Influences of Teachers, Students and School Climate on Bullying Victimization: Evidence from China Ying Zhu, 1,3 Yiying Teng 2,3 1. Shanghai Sanda University, Shanghai, China 2. Shanghai Zhongqiao Vocational and Technical University, Shanghai, China; 3. Chapman University, California, USA Abstract: Given the common occurrence of school bullying incidents and high prevalence rates of victimization in China, this study aims to explore the association between multiple school-related predictors and Chinese adolescents’ overall experiences with bullying victimization. Guided by the social-ecological framework for violence prevention, this study integrated different factors involving teachers, students, and school climate into one single research to detect the bullying problem more systematically and holistically. Further, the study applied the data from the 2018 Program for International Student Assessment while utilizing binary logistic regression analyses to perceive anti-bullying variables and their relationships with bullying victimization. The study revealed that teachers’ emotional, instrumental, and informational support other than appraisal support were negatively associated with students’ experiences of being bullied and victimized. The research also indicated that students’ sense of belonging, a cooperative school environment, and classroom disciplinary climate played a buffering role in bullying victimization while competition in school settings adversely increased overall bullying exposure. The results have highlighted the integration of various predictors in influencing multiple social relations and school environments to battle against in-person bullying. The results also have implications for stopping cyberbullying to achieve inclusive school education for all in the post-COVID-19 era. Best Evidence in Chinese Education 2022; 12(1):1547-1571. Doi: 10.15354/bece.22.or065 How to Cite: Zhu, Y., & Teng, Y. (2022). Influences of teachers, students and school climate on bullying victimization: Evidence from China. Best Evidence in Chinese Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No.1, 2022 1548 Education, 12(1):1547-1571. Keywords: Bullying Victimization, Classroom Disciplinary Climate, Cooperation and Competition, Sense of Belonging, Teacher Support About the Authors: Ying Zhu, Shanghai Sanda University, Shanghai, China; and Chapman University, California, USA. E-mail: yinzhu@chapman.edu Correspondence to: Yiying Teng, Shanghai Zhongqiao Vocational and Technical University, Shanghai, China; and Chapman University, California, USA. E-mail: yiteng@chapman.edu Author Contribution: Zhu and Teng contributed equally to the design, draft, critical revision, and final agreement of the present article to be published. Conflict of Interests: None. © 2022 Insights Publisher. All rights reserved. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed by the Insights Publisher. mailto:yinzhu@chapman.edu mailto:yiteng@chapman.edu http://www.creativecommons.org/licenses/by-nc/4.0/ Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1549 HE significance of bullying prevention and intervention has been well addressed in a series of initiatives taken by the Chinese government, including The Guidance on the Prevention and Treatment of Bullying and School Violence in 2016, Comprehensive Plan on Strengthening the Management of Bullying among Primary and Middle School Students in 2017, and the newly revised Minor Protection Law that took effect in 2021. However, school bullying still topped the agenda of this year’s two plenary sessions of China’s political bodies (2022 two sessions) and incidents of bul- lying victimization are often reported in media outlets. In one case, a teenag- er in Guangdong Province drowned after being slapped and knocked by peers in a restroom (Zuo, 2021); in another case, an adolescent from Anhui Province suffered from being bullied by a group of 12 schoolmates (China National Radio [CNR], 2022). These single incidents are just a tip of the ice- berg and in fact, more instances of school bullying have surfaced with vic- timization constituting a major source of injuries (Li et al., 2020). Statistics from a national survey led by Central China Normal University has revealed that the proportion of students who had bullying experiences in 2019 and 2020 amounted to 32.4 percent (Zhao, 2021). Worse still, when classes were moved online due to the outbreak of the COVID-19 pandemic, cyberbullying (a form of bullying using the Internet) still persisted in China (Han et al., 2021). That is why legislators and deputies at the 2022 two sessions called on schools and communities to speed up the process of building a bullying- free, equitable, and inclusive campus for all. To achieve this goal, it is im- perative for Chinese researchers and educators to identify intervention pre- dictors pertaining to school violence and bullying victimization and work out detailed plans to reduce the incidence of bullying behaviors. As for the factors predicting bullying victimization, teachers, students and school climate are generally regarded as three major components for as- sessing