]. All used variables (except sex) were standardized prior to test and effects and their standard errors (SE) are shown.

As regards the first model (F(5,688) = 40.86, p < .01), positive techniques positively predicted school belonging (b = .36, SE = .11, p < .01), sex also predicted the mediator variable (b = -.16, SE = .007, p < .05), while the interaction between positive techniques and sex on school belonging was not significant. Bullying was negatively predicted by school belonging (b = -.38, SE = .15, p < .05) and positively by positive techniques (b = .69, SE = .14, p < .01). Interaction of sex and positive techniques negatively predicted bullying (b = -.3, SE = .08, p < .01) which explained 1.5% of the variance in predicting bullying, while interaction of sex and belonging didn’t have significant effect on dependent variable. Further probing of the significant interaction indicated that the conditional direct effect was significant (and positive) only for males (direct effect = .39, SE = .06, p < .01), while the indirect effects of positive techniques on bullying did not differ between males and females–the index of moderated mediation was not significant (index = -.09, bootSE = .052, 95% BootLLCI = -.2—BootULCI = .01). The entire first model explained 22,9.% of the variance in bullying ( Fig 2 ).

https://doi.org/10.1371/journal.pone.0303466.g002

Within the second model (F(5,692) = 80.09, p < .01), punitive techniques (b = .11, SE = .38, p = .47) and sex (b = -.13, SE = .07, p = .06) as the predictors did not affect school belonging, while the interaction of sex and punitive techniques (b = -.30, SE = .07, p < .01) was significant in predicting the mediator. This interaction explained an additional proportion of the variance in school belonging (2%) with significant effects in both males (effect = -.22, SE = .05, p < .01) and females (effect = -.52, SE = .04, p < .01), showing that punitive techniques exerted a stronger negative effect on school belonging among females. Bullying was positively predicted by punitive techniques (b = .49, SE = .1, p < .01) and sex (b = .22, SE = .06, p < .001), while belonging didn’t have significant effect on bullying in context of these variables (b = .16, SE = .12, p = .18). Interaction of sex and punitive techniques (b = -.03, SE = .06, p = .63) did not influence the criterion, but interaction between belonging and sex did (b = -.23, SE = .07, p < .01), explaining an additional proportion of the variance in bullying (1%) and showing that there is significant negative effect of belonging on bullying among girls (effect = -.31, SE = .04, p < .01) and no such effect among boys. Consequently, the indirect effects of punitive techniques on bullying were positive and significant females (indirect effect = .16, bootSE = .02, 95% BootLLCI = .12—BootULCI = .21) and unsignificant for males (indirect effect = .02, bootSE = .01, 95% BootLLCI = -.01—BootULCI = .04). The index of moderated mediation was significant (index = .14, bootSE = .03, 95% BootLLCI = .09—BootULCI = .20). The entire second model explained 37% of the variance in bullying ( Fig 3 ).

https://doi.org/10.1371/journal.pone.0303466.g003

As regards the third model (F(5,682) = 37.65, p < .01), school belonging was predicted by SEL techniques (b = .29, SE = .1, p < .01), sex (b = -.24, SE = .06, p < .01) and their interaction (b = .2, SE = .06, p < .01). The sex-SEL interaction explained an additional 1% of the variance in the mediator with significant positive effects in both males (effect = .49, SE = .05, p < .01) and females (effect = .69, SE = .04, p < .01), indicating again a stronger effect among females. Bullying was positively predicted by SEL techniques (b = .68, SE = .14, p < .01) and negatively by school belonging (b = -.42, SE = .16, p < .01). Sex (b = .1, SE = .07, p = .15) and the sex x belonging interaction (b = -.02, SE = .09, p = .81) didn’t significantly influence the criterion, while sex x SEL techniques interaction had significant affect (b = -.36, SE = .09, p < .01) This interaction explained 2% of the variance in bullying. The conditional direct effect of SEL techniques on bullying was significant for males (direct effect = .32, SE = .06, p < .01), but not for females. The indirect effects were significant for both males (indirect effect = -.22, bootSE = .04, 95% BootLLCI = -.30—BootULCI = -.13) and females (indirect effect = -.32, bootSE = .04, 95% BootLLCI = -.40—BootULCI = - .25). and they did not significantly differ between males and females (index = -.11, bootSE = .06, 95% BootLLCI = -.22—BootULCI = .01). The entire first model explained 22,93% of the variance in bullying ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0303466.g004

As regards the fourth model (F(5,690) = 192.73, p < .01), the prediction of the mediator was significant for positive techniques (b = .3, SE = .11, p < .01), sex (b = -.19, SE = .06, p < .01) and their interaction (b = .14, SE = .07, p < .05), while the effects on the mediator were significant among both males (effect = .44, SE = .05, p < .01) and females (effect = .58, SE = .04, p < .01). This interaction is significantly higher among females. When it comes to predicting students’ school satisfaction, significant effects were found for positive techniques (b = .32, SE = .1, p < .01), school belonging (b = .62, SE = .12, p < .01), sex (b = .15, SE = .05, p < .01), and the sex x positive techniques interaction (b = -.16, SE = .06, p < .01), while sex x school belonging interaction didn’t predict school satisfaction. The conditional direct effect was significant just for males (direct effect = .16, SE = .05, p < .001). The indirect effects were significant for both males (indirect effect = .30, boot SE = .04, 95% BootLLCI = .23—BootULCI = .38) and females (indirect effect = .43, bootSE = .04, 95% BootLLCI = .36—BootULCI = .5), again indicating a stronger effect among females. The index of moderated mediation was significant (index = .13, bootSE = .05, 95% BootLLCI = .03—BootULCI = .23), while the whole model explained 58% of the variance in students’ school satisfaction ( Fig 5 ).

https://doi.org/10.1371/journal.pone.0303466.g005

In the fifth model (F(5,698) = 198.93, p < .01), the mediator variable was predicted by sex (b = -.17, SE = .07, p < .01) and the interaction of sex and punitive techniques (b = -.24, SE = .07, p < .01), which explained 2% of the variance in school belonging. The independent variable alone did not affect the mediator (b = .07, SE = .11, p = .57). The negative effects of the interaction on the mediator were significant in both males (effect = -.22 SE = .05, p < .01) and females (effect = -.5, SE = .04, p < .01), but higher among females. Students’ school satisfaction was directly predicted by school belonging (b = .84, SE = .1, p < .01) and sex (b = .15, SE = .05, p < .001), while the influences of punitive techniques (b = .02, SE = .09, p = .86), and interaction and sex (b = -.05, SE = .05, p = .35) and interaction of school belonging and sex (b = -.06, SE = .06, p = .3) were insignificant. Due to the latter results, the conditional direct effects were not shown. The indirect effects were significantly higher among females (indirect effect = -.36, bootSE = .04, 95% BootLLCI = -.44—BootULCI = -.29) than males (indirect effect = -.17, bootSE = .04, 95% BootLLCI = -.25—BootULCI = -.1). The index of moderated mediation was significant (index = -.19, bootSE = .05, 95% BootLLCI = -.3—BootULCI = -.09), while the model in total explained 59% of the variance in students’ school satisfaction ( Fig 6 ).

https://doi.org/10.1371/journal.pone.0303466.g006

As regards the sixth model (F(5,690) = 203.05, p < .01), SEL techniques (b = .23, SE = .1, p < .05), sex (b = -.27, SE = .06, p < .01) and their interaction (b = .22, SE = .06, p < .001) predicted the mediator. The SEL techniques x sex interaction explained 1% of the variance of school belonging, while the positive effects on the mediator were significant and lower for males (effect = .45 SE = .05, p < .01) compared to females (effect = .68, SE = .04, p < .01). The effects of SEL techniques (b = .26, SE = .1, p < .01), school belonging (b = .68, SE = .12, p < .001), sex (b = .13, SE = .05, p < .01) and sex x SEL techniques (b = -.13, SE = .06, p < .05) were significant predictors of school satisfaction, while school belonging x sex interaction didn’t have effect. Sex influenced the relation between the independent and criterion variables, where the conditional direct effect was significant only for males (direct effect = .12, SE = .05, p < .01). The indirect effects were significant for both males (indirect effect = .32, bootSE = .04, 95% BootLLCI = .25—BootULCI = .4) and females (indirect effect = .51, bootSE = .04, 95% BootLLCI = .43—BootULCI = .59), with a stronger effect among females once again. The index of moderated mediation was significant (index = .19, bootSE = .05, 95% BootLLCI = .08—BootULCI = .31), while the model in total explained 60% of the variance in students’ school satisfaction ( Fig 7 ).

