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Article

How Classroom Composition and Size Shape Adolescent School Victimization: Insights from a Doubly Latent Multilevel Analysis of Population Data

by
Elisa Cavicchiolo
1,
Giulia Raimondi
2,*,
Laura Girelli
3,
Michele Zacchilli
2,
James Dawe
4,
Ines Di Leo
5,
Pierluigi Diotaiuti
6,
Tommaso Palombi
7,
Andrea Chirico
2,
Fabio Lucidi
2,
Fabio Alivernini
2 and
Sara Manganelli
2
1
Department of Systems Medicine, Tor Vergata University of Rome, Via Montpellier 1, 00133 Rome, Italy
2
Department of Developmental and Social Psychology, Sapienza University of Rome, Via dei Marsi 78, 00185 Rome, Italy
3
Department of Humanities, Philosophy and Education, University of Salerno, 84084 Fisciano, Italy
4
Department of Humanities and Social Sciences, Universitas Mercatorum Telematic University, Pizza Mattei 10, 00186 Rome, Italy
5
National Institute for the Evaluation of the Education System (INVALSI), 00153 Rome, Italy
6
Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, 03043 Cassino, Italy
7
Department of Dynamic and Clinical Psychology, and Health Studies, Sapienza University of Rome, Via dei Marsi 78, 00185 Rome, Italy
*
Author to whom correspondence should be addressed.
Soc. Sci. 2025, 14(10), 573; https://doi.org/10.3390/socsci14100573
Submission received: 7 July 2025 / Revised: 15 September 2025 / Accepted: 19 September 2025 / Published: 24 September 2025
(This article belongs to the Special Issue Revisiting School Violence: Safety for Children in Schools)
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Versions Notes

Abstract

Adolescent school victimization is a socially regulated experience, making it important to consider classroom-level compositional effects beyond individual characteristics. This study investigated the role of classroom characteristics, specifically, classroom socioeconomic status, average academic achievement, sex composition, immigrant density, and class size, in shaping students’ experiences of school victimization. Victimization was analyzed using a doubly latent multilevel modeling approach, which accounts for measurement error at both individual and classroom levels. The analyses drew on the entire Italian 10th grade student population (N = 254,177; Mage = 15.58 years; SDage = 0.74) and a considerable number of classrooms (N classrooms = 14,278), a sample size rarely available in the social sciences. Results indicated that classroom characteristics played a significant role in victimization, beyond individual-level variables. The most important factors were sex and prior academic achievement: classrooms with a higher proportion of male students experienced greater victimization, whereas higher average achievement was associated with lower victimization. A greater proportion of second-generation immigrant students, but not first-generation students, was also associated with increased victimization. By contrast, classroom socioeconomic status and class size were not significant predictors of victimization. In conclusion, these findings highlight the importance of considering the additional influence of the classroom context for school-based interventions, particularly the composition of classrooms in terms of sex and academic achievement, when addressing student victimization.

