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Article

Bullying and Victimization Among Youth Athletes: A Multivariate Analysis of School and Sport Environments

by
Efpraxia Kalapoda
1,*,
Chrysovalanto Staneloudi
2,
Ioannis Trigonis
3,
Evaggelia Manolaki
1,
Ioannis Tsartsapakis
1 and
Aglaia Zafeiroudi
4
1
Department of Physical Education and Sport Science at Serres, Aristotle University of Thessaloniki, 62100 Serres, Greece
2
Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sport Science at Serres, Aristotle University of Thessaloniki, 62100 Serres, Greece
3
Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece
4
Department Physical Education & Sport Science, University of Thessaly, 42100 Trikala, Greece
*
Author to whom correspondence should be addressed.
Adolescents 2026, 6(3), 37; https://doi.org/10.3390/adolescents6030037
Submission received: 25 February 2026 / Revised: 6 April 2026 / Accepted: 21 April 2026 / Published: 24 April 2026
Review Reports Versions Notes

Abstract

Bullying and victimization are prevalent in school and sport settings, yet they are rarely examined concurrently. This study explored the relationships between school and sport bullying among youth athletes, assessing whether demographic and sport-related factors are associated with these behaviors across contexts. Participants included 189 youth athletes (aged 8–15 years) from Central Macedonia, Northern Greece. They completed a demographic survey and the Bullying and Victimization Questionnaire twice, assessing both school and sport environments. A multivariate analysis of variance (MANOVA) evaluated the effects of gender, educational level, sport type, and contact classification, followed by regression analyses. Results showed that educational level yielded a significant multivariate effect, with secondary school students reporting higher involvement in school bullying, sport bullying, and sport victimization. Crucially, regression analyses revealed that school-context bullying and victimization were the strongest factors associated with corresponding behaviors in sports. Additionally, team sport participation was associated with sport victimization, while demographic factors were related to school bullying perpetration. These findings demonstrate the interconnected nature of bullying between school and sport environments, emphasizing the critical need for coordinated, multi-contextual prevention strategies among educators and coaches.