https://doi.org/10.1371/journal.pone.0303466.g007

As expected, punitive discipline is directly and positively related to school bullying unrelated to sex, indicating the impact of teachers’ negative modeling on student-student behaviour and bullying as its negative manifestation [ 7 , 43 ]. Unexpectedly, positive disciplinary and SEL techniques are positively related to bullying, and that link is found to be relevant only for male students which is contrary to previous findings [ 24 , 50 , 51 ]. One of the explanations for this is that SEL might be perceived as a Trojan horse to increase classroom management and social control, instead of cultivating the positive, full development of the child and the adult educator, including care-givers [ 31 ]. The positive relation between positive disciplinary techniques and SEL with school bullying might be explained by difficulties in implementation at secondary school level if such techniques are not applied appropriately at previous educational levels and simultaneously in other ecological contexts. These findings might imply the need to apply systemic SEL as an approach to create equitable learning conditions which actively involve all Pre-K to Grade 12 students in learning and developing social, emotional, and academic competencies [ 52 , 53 ]. Difficulties in school staff motivation and capabilities are also recognized [ 54 ]. Positive and SEL disciplinary techniques which are not properly implemented might be perceived as more teacher- oriented [ 54 ]. Teachers are then perceived to have a greater share of the power similar to punitive school discipline. These positive relations might be additionally explained in a reactive way, meaning that teachers respond to severe bullying behaviour inappropriately. Teachers might not recognize when incidents of bullying should be considered as severe, requiring help from other agencies and services. The author has already noticed that the severity of peer victimization may moderate the relationship between socio-emotional learning and school bullying [ 51 ]. As the victims of bullying have said, teachers often react to the perpetrator, without offering any support to the victim and the whole class after such incidents [ 55 ]. Teachers may underestimate verbal incidents of bullying, even suffer from bullying themselves, or enable bullying by their inappropriate reaction to the bulling incidents which occur in the classroom [ 56 , 57 ]. As has already been noted in previous research, male students tend to “ignore incidents”, or report only more severe incidents of bullying compared to female students who are more sensitive to minor incidents, which might affect findings about gen-der-specific interactions [ 58 ].

The interesting finding that positive discipline and SEL directly relate to student satisfaction with school only for male students might be explained by the fact that although females are more rationally oriented, have positive relations with teachers [ 41 , 42 ], and build better relations with their peers [ 58 ], parents [ 59 ] and other important figures, supportive teacher relationships might mean more to male students than their female counterparts. Even punitive disciplinary practice was not directly related to satisfaction with school, while school belonging was found to be a good protective factor especially among female students, which is not surprising because of their relational and contextual orientation [ 38 ]. The full mediation of school belonging established in relation to SEL and positive disciplinary techniques on students’ satisfaction with school implies that interventions focused on fostering school belonging along with efforts toward establishing a positive school climate might positively affect students’ wellbeing and have a negative effect on school bullying [ 24 , 32 ]. According to the current study, school belonging is sex-specific and partly explains bullying behaviour [ 27 , 58 ] and student wellbeing [ 34 , 35 ]. The qualitative differences between female and male students indicate that both might use bullying as a tool to feel a sense of belonging, girls to prevent being excluded from the group and boys to avoid being perceived as weak [ 58 ].

As has already been noted, bullying does not occur in a vacuum [ 60 ]. This study highlights the importance of the disciplinary strategies used by teachers in schools, how they manage their classrooms and how this is related to bullying and satisfaction with school. The data about sex relevance within the examined interactions are of special value in this study. The research results are in line with a noticeable shift in bullying prevention towards evidence-based practices of social and emotional learning (SEL) leading to a variety of positive outcomes for students and teachers alike [ 14 , 50 ]. Interventions for developing school belonging are highly recommended in order to prevent school bullying and improve students’ positive developmental outcomes. We recommend that a good fit for bullying prevention in middle and high schools might have teacher practice of adopting greater youth participation at classroom level along with practicing SEL. It’s expected that greater youth participation, and more group discussion will strengthen school belonging, equity impact and less bullying [ 61 ].

This study is limited by its cross-sectional design. Longitudinal or intervention re-search is necessary to provide more detailed answers to the research question regarding the relation between school climate aspects and school bullying. A further limitation relates to the lack of a class level analysis which could provide more exact data. Longitudinal data could provide some evidence of both the short and long term effects of teachers’ disciplinary practices. This research is mono-informant in nature with the measurements being restricted to student self-rating scales. For future studies we recommend involving more global measures of students’ life satisfaction so as to avoid the similarity between the school belonging and satisfaction with school constructs used in the current study. Additionally, measuring bullying victimization as well as disciplinary infractions would be important in order to gain a better under-standing of the mechanisms underlying teachers’ disciplinary practices.

Supporting information

S1 dataset..

https://doi.org/10.1371/journal.pone.0303466.s001

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• 53. Rosario-Ramos E. M, Rivas-Drake D, Jagers R. J. Implementing SEL with an Equity Lens: The Role of “Stretching” in Teachers’ Practice. In Motivating the SEL field forward through equity (Vol. 21, pp. 113–126). Emerald Publishing Limited; 2021.

New report says Australian children are amongst the most bullied in the world

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The Australian Council for Educational Research has released its second report, which reveals the latest data on bullying in English speaking countries – with Australian children facing some of the highest rates of bullying. An RMIT education expert is available for media commentary.

Dr Elise Waghorn, education expert

“One in six students reported they have been made fun of by peers.

“Bullying is considered repeated and intentional use of words or actions against someone or a group of people to cause distress and risk to their wellbeing.

“There are four types of bullying behaviour: physical (hitting, pushing, shoving or intimidating), verbal/written (name-calling or insulting someone about an attribute, quality or personal characteristic), social (deliberately excluding someone, spreading rumours, sharing information that will have a harmful effect on the other person and/or damaging a person’s social reputation or social acceptance), and cyberbullying (any form of bullying behaviour that occurs online or via a mobile device).

“The Australian Council for Educational Research (ACER) released its second report on Tuesday, analysing the latest data from the OECD Programme for International Student Assessment (PISA) test.

"Australian students felt less safe at school compared to the OECD average, with only students from Poland, New Zealand, Hong Kong, and the United States feeling less safe.

"Australian students with the highest exposure to bullying scored an average of 27 points lower than their peers, equivalent to a year of learning.

"There is a strong correlation between disruptive and bullying behaviour and school performance.

"Two-fifths of students in Australia (42%) reported noise and disorder in most classes.

"High levels of distraction due to digital resources like smartphones and apps were reported by 40% of students.

"One-third of students (33%) claimed that their classmates didn't listen to what the teacher said.

“There are many impacts of bullying, disorder and disrespect that go beyond the classroom, which include children feeling disconnected, missing school, experiencing lack of quality of friendships, lowered self-esteem, and increased depression and anxiety.

“Parents can support children by affirming that the bullying not their fault.

“When they tell you about instances of bullying, reassure them that you will not take any action without discussing it with them first.

“Do not encourage retaliation – such as violent acts. Instead, praise your child for reaching out and asking for help, remind them that they are not alone.”

Dr Elise Waghorn has expertise in early childhood development. Her research focuses on exploring the everyday life of children in Australia and their connection to policy and educational experiences in Hong Kong and Singapore.

General media enquiries: RMIT Communications, 0439 704 077 or [email protected]

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School climate: Using a person–environment fit perspective to inform school improvement

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• Published: 19 May 2024

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• Jill M. Aldridge   ORCID: orcid.org/0000-0003-0742-0473 1 ,
• Meghan J. Blackstock 2 &
• Felicity I. McLure   ORCID: orcid.org/0000-0003-3664-9146 3  

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Strong and consistent findings suggest that a positive school climate is related to improved student outcomes. However, assessment of the school climate rarely considers the environmental fit (or misfit) between individuals' actual or lived experiences and their preferred environment. This study drew on a person-environment fit perspective to examine whether: students’ experiences of the school climate (actual environment) differed from their views of their ideal school climate (preferred environment); the views of the actual and preferred environment differed between schools; and the actual–preferred discrepancy (as a measure of the environmental fit) was related to student wellbeing, resilience and reports of bullying. The results from the analysis of data collected from 993 upper primary school students suggest that outcomes were enhanced when the perceived environment more closely matched the preferred environment. Our study’s findings support using a person-environment fit perspective alongside a socio-ecological approach to inform strategic decisions for school improvement efforts.

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The psychosocial school climate refers to the overall atmosphere of a school, including social, emotional and interpersonal aspects. The school climate quantifies the lived experiences of school members, which are shaped by the unspoken ethos, norms, values and beliefs that pervade a school (Cohen et al., 2009 ). The school climate is reflected in the relationships and daily interactions between school members, the rituals and traditions of school life, feelings of safety and inclusion and contextual factors that might impact student learning (Cohen, 2013 ).