Graphical Abstract

1. Introduction

Bullying victimization at school poses a serious risk for adolescents in Western countries (Cosma et al. 2020). Globally, according to the United Nations Educational, Scientific and Cultural Organization (UNESCO 2019), almost one in three students (32%) has been bullied by their peers at school at least once in the past month. Furthermore, a recent cross-national study (Cosma et al. 2020) conducted in 37 countries has revealed different trends across Europe and North America.
According to Olweus, bullying victimization occurs when a student “is exposed, repeatedly and over time, to negative actions on the part of one or more other students” (Olweus 1994, p. 1173). These negative actions can take various forms, including physical aggression (direct bullying, e.g., being hit by a peer), verbal abuse (direct verbal bullying, e.g., being insulted by other students), or social exclusion (relational bullying), where a student is intentionally left out of a group (Olweus and Breivik 2014). During adolescence, aggression may become less overt, and other forms of bullying, such as social exclusion, as well as dynamics of peer contagion may also emerge (Dishion and Tipsord 2011).
Over the past few decades numerous studies have highlighted the harmful effects of bullying on young victims. They are more likely to experience a range of internalizing problems, including psychosomatic symptoms (Gini and Pozzoli 2013; Natvig et al. 2001; Zwierzynska et al. 2013). They also show elevated levels of anxiety and depression (Arseneault et al. 2010; Balluerka et al. 2023; Brunstein Klomek et al. 2019; Sweeting et al. 2006; Ttofi et al. 2011a), in addition to increased feelings of loneliness, social withdrawal, and avoidance behaviors (Coelho and Romão 2018; Espelage and Holt 2001). They are also at greater risk of suicidal ideation (Brunstein Klomek et al. 2019) and, in the most extreme cases, of suicide attempts (Kaltiala-Heino et al. 2000; Klomek et al. 2011; Rigby and Slee 1999; Yang et al. 2021). Victimization is also associated with a general sense of sadness, low self-esteem, and poor academic performance, which, in severe cases, can lead to dropout from school (Cornell et al. 2013; Hutson 2018; Nakamoto and Schwartz 2010; van Geel et al. 2018; Zych et al. 2015). Numerous studies have also documented that the negative consequences of bullying can persist in the long term (Arseneault et al. 2010; McDougall and Vaillancourt 2015; Ttofi et al. 2011a, 2011b; Walsh et al. 2013; Wolke et al. 2013; Wolke and Lereya 2015).
Bullying is a social phenomenon, which makes it essential to examine it within the broader social context in which it occurs (Alivernini 2013; Paletta et al. 2017; Williford et al. 2019). Although bullying can occur in various social settings, including sports, children’s residential care homes, and online environments (e.g., Cheever and Eisenberg 2022; Monks et al. 2009; Strohmeier and Gradinger 2022), schools remain particularly significant for adolescents. In these contexts, students spend a substantial amount of time developing social relationships, which may foster positive bonds such as friendships but may also expose them to bullying (Rambaran et al. 2020). Because the classroom often constitutes the immediate peer context in which bullying dynamics unfold, it is important to consider not only individual characteristics but also group-level factors (Salmivalli et al. 1998; Salmivalli 2010b). Previous studies have emphasized the importance of classroom effects, particularly with regard to class norms (see for example, Salmivalli 2010a), and social status (Wiertsema et al. 2023). However, less attention has been paid to class-level characteristics related to compositional factors (e.g., sex composition or classroom socioeconomic status) and to structural features such as class size.
In the present study, we examined several contextual characteristics related to classroom composition and size. Specifically, we considered the proportion of males in the classroom, immigrant density (including first- and second-generation students), classroom socioeconomic status (SES), average academic achievement, and class size. These characteristics reflect aspects of the classroom context that are relatively less malleable than individual-level variables, such as academic motivation or self-efficacy. However, understanding how such compositional characteristics influence the experiences of students is essential to identify structural conditions that may hinder or foster a safe and inclusive learning environment. Previous research has already emphasized the role of classroom context in shaping psychological well-being (e.g., Alivernini et al. 2019a) and intergroup dynamics such as prejudice (Albarello et al. 2023). Nonetheless, studies focusing on classroom-level factors remain relatively scarce, and the findings to date are often mixed.
In the next section, we provide a brief review of the literature that examines the relationship between victimization and classroom composition and class size.

1.1. Victimization and Classroom Characteristics

1.1.1. Sex Composition

While several studies have consistently shown that, on average, male students are more frequently involved in bullying episodes than their female counterparts, including as victims (Bokhove et al. 2022; Bouffard and Koeppel 2017; Cook et al. 2010; Seals and Young 2003; Whitney and Smith 1993), findings remain mixed with regard to compositional effects. Some studies have reported a non-significant relationship between bullying and victimization and the classroom’s sex composition (Garandeau et al. 2014; Saarento et al. 2013), whereas others suggest that a higher proportion of male students within a class is associated with increased levels of bullying victimization (Coelho and Sousa 2018; Khoury-Kassabri et al. 2004; Thornberg et al. 2017). For example, Thornberg et al. (2017) found that classrooms with a higher number of boys reported higher levels of victimization, possibly because male students are more likely than female students to engage in bullying behaviors.

1.1.2. Classroom Socioeconomic Status (SES)

Schools located in disadvantaged areas, or those with a high proportion of students of lower socioeconomic backgrounds, tend to report a higher incidence of bullying-related issues (Q’Moore et al. 1997; Whitney and Smith 1993). Wolke et al. (2001) identified a significant, albeit weak, relationship between greater social disadvantage in schools and victimization. Similarly, Khoury-Kassabri et al. (2004) found a significant association between being a victim of bullying and coming from a lower socioeconomic background. The systematic review by Azeredo et al. (2015) showed that contexts marked by a greater income inequalities were associated with an increased risk of bullying. Other studies have suggested that a higher prevalence of students from very low socioeconomic backgrounds may contribute to the development of an unsafe school climate, which in turn is associated with increased levels of bullying and victimization (Bradshaw et al. 2009; Malecki et al. 2020). However, some researchers argue that it is not poverty per se, but rather perceived economic disparities between students that can drive bullying behaviors in school settings (Attree 2006; Chaux et al. 2009). In contrast, other studies have not found a statistically significant relationship between socioeconomic background and bullying-related issues (Ma 2002; Olweus 1994; Thornberg et al. 2022).