1. Introduction

Bullying is widely recognized as a deliberate and repeated form of aggressive behavior directed toward individuals who are perceived as less powerful [1]. It involves intentional harm, an imbalance of power and recurrent victimization, and is considered a pervasive public health concern with significant psychological, social and physical consequences. Victims often experience declines in self-esteem, social functioning and overall, well-being, whereas perpetrators may develop persistent antisocial patterns [2]. Although bullying has been extensively examined in school settings, its presence in youth sport environments has received comparatively less empirical attention, despite increasing media reports and growing concern among practitioners [3]. In the context of Greek youth sport, recent evidence highlights that bullying and victimization are significant concerns, with prevalence rates indicating that a notable percentage of young athletes experience such negative behaviors [4]. The competitive nature of sport, the emphasis on performance and the hierarchical relationships between athletes and coaches create a unique social environment in which bullying may manifest differently than in school contexts.
School remains the primary context in which bullying has been studied, with research consistently demonstrating high prevalence rates and notable gender differences. Boys tend to engage more frequently in direct physical aggression, whereas girls are more often involved in relational or indirect forms of bullying [5]. Bullying involvement is also associated with adverse health outcomes, including psychosomatic symptoms and increased school absenteeism [6]. More recent studies highlight the complexity of victimization experiences, showing that adolescents may be exposed to multiple forms of bullying, including physical, verbal, discriminatory and cyber, each with distinct developmental and gender-related patterns [7]. In Greece, large scale research has shown that school type, gender and age are significant factors associated with bullying involvement (Refs. [8,9], while moral disengagement and self-efficacy also play important roles [10,11]. These findings underscore the multifaceted nature of bullying and the need to examine how different social environments shape children’s experiences.
Youth sport represents another major social environment where children and adolescents interact, compete and develop social identities. Despite its widely acknowledged benefits for physical, emotional and social development, sport can also foster conditions that enable bullying, exclusion and harassment [12]. The structure of sport teams, the emphasis on hierarchy and performance, and the presence of peer-dominated spaces such as locker rooms create opportunities for negative peer interactions. Athletes who underperform or fail to meet competitive expectations may become targets of ridicule or exclusion [13], while locker rooms, often characterized by limited adult supervision, are particularly vulnerable to bullying incidents [14]. Victimization in sport has been linked to early dropout, emotional distress and maladaptive coping strategies [15]. Contemporary research shows that athletes respond to stressors through both emotion-focused and problem-focused coping strategies, each with distinct implications for psychological adjustment and help-seeking behaviors [16].
Differences across sport types further complicate the phenomenon. Individual sport athletes may experience heightened anxiety, performance pressure and self-focused responsibility, which can increase vulnerability to victimization [17,18]. These athletes often rely heavily on their coaches for guidance and emotional support, and the coach–athlete relationship may influence how they cope with bullying experiences [19]. Team sports, especially those involving physical contact, show higher rates of bullying behaviors, often occurring in peer-dominated spaces such as locker rooms [15,20]. Risk factors in team sports include lower athletic ability [21], performance expectations [22], obesity [23], disability [24], ethnicity [25], gender [26,27] and sexual orientation [28]. These findings highlight that bullying in sport is shaped by social hierarchies, performance norms and group dynamics rather than occurring randomly.
Combat sports present a unique context. While physical aggression is inherent to the discipline, long-term training in martial arts has been associated with reduced aggression, improved self-control and enhanced emotional regulation [29,30]. However, differences between martial arts styles indicate that some disciplines may foster more aggressive tendencies than others. For example, Shotokan karate is associated with lower levels of aggression compared to other Kumite systems, whereas Kyokushin karate is linked to higher levels of physical, verbal and social aggression [31]. These findings suggest that the culture and training philosophy of each sport may influence athletes’ behavioral tendencies and susceptibility to bullying.
Recent international studies confirm that bullying and harassment occur across all sport types, with team sports showing the highest prevalence of victimization and male athletes more frequently assuming the roles of perpetrators and bystanders [32]. Other research highlights that although prevalence rates may differ, bullying is present in team, individual and combat sports, with distinct behavioral patterns across roles [33]. Additional evidence suggests that organizational responses to bullying in sport are often insufficient, and athletes’ trust in coaches and support networks plays a critical role in reporting and addressing incidents [34]. Coaches themselves frequently lack adequate knowledge of bullying definitions, typologies and prevention strategies, underscoring the need for targeted education and intervention programs [35].
To provide a conceptual foundation for understanding the interconnectedness of school and sport environments, this study is grounded in the Social-Ecological Model [36]. According to this theoretical framework, youth development occurs within nested environmental systems. School and sport clubs represent two primary “microsystems” where adolescents interact with peers and authority figures. The intersection of these environments forms a “mesosystem”, suggesting a cross-contextual association where experiences in one setting can directly influence psychosocial outcomes in another.
Consequently, children’s experiences in one context may influence their behavior in another. For example, school victimization may increase vulnerability to bullying in sport, while sport participation may either buffer or exacerbate school bullying involvement depending on the quality of peer relationships and coaching practices. Several studies suggest that participation in sports can reduce school violence by promoting positive peer interactions, self-esteem and social skills [37,38,39]. However, other research indicates that sport participation alone is not sufficient to prevent bullying and may even expose youth to additional risks if the sport environment lacks appropriate supervision and ethical guidance [40,41,42]. By utilizing this theoretical lens, we can conceptually justify the necessity of evaluating school and sport bullying concurrently rather than in isolation.
Despite the growing body of literature, significant gaps remain. Few studies have simultaneously examined bullying in both school and sport environments, and even fewer have used multivariate approaches to explore how experiences in one context are related to behaviors in another. Understanding these cross-contextual relationships is essential, given that children’s social experiences are interconnected across settings and may reinforce or buffer one another. Moreover, limited research has examined how demographic and sport-related variables, such as gender, educational level, sport type, contact classification and training experience, jointly associate with bullying involvement across contexts.
The purpose of the present study was to examine bullying and victimization among youth athletes across school and sport environments and to identify demographic, sport-related and cross-contextual associations using multivariate analyses.
Research Hypotheses:
H1. 
Significant differences in bullying and victimization will exist based on educational level, primarily with secondary school students reporting higher involvement.
H2. 
Boys are expected to report higher levels of bullying perpetration than girls in both school and sport environments.
H3a. 
Athletes in team sports are expected to show higher levels of association with bullying involvement than athletes in individual sports.
H3b. 
Athletes in contact sports are expected to show higher levels of association with bullying involvement than athletes in non-contact sports.
H4. 
School bullying and school victimization are expected to be significantly associated with bullying and victimization in sport.
H5. 
Demographic variables (gender, age, educational level) and sport-related characteristics (sport type, contact classification, years of sport participation, weekly training frequency, and training months per year) will be significantly associated with bullying and victimization across contexts.

2. Materials and Methods

2.1. Participants

The study included 189 youth athletes (111 boys and 78 girls) aged 8 to 15 years (M = 12.16, SD = 1.77). Participants were recruited from sports clubs and school-based athletic programs in Central Macedonia, Northern Greece. Athletes represented both primary (n = 73) and lower secondary education (n = 116). At the time of the study, a wide range of sports was represented, including individual sports (n = 119) and team sports (n = 70), as well as contact (n = 102) and non-contact disciplines (n = 87).
In addition to demographic information, athletes reported key sport participation characteristics. On average, participants trained 3.90 times per week (SD = 1.15), for 9.62 months per year (SD = 1.88), and had been involved in organized sport for 3.92 years (SD = 2.60). Descriptive statistics for all continuous variables, including the four BVQ composite scores (school bullying, school victimization, sport bullying and sport victimization), are presented in Table 1 in the Section 2.
Inclusion criteria required that participants were currently engaged in organized sport training for at least one year and were enrolled in primary or lower secondary school. Athletes with diagnosed developmental, cognitive or behavioral disorders that could affect questionnaire comprehension were excluded. To adhere to ethical guidelines and protect participants’ privacy, no medical records were accessed. Instead, this information was confidentially self-reported by parents or legal guardians on the demographic background section attached to the informed consent forms. Participation was voluntary, and parental consent was obtained for all minors.
The sports represented in the sample reflected the activities naturally available within the participating clubs in the region. For analytical purposes, these were grouped into individual (tennis, swimming, track and field, table tennis, taekwondo, kick boxing, gymnastics) and team (basketball, volleyball, football) categories. Furthermore, they were classified into contact and non-contact categories based on the nature of physical interaction. Contact sports included disciplines involving direct bodily engagement or frequent physical collision (football, basketball, taekwondo, kick boxing), while non-contact sports included activities where physical interaction is absent or restricted by rules (tennis, swimming, track and field, table tennis, gymnastics). Notably, volleyball was classified as non-contact because, although it is a team sport, the rules strictly separate opponents by a net, practically eliminating direct physical engagement or the frequent bodily collisions inherent in contact sports like basketball or martial arts. These groupings were applied to facilitate statistical comparisons and do not reflect any selection criteria.

