a case study on the victims of bullying in school

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Survivors of School Bullying: A Collective Case Study

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Octavio Ramirez, Survivors of School Bullying: A Collective Case Study, Children & Schools , Volume 35, Issue 2, April 2013, Pages 93–99, https://doi.org/10.1093/cs/cdt001

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This article explores the coping strategies of five junior-high school students with a history of peer victimization and how those strategies help them manage the effects of bullying. The data were collected using observations, interviews, and a review of school records. The data were analyzed using categorical aggregation, direct interpretation, constant comparison, and identification of patterns. On analysis, the following categories emerged from the data: identification of supportive systems, in-class strategies, premonition and environmental analysis, thought cessation and redirection, and masking. These categories were amalgamated into two general patterns: preventive and reactive strategies. The results of the study show that although the strategies helped participants to cope with the immediate effects of bullying, they did not exempt participants from the psychological and emotional implications of peer victimization.

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Bullying in schools: the power of bullies and the plight of victims

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• 1 Department of Psychology.
• PMID: 23937767
• DOI: 10.1146/annurev-psych-010213-115030

Bullying is a pervasive problem affecting school-age children. Reviewing the latest findings on bullying perpetration and victimization, we highlight the social dominance function of bullying, the inflated self-views of bullies, and the effects of their behaviors on victims. Illuminating the plight of the victim, we review evidence on the cyclical processes between the risk factors and consequences of victimization and the mechanisms that can account for elevated emotional distress and health problems. Placing bullying in context, we consider the unique features of electronic communication that give rise to cyberbullying and the specific characteristics of schools that affect the rates and consequences of victimization. We then offer a critique of the main intervention approaches designed to reduce school bullying and its harmful effects. Finally, we discuss future directions that underscore the need to consider victimization a social stigma, conduct longitudinal research on protective factors, identify school context factors that shape the experience of victimization, and take a more nuanced approach to school-based interventions.

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Dealing with a schoolyard bully: a case study, additional details, no download available, availability, related topics.

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A case study of bullying: Ex-Freeman High School student says peer harassed him for years; alleged bully denies it

Dana Condrey’s son didn’t want to leave his high school, especially not because of a bully.

But in September, the 16-year-old junior transferred to Ferris High School, after what the family describes as years of being taunted and beat up by a fellow Freeman High School student.

“It just got to the point where (he) just said, ‘I’m done. I want out,’ ” Condrey said.

The bullying started in the fifth grade. Five years later, in June 2015, Condrey’s son was thrown to the ground during gym class at Freeman by a fellow student. The fall blackened his eye and burst his eardrum, according to a police record of the incident.

Both boys were freshmen and the violence was captured on video and investigated by police. No charges were filed.

That was the most egregious and visible act in a long string of harassment and intimidation, according to the boy and his parents.

They obtained an anti-harassment order from a judge in October 2015 after a hearing where testimony and documents were submitted.

However, the boy accused of the harassment and his parents have been fighting back. Their attorney, Julie Watts, found the order troubling. So far those efforts, including a February ruling by the Washington State Court of Appeals, have failed.

“Anti-harassment orders have criminal penalties if they are violated, even accidentally, and having one on your record can prevent you from getting future employment or future housing,” Watts said in an email in response to questions about the case.

For instance, Watts said the order allows a kid to “sit down at the restrained kid’s lunch table so that he has to leave or can’t eat with his friends without being charged with a crime.”

However, Condrey, the mother of the boy thrown to the ground, said this is not a valid concern, since her son transferred to Ferris in September.

Robert Cossey, the attorney for Condrey and her son, said the family didn’t want to go to court, and tried multiple times to resolve the issue informally.

“It was the last resort,” Cossey said. “My clients didn’t have a lot of money. They didn’t want to hire me. They didn’t want to go through this process.”

In court documents, the boy who claims he was bullied wrote that he’d asked teachers and administrators to put a stop to the harassment numerous times.

“I have tried to do the right thing for many years but it hasn’t made it stop,” he wrote in a statement to the court.

The accused bully and his family claim the two teenagers were friends and that the incident in the gym was “simply an accident.”

“I have never physically threatened him or harmed him,” the boy stated in written testimony to the court.

His father is a member of the Freeman School Board and hired a private investigator to probe the claims against his son.

According to the private investigator’s interview with staff and students, no one witnessed the alleged bullying and harassment prior to the gym incident. Several of the alleged bully’s football teammates also wrote letters in support of him.

However, an email exchange from 2011 documents an incident in which the alleged bully shoved the other child into a garbage can.

In that email, sent to a school staff member, the bullied boy’s father writes, “We can deal with a little childish play amongst boys … but we are really concerned that one day the pushing on ice into a garbage can is going to result in him hitting his head, (or) him getting really hurt by getting punched in the lower back.”

The alleged victim’s family claimed they tried multiple times to resolve the issues informally. However, the alleged bully’s family said they received no such communications, according to court documents.

In 2013, Condrey, the alleged victim’s mother, sent an email to a Freeman staff member claiming her son had “been punched, tripped, kicked, wrestled to the ground in the parking lot, spit on, pulled out of his chair, and hit in the head with a book bag” by the alleged bully.

That email was subsequently forwarded to the alleged bully’s father’s official Freeman School District email address, according to court documents.

The protection order allows the alleged bully to graduate from Freeman. However, he must stay 20 feet away from the alleged victim and may not speak to him.

In the appeals, the alleged bully challenged the validity of the anti-harassment order, claiming there wasn’t sufficient evidence, that the investigation wasn’t sufficient and that the incident in the gym was not indicative of a pattern.

Watts argued the anti-harassment order is not intended to be used to resolve what state code calls “schoolyard scuffles.”

However, the appellate judges upheld the October 2015 decision, claiming that by virtue of the police investigating the gym incident it had become more than a school yard scuffle.

“From these facts, it was reasonable for the trial court to conclude that (he) would likely resume harassment … as he had before, if the order did not extend through the end of high school,” the appellate court wrote.

Condrey said her son is shocked at the difference in school cultures between Ferris and Freeman.

“It was normal, it was part of the day,” she said of bullying. “And now he’s at Ferris and he never sees any of that, it’s not tolerated.”

Editors note: This story has been updated to include a correction that the case was not tried by a jury.

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How teachers deal with cases of bullying at school: what victims say.

1. Introduction:

1.1. the nature of interventions in cases of school bullying, 1.2. victim-reported experiences and effective teacher action, 1.3. severity, 1.4. bullying by groups, 1.5. gender and age, 1.6. aim and hypotheses.

• The aim was to describe what victimized students believed the school did after they sought help from a teacher.
• the success of the intervention, as reported by students, was inversely related to the severity of the reported negative emotional impact of the bullying;
• the greater the reported frequency with which the bullying was seen to be perpetrated by a group of students, the less successful the intervention would be;
• interventions with younger students would be associated with more positive outcomes.

2.1. Ethics

2.2. procedure, 2.3. sample, 3. measures, 3.1. frequency of being bullied, 3.2. severity of the bullying, 3.3. effectiveness of the intervention, 3.4. victims’ perceptions of actions taken by the school after requesting help, 3.5. data analysis, 3.6. demographics, 4.1. reported frequencies of bullying, 4.2. reported teacher actions, 4.3. reported outcomes for bullying following interventions in cases according to gender and age group, 4.4. reported emotional impact and reported frequency of being bullied by (i) an individual and (ii) a group in relation to intervention outcomes, 5. discussion, 5.1. implications for interventions in cases of bullying, 5.2. strengths and limitations, 6. conclusions, conflicts of interest.

• Cornell, D.; Limber, S.P. Law and Policy on the concept of bullying at school. Am. Psychol. 2015 , 70 , 333–343. [ Google Scholar ] [ CrossRef ]
• Thompson, F.; Smith, P.K. The Use and Effectiveness of Anti-Bullying Strategies in Schools ; Research Report, DFE-RR098; Department for Education: London, UK, 2011. [ Google Scholar ]
• Rigby, K.; Johnson, K. The Prevalence and Effectiveness of Anti-Bullying Strategies Employed in Australian Schools ; University of South Australia: Adelaide, Australia, 2016. [ Google Scholar ]
• Sherer, Y.C.; Nickerson, A.B. Anti-bullying practices in American schools: Perspectives of school psychologists. Psychol. Sch. 2010 , 47 , 217–229. [ Google Scholar ] [ CrossRef ]
• Smith, P.K.; Sharp, S. School Bullying: Insights and Perspectives ; Routledge: London, UK, 1994. [ Google Scholar ]
• Olweus, D. Bullying at School: What We Know and What We Can Do ; Blackwell: Oxford, UK, 1993. [ Google Scholar ]
• UNESCO. School Bullying and Violence: Global Status, Trends, Drivers and Consequences ; United Nations Educational, Scientific and Cultural Organization, UNESCO Publication: Paris, France, 2018. [ Google Scholar ]
• Smith, B.H.; Low, S. The role of social-emotional learning in bullying prevention. Theory Pract. 2013 , 52 , 280–287. [ Google Scholar ] [ CrossRef ]
• Divecha, D.; Brackett, M. Rethinking School-Based Bullying Prevention through the Lens of Social and Emotional Learning: A Bioecological Perspective. Int. J. Bullying Prev. 2019 . [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Rigby, K. School perspectives on bullying and preventive strategies: An exploratory study. Aust. J. Educ. 2017 , 24 , 24–39. [ Google Scholar ] [ CrossRef ]
• Garandeau, C.F.; Poskiparta, E.; Salmivalli, C. Tackling acute cases of school bullying in the KiVa anti-bullying program: A comparison of two approaches. J. Abnorm. Child Psychol. 2014 , 42 , 981–991. [ Google Scholar ] [ CrossRef ]
• Shu, S.; Smith, P.K. What good schools can do about bullying: Findings from a survey in English schools after a decade of research and action. Childhood 2000 , 7 , 193–212. [ Google Scholar ]
• Fekkes, M.; Pijpers, F.I.M.; Verloove-Vanhorick, S.P. Bullying: Who does what, when, and where? Involvement of children, teachers, and parents in bullying behaviour. Health Educ. Res. 2005 , 20 , 81–91. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Davis, S.; Nixon, C. What students say about bullying. Educ. Leadersh. 2011 , 69 , 18–23. [ Google Scholar ]
• Rigby, K. Manual for the Peer Relations Questionnaire (PRQ) ; Professional Reading Guide: Point Lonsdale, Australia, 1998. [ Google Scholar ]
• Rigby, K.; Barnes, A. To tell or not to tell: The victimized student’s dilemma. Youth Stud. Aust. 2002 , 21 , 33–36. [ Google Scholar ]
• Rigby, K.; Smith, P.K. Is school bullying really on the rise? Soc. Psychol. Educ. 2011 , 14 , 441–455. [ Google Scholar ] [ CrossRef ]
• Wachs, S.; Bilz, L.; Niproschke, S.; Schubarth, W. Bullying Intervention in Schools: A Multilevel Analysis of Teachers’ Success in Handling Bullying from the Students’ Perspective. J. Early Adolesc. 2019 , 39 , 642–668. [ Google Scholar ] [ CrossRef ]
• Rigby, K. Bullying Interventions in Schools: Six Basic Approaches ; Wiley-Blackwell: Chichester, UK, 2012. [ Google Scholar ]
• Rigby, K. How teachers address cases of bullying in schools: A comparison of five reactive approaches. Educ. Psychol. Pract. Theory Res. Educ. Psychol. 2014 , 30 , 409–419. [ Google Scholar ] [ CrossRef ]
• Robinson, G.; Maines, B. Bullying: A Complete Guide to the Support Group Method ; Sage: London, UK, 2008. [ Google Scholar ]
• Pikas, A. New developments of the Shared Concern Method. Sch. Psychol. Int. 2002 , 23 , 307–336. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Bauman, S.; Del Rio, A. Pre-service teachers’ response to bullying scenarios: Comparing physical, verbal, and relational bullying. J. Educ. Psychol. 2006 , 98 , 219. [ Google Scholar ] [ CrossRef ]
• Strout, T.D.; Vessey, J.A.; DiFazio, R.L.; Ludlow, L.H. The Child Adolescent Bullying Scale (CABS): Psychometric evaluation of a new measure. Res. Nurs. Health 2018 , 41 , 252–264. [ Google Scholar ] [ CrossRef ]
• Ortega, R.; Elipe, P.; Mora-Mercha, J.A.; Luisa, M.; Genta, N.L.; Brighi, G.A.; Smith, P.K.; Thompson, F.; Tippett, P.T. The Emotional Impact of Bullying and Cyberbullying on Victims: A European Cross-National Study. Aggress. Behav. 2012 , 38 , 342–356. [ Google Scholar ]
• Veenstra, R.; Siegwar, S.; Bonne, J.H.; DeWinter, A.F.; Verhuslt, F.C.; Ormel, J. The dyadic nature of bullying and victimization: Testing a Dual-perspective Theory. Child Dev. 2007 , 78 , 1843–1854. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Thornberg, R.S.; Knutsen, S. Teenagers’ Explanations of Bullying. Child Youth Care Forum 2011 , 3 , 177–192. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Stylianos, S.; Plexousakis, S.S.; Kourkoutas, E.T.; Chatira, K.; Nikolopoulos, D. School Bullying and Post-traumatic Stress Disorder Symptoms: The Role of Parental Bonding. Front. Public Health 2019 , 7 , 75. [ Google Scholar ]
• The Wesley Mission. Give Kids A Chance: No One Deserves to be Left Out ; Wesley Mission: Sydney, NSW, Australia, 2009. [ Google Scholar ]
• Deng, Y.; Chang, L.; Yang, M.; Huo, M.; Zhou, R. Gender Differences in Emotional Response: Inconsistency between Experience and Expressivity. PLoS ONE 2016 , 11 , e158666. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Chaplin, T.; Aldao, A. Gender differences in emotion expression in children: A meta-analytic review. Psychol. Bull. 2012 , 139 , 735–765. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Smith, P.K.; Salmivalli, C.; Cowie, H. Effectiveness of school-based programs to reduce bullying: A commentary. J. Exp. Criminol. 2012 , 8 , 433–441. [ Google Scholar ] [ CrossRef ]
• Yeager, D.S.; Fong, C.T.; Lee, H.Y.; Espelage, D.L. Declines in efficacy of anti-bullying programs among older adolescents: Theory and three-level meta-analysis. J. Dev. Psychol. 2015 , 37 , 36–51. [ Google Scholar ] [ CrossRef ]
• Finkelhor, D.; Turner, H.A.; Shattruck, M.A.; Sherry, L.H. Childhood exposure to violence, crime and abuse. JAMA Pediatrics 2014 , 169 , 746–754. [ Google Scholar ] [ CrossRef ]
• Hair, J.F.; Tatham, R.L.; Anderson, R.E. Multivariate Data Analysis ; Prentice Hall: Upper Saddle River, NJ, USA, 1998. [ Google Scholar ]
• Bauman, S.; Rigby, K.; Hoppa, K. US teachers’ and school counsellors’ strategies for handling school bullying incidents. Educ. Psychol. 2008 , 28 , 837–856. [ Google Scholar ] [ CrossRef ]
• Burger, C.D.; Strohmeier, D.; Sprober, N.; Bauman, S.; Rigby, K. How teachers respond to school bullying: An examination of self-reported intervention strategy use, moderator effects, and concurrent use of multiple strategies. Teach. Teach. Educ. 2015 , 51 , 191–201. [ Google Scholar ] [ CrossRef ]
• Rigby, K. Effects of peer victimization in schools and perceived social support on adolescent well-being. J. Adolesc. 2000 , 23 , 57–68. [ Google Scholar ] [ CrossRef ]
• Newman, M.L.; Holden, G.W.; Delville, Y. Isolation and the stress of being bullied. J. Adolesc. 2005 , 28 , 343–357. [ Google Scholar ] [ CrossRef ]
• Healy, K.L.; Sanders, M.R.; Aarti, I. Facilitative parenting and children’s social, emotional and behavioral adjustment. J. Child Fam. Stud. 2014 , 24 , 1762–1779. [ Google Scholar ] [ CrossRef ]
• Smith, P.K.; Howard, S.J.; Thompson, F. Use of the Support Group Method to Tackle Bullying and Evaluation from Schools and Local Authorities in England. Pastor. Care Educ. 2007 , 5 , 4–13. [ Google Scholar ] [ CrossRef ]
• Rigby, K. The Method of Shared Concern: A Positive Approach to Bullying ; ACER: Camberwell, UK, 2011. [ Google Scholar ]
• Rigby, K.; Griffiths, C. Addressing cases of bullying through the Method of Shared Concern. Sch. Psychol. Int. 2011 , 32 , 345–357. [ Google Scholar ] [ CrossRef ]
• Veldkamp, S.A.M.; Boomsma, D.I.; De Zeeuw, E.L.; van Beijsterveldt, C.E.; Bartels, M.; Dolan, C.V.; van Bergen, E. Genetic and Environmental Influences on Different Forms of Bullying Perpetration, Bullying Victimization, and Their Co-occurrence. Behav. Genet. 2019 , 49 , 432. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Solberg, M.E.; Olweus, D. Prevalence estimation of school. J. Couns. Psychol. 2003 , 35 , 281–296. [ Google Scholar ]

Share and Cite

Rigby, K. How Teachers Deal with Cases of Bullying at School: What Victims Say. Int. J. Environ. Res. Public Health 2020 , 17 , 2338. https://doi.org/10.3390/ijerph17072338

Rigby K. How Teachers Deal with Cases of Bullying at School: What Victims Say. International Journal of Environmental Research and Public Health . 2020; 17(7):2338. https://doi.org/10.3390/ijerph17072338

Rigby, Ken. 2020. "How Teachers Deal with Cases of Bullying at School: What Victims Say" International Journal of Environmental Research and Public Health 17, no. 7: 2338. https://doi.org/10.3390/ijerph17072338

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• DOI: 10.1007/s43076-024-00385-0
• Corpus ID: 270386090

Understanding Children and Adolescents’ Experiences Being Bullied: A Mixed-Methods Study

• Makenna A. Snodgrass , Sarah L. Smith , Samantha J. Gregus
• Published in Trends in Psychology 10 June 2024
• Psychology, Sociology

49 References

Bullying among young adolescents: the strong, the weak, and the troubled., symptoms of post-traumatic stress among victims of school bullying, school bullying and association with somatic complaints in victimized children, bullying and ptsd symptoms, distressed bullies, social positioning and odd victims: young people's explanations of bullying, bullying involvement in adolescence: implications for sleep, mental health, and academic outcomes, bullying involvement, teacher–student relationships, and psychosocial outcomes, continued bullying victimization in adolescents: maladaptive schemas as a mediational mechanism, retrospective accounts of bullying victimization at school: associations with post-traumatic stress disorder symptoms and post-traumatic growth among university students, bullying victimization and perpetration among u.s. children and adolescents: 2016 national survey of children’s health, related papers.