1.1.3. Immigrant Composition

While some research indicates that immigrant students are at higher risk of being victims of aggressive behaviors compared to their non-immigrant peers (Alivernini et al. 2019b; Bjereld et al. 2015; Fu et al. 2013; Graham and Juvonen 2002; Pistella et al. 2020; Pottie et al. 2015; Strohmeier et al. 2011), regardless of whether they are first- or second-generation (Walsh et al. 2016), the role of compositional effects remains unclear. Some research has reported a significant, albeit modest, association between higher immigrant density and increased levels of physical fighting and bullying perpetration among both immigrant and non-immigrant adolescents (Walsh et al. 2016). However, other studies have found no significant relationship between the number of immigrant students in a classroom or school and the risk of bullying victimization (Basilici et al. 2022). For instance, evidence suggests that it is not the proportion of immigrant students per se, but rather the classroom climate and levels of support that influence bullying victimization (Dimitrova 2017).

1.1.4. Classroom Academic Achievement

Previous research has examined student academic performance both as a potential consequence of bullying and as a predictor of involvement in such episodes (Card and Hodges 2008). In addition to individual-level effects, it has also been shown that the academic level of the peer group is a relevant contextual factor in understanding bullying dynamics. For example, Garandeau et al. (2011) found that aggressive students were more disliked in classrooms where academic achievement was highly valued, suggesting that a learning-oriented classroom climate may discourage aggressive behaviors by reducing their social rewards. Similarly, classrooms characterized by overall lower academic performance appear to be at higher risk for antisocial behaviors among students (Junger-Tas et al. 2010). Finally, schools with a high proportion of students who have repeated a grade—often a proxy of low academic achievement—tend to report increased levels of victimization (Organisation for Economic Co-operation and Development, OECD 2017).

1.1.5. Class Size

Previous studies have produced mixed findings on the relationship between class size and bullying behaviors (Menesini and Salmivalli 2017; Garandeau et al. 2019). Some studies have found a non-significant relationship between class size and bullying (Coelho and Sousa 2018; Wang and Chen 2023; Whitney and Smith 1993). On the contrary, other research has shown a positive association between victimization and larger class sizes (Garandeau et al. 2014). For example, in nationally representative study by Khoury-Kassabri et al. (2004) of more than 10,000 students, higher levels of victimization were observed in larger classrooms. On the contrary, several studies suggest the opposite, namely, that smaller class sizes may be associated with increased levels of aggressive behaviors. Q’Moore et al. (1997) reported significantly higher levels of bullying in smaller secondary school classrooms. Similarly, Garandeau et al. (2014) found that bullying was less prevalent in larger classes. A subsequent study by Garandeau et al. (2019) using peer-reported measures confirmed a similar pattern for both bullying and victimization. Consistent with these findings, Saarento et al. (2013) reported higher levels of peer-reported victimization in smaller classrooms. According to the authors, this may be explained by the increased visibility of bullying episodes in smaller settings, which makes it easier for students to identify who among their peers is being targeted.

1.2. Objectives

Acknowledging the importance of considering the social context in which bullying occurs (Hong and Espelage 2012; Williford et al. 2019), and drawing on previous evidence consistently showing that peer victimization varies significantly between classrooms (Saarento et al. 2015; Stefanek et al. 2011; Thornberg et al. 2022; Thornberg et al. 2024), the present study aims to investigate the role of classroom composition and class size in students’ experiences of bullying victimization at school. We focused on the classroom context because studies examining classroom-level factors remain relatively limited (Thornberg et al. 2024) and have yielded mixed results. Moreover, prior research has indicated that differences in bullying between classrooms are equal to, or even greater than, those between schools (Kloo 2025; Thornberg et al. 2024).
This study analyzed victimization using a doubly latent multilevel modeling approach with cross-level measurement invariance (Lüdtke et al. 2011; Marsh et al. 2012), thereby accounting for potential measurement errors at both levels. In addition, in our model we have included several classroom characteristics related to compositional variables (i.e., classroom socioeconomic and academic achievement levels, male student proportion, immigrant density) and class size, drawing on a considerable number of classrooms (N classrooms = 14,278). Such a large sample is rarely available in social sciences and allows for highly accurate estimates (Núñez et al. 2013), for a recent review see (Asampana Asosega et al. 2024).