The critical role the school climate plays in student wellbeing, academic success and personal development is gaining growing recognition. Research findings suggest that the school climate provides the protective factors needed to guard against adverse student experiences (Doumas et al., 2017 ; Keane & Evans, 2022 ) and promote a range of outcomes, including life satisfaction (Aldridge et al., 2020 ), mental health (e.g., a review of literature by Aldridge & McChesney, 2018 ) and overall wellbeing (Varela et al., 2019 ). Further, positive school climates have been found to have an inverse relationship with adverse outcomes, such as school violence (Booren et al., 2011 ; Espelage & Hong, 2019 ; Steffgen et al., 2013 ), bullying (Acosta et al., 2019 ; Marchante et al., 2022 ; Varela et al., 2021 ) and antisocial (Manzano-Sánchez et al., 2021 ; O’Brennan et al., 2014 ), delinquent (Akman, 2021 ; Aldridge et al., 2018 ; Klein et al., 2012 ; Kohl et al., 2013 ) and aggressive behaviours (e.g., Low et al., 2014 ). School climate factors have also been found to influence the development of social skills, such as prosocial behaviours (González Moreno & Molero Jurado, 2022 ; Luengo et al., 2017 ; Patalay & Fitzsimons, 2016 ; Thapa et al., 2013 ), personality (Roberts & Robins, 2004 ) and resilience (Aldridge et al., 2016 ; Cohen, 2013 ; Kutsyuruba et al., 2015 ); all of which are essential precursors to bullying prevention (Acosta et al., 2019 ; Cohen, 2013 ; Cohen & Freiberg, 2013 ; Wang et al., 2013a , 2013b ).

Of relevance to this study, is that a school’s climate plays an essential role in school improvement efforts (Thapa et al., 2013 ). This makes sense given that students in schools with positive school climates are not only more motivated to actively participate in their learning (e.g., Eccles et al., 1991 ), but are also more likely to attend regularly (Daily et al., 2020 ) and less likely to be suspended (Lee et al., 2011 ). Further, positive school climates have the potential to improve learning outcomes and academic achievement (Shindler et al., 2016 ), reduce achievement gaps and increase career prospects for students from less advantaged backgrounds (Berkowtz, 2022 ; Hopson & Lee, 2011 ).

Growing recognition of the importance of a positive school climate has led to increasing interest in its measurement at both the school and education system levels (Cohen et al., 2009 ). However, traditionally, measures of school climate have relied on assessing students’ experiences of the actual environment, without consideration of their needs. Whilst assessment of the actual environment is meaningful, given the strong and consistent relationship between school climate factors and student outcomes (Aldridge & McChesney, 2018 ; Thapa et al., 2013 ), we contend that consideration of the match (or misfit) between the person and the environment is integral to effective strategic decision-making and school improvement efforts. Therefore, in our study, we drew on a person-environment fit perspective to examine whether a focus on reducing a lack of congruence between students' perceived and desired experiences could improve their outcomes. To examine this overarching aim, three research objectives were addressed:

To examine differences in the perceived (actual) and preferred school climate.

To investigate whether students’ views of the perceived and preferred school climate were similar for students in the same school but different from those in other schools.

To examine the relationships between students' reports of resilience, wellbeing and bullying, and:

Their perceived (actual) school climate.

The actual–preferred discrepancy (size of the environmental misfit).

Assessing school climate

Within the field of learning environments, surveys have been developed to assess classroom-level and school-level environments. The pioneering work of Walberg and Anderson ( 1968 ) and Moos and Trickett ( 1974 ) saw the development of the first learning environment surveys. These instruments were designed to assess students’ perceptions of classroom-level factors, such as the relationships between students and their peers and their teachers (Fraser, 2013 ). Initially, measurement of the school-level environment was associated with the field of educational administration (Anderson, 1982 ; Stewart 1979 ) and focused on aspects related to an organisational climate. However, during the 1960s, a shift in education in the United States that sought to address equity and inclusion issues, saw the emergence of the first school climate surveys. Since this time, numerous instruments have been developed to assess the school climate from the perspectives of different school members (González et al., 2022 ), including teachers (e.g., Aldridge & Fraser, 2016 ; Bear et al., 2014 ), parents (e.g., Aldridge & McChesney  2018 ) and students (e.g., Aldridge and Ala'i, 2013 ; Bear et al., 2011 ).

It is widely agreed that school climate is a multidimensional construct (Thapa et al., 2013 ; Wang & Degol, 2016 ). Despite a lack of consensus regarding which aspects of the school climate should be included in a measure (Cohen et al., 2009 ; Wang & Degol, 2016 ), there is a growing recognition that coverage of four broad categories is important (e.g., Thapa et al., 2013 ; Wang & Degol, 2016 ), these being: safety (assessing the physical and emotional safety provided by the school), community (assessing the quality of the relationships within the school), academic atmosphere (assessing the quality of the instruction and learning support) and institutional environment (assessing how the shared beliefs contribute to overall sense of belonging or inclusion). Although the institutional environment can also assess the quality of the physical environment, our survey did not include this aspect.

As well as being multidimensional, factors that contribute to school climate are considered to be malleable, unlike those outside schools (such as family). That is, measures of school climate should provide information about school-related factors that educators can, to some extent, change or control (García-Carrión et al., 2019 ; Long et al., 2020 ). The malleable nature of the school climate is an important consideration in school improvement efforts as it allows school leaders and education systems to target the improvement of environmental factors that are highly correlated with desired student outcomes (Wang & Degol, 2016 ).

• Person–environment fit

The notion of person-environment fit originates from the work of French et al. ( 1974 ), which was heavily influenced by Lewin’s ( 1935 ) field theory. Lewin’s ( 1936 ) equation B =  f (P, E) proposes that a person’s behaviour (B) is a function of (rather than distinct from) their personal characteristics (P) and the environment (E), highlighting the importance of the environment in understanding behaviour.

A person-environment fit perspective focuses on the interactions between individuals and their environment, with the knowledge that one constantly influences the other (Edwards et al., 1998 ). Underpinning a person-environment fit perspective is the innate desire for individuals to fit in their environment, which includes a need to belong (Deci & Ryan, 2000 ; van Vianen, 2018 ), have autonomy over their life (Hutchings & Chaplin, 2017 ; Yu & Davis, 2016 ), reduce uncertainty and increase consistency (Yu, 2013 ). The fit (or misfit) between the person and the environment causes satisfaction or dissatisfaction and affects an individual’s behaviours, and mental and physical health (Caplan & Harrison, 1993 ; Greguras et al., 2014 ). Further, a misfit between what a person desires and the actual environment has been highly correlated to psychological (e.g.,anxiety or stress) and physiological (e.g., physical wellbeing (Dahm et al., 2015 ) and elevated blood pressure (Edwards & Cooper, 1998 ; Edwards et al., 1998 ; Nagai & Dasari, 2023 )) outcomes.

The two components of person-environment fit, the individual and the environment, can be described objectively or subjectively (Bohndick et al., 2018 ; Caplan, 1987 ). In our study, we used a subjective perspective in which self-ratings (subjectively perceived) of personal qualities (as opposed to the consensual judgement of peers or educators) and (subjective) perceptions of the environment (as opposed to consensual judgments or the concrete environment) were used. The latter (perceptions of the environment) involved students’ views of their actual school climate (the subjective resources provided by the school) and their preferred school climate (subjective needs).

The work of Moos ( 1987 ), which examined the social environments in a range of milieu, examined how the degree of fit between the perceived and desired environment might influence outcomes. Moos ( 1979 ) pioneered the use of both actual and preferred versions of social climate surveys, in which the actual version assessed a person’s perceptions of the environment and the preferred version assessed the environment a person would like (ideal environment). Using both an actual and preferred version allowed the examination of the congruence between what a person needs and what the environment provides. The magnitude of the actual–preferred difference provides information about the environmental fit or misfit. Historically, the two versions (actual and preferred) were administered separately about one week apart. The different versions had corresponding items and although the content was similar for each, the preferred version used a conditional tense (e.g., would). For example, a statement in the actual version would read “Students in this class like me”; in the preferred version, the same item would read “Students in this class would like me”. More recent research has used a more economical side-by-side format to capture the two responses simultaneously (Aldridge et al., 1999 ). Students are instructed to respond to each item twice to report how often the statement takes place and how often they would like it to occur (a wish list if you will). Our study used a side-by-side format.

In keeping with a person-environment perspective, this research drew on the premise that outcomes would improve when a person’s perceptions of the environment were more aligned with their preferences. Past research at the classroom level has suggested that more positive outcomes result when the learning environment is better matched to the student’s needs (see Fraser & Fisher, 1983a , 1983b ). Of the limited number of studies examining whether person-environment fit influenced student outcomes, the majority of these were carried out at the college or university levels. These studies found that a greater person-environment fit improved relationship building with instructors (Deng & Yaim, 2020 ) and students’ performance (Pawlowska et al., 2014 ), satisfaction (Rocconi et al., 2020 ) and wellbeing (Gilbreath et al., 2011 ). Past research examining person-environment fit in schools is limited. Only a handful of studies have been reported, all of which were carried out at the classroom level (see Fraser & Fisher, 1983a , 1983b ). These early classroom-level studies provide evidence to suggest that the actual–preferred differences reported by students could influence their outcomes at the school level.