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Analyzing the Risk of Being a Victim of School Bullying. The Relevance of Students’ Self-Perceptions

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• Published: 15 June 2023
• Volume 16 , pages 2141–2163, ( 2023 )

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• M.M. Segovia-González   ORCID: orcid.org/0000-0003-0112-5668 1 ,
• José M. Ramírez-Hurtado   ORCID: orcid.org/0000-0002-2289-1874 1 &
• I. Contreras   ORCID: orcid.org/0000-0003-3259-5697 1  

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School bullying is a growing concern in almost all developed economies, bringing negative and serious consequences for those students involved in the role of victims. In this paper, we propose to analyze this topic for the case of Spain, considering the data compiled in the Programme for International Student Assessment (PISA) report in 2018. The sample size consists of 12,549 15-old-year students (51.84% females and 48.16% males). With the help of structural equation models (SEM), we aim to detect the relationship between the risk of being a victim of bullying and several self-appreciations expressed by the students. We have considered variables that try to measure individual perceptions in several aspects, such as the self-image, the help provided by parents and teachers and how the school environment’s safety is perceived. A multigroup analysis was also performed to see the impact of the socioeconomic level of the families and the students’ academic performances on the proposed model. We conclude that several of those aspects are directly related with the risk of being bullied and this risk is higher in those students who present school failure and have a lower socioeconomic status. In this regard, the results would permit pointing out some aspects in which the decision-makers can focus their proposals to establish prevention measures.

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1 Introduction

Education must be seen as one of the main factors that impact on the progress and development of individuals and societies. It not only provides knowledge, it is also a vehicle to fortify positive values that, as a society, we need to develop. Education has proven itself to be a valuable tool to improve welfare standards, reduce social inequalities and guarantee a sustained economic growth. In that line, it should be considered as one of the sources in the sustainable development of economies.

From an individual point of view, every phase of the educational process is a significant step in the individual’s development. And at every one of those stages both the schools and the families are the main support for the development of teenagers. The contents and values they receive at these centers and obtain from their families will be used as the basis to prevent the formation of undesired behaviors. The salience of these contexts justifies the importance of guaranteeing that schools should be a safe place.

Peer violence in schools is a widespread and growing phenomenon that concerns most societies around the world. One of the forms of violence that has been attracting attention in the last decades is bullying. This is defined as “a behavior of physical and/or psychological persecution carried out by one or several students against another student who is chosen as the victim of repeated attacks” (Olweus, 1993 ). The most defining characteristic of bullying is the existence of a systematic abuse of power and an unequal power relationship between the bully and the victim (Pellegrini & Long, 2002 ; Salmivalli & Peets, 2008 ). Many researchers have shown that bullying is not an isolated problem, exclusive of certain countries or cultures. On the contrary, it is widely extended in societies all over the world (Cook, et al., 2010a ; Eslea, et al., 2004 ).

The literature has studied the problem of bullying as a group phenomenon. In addition to the main participants, bullies and bully victims, the remaining students are part of the process, assuming different roles. Hence, we can find reinforcers of the bully, defenders of the victim, or passive bystanders. Adverse behavioral and psychological outcomes have been found for all the referred groups (Rivers, et al., 2009 ; Salmivalli, 2010 ).

With respect to actions, bullying can be classified into three main categories (Olweus, 1993 ): physical, that includes pushing, kicking, taking belongings…; verbal, including performances like name-calling, teasing, threatening, etc.; and relational, including public humiliation and social exclusion. Considering the form of interaction, the actions can be direct or indirect. The former includes those physical and verbal behaviors that occur face-to-face (pushing or verbal harassment). The latter involves those attitudes in which the victim or the bullies are not necessarily present, for instance, spreading malicious rumors, and relational aggression (Olweus, 1993 ). This last form of victimization is more difficult to detect and remove. In fact, most analyses of bullying victimization have found that students more commonly report indirect forms of bullying as opposed to the direct physical form of bullying (Dinkes, et al., 2007 ; Wang, et al., 2009 ).

It has been shown that these categories of bullying do not occur in schools with the same incidence and intensity. Moreover, the prevalence of each type of actions is related with different aspects such as the students’ ages, the country’s culture, gender, and the socioeconomic level, among others. With respect to students’ ages, the rates of bullying vary significantly from one grade to another. On the whole, the risk of being a victim of bullying declines as we move forward to the next school level: it reduces as the students pass from elementary to middle school and from middle school to high school (Khoury-Kassabri, et al., 2004 ; Rigby, 2002 ). Other studies that highlight the relation between bullying and the students’ ages are, among others, those ofÁlvarez-García et al. ( 2015 ); Cook, et al., 2010b ); Saarento et al. ( 2015 ).

Regarding the role of gender, the literature shows that boys are more frequently involved in bullying than girls (Álvarez-García, et al., 2015 ; Cook, et al., 2010b ; Smith, et al., 2019 ). Boys are implicated more frequently in both roles, as victims and bullies, especially in those actions that include physical aggressions. On the contrary, girls are involved in those actions that involve indirect aggressions: teasing or gossiping about peers or relational victimization (Bradshaw, et al., 2015 ; Carbone-Lopez, et al., 2010 ; Tiliouine, 2015 ).

There are also studies analyzing a possible relationship between bullying victimization and socioeconomic status (Allen, et al., 2022 ; Jain, et al., 2018 ). In Tippett & Wolke ( 2014 ) we can find a review of the published literature on bullying in schools related with socioeconomic status. In the analysis, the authors found that victimization was positively associated with low socioeconomic levels and negatively associated with high socioeconomic levels. In the same line, Tiliouine ( 2015 ) indicates that victims of bullying came from less advantaged families and present more frequent absenteeism at school.

From the premise that bullying is a very complex process in which many interrelated variables should be considered, the aim of this study is the analysis of the main factors associated with the risk of being a victim of bullying attitudes. We have considered a quantitative approach to analyze the importance of several aspects, such as the performance of the family, teachers, the environment provided by the school and the students’ self-esteem. The target is to analyze if certain aspects can be considered as determinant for an individual to be a victim of bullying.

We have considered the information provided by the Program for International Student Assessment (PISA) report from 2018. In our view, students aged 15 are at a crucial moment in their physical and emotional development. The PISA reports include not only academic performance data. A large amount of context information is included in every report that permits obtaining a broad picture of the situation of students in every country. In particular, we have considered three main aspects of their life that influence how they feel: how satisfied they are with how they look, with their relationships with their parents, and with life at school (OECD, 2019b ).

1.1 Literature Review

There is a large body of research on the problem of bullying. It is one of the main topics in the field of education because of its social impacts. We can find some systematic investigations that try to analyze the risk factors from a global perspective, examining individual and contextual factors that have proven to be correlated with bullying. In this line, we come across works mainly focused on reviewing the literature and meta-analyses at the level of the individual’s characteristics. Examples of these works are the studies of Álvarez-García et al. ( 2015 ); Cook, et al., 2010b ); Lopez et al. ( 2011 ). Other papers have proposed a systematic review of the existing literature at a school and classroom level, analyzing which factors are directly related with bullying situations; see, among others Azeredo et al. ( 2015 ), and Saarento et al. ( 2015 ). Other works have tried to analyze the predictive value of specific factors, such as the socioeconomic status (Tippett & Wolke, 2014 ), empathy (Van Noorden, et al., 2014 ), and the role of parents (Lereya, et al., 2013 ; Nocentini, et al., 2019 ).

Other meta-analysis papers that analyze the consequences of bullying victimization are those of Gini and Pozzoli ( 2009 ), Moore et al. ( 2017 ), (with a particular interest in psychosomatic problems), Hansen et al. ( 2012 ) (analyzing psychological factors), and Hawker and Boulton ( 2000 ) (which proposes the study of psychosocial maladjustment).

Much of the research uses quantitative methods to deal with the problem. In particular, a number of studies propose the analysis of relations among variables using structural equation models (SEM), which will be the basis of our subsequent analysis. In this line, there is the work of Gini et al. ( 2007 ), which shows the relations between empathy and individual behavior in bullying situations, differentiating between pro-bullying and defending-bullying individuals. Considering a sample of Italian adolescents, it presents two possible factors (the cognitive component and the emotional aspect of empathy) that can influence the behavior of individuals against bullying (for both active defenders and passive bystanders). In a posterior paper, Gini et al. ( 2008 ), the relevance of gender and social self-efficacy is incorporated into the analysis and Pozzoli and Gini ( 2012 ) analyze the attitudes toward bullying.

In Roland and Idsøe ( 2001 ) the authors study how proactive (emotions involved in the aggressor) and reactive (the social event that induces the behavior) aggressiveness were related to bullying. In Meyer-Adams and Conner ( 2008 ) the victimization by bullying is analyzed, identifying those risk factors in the psychosocial environment of the school. Other authors find mediating effects of emotional symptoms on the association between homophobic bullying victimization and problematic internet/smartphone (Li, et al., 2020 ) or the mediating effect of regulatory emotional self-efficacy on the link between self-esteem and school bullying (Wang, et al., 2018 ).

Additional factors, such as the school climate, satisfaction at school, and schoolwork-related anxiety are included in the models in an attempt to explain satisfaction in life and well-being. Examples of this working line are the papers from Borualogo and Casas ( 2023 ), Huang ( 2020 ), Tiliouine ( 2015 ), and Varela et al. ( 2019 , 2021 ). The connection between the school climate and bullying victimization was studied by Chen et al. ( 2020 ) from a cross-country perspective.

It is important to bear in mind that bullying could have very serious consequences. Hence, some studies have shown a relevant link between non-fatal suicidal behaviors and bullying victimization (Zhao, et al., 2022 ), and the different bullying experiences: bullies, victims, and bully-victims (Wu, et al., 2021 ). In Zhang et al. ( 2022 ), the mediating role of the family, anxiety and resilience is analyzed.

In this context, we propose to analyze the relevance of students’ perceptions about the help and support provided by parents, teachers, and the school when the risk factors of being a bullying victim are measured.

1.2 Theoretical Background

The theoretical framework of the present study is based on the theories of the social-ecological model (Bronfenbrenner, 1979 ) and person- and stage-environment fit (Eccles, et al., 1993 ), in the sense that social settings can impact on the human behavior and human development. Specifically, we draw on social learning theory to emphasize that individuals learn from their family, peers, and prior events (Bandura, 1973 ). Learning by seeing and doing is the foundation of social learning theory of bullying. In this regard, we refer to the immediate context in which the adolescent is directly involved, and we consider the parent-child relationship, the role of the teachers, and the safety at school.

The aim of this work is to study the relationships between bullying victimization and students’ own perceptions of their parents, teachers, school safety, and positive self-beliefs. A multigroup analysis was also carried out to see the impact of the socioeconomic level of the families and the students’ academic performances on the proposed model. There are few studies that jointly relate all the characteristics that we consider in the proposed model, which includes the analysis of the impact of the socioeconomic and cultural level and academic failure. The existing relationships of each or several of the characteristics considered have been partially studied. We believe that it is essential to analyze all of them as a whole in order to have a vision as close as possible to reality.

1.3 Hypothesis of the Model

The main idea is to consider the students’ perceptions about the help and support provided by parents, teachers, and the school, as well as their opinion of themselves, as feasible causes behind the bullying phenomenon. Teenagers at the end of secondary education experience physical and psychological changes that decisively influence their intrapersonal and interpersonal behaviors. Due to social pressure from friends and classmates, they often disregard the advice of their parents and teachers. For this reason, we consider the analysis from the student’s point of view to be a key aspect. Likewise, the connections between family variables and school bullying practice or victimization have been documented in different papers (Foster & Brooks-Gunn, 2013 ; Patton, et al., 2013 ). Distinct aspects of this relationship can be contemplated as key aspects in the students’ welfare.

To carry out this analysis, the following hypotheses are put forward, which we will explain below.

1.3.1 Student Relationships with Their Parents, and Bullying Victimization

Previous studies highlighted that the action of parents within families is fundamental when it comes to instilling values in their children and giving them support to recognize and solve problems (Oliveira, et al., 2020 ; Patton, et al., 2013 ). Some studies reveal that warm and supportive parental relationships are related to child’s social and emotional well-being even in the context of exposure to adversity (Kim-Cohen, et al., 2004 ; Murphy, et al., 2017 ). Similarly, Davis-Kean et al. ( 2021 ) point out that the parents’ educational support is directly related with their affective environment.

At that point, the perceived parental support is crucial to maintain self-esteem, the psychological well-being, including positive self-beliefs and reduced levels of internalizing symptoms (Boudreault-Bouchard, et al., 2013 ; Dutton, et al., 2020 ). Studies show that positive parental factors, such as support and positive parent-child relationships, help adolescents feel better about themselves, have positive feeling about themselves and have greater life satisfaction (Van der Kaap-Deeder, et al., 2017 ; Raboteg-Saric & Sakic, 2014 ). In some way, the former results point out that the role that families play in bullying prevention is fundamental (Arseneault, et al., 2010 ; Ttofi & Farrington, 2009 ). In addition, positive relationships and interaction between parents and children reduce the possibility of being bullied and play a role in the emotional adjustment of victims of bullying, making interventions for victims more successful (Lereya, et al., 2013 ; Zych, et al., 2019 ). In contrast, low social support and poor interpersonal relationships could increase the risk of students being victims of bullying (Hong, et al., 2012 ; Patton, et al., 2013 ).

In view of the above, it is reasonable to hypothesize:

H 1 : Parents´ educational support influences the emotional support they give their children.

H 2 : Parents´ emotional support influences the student’s self-efficacy.

H 3 : Parents´ emotional support influences the student’s positive feelings.

1.3.2 Self-efficacy, Positive Feeling, self-image and Bullying Victimization

Positive self-related cognitions, defined as children`s thoughts, beliefs, or attitudes about themselves, such as self-efficacy, self-respect or self-image are identified in the literature as being considered protective factors in the victimization of bullying (see Cook et al. ( 2010b ) for a complete revision).

Negative affectivity, i.e., having negative feelings about the environment and oneself is related to being introverted, having a low self-esteem and a negative self-image. The appearance of these children together with a nervous temperament means a risk of victimization (Hansen, et al., 2012 ). Several researchers have reported the positive association between low self-esteem and school bullying (Gendron, et al., 2011 ; Tsaousis, 2016 ).

With respect to their emotions and the perception that they have about themselves we consider students’ self-efficacy, positive feelings and self-image, and it can be hypothesized that.

H 4 : The student´s positive feelings are related with the child’s perception of being bullied.