2. Materials and Methods

2.1. Study Design

The data analyzed in this study were drawn from a large-scale Italian national assessment of learning conducted by the National Institute for the Evaluation of the Education System (INVALSI). This assessment, based on a cross-sectional design, covered the entire population of 10th-grade students in Italy. In each upper secondary school, all students enrolled in second-year classes (equivalent to 10th grade) participated by completing standardized paper and pencil tests of reading comprehension in Italian and mathematical skills. In addition, students filled out a paper and pencil questionnaire that included the victimization scale and demographic information, which are the focus of the present study.

2.2. Sample and Procedures

Data are based on the population of Italian 10th-grade students (N = 254,177; Mage = 15.58 years; SDage = 0.74; N classrooms = 14,278, average class size = 21.2 students) who participated in the national assessment of learning conducted by INVALSI in 2015.
In the Italian educational system, the 10th grade corresponds to the second year of upper secondary education (ISCED 3), typically attended by students aged 15–16 years old. Upper secondary schools in Italy are structured into three different paths. The general education path (i.e., “licei” in Italian) prepares students to higher-level studies and to the labor world by providing broad knowledge, key competences, and cultural instruments for developing their own critical point of view. Technical education (i.e., “istituti tecnici”), provides students with scientific and technological competences in the technological and economic professional sectors. Vocational education (i.e., “istituti professionali”), provides technical and vocational general background in the sectors of services, industry and handicraft, to facilitate access to specific occupations. In Italy, as in many other countries, upper secondary classrooms are stable groups of approximately 20–30 students (Decreto del Presidente della Repubblica 20 marzo 2009, n. 81 2009) who spend most of their school time together, attending all subjects throughout the academic year (with the exception of optional subjects or extracurricular activities). Subject-specific teachers rotate between classrooms, while the student groups remain largely unchanged from grade 9 to grade 13.
All participants completed the anonymous questionnaires in class during the first part of a typical school day. Before starting, students received a standardized introduction to the survey that explained its purpose and provided instructions on how to complete the questionnaire. The evaluation adhered to the ethical guidelines of INVALSI (2015), which reviewed and approved the evaluation process. This study was conducted in accordance with the Declaration of Helsinki, and approved by the National Institute for the Evaluation of the Education and Training System (INVALSI). Data collection was approved by the Ministry of Education, University and Research, with Directive No. 85 of 12 October 2012, ensuring that the study adheres to both national and international guidelines. Each school was responsible for managing informed consent and obtaining parental permission according to the national assessment protocol. Informed consent was obtained from all the parents of the students involved in the study. Data are available at https://serviziostatistico.invalsi.it/en/catalogo-dati/ (accessed on 24 September 2024).

2.3. Measures

2.3.1. Victimization

Victimization was assessed using an adapted version of the scale developed by Roland and Idsøe (2001) which addresses general and specific victimization behaviors through four items (i.e., bullied/hassled by other students at school by being hit, kicked, or shoved). The students responded using a 4-point scale (1 = never; 2 = now and then; 3 = weekly; 4 = daily), with higher scores indicating a more frequent victimization at school. The scale has demonstrated good psychometric properties in previous studies (Alivernini et al. 2019b; Bianchi et al. 2021), and its reliability was also confirmed in the present study (Cronbach’s alpha = 0.76; Omega coefficient = 0.79).

2.3.2. Sex

Sex was assessed via self-report and subsequently categorized into two groups: 0 for female and 1 for male.

2.3.3. Immigrant Background

Following the OECD classification (OECD 2014), the immigrant background was coded into three categories. Native students were defined as those born in Italy and with at least one parent also born in Italy. First-generation immigrants included students who were defined as foreign-born and with parents born abroad. Second-generation immigrants referred to those born in Italy and with parents born abroad. In this study, the immigrant background was coded by using two dummy variables (0/1): one indicating first-generation immigrants and the other indicating second-generation immigrants. Native students served as the reference category.

2.3.4. Socioeconomic Status (SES)

Socioeconomic status (SES) is a composite score based on four indicators. The first indicator, “parents’ highest level of education”, was assessed through students’ reports of their parents’ educational attainment, categorized according to the six levels of the International Standard Classification of Education (ISCED) (UNESCO 2012). This indicator reflects the higher level of schooling attained by students’ parents. The second indicator, “parents’ highest occupational status”, was derived from students’ reports of their parents’ occupations (e.g., manager, teacher, clerk), which were coded into six groups ranked by occupational status. This indicator reflects the higher occupational status of students’ parents. The third indicator, “home literacy resources”, was measured by students’ reports of the number of books available at home, ranging from “0 to 10 books” to “more than 500 books”. Lastly, the “home possessions” indicator was based on students’ reports of household items and facilities, such as personal computers, internet access, and desks for homework. A principal Component Analysis (PCA) was conducted on these indicators, and the factor scores from the first component were used as SES scores. Previous studies have shown that the first component explains more than 56% of the total variance (Campodifiori et al. 2010). Based on this procedure, SES was computed as a standardized index, with a mean of 0 and a standard deviation of 1.