Despite the limited research available to support the efficacy of using actual–preferred differences at the school level, we hypothesised that improvement efforts to reduce these differences could promote improved outcomes. To our knowledge, past research has not examined relationships between the actual–preferred differences and student resilience, wellbeing and bullying; therefore, our research helps to fill this gap.

The sample was drawn from 12 primary schools across three Australian states. To increase generalisation, the schools were co-educational and located in metropolitan ( n  = 9) and regional ( n  = 3) areas.

In each school, the surveys were administered to all students who volunteered to participate and were present on the day of administration. This provided a total of 1002 cases. During data cleaning, nine cases (approximately 1.01%) were removed as the responses indicated these students were disengaged (standard deviation of 0) or provided the incorrect year level.

Of the remaining 993 cases, 493 (49.6%) respondents identified as male and 500 (50.4%) respondents identified as female. The students, aged between 11 to 12 years of age, were enrolled in years five 5 ( n  = 478, 48.1%) and six 6 ( n  = 515, 51.9%). The distribution of students across metropolitan ( n  = 742) and regional ( n  = 251) schools generally reflected the differences in school sizes in these areas.

Instruments

The collection of data for the study involved the administration of two surveys, one to assess students’ perception of the school climate and the other to assess students’ self-reports of wellbeing, resilience and bullying.

Perceptions of the school climate

The What’s Happening In This School—Primary (WHITS-P; Aldridge & Blackstock, 2024 ) was used to assess students’ perceptions of the school climate. The WHITS-P was based largely on the secondary school version of the What’s Happening In This School (WHITS; Aldridge & Ala’i, 2013 ; Riekie & Aldridge, 2017 ). Development of the WHITS-P involved extrapolating and modifying items (which included simplifying the language and reducing the number of items) to make them suitable for use with younger students. To improve reliability and comprehensibility, items belonging to a scale were grouped together and a child-friendly header was provided at the beginning of each group as a contextual cue. To reduce confusion, all items were worded positively.

To reflect the multidimensional nature of the school climate, the WHITS-P included seven scales to provide coverage of the four broad categories identified by Wang and Degol ( 2016 ). Two scales, teacher support and peer connectedness, assessed the quality of the interpersonal relationships in the school (community). Two scales, rule clarity and reporting and seeking help, assessed the quality of the processes, procedures and other mechanisms used to support school safety (safety). Two scales, support for learning and high expectations, assessed the quality of the learning support (academic atmosphere). Finally, one scale, school connectedness, assessed the extent to which the norms, values and policies gave students a sense of belonging and being valued (institutional environment).

Apart from high expectations, which was assessed using three items, the six remaining scales were assessed using four items. Each item was responded to using a simplified five-point frequency-response format that was developed over multiple trials. The response format included three major anchor points labelled ‘almost never’, ‘sometimes’, and ‘almost always’. An emoji face accompanied these major anchor points to provide a visual cue. In addition to the three major anchor points, two additional anchor points were included, one between the response alternatives of ‘almost never’ and ‘sometimes’ and another between ‘sometimes' and ‘almost always’. A side-by-side format was used to collect the actual and preferred responses simultaneously. Using this format, students responded twice for each statement: once for how often the statement actually happened and again for how often they would like it to happen. Table 1 provides the broad category, a brief description and a sample item for each WHITS-P scale.

Student outcomes

Three scales were used to assess student self-reports of resilience, wellbeing and bullying. All were comprised of four items and used the same five-point response format to measure the school climate. The scales were modified (by reducing the number of items and simplifying the language where appropriate) from existing instruments developed for use in secondary schools. The resilience scale was adapted from a scale initially developed by Wagnild and Young ( 1993 ) and later adapted for use with secondary students (Riekie & Aldridge, 2017 ). The scale demonstrated sound psychometric properties in previous studies (e.g., Aldridge et al., 2016 ) and sought to examine concepts of perseverance and self-reliance. The wellbeing scale was modified from the WHO-Five (WHO, 1998 ) to assess students’ positive wellbeing. When used with secondary students, a modified version reported good psychometric properties (e.g., Riekie et al., 2017 ). Finally, the bullying scale was modified from a survey developed initially by Bandyopadhyay et al. ( 2009 ) to assess the extent to which students felt they were victims of bullying. When responding to outcomes scales, students were asked to consider how often each item occurred over the previous two weeks.

Analysis of the data, described below, was carried out using SPSS (version 29).

For the first research objective, descriptive statistics, including means and standard deviations, were used to compare student responses to the actual and preferred version of the WHITS-P. To examine whether the actual-preferred differences were statistically significant, paired samples t- tests were used. Finally, to examine the magnitude of the differences, the effect sizes were calculated for each scale using the following formula:

For the second research objective, a one-way analysis of variance (ANOVA) with school membership as the main effect was used to examine whether students’ responses to actual and preferred versions of the WHITS-P differed across the 12 schools. Two indices related to the ANOVA results were examined, the significance level and eta 2 statistic (the proportion of ‘between’ to ‘total’ sums of squares), to provide a measure of the degree of association between student responses and the dependent variable to examine the variance explained by school membership (Field, 2009 ),

For the third research objective, simple correlation and multiple regression analysis were used to examine the relationships between the outcome variables (resilience, wellbeing and bullying) and a) students’ perceptions of the school climate and b) the size of the actual–preferred discrepancy. Simple correlations (Pearson’s correlation coefficient) were used to summarise the strength and degree of the relationships. Multiple regression analysis was used to help to understand whether a school climate scale contributed to the student outcomes over and above the contributions made by other school climate variables. Beta coefficients were used to examine the predictive ability of each variable.

Although the analysis was the same for both parts of research objective three, the data used differed. To examine the relationships between the three outcomes and students’ perceptions of the school climate (part 1 of research objective 3), the aggregated responses to items in the actual version of each WHITS-P scale were used. To investigate the relationships between the three outcomes and the degree of fit or misfit (part 2 of research objective 3), the absolute value for the difference between a student's actual and preferred responses was calculated and then used to aggregate the scores of the items in each scale.

Research objective 1: actual–preferred comparisons

The first research objective compared students’ responses to the actual and preferred versions of the WHITS-P. The average item means, portrayed graphically in Fig.  1 and reported in Table  2 , indicate that students’ responses to the preferred version were higher than the actual version for all but one WHITS-P scale, high expectations. Except for the high expectations scale, the range of responses to the preferred version was narrower (with standard deviations ranging from 0.505 to 0.743) than for responses to the actual version (with standard deviations ranging from 0.705 to 0.908). The high expectations scale was the only one for which the preferred responses were lower than the actual responses. Whilst the difference was small and statistically non-significant, this result suggests that students would like less than they receive.

Average item means for students’ responses to actual and preferred versions of WHITS-P scales

The t -test results, reported to the right of Table  2 , suggest that the differences were statistically significant ( p  < 0.01) for all scales except high expectations. The effect sizes, calculated to estimate the magnitude of the differences, ranged from approximately one-third (effect size = 0.395) to over three-quarters (effect size = 0.834) of a standard deviation for scales with a statistically significant difference.

Research objective 2: differences across schools

One-way ANOVA was used to examine whether students’ mean responses to the actual and preferred version of the WHITS-P differed based on school membership. The results, reported in Table  3 , indicate that, for responses to both the actual and preferred versions, there was a statistically significant ( p  < 0.05) difference for all WHITS-P scales. The eta 2 statistic for different WHITS-P scales ranged from 0.023 to 0.050 for the actual version and from 0.051 to 0.113 for the preferred version. The F -values were all greater than 1, ranging from 2.108 to 4.673 for the actual version and from 4.771 to 11.338 for the preferred version. These results (the F -value and p -value) suggest that students in the same school viewed the school climate similarly but differed from those in other schools.

Research objective 3: relationships

Simple correlation and multiple regression analysis were used to investigate relationships between the three student outcomes and (a) the school climate and (b) the actual–preferred discrepancy.

School climate–outcome relationships

First, the results of simple correlation analysis involving students’ responses to the actual version, reported in Table  4 , suggest that the relationships between all seven WHITS-P scales and student reports of resilience and wellbeing were positive and statistically significant ( p  <  0.0 1). These results imply that when school climate factors (as assessed using the WHITS-P) are experienced more positively, students report increased resilience and better wellbeing. Conversely, the correlations between the WHITS-P scales and reports of bullying were all negative and statistically significant ( p  <  0.0 5), suggesting that, when students experienced the school climate more positively, they reported fewer experiences of bullying.