H 5 : The student’s self-efficacy is related with the child’s perception of being bullied.

H 6 : The student’s self-image is related with the child’s perception of being bullied.

1.3.3 Sense of Belonging to the School, Teacher Support, and Bullying Victimization

The school environment and the relationship of its members with the student and the relation with bullying has been extensively studied (Azeredo, et al., 2015 ; Saarento, et al., 2015 ). The student-teacher relationship and the connections with school are relevant to bullying behavior (Gendron, et al., 2011 ; Raskauskas, et al., 2010 ).

Adolescents who feel less close to their school and their members are more likely to be victims of bullying and have less satisfaction with their lives (Varela, et al., 2019 , 2021 ). On the contrary, negative factors of the school environment (e.g., a lack of decisions and rules in the face of bullying by the management and teachers, a negative school climate perceived by students) can lead to an increase in the frequency of bullying, aggression, and victimization (Cook, et al., 2010b ; Goldweber, et al., 2013 ). Hence, we can consider the students’ feelings of belonging to the school, understood as the feeling of respect and acceptance that the students have toward the school, as a key aspect in this topic.

On the other hand, teachers play a key role in this process. Although there are studies that show discrepancies between how teachers and staff perceive bullying compared to their students (Bradshaw, et al., 2007 ; Waasdorp, et al., 2011 ), the influence of positive teacher-student relationships, as well as teacher involvement, have a great implication in bullying prevention (Espelage, et al., 2014 ; Saarento, et al., 2015 ). Teacher support is a protective factor in bullying (Álvarez-García, et al., 2015 ; Azeredo, et al., 2015 ), as they often play an important role in advising students how to respond to bullying. (Sokol, et al., 2016 ; Troop-Gordon & Ladd, 2015 ).

With respect to the student’s life at school, we consider that the following hypotheses can be formulated:

H 7 : A sense of belonging to the school is related with the child’s perception of being bullied.

H 8 : The teacher`s support is related with the child’s perception of being bullied.

1.3.4 Influence of Academic Success or Socioeconomic and Cultural Status of Students

The scientific literature shows that concrete indications about the influence of bullying on academic performance can be found (Huang, 2022 ; Riffle, et al., 2021 ). In this paper, we have considered a multigroup analysis to analyze the influence of the academic performance on the results obtained from the proposed SEM model. In a similar way, previous studies (see, among others, Allen et al. ( 2022 ) and Jain et al. ( 2018 ), pointed out the influence of the socioeconomic level. An additional analysis has been also performed considering the socioeconomic level as a differential factor.

Based on the hypotheses formulated above, a model based on structural equations is proposed and computed. SPSS and AMOS software were used to examine the variables and the fitness of the proposed model.

2.1 Dataset

This study analyses Spanish data from the 2018 Program for International Student Assessment (PISA). This program has been designed by the Organization for Economic Cooperation and Development (OECD) to collect information about 15-year-old students in the participating countries and economies. A two-stage stratified sampling method was adopted (schools are first sampled and then students are sampled in the participating schools) (OECD, 2009 ). In schools were there were fewer than 42 age-eligible adolescents, all students aged 15 were selected.

In this study the sample size consists of 12,549 students. There were 6,505 females (51.84%) and 6,044 males (48.16%).

2.2 Measures

All the variables have been calculated from the PISA report published data. The latent and observable variables are summarized in Table  1 , note that some observable variables have been removed after the factorial structure. Following the practical suggestion from Kline ( 2015 ), the number of variables selected to represent latent variables vary from 3 to 5. The selection of the items in the measurement of each latent variables is based on literature review and theoretical foundations of SEM (Bollen, 1989 ). In some cases, we have suppressed some non-representative items by considering a mixed procedure which include factorial analysis and Cronbach alpha coefficient (Brown, 2006 ). It is important to bear in mind that some constructs can be more difficult to measure and, consequently demands a larger number of items for an adequate representation (Bollen, 1989 ).

Due to correlation problems, item BE2 has been defined negatively for the structure of the three observable variables of the sense of belonging to converge correctly. Also, an exploratory factor analysis was carried out with SPSS, with varimax rotation, in order to identify the adequacy of the items or indicators to each construct. Because of that, some indicators were deleted to properly define the internal structure of the model. Based on this, the constructs were defined by the items presented in Table  1 .

The academic performance has been defined with two feasible values: success and failure. We have estimated the levels of proficiency in Mathematics and Science (this has not been done in the case of language since this information is not available for the case of Spain) following the recommendations provided by PISA, which establishes six levels of proficiency. Each successive level is associated with increasingly difficult tasks passed by the student. The students are considered to have failed academic performance if they do not reach level 2 of proficiency in any of the subjects, this is the minimum level of proficiency established in the context of the United Nations Sustainable Development Goals (OECD, 2009 ).

On the other hand, we have constructed a new variable to represent the socioeconomic level. We have considered three levels (low, medium, and high) based on the Economic, Social and Cultural index (ESCS index) provided by PISA (OECD, 2019a ). We have considered that students with ESCS values lower than the 25th percentile constitutes the group with a low socioeconomic level and those included at the 75th percentile the group with a high socioeconomic level.

Based on the hypotheses formulated in the previous section, the proposed model is the one represented in Fig.  1 .

Structural Equation Model

2.3 Procedure

Four phases of data analysis were completed in accordance with the method advised by various authors (Frash & Blose, 2019 ). Firstly, a descriptive analysis using SPSS was used to determine the sample’s demographic characteristics. Secondly, to assess the suitability of the constructs’ dimensions, an exploratory factor analysis using varimax rotation was performed by means of SPSS. Thirdly, a confirmatory factor analysis was carried out using AMOS software to verify the measurement model. Fourthly, the structural model’s validity was examined. Finally, to confirm the relationships between the latent variables, the structural model’s coefficients were computed using AMOS software.

This section presents the analysis of the results obtained for the proposed model. The dataset has been analyzed by means of AMOS-IBM software.

The internal structure of latent variables and indicators has been assessed by means of factorial analysis. The internal consistency of the scales was measured through the Cronbach alpha coefficient, obtaining in all cases values greater than the 0.7 threshold.

The data normality was also analyzed, checking if the skewness coefficient was between − 1 and 1, and that the kurtosis coefficient was between − 7 and 7. Most of the items were normal, although there were some cases in which this hypothesis was not verified. On the other hand, multivariate normality was measured by means of the Martia test. The multivariate normality hypothesis was rejected because the value of the Martia test was 251.048 (> 5.99 for a significance level of 5%), the critical ratio being greater than the required 1.96. Thus, multivariate normality is not supported. However, since the sample is large enough, it has been decided to opt for the maximum likelihood estimation method, because this method facilitates the convergence of the estimates even in the absence of multivariate normality (Lèvy, et al., 2006 ).

The assessment of the proposed model has been carried out by analyzing the measurement model and the structural model. Reliability and validity have been used for the assessment of the measurement model. Regarding the first issue, the reliability of the items and the reliability of the constructs have been analyzed.

For the reliability of the items, it was found that the standardized factor loads were greater than the 0.707 threshold. This implies that the shared variance between the construct and its indicators is greater than the error variance. In this way, more than 50% of the variance of the observable variable (communality) is shared by the construct. In any case, some authors consider that a factor loading greater than 0.5 is also acceptable (Chau, 1997 ). All the standardized factorial loads are greater than 0.707, except those of items EF1, BE2 and BU3, which are greater than 0.5, so the reliability of the items is verified (Table  2 ).

The Cronbach alpha coefficient and the Composite Reliability (CR) coefficient were used for the assessment of the constructs’ reliability. All the Cronbach alpha coefficients were greater than 0.7, so the reliability is high. The minimum required value of the composite reliability coefficient is 0.7 (Nunnally & Bernstein, 1994 ). In Table  2 , we can see that all the constructs have a CR coefficient greater than 0.7, so the reliability of the constructs is also verified.

Convergent validity and discriminant validity were analyzed for the assessment of the measurement model’s validity. The average variance extracted (AVE) was used for the analysis of the convergent validity. Values greater than 0.5 indicate that the construct explains more than the variance of its indicators (Hair, et al., 2014 ). In Table  2 , we can see that all the AVE values are greater than 0.5, except the value of the student’s self-efficacy construct. This value is practically on the limit, so we can say that the convergent validity is verified.

Regarding the discriminant validity, we must verify that the correlations between the constructs are not high or are at least lower than the square root of the AVE. The correlation matrix between the constructs is shown in Table  3 . In the main diagonal appears the square root of the AVE. We can see that all the correlations are lower than the square root of the AVE, so the discriminant validity is verified.

With respect to the assessment of the structural model, Table  4 shows that all the coefficients are significative, except the coefficient of the hypothesis H 3 . On the other hand, the R 2 values were greater than 0.1, exceeding this minimum value recommended by some authors, since lower values lack an adequate predictive level, even though significant (Hair, et al., 2014 ). For all these reasons, we can affirm that the validity of the structural model is verified.

The estimated structural model

The results of the structural model also reveal a good fit of the data. The χ 2 statistic shows if the discrepancy between the original data matrix and the reproduced matrix is significant or not. In this case, the p -value is lower than 0.05; therefore, this hypothesis is rejected. However, it should be noted that the value of the χ 2 statistic is highly influenced by the size of the sample, the complexity of the model and by the violation of the multivariate normality assumption. For these reasons, other measurements of global fit are used in AMOS software. In this sense, the remaining measures are consistent with a high degree of fit of the model (RMSEA = 0.042; CFI = 0.956; GFI = 0.950; NFI = 0.955; TLI = 0.952; AGFI = 0.940).

Finally, the total standardized effects have been obtained for analysing the influence of the constructs on bullying. The sense of not belonging is the construct that most influences bullying (total effect of 0.384). This variable is followed in order by student’s positive feeling, student’s self-image, teacher’s support, parents’ emotional support and parents’ educational support, with values of -0.095, -0.090, -0.062, -0.042 and − 0.026, respectively.

To identify if the results obtained from the SEM model are invariant with respect to socioeconomic and academic performance factors, two separate multigroup analyses have been computed, considering the tool developed in Gaskin ( 2016 ), which evaluates the differences between critical ratios.

Table  5 summarizes the results for multigroup analysis based on academic performance. We can observe that three relationships are invariant when the results for academic success and academic failure are compared. The relationship between parents’ emotional support and the students’ self-efficacy are higher for those students who are considered as successful in their academic performance. In a similar way, the intensity of the relation between students’ self-efficacy and the risk of being victim, is moderated by the values of academic performance. Finally, the relation between students’ self-image and the risk of being bullied is also affected by the academic performance.

Regarding the influence of socioeconomic values on the results from the SEM model, we do not find significant differences between the groups of low and medium socioeconomic levels. The only remarkable differences emerge with respect to teachers’ support and the risk of being bullied. In this case, those students with a lower socioeconomic level present a greater risk of being bullied. This must be explained by the fact that these group of students are most familiar with unsafe environments (Glew, et al., 2008 ).

4 Discussion

The results obtained from the computation of the SEM model point out that the feeling of help and support from their parents is a positive factor in the skill development oriented to resolving and overcoming difficult situations and fostering students’ positive feelings. Previous studies support this finding. Dutton et al. ( 2020 ) analyzed how perceived parental support influenced positive self-beliefs and is very important for the psychological well-being of adolescents across different cultural contexts.

Regarding positive feelings and the student’s self-image, both are negatively related with being a victim of bullying. However, the student’s self-efficacy and victimization has not been found to be significantly related. Most of the previous studies reported that positive self-related cognitions should be considered as protective factors and a negative association with the victimization of bullying (Cook, et al., 2010b ; Gendron, et al., 2011 ; Tsaousis, 2016 ). Considering intermediate variables, we can think that there is a relationship between parental educational and emotional support and bullying victimization. This agrees with many other works such as the systematic review by Nocentini et al. ( 2019 ).

With respect to the school environment, the support of the teaching staff and the security provided by the educational center have been found significant in preventing the victimization of bullying. The sense of belonging to the school is the construct that presents the most influence. The results found for the school environment are in line with other studies that showed how the students’ relationships with their teachers, as well as the involvement of teachers in the development process of adolescents are relevant to the phenomenon of bullying, mitigating its adverse effects (Espelage, et al., 2014 ; Gendron, et al., 2011 ; Raskauskas, et al., 2010 ; Saarento, et al., 2015 ). Likewise, feeling displaced and not close to the school is associated with being a victim of bullying (Varela, et al., 2019 , 2021 ).

Considering the theories on social-ecological models (Bronfenbrenner, 1979 ) and the environmental-fit (Eccles, et al., 1993 ), the bullying victimization is related with their closer environment. In this study, we have considered the students’ context, that is to say, the relations with their parents, teaching staff and school center, as this environment.

The findings suggest that, in the line pointed by the social learning theory, that a main part of the learning process is based on the observation and replication of some behaviors. In addition, this learning process is influenced by their attention and motivation and by the context found by the students.

When we considered the academic success and computed the model for two differentiated groups, all the relationships proposed in the initial model turn out to be significant (with the expected sign), including the relationship between self-efficacy and victimization, which was not in the original model. There are significant differences between the relationships of parental emotional support and the self-efficacy of the children and the victimization, being greater for the advantaged students. The opposite occurs when we compare the relationship between self-image and victimization. The relations between bullying and poor academic performance haven been analyzed is several works; see for instance Huang ( 2022 ), Nakamoto and Schwartz ( 2010 ), and Riffle et al. ( 2021 ), obtaining results in the same line as that described above.

Finally, the analysis performed for the three levels of the socioeconomic status permits seeing how the relations for the higher level are stronger than those obtained in the global model and those obtained for the lower socioeconomic levels. The metanalysis performed in Tippett and Wolke ( 2014 ) pointed out how those students with a lower socioeconomic level were more exposed to bullying victimization, which could be explained by the risk of being excluded (because of their limited resources).

5 Concluding Remarks

Peer violence in schools and bullying attitudes is a growing problem for most developed countries. Adolescents constitute a vulnerable group that demands care since certain traumatic experiences lived out in each human being’s life stage can determine his/her future development. Bullying attitudes have relevant consequences, resulting in disorders in those bullied students, even triggering suicide attempts.

This situation has captured the attention of many researchers, a large body of literature on this topic having been developed, including an analysis of causes and consequences, a classification of these activities, and metanalyses. This work is embedded in this context. We have proposed a quantitative analysis, based on Structural Equation Models, to study the relationships of the risk of being bullied with some variables of interest. We have considered the information published in PISA reports, considering the information provided by the students themselves that included self-perceptions about their behavior and experiences in their school stage.

In this paper, we have proposed and computed a quantitative model to detect significant relations of some relevant variables with the risk of being bullied. This ensemble of results could be valuable in the decision-making process. On some occasions the problem of bullying is increased by the lack of interest of educational centers in addressing this problem when it is in its initial phase and trying to silence it (this can be an embarrassing situation for the students or the institutions). Therefore, prevention programs have become an essential tool that must be accessible for teachers and parents to detect the problem as soon as possible. We show that the first warning signs can be obtained from the analysis of public datasets like the ones published in PISA reports.

Several limitations of this study need to be mentioned. One is only using self-reports by the student. Although it is very important to have the students’ perceptions, it would also be desirable to know the perceptions of the school and family environment, which would increase the validity of the results found. Furthermore, a key aspect to be considered as a part of the school environment is the response of the other students. It is important to explore if their response is passive, by defending their classmates or by cooperating with the bullies. Similarly, the consideration of the activity on the social networks should be a key point in future studies. And finally, it is important to point out that the cross-sectional research designs in the current study did not permit to analyze informing causal relationships between the variables.

Future lines of research include broadening and deepening the analysis, including complementary methodologies that permit incorporating contextual variables (the level of income, the level of education, family contexts) and individual information that would enable tailoring conclusions and proposals. Also, the consideration of cyberbullying, which unfortunately are becoming increasingly frequent and not only inside but also outside of the school center, should be an additional aspect to be considered. On the other hand, a cross analysis considering different countries to explore differences between them should be an interesting extension of this study.

Data Availability

All the data considered in this study is derived from public repositories included at the reference Section.