2.3.5. Prior Academic Achievement

Prior academic achievement was assessed using the final grades of the students from the national state examination taken at the end of the lower secondary school (grade 8) in Italy. The grading scale ranged from 6 to 10, with honors being the highest distinction. At the time of the study, the state examination consisted of four written tests (in Italian, mathematics and two foreign languages), standardized assessments of Italian comprehension and mathematical skills, as well as an oral exam covering all subjects.

2.3.6. Class Size

The class size was defined as the total number of students enrolled in each class during the school year in which the study was conducted. This information was obtained from the official school records provided by the participating schools. The reported numbers included all enrolled students, even those who, for various reasons, did not participate in the study. In the present study, the average class size is 21.2.

2.4. Data Analysis

We first conducted a multilevel confirmatory factor analysis (MCFA) to assess the factor structure of the victimization scale. A one-factor model was specified at both the within-class level (L1) and the between-class level (L2). All factor loadings were constrained to be equal across levels (Mehta and Neale 2005). Intraclass correlation (ICC) was also calculated.
Subsequently, we implemented a multilevel structural equation model. At L1, the following variables were included: sex of the student, immigrant background (first and second generations), SES, and prior academic achievement. SES and prior achievement were centered at their grand mean. Therefore, the estimates of SES and prior achievement aggregated at the classroom level were interpretable as compositional effects (Raudenbush and Bryk 2002; Marsh et al. 2012). Compositional effects refer to the influence of an L2 variable on an L2 outcome, after accounting for the effect of the corresponding L1 variable on the L1 outcome. Class size was also included as a continuous predictor. The stable structure of the classrooms in the Italian school system allows for consistent peer groups across school years and facilitates the analysis of classroom-level effects. School type (Liceo, Technical Institute, or Vocational Institute) was included as a class-level control variable to account for potential influences and to obtain results net of these effects.
Analyses were conducted using Mplus 8 software version 1.6(1) (Muthén and Muthén 2017) with the Robust Maximum Likelihood (MLR) estimator, which is robust to nonnormality and accounts for nested data structures. Model fit was assessed using the MLR chi-square test statistic and multiple fit indices (comparative fit index [CFI], root mean square error of approximation [RMSEA] and standardized root mean square residual [SRMR]), referring to conventional criteria for an acceptable model fit (Hu and Bentler 1999).
Victimization was analyzed using a doubly latent approach with cross-level measurement invariance (Lüdtke et al. 2011; Marsh et al. 2012). In this approach, the construct is modeled as latent at the item level, and a latent aggregation of individual student responses is used to form indicators at classroom-level (Televantou et al. 2015). Employing latent measurement models at both levels allowed us to account for potential measurement errors.
Missing data, which ranged from 1.5% to 4.7%, were handled using the Full Information Maximum Likelihood method implemented in Mplus.

3. Results

Table 1 shows the frequency table for the victimization items.
The MCFA results confirmed the one-factor structure for victimization: CFI = 0.99; RMSEA = 0.03; SRMR = 0.013. Intraclass correlation (ICC) for victimization was 0.087, indicating that 8.7% of the variance in victimization is attributable to differences between classes.
Table 2 shows the standardized factor loadings for this model at both the within- and between-levels. At the within-level, the factor loadings of the items range from 0.50 to 0.81. The items load strongly onto the single factor at the between-level, ranging from 0.59 (“Bullied/hassled by other students at school by being hit, kicked, or shoved”) to 0.99 (“Bullied/hassled by other students at school”).
The fit statistics of the tested model were adequate (CFI = 0.953; RMSEA = 0.028; SRMR = 0.023; SRMRbetween = 0.104). At the student level (L1), the model explained 1.5% of the total variance in victimization (see Appendix A). All predictors showed significant effects: male students and students with an immigrant background (both first- and second-generation) reported higher levels of victimization, whereas students with higher socioeconomic status (SES) and better prior academic achievement reported lower levels of victimization than their peers.
The results of the multilevel SEM analysis at the classroom level are shown in Figure 1. The findings revealed that a higher proportion of male students in the class was associated with higher levels of victimization (β = 0.35, SE = 0.01, p < 0.001). Similarly, classrooms with a higher percentage of second-generation immigrant students (β = 0.11, SE = 0.02, p < 0.001), but not first-generation students (β = 0.01, SE = 0.02, p = 0.34), reported higher levels of victimization. In contrast, classroom academic achievement was negatively associated with victimization rates (β = −0.20, SE = 0.02, p < 0.001), after controlling for students’ individual achievement: students with similar academic performance tended to report less victimization in classrooms with higher average achievement. Classroom SES (β = −0.02, SE = 0.02, p = 0.30) and class size (β = 0.03, SE = 0.01, p = 0.06) were not significantly associated with victimization. At the classroom level, the model explained 31.7% of the variance in victimization.