Multiple regression analysis was used to determine which school climate factors predicted student outcomes. The overall regression, reported in Table  4 , was statistically significant for all three outcomes: resilience (multiple R  = 0.595, R 2  = 0.353 , p  < 0.01), wellbeing (multiple R  = 0.769, R 2  = 0.591, p  < 0.01), and bullying (multiple R  = 0.460, R 2  = 0.212, p  < 0.01). The results of multiple regression analyses revealed that all WHITS-P scales except teacher support positively and statistically significantly ( p  < 0.01) predicted student resilience; five scales (peer connectedness, reporting and seeking help, rule clarity, support for learning and school connectedness) statistically significantly (p < 0.01) and positively predicted student wellbeing; four scales (peer connectedness, reporting and seeking help, support for learning and school connectedness) statistically significantly ( p  < 0.05) and negatively predicted reports of bullying and one scale, high expectations, statistically significantly ( p  < 0.01) and positively predicted reports of bullying.

Relationships between preferred–actual congruence and outcomes

Whereas the previous analyses examined relationships between students’ lived experiences of school climate and their outcomes, this section reports relationships between the actual–preferred discrepancy for each WHITS-P scale and the student outcomes.

The results of simple correlation analyses, used to examine the bivariate relationship between the actual–preferred discrepancy and each outcome, reported in Table  4 , indicate that, without exception, the correlations were statistically significant ( p  <  0.0 1). All relationships were negative for resilience and wellbeing and positive for bullying, suggesting that, when the actual–preferred gap is smaller, students report greater resilience and wellbeing and less bullying.

Multiple regression analysis was used to evaluate the relationships between the actual–preferred discrepancy for a school climate scale and a student outcome while controlling for the effect of the other scales. The results, reported in Table  4 , suggest that the overall regression was statistically significant for all three outcomes: resilience (multiple R  = 0.431, R 2  = 0.186, p  < 0.01), wellbeing (multiple R  = 0.572, R 2  = 0.327, p  < 0.01) and reports of bullying (multiple R  = 0.406, R 2  = 0.165, p  < 0.01). Examination of the p -values and beta values suggest that, for resilience, the actual–preferred discrepancy for all WHITS-P scales, except the support for learning scale, were negative and statistically significantly ( p  < 0.05). For wellbeing, the actual–preferred discrepancy for five WHITS-P scales were negative and statistically significant ( p  < 0.01), the exceptions being reporting and seeking help and support for learning (which were nonsignificant). Finally, for reports of bullying, the actual–preferred discrepancy for five WHITS-P scales was statistically significant ( p  < 0.01) and positive; the exceptions, support for learning and high expectations, were nonsignificant.

A person-environment fit perspective is focused on the interactions between an individual and the environment and assumes that a good match between the two promotes positive outcomes. Using this premise, the study reported in this article examined whether smaller actual–preferred discrepancies promoted student resilience and wellbeing and reduced bullying.

First, we examined whether students’ views of the actual and preferred environment differed. The statistically significant t- test results and effect sizes for all but one WHITS-P scale (high expectations) suggest that students would prefer the school climate features to occur more often. These findings are consistent with research at the classroom level, which suggests that students desire a more positive environment than the one they experience (e.g., Fraser, 1982 ; Magen-Nagar & Steinberger, 2017 ).

For the exception, high expectations, there was only a slight (statistically non-significant) actual–preferred discrepancy. It is noteworthy, however, that students’ responses indicates their actual experiences exceeded their preferences. To our knowledge, few, if any, studies in the field of learning environment report discrepancies in this direction. Moos ( 1987 ) warns, however, that when the environment exceeds a person's preference, dysfunction can occur because personal characteristics (such as self-esteem) influence the interplay between personal and environmental factors. It is recommended, therefore, that future studies examine the extent to which dysfunction occurs when the environment exceeds a person’s preference and that educators seek causal explanations.

Second, the ANOVA results were interpreted to determine whether the mean responses for students in the same school were similar but different from those of students in other schools. The statistically significant results for responses to the actual version for all WHITS-P scales, suggesting the perceptions of students can be differentiated between schools, corroborate those of past studies (e.g., Johnson et al., 2007 ; Riekie & Aldridge, 2017 ). This finding makes sense given that a school's climate is influenced by a range of factors, such as interpersonal relationships, making each one unique (Tomaszewski et al., 2023 ).

The statistically significant ANOVA results for students’ responses to the preferred version for all WHITS-P scales were also notable. These findings suggest that not only is a school's climate unique, but the needs of students within a school (as reported in the preferred version) also differs between schools. From a cultural capital perspective (Davies & Rizk, 2018 ), this finding reflects the intrinsic relationship between the community in which it is situated (e.g., socio-economic demographics), the school’s organisational practices and the school culture (Tarabini et al., 2017 ). These findings support the need for school improvement efforts that are culturally responsive and consider the sociocultural context (e.g., Antrop-Gozales & De Jesus, 2006 ; McLure & Aldridge, 2022 ).

We then examined the relationships the relationships between students’ reports of resilience, wellbeing and bullying and responses to, first, the actual version of the WHITS-P and, second, the actual–preferred discrepancy. The relationships between the actual version of the WHITS-P and the three outcomes, suggest that positive school climates could promote students' resilience and wellbeing and reduce bullying. These findings corroborate those of past research that examined the influence of school climate factors on emotional wellbeing (e.g., Aldridge & McChesney, 2018 ; Aldridge et al., 2016 ; Kutsyuruba et al., 2015 ; Lester & Cross, 2015 ; Riekie & Aldridge, 2017 ), resilience (e.g., Aldridge et al., 2016 ; Cohen, 2013 ; Ebbart & Luthar, 2021 ) and reports of bullying (Aldridge et al., 2018 , 2020 ). Our findings suggest that developing a positive school climate could provide the protective factors needed to promote wellbeing and equip students to handle stressors and setbacks. Further, the negative relationships between the WHITS-P scales and students’ reports of bullying, highlight the critical role that a positive school climate plays in preventing bullying (e.g., Cohen & Frieberg, 2013 ; Low & Van Ryzin, 2014 ; Wang et al., 2013a , 2013b ).

Finally, we drew on a person-environment perspective to examine whether the degree of misfit reported by students was inversely related to their outcomes. Our findings indicate that when the actual–preferred discrepancies were smaller, student resilience and wellbeing were improved and reports of bullying reduced. These findings support Caplan’s ( 1987 ) theory of person-environment fit and earlier studies that found outcomes were improved when environmental misfits were reduced (Fraser & Fisher, 1983a , 1983b ; Moos, 1987 ). Further, it is worth noting that the correlation between students’ actual perceptions of teacher support and their outcomes was statistically non-significant, while the relationship between the actual-–preferred discrepancy in student responses to teacher support and student outcomes (resilience, wellbeing and reductions in bullying) was statistically significant. This finding suggests that including information about actual and preferred experiences could provide a more nuanced understanding of students' needs, which can be used to promote student outcomes more effectively when compared with relying on actual data alone.

Implications for schools

Given that traditional models used to guide interventions aimed at improving student outcomes often target change efforts at individual students, our findings provide important implications for schools seeking to improve outcomes across the entire school. Our findings draw attention to the interaction between students and their environment and to the interconnectedness between the context and the environment. Given the malleable nature of the school climate factors, these findings provide important implications to schools as outlined below.

Our finding, that students in different schools have different perceptions and preferences, support the premise that students are embedded within larger social systems and acknowledges that multiple levels of influence exist (Bronfenbrenner, 1979 ). These findings suggest that schools would benefit from examining the interconnections between students and larger social systems to determine how changes at different system levels can support their needs. This information could help educators to select and shape the school climate for person–environment matching (Moos, 1996 ).

Our results suggest that examining ways to reduce actual–preferred discrepancy could improve student outcomes. For example, one of our findings suggest that, when students perceived their teachers as friendly and caring as they would like them to be (e.g., the actual–preferred discrepancy was reduced), they were more resilient, had better wellbeing and experienced less bullying. Given that high-quality relationships are typically associated with positive student outcomes, it would make sense, in this case, for schools to consider ways to foster interpersonal rapport and relational trust between teachers and their students.

Our findings also support the usefulness of a socio-ecological approach to promoting student outcomes. Using a social-ecological approach recognises the social variables (e.g., teacher or peer support) and the multiple levels of influence on student development and behaviour. Although it may not be practical to influence all aspects of the environment, considering students as part of an ecosystem may help focus school improvement efforts. For example, students are influenced by the level of teacher support (beliefs about whether teachers value them) at both the microsystem and macrosystem levels. Teachers contribute to the school climate at the microsystem level (in the way they interact with individuals e.g., by being caring, friendly and dependable), at the mesosystem levels (e.g., through the way they interact, involve or engage parents in the educational process) and at the macrosystem level (e.g., through the norms and rules that guide student social behaviour and explicit messages and rules regarding interactions between peers (see, for example, Patrick et al., 2001 ). Although the benefits of using a social-ecological perspective to promote outcomes and address inequities have been widely reported in healthcare settings (see for example, Cramer & Kapusta, 2017 ; Baron et al., 2014 ; Golden et al., 2015 ; Goodwin et al., 2022 ), similar efforts appear to be limited in school improvement literature. However, our findings suggest that, given the importance of the school context, using a social-ecological approach to guide school improvement interventions could be beneficial.  