Allen, K. A., Cordoba, B. G., Parks, A., & Arslan, G. (2022). Does socioeconomic Status Moderate the relationship between School Belonging and School-Related factors in Australia? Child Indicators Research , 15 , 1741–1759. https://doi.org/10.1007/s12187-022-09927-3

Article   Google Scholar  

Álvarez-García, D., García, T., & Núñez, J. C. (2015). Predictors of school bullying perpetration in adolescence: A systematic review. Aggression and Violent Behavior , 23 , 126–136. https://doi.org/10.1016/j.avb.2015.04.007

Arseneault, L., Bowes, L., & Shakoor, S. (2010). Bullying victimization in youths and mental health problems: ‘Much ado about nothing’? Psychological Medicine , 40 , 717–729. https://doi.org/10.1017/S0033291709991383

Azeredo, C. M., Rinaldi, A. E. M., Moraes, C. L., Levy, R. B., & Menezes, P. R. (2015). School bullying: A systematic review of contextual-level risk factors in observational studies. Aggression and Violent Behavior , 22 , 65–76. https://doi.org/10.1016/j.avb.2015.04.006

Bandura, A. (1973). Aggression: A social learning theory analysis . Prentice-Hall.

Bollen, K. A. (1989). Structural equations with latent variables . John Wiley & Sons.

Borualogo, I. S., & Casas, F. (2023). Bullying victimisation and children’s Subjective Well-being: A comparative study in seven asian countries. Child Indicators Research , 16 , 1–27. https://doi.org/10.1007/s12187-022-09969-7

Boudreault-Bouchard, A. M., Dion, J., Hains, J., Vandermeerschen, J., Laberge, L., & Perron, M. (2013). Impact of parental emotional support and coercive control on adolescents’ self-esteem and psychological distress: Results of a four-year longitudinal study. Journal of Adolescente , 36 , 695–704. https://doi.org/10.1016/j.adolescence.2013.05.002

Bradshaw, C. P., Sawyer, A. L., & O’Brennan, L. M. (2007). Bullying and peer victimization at school: Perceptual differences between students and school staff. School Psychology Review , 36 (3), 361–382. https://doi.org/10.1080/02796015.2007.12087929

Bradshaw, C. P., Waasdorp, T. E., & Johnson, S. L. (2015). Overlapping Verbal, Relational, Physical, and electronic forms of bullying in adolescence: Influence of School Context. Journal of Clinical Child & Adolescent Psychology , 44 (3), 494–508. https://doi.org/10.1080/15374416.2014.893516

Bronfenbrenner, U. (1979). The ecology of human development . Cambridge, MA: Harvard University Press.

Google Scholar  

Brown, T. A. (2006). Confirmatory factor analysis for applied research . The Guilford Press.

Carbone-Lopez, K., Esbensen, F. A., & Brick, B. T. (2010). Correlates and consequences of peer victimization: Gender differences in direct and indirect form of bullying. Youth Violence and Juvenile Justice , 8 (4), 332–350. https://doi.org/10.1177/1541204010362954

Chau, P. Y. K. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences , 28 (2), 309–334. https://doi.org/10.1111/j.1540-5915.1997.tb01313.x

Chen, C., Yang, C., Chan, M., & Jimerson, S. R. (2020). Association between School climate and bullying victimization: Advancing Integrated perspectives from parents and cross-country comparisons. School Psychology , 35 (5), 311–320. https://doi.org/10.1037/spq0000405

Cook, C. R., Williams, K. R., Guerra, N. G., & Kim, T. E. (2010a). Variability in the prevalence of bullying and victimization: A cross-national and methodological analysis. In S. R. Jimerson, S. M. Swearer, & D. L. Espelage (Eds.), Handbook of bullying in schools: An international perspective (pp. 347–362). Routledge/Taylor & Francis Group.

Cook, C. R., Williams, K. R., Guerra, N. G., Kim, T. E., & Sadek, S. (2010b). Predictors of bullying and victimization in Childhood and Adolescence: A Meta-analytic investigation. School Psychology Quarterly , 25 (2), 65–83. https://doi.org/10.1037/a0020149

Davis-Kean, P. E., Tighe, L. A., & Waters, N. E. (2021). The role of parent Educational Attainment in parenting and Children`s Development. Current Directions in Psychological Science , 30 (2), 186–192. https://doi.org/10.1177/0963721421993116

Dinkes, R., Cataldi, E. F., Lin-Kelly, W., & Snyder, T. D. (2007). Indicators of School Crime and Safety: 2007 (NCES 2008-021/NCJ 219553). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education and Bureau of Justice Statistics, Office of Justice Programs, U.S. Department of Justice.

Dutton, Y. E. C., Choi, I. J., & Choi, E. (2020). Perceived parental support and adolescents’ positive self-beliefs and levels of Distress Across Four Countries. Frontiers in Psychology , 11 , 1–11. https://doi.org/10.3389/fpsyg.2020.00353

Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Iver, D. M. (1993). Development during adolescence. The impact of stage-environment on young adolescents´ experiences in schools and in families. The American Psychologist , 48 (2), 90–101.

Eslea, M., Menesini, E., Morita, Y., O’Moore, M., Mora-Merchan, J. A., Pereira, B., & Smith, P. K. (2004). Friendship and loneliness among bullies and victims: Data from seven countries. Aggressive Behavior , 30 (1), 71–83. https://doi.org/10.1002/ab.20006

Espelage, D. L., Polanin, J. R., & Low, S. K. (2014). Teacher and staff perceptions of school environment as predictors of student aggression, victimization, and willingness to intervene in bullying situations. School Psychology Quarterly , 29 (3), 287–305. https://doi.org/10.1037/spq0000072

Foster, H., & Brooks-Gunn, J. (2013). Neighborhood, Family and Individual Influences on School Physical victimization. Journal of Youth and Adolescence , 42 (10), 1596–1610. https://doi.org/10.1007/s10964-012-9890-4

Frash, R. E., & Blose, J. E. (2019). Serious leisure as a predictor of travel intentions and flow in motorcycle tourism. Tourism Recreation Research , 44 (4), 516–531. https://doi.org/10.1080/02508281.2019.1626118

Gaskin, J. (2016). Stats Tools Package . http://statwiki.gaskination.com

Gendron, B. P., Williams, K. R., & Guerra, N. G. (2011). An analysis of bullying among students within schools: Estimating the effects of individual normative beliefs, self-esteem, and school climate. Journal of School Violence , 10 (2), 150–164. https://doi.org/10.1080/15388220.2010.539166

Gini, G., & Pozzoli, T. (2009). Association between bullying and psychosomatic problems: A meta-analysis. Pediatrics , 123 (3), 1059–1065. https://doi.org/10.1542/peds.2008-1215

Gini, G., Albiero, P., Benelli, B., & Altoè, G. (2007). Does empathy predict adolescents´ bullying and defending behavior? Aggressive Behavior , 33 (5), 467–476. https://doi.org/10.1002/ab.20204

Gini, G., Albiero, P., Benelli, B., & Altoè, G. (2008). Determinants of adolescents’ active defending and passive bystanding behavior in bullying. Journal of Adolescence , 31 (1), 93–105. https://doi.org/10.1016/j.adolescence.2007.05.002

Glew, G. M., Fan, M. Y., Katon, W., & Rivara, F. P. (2008). Bullying and school safety. The Journal of Pediatrics , 152 (1), 123–128. https://doi.org/10.1016/j.jpeds.2007.05.045

Goldweber, A., Waasdorp, T. E., & Bradshaw, C. P. (2013). Examining the link between forms of bullying behaviors and perceptions of safety and belonging among secondary school students. Journal of School Psychology , 51 (4), 469–485. https://doi.org/10.1016/j.jsp.2013.04.004

Hair, J. F. J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review , 26 (2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128

Hansen, T. B., Steenberg, L. M., Palic, S., & Elklit, A. (2012). A review of psychological factors related to bullying victimization in schools. Aggression and Violent Behavior , 17 (4), 383–387. https://doi.org/10.1016/j.avb.2012.03.008

Hawker, D. S., & Boulton, M. J. (2000). Twenty years’ research on peer victimization and psychosocial maladjustment: A meta-analytic review of cross-sectional studies. Journal of Child Psychology and Psychiatry and Allied Disciplines , 41 (4), 441–455. https://doi.org/10.1111/1469-7610.00629

Hong, J. S., Espelage, D. L., Grogan-Kaylor, A., & Allen-Meares, P. (2012). Identifying potential mediators and moderators of the association between child maltreatment and bullying perpetration and victimization in school. Educational Psychology Review , 24 (2), 167–186. https://doi.org/10.1007/s10648-011-9185-4

Huang, L. (2020). Peer victimization, teacher unfairness and adolescent life satisfaction: The mediating roles of sense of belonging to school and schoolwork-related anxiety. School Mental Health: A Multidisciplinary Research and Practice Journal , 12 (3), 556–566. https://doi.org/10.1007/s12310-020-09365-y

Huang, L. (2022). Exploring the relationship between school bullying and academic performance: The mediating role of students’ sense of belonging at school. Educational Studies , 48 (2), 216–232. https://doi.org/10.1080/03055698.2020.1749032

Jain, S., Cohen, A. K., Paglisotti, T., Subramanyam, M. A., Chopel, A., & Miller, E. (2018). School climate and physical adolescent relationship abuse: Differences by sex, socioeconomic status, and bullying. Journal of Adolescence , 66 , 71–82. https://doi.org/10.1016/j.adolescence.2018.05.001

Khoury-Kassabri, M., Benbenishty, R., Astor, R. A., & Zeira, A. (2004). The contributions of community, family, and school variables to student victimization. American Journal of Community Psychology , 34 (3–4), 187–204. https://doi.org/10.1007/s10464-004-7414-4

Kim-Cohen, J., Moffitt, T. E., Caspi, A., & Taylor, A. (2004). Genetic and environmental processes in young children’s resilience and vulnerability to socioeconomic deprivation. Child Development , 75 (3), 651–668. https://doi.org/10.1111/j.1467-8624.2004.00699.x

Kline, R. B. (2015). Principles and practice of structural equation modeling, fourth edition . Guilford Publications.

Lereya, S. T., Samara, M., & Wolke, D. (2013). Parenting behaviour and the risk of becoming a victim and a bully/victim: A meta-analysis study. Child Abuse & Neglect , 37 (12), 1091–1108. https://doi.org/10.1016/j.chiabu.2013.03.001

Lèvy, J. P. M., Martín, M., & Román, M. (2006). Optimización según estructuras de covarianzas. In J. Varela Mallo & J. P. M. Lèvy (Eds.), Modelización con estructuras de covarianzas en ciencias sociales: temas esenciales, avanzados y aportaciones especiales .

Li, D. J., Chang, Y. P., Chen, Y. L., & Yen, C. F. (2020). Mediating Effects of emotional symptoms on the association between homophobic bullying victimization and problematic internet /Smartphone use among gay and bisexual men in Taiwan. International Journal of Environmental Research and Public Health , 17 (10), 3386, 1–10. https://doi.org/10.3390/ijerph17103386

Lopez, R., Amaral, A. F., Ferreira, J., & Barroso, T. (2011). Factors related to the bullying phenomenon in school context: Integrative literature review. Revista de Enfermagem Referência, 3 (5), 153–162. https://doi.org/10.12707/RIII1169

Meyer-Adams, N., & Conner, B. T. (2008). School Violence: Bullying behaviors and the Psychosocial School Environment in Middle Schools. Children & Schools , 30 (4), 211–221. https://doi.org/10.1093/cs/30.4.211

Moore, S. E., Norman, R. E., Suetani, S., Thomas, H. J., Sly, P. D., & Scott, J. G. (2017). Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis. World Journal of Psychiatry , 7 (1), 60–76. https://doi.org/10.5498/wjp.v7.i1.60

Murphy, T. P., Laible, D., & Augustine, M. (2017). The influences of parent and peer attachment on bullying. Journal of Child and Family Studies , 26 (5), 1388–1397. https://doi.org/10.1007/s10826-017-0663-2

Nakamoto, J., & Schwartz, D. (2010). Is peer victimization associated with academic achievement? A meta-analytic review. Social Development , 19 (2), 221–242. https://doi.org/10.1111/j.1467-9507.2009.00539.x

Nocentini, A., Fiorentini, G., Paola, L. D., & Menesini, E. (2019). Parents, family characteristics and bullying behavior: A systematic review. Aggression and Violent Behavior , 45 , 41–50. https://doi.org/10.1016/j.avb.2018.07.010

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

OECD. (2009). PISA Data Analysis Manual: SPSS, Second Edition . OECD Publishing. https://doi.org/10.1787/9789264056275-en

OECD. (2019a). PISA 2018 results (volume II): Where all students can succeed. OECD Publishing . https://doi.org/10.1787/b5fd1b8f-en

OECD. (2019b). PISA 2018 results (volume III): What School Life means for Students`Lives. OECD Publishing . https://doi.org/10.1787/acd78851-en

Oliveira, W. A., Silva, J. L., Fernández, J. E. R., Santos, M. A. D., Caravita, S. C. S., & Silva, M. A. I. (2020). Family interactions and the involvement of adolescents in bullying situations from a bioecological perspective. Estudios de Psicología (Campinas) , 37 , 1–12. e180094.

Olweus, D. (1993). Bullying at School: What we know and what we can do . Blackwell Publisher.

Patton, D. U., Hong, J. S., Williams, A. B., & Allen-Meares, P. (2013). A review of research on school bullying among african american youth: An ecological systems analysis. Educational Psychology Review , 25 (2), 245–260. https://doi.org/10.1007/s10648-013-9221-7

Pellegrini, A. D., & Long, J. D. (2002). A longitudinal study of bullying, dominance, and victimization during the transition from primary school through secondary school. British Journal of Developmental Psychology , 20 (2), 259–280. https://doi.org/10.1348/026151002166442

Pozzoli, T., & Gini, G. (2012). Why do bystanders of bullying help or not? A Multidimensional Model. The Journal of Early Adolescence , 33 (3), 315–340. https://doi.org/10.1177/0272431612440172

Raboteg-Saric, Z., & Sakic, M. (2014). Relations of parenting styles and friendship quality to self-esteem, life satisfaction and happiness in adolescents. Applied Research in Quality of Life , 9 (3), 749–765. https://doi.org/10.1007/s11482-013-9268-0

Raskauskas, J. L., Gregory, J., Harvey, S. T., Rifshana, F., & Evans, I. M. (2010). Bullying among primary school children in New Zealand: Relationships with prosocial behaviour and classroom climate. Educational Research , 52 (1), 1–13. https://doi.org/10.1080/00131881003588097

Riffle, L. N., Kelly, K. M., Demaray, M. L., Malecki, C. E., Santuzzi, A. M., Rodriguez-Harris, D. J., & Emmons, J. D. (2021). Associations among bullying role behaviors and academic performance over the course of an academic year for boys and girls. Journal of School Psychology , 86 , 49–63. https://doi.org/10.1016/j.jsp.2021.03.002

Rigby, K. (2002). New perspectives on bullying . Jessica Kingsley Publishers.

Rivers, I., Poteat, V. P., Noret, N., & Ashurst, N. (2009). Observing bullying at school: The mental health implications of witness status. School Psychology Quarterly , 24 (4), 211–223. https://doi.org/10.1037/a0018164

Roland, E., & Idsøe, T. (2001). Aggression and bullying. Aggressive Behavior , 27 (6), 446–462. https://doi.org/10.1002/ab.1029

Saarento, S., Garandeau, C. F., & Salmivalli, C. (2015). Classroom- and school-level contributions to bullying and victimization: A review. Journal of Community and Applied Social Psychology , 25 (3), 204–218. https://doi.org/10.1002/casp.2207

Salmivalli, C. (2010). Bullying and the peer group: A review. Aggression and Violent Behavior , 15 (2), 112–120. https://doi.org/10.1016/j.avb.2009.08.007

Salmivalli, C., & Peets, K. (2008). Bullies, victims, and bully–victim relationships. In K. Rubin, W. Bukowski, & B. Laursen (Eds.), Handbook of peer interactions, relationships, and groups (pp. 322–340). Guilford Press.