4. Discussion

This study investigated the impact of classroom composition and size on bullying victimization in a population of 254,177 Italian 10th grade students. As pointed out in previous studies, bullying is a peer-group phenomenon (Williford and Zinn 2018) and classroom characteristics can influence group-level experiences. Our results are in line with this theoretical framework, as they indicated that classroom composition played a key role in bullying dynamics. Specifically, sex composition emerged as the most important factor, followed by classroom academic performance. Furthermore, a higher proportion of second-generation immigrant students in the classroom, but not first-generation immigrants, was associated with a slight but statistically significant increase in victimization. In contrast, neither socioeconomic composition nor class size showed a significant effect on bullying victimization.
The results concerning sex are consistent with previous studies that indicate that classrooms with a higher proportion of male students tend to exhibit higher levels of bullying victimization (Coelho and Sousa 2018; Khoury-Kassabri et al. 2004; Thornberg et al. 2017). A male-dominated classroom environment can contribute to a more aggressive school climate (Khoury-Kassabri et al. 2004), characterized not only by a higher prevalence of perpetrators but also by an increased number of male victims. Given the relationship between sex and the type of bullying, where boys are more often involved in physical forms and girls in relational or verbal forms of aggression (Menesini and Salmivalli 2017), it is crucial to consider not only the prevalence of male students, but also how classroom norms may shape these behaviors. For example, when the majority of students are male, physical forms of aggression may be more normalized, and even rewarded as a marker of social dominance, reinforcing peer group dynamics that sustain victimization (Rosen and Nofziger 2019). Conversely, in more gender-balanced classrooms, alternative pathways to recognition and status may weaken the link between male prevalence and bullying, reducing the likelihood of persistent victimization. These mechanisms help explain why sex composition emerges as an important contextual factor and highlight the need for interventions that target classroom climate and peer norms rather than individual students alone.
Regarding classrooms’ prior academic achievement, our findings build on previous research showing that students with lower academic performance are more likely to be victims of bullying. Academic ability may shape peer group perceptions, which could lead to the exclusion or mistreatment of students who underperform (Cavicchiolo et al. 2022; Plenty and Jonsson 2017; Schwartz et al. 2002). The present study extends these findings to the classroom level: regardless of individual achievement, students experience less victimization in higher-performing classrooms. This suggests that the overall academic performance of the class not only influences students’ well-being and academic self-concept (Alivernini et al. 2020; Belfi et al. 2012; Cavicchiolo et al. 2025), but also acts as a protective factor against negative school experiences such as victimization. Previous studies have highlighted that a learning-oriented classroom climate may discourage aggressive behaviors by reducing their social rewards (Garandeau et al. 2011). Garandeau et al. (2011) found that in classrooms where academic achievement was highly valued, aggressive students were more disliked, indicating that a learning-oriented classroom climate may discourage aggressive behaviors by reducing their social rewards. The importance of classroom-level academic performance is particularly salient in educational contexts such as Italy, where classrooms consist of stable groups of students and a substantial share of the variability in academic outcomes is attributable to the class or school attended (OECD 2023). In such settings, differences between classes can be considerable and persist across school years, potentially creating classroom environments in which students are at greater risk of victimization.
As regards immigrant density, our findings showed a significant positive association between the proportion of second-generation immigrant students and victimization, whereas the concentration of first-generation students showed no effect. This pattern is in line with the so-called “immigrant paradox” (Coll and Marks 2012; Suárez-Orozco et al. 2018). According to this phenomenon, second-generation youth exhibit less optimal school adjustment compared to their first-generation peers (Marks et al. 2014). This pattern appears to be paradoxical, as one might expect the opposite: first-generation students have less time to adjust to the difficulties of schooling in a new country and often possess lower proficiency in the host country’s language than later generations (Cavicchiolo et al. 2020, 2023; Diemer et al. 2014). One possible explanation is that, unlike first-generation students, second-generation students do not have the advantage of a dual frame of reference (i.e., one from the family of origin and one from the host country) (Suárez-Orozco et al. 2018) that might protect them from integration challenges. Our results show that when a high number of second-generation students are in the same classroom, these challenges may intensify, creating peer dynamics that might foster increased victimization.
In the present study, classroom SES was not significantly associated with victimization, consistent with previous findings highlighting the limited impact of group-level SES on bullying (Bokhove et al. 2022). One possible explanation relates to the levels of equity in education, which reflect the extent to which the school system provides learning opportunities to all students (OECD 2018). According to the OECD (2018), equity levels and socioeconomic segregation in schools vary across countries, with Italy being among those with the highest levels of equity and relatively low segregation (OECD 2018). This suggests that disadvantaged students in our sample might attend schools with resources and opportunities comparable to those of their more advantaged peers, potentially mitigating the effects of group-level SES on bullying. However, the absence of significant classroom SES effects may also reflect the complexity of group-level mediating mechanisms. Previous research has suggested that classroom SES can influence bullying behavior primarily through more proximal factors, such as teacher-student relationship quality, school climate, and teachers’ attitudes toward bullying (Thornberg et al. 2024).
Regarding class size, although larger classrooms are often assumed to be associated with more bullying episodes, empirical evidence supporting this claim is limited (Saarento et al. 2015). Consistent with this, in our study, class size was not significantly related to self-reported victimization. One possible explanation is that class size may influence victimization indirectly. Similarly to classroom SES, class size may operate through indirect pathways rather than direct mechanisms. Specifically, class size may affect victimization through its impact on classroom management, teacher style, and peer group dynamics. These factors may be more proximal predictors of victimization than structural characteristics like class size.