2.2. Instruments

Bullying and victimization were assessed using the Bullying and Victimization Questionnaire (BVQ), originally developed by Olweus [43]. The Greek version of the BVQ, which has been previously adapted and used in Greek educational settings [44], was employed in this study. This initial psychometric evaluation [44] established the instrument’s conceptual alignment with the original scale and reported satisfactory properties for Greek youth.
The BVQ consists of sixteen items rated on a 5-point Likert scale (1 = “not at all”, 2 = “very little”, 3 = “a little”, 4 = “quite a lot”, 5 = “very much”). In the current sample, while the full 5-point scale was available to participants, the observed responses ranged from 1 to 4, as no athlete selected the highest frequency option (“very much”) for any of the items; consequently, the mean scores reported reflect this observed range. Eight items assess bullying perpetration (e.g., “I have bullied other children”), while the remaining eight items assess victimization (e.g., “Other children have bullied me”).
For the purposes of the present study, the BVQ was administered twice: once for the school environment and once for the sport environment. Four composite scores were created: school bullying, school victimization, sport bullying and sport victimization. To ensure the reliability of the instrument for this specific dual-context application, internal consistency was calculated directly from the present sample. Cronbach’s alpha coefficients demonstrated high reliability across all subscales: school bullying (α = 0.84), school victimization (α = 0.86), sport bullying (α = 0.82), and sport victimization (α = 0.85). Although a full Confirmatory Factor Analysis (CFA) was not performed, due to the modest sample size (N = 189) relative to the complexity of a 32-item dual-context model, the high internal consistency and the instrument’s established history [43,44] support its suitability. The absence of a context-specific CFA is acknowledged as a methodological limitation.
In addition to the BVQ, a short demographic and sport participation questionnaire was developed. This instrument collected essential background information regarding each athlete’s personal and athletic profile. Participants reported their gender, age, school grade and educational level. They also provided information about their sport, including whether they participated in an individual or team sport and whether their sport was classified as contact or non-contact. Further items assessed years of sport participation, weekly training frequency, training months per year and competitive category (competitive vs. pre-competitive). All items were phrased clearly and were age-appropriate for athletes aged 8 to 15 years.

2.3. Procedure

Prior to the main analyses, an a priori power analysis was conducted using G*Power 3.1. For a MANOVA with four dependent variables, a medium effect size (f2 = 0.0625), and an alpha level of 0.05, the required sample size to achieve a power of 0.80 was determined to be 170 participants. Thus, the final sample of 189 athletes was considered sufficient to detect significant effects.
A convenience sampling method was employed to recruit participants from various sports clubs and school-based athletic programs in Central Macedonia, Northern Greece. Data collection was conducted in collaboration with these organizations, whose coaches and club administrators were first informed about the aims and procedures of the study and granted permission for data collection. Parents or legal guardians received written information describing the study’s purpose, confidentiality procedures and voluntary nature of participation, and provided written consent.
Questionnaires were administered in small groups before or after scheduled training sessions, in a quiet setting free from distractions. Given the sensitive nature of the behaviors assessed, specific measures were implemented to minimize social desirability bias and protect ecological validity. Data collection strictly avoided peer-dominated spaces, such as locker rooms, where athletes might feel monitored. Instead, participants were physically spaced apart in controlled areas (e.g., meeting rooms or empty classrooms) to ensure that teammates could not oversee each other’s responses. Athletes were informed that their responses were anonymous and that there were no right or wrong answers. They were encouraged to answer honestly and were assured that their coaches and peers would not have access to their responses. To further guarantee confidentiality and eliminate adult influence, coaches and team staff were explicitly excluded from the room during the entire administration process. Completion time ranged from 10 to 15 min. To address the potential dependency of observations within specific sports clubs, participants were recruited from a wide range of diverse teams and settings, while the standardized administration environment was designed to ensure that individual responses remained independent and unaffected by immediate peer or coaching influence.
The study adhered to ethical standards for research with minors and was conducted in accordance with the Declaration of Helsinki by the Internal Ethics Committee of the Department of Physical Education and Sport Science, in Serres, Greece of Aristotle University of Thessaloniki (ERC-024/2025, 15 December 2025).