an engaging or a horrifying learning experience (e.g., Ahnert et al., 2012; Maxwell et al., 2017). Among them, teacher support (Flaspohler et al., 2009; Huang & Zhao, 2019), a fundamental need to belong (Underwood & Ehrenreich, 2014), a socially cooperative environment (Van Ryzin & Roseth, 2018a), and benign competition in one’s immediate settings (Volk et al., 2015) have been respectively evidenced in previous bullying literature. De- rived from classroom settings, management style or disciplinary climate is more associated with students’ academic achievement (Sortkær & Reimer, 2018), but seldom mentioned to be directly linked to school bullying. Further, researchers’ renewed attention to the fundamental relationships involving teachers, students, classroom settings, and school cultures could help to ex- plain cyberbullying patterns during the COVID-19 pandemic (Vaillancourt T Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1550 et al., 2021). But in the Chinese context, little has been known about the multiple school-related factors that jointly work on anti-bullying endeavors. Therefore, this empirical study aims to explore the association between the different facets of school learning and Chinese students’ overall experiences with bullying victimization while controlling for such demographics as gen- der, age, student backgrounds, and grade repetition. Three overarching re- search questions have guided this exploration. (i) How much variance in overall bullying experience is explained by school-related factors and demographics? (ii) Do school-related predictors have associations with high or low fre- quencies of bullying experiences? (iii)What intervention factors predict the likelihood of Chinese students’ high or low exposure to bullying victimization? Literature Review Theoretical Framework Guided by the social-ecological framework for violence prevention (CDC, 2004), this study addresses the complex interplay between individual, rela- tionship, community, and societal factors in relation to bullying and bullying victimization. Originating from Bronfenbrenner’s (1979) social-ecological model (SEM), this updated framework offers an ecological angle to “investi- gate the combined impact of social contexts and influences on behavioral development” (Swearer et al., 2010, p. 42). As Figure 1 shows, a range of factors work to alert people to the possible risks for experiencing or perpetrating violence while the overlap- ping circles indicate how one level of factors influences another and how different levels of factors coexist to function on the entire model. At the in- dividual level, prevention strategies may involve personal attitudes, beliefs, or behaviors that prevent or stop violence. At relationship and community levels, a person’s close connection to family members and active interaction with schools/workplaces/ neighborhoods may provide a pathway for risk re- duction and violence prevention, including teacher-student interaction, posi- tive peer relations, and reliable school/work environments. The final level (societal factors) features social and cultural norms that encourage or hamper violence. The following sections briefly introduce the variables that fall within this framework, which will form the basis of the bullying model to be tested in our empirical study and help to understand anti-bullying efforts over time and beyond human-level impact. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1551 Figure 1: Social-Ecological Model - A Framework for Prevention. Note: Adapted from Centers for Disease Control and Prevention (p.5), 2004, CDC. Teacher Support Students’ healthy development cannot be sustained without the involvement of teachers, who provide support for, build trust in, and form close interper- sonal relationships with students (e.g., Hughes et al., 2012; Quin et al., 2018; Ryan & Patrick, 2001; Wentzel et al., 2010). Moreover, such teacher-student relationships seem more collaborative rather than hierarchical (Schleicher, 2018). Tardy (1985) pointed out that teacher support as a form of social sup- port was composed of four categories, namely emotional, instrumental, ap- praisal, and informational support. Emotional support is the type of teacher support that reflects love, concern, empathy, confidence, and patience; in- strumental support refers to the substantial help passed on to the students in real need; appraisal support could be interpreted as the constructive feedback and appropriate evaluation system offered for students who will then know where and how to improve their learning behaviors; informational support is viewed as instruction, guidance, assistance, and counselling provided to help with students’ problem-solving (Wentzel, 2016). Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1552 Previous literature has revealed that teacher support positively corre- lates with students’ emotional and cognitive development (Quin, 2016; Quin et al., 2018) as well as with their interest in classroom activities (Lapointe et al., 2005) and their academic enjoyment (Ahmed et al., 2010; Ma et al., 2021). Despite much attention devoted to the connection between teacher support and academic performance, scholars have begun to realize the im- portance of anti-bullying efforts in the presence of teachers. Furlong and Chung (1995) early indicated in their empirical research that those non- victims are almost twice as likely as bullying victims to report the presence of a teacher to whom they can express their problems and pour out their feel- ings; other studies (e.g., Baik et al., 2019; Colarossi & Eccles, 2003; Mazzer & Rickwood, 2015) then emphasized the close relationship between teacher influences and students’ well-being, which could further determine students’ sense of security, problem behavior and victimization experience (Berkowitz & Benbenishty, 2012; McNeely & Falci, 2004). Besides, through analyzing the index of informational support, Huang and Zhao (2019) implied that teacher support could slightly mitigate bullying exposure, but they did not discuss the remaining three categories. Hence in this study, all four types of teacher support will be examined in relation to bullying victimization in China. Students’ Sense of Belonging In educational settings, belonging is identified as the feeling of security, ac- ceptance and inclusion a student connects to peers, teachers, and the school (Goodenow, 1993). Research shows that students’ sense of belonging is closely linked to academic achievement (Wang & Eccles, 2012; Wang & Holcombe, 2010) and psychological adjustment (Lester et al., 2013; Loukas et al., 2016), and has sparked renewed concern for educators as a result of a high prevalence of bullying exposure (Duggins et al., 2016; Ma, 2003). Pre- vious studies have suggested that the stronger a sense of belonging students have, the lower the level of bullying perpetration and victimization occurs (Goldweber et al., 2013; Raskauskas et al., 2010). Accordingly, we hypothe- size that students’ sense of belonging might play a buffering role in bullying victimization while influencing multiple relationships and different commu- nities. Classroom Disciplinary Climate A major component of a positive classroom environment, disciplinary cli- mate is provided when students listen to their teachers and peers attentively and focus only on their academic tasks without the interference of noise or Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1553 disorder (Moos, 1979). Three key elements characterize the variable: stu- dents’ reverence for classroom rules as always, teachers’ utmost responsibil- ity for ensuring a favorable learning environment, and peers’ disruptive-free behavior in the classroom (Cheema & Kitsantas, 2014; Matsumura et al., 2008). A positive disciplinary classroom secures more teaching and learning opportunities (Mostafa et al., 2018), better academic performance (Blank & Shavit, 2016), students’ psychological wellbeing (Kim et al., 2021; Wang et al., 2020), and the efforts against bullying involvement (e.g., victimization and witnessing) (Kim et al., 2021). Additionally, an orderly, nondisruptive classroom can also facilitate students’ sense of belonging (Organization for Economic Cooperation and Development [OECD], 2017) and benefit ethnic minorities and students in a disadvantaged position (Cheema & Kitsantas, 2014). In this research, we hypothesize that classroom disciplinary climate might predict bullying victimization while influencing various social rela- tions. Cooperation and Competition Skills of cooperation is nurtured in an educational setting where students learn together (usually in small groups) to fulfill well-structured learning tasks and accomplish a well-defined learning goal (Van Ryzin & Roseth, 2019; Zook, 2018). If properly created, a cooperative learning environment brings about a high level of peer relatedness or peer relations (Roseth et al., 2008; Van Ryzin & Roseth, 2018a), which in turn promotes the attainment of learning goals (Johnson et al., 2014) as well as encourages positive feel- ings and supportive interactions. Ultimately, benign spiral emerges with the repetition of collaborative learning atmosphere and positive social interac- tions within the group (Deutsch, 1949, 1962). After class, students still have the opportunity to enhance their favorable peer relations by relating each in- dividual’s contribution to the performance of the entire group. This type of cooperation with an emphasis on social contact and skills benefits anti- bullying behaviors and helps to reduce bullying victimization (Van Ryzin & Roseth, 2019). The opposite side of school learning is perceived as having a climate of competition, in which students compare one another or work against each other to obtain their academic or social benefits (e.g., excellent grades and admission to prestigious universities) (Johnson & Johnson, 1978; Volk et al., 2015). Views differ as to whether competition should be fostered in the learning process. One perspective considers competition as being supported by in-group distinctions, social hierarchy, and socioeconomic backgrounds and hence linked to increased bullying (Volk et al., 2015); another opinion Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1554 