Smith, P. K., López-Castro, L., Robinson, S., & Görzig, A. (2019). Consistency of gender differences in bullying in cross-cultural surveys. Aggression and Violent Behavior , 45 , 33–40. https://doi.org/10.1016/j.avb.2018.04.006

Sokol, N., Bussey, K., & Rapee, R. M. (2016). Teachers` perspectives on effective responses to overt bullying. British Educational Research Journal , 42 (5), 851–870. https://doi.org/10.1002/berj.3237

Tiliouine, H. (2015). School bullying victimisation and subjective well-being in Algeria. Child Indicators Research , 8 , 133–150. https://doi.org/10.1007/s12187-014-9286-y

Tippett, N., & Wolke, D. (2014). Socioeconomic status and bullying: A meta-analysis. American Journal of Public Health , 104 (6), e48–e59. https://doi.org/10.2105/AJPH.2014.301960

Troop-Gordon, W., & Ladd, G. W. (2015). Teachers’ victimization-related beliefs and strategies: Associations with students’ aggressive behaviour and peer victimization. Journal of Abnormal Child Psychology , 43 (1), 45–60. https://doi.org/10.1007/s10802-013-9840-y

Tsaousis, I. (2016). The relationship of self-esteem to bullying perpetration and peer victimization among schoolchildren and adolescents: A meta-analytic review. Aggression and Violent Behavior , 31 , 186–199. https://doi.org/10.1016/j.avb.2016.09.005

Ttofi, M. M., & Farrington, D. P. (2009). What works in preventing bullying: Effective elements of anti-bullying programmes. Journal of Aggression Conflict and Peace Research , 1 (1), 13–24. https://doi.org/10.1108/17596599200900003

Van der Kaap-Deeder, J., Vansteenkiste, M., Soenens, B., & Mabbe, E. (2017). Children’s daily well-being: The role of mothers’ teachers’, and siblings’ autonomy support and psychological control. Developmental Psychology , 53 (2), 237–251. https://doi.org/10.1037/dev0000218

Van Noorden, T. H. J., Haselager, G. J. T., Cillessen, A. H. N., & Bukowski, W. M. (2014). Empathy and involvement in bullying in children and adolescents: A systematic review. Journal of Youth and Adolescence , 44 , 637–657. https://doi.org/10.1007/s10964-014-0135-6

Varela, J. J., Guzmán, J., Alfaro, J., & Reyes, F. (2019). Bullying, cyberbullying, student life satisfaction and the community of chilean adolescents. Applied Research in Quality of Life , 14 (3), 705–720. https://doi.org/10.1007/s11482-018-9610-7

Varela, J. J., Sánchez, P. A., González, C., Oriol, X., Valenzuela, P., & Cabrera, T. (2021). Subjective Well-being, bullying, and School Climate among chilean adolescents over Time. School Mental Health , 13 , 616–630. https://doi.org/10.1007/s12310-021-09442-w

Waasdorp, T. E., Pas, E. T., O’Brennan, L. M., & Bradshaw, C. P. (2011). A multilevel perspective on the climate of bullying: Discrepancies among students, school staff, and parents. Journal of School Violence , 10 (2), 115–132. https://doi.org/10.1080/15388220.2010.539164

Wang, J., Iannotti, R. J., & Nansel, T. R. (2009). School bullying among adolescents in the United States: Physical, verbal, relational, and Cyber. Journal of Adolescent Health , 45 , 368–375.

Wang, X., Zhang, Y., Hui, Z., Bai, W., Terry, P. D., Ma, M., Li, Y., Cheng, L., Gu, W., & Wang, M. (2018). The Mediating Effect of Regulatory Emotional Self-Efficacy on the association between self-esteem and school bullying in Middle School students: A cross-sectional study. International Journal of Environmental Research and Public Health , 15 (5), 991. https://doi.org/10.3390/ijerph15050991

Wu, N., Hou, Y., Zeng, Q., Cai, H., & You, J. (2021). Bullying experiences and nonsuicidal self–injury among chinese adolescents: A longitudinal moderated mediation model. Journal of Youth and Adolescence , 50 , 753–766. https://doi.org/10.1007/s10964-020-01380-1

Zhang, H., Han, T., Ma, S., Qu, G., Zhao, T., Ding, X., Sun, L., Qin, Q., Chen, M., & Sun, Y. (2022). Association of child maltreatment and bullying victimization among chinese adolescents: The mediating role of family function, resilience, and anxiety. Journal of Affective Disorders , 299 , 12–21. https://doi.org/10.1016/j.jad.2021.11.053

Zhao, H., Gong, X., Huebner, E. S., Yang, X., & Zhou, J. (2022). Cyberbullying victimization and nonsuicidal self-injury in adolescents: Testing a moderated mediating model of emotion reactivity and dispositional mindfulness. Journal of Affective Disorders , 299 , 256–263. https://doi.org/10.1016/j.jad.2021.11.070

Zych, I., Farrington, D. P., & Ttofi, M. M. (2019). Protective factors against bullying and cyberbullying: A systematic review of meta-analyses. Aggression and Violent Behavior , 45 , 4–19. https://doi.org/10.1016/j.avb.2018.06.008

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Segovia-González, M., Ramírez-Hurtado, J.M. & Contreras, I. Analyzing the Risk of Being a Victim of School Bullying. The Relevance of Students’ Self-Perceptions. Child Ind Res 16 , 2141–2163 (2023). https://doi.org/10.1007/s12187-023-10045-x

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A comprehensive overview of current bullying prevention research conducted by government and higher education agencies.

Rates of Incidence

• One out of every five (20.2%) students report being bullied. ( National Center for Educational Statistics, 2019 )
• A higher percentage of male than of female students report being physically bullied (6% vs. 4%), whereas a higher percentage of female than of male students reported being the subjects of rumors (18% vs. 9%) and being excluded from activities on purpose (7% vs. 4%). ( National Center for Educational Statistics, 2019 )
• 41% of students who reported being bullied at school indicated that they think the bullying would happen again. ( National Center for Educational Statistics, 2019 )
• Of those students who reported being bullied, 13% were made fun of, called names, or insulted; 13% were the subject of rumors; 5% were pushed, shoved, tripped, or spit on; and 5% were excluded from activities on purpose. ( National Center for Educational Statistics, 2019 )
• A slightly higher portion of female than of male students report being bullied at school (24% vs. 17%). ( National Center for Educational Statistics, 2019 )
• Bullied students reported that bullying occurred in the following places: the hallway or stairwell at school (43%), inside the classroom (42%), in the cafeteria (27%), outside on school grounds (22%), online or by text (15%), in the bathroom or locker room (12%), and on the school bus (8%). ( National Center for Educational Statistics, 2019 )
• 46% of bullied students report notifying an adult at school about the incident. ( National Center for Educational Statistics, 2019 )
• The reasons for being bullied reported most often by students include physical appearance, race/ethnicity, gender, disability, religion, sexual orientation. ( National Center for Educational Statistics, 2019 )
• The federal government began collecting data on school bullying in 2005, when the prevalence of bullying was around 28 percent. ( U.S. Department of Education, 2015 )
• One in five (20.9%) tweens (9 to 12 years old) has been cyberbullied, cyberbullied others, or seen cyberbullying. ( Patchin & Hinduja, 2020 )
• 49.8% of tweens (9 to 12 years old) said they experienced bullying at school and 14.5% of tweens shared they experienced bullying online. ( Patchin & Hinduja, 2020 )
• 13% of tweens (9 to 12 years old) reported experiencing bullying at school and online, while only 1% reported being bullied solely online. ( Patchin & Hinduja, 2020 )

Effects of Bullying

• Students who experience bullying are at increased risk for depression, anxiety, sleep difficulties, lower academic achievement, and dropping out of school. ( Centers for Disease Control, 2019 )
• Students who are both targets of bullying and engage in bullying behavior are at greater risk for both mental health and behavior problems than students who only bully or are only bullied. ( Centers for Disease Control, 2019 )
• Bullied students indicate that bullying has a negative effect on how they feel about themselves (27%), their relationships with friends and family (19%), their school work (19%), and physical health (14%). ( National Center for Educational Statistics, 2019 )
• Tweens who were cyberbullied shared that it negatively impacted their feelings about themselves (69.1%), their friendships (31.9%), their physical health (13.1%), and their schoolwork (6.5%). ( Patchin & Hinduja, 2020 ).
• Among students ages 12 – 18 who reported being bullied at school, 15% were bullied online or by text ( National Center for Educational Statistics, 2019 )
• Reports of cyberbullying are highest among middle school students, followed by high school students, and then primary school students ( Centers for Disease Control, 2019 )
• The percentages of individuals who have experienced cyberbullying at some point in their lifetimes have more than doubled (18% to 37%) from 2007-2019 ( Patchin & Hinduia, 2019 )
• When students were asked about the specific types of cyberbullying they had experienced, mean and hurtful comments (25%) and rumors spread online (22%) were the most commonly-cited ( Patchin et al., 2019 )
• The type of cyberbullying tends to differ by gender. Girls were more likely to say someone spread rumors about them online while boys were more likely to say that someone threatened to hurt them online ( Patchin et al., 2019 )

Cyberbullying Among Tweens (9-12 Years Old)

• One in five tweens (20.9%) has been cyberbullied, cyberbullied others, or seen cyberbullying
• 49.8% of tweens said they experienced bullying at school and 14.5% of tweens shared they experienced bullying online
• 13% of tweens reported experiencing bullying at school and online, while only 1% reported being bullied solely online
• Nine out of ten tweens use social media or gaming apps (Patchin & Hinduja, 2020)
• Tweens shared they were engaging on the following sites, apps, or games: YouTube, Minecraft, Roblox, Google Classroom, Fortnite, TikTok, YouTube Kids, Snapchat, Facebook Messenger Kids, Instagram, Discord, Facebook, and Twitch
• Tweens who were cyberbullied shared that it negatively impacted their feelings about themselves (69.1%), their friendships (31.9%), their physical health (13.1%), and their schoolwork (6.5%)
• Tweens reported using a variety of strategies to stop the bullying including blocking the person bullying them (60.2%), telling a parent (50.8%), ignoring the person (42.8%), reporting it to the website or app (29.8%), and taking a break from the device (29.6%)
• Two-thirds of tweens are willing to step in to defend, support, or assist those being bullied at school and online when they see it
• Barriers to helping when tweens witness bullying at school or online included being afraid of making things worse, not knowing what to do or say, not knowing how to report it online, being afraid others kids will make fun of them, being afraid to get hurt, and not knowing who to tell

SOURCE: Patchin, J.W., & Hinduja, S. (2020). Tween Cyberbullying in 2020. Cyberbullying Research Center and Cartoon Network. Retrieved from: https://i.cartoonnetwork.com/stop-bullying/pdfs/CN_Stop_Bullying_Cyber_Bullying_Report_9.30.20.pdf.

Bullying of Students with Disabilities

• Students with specific learning disabilities, autism spectrum disorder, emotional and behavior disorders, other health impairments, and speech or language impairments report greater rates of victimization than their peers without disabilities longitudinally and their victimization remains consistent over time ( Rose & Gage, 2016 )

Bullying of Students of Color

• 23% of African-American students, 23% of Caucasian students, 16% of Hispanic students, and 7% of Asian students report being bullied at school ( National Center for Educational Statistics, 2019 )

Bullying of Students Who Identify or Are Perceived as LGBTQ

Bullying and suicide, interventions.

• Tweens reported using a variety of strategies to stop the bullying including blocking the person bullying them (60.2%), telling a parent (50.8%), ignoring the person (42.8%), reporting it to the website or app (29.8%), and taking a break from the device (29.6%) ( Patchin & Hinduja, 2020 ).
• Two-thirds of tweens are willing to step in to defend, support, or assist those being bullied at school and online when they see it ( Patchin & Hinduja, 2020 ).
• Barriers to helping when tweens witness bullying at school or online included being afraid of making things worse, not knowing what to do or say, not knowing how to report it online, being afraid others kids will make fun of them, being afraid to get hurt, and not knowing who to tell ( Patchin & Hinduja, 2020 ).

References:

Centers for Disease Control, National Center for Injury Prevention and Control (2019). Preventing bullying. Retrieved from https://www.cdc.gov/violenceprevention/pdf/yv/bullying-factsheet508.pdf .

National Center for Educational Statistics. (2019). Student reports of bullying: Results from the 2017 School Crime Supplement to the National Victimization Survey. US Department of Education. Retrieved from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2015056 .

Patchin, J. W., & Hinduja, S. (2019). 2019 Cyberbullying Data. Cyberbullying Research Center. Retrieved from https://cyberbullying.org/2019-cyberbullying-data .

Patchin, J.W., & Hinduja, S. (2020). Tween Cyberbullying in 2020. Cyberbullying Research Center and Cartoon Network. Retrieved from: https://i.cartoonnetwork.com/stop-bullying/pdfs/CN_Stop_Bullying_Cyber_Bullying_Report_9.30.20.pdf .

Rose, C. A., & Gage, N. A. (2016). Exploring the involvement of bullying among students with disabilities over time. Exceptional Children, 83 , 298-314. Retrieved from http://journals.sagepub.com/doi/abs/10.1177/0014402916667587 .

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A Multilevel Analysis of Factors Influencing School Bullying in 15-Year-Old Students

Yu-jiao wang.

1 School of Education Science, Liupanshui Normal University, Liupanshui 553004, China

2 Chinese Academy of Education Big Data, Qufu Normal University, Qufu 273100, China

Associated Data

The original data of the study can be found in the website https://www.oecd.org/pisa/data/2018database/ (accessed on 15 October 2021).

Background: School bullying causes serious impacts on adolescents’ physical and mental health. Few studies have explored the various factors influencing bullying by combining different levels of data. Methods: Based on the database of four Chinese provinces and cities of the Program for International Student Assessment (PISA) in 2018, this study used a multilevel analysis model that combined school-level variables and student-level variables to explore the influencing factors of students being bullied. Results: Students’ gender, grade repetition, truancy and arriving late for class, economic, social, and cultural status (ESCS), teacher support, and parent support had significant explanatory power on school bullying on the student-level; on the school-level, school discipline atmosphere and competitive atmosphere among students had significant impacts on school bullying. Conclusions: Boys, students who have repeated grades, truancy and arriving late for class, and students with lower ESCS suffer from more severe school bullying. When developing school bullying interventions, teachers and parents should pay more attention to those students and provide more emotional support and encouragement to them. Meanwhile, students in schools with a lower discipline atmosphere and a higher level of competitive atmosphere experience greater levels of bullying, and schools should create more positive and friendly environments to prevent bullying events.

1. Introduction

In the 1980s, a young Norwegian boy committed suicide after suffering school bullying; since then, school bullying has begun to enter the field of researchers and has become an important research topic [ 1 ]. Nowadays, it is receiving more and more attention from many international organizations. Among the research topics related to school bullying, the primary focuses include the following: What characteristics cause individuals to be more likely to suffer from school bullying? Why are individuals with these characteristics easily bullied by others? What are the factors that cause bullying in schools? These issues have always been topics of great concern to researchers both nationally and worldwide.

Previous studies have shown that various types of factors affect students’ exposure to bullying, including individual characteristics, schools, and families [ 2 , 3 , 4 , 5 , 6 , 7 ]. Ruan examined the influencing factors of student suffering from school bullying through factor analysis and logistic regression [ 2 ]. The results showed that, from the cross-sectional dimension analysis, the ranking of factors was as follows: students’ individual characteristics, schools’ background features, and emotional support.

From a logistic regression of the longitudinal section, among the students’ background characteristics, boys were more likely to suffer from school bullying than girls; senior students were more likely to suffer from bullying than those in lower grades; and students with lower academic performance scores were more likely to suffer from school bullying than those with higher scores [ 2 ]. However, some studies have found different results. Regarding age, for example, Rigby and Slee found that younger children were more likely to experience bullying than older children [ 8 ]. With age increase, bullying tended to stop; the reason for this may be because individuals acquire more social skills that improve self-esteem [ 9 ].

In terms of school background characteristics, Ruan’s analysis showed that, compared with urban schools, students in rural schools suffered more school bullying; students in private schools suffered more school bullying than those in public schools; the more repeating students on a campus, the higher the proportion of school bullying, and the better the school discipline atmosphere, the fewer the bullying incidents [ 2 ]. Lastly, the class size, school size, and teacher–student ratio of a school’s background characteristics had no significant impact on students’ school bullying [ 2 ]. Contrary to Ruan’s results, however, Huang’s study found that school location (urban or rural) and school type (public or private) had no effect on students’ school bullying [ 5 ].

In addition, teacher support plays a very important role in school background characteristics. Effective teacher support greatly reduces the occurrence of school bullying, but if teachers treat students unfairly, it may increase the occurrence [ 5 ]. Regarding the home environments of school bullies and victims, children who perpetrated bullying reported that their parents did not exercise caring and supervisory functions, sometimes even neglecting them [ 7 ]. This is in contrast to the home environments of bullying victims, who had very close relationships with their parents and were, therefore, vulnerable to overprotection. In addition, Fu et al. pointed out that students from families with lower socioeconomic statuses were more likely to be victims of more severe types of bullying, as school is an integral indicator of social stratification [ 10 ]. Parental emotional support was an important family factor affecting students’ suffering from school bullying, and insufficient parental emotional support was an important reason why many young people suffered from school bullying and could not cope effectively [ 5 ].

In conclusion, it can be seen that school bullying is affected by various factors of individuals, families, and schools, but there have been some contradictions among past studies, such as age and school type, which may be related to sampling or research methods. In addition, few studies have explored the various factors influencing bullying by combining different levels of data. When discussing this topic, these influencing factors should be considered comprehensively, but different levels cannot be analyzed at the same level, which leads to analytical bias. When facing these data from different sources, a multilevel analysis method should be used for an accurate analysis.