2.4. Statistical Analysis

All analyses were conducted using IBM SPSS Statistics (version 29.0, IBM Corp., Armonk, NY, USA). Descriptive statistics (means, standard deviations, frequencies and percentages) were computed for all variables. Internal consistency of the BVQ subscales was assessed using Cronbach’s alpha.
A multivariate analysis of variance (MANOVA) was performed to examine the effects of gender, educational level, sport type (individual vs. team) and contact classification (contact vs. non-contact) on the four dependent variables: school bullying, school victimization, sport bullying and sport victimization. Wilks’ Lambda was used as the primary multivariate test statistic. Significant multivariate effects were followed by univariate ANOVAs with partial eta squared as an index of effect size.
Four multiple regression analyses were subsequently conducted. The first two models examined factors associated with school bullying and school victimization, including gender, age, educational level, sport type, contact classification, years of sport participation, weekly training frequency, and training months per year. The remaining two models examined the associations for sport bullying and sport victimization, incorporating all the aforementioned variables along with school bullying and school victimization as additional independent variables.
Assumptions of normality, linearity, homoscedasticity and multicollinearity were evaluated through residual plots, tolerance values and variance inflation factors.

3. Results

Descriptive statistics were first examined for all continuous variables included in the study, namely age, years of sport participation, weekly training frequency, training months per year and the four composite BVQ scores assessing bullying and victimization in school and sport contexts. The means, standard deviations and observed score ranges for all continuous measures are presented in Table 1.
Frequencies and percentages were subsequently calculated for all categorical variables describing the demographic and sport-related characteristics of the sample, including gender, school grade, educational level, specific sport, sport type, contact classification and competitive category. The distribution of participants across all categorical classifications is shown in Table 2.
As detailed in the Section 2, internal consistency was assessed for each of the four BVQ subscales. Cronbach’s alpha coefficients indicated satisfactory reliability across all scales, as displayed in Table 3.
Prior to conducting the MANOVA, fundamental statistical assumptions were evaluated. Univariate normality was assessed using the Shapiro–Wilk test (W range = 0.96–0.98, p range = 0.07–0.18). The assumption of multicollinearity was rigorously tested using Variance Inflation Factor (VIF) and Tolerance statistics. All VIF values were below 3.2 (well under the threshold of 5), and Tolerance values were above 0.30, indicating that multicollinearity did not bias the models. The assumption of homogeneity of variance–covariance matrices was examined using Box’s M test (Box’s M = 23.41, p = 0.214), justifying the use of Wilks’ Lambda. Given the robustness of MANOVA to minor violations when groups are nearly equal in size, the current sample (N = 189) provided adequate statistical power. A multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, educational level, sport type, and contact classification on the dependent variables. The multivariate test revealed a statistically significant overall effect of educational level, Wilks’ Λ = 0.905, F(4, 171) = 4.506, p = 0.002, partial η2 = 0.095. No other main effects or interaction effects reached statistical significance at the multivariate level. Full multivariate results are presented in Table 4.
Follow-up univariate analyses indicated that educational level significantly affected school bullying, F(1, 174) = 14.111, p < 0.001, partial η2 = 0.075, sport bullying, F(1, 174) = 11.667, p < 0.001, partial η2 = 0.063, and sport victimization, F(1, 174) = 5.975, p = 0.016, partial η2 = 0.033. Gender had a statistically significant effect on school bullying, F(1, 174) = 4.071, p = 0.045, partial η2 = 0.023, with boys reporting higher perpetration scores. Although the effect of sport type on sport victimization approached the significance threshold, F(1, 174) = 3.707, p = 0.056, it did not reach statistical significance. Detailed univariate results are provided in Table 5.
Four multiple regression analyses were conducted to examine the associations between demographic variables, sport characteristics, and bullying/victimization roles. The first model, examining factors associated with school bullying perpetration, was statistically significant, F(8, 180) = 4.571, p < 0.001 (Adjusted R2 = 0.132). Significant associated factors included gender (β = −0.218, p = 0.003), educational level (β = 0.279, p = 0.021), sport type (β = 0.161, p = 0.031) and contact classification (β = 0.154, p = 0.048). Conversely, the model for school victimization was not statistically significant, F(8, 180) = 1.610, p = 0.125, and thus individual predictors were not further interpreted. Regression coefficients for both school models are presented in Table 6.
The remaining two regression models examined the associated role of school-based experiences on bullying and victimization within the sport environment (Table 7). The model for sport bullying perpetration demonstrated high explanatory power, F(10, 178) = 14.154, p < 0.001, accounting for 41.2% of the total variance (Adjusted R2 = 0.412). School bullying emerged as the primary associated factor (β = 0.499, p < 0.001), followed by school victimization (β = 0.141, p = 0.047). Finally, sport victimization was also significantly accounted for by the overall model, F(10, 178) = 8.643, p < 0.001 (Adjusted R2 = 0.289). The strongest associated factor for victimization in sport was school victimization (β = 0.394, p < 0.001), followed by school bullying (β = 0.178, p = 0.033) and participation in team sports (β = 0.155, p = 0.024).