identifies competition as a catalyst for student engagement and students’ competitive instincts (Anderson, 2006); a third perception regards competi- tion as potentially feasible depending on different disciplines and education- al levels (Chen & Chen, 2014; Vandercruysse et al., 2013). Whatever views prevail and whatever environmental attribute is outlined, students need to learn to create and bolster positive social relations while taking advantage of every factor in the learning community (e.g., teacher and peers) to achieve what is to be achieved (Johnson & Johnson, 1978; Gutiérrez-Braojos et al. 2019). In this study, we hypothesize that both cooperation and competition might work together to influence school violence and bullying victimization while affecting different relationships and school environments. Study Design Previous bullying-related literature has identified that in both Chinese and non-Chinese contexts, gender, grade repetition (or the practice of having stu- dents remain in the same grade without promotion), and economic, social and cultural status (ESCS) all closely correlate with bullying exposure and bullying victimization. Therefore, this study regards the above literature- supported predictors as student-level control variables (as they might con- found the bullying model) and centers the underlying mechanism of the as- sociation between the fore mentioned school-related predictors and bullying victimization for Chinese adolescents. In line with the theoretical model and out of the urge to identify anti-bullying factors in the Chinese context, we proposed the following three hypotheses for the present study (see Figure 2). H1: Teacher support (at the relationship level) significantly influences bullying victimization at school. H1-1: Emotional support significantly influences bullying victimiza- tion. H1-2: Instrumental support significantly influences bullying victimiza- tion. H1-3: Appraisal support significantly influences bullying victimization. H1-4: Informational support significantly influences bullying victimi- zation. H2: Students’ sense of belonging (at the community level) strongly predicts bullying victimization. H3: School climate (at the community level) greatly affects bullying victimization while influencing various social relations. H3-1: Classroom disciplinary climate strongly predicts bullying vic- timization. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1555 Figure 2: School-Related Predictors Hypothesized for Bulling Victimization. H3-2: Cooperation greatly influences bullying victimization. H3-3: Competition greatly influences bullying victimization. Methods Sample This study analyzed the publicly available dataset from the 2018 Program for International Student Assessment (PISA 2018) conducted by OECD in Chi- na’s Beijing, Shanghai, Jiangsu, and Zhejiang provinces (B-S-J-Z, China). PISA, a triennial survey featuring 15-year-olds, measures to what extent they have obtained the critical knowledge and skills essential for active involve- ment in society. PISA 2018 adopted a stratified two-stage sampling proce- dure to select sample students. In the initial phase, schools were chosen through systematic probability proportional to size (PPS) sampling (OECD, 2019c). In the subsequent phase, 42 students were selected with equal prob- ability within each sampled school. For schools with a required number of students fewer than 42, all 15- year-olds were singled out (OECD, 2019c). Ultimately, 12,058 adolescents were selected from 361 schools, among which 4306 (35.7%) came from lower-secondary schools, 5594 (46.4%) from upper secondary schools, and 2158 (17.9%) from vocational schools. As stipulated by PISA’s international protocol (OECD, 2019b), PISA 2018 Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1556 China data met the minimum requirements of the weighted response rate for selected schools within participating countries/regions (85%) and that for students from those selected schools (80%). Before data collection, informed consent was acquired from principals, teachers, parents, and students. The secondary data analyses of PISA 2018 would be crucial for this study as the large-scale survey through a careful sampling process reflected the real bul- lying situation in Chinese schools. Dependent Variable The dependent variable in PISA 2018 was measured from the perspective of the bullying victims (OECD, 2019a) and assessed by asking students to re- port how often they had experienced physical, verbal and social forms of school bullying during the past 12 months (see Table 1). Participants re- sponded on a four-point Likert-type scale ranging from 1 = never or almost never to 4 = once a week or more. The corresponding items were then added up for the bullying scale with the internal consistency or reliability tested (Cronbach’s α = 0.843). Demographic Variables Included in the demographic variables were such student background predic- tors as age, gender, grade repetition, and the ESCS index (see Table 2). Age, a continuous variable, spanned from 15.33 to 15.77 years old (mean = 15.77, SD = 0.29). Gender and grade