5. Limitations

Bullying victimization is a socially regulated experience, and the present study sheds new light on the role of classroom characteristics, which represent the most proximal and prominent environment for adolescents. Despite its strengths, this study is not without limitations. The variables considered referred to group characteristics present at the beginning of socialization processes (i.e., entry into high school), but longitudinal data would be needed to provide stronger evidence of causal relationships.
The study included the entire population of 10th grade students and a very large number of classes, in a context where classroom structures remain relatively stable throughout adolescence. While this enhances the robustness of the findings, it may also limit their generalizability to other age groups.
One of the strengths of our study, namely the use of the entire population, could also be regarded as a potential limitation, given the increased likelihood of detecting statistically significant results in very large samples. However, the fact that not all tested relationships were significant suggests that statistical power alone does not account for the observed findings.
Another limitation concerns the measurement of victimization, which was assessed through a scale with good psychometric properties but based solely on student self-reports. These may be influenced by biases such as social desirability. Future studies could strengthen the assessment by incorporating multiple informants (e.g., peers, teachers, or parents) to capture a broader perspective on bullying-related behavior (Casper et al. 2015).
Finally, the study was conducted within the Italian educational system, whose distinctive features may shape peer dynamics and victimization processes. While our findings may offer useful insights into educational systems with similar characteristics, caution is warranted when generalizing them to countries with different school structures.

6. Conclusions

This study highlights the important role of classroom context in student victimization. Specifically, when planning school-based monitoring and prevention programs, classroom composition in terms of sex and academic achievement should be carefully considered. Classrooms represent one of the most significant social contexts for adolescents, where they develop and sustain both positive and negative interactions with their peers. Therefore, intervention strategies aimed at promoting safer and more supportive relational environments should take into account the characteristics of the class attended by students, in addition to their individual characteristics.

Author Contributions

Conceptualization, E.C. and F.A.; methodology, E.C., F.A. and S.M.; formal analysis, E.C.; investigation, S.M. and I.D.L.; data curation, S.M., I.D.L. and L.G.; writing—original draft preparation, E.C.; writing—review and editing, G.R., L.G., M.Z., J.D., I.D.L., P.D., T.P., A.C., F.L., F.A. and S.M.; visualization, G.R., M.Z. and J.D.; supervision, S.M. and F.A.; project administration, F.A.; funding acquisition, F.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported by Sapienza University of Rome, “Economically deprived and immigrant youth: the protective role of psychological resources and educational context”, project number RD12318A949D7606.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the National Institute for the Evaluation of the Education and Training System (INVALSI). Data collection was approved by the Ministry of Education, University and Research, with Directive No. 85 of 12 October 2012, ensuring that the study adheres to both national and international guidelines.