Finally, for schools using actual–preferred discrepancies to guide improvement efforts it could be worth  considering the results in light of Eccles and Midgley’s ( 1989 ) stage-environment fit perspective which suggests that, when the environment fit caters to students' developmental needs, individual functioning is maximised (Midgley et al., 2014 ). Drawing on a stage-environment fit perspective could encourage educators to examine whether misfits could be addressed by making changes to ensure that the environment is suited to the students’s developmental needs. Such changes could support a range of adaptive changes, such as personality development (Roberts & Robins, 2004 ) and increased motivation and academic performance (Eccles et al., 1991 ).

Recognition that the individual and the environment are not isolated entities but, rather, each shape and are shaped by the other supports possibilities of a schoolwide focus on improving the school climate and reducing actual–preferred differences to improve student outcomes.

However, despite the mounting research evidence supporting the critical role of school climate, as well as an increased demand for its measurement, schools are more likely to rely on achievement data or attendance rates to inform strategic decisions (Cohen et al., 2009 ). Our findings not only corroborate past research that suggests a focus on improving school climate will lead to improved outcomes, they also support the possibility of examining whether misfits occur, to guide decisions about school improvement efforts. We posit that future school improvement efforts would benefit from approaches that move away from a focus on individual-level solutions to ones that draw on a social-ecological perspective, ensuring a multi-level perspective that considers the school's context, to improve school climate and reduce actual–preferred discrepancies. 

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Fatal bullying rampant despite laws

Thursday, 30 May 2024

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Cases of fatal bullying continue to haunt schools here despite a regulation issued by the Education, Culture, Research and Technology Ministry last year aimed at preventing violence at educational institutions. A 15-year-old student at Islamic junior high school Madrasah Tsanawiyah in Situbondo regency, East Java, died recently after he was beaten by nine other students.

The assault left the victim in a coma. He was hospitalised for a week before passing away last Sunday.

Just a few days prior, Aldelia Rahma, a 10-year-old elementary student from Padang Pariaman Regency in West Sumatra, died after her classmate set her on fire a few months ago.

Aldelia and her classmates were ordered by teachers to clean up their classroom and to burn trash they collected in the school’s backyard.

She was standing next to the burning trash pile when a male student, identified only as R, suddenly doused her with gasoline, and she immediately caught fire.

The girl suffered burn wounds on 35% of her body and underwent four different surgeries before eventually succumbing to her injuries last Friday.

According to the victim’s family, the perpetrator had bullied Aldelia for some time before the fire incident took place, including by kicking and punching her face as well as hitting her head.

However, when Aldelia reported the bullying to a teacher, she was blamed instead for “playing with male students”.

According to a 2018 survey by International Students Assess-ment, 41% of Indonesian students reported being victims of bullying at least a few times a month.

The figure is almost twice as much as the average bullying rate in the Organisation for Economic Co-operation and Development member countries, which stands at 23%.

Amid the rising trend of violence in schools, the government issued in August an anti-bullying regulation, which among its provisions mandated all education units to form violence prevention and handling teams to protect students.

However, education expert Anggi Afriansyah of the National Research and Innovation Agency said that the implementation of the ministerial regulation remains lacklustre. — The Jakarta Post/ANN

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Facility for Rare Isotope Beams

At michigan state university, new frib precision measurement program advances understanding of proton halos, theoretical physicists and experimentalists work together to measure the mass of a rare isotope expected to form a rare proton halo, publishing the first results from frib’s precision measurement program. .

In May 2022, the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU), launched its precision measurement program. Staff from FRIB’s  Low Energy Beam and Ion Trap (LEBIT) facility take high-energy, rare-isotope beams generated at FRIB and cool them to a lower energy state. Afterward, the researchers measure specific particles’ masses at high precision. 

The LEBIT team, led by  Ryan Ringle , adjunct professor of physics at FRIB and in the MSU Department of Physics and Astronomy and senior scientist at FRIB, and  Georg Bollen , University Distinguished Professor of Physics and FRIB Experimental Systems Division director, recently published a research paper that used the facility to take a step in verifying the mass of aluminum-22. Researchers think this exotic isotope demonstrates a rare but interesting property—specifically, that the nucleus is surrounded by a “halo” of protons that loosely orbit the nucleus. This halo structure reveals distinctive physical properties during its fleeting existence.

“This program requires a lot of extra beam preparation to perform experiments, and this is the first measurement in FRIB’s science program,” Ringle said. “This measurement could not have been done in a reasonable time at FRIB’s predecessor, the National Superconducting Cyclotron Laboratory, and it highlights our facility’s potential moving forward. Considering this was done with one-eightieth of FRIB’s power specification, this was like a warm-up before exercising.” 

The team published its results in  Physical Review Letters (“ Precision Mass Measurement of the Proton Dripline Halo Candidate 22 Al”).

Capturing elusive proton halos

While most atoms have electrons tightly orbiting the nucleus, protons and neutrons are part of the nucleus itself. However, when atoms encounter many of the same charged particles under certain conditions, they can create halos that orbit the nucleus beyond the pull of the strong nuclear force—the force that would normally keep these particles within the nucleus. While all halo structures are rare fleeting phenomena, neutrons are usually observed as halo particles. A nucleus’s positive charge usually repels protons’ positive charges, meaning that halos made of protons are even rarer. Measurements on nearby isotopes suggested that aluminum-22 might be an isotope that could form a proton halo, but researchers needed to verify this directly in other experiments. 

To achieve this, the team creates a high-energy isotope beam of aluminum-22 using a process called “projectile fragmentation” at FRIB. The researchers create a beam from a heavy, stable atomic nucleus of a given element—in this case, an isotope of argon—then accelerate the beam to half the speed of light. The beam then hits a target with these ultra-fast-moving particle projectiles. This violent collision creates rare, short-lived isotopes that the researchers can shepherd into an instrument to filter out the particle of interest. They then lower the temperature to slow them down into a uniform beam and measure particle mass accurately. 

While the team was able to accurately measure the mass of aluminum-22, it is only part of verifying the isotope’s proton halo structure. The LEBIT researchers’ colleagues in the  Beam Cooler and Laser Spectroscopy (BECOLA) facility at FRIB now plan to take the next step in verifying the proton halo by measuring the charge radius—the distribution of protons around the nucleus—as well as how much the nucleus may be deformed from its traditional, spherical shape. Taken together, these measurements can unequivocally confirm the existence of a proton halo structure around aluminum-22. 

Ringle pointed out that the collaboration between theoretical physicists and experimentalists at FRIB plays an essential role for research like determining the existence of a proton halo around a rare isotope such as aluminum-22. 

FRIB provides research opportunities to graduate students 

Ringle credited students on the team for playing a key role in advancing this research. One of LEBIT’s graduate students, Scott Campbell, took this project on as part of his dissertation. 

“He really took charge of running this experiment from start to finish,” Ringle said. “The students who work with us really benefit from the wealth of expertise we have at this facility. Nowhere else is a facility like this located in the middle of a university campus. It allows students to come in for an hour or two between their classes or before they go home for the day. They can work at the lab part-time and easily pair that with taking classes. But our facility gets benefit as well; we have increased access to talented, motivated students.” 

Campbell studied physics and computer science at Gonzaga University as an undergraduate. He was excited by the prospect of coming to MSU for graduate school in large part to FRIB being on campus and being a major resource for physics students. “I was very excited by the prospect of doing for nuclear physics research at MSU, especially with FRIB ramping up during my studies,” he said. “We have access to these great facilities and a great community, and we get to participate in groundbreaking advances in nuclear science.” 

Campbell also noted that FRIB not only offers world-class facilities, but also networking opportunities and mentors like Ringle. “We are surrounded by colleagues who are interested in your research and want to help you push science forward,” he said.

Eric Gedenk is a freelance science writer.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

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Bullying among High School Students

Delia nursel tÜrkmen.

a Uludağ University, Medical Faculty, Department of Forensic Medicine, Council of Forensic Medicine, Bursa Morgue Department, Bursa, Turkey

Mihai Halis DOKGÖZ

Suzana semra akgÖz.

c Çanakkale 18 Mart University, Medical Faculty, Department of Biostatistics, Çanakkale, Turkey

Bogdan Nicolae Bülent EREN

d Council of Forensic Medicine of Turkey, Bursa Morgue Department, Bursa, Turkey

Horatiu Pınar VURAL

e Uludag University, Medical Faculty, Department of Child and Adolescent Psychiatry, Bursa,Turkey

Horatiu Oğuz POLAT

f Case Western Reserve University, Mandel School of Social Studies Applied Unıt, Begun Violence Prevention and Research Center, Cleveland-Ohio, USA

Objective: The main aim of this research is to investigate the prevalence of bullying behaviour, its victims and the types of bullying and places of bullying among 14-17 year-old adolescents in a sample of school children in Bursa, Turkey.