repetition were all used as dummy variables with “0” for boys/no grade repetition and “1” for girls/grade repetition. The ESCS index, a weighted score rooted in PISA 2018, contained three family background variables, namely home possessions, parents’ highest education- al levels, and their highest occupational status (OECD, 2019c). Independent Variables All the independent variables (teacher support, students’ sense of belonging, cooperation and competition, classroom disciplinary climate) in the study were directly derived from the PISA 2018 database (see Table 3). To ensure validity and reliability of the independent scales applied to this research, scaling procedures and construct validation of context questionnaire data were well documented in the dataset with the internal consistency (Cronbach’s alpha) all exceeding 0.800 (Cronbach’s α > 0.800) (OECD, 2019c). Parallel with Tardy’s (1985) and Wentzel’s (2016) categorization of teacher support, this study applied four indices from PISA 2018: TEACHINT (rep- Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1557 Table 1: Dependent Variable: Bullying Scale. Bullying Scale: 1 (never or almost never) to 4 (once a week or more) 1. Other students left me out of things on purpose. 2. Other students made fun of me. 3. I was threatened by other students. 4. Other students took away or destroyed things that belonged to me. 5. I got hit or pushed around by other students. 6. Other students spread nasty rumors about me. Table 3: Independent Variables and Scale Reliabilities. Teacher Support Emotional Support (TEACHINT) Cronbach’s α = 0.893 It reflects teachers’ love, concern, enthusiasm, and encouragement for students. Instrumental Support (DIRINS) Cronbach’s α = 0.805 It represents pedagogically tangible help (e.g., clear goals for learn- ing, instructions, a short summary of the previous lesson, and check- ing questions on whether teaching has been understood) in student learning. Appraisal Support (PERFEED) Cronbach’s α = 0.892 It refers to the feedback on students’ strengths in a subject, the areas that should be improved, and how the areas can be improved. Informational Support (TEACHSUP) Cronbach’s α = 0.851 It indicates guidance, assistance, and counseling provided to help students understand the subject. Sense of Belonging Cronbach’s α = 0.822 It refers to students’ perceptions of community connectedness and school inclusion. School Climate Disciplinary Climate in the Test Language Classroom (DISCLIMA) Cronbach’s α = 0.892 It measures order and discipline to be maintained in classroom set- tings. Perception of Cooperation (PERCOOP) Cronbach’s α = 0.924 It shows the environment where cooperation is addressed by stu- dents in target schools. Perception of Competition (PERCOMP) Cronbach’s α = 0.829 It refers to the environment where competitiveness is reported by students in target schools. Table 2: Descriptive Statistics for Demographic Variables. Continuous demographic variable(s) Minimum Maximum Mean SD N Age (years) 15.33 16.25 15.77 0.29 12,058 Categorical demographic variables Variables Frequency % Gender Female Male 5,775 6,283 47.9 52.1 Grade Repetition No Yes 11,237 753 93.2 6.8 Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1558 resenting emotional support), DIRINS (indicating instrumental support), PERFEED (reflecting appraisal support), and TEACHSUP (pointing to in- formational support). As for students’ sense of belonging, the index naturally derived from the PISA data examined how easy it was for students to make friends at school, how they were welcomed or accepted by peers, and how they felt isolated or asocial in their community (Goodenow, 1993). For school climate predictors in PISA 2018, disciplinary climate in the test language classroom (DISCLIMA), perception of cooperation (PERCOOP), and perception of competition (PERCOMP) were singled out for study. The disciplinary climate index described how orderly or disruptive the entire classroom environment appeared with higher values pertaining to positive climate appropriate for student learning and classroom communica- tion. Meanwhile, the cooperation index asked respondents to assess if they value cooperation, collaborate with each other, and are encouraged to coop- erate at school; the competition index required participants to report if they cherish competition and compete with each other in the school environment. Analytic Procedure Because the dependent variable (the bullying scale) was not normally dis- tributed, we split it into a dummy one (high and low frequencies of being bullied or victimized) in response to the research questions. Low frequency means that participants never or almost never experienced the listed forms of bullying events while high frequency indicates that respondents experienced at least one of the listed bullying events a few times a year or more (see Ta- ble 4). Further, inspired by previous logistic regression models used to un- derstand Chinese students’ perceptions of and experiences with an educa- tional phenomenon (Allen, 2019), we conducted the research developing a stepwise binary logit model (Pallant, 2016). Utilizing