The Program for International Student Assessment (PISA), which was first implemented by the Organization for Economic Cooperation and Development (OECD) in 2000, added a survey of students’ experiences of bullying in schools for the first time in 2015, including three types of bullying: relational bullying, verbal bullying, or physical bullying. In 2018, PISA continued to conduct a school-bullying survey in 75 countries and regions, showing the close concern that educators around the world have toward the problem. School bullying should be a high-priority concern for education policy makers and school administrators. Moreover, the PISA data includes those from both the students and the schools, which meets the requirements of multi-level analysis.

Therefore, based on the survey data of PISA 2018, our study used a multilevel analysis model and combines school-level and student-level variables to jointly explore various factors affecting school bullying and reveal the specific causes behind this phenomenon. Individual level variables included school bullying (including total school bullying, relational bullying, verbal bullying, and physical bullying), students’ gender, grade, education type, grade repetition, truancy and arriving late for class, family economic, social, and cultural status (ESCS), teacher support, and parent support they perceived, some of which were discussed above. School level variables included the describing characteristics of schools, such as school location, school type, school size, or school atmosphere, etc. The purpose of this paper is to investigate whether these factors have impacts on students’ bullying and what the effect of the impact is.

2. Materials and Methods

2.1. materials.

The data for this study came from the PISA 2018 survey database of four provinces and cities in mainland China (Beijing, Shanghai, Jiangsu, and Zhejiang). First, we downloaded the 2018 global Student questionnaire data file and School questionnaire data file from the PISA website https://www.oecd.org/pisa/data/2018database/ (accessed on 15 October 2021). For a brief introduction to PISA and descriptions of the questionnaires, see Appendix A . Then, we selected the data for mainland China. The student questionnaire data of mainland China includes 12,058 middle school students aged 15 (from 15 years and 3 months to 16 years and 2 months), and the school questionnaire data includes 361 schools. Finally, after deleting samples with missing data and those unable to meet the statistical criteria, the sample size of this study was 11,497 students from 334 schools (see Appendix A for detailed standards and procedures).

2.2. Research Variables

The variables of our study included individual-level variables of students and environment-level variables of school.

The student-level variables included the following: suffering from school bullying (including total school bullying, relational bullying, verbal bullying, and physical bullying), which was the outcome variable of the study; gender, grade, education type, grade repetition, truancy and arriving late for class, family economic, social, and cultural status (ESCS, teacher support, and parent support, which were predictor variables.

The school-level variables were divided into two categories. One was variables derived from the group level describing the characteristics of the schools, including school location, school type, school size, class size, student–teacher ratio, proportion of boys, proportion of special needs students, proportion of students without graduation certificates, student behaviors that hindered learning, and teacher behaviors that hindered learning. All of the above variables were completed by the principal (or principal representative) of each school. The other type was variables based on shared constructs, in which group characteristics were derived from combinations of group members and contained the attitudes, perceptions, or behaviors of group members. The variables were taken from student questionnaires, but they were aggregated by group, averaged, and then integrated into group variables, including school discipline atmosphere, competitive atmosphere among students, and cooperative atmosphere among students. See Appendix B for question descriptions, original corresponding items, and coding of these variables. Descriptive statistics of the above variables are shown in Table 1 .

Descriptive statistics of the variables.

1 For categorical variables, the Average refers to the percentage of the latter category in each variable. For example, for Gender, 0.521 represents that the proportion of male students is 52.1%; for Grade repetition, 0.063 represents that the proportion of students’ repeating grade is 6.3%; and for School type, 0.140 represents that the proportion of private schools is 14%. Other categorical variables are similarly interpreted.

2.3. Statistical Analyses

The statistical software packages used in this study were SPSS 24 and HLM 6.08. The statistical methods included reliability and validity tests, a regression analysis, and a multilevel model analysis.

In many social science research fields, such as psychology, education, and management, data are often in nested structures (nested data, multilayer data, or multilevel data) where, for example, students are nested under a class, and the class is under the school. The sample data from such nested structures are generally not independent, which violates traditional statistical assumptions (residual independence and a homogeneous regression slope). Using a traditional OLS regression method to analyze nested samples and, thus, ignoring the problem of hierarchical differences can bring about statistical estimation bias. If the conclusions obtained from a high-level data analysis are inferred with lower-level data, it is easy to overestimate the lower-level conclusions, resulting in “ecological fallacy”. Conversely, if the conclusions obtained from a lower-level data analysis are inferred with higher-level data, this leads to “atomistic fallacy” [ 11 ]. Therefore, it is very important to understand the variation caused by different groups using a multilevel analysis method.

An analysis for nested data has been gradually developed, and finally in the 1990s, a complete and systematic theory and method was developed, namely the multilevel model analysis or multilevel analysis (HLM); in addition, HLM software was designed for multilevel analyses. Using the multilevel analysis method enables the analysis of multilevel data in one model at the same time, reducing the statistical errors mentioned above, and it can analyze the possible interactions between different levels’ data, describing the characteristics of a phenomenon more objectively. In this study, using HLM software, we combined school-level variables and student-level variables to explore the influencing factors that affected school bullying and attempted to reveal the specific causes behind this phenomenon.

A structure diagram of this study is shown in Figure 1 .

The structure of the study.

As suggested by Bryk and Raudenbush [ 12 ], a multilevel analysis should include the implementation of four sub-models: Null Model, Random Coefficient Model, Intercepts as Outcomes Model, and Slopes as Outcomes Model. Since our study did not specifically explore the moderating effects of the school-level contextual variable group, Slopes as Outcomes Model was not performed. Therefore, this study analyzed three multilevel models (see Table 2 for total school bullying): Model I (Null Model) was used to test the proportion of group variation to the overall variance in student suffering from school bullying and to three different types of bullying (that is, the contextual effect between different schools), which provided a reasonable basis for a subsequent multilevel analysis to confirm the intraclass correlation coefficient (ICC) of the dependent variable, and the between-group variation component could meet the requirements for performing a multilevel model analysis. Model II (Random Coefficient Model) was used to test the direct impacts of student-level variables on school bullying. Model III (Intercepts as Outcomes Model) was used for testing the direct impacts of school-level variables on school bullying. Model III was the full model for this study.

Multilevel analysis results of the influencing factors of students suffering from school bullying.

3.1. Model I: Null Model

No explanatory variables were included in the Null Model; instead, it only contained the result variables, and the corresponding formula is shown in Appendix C .

As shown in the results of Table 2 , the between-group variation component (τ 00 ) of suffering from school bullying was significantly different from 0 (χ 2 = 444.065, p < 0.001), indicating that the degree of student suffering from school bullying in the same school was similar, but there were significant differences in different schools. Similarly, as shown in Table A1 , Table A2 and Table A3 (these three tables can be seen in Appendix C ), the between-group variance components (τ 00 ) of relational bullying (χ 2 = 409.931, p = 0.003), verbal bullying (χ 2 = 387.921, p = 0.020), and physical bullying (χ 2 = 470.758, p < 0.001) were also significantly different from 0. These results illustrate that the variation between groups could not be ignored. In order to avoid biased interpretation of the results, it was necessary to use the multilevel model for data analysis.

3.2. Model II: Random Coefficient Model

In this model, the student-level variables are not uncentered, with the exception of grades, teacher support, and parent support, which were generally grand-centered. Kreft pointed out that categorical variables must not be mean centered [ 13 ]. If a continuous variable is meaningful for 0, it does not need to be centered because, whether it is centered or not, it has no effect on the estimated value and significance but only affects the interpretation of the results. To make an interpretation meaningful, it needed to be mean-centered in both Level 1 (student-level) and Level 2 (school-level) and always use grand-centered variables which is equivalent to the original data, while group-centered variables are not equivalent to the original data [ 13 ]. The corresponding formula is shown in Appendix C .

From the results in Table 2 , it can be seen that, in addition to grade and education type, gender, grade repetition, and truancy and arriving late for class at the individual level all had significant positive explanatory powers on students’ total school bullying. Both teacher support and parent support have significant negative explanatory powers on students’ total school bullying.

Similarly, relational bullying, verbal bullying, and physical bullying showed the same effects, as shown in Table A1 , Table A2 and Table A3 (these three tables can be seen in Appendix C ). When teacher support increased by 1, total school bullying decreased by 0.562, relational bullying decreased by 0.195, verbal bullying decreased by 0.180, and physical bullying decreased by 0.188. When parent support increased by 1, total school bullying decreased by 0.391, relational bullying decreased by 0.142, verbal bullying decreased by 0.133, and physical bullying decreased by 0.117. Lastly, ESCS only had a significant negative explanatory power on students suffering from total school bullying and physical bullying but had no significant effect on relational bullying and verbal bullying. When family ESCS increased by 1, total school bullying decreased by 0.066, and physical bullying decreased by 0.042.

The above results indicate that boys suffered from a greater degree of school bullying than girls (including total school bullying and three types of bullying), and students who repeated grades, were truant, and arrived late in the past two weeks were more severely bullied than those who had not. The lower the student family ESCS is, the higher the levels of school bullying and physical bullying are. The lower students perceived teacher support and parent support, the more severe the school bullying.

3.3. Model III: Intercepts as Outcomes Model

In this model, with the exception of the variables of school location, school type, proportion of special needs students, and proportion of students without graduation certificates being uncentered, all the other variables were grand-centered.

The results in Table 2 and Table A1 , Table A2 and Table A3 (these three tables can be seen in Appendix C ) show that only the two variables of school discipline atmosphere and competitive atmosphere among students had a significant impact on student suffering from total school bullying and three other types of bullying. The variable of school discipline atmosphere had a significant negative explanatory power on the degree of student suffering from bullying, while the variable of competitive atmosphere among students had a significant positive explanatory power on the degree of student suffering from bullying. The analysis results of Model III show that, when the school discipline atmosphere increased by 1, school bullying decreased by 0.572, relational bullying decreased by 0.198, verbal bullying decreased by 0.143, and physical bullying decreased by 0.231. However, when the variable of competitive atmosphere among students increased by 1, school bullying increased by 0.806, relational bullying increased by 0.263, verbal bullying increased by 0.289, and physical bullying increased by 0.245.

These results indicate that the worse a school’s discipline atmosphere is, the more severe the level of school bullying students experienced is, i.e., students in schools with poor discipline atmospheres experienced a greater degree of school bullying than those in schools with better discipline atmospheres. However, the higher the competitive atmosphere among students is, the higher the level of school bullying students experienced is, i.e., students in schools with high inter-student competition atmospheres experienced greater levels of bullying than those in schools with low inter-student competition atmospheres.

The remaining variables of school background characteristics all did not have significant impacts on students’ suffering from school bullying or the three other types of bullying.

4. Discussion

4.1. influence of student-level variables on students being bullied.

According to the results in Model II, in addition to grade and education type, the student-level variables of gender, grade repetition, and truancy and arriving late for class all have significant positive effects on total school bullying and the three types of bullying, while teacher support and parents’ support both have significant negative explanatory power on students’ total school bullying and the three types of bullying. ESCS only negatively affects students’ total school bullying and physical bullying but not relational bullying and verbal bullying. The results above show that boys suffer from a greater degree of school bullying than girls, and students who have repeated grades, who are truant, and who have been late for class in the past two weeks are more severely bullied than those who have not. The lower the family’s ESCS is, the higher the level of total school bullying and physical bullying are. The lower the perceived teacher support and parents support are, the more severe the school bullying is. The above results are discussed further below.

First, in our study, we found that boys suffered more severe bullying than girls, both for total school bullying and for the three different types of bullying, which is partly consistent with previous studies. Previous studies have confirmed that boys are at greater risk of school bullying than girls [ 8 , 14 ]. In terms of different types of bullying, previous studies have found that girls are more susceptible to relational bullying [ 15 ], and data from OECD countries also show that girls are more likely to be exposed to “spreading rumors by other students” [ 16 ], while boys are more likely to suffer from physical bullying [ 17 ]. Based on the data analysis of PISA 2015, Huang found that boys were more prone to physical bullying than girls [ 5 ], such as physical hitting or pushing. In addition, boys were also more likely to experience verbal bullying than girls, such as being teased by others. In summary, boys are at greater risk of bullying than girls. The reason for this may be that boys are more prone to agitation and conflict than girls, which makes boys significantly more likely than girls to be bullied or to bully others. Therefore, we should pay more attention to the male group and give them more help related to the phenomenon of bullying.

Second, our study found that students who repeated grades, had absenteeism, and were late to class within the last two weeks were more likely to be bullied at school. In addition to poor academic performance, repeat-grade students may also have difficulties with the development of social and emotional skills. When these older students study and live with new, younger classmates, they may be very easily discriminated against, laughed at, or teased by other students and may even be socially excluded [ 18 ], which may, in turn, lead to bullying incidents [ 19 ]; this is similar for students with absenteeism and lateness. According to previous studies, disciplinary violations such as those for truancy, skipping class, and lateness may be external manifestations of students rejecting learning. If students are unwilling to enter a classroom, or even skip class, it is naturally difficult for them to achieve good academic performances [ 20 ], while students with poor academic performances are more likely to be bullied, which has been confirmed by previous research [ 10 , 21 ]. On the other hand, those who are bullied protect themselves by avoiding school or being truant, and then these truant students have more difficulties keeping up with teaching or are unable to obtain help from the school due to not showing up to school on time. This also weakens the connection between students and the school environment, leading to poor academic achievement [ 22 , 23 ]. Therefore, there may be a mutual causal relationship between truancy, absenteeism, lateness, and other disciplinary violations and students being bullied on campus. To reduce bullying on campus, educators can start with the strict management of students’ disciplinary violations to ensure that students can attend school on time because this is a premise to ensure quality of learning. In this way, it is possible to improve their academic achievements and help them establish a close relationship with the school, making it easier to seek help from teachers and classmates, which is conducive to reducing the occurrence of bullying.

Furthermore, the results show that students’ ESCS had a significant negative impact on students’ total school bullying and physical bullying, which meant that the lower a student’s family economic sociocultural status is, the higher the degrees of overall school and physical bullying is. This result is consistent with the results of Huang and Zhao [ 23 ], as well as empirical research from the Netherlands, which showed that adolescents with lower social status had a higher proportion of physical and psychological symptoms, which were more likely to be aggression by peers [ 24 ]. Therefore, schools and teachers should pay more attention to students from disadvantaged backgrounds and carry out targeted psychological counseling and assistance to reduce the risk of bullying for these students.

Finally, this study found that the higher the levels of teacher support and parent support perceived by students are, the lower the level of suffered school bullying is. A close parent–child relationship can help students obtain more help when they suffer from school bullying, and parents who care about and support their children emotionally can not only help their children decrease school bullying but can also relieve children’s psychological pressure and pain after students are bullied [ 25 ]. In terms of teacher–student relationships, teachers’ actions of supporting, caring about students’ academic progress, and expecting students’ success make students feel accepted, respected, and cared for. On the one hand, students can better seek help from teachers; on the other hand, closeness and harmony of teacher–student relationships greatly reduces the chance of negative interpersonal behaviors, such as bullying [ 26 ]. Thus, both families and schools are key forces to fight against school bullying, and home–school cooperation can better build antibullying barriers in students’ lives and learning.

In conclusion, when developing school bullying interventions, more attention should be paid to male students, students who repeat grades, are late, or are absent from class, and students with lower ESCS. For example, physical bullying of male students should be paid concern. Pushing, beating, and other similar behaviors should be stopped in time. As for students with low academic performance, parents should encourage and support their children rather than criticize and blame them. Teachers should also pay more attention to students who are often late, absent, or from lower backgrounds and should strengthen their ability to recognize bullying incidents, especially the two types of relationship bullying and verbal bullying, because they will not cause obvious physical harm, making it very difficult to identify. In addition, teachers can pay close attention to the way students make friends and interact with each other. They can observe whether a particular student is excluded or isolated in group activities, PE class, and after class. Once they find signs of bullying, appropriate treatment should be provided the first time to prevent the occurrence of the event. Finally, teachers should consult more professional counselors, attend seminars on school bullying cases, and flexibly use effective ways to deal with bullying cases to reduce the harm caused by bullying.

4.2. Influence of School-Level Variables on Students Being Bullied

The results of Model III show that only the school discipline atmosphere and the competitive atmosphere among students of the school environment level variables have significant impacts on the total school bullying and the three types of bullying. School discipline atmosphere has a significant negative explanatory power on school bullying, while the competitive atmosphere among students has a significant positive explanatory power on students being bullied, indicating that students in schools with a worse discipline atmosphere experience greater levels of bullying than students in schools with a better one; students in schools with a high level of inter-student competition are more likely to experience higher levels of school bullying than those in schools with a lower level. A good school discipline atmosphere helps protect students and make them less vulnerable to school bullying [ 23 ], but the competitive atmosphere among students may make some students feel jealous or hate other classmates, which in turn increases the chances of students being bullied at school.