4. Discussion

The present study examined bullying and victimization among youth athletes across school and sport environments, focusing on demographic, sport-related and cross-contextually associated factors. The findings provide meaningful insights into the developmental and contextual factors that shape adolescents’ experiences of bullying, although they should be interpreted with caution due to the modest sample size and the cross-sectional design. Nevertheless, the observed patterns align with a substantial body of international research and contribute to a more integrated understanding of how bullying manifests across the two primary social environments in which young people spend much of their time: school and organized sport.
One of the most consistent findings in the literature concerns gender differences in bullying involvement. Boys typically report higher levels of physical and direct aggression, whereas girls tend to experience more relational or indirect forms of victimization [5,45,46]. In the present study, gender showed a small but statistically significant association on school bullying, with boys reporting higher levels of perpetration. This finding is consistent with earlier work indicating that boys are more likely to engage in overt forms of aggression during early adolescence, a developmental period characterized by heightened sensitivity to peer status and dominance hierarchies [47,48]. The absence of gender differences in sport bullying and sport victimization may reflect the structured nature of sport environments, where behaviors are shaped by coaching practices, team norms and performance expectations rather than by gender alone. It is also possible that the sample size limited the detection of subtle gender effects in sport settings.
Educational level emerged as the strongest demographic factor in the MANOVA, with secondary school students reporting higher levels of school bullying, sport bullying and sport victimization. This pattern is consistent with international evidence showing that bullying tends to peak during early adolescence, particularly between the ages of 11 and 14 [46,47]. Several large-scale studies have documented increased vulnerability to victimization during this developmental period, which is marked by intensified peer competition, shifting social hierarchies and increased academic and social pressures [48,49]. The higher levels of bullying and victimization among older athletes in the present study may reflect these developmental dynamics. As adolescents progress through school, peer groups become more complex and competitive, and social status becomes increasingly salient. These changes may intensify both the perpetration and experience of bullying. The finding that educational level was associated with bullying in both school and sport environments suggests that developmental factors influence behavior across contexts, reinforcing the idea that bullying is not confined to a single setting but reflects broader social and emotional processes.
Contrary to expectations, sport type and contact classification did not produce significant multivariate effects. This finding diverges from studies reporting higher bullying rates in team sports and contact sports, where physicality, competition and group dynamics may create conditions conducive to aggression [15,20,50]. However, the regression analysis showed that participation in team sports was associated with higher school bullying and higher sport victimization, suggesting that sport type may still play a role, albeit in more nuanced ways. Team sports often involve complex social hierarchies, which can increase opportunities for exclusion, ridicule or dominance behaviors [21,22]. At the same time, individual sports may expose athletes to performance-related stress and self-focused pressure, which can also contribute to victimization [17,18]. Crucially, the lack of significant differences between contact and non-contact sports suggests that the physical nature of the sport itself is less strongly associated with bullying than the overarching “sporting climate”. While not directly measured in the present study, it is plausible that psychosocial factors and the overall environment established by the coach play a more significant role than physical contact rules. Future research should empirically examine these climate-related variables to better understand their specific contribution. Previous research has shown that locker rooms, in particular, are high-risk spaces for bullying due to limited adult supervision and strong peer influence [14,50]. Ultimately, the absence of significant effects for contact classification indicates that contact intensity alone does not dictate bullying risk without considering broader team dynamics, coaching practices, and the implicit culture of the club.
The lack of significant differences for contact classification might also be attributed to the highly regulated nature of modern contact sports in Greece (e.g., martial arts). In these settings, strict rules, official supervision, and a traditional emphasis on discipline and respect for the opponent may counteract the inherent aggressiveness of physical contact, thereby mitigating bullying risks. However, these mixed findings underscore the complexity of sports categorization; for instance, recent evidence indicates that participation in specific organized physical activities, such as wrestling or combat sports, may present distinct risk profiles for both victimization and perpetration compared to general unorganized physical activity [51].
One of the most important contributions of the study lies in the examination of cross-contextual associated factors. The regression analyses demonstrated that school bullying and school victimization were the strongest factors related to sport bullying and sport victimization. This finding provides empirical support for ecological models of development, which emphasize the interplay between different social systems in shaping behavior. Adolescents who engage in bullying at school may carry similar behaviors into sport settings, where competitive pressures and peer interactions can reinforce existing patterns [12,32]. Likewise, students who experience victimization at school may be more vulnerable to negative treatment in sport, possibly due to lower self-esteem, reduced social support or difficulties in forming positive peer relationships [52,53]. These results align with research showing that victimization in one context can increase susceptibility to victimization in another, particularly when adolescents lack protective factors such as supportive friendships, positive school climate or strong coach–athlete relationships [54,55].
The finding that school bullying was the strongest factor associated with sport bullying underscores the importance of early identification and intervention in school settings. If bullying behaviors are not addressed at school, they may generalize to other environments, including sport. Similarly, the strong associated role of school victimization for sport victimization suggests that vulnerable adolescents may require targeted support across multiple domains of their lives. Recent evidence from 2025 further emphasizes that sport-based interventions, when integrated with school policies, can significantly mitigate bullying behaviors by fostering a unified supportive climate [56]. These cross-contextual effects highlight the need for coordinated prevention strategies that involve both schools and sport organizations. Interventions that focus solely on one environment may overlook the broader social patterns that contribute to bullying. In this context, school physical education often serves as a crucial transitional environment where traditional school bullying dynamics intersect with physically demanding activities, highlighting the need for holistic observational and preventive strategies [57]. Research has shown that positive school climate, strong teacher–student relationships and parental involvement can reduce victimization and buffer its negative effects [52,58]. Comparable findings in sport suggest that supportive coaching, clear behavioral expectations and inclusive team cultures can reduce bullying and enhance athletes’ well-being [35,56]. Adapting established evidence-based frameworks from the school context, such as the Olweus Bullying Prevention Program, to youth sport settings could provide a structured and effective approach to prevention. These patterns are consistent with extensive evidence showing that bullying during early adolescence is associated with significant short- and long-term consequences for mental health, academic functioning and overall, well-being [46,48,49].
The study also revealed that demographic and sport-related variables explained a modest proportion of variance in school bullying and school victimization, but a substantially larger proportion of variance in sport bullying and sport victimization. This suggests that bullying in sport may be influenced by a combination of individual characteristics and experiences in other contexts, particularly school. The relatively low explanatory power of demographic variables for school victimization is consistent with research showing that victimization is shaped by a complex interplay of individual vulnerabilities, peer dynamics and contextual factors [59,60]. The stronger association of school bullying and victimization for sport outcomes highlights the importance of understanding bullying as a cross-contextual phenomenon rather than as a behavior confined to a single environment.
The pattern of findings provided partial support for the proposed hypotheses. Gender differences were observed primarily in school bullying and victimization, whereas educational level emerged as a consistent associated factor across school and sport environments. The expectation that team and contact sports would show higher bullying involvement was only partially confirmed, with team sports, but not contact classification, being associated with higher bullying and victimization. As anticipated, school bullying and victimization were strong correlates of bullying and victimization in sport, highlighting the cross-contextual nature of these behaviors. Finally, demographic and sport-related variables accounted for a modest proportion of variance in school bullying and victimization, but played a more substantial role when combined with school experiences in explaining sport-related outcomes.
Although the findings provide meaningful insights, several limitations must be acknowledged. The sample consisted of athletes aged 8–15 years from sports clubs located in Central Macedonia, Northern Greece, which may limit the generalizability of the results to broader youth sport populations. The distribution of sports represented in the sample reflected the programs available within participating clubs, resulting in uneven representation across sport types. Although this naturalistic sampling enhances ecological validity, it may restrict the extent to which findings can be generalized to athletes in other sports or competitive levels. The study relied exclusively on self-report questionnaires completed privately and anonymously, which, despite reducing social desirability pressures, may still be subject to under- or over-reporting of bullying involvement. The cross-sectional design limits causal interpretations, and contextual variables such as coaching style, team climate and parental involvement were not assessed. Future research would benefit from longitudinal designs, multi-informant data and more diverse samples across regions and sport disciplines.
Taken together, the findings highlight the importance of examining bullying as a cross-contextual phenomenon shaped by developmental, interpersonal and environmental factors. Understanding how experiences in school and sport interact can inform more comprehensive models of adolescent peer relations and guide future research toward integrated approaches.