SPSS software Version 28.0, the whole analytical process of data began with the entrance of demo- graphic variables to create a predictive model (Model 1), which was fol- lowed by the addition of other variables of interest, namely the teacher- support model (Model 2), the sense-of-belonging model (Model 3), and the school-climate model (Model 4). The final model (Model 5) ended up with all the above predictors. However, preliminary assumption tests revealed that for Models 3 and 4 1 (see Appendix I), the Hosmer and Lemeshow Goodness of Fit Tests were not passed (significance values all below 0.05), suggesting no support for these three models (Hosmer & Lemeshow, 2000). Hence, this study only concentrated on the other three models (i.e., Model 1: demographic model; Model 2: teacher-support model; Model 5: full-predictor model). Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1559 Table 5: Logistic Regression Analysis of Demographic, Teacher-Support and Full-Predictor Models. Variables Model 1a Model 2b Model 5c B S.E. Exp(B) B S.E. Exp(B) B S.E. Exp(B) Gender Age Grade Repetition ESCS 0.506‡ 0.004 0.245† -0.072‡ 0.037 0.064 0.078 0.017 1.658 1.004 1.278 0.930 0.524‡ -0.104 0.264‡ -0.017 0.039 0.066 0.080 0.018 1.690 0.901 1.302 0.983 0.495‡ -0.235‡ 0.211* 0.030 0.040 0.069 0.084 0.019 1.640 0.791 1.235 1.031 TEACHINT DIRINS PERFEED TEACHSUP -0.264‡ -0.110‡ -0.022 -0.200‡ 0.025 0.025 0.024 0.028 0.768 0.896 0.978 0.819 -0.098‡ -0.064* 0.30 -0.142‡ 0.027 0.026 0.025 0.030 0.907 0.938 1.031 0.867 BELONG -0.454‡ 0.027 0.635 DISCLIMA -0.311‡ 0.022 0.733 PERCOOP PERCOMP -0.168‡ 0.248‡ 0.023 0.022 0.846 1.281 Notes. *<0.05, †p < 0.01, ‡p < 0.001 a Demographic model, b Teacher-support model, c Full-predictor model Results Through binary logistic regression analyses, this study explored the likeli- hood that Chinese adolescents were exposed to high or low frequencies of being bullied or victimized. For Model 1 using age, gender, grade repetition, and ESCS, the likelihood-ratio test produced a chi-square value of 16,101.62 and was statistically significant (p < 0.001), indicating the logistic model was better than the null model without predictors. The chi-square value for the Hosmer-Lemeshow test was 11.07 with a significance level of 0.198 (p > 0.05), suggesting the data fit the above model well (Hosmer & Lemeshow, 2000). The statistical significance (χ 2 (4, N = 11,847) = 224.125, p < 0.001) of the demographic model implied that it was able to distinguish between respondents’ high or low exposure to bullying experiences. Moreover, the Table 4: Descriptive Statistics for Categorical Dependent Variable(s). Variables Frequency % Bullying Low 6,463 54.5 Scale High 5,390 45.5 Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1560 model as a whole explained 1.9% (Cox & Snell R square) and 2.5% (Nagelkerke R square) of the variance in the two bullying groups, and cor- rectly classified 56% of the cases with a very small improvement of 1.5% in predictions. As presented in Table 5, three of the four demographic variables made a unique statistically significant contribution to the model (except for age, p > 0.05). This meant that male students were more likely to be found in the high-level bullying groups than girls when controlling for other factors in the model. The strongest predictor of reporting the high-level bullying groups was gender, recording an odds ratio of 1.658. Likewise, the odds ratio of being in the high-level bullying groups was positively associated with grade repetition (p < 0.01). For ESCS, its negative correlation with bullying exposure and bullying victimization was identified (p < 0.001). In Model 2 with all teacher-support predictors added to the de- mographics, the likelihood-ratio test and the Hosmer-Lemeshow test again identified the model as being worthwhile with the former yielding a χ 2 (8) of 15,498.97 (N = 11,081, p < 0.001) and the latter obtaining the chi-square value of χ 2 (8) of 9.67 (p > 0.05). Moreover, able to distinguish between par- ticipants’ high or low exposure to bullying behaviors (χ 2 (8, N = 11818) = 786.503, p < 0.001), the teacher-support model explained 6.4% (Cox & Snell R square) and 8.6% (Nagelkerke R square) of the variance in bullying groups, and correctly classified 61.2% of the cases with a modest improve- ment of 6.7% in predictions. As observed in Table 5, five of the eight pre- dictors made a unique statistically significant contribution to the model (gender, grade repetition, TEACHSUP, DIRINS, TEACHINT). The two demographic variables (gender and grade repetition) of reporting the high- level bullying groups echoed those in Model 1, recording a slightly higher odds ratio of 1.690 and 1.302 respectively when compared with those in Model 1. Additionally, adolescents with more teacher support (TEACHINT, DIRINS, and TEACHSUP) were 0.768, 0.896, and 0.819 times less likely to be reported in the high-level bullying groups (p < 0.001). This pointed to the fact that emotional, instrumental, and informational support all played a buffering role in bullying victimization with emotional support being most conducive to anti-bullying