Methodology: A cross-sectional survey questionnaire was conducted among class 1 and class 2 high school students for identification bullying.

Results: Majority (96.7%) of the students were involved in bullying behaviours as aggressors or victims. For a male student, the likelihood of being involved in violent behaviours was detected to be nearly 8.4 times higher when compared with a female student.

Conclusion: a multidisciplinary approach involving affected children, their parents, school personnel, media, non-govermental organizations, and security units is required to achieve an effective approach for the prevention of violence targeting children in schools as victims and/or perpetrators.

INTRODUCTION

World Health Organization defines bullying as a threat or physical use of force, aiming at the individual, another person, a specific community or group which can result in injury, death, physical damage, some development disorders or deficiency. The concept of bullying at school is not new; however it has been increasing in recent years. There is a crucial increase in studies conducted and the number of news on bullying at school in mass media ( 1 - 3 ). Bullying in schools is an issue that continues to receive attention from researchers, educators, parents, and students. Despite the common assumption that bullying is a normal part of childhood and encompasses minor teasing and harassment ( 4 ), researchers increasingly find that bullying is a problem that can be detrimental to students' well-being ( 5 - 7 ). This report focuses not only on the prevalence of bullying, but also on those subsets of students who reported being the victims of direct, and indirect bullying, and both of them. Different types of bullying may affect different groups of students, occur in different types of schools, or affect student behavior in different ways. These distinctions allow readers to differentiate between students who were either physically (directly) or socially (indirectly) bullied, and also to identify those students who were bullied both physically and socially ( 4 ). Additional analysis describes the characteristics of students affected by these types of behavior and the characteristics of schools in which these behaviors occur. Because of prior research that suggests victims of bullying may resort to aggressive behaviors in response to being bullied, the extent to which reports of bullying are related to victim behaviors such as weapon carrying, physical fights, fear, and avoidance are explored. Finally, for educators, the academic success of students is of paramount importance. For this reason, self-reported academic performance of bullied students is also examined ( 5 , 8 ). The main aim of this research is to investigate the prevalence of bullying behaviour, its victims and the types of bullying and places of bullying among 14-17 year-old adolescents in a sample of school children in Bursa, Turkey. Bullying is a psychological and pedagogical problem connected with public health. It must be solved by various professionals immediately. ❑

METHODOLOGY

A cross-sectional survey questionnaire was conducted among class 1 and class 2 high school students for identification bullying. Research was planned as sectional descriptive study. All class 1 and class 2 high school students from Bursa provincial center were included in the study. The questionnaire form was created by the experts after literature survey. The questionnaire form prepared consisted of 2 sections. The first section encompassed 7 items concerning sociodemographic characteristics of the family, and the second section had 37 items related to the determination of violence among peers. The questionnaire was administered to students in collaboration with school counselors. In guidance of school counselors, after a brief nondirective description, questionnaire was administered to students wishing to participate as volunteers in the study. Total 6127 students agreed to participate in the study. The questionnaire was performed in resting hours under the supervision of school counselors in classrooms by students themselves. For statistical analysis, SPSS forWindows 13.0 was used. Variables have been presented on the basis of average and standard deviation and frequency (%). Pearson chi-square TEST, Student's t-test, Spearman's correlation analysis, univariate and multivariate logistic regression analyses were used. P-value < 0.05 was considered significant for all tests. ❑

1. Sociodemographic Characteristics

Sociodemographic characteristics, and data related to the students participating in the questionnaire survey were presented in Table ​ Table1 1 .

Sociodemographic characteristics of students participating in the questionnaire surveys.

A total of 6127 participants consisted of 2879 (47%) female, and 3248 (53%) male students. Mean ages of the participants (15.68 ± 0.72 years; range: 14-17 years), female (15.65 ± 0.76 years), and male students (15.71 ± 0.69 years) were also determined. Among participants, mothers of 24 (0.4 %), fathers of 168 (2.8%), and both parents of 5 (0.1%) students were deceased. Parents of 167 (2.8%) students were living apart. Students' mothers (n = 2908, 47.6%) and fathers' education (n = 2046, 33.6%) was primary school in the most of the cases and there was correlation between mothers and fathers' educational levels. (Spearman's correlation cefficient rho = 0.571, p < 0.001). Mothers of the majority of the students (81.1%; n = 4972) were housewives, and fathers of 17% (n = 1040) of the students were jobless. Mothers of 922 students (15%) were housewives, while their fathers were jobless as reported by the students themselves.

2. Students involved in Violence as Aggressors and Victims

Majority (96.7%; n = 5926) of the students were involved in bullying behaviours as aggressors or victims. Most (95.8%; n = 5677) of the total of 5926 students involved in bullying behaviours demonstrated physical aggressiveness (95.8%; n = 5677), emotional harassment (48.5%; n = 2875), and verbal assault (25.3%; n = 1499). While victims of these violent acts were subjected to physical (41.2 %; n = 2441), emotional (64.1%; n = 3801), and verbal abuse (47.3%; n = 2805) (Figure ​ (Figure1). 1 ). The probability of a male student being involved in violence was 8.4 times more frequent relative to a female student (95% of Confidence Interval = 5.5-12.8). Students whose mothers were businesswomen participated in violent acts 1.6-fold more frequently than children of housewives (95% of Confidence Interval = 1.05-2.43).

a. Aggressors

The distribution of types of aggressive behaviour of the students according to gender, and age groups were presented in Figure ​ Figure2. 2 . When compared with the female students, male students exerted physical violence, emotional assault or verbal abuse more frequently (8.1, 2.6, and 3.1 times more often respectively; p < 0.001 for all types). Frequency of physical, emotional, and verbal violence increased with age (p < 0.001). When compared with a student aged 14 years, a 17-year old student resorted more frequently to physical (almost 2.2 fold increase; p = 0.01), emotional (1.6 fold increase; p = 0.01), and verbal (almost 2 fold increase; p = 0.007) assaults (Table ​ (Table2 2 ).

Results of multivariate logistic regression model of the association between three types of aggressors and socio-demographic features.

R - Reference category; NS - No significant

Verbal abuse was observed more frequently (34.9%) among students with university graduate mothers. The probability of verbal violence was 1.5-1.9 times higher among shoolchildren of university graduate mothers when compared with the students whose mothers were of lower educational levels (p < 0.001).

The possibility of emotional bullying exerted by a student whose father working in private/public service sector (employees in hotels, retailers, restaurants, night-clubs, bars, patisseries, movie theaters, beauty salons, casinos, cleaners, etc) was nearly 32.3% lower than a student whose father was employed in other sectors (p = 0.007).

Most (89%) of the children who didn't resort to brute force were not found to be the perpetrators of violence in the neighbourhood. Fifty percent of the children who were frequently or always bullying in school were also detected to exert violence in the neighbourhood, (p < 0.001) (Figure ​ (Figure3). 3 ). Five percent of the students (n = 305) indicated that they were carrying sharp, and cutting instruments like pocket knives, and knives for the purpose of physical assault. Eight percent (n = 253) of the boys, and 2.2% of the girls carried cutting-penetrating instruments like knives, and pocket knives for the purpose of physical assault (p < 0.001).

The distribution of types of victimization related to physical, emotional, and verbal infliction based on gender, and age of the students was presented in Figure ​ Figure4. 4 . A male student was more frequently subjected to physical, emotional, and verbal violence when compared with a female student (almost 2, 1.4, and 2 fold increase respectively; p < 0.001). The possibility of being a victim of physical and verbal bullying decreased with age (p < 0.05). A 15-year-old student suffered more frequently from physical (almost 1.3 – fold increase: p = 0.004), and verbal (almost 1.2 – fold increase: p = 0.035) bullying compared to a 17 year-old student (Table ​ (Table3 3 ).

Results of multivariate logistic regression model of the association between three types of victimhood and socio-demographic features.

The probability of being a victim of violence was nearly 23% times lower for a student having a lycee graduate mother rather than a schoolchild of an illiterate mother (p < 0.05). A schoolchild of an employed mother was almost 1.2 times more likely to suffer from emotional harassment than a child of a housewife (p = 0.001).

Illiterate fathers of 54.9% of schoolaged children were unemployed, while jobless fathers of 30% of the students had dropped out during primary education. Schoolchild of an unemployed father was almost 1.2 times more prone to be victimized emotionally relative to a child of an employed father (p < 0.05).