5. Conclusions

The present study examined bullying and victimization among youth athletes across school and sport environments, highlighting the extent to which experiences in one context are linked to behaviors in another. Secondary school students reported higher levels of bullying and victimization than primary school students, and gender was significantly associated with school bullying. School bullying and school victimization emerged as the strongest factors related to bullying involvement in sports, underscoring the cross-contextual nature of adolescents’ social experiences.
Despite the study’s limitations, the findings contribute to a growing body of evidence highlighting the interconnected nature of bullying across school and sport contexts. The results emphasize the need for integrated prevention and intervention strategies that address the broader social ecology of adolescents’ lives. Rather than relying on generic awareness programs, stakeholders must implement specific, actionable, cross-contextual strategies. For example, “Anti-Bullying Policies” within schools should be formally aligned with “Sports Club Charters” to create a unified, zero-tolerance code of conduct that youth athletes must follow in both domains. Furthermore, coach education programs must be updated; coaches should be specifically trained to identify behavioral markers of victimization (e.g., social withdrawal or sudden drops in self-esteem) that may have originated in the school environment before they escalate within the team. Sports organizations could also benefit from establishing “dual-environment reporting systems” or designating team welfare officers who can safely liaise with school counselors to monitor at-risk youths. In addition to these structural changes, schools and sport organizations should collaborate to promote positive peer relationships and strengthen adult supervision in high-risk areas such as locker rooms. Programs that enhance adolescents’ social skills, emotional regulation and resilience may further reduce vulnerability to victimization and mitigate its negative consequences. Given the well-documented short- and long-term effects of bullying on mental health, academic performance and overall well-being, these specific and coordinated efforts across educational and athletic systems are essential.

Author Contributions

Conceptualization, E.K. and E.M.; methodology, E.K. and E.M.; software, E.K. and I.T. (Ioannis Tsartsapakis); validation, E.K., I.T. (Ioannis Tsartsapakis) and A.Z.; formal analysis, E.K. and I.T. (Ioannis Tsartsapakis); investigation, C.S., I.T. (Ioannis Trigonis) and A.Z.; resources, C.S., I.T. (Ioannis Trigonis) and A.Z.; data curation, E.K., E.M., I.T. (Ioannis Tsartsapakis) and C.S.; writing—original draft preparation, I.T. (Ioannis Tsartsapakis), E.K. and E.M.; writing—review and editing, I.T. (Ioannis Tsartsapakis) and E.K.; visualization, E.K. and E.M.; supervision, E.K., I.T. (Ioannis Tsartsapakis), A.Z. and I.T. (Ioannis Trigonis); project administration, C.S., I.T. (Ioannis Trigonis) and A.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the Department of Physical Education and Sport Science, in Serres, Greece of Aristotle University of Thessaloniki (ERC-024/2025, 15 December 2025).