efforts. Thus, Hypothesis 1 was partially support- ed except for the role of appraisal support. In the final model (Model 5) with all independent variables added, the likelihood-ratio test achieved a χ 2 (12) of 14,525.39 (N = 11,723, p < 0.001), suggesting that the model was better than the null model with all predictors removed. The Hosmer-Lemeshow test yielded a χ 2 (8) of 9.68 (p > 0.05), indicating that the data fit the model well. The whole model again sig- nified its ability to differentiate between respondents’ high or low frequen- Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1561 cies of bullying exposure (χ 2 (8, N = 11,723) = 1,627.086, p < 0.001). More- over, the model as a whole explained 13% (Cox & Snell R square) and 17.3% (Nagelkerke R square) of the variance in bullying groups, and correctly clas- sified 65.8% of the cases with a remarkable improvement of 11.2% in pre- dictions. Ten of the 12 predictors made a unique statistically significant con- tribution to the model (gender, age, grade repetition, TEACHSUP, DIRINS, TEACHINT, DISCLIMA, PERCOMP, PERCOOP, and BELONG) except for ESCS and PERFEED (p > 0.05). The two demographic variables (gender and grade repetition) of reporting the high-level bullying groups recorded a slightly lower odds ratio of 1.640 and 1.235 compared with those in Models 1 and 2. Statistically insignificant in the previous two models, age (p < 0.001) this time witnessed a 0.791 likelihood increase in the high-level bullying groups. For the three forms of teacher support (TEACHINT, DIRINS, and TEACHSUP), they displayed similar patterns as were revealed in Model 2, reporting a mitigating effect on the high level of bullying exposure with in- strumental support (DIRINS) replacing emotional support (TEACHINT) in Model 2 as the most effective form of teacher support for anti-bullying en- deavors. Here in the full-predictor model, the first hypothesis was again ba- sically supported. Regarding the newly added factors in the model, students with a strong sense of belonging, in a better disciplinary climate, and in a cooperative environment were respectively 0.733, 0.846, and 0.635 times less likely to be identified in the high-level bullying groups (p < 0.001). On the contrary, students in the school settings that fostered competition among peers were 1.281 times more likely to report a high level of bullying victimi- zation (p < 0.001). Thus, Hypothesis 2 was fully supported while Hypothesis 3 only was partially supported. Discussion Applying PISA 2018 China data and utilizing binary logit regression anal- yses, this study has added to the empirical experience by investigating the relationship between multiple intervention factors and bullying victimization involving teachers, students, and school climate in the Chinese context. From the perspective of student characteristics, male adolescents, grade re- peaters (regardless of their gender), younger students, and low-income stu- dents/students from disadvantaged families are more likely to be bullied and victimized, as has been reported in a variety of Chinese literature (e.g., Ba et al., 2019; Huang & Zhao, 2019; Li et al., 2020; Lian et al., 2021; Yu & Zhao, 2021). In this sense, top priority needs to be given to the above types of stu- dents when intervention measures are introduced locally or nationwide. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1562 Second, the research findings have verified that teacher support emotionally, informationally, and instrumentally moderates school bullying and bullying victimization. This could link teachers to their practical assistance and sub- stantial help students can seek in case of bullying occurrence. Such support at the relationship level could extend beyond daily instructions provided for adolescents and penetrate further into almost every aspect of classroom learning, eventually benefiting multiple levels of influencing factors within the social-ecological framework. For example, student-perceived love, con- cern, enthusiasm, encouragement, and guidance are beneficial not only to students themselves, but to teacher-student communication channels, peers’ recognition, positive school climate, and a set of core social values to be pre- served. To minimize bullying exposure for all students, teachers are encour- aged to treat students more fairly, evaluate their behavioral and mental pro- gress more proactively, and offer timely support to those in academic diffi- culties and with life or socializing problems (Bosworth et al., 2018). Howev- er, appraisal support, identified as a teacher’s feedback on students’ strengths or weaknesses, is more directly associated with their behavioral engagement (Carvalho et al., 2020) and academic performance (e.g., Carvalho et al. 2014; Fyfe & Rittle-Johnson, 2016; Wei & Xie, 2017), thus requiring more empiri- cal evidence to identify its possible correlation with bullying victimization. Third, consistent with previous Chinese studies (Huang, 2020; Li et al., 2020), this research has illustrated that students’ sense of belonging acts as an important buffer against the detriment of bullying