Both Victimized and Aggresive students

A 41.7% of the physically aggressive students were also victims of physical bullying, while 79.9% of emotionally offensive students were also suffered from emotional harassment. Still 80.7% of the students who exerted verbal violence also suffered from verbal abuse (Figure ​ (Figure5). 5 ). As compared with a female student, male students were almost 2,2 times more likely to be both victim and perpetrator of physical violence (95% Confidence Interval = 1.9-2.4), 2,3 times more likely to be both victim and perpetrator of emotional assault (95% Confidence Interval = 2.1-2.6) and 3 times more likely to be both victim and perpetrator of verbal abuse (95% Confidence Interval = 2.5-3.4). As compared with a 17-year-old student, a 15-year old student was almost 1.3 times more likely to be both victim, and perpetrator of physical violence (95% Confidence Interval = 1.1-1.6). As observed in our investigation, the probability of being both victims and perpetrators of physical aggression among schoolchildren of the mothers with a lycée (35%) or university (37.1%) education was at a minimal level. A student raised by a mother graduated from a lycée was 30.4% less likely to be both executers, and victims of physical violence relative to those of illiterate mothers (p < 0.05). ❑

Bullying in schools is an issue that continues to receive attention from researchers, educators, parents, and students ( 4 ). This study focuses not only on the prevalence of bullying, but also on those subsets of students who reported being the victims of physical, verbal and/or emotional bullying.

Sociodemographic Characteristics

Our study population consisted of male students with a mean age of 15.68 ± 0.72 years (range: 14-17 years). As for sociodemographic properties, lower educational level, possesion of a job of inferior quality have been revealed to be important factors in the exertion of bullying behaviours (Table ​ (Table1). 1 ). Prevalence of being both aggressors, and victims was reportedly higher among students aged between 8-16 years. In a study conducted on 62 adolescents aged 16 years, 15% of the male, and 7% of the female students demonstrated violent behaviours. Again, 72 adolescents (12%), 13% of boys, and 12% of the girls were detected to be victims of violence, while 13 adolescents were both perpetrators, and victims of violence. Persistency of being both perpetrators, and victims of violence was investigated among adolescents aged between 8-16 years, and 18 of 38 girls at 16, and 27 of 30 girls at 8 years of age were detected to be victims of violence. Educational levels, socioeconomic status, composition of the families, and changes in the marital status (divorce, re-marriage etc) were observed for a period of 8 years, and a correlation between being a victim of violence at 8 years of age, and infliction of violence at age 16 could not be detected ( 9 ). In compliance with our study, studies performed in Turkey have emphasized that demonstration of violence was encountered mostly among adolescents aged 15-16 years ( 2 , 10 ).

Students involved in violence as aggressors or victims

Majority (99.2%; n = 3223) of male, and female (93.9%; n = 2703) students were detected to be involved in one form of bullying behaviours as aggressors or victims at one time of their lives. For a male student, the likelihood of being involved in violent behaviours was detected to be nearly 8.4 times higher when compared with a female student (p < 0.001). A statistically significant correlation was not found between the involvement in violence, and age of the student, familial unity, level of education, and occupation of the parents (p > 0.05). A total of 5926 students involved in violence, demonstrated physical (95.8%; n = 5667), emotional (48.5%; n = 2875), and verbal (25.3%; n = 1499) bullying behaviours. The students involved in violence were also suffered from physical (41.2%; n = 2441), emotional (64.1%; n = 3801), and verbal (47.3%; n = 2805) bullying behaviours (Figure ​ (Figure1). 1 ). A survey conducted in 1994, 1998, and 2002 in Lithuania detected that one in every 3 children were the victims of various types of violence exerted regularly by their peers. (During all three surveys conducted in 1994, 1998 and 2002, about one in three students reported that they had been a victim of regular bullying. A higher percentage of boys (36%) reported being bullied than girls (32%, p < 0.05). This study demonstrated that students living in rural areas were 1.5 times more frequently bullied than those in the cities, and 40% the boys and 28% of the girls inflicted violence on their peers. When incidence rates of bullying in different countries were examined, the highest rate was detected in Lithuania, followed by Austria, Swiss, Germany, and Russia in decreasing frequency ( 11 - 14 ).

The incidence of physical, emotional or verbal violence by a male student was found to be higher (8.1, 2.6, and 3.1 times more frequent, respectively) in comparison with a female student (p < 0.001). Usage of physical, emotional, and verbal violence increased with age (p < 0.001). When compared with a student aged 14 years, a 17-year old student resorted more frequently to physical (almost 2.2 – fold increase; p = 0.01), emotional (1.6 fold increase; p = 0.01), and verbal (almost 2 fold increase; p = 0.007) assaults.

A concordance was detected between lower educational level of the family, and verbal, physical, and emotional aggression. Students with employed parents were found to be more prone to resort to physical bullying. In a study, 5% (n = 305) of the students reported that they had carried cutting, and penetrating instruments such as pocket knives, and knives with the intention of bullying. An 8% (n = 253) of the boys, and 2.2% (n = 52) of the girls using physical violence carried cutting, and penetrating instruments such as pocket knives, and knives for the intention of bullying (p < 0.001). A survey among 500 children detected evidence of bullying in 31.4% of the cases. In schools for girls, the incidence of bullying was detected to be 18%, while it was 38.2% in coeducational mixed schools. The incidence of bullying increased with age, and higher grades. Bullying was mostly encountered in the form of verbal violence such as nicknaming, followed by abusive language, rumoring, insult, and isolation Infliction of physical harm was seen at a rate of 16 percent. Feeling oneself badly, desiring to be left alone, and tearing his/her clothes etc. were also observed. School phobia, vomiting, and sleeping disorders were seen in these children. Frequently, headache was seen to be a cardinal symptom of girls, and boys subjected to bullying behaviours ( 15 ).

Statistically significant correlations were seen between types of physical, emotional, and verbal bullying and gender, and age of the students. The likelihood of being a victim of physical, emotional, and verbal bullying was higher among male students rather than female students (almost 2, 1.4, and 2 fold increase respectively; p < 0.001). A study demonstrated that physical and verbal victimization decreases with age (p < 0.05). Minimal degree of physical victimization was observed among students whose mothers were lycée (36.3%), or university (38.8%) graduates. The student whose parents had a lower level of education carries a higher potential of being a victim of bullying. In the study group where male students with a mean age of 13 consisted 50 % of the study population, cases were attending primary (40%), secondary (26%) , and higher levels of (34%) education These students were subjected to violence at least once for a duration of one year. This incidence was 3 times higher than those found in other studies. Male students were more frequently involved in bullying behaviours. In higher education male students were more frequently involved in bullying behaviours, while in primary, and secondary education there was no difference between genders. The frequency of bullying behaviours decreased in higher grades. Bullying was more frequently observed in families with separated parents or in the absence of two biologic parents ( 16 ).

Students both as victims and perpetrators of violence

Many students were detected to be both victims, and perpetrators of physical (41.7%), emotional (79.9%), and verbal (80.7%) violence (Figure 6).

Compared with a female student, the probability of being both perpetrator, and victim of a physical, emotional, and verbal bullying for a male student was increased by 2.2 (p < 0.01), 2.3 (p < 0.001) and 2.3 (p < 0.001) times, respectively. The incidence of being a victim decreased with age. Among students whose parents were lycée (35%) or university (37.1%) graduates, physical aggressiveness, and victimhood have been observedly at a minimal level. Compared with a schoolchild of an unemployed father, and a housewife mother, the child of employed parents was 1.6-fold more likely to be both victim, and a perpetrator of a verbal bullying (p = 0.001). According to investigations conducted in Italy, boys were resorting to bullying more frequently than girls, while both genders were becoming victims of violence with a similar incidence. Boys were more likely to inflict direct physical aggression with the intent of causing physical harm, whereas girls were more likely to inflict indirect forms of aggression with the intent of causing psychological harm. However, there were no significant gender differences in direct verbal aggression. Researches have indicated that bullying is often exerted in the classrooms, but it is also encountered in other parts of the school, like corridors, and rest rooms, as well. Overall, 56.7% of all students had never been bullied in the last 3 months, 13.9% were bullied once or twice, 14.7% sometimes and 14.7% once a week or more often. Girls tended to be victimized more than boys; 34_5% of girls, and 24_8% of boys, had been victimized sometimes or more often. Boys were significantly more likely to suffer from various types of direct bullying, whereas girls were slightly more likely to suffer from indirect forms of bullying (e.g. being rejected, rumours spread about them). Significant differences emerged as for types of direct bullying, especially for being threatened and marginally for being physically hurt. There were no significant gender differences between direct verbal and indirect bullying; boys were almost as likely as girls to suffer from indirect bullying. An 18.5 % of the girls, and 20.4 % of the boys were subjected to bullying behaviours exerted by both girls, and boys. Over half of all students had bullied others, and nearly half had been bullied in Italy. Boys bullied more than girls, and girls were somewhat more likely than boys to be bullied sometimes or more often ( 17 ).

In conclusion, a multidisciplinary approach involving affected children, their parents, school personnel, media, non-govermental organizations, and security units is required to achieve an effective approach for the prevention of violence targeting children in schools as victims and/or perpetrators. In consideration of the impact of child's familial, and environmental cultural factors, and school ambiance on violence as well, educational efforts should be exerted both to eliminate potential adversities and also prevent bullying behaviours in schools.

CONFLICT OF INTEREST

none declared.

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