First, the negative correlation between school disciplinary atmosphere and students suffering from bullying has been confirmed by some studies [ 2 , 18 , 27 ]. A good school discipline atmosphere helps to protect students and make them less vulnerable to school bullying [ 23 ]. The reason for this may be because when students learn and interact in a well-ordered environment, they are often more willing to engage in it because they feel safe, and the trigger factors for student aggressive behavior are greatly reduced [ 28 ]. Therefore, when formulating plans to prevent school bullying at the school level, more consideration should be given to the important role of school disciplinary atmosphere, which is not only an invisible school culture but also can be reflected in the implementation of school rules and discipline. In addition, this is also consistent with strengthening the management of skipping class, truancy, lateness, and other disciplinary violations mentioned above.

Second, atmospheres of competition and cooperation among students in schools are important aspects of the school climate [ 29 ]. This is the first time that this topic has appeared in the PISA questionnaire survey. The results show that competitive atmosphere had a significant positive explanation for the degree of school bullying. However, cooperative atmosphere did not have a significant impact on student suffering from school bullying. This is an interesting result, suggesting that competitive and cooperative atmospheres at the school level may not be two opposing aspects, and they may have their own working principles.

The positive association between perceived competitive atmosphere and school bullying has been supported by some studies. Volk proposed that a competitive atmosphere may make some students feel jealous or hateful toward other classmates, which in turn increases the chances of students being bullied at school [ 30 ]. Wang’s research showed that both academic competition and social competition perceived by primary and secondary school students were significantly positively correlated with school bullying [ 31 ]. In another research project, Wang proposed that a vicious, competitive atmosphere formed among students not only led to campus bullying [ 32 ] but also generated countless indifferent bystanders who saw the campus bullying but were unwilling to lend a helping hand. Therefore, when intervening in bullying in schools, students should be consciously guided to engage in positive and benign competition and to avoid vicious competition. In this way, good peer relationships in the school environment form, and the occurrence of bullying is reduced.

Finally, a surprising result in our study is that student behaviors and teacher behaviors that hinder learning in schools both had no effect on students’ experiences of school bullying. A previous study regarded these two variables as a measure of school spirit [ 33 ]. Through a multilevel analysis based on PISA 2015 data from four provinces and cities in China, the study found that student and teacher behaviors that hindered learning had significant negative impacts on students’ scientific literacy without controlling for student and school ESCS values; however, when controlling for them, the effects were smaller and no longer significant. Due to the large number of control variables involved in our study and different combinations of control variables producing various different results, this part may therefore need to be further explored in future studies.

Here are some suggestions on the results. Students spend a lot of time in school. As an important place of education, school plays a decisive role in the formation of students’ personality and behavior. When the school atmosphere is positive and friendly, bullying can be reduced. Schools should instruct students to learn ways to protect themselves, identify bullying in schools, and seek help from teachers and classmates to better protect themselves. Schools should strengthen the moral education of students and cultivate students’ good sense of justice and moral sense, making students brave enough to stop school bullying or report bullying to teachers.

The psychological counseling institution of schools should play an active role in school bullying and treat every bullying case as a major campus crisis. In addition to isolation, placement, and counseling, it is important to continuously observe and follow up the development of physical and mental status of the cases, both of the perpetrator and the victim, making sure they are physically and mentally healthy. In addition, schools should strengthen students’ interpersonal communication and life education. Students must learn to respect each other’s lives and cherish their own. They must understand that certain behaviors should not be allowed, such as making fun of each other’s sexual orientation and physical characteristics. It must be made clear that students’ bullying behavior may directly or indirectly kill their classmates. When students are aware that bullying can have such serious consequences, it may be effective in reducing the incidence of school bullying.

At last, bullying should not be seen as a problem of a few but as one of society’s problems. The whole society should work together to create a friendly campus environment. Education authorities should integrate schools, neighboring communities, police and government organs, social welfare organizations, mental health units and other relevant social resources, and professional assistance to provide students with the most appropriate treatment. In order to prevent bullying, teachers and schools are encouraged to make more use of social resources. A variety of professional teams, including school principals, directors, tutors, psychological consultants, students, parents, juvenile police officers, social workers of welfare organizations, and other experts should work together to investigate, evaluate, and formulate counselling programs to effectively reduce bullying incidents in schools.

4.3. Limitations and Future Research Directions

Because the selected variables were all obtained from the PISA test and were limited by the scope of the database, our study may not contain all the factors that affect students’ experiences of school bullying. In follow-up research, other methods, such as using other databases or questionnaires made by the researchers themselves, should be used to include more influence factors to analyze this topic. In addition, some factors in our study were not obviously related to school bullying, such as grade and education type of student-level, student behaviors and teacher behaviors that hindered learning, and cooperative atmosphere among students of school-level, so more rigorous field investigations may be needed [ 34 ].

Furthermore, regarding the multilevel analysis model, the analysis method of a multi-level mediation model can also be considered to further elaborate the specific operation paths of these influencing factors [ 35 ]. A multilevel mediation model can set the possible influence paths for factors that were found to have significant explanatory power based on the existing research so that all the independent variables can be included in the model at one time. It can provide more specific reference information for educational administrators and can broaden the scope of related research topics, providing more theoretical significance.

5. Conclusions

Based on the PISA 2018 survey data (including student data and school data) and using a multilevel analysis model, this study explored the impacting factors that affected school bullying. While the results are consistent with some previous studies, there are some new developments.

In the student-level variables, boys, students who have repeated grades, who are truant, and who have been late for the class in the past two weeks, and students whose economic, social, and cultural status is lower suffer from more severe school bullying. Furthermore, students who have perceived lower teacher support and parents support are more severely bullied than those who have not. Thus, when developing school bullying interventions, more attention should be paid to these students. Teachers and parents should give more emotional support to them. Additionally, school administrators, consulting teachers, and other relevant personnel should pay more attention to students. Once they find signs of bullying, appropriate treatment should be provided the first time to prevent the occurrence of the event.

In the school-level variables, students in schools with a worse discipline atmosphere and a higher level of inter-student competitive atmosphere experience greater levels of bullying. Therefore, when formulating plans to prevent school bullying at the school level, more consideration should be given to the important role of strengthening school disciplinary atmosphere and reducing the competitive atmosphere. A safe, well-ordered, positive, and friendly school environment helps protect students and make them less vulnerable to school bullying, and the establishment of such a campus environment needs the efforts of the whole society.

Acknowledgments

We sincerely appreciate the open access data provided by the PISA tests administered by OECD. We would also like to take this opportunity to express heartfelt gratitude to three anonymous reviewers for their positive suggestions and constructive comments which were very helpful in making appropriate corrections and modifications. Additionally, we appreciate the time and detail provided by each editor.

Appendix A.1. The Introduction to PISA and Descriptions of Student and School Questionnaires

The data materials of this study come from the PISA 2018 survey database. The Program for International Student Assessment (PISA), implemented by the Organization for Economic Cooperation and Development (OECD), mainly tests the levels of reading, math, and science of 15-year-old middle school students to evaluate the degree of their knowledge and skills which are necessary to fully participate in modern social and economic life. This assessment not only confirms whether students can replicate knowledge but also the extent to which they can extrapolate from what they have learned and apply it to unfamiliar situations in and outside of school, i.e., their abilities to use these knowledge and skills to deal with real-life challenges.

The first PISA test was conducted in 2000 and has been conducted every three years. In each round of PISA, students are tested in detail in one of the three core school subjects of reading, math, and science. According to this schedule, a comprehensive performance analysis is conducted every nine years for each of the three core themes. The latest data are the seventh assessment of 2018, which should be conducted in 2021, but because of the influence of COVID-19, “OECD member countries and Associates decided to postpone the PISA 2021 assessment to 2022 and the PISA 2024 assessment to 2025 to reflect post-COVID difficulties ( https://www.oecd.org/pisa ) (accessed on 15 October 2021)”. Due to the time of the implementation process, the most recent data available for analysis are still from 2018.

In addition to the tests in reading, math, and science, students also fill in a background questionnaire that collects their family background and school information, including their attitudes, personalities, and beliefs and their family, school, and learning experiences. Many issues of public concern have also been added to the survey of this project in recent years. In 2015, the survey of school bullying was added to the questionnaire. In 2018, the school bullying survey was continued, and attitudes towards school bullying was added.

Furthermore, the students’ parents, teachers, and school principals or leaders they studied are also included in the program. The school principal or leader completed a questionnaire covering the school’s management, organization, and learning environment. Therefore, the content of PISA is very broad. Since its first implementation in 2000, it has attracted the participation of more than 90 countries. A total of more than 3 million students worldwide have participated in the program which has very comprehensive educational data of students worldwide.

Appendix A.2. The Procedure of Data Collection

The PISA 2018 data comes from 75 countries and economies around the world and is aimed at 15-year-old students in grade 7 and above in educational institutions. The sampling design used for the PISA assessment is a two-stage stratified sample design.

The sampling unit of the first stage is schools with 15-year-old students. Schools were sampled systematically from a comprehensive national list of all PISA-eligible, known as the school sampling frame. This type of sampling is known as systematic probability proportional to size (PPS) sampling. Prior to their selection, schools in the sampling frame were assigned to mutually exclusive groups based on school characteristics called explicit strata. These methods were developed to improve the accuracy of sample-based estimates.

The sampling unit of the second stage is students in the sampled schools. Once schools have been selected for the sample, a full list of 15-year-olds from each school sampled will be prepared. Each country/economy participating in computer-based assessment (CBA) and Global Competency (GC) must set a target cluster size (TCS) of 42 students. Countries/economies participating in the paper-based assessment (PBA) and CBA countries/economies without GC set a TCS of 35. For lists with fewer than the target number of students, all students on the list were selected.

At least 150 schools are selected from each country, but if a participating country has fewer than 150 schools, then all schools were selected to participate. In each participating school, a predetermined number of students—the target cluster size defined earlier—were randomly selected with the same probability. In schools with a small number of students matching the target cluster size, all students are selected. Overall, a minimum of 6300 students will be required for computer-based countries and 5250 students for paper-based countries and computer-based countries.

Appendix A.3. The Statistical Criteria and Procedure of Deleting Data

In order to meet the criteria of multi-level analysis, the following two steps were carried out for the data used:

Firstly, to conduct multi-level model analysis on data, at least two levels of variables should be included, and our study contains two categories of variables: individual-level variables of students and environment-level variables of school. Different researchers proposed different sample number requirements for the variable analysis of two levels. Kreft proposed the 30/30 rule; that is, there should be at least 30 groups, and each group should have at least 30 subjects or observed values [ 36 ]. Hox suggested that there should be a minimum ratio of 50/20 as to test cross-layer interactions [ 37 ], i.e., there should be at least 50 groups with at least 20 subjects or observations in each group, and the minimum ratio of random effects is 100/10; that is, there should be at least 100 groups with at least 10 subjects or observations in each group. There are 361 groups (361 schools) in our study, most of which have about 35 students, meeting the above criteria. Then, in order to make the analysis criteria, the groups with less than 30 students (that is, the number of students in each school) are deleted (school numbers: 97500019, 97500024, 97500027, 97500074, 97500077, 97500094, 97500118, 97500147, 97500165, 97500168, 97500186, 97500204, 97500217, 97500220, 97500249, 97500253, 97500273, 97500274, 97500275, 97500280, 97500332).

Secondly, the variables of the school-level used in the study are classified into two categories [ 38 ]. One is variables based on Global Constructs, which are derived from the group levels and describe group features, such as the location and scale of the school. The other is variables based on Shared Constructs, of which group features are derived from the group members. The attitudes, perceptions, or behaviors of the group members are summarized and averaged based on groups and then integrated into group variables, such as the school discipline atmosphere perceived by the students. According to Zohar [ 39 ], in order to integrate variables at a lower level into variables at a higher level, the interrater agreement indicator Rwg(j) must be greater than 0.7, and the higher Rwg(j) is, the more appropriate it is. Therefore, after calculating the Rwg(j) of each group of each variable at the school level, delete the group with Rwg(j) less than 0.7 (school numbers: 97500043, 97500360, 97500361, 97500362). Then delete the group with missing values (school number: 975000299) (in the analysis of multilevel analysis, Level 1 is allowed to have missing values, but Level 2 cannot). Finally, a total of 11,497 student-level data and 334 school-level data were included in the final data analysis.

The code for calculating Rwg is as follows:

Appendix B.1. Outcome Variables (Y)

The outcome variables of this study are students “suffering from school bullying”, “suffering from relational bullying”, “suffering from verbal bullying”, and “suffering from physical bullying”, which are student-level variables. The PISA 2018 background questionnaire surveyed students’ experiences of bullying-related behaviors in school and measured three different types of bullying: physical bullying, relational bullying, and verbal bullying [ 40 ]. PISA 2018 asked students “During the past 12 months, how often have you had the following experiences in school? (Some experiences can also happen in social media.):

• “Other students left me out of things on purpose.” (Relational bullying),
• “Other students made fun of me.” (Verbal bullying),
• “I was threatened by other students.” (Verbal bullying),
• “Other students took away or destroyed things that belonged to me.” (Physical bullying),
• “I got hit or pushed around by other students. “ (Physical bullying),
• “Other students spread nasty rumors about me.” (Relational bullying).

If a student chooses “Never or almost never” they receive 1 score, “A few times a year” receives 2 scores, “A few times a month” receives 3 scores, and “once a week or more” receives 4 scores. Add up the scores of six items to obtain the “suffering from school bullying” variable. The score ranges from 6 to 24 scores. Similarly, add the scores of questions 1 and 6, the scores of questions 2 and 3, and the scores of questions 4 and 5, respectively, to obtain the variables of relational bullying, verbal bullying, and physical bullying. The higher the scores are, the more serious the bullying is.

Since there is not necessarily a high correlation between the six measurement items of school bullying (for example, students may be suffering from relational bullying but not physical bullying), the measurement of school bullying should be a Formative Indicator. There is still no comprehensive way to test the reliability and validity of the formative indicators now, but most scholars believe that there should not be serious multi-collinearity problems among the combined indicators, which will reduce the reliability and validity of the measurement model [ 41 , 42 ]. Based on this, we carried out the multi-collinearity test of these six items. The result showed that the VIF values reflecting the severity of the collinearity problem were between 1.552 and 2.041, which met the standard of less than 3.3, indicating that there was no multi-collinearity problem among the 6 items. It means that the reliability and validity can be guaranteed. Similarly, the VIF values of relational bullying, verbal bullying, and physical bullying were 1.484, 1.203, and 1.270, respectively, none of which was greater than 3.3, indicating that there were no multicollinearity problems for the items in these 3 different types of bullying variables. Additionally, the reliability and validity can be guaranteed.

Appendix B.2. Predictor Variables (X)

The predictors at the student-level of students are as follows:

• Gender. In this study, gender is a binary dummy variable, female = 0, male = 1. Studies found that the number of male students who suffered from school bullying was significantly higher than that of female students [ 8 , 14 ], so gender is an important factor that affects a student’s suffering from school bullying.
• Grade (continuous variable). Students are all in grades 7 to 12. Research showed that the amount of school bullying decreases with the grades increasing [ 8 , 9 , 43 ].
• Education Type (two-category dummy variable), general education = 0, vocational education = 1;
• Grade repetition (two-category dummy variable), no grade repetition = 0, grade repetition = 1;
• Truancy (two-category dummy variable), no truancy = 0, truancy = 1;
• Arriving late for class (two-category dummy variable), no lateness = 0, lateness = 1;
• Family’s economic, social, and cultural status (continuous variable). PISA uses IRT technology to synthesize ESCS according to the parents’ highest educational degree (PARED) which selects the maximum value of parents, parents’ highest occupational status (HISEI) which is assigned based on the occupational prestige index in previous research [ 44 ] and adopts the maximum value of parents, and home properties (HOMEPOS) which is based on the property condition reported by students of their family’s computers, books, musical instruments, internet, independent bedrooms, vehicles (cars), and other household assets, etc. Then, they are added up to obtain the individual overall household economic status score. Finally, the three variables of PARED, HISEI, and HOMEPOS were converted into standard Z-values and subjected to principal component analysis to obtain the ESCS value of each student. The average value of students in OECD countries is 0, and if the value is negative/positive, it is lower/higher than the average level of students in OECD countries. The higher the score is, the higher the family’s economic, social, and cultural status is.

“The teacher shows an interest in every student’s learning”;

“The teacher gives extra help when students need it”;

“The teacher helps students with their learning”;

“The teacher continues teaching until the students understand”.