Informed Consent Statement

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

Data Availability Statement

Data available on request due to restrictions (e.g., privacy, legal or ethical reasons).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ANOVAAnalysis of Variance
BVQBullying and Victimization Questionnaire
MANOVAMultivariate Analysis of Variance
dfDegrees of Freedom
SPSSStatistical Package for the Social Sciences
βStandardized Regression Coefficient
η2 (partial eta squared)Effect Size
Λ (Wilks’ Lambda)Multivariate Test Statistic
R2Coefficient of Determination

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Table 1. Descriptive statistics for continuous variables.
Table 1. Descriptive statistics for continuous variables.
VariableNMinimumMaximumMSD95% CI
Age18981512.161.77[11.91, 12.41]
Training sessions per week189273.901.15[3.74, 4.06]
Training months per year1892129.621.88[9.35, 9.89]
Years of sport participation1891103.922.60[3.55, 4.29]
School bullying189141.420.52[1.35, 1.49]
School victimization189141.710.70[1.61, 1.81]
Sport bullying189131.190.36[1.14, 1.24]
Sport victimization189141.250.45[1.19, 1.31]
Note: M = Mean; SD = Standard deviation; 95% CI = 95% Confidence Interval for the mean; N = number of participants. BVQ scores range from 1 to 5, although the maximum observed score in this sample was 4. Higher scores indicate higher levels of bullying or victimization.
Table 2. Frequencies for categorical variables.
Table 2. Frequencies for categorical variables.
VariableCategoryNPercent (%)
GenderBoys11158.7
Girls7841.3
School gradeGrade 4 (primary)1910.0
Grade 5 (primary)2111.1
Grade 6 (primary)3317.5
Grade 7 (Secondary)3920.6
Grade 8 (Secondary)3317.5
Grade 9 (Secondary)4423.3
Educational levelPrimary school7338.6
Secondary school11661.4
SportTennis189.5
Swimming2613.8
Volleyball1910.1
Football147.4
Taekwondo157.9
Track and field147.4
Basketball3719.6
Kick boxing3619.0
Table tennis105.3
Sport typeIndividual11963.0
Team7037.0
Contact classificationContact10254.0
Non-contact8746.0
Competitive categoryCompetitive6836.0
Pre-competitive12164.0
Note: Percentages are calculated within each categorical variable and may not sum to 100 due to rounding. In the Greek educational system, Grades 4–6 correspond to primary school, whereas Grades 7–9 correspond to lower secondary school (Gymnasium).
Table 3. Internal consistency (Cronbach’s alpha) for the BVQ subscales.
Table 3. Internal consistency (Cronbach’s alpha) for the BVQ subscales.
SubscaleCronbach’s αNumber of Items
School bullying (perpetration)0.848
School victimization0.868
Sport bullying (perpetration)0.828
Sport victimization0.858
Note: Cronbach’s α values above 0.80 indicate good internal consistency. All BVQ subscales consist of 8 items rated on a 1–4 Likert scale.
Table 4. Multivariate effects (Wilks’ Lambda).
Table 4. Multivariate effects (Wilks’ Lambda).
EffectWilks’ ΛFHypothesis dfError dfpPartial η2
Gender0.9681.42841710.2270.032
Educational level0.9054.50641710.0020.095
Individual vs. team0.9751.10941710.3540.025
Contact vs. non-contact0.9920.36141710.8360.008
Gender × Educational level0.9800.88841710.4720.020
Gender × Individual/team0.9980.06541710.9920.002
Gender × Contact0.9930.28941710.8850.007
Educational level × Individual/team0.9671.44541710.2210.033
Educational level × Contact0.9790.90241710.4640.021
Individual/team × Contact0.9820.80441710.5240.018
Three-way interactionsAll ns—————
Note: Λ = Wilks’ Lambda; df = degrees of freedom; p = significance level; partial η2 = effect size; ns = non-significant.
Table 5. Univariate ANOVAs for each dependent variable.
Table 5. Univariate ANOVAs for each dependent variable.
EffectSchool Bullying F (p)η2School Victimization F (p)η2Sport Bullying F (p)η2Sport Victimization F (p)η2
Gender4.071 (0.045)0.0232.714 (0.101)0.0150.060 (0.806)0.0000.044 (0.834)0.000
Educational level14.111 (<0.001)0.0751.884 (0.172)0.01111.667 (<0.001)0.0635.975 (0.016)0.033
Individual vs. team2.327 (0.129)0.0131.831 (0.178)0.0102.320 (0.130)0.0133.707 (0.056)0.021
Contact vs. non-contact0.692 (0.407)0.0041.198 (0.275)0.0070.109 (0.741)0.0010.038 (0.846)0.000
Gender × Educational level2.475 (0.117)0.0140.076 (0.783)0.0001.339 (0.249)0.0080.092 (0.762)0.001
Gender × Individual/team0.115 (0.734)0.0010.015 (0.901)0.0000.156 (0.693)0.0010.179 (0.673)0.001
