Session Information
14 SES 07 A, Preventive Interventions and Initiatives.
Paper Session
Contribution
School aggression is a serious problem found in various cultures and societies all over the world, as evidenced by representative cross-national studies (Chester et al., 2015). According to Bronfenbrenner’s ecological model (1994), risk factors associated with aggression act on different levels. These factors include relations with peers, parents, and teachers, as well as local norms and school climate (Hong and Espelage, 2012). We have studied some of these factors and the prevalence of bullying in Russian schools (Ivaniushina et al., 2021; Ivaniushina, Alexandrov, 2022).
In our current work we aim at studying community effects of collective production and maintenance of aggressive environment in schools. To discern these community effects, we use survey data from rural areas, where each village or small town has just one school, and students and schools are unequivocally nested in the local communities. In Russian cities with several schools there is always a certain level of school differentiation and certain level of freedom in school choice, and thus it is hard to match schools and children to local territorial communities, while in rural areas we are certain that parents and teachers belong to the same local community.
In the schools surveyed girls and boys are bullied at approximately the same frequency, but boys are more exposed to physical abuse while girls are more likely to be victimized verbally and socially. Prevalence rates of bullying vary dramatically across schools, from 0 to 40% of students in a school being exposed to bullying during the school year, yet the prevalence of bullying is unrelated to schools’ standard structural characteristics (type of curriculum, urban/rural location, size, aggregate socioeconomic status of parents). Therefore, we are aiming at explaining this variation by other factors – by parental and teachers’ behavior and local norms related to aggression.
Such explanations are in line with Albert Bandura’s social cognitive theory of behavior (Bandura, 1986), mainly his social learning theory and the theory of moral disengagement. In addition to it, we propose to use the theory of social disorder as disorganized environment, whether it is a dysfunctional family, disordered school, or violent neighborhood, has been shown to affect children’s development and influence their behavior. Social disorder theory (known widely through “broken windows” theory) is extensively used in criminology, and there are attempts to apply it directly to school environment (Plank et al., 2009; Espelage and Swearer, 2009; Bradshaw et al., 2009). We hypothesize that social disorder in communities is spread through all local levels of Bronfenbrenners’ system. Our goal is to investigate the relative impact of different components of the system by comparing the effect sizes in regression and the paths of influence by developing structural equation models.
Method
We use data from a larger project on school climate conducted in the Kaluga region of Russia in 2016-2019. All schools in the region enrolling over 100 students participated in this study, the survey was administered to all students in grades 6–9 (12–15 years old). In total, 18466 students from 204 schools were surveyed. The questionnaire was internet-based, and the students completed the questionnaires online, in computer classes at school; the average time for completion was 22 min. The use of self-administered questionnaires is prone to eliciting inattentive or careless responses. To evaluate the validity of our sample, we used two methods: a screening validity item (“How many of the questions on this survey did you answer truthfully?”) and the survey completion time. This combination has been recommended as effective in identifying careless and/or misleading respondents’ data that should be omitted from analyses (Jia et al., 2018). Ultimately, about 9% of questionnaires were eliminated as not valid. In line with our research aim, our analytical sample consisted of rural schools, with only one school per village or small town. The sample consisted of 94 schools and 3068 students. Attitudes and behavior were measured on Lickert scale using short lists of items adapted from relevant instruments proven to be working well in school surveys. Teachers aggression was measured with five items adapted from the Bullying by Teachers Scale (example: “How often this school year have you been reluctant to answer questions in class because you were afraid the teacher would make fun of you?”), and peer aggression was measured with four items from the Prevalence of Bullying and Teasing Scale (example: “This school year, how often did your classmates mock other students and talk nasty about them?”) (both scales from Cornell, 2015). Parental aggressive behavior was measured by four items (example: "How often do adults in your family yell at you?"). For data analysis we used hierarchical linear modeling (Snijders & Bosker, 2011) and structural equation modeling (Kline, 2023). All analyses were conducted using R statistical software (version 4.2.1).
Expected Outcomes
Our results show parental aggression at home and authoritarian style of parenting, teachers’ aggressive behavior, the lack of school order, collective moral disengagement in schools and peer aggression in classrooms to be strongly correlated across localities. In regression analysis teachers’ behavior shows larger size effects than parental behavior despite evident and well-established primary role of family environment in influencing children behavior. There are two possible explanations for such effect: (1) domain specificity of behavior (people behave in different social domains according to local norms, and we measured school behavior); (2) schools have a larger role in shaping children’s behavior by providing social learning practices for social interactions which are more diverse than interactions in family settings. Either way schools have very strong effects on both aggressive behavior and attitudes towards it. Social disorganization in communities is self-perpetuating through a feedback loop (“vicious circle”) of disorder and social-cognitive perception of it. People living in violent environments are getting used to aggression, develop moral disengagement, and then either commit more aggression themselves or distance themselves from the acts of violence (bystanders who are morally disengaged never intervene), thus contributing to the maintenance of aggression. Our results point to the prevalent role of schools in this vicious circle and thus suggest that the schools should take a leading role in breaking it up.
References
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Inc. Bradshaw, C. P., Sawyer, A. L., and O’Brennan, L. M. (2009). A social disorganization perspective on bullying-related attitudes and behaviors: The influence of school context. Am. J. Community Psychol. 43, 204–220 Bronfenbrenner, U. (1994). “Ecological models of human development,” in The international encyclopedia of education, 2nd edition, eds T. Husen and T. N. Postlethwaite (New York, NY: Elsevier Sciences), 1643–1647. Chester, K. L., Callaghan, M., Cosma, A., Donnelly, P., Craig, W., Walsh, S., et al. (2015). Cross-national time trends in bullying victimization in 33 countries among children aged 11, 13 and 15 from 2002 to 2010. Eur. J. Public Health 25, 61–64. doi: 10.1093/eurpub/ckv029 Cornell, D. (2015). The authoritative school climate survey and the school climate bullying survey: Research summary. Charlottesville, VA: Curry School of Education, University of Virginia. Espelage, D. L., and Swearer, S. M. (2009). “Contributions of three social theories to understanding bullying perpetration and victimization among school-aged youth,” in Bullying, rejection, and peer victimization: A social cognitive neuroscience perspective, ed. M. J. Harris (New York, NY: Springer), 151–170. Hong, J. S., Espelage, D. L., and Lee, J. M. (2018). “School climate and bullying prevention programs,” in The Wiley handbook on violence in education: Forms, factors, and preventions, ed. S. Harvey (Hoboken, NJ: John Wiley & Sons, Inc), 359–374. Ivaniushina, V., Khodorenko, D., & Alexandrov, D. (2021). Age and gender differences and the contribution of school size and type in the prevalence of bullying. Voprosy obrazovaniya/Educational Studies Moscow, (4), 220-242. Ivaniushina, V., & Alexandrov, D. (2022). School structure, bullying by teachers, moral disengagement, and students’ aggression: A mediation model. Frontiers in psychology, 13, 883750. Jia, Y., Konold, T. R., Cornell, D., and Huang, F. (2018). The impact of validity screening on associations between self-reports of bullying victimization and student outcomes. Educ. Psychol. Meas. 78, 80–102. Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications. Plank, S. B., Bradshaw, C. P., and Young, H. (2009). An application of “broken-windows” and related theories to the study of disorder, fear, and collective efficacy in schools. Am. J. Educ. 115, 227–247. Snijders, T. A., & Bosker, R. (2011). Multilevel analysis: An introduction to basic and advanced multilevel modeling. SAGE Publications.
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