The options are “Every lesson” for 1 score, “Most lessons” for 2 scores, “Some lessons” for 3 scores, and “Never or hardly ever” for 4 scores. For the sake of explanation, all the items are converted into reverse scores, and then we add these items to obtain the average for the index measurement of teacher support. The index range is 1 score to 4 scores. The higher the score is, the higher the teacher’s support for students’ learning is. The Cronbach’s alpha coefficient between the 4 items is 0.864, which indicates high internal consistency reliability.

“My parents support my educational efforts and achievements”;

“My parents support me when I am facing difficulties at school”;

“My parents encourage me to be confident”.

They receive 1 score for “Strongly disagree”, 2 scores for “Disagree”, 3 scores for “Agree”, and 4 scores for “Strongly agree”. Add up the scores of the three items and take the average to obtain the parent emotional support index. The index ranges from 1 score to 4 scores, and the higher the score is, the higher the level of parents’ emotional support for students is. The Cronbach’s alpha coefficient between the 3 items is 0.908, which indicates high internal consistency reliability. Relevant studies have shown that teachers’ support and parents’ support for students can influence their experiencing of school bullying [ 25 , 26 ].

At the school-level, there are two types of predictor variables: one type is the variables which are based on the overall construct, originate from the group level, and describe the characteristics of the group, including nine variables:

• School location (categorical variable): divided into town schools and city schools, town schools = 0, city schools = 1. The areas where schools are located in villages (less than 3000 people), towns (about 3000 to 15,000 people), and county towns (about 15,000 to 100,000 people) are classified as town schools, and the areas where schools are located in cities (100,000 to 1 million people) and large cities (more than 1 million people) are classified as city schools;
• School type (categorical variable): divided into public schools, which refer to schools directly or indirectly managed by the government or public educational institutions, and the leadership of the school is appointed or openly elected by the government, and private schools, which refer to schools directly or indirectly managed by non-government organizations, such as churches, unions, businesses, or other private institutions. Public schools are assigned the value of 0, and private schools as 1;
• School size (continuous variable): the school size measures the total number of students enrolled in the school. When the total number of students is larger, it means that the school is larger in size;
• Class size (continuous variable): class size refers to the average number of class members in the school, and the larger the value is, the larger the class size is;
• Student–teacher ratio (continuous variable): the ratio of the total number of students to the total number of teachers in the school, and the larger the value is, the more students are supervised by each teacher;
• Proportion of boys (continuous variable): refers to the proportion of the number of boys in school to the total number of students, and the larger the value is, the more boys in the school there are;
• Proportion of special needs students (continuous variable): refers to the sum proportion of students whose native language is not Chinese, students with special educational needs, and students who are from families with financial difficulties. The larger the value is, the more of students with special needs there are;
• Proportion of students without graduation certificate (continuous variable): refers to the proportion of the students’ number who leave the school without obtaining a graduation certificate to the total number of students. The larger the value is, the more students without a graduation certificate there are;

Similarly, the above (1) to (8) variables are not potential constructs, and they belong to the measurement of non-psychological constructs; there is no measurement error, so there is no need to discuss their reliabilities and validities

• 9. Student behaviors and teacher behaviors that hinder learning at school (continuous variable): in the school questionnaire, we learned about student behaviors and teacher behaviors that hinder student learning by asking “In your school, to what extent is the learning of students hindered by the following phenomena?”

Student behaviors that hinder student learning include six items:

“Student truancy”,

“Student skipping classes”,

“Student lacking respect for teacher”,

“Students’ use of alcohol or illegal drugs”,

“Student intimidating or bullying other students”,

“Students not being attentive”.

Teacher behaviors that hinder students’ learning include five items:

“Teachers not meeting individual students’ needs”,

“Teachers’ absenteeism”,

“Staff resisting change”,

“Teachers being too strict with students”,

“Teachers not being well prepared for classes”.

If students choose “Not at all” they receive 1 score, “Very little” receives 2 scores, “To some extent” receives 3 scores, and “A lot” receives 4 scores. The higher the score is, the greater the impact that hinders students’ learning is.

Because there are not necessarily correlations between these behaviors of students and teachers (e.g., students who skip classes are not necessarily disrespectful to teachers, and similarly, teachers who are reluctant to change are not necessarily insufficiently prepared), the measurement models of the two variables are also combinedmeasurement index (Formative Indicator), and their reliabilities and validities are still tested by the existence of multi-collinearity. The multi-collinearity diagnosis results of the variable of student behaviors that hinder learning show that the first two items (Student truancy, Student skipping classes) have certain collinearity (VIF = 15.605 and 14.251), so the first item is deleted, and the sum scores of the five items left behind are used as the measurement of student behaviors that hinder learning. Then, the multi-collinearity diagnosis is carried out again, and results show that the VIF values of the 5 items are between 1.860 and 8.024. Although the VIF values of some items exceeds 3.3, according to Hair’s suggestion [ 45 ], as long as the VIF is below 10, it is still an acceptable range, indicating that there is no collinearity problem, and the reliability and validity of the measurement model can be guaranteed. Therefore, the variable of student behaviors that hinder learning ranges from 5 to 20 scores. Similarly, the multi-collinearity diagnostic results of the variable of teacher behaviors that hinder learning show that the VIF values of the 5 items are between 1.881 and 4.179, which is also in an acceptable range, indicating that there is no collinearity problem between these items. The reliability and validity of the measurement model is good. The variable of teacher behaviors that hinder learning also ranges from 5 to 20 scores.

Another type of school-level variables are those based on shared constructs, including three variables as follows:

“Students don’t listen to what the teacher says”;

“There is noise and disorder”;

“The teacher has to wait a long time for students to quiet down “;

“Students cannot work well”;

“Students don’t start working for a long time after the lesson begins”.

Students choosing “Every lesson” receive 1 score, “Most lessons” for 2 scores, “Some lessons” for 3 scores, and “Never or hardly ever” for 4 scores. Add the scores of the five items and take the average to obtain the disciplinary atmosphere index. The index ranges from 1 score to 4 scores. The higher the score is, the better the disciplinary atmosphere of the student’s class is. The Cronbach’s alpha coefficient of the 5 items is 0.894, which has high internal consistency reliability. Then, the scores of each student in each school are summed and averaged to synthesize the school-level disciplinary atmosphere.

“Students seem to value competition/cooperation”,

“It seems that students are competing/cooperating with each other”,

“Students seem to share the feeling that competing/cooperating with each other is important”,

“Students feel that they are being compared with others”/“Students feel that they are encouraged to cooperate with others”.

The answer is “Not at all true” for 1 score, “Slightly true” for 2 scores, “Very true” for 3 scores, and “Extremely true” for 4 scores. The index ranges from 1 to 4 scores. The higher the score is, the higher the perceived level of competitive/cooperative atmosphere is. The Cronbach’s alpha coefficient between the 4 items of competition is 0.813 and of cooperation is 0.934, which have high internal consistency reliability. Then, the scores of each student in each school are added and averaged to synthesize the index of competitive/cooperative atmosphere among students at the school level.

Appendix C.1. The Formula of Model I

Level 1: suffering from school bullying (relational bullying, verbal bullying, and physical bullying) ij = β 0j + γ ij .

Level 2: β 0j = γ 00 + U 0j .

Appendix C.2. The Formula of Model II

Level 1: suffering from school bullying (relational bullying, verbal bullying, and physical bullying) ij = β 0j + β 1j (gender ij ) + β 2j (grade ij ) + β 3j (education type ij ) + β 4j (grade repetition ij ) + β 5j (truancy ij ) + β 6j (arriving late for class ij ) + β 7j (ESCS ij ) + β 8j (teacher support ij ) + β 9j (parent support ij ) + γ ij .

Level 2: β 0j = γ 00

    β 1j = γ 10

    β 2j = γ 20 + U 2j

    β 3j = γ 30

    β 4j = γ 40

    β 5j = γ 50

    β 6j = γ 60

    β 7j = γ 70

    β 8j = γ 80 + U 8j

    β 9j = γ 90 + U 9j

In the above formula, γ 10 , γ 20 , γ 30 , γ 40 , γ 50 , γ 60 , γ 70 , γ 80 , and γ 90 represent the estimated parameters of the student-level variables of students (gender, grade, education type, grade repetition, truancy, arriving late for class, ESCS, teacher support, and parent support, respectively) to student suffering from school bullying, relational bullying, verbal bullying, and physical bullying.

Appendix C.3. The Formula of Model III

Level 2: β 0j = γ 00 + γ 01 (school location j ) + γ 02 (school type j ) + γ 03 (school size j ) + γ 04 (class size j ) + γ 05 (student–teacher ratio j ) + γ 06 (proportion of boys j ) + γ 07 (proportion of special needs students j ) + γ 08 (proportion of students without graduation certificates j ) + γ 09 (student behaviors that hinder learning j ) + γ 010 (teacher behaviors that hinder learning j ) + γ 011 (school discipline atmosphere j ) + γ 012 (competitive atmosphere among students j ) + γ 013 (cooperative atmosphere among students j ) + U 0j .

In the above formula, γ 01 , γ 02 , γ 03 , γ 04 , γ 05 , γ 06 , γ 07 , γ 08 , γ 09 , γ 010 , γ 011 , γ 012 , and γ 013 represent the estimated parameters of school-level variables to student suffering from school bullying, relational bullying, verbal bullying, and physical bullying, which are school location, school type, school size, class size, student–teacher ratio, proportion of boys, proportion of special needs students, proportion of students without graduation certificates, student behaviors that hinder learning, teacher behaviors that hinder learning, school discipline atmosphere, competitive atmosphere among students, and cooperative atmosphere among students, respectively.

Multilevel analysis results of the influencing factors of students suffering from rational bullying.

Multilevel analysis results of the influencing factors of students suffering from verbal bullying.

Multilevel analysis results of the influencing factors of students suffering from physical bullying.

Funding Statement

This research was funded by key discipline construction project of Liupanshui Normal University, grant number LPSSYZDPYXK201704, and scientific and technological innovation team project in teacher education of Liupanshui Normal University, grant number LPSSYKJTD201603.

Author Contributions

Conceptualization, Y.-J.W.; methodology, Y.-J.W. and I.-H.C.; software, Y.-J.W.; formal analysis, Y.-J.W.; writing—original draft preparation, Y.-J.W.; writing—review and editing, Y.-J.W. and I.-H.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to openness and availability of the data. The data of this study were taken from the public data provided by PISA (Programme for International Student Assessment), which is easily available on this website https://www.oecd.org/pisa/data/2018database/ (accessed on 15 October 2021), and is not collected by the researchers. PISA measures 15-year-olds’ ability to use their reading, mathematics and science knowledge and skills to meet real-life challenges. On the webpage, PISA said that “The PISA database contains the full set of responses from individual students, school principals, teachers and parents. These files will be of use to statisticians and professional researchers who would like to undertake their own analysis of the PISA 2018 data”. So, our research used the secondary data, which everyone can access on Internet.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

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‘Victim of Bullying’: Attorney for 15-Year-Old Black Girl Fights to Keep Case In Juvenile Court as Kaylee Gain’s Family Says Teen’s Showing Signs of ‘Significant Cognitive Impairment’

The family of Kaylee Gain, the teen hospitalized following the viral fight near Hazelwood East High School in Missouri, has acknowledged her alleged attacker’s desire to apologize .

Their response comes after a judge said the state must determine if 15-year-old Maurnice DeClue will be tried as an adult in this case, KTVI reported.

The teen was  charged  with assault and has been in the custody of St. Louis County Family Court since the altercation in early March that left Gain, 16, with severe injuries.

Video captured the accused slamming Gain’s head on the pavement multiple times. 

While  local officials and Gain’s family suggested that DeClue should receive a harsher charge, the county juvenile attorneys requested an additional 30 days to finish a report that highlights her background, according to the report.

The hearing to determine whether DeClue shall be certified as an adult for the case is scheduled for Wednesday, May 10. 

“Our position is that she should not be certified. We understand that the law says that there has to be a certification hearing based on what she has been charged with,” DeClue’s attorney, Greg Smith, told Fox 2 Now.

“Everything is out there, about her being an honor student, she was taking AP courses, she has no history with the juvenile court,” he continued. “She has been the victim of bullying. There are other facts that we are going to save for court.”

Gain’s family’s lawyer Bryan Kaemmerer has based the push for increased punishment against DeClue on unverified social media posts.

In a statement released on March 29, the attorney claims Gain’s parents have seen now deleted posts on social media that show “an utter lack of remorse” from the 15-year-old Black honor roll teen.

While admitting the posts have not been verified, Kaemmerer says the “timing of when they were made suggest that the accused did, in fact, make them.”

“In one post, the accused admits ‘this was calculated,’ and even flippantly jokes about whether she should ‘join MMA or WWE.’ Given that Kaylee began visibly convulsing within seconds after the attack, the serious nature of Kaylee’s injuries should have been immediately apparent to the accused.”

Local news station KSDK confirmed the posts were not made by DeClue based on the timing. DeClue was arrested before noon on Saturday, March 9 while the posts were published on X, formerly known as Twitter the following day, on Sunday night at 9:13 p.m.

DeClue’s family has maintained positive sentiments about her character and achievements in a Charge.org petition as well as interviews with local news stations.

Her mother Consuella told KSDK that DeClue was “not the aggressor,” but that she still wants to apologize to Gain. After the judge’s ruling on Monday, Gain’s family released a statement. 

“The family is encouraged, however, by public statements by those associated with the accused stating that the accused would like to apologize to Kaylee for what occurred,” the parents said, per Fox 2 Now. “While these statements do not change the family’s position that it is appropriate for the accused to be tried as an adult, it is encouraging that the accused appears to be remorseful for what transpired during these unfortunate events.”

The family provided an another update on Gain’s condition via a statement from the family’s attorney that was obtained by Fox News.

“Kaylee’s ability to walk has slightly improved, but she is still unable to do so without the assistance of the hospital staff. However, Kaylee is still showing signs of significant cognitive impairment during the limited conversations that she is able to have, and she tends to reiterate the same short sentences over and over,” said Kaemmerer.

They also added that Gain has no recollection of the March 8 conflict. 

Smith, had previously come forward and  revealed  that Gain was involved in a separate fight at the school, which resulted in her suspension. He said it was the precursor to the fight with his client. 

“And despite that, found her way back towards the neighborhood around the high school the following day at dismissal time,” Smith added.

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Lawyer whose absence lost school bullying death case in South Korea ordered to compensate victim's family

• South Korea

Thursday, 13 Jun 2024

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Lee Gi-cheol (second from right), the mother of a teenage girl who died in a school bullying case, speaks to reporters June 11 at the Seoul Central District Court, after partially winning a civil case against her lawyer. The lawyer’s repeated failure to show up to hearings in the suit against the school bullies resulted in Lee and her family losing the case. - The Korean Herald/ANN

SEOUL: Kwon Gyeong-ae, a lawyer whose repeated failures to show up to court lost a case involving a teenage girl's death caused by school bullying, was ordered by another court to pay 50 million won (US$36,000) in compensation to the bereaved family of the victim.

The Seoul Central District Court on Tuesday (June 11) ruled against Kwon in the civil damages suit filed by the girl’s mother, Lee Gi-cheol, and her family, in which they requested a total of 200 million won in financial and psychological damages caused by the lawyer's blunder.

The total included financial compensation that the family would have received if they won the school bullying case regarding the death of Lee's daughter.

The court said that Kwon did not carry out her duties as a lawyer during the school bullying trial.

She also failed to notify her clients of the loss, which prevented the family from taking the case to the Supreme Court.

But the court did not determine that Lee and her family would have won the case if Kwon had properly represented them, and awarded the plaintiffs only the compensation for the psychological damages.

Kwon represented Lee’s family in their civil lawsuit seeking compensation for the 2015 death of Lee's daughter.

The family initially won the case in 2019, but Kwon then failed to show up at the hearings for the appellate case three times.

Kwon's absences led to the court overturning the previous ruling under Article 268 of the Civil Procedure Act, which regards such absences as showing intent not to pursue the lawsuit.

The loss also meant that the victim's family was forced to shoulder all legal costs related to the trial, as South Korean law stipulates the person who lost the case is mandated to pay the legal costs of both sides.

Tuesday's ruling also ordered Kwon to cover a quarter of the legal costs in the case she lost.

Lee appeared on a local radio show and decried the ruling.

She said the ruling was "inhumane and machinelike," as the verdict was a rote application of the law and did not consider human elements.

Lee indicated she would appeal the case. - The Korea Herald/ANN

Tags / Keywords: South Korea , Lawyer , absence , school bullying , death case , compensate , victim

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