Gender × Contact0.493 (0.483)0.0030.437 (0.509)0.0030.035 (0.851)0.0000.017 (0.898)0.000
Educational level × Individual/team0.867 (0.353)0.0050.331 (0.566)0.0020.277 (0.600)0.0021.132 (0.289)0.006
Educational level × Contact0.812 (0.369)0.0050.281 (0.597)0.0021.385 (0.241)0.0080.557 (0.456)0.003
Individual/team × Contact0.513 (0.475)0.0030.517 (0.473)0.0033.129 (0.079)0.0182.183 (0.141)0.012
Note: F = F-statistic; p = significance level; η2 = partial eta squared (effect size). p-values in parentheses correspond to the F-value in the same cell.
Table 6. Multiple regression models examining factors associated with school bullying and school victimization.
Table 6. Multiple regression models examining factors associated with school bullying and school victimization.
PredictorSchool Bullying (β)tp95%
CI		School Victimization (β)tp95% CI
Gender−0.218−3.0330.003[−0.37, −0.08]−0.163−2.1490.033[−0.44, −0.02]
Age0.1000.8440.400[−0.04, 0.10]0.1030.8250.410[−0.06, 0.14]
Educational level0.2792.3320.021[0.05, 0.54]0.0680.5360.593[−0.26, 0.45]
Individual vs. team0.1612.1800.031[0.02, 0.33]0.1361.7370.084[−0.03, 0.42]
Contact vs. non-contact0.1541.9910.048[0.00, 0.32]0.1221.4890.138[−0.06, 0.40]
Years of participation−0.002−0.0240.981[−0.03, 0.03]0.0450.5300.597[−0.03, 0.06]
Weekly training days−0.004−0.0470.963[−0.07, 0.07]0.0050.0610.952[−0.09, 0.10]
Training months−0.067−0.9300.354[−0.06, 0.02]−0.089−1.1560.249[−0.09, 0.02]
Model R20.169 0.067
Adjusted R20.132 0.025
Model F4.571 <0.001 1.610 0.125
Note: β = standardized regression coefficient; t = t-statistic; p = significance level; R2 = coefficient of determination; Adjusted R2 = adjusted coefficient of determination; F = model F-statistic.
Table 7. Multiple regression models examining factors associated with sport bullying and sport victimization.
Table 7. Multiple regression models examining factors associated with sport bullying and sport victimization.
FactorSport Bullying (β)tp95%
CI		Sport Victimization (β)tp95%
CI
Gender0.0661.0910.277[−0.04, 0.13]0.0450.6770.500[−0.08, 0.16]
Age0.0390.3990.690[−0.03, 0.05]−0.019−0.1740.862[−0.06, 0.05]
Educational level0.1301.3020.195[−0.05, 0.24]0.1151.0410.299[−0.09, 0.30]
Individual vs. team0.1131.8340.068[−0.01, 0.17]0.1552.2810.024[0.02, 0.26]
Contact vs. non-contact0.0510.7860.433[−0.05, 0.13]0.0010.0150.988[−0.12, 0.12]
Years of participation−0.126−1.9140.057[−0.03, 0.00]−0.013−0.1810.857[−0.03, 0.02]
Weekly training days0.0811.2900.199[−0.01, 0.06]0.0480.7020.484[−0.03, 0.07]
Training months0.0751.2550.211[−0.01, 0.04]0.0510.7810.436[−0.02, 0.04]
School bullying0.4996.653<0.001[0.25, 0.45]0.1782.1540.033[0.01, 0.29]
School victimization0.1411.9970.047[0.00, 0.14]0.3945.055<0.001[0.15, 0.35]
Model R20.443 0.327
Adjusted R20.412 0.289
Model F14.154 <0.001 8.643 <0.001
Note: β = standardized regression coefficient; t = t-statistic; p = significance level; R2 = coefficient of determination; Adjusted R2 = adjusted coefficient of determination; F = model F-statistic.
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Kalapoda, E.; Staneloudi, C.; Trigonis, I.; Manolaki, E.; Tsartsapakis, I.; Zafeiroudi, A. Bullying and Victimization Among Youth Athletes: A Multivariate Analysis of School and Sport Environments. Adolescents 2026, 6, 37. https://doi.org/10.3390/adolescents6030037

AMA Style

Kalapoda E, Staneloudi C, Trigonis I, Manolaki E, Tsartsapakis I, Zafeiroudi A. Bullying and Victimization Among Youth Athletes: A Multivariate Analysis of School and Sport Environments. Adolescents. 2026; 6(3):37. https://doi.org/10.3390/adolescents6030037

Chicago/Turabian Style

Kalapoda, Efpraxia, Chrysovalanto Staneloudi, Ioannis Trigonis, Evaggelia Manolaki, Ioannis Tsartsapakis, and Aglaia Zafeiroudi. 2026. "Bullying and Victimization Among Youth Athletes: A Multivariate Analysis of School and Sport Environments" Adolescents 6, no. 3: 37. https://doi.org/10.3390/adolescents6030037

APA Style

Kalapoda, E., Staneloudi, C., Trigonis, I., Manolaki, E., Tsartsapakis, I., & Zafeiroudi, A. (2026). Bullying and Victimization Among Youth Athletes: A Multivariate Analysis of School and Sport Environments. Adolescents, 6(3), 37. https://doi.org/10.3390/adolescents6030037

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