Informed Consent Statement

Each school dealt with the process of informed consent and parental permission according to a National assessment protocol provided by the National Institute for the Evaluation of the Education and Training System (INVALSI). Informed consent was obtained from all the parents of the students involved in the study.

Data Availability Statement

Publicly available datasets were analyzed in this study. This data can be found here upon free registration: INVALSI—Statistical Office https://serviziostatistico.invalsi.it/catalogo-dati (accessed on 24 September 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Estimates and standard errors from multilevel analyses. Student level (L1).
Table A1. Estimates and standard errors from multilevel analyses. Student level (L1).
Student Level (L1)EstimateSE
Sex, male0.03 ***0.003
Immigrant background, first generation0.04 ***0.003
Immigrant background, second generation0.09 ***0.003
SES−0.06 ***0.003
Prior academic achievement−0.01 **0.003
Note. Standardized estimates. SE = standard error; SES = socioeconomic status. ** p < 0.01. *** p < 0.001.

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Socsci 14 00573 g001
Figure 1. Multilevel SEM results. Note. Standardized coefficients. *** p < 0.001. The dashed lines represent statistically non-significant effects. At the classroom level, the coefficients and explained variance in the model account for the type of school attended by the students (general, technical, and vocational upper secondary schools). Intraclass correlation (ICC) = 8.7%.
Figure 1. Multilevel SEM results. Note. Standardized coefficients. *** p < 0.001. The dashed lines represent statistically non-significant effects. At the classroom level, the coefficients and explained variance in the model account for the type of school attended by the students (general, technical, and vocational upper secondary schools). Intraclass correlation (ICC) = 8.7%.
Socsci 14 00573 g001
Table 1. Frequencies (%) for the four items of the victimization scale.
Table 1. Frequencies (%) for the four items of the victimization scale.
ItemsNeverNow and ThenWeeklyDaily
  • Bullied/hassled by other students at school
49.941.85.03.3
2.
Bullied/hassled by other students at school by being teased
63.629.64.02.8
3.
Bullied/hassled by other students at school by being isolated or shut out from others
73.021.73.12.2
4.
Bullied/hassled by other students at school by being hit, kicked, or shoved
92.84.41.31.5
Table 2. Standardized factor loadings of victimization scale items.
Table 2. Standardized factor loadings of victimization scale items.
ItemsStandardized Factor Loadings: WithinStandardized Factor Loadings: Between
  • Bullied/hassled by other students at school
0.810.99
2.
Bullied/hassled by other students at school by being teased
0.770.92
3.
Bullied/hassled by other students at school by being isolated or shut out from others
0.600.79
4.
Bullied/hassled by other students at school by being hit, kicked, or shoved
0.500.59
Note. All the values are statistically significant at p < 0.001.
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Cavicchiolo, E.; Raimondi, G.; Girelli, L.; Zacchilli, M.; Dawe, J.; Di Leo, I.; Diotaiuti, P.; Palombi, T.; Chirico, A.; Lucidi, F.; et al. How Classroom Composition and Size Shape Adolescent School Victimization: Insights from a Doubly Latent Multilevel Analysis of Population Data. Soc. Sci. 2025, 14, 573. https://doi.org/10.3390/socsci14100573

AMA Style

Cavicchiolo E, Raimondi G, Girelli L, Zacchilli M, Dawe J, Di Leo I, Diotaiuti P, Palombi T, Chirico A, Lucidi F, et al. How Classroom Composition and Size Shape Adolescent School Victimization: Insights from a Doubly Latent Multilevel Analysis of Population Data. Social Sciences. 2025; 14(10):573. https://doi.org/10.3390/socsci14100573

Chicago/Turabian Style

Cavicchiolo, Elisa, Giulia Raimondi, Laura Girelli, Michele Zacchilli, James Dawe, Ines Di Leo, Pierluigi Diotaiuti, Tommaso Palombi, Andrea Chirico, Fabio Lucidi, and et al. 2025. "How Classroom Composition and Size Shape Adolescent School Victimization: Insights from a Doubly Latent Multilevel Analysis of Population Data" Social Sciences 14, no. 10: 573. https://doi.org/10.3390/socsci14100573

APA Style

Cavicchiolo, E., Raimondi, G., Girelli, L., Zacchilli, M., Dawe, J., Di Leo, I., Diotaiuti, P., Palombi, T., Chirico, A., Lucidi, F., Alivernini, F., & Manganelli, S. (2025). How Classroom Composition and Size Shape Adolescent School Victimization: Insights from a Doubly Latent Multilevel Analysis of Population Data. Social Sciences, 14(10), 573. https://doi.org/10.3390/socsci14100573

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