victimization. This indicates that students’ identification with and connectedness to a peer group or a school environment at the community level are viewed as major social resources to protect student learning against being hampered by school vio- lence/bullying victimization (Adams & Hannum, 2018). For school climate, the findings have demonstrated that a disciplinary, cooperative environment supported anti-bullying endeavors. Specifically, this study augments prior research on cooperative learning by showing that a cooperative environment reduces bullying victimization while promoting peer relatedness across the entire student population (Ryzin & Roseth, 2019). However, a socially competitive climate in this study tends to catalyze bully- ing victimization, urging schools and educators to reconsider the balanced relationship between cooperation and competition in bringing about student engagement and facilitating anti-bullying behaviors in school settings (OECD, 2019a). Besides, a positive school climate cannot be maintained without the participation of teachers, who help students cultivate such class- room habits as being friendly to and respectful for peers as well as becoming social, feeling inclusive, and fostering values that will form certain school Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1563 norms. The connectedness within the entire school system will in turn bene- fit teachers, students, and schools, and eventually bullying prevention and control efforts. Therefore, a single bullying incident is interpreted not as an isolated phenomenon that probably causes victimization, but as the social behavior dynamically incorporated into an intricate network of interpersonal relation- ships, institutional factors, community contexts, and policy components. As is reflected in the socio-ecological framework, its interactive and reciprocal nature implies that individual behavior influences and is influenced by mul- tiple levels of factors while shaping and being shaped by the socio-cultural environment (Salihu et al., 2015; Townsend & Foster, 2011). In this sense, to better understand students’ bullying behaviors is not to split them from the larger social context—schools in which students acquire knowledge, com- municate with teachers, get along with peers, develop egos, and gradually form the way a school culture is fostered or ruined. This may point to the necessity of creating improved school conditions for increasing anti-bullying awareness on campus and encouraging sustained behavioral change on bul- lies. The close contact between schools and individuals also promotes the building of a nonviolent campus and effectively supports the implementation of anti-bullying programs/policies. Limitations Despite our focus on school-based factors in bullying victimization and the strength in integrating multiple predictors to address the issue holistically, there exist limitations in this study. First, at the individual and relationship levels, only student-perceived teacher support was taken into consideration, but in fact in the entire school community, the involvement of school admin- istrators, principals, and other school leaders would never be ignored (Minis- try of Education [MOE], 2021). Their active participation in building an ap- propriate school climate and use of process-oriented strategies (Bosworth et al., 2018) could exert a far-reaching impact on anti-bullying endeavors and reduction of victimization. Besides, this study only featured 15-year-olds in general in the test language classroom, but seldom explored the subcatego- ries of this student body including those marginalized or at-risk groups who are prone to be bullied or victimized (e.g., students with disabilities and un- der-achieving students) (MOE, 2017, 2021). Hence, future studies can be realized in showing concern for special student groups as well as considering professionals (e.g., school counselors) and school leadership in the battle against bullying. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1564 Implications The present study has provided implications for minimizing the impacts of bullying victimization and the development of different intervention measures from the perspective of school settings, especially in the context of Chinese schools. Theoretically, the research allows for the room to perceive school bullying and school violence as something complicated yet intercon- nected that springs from a combination of multiple influences upon individu- al behaviors. Thus, the interaction of various levels of factors for violence prevention could offer an effective mechanism for the understanding of how school bullying occurs and what to do with bullying before it begins. Empir- ically, the findings adds to the Chinese-based evidence of the association be- tween school-based predictors and anti-bullying awareness. Since the enact- ment of the Comprehensive Plan on Strengthening the Management of Bul- lying among Primary and Middle School Students in 2017, great importance has been attached to anti-bullying education for all and bullying prevention before it develops (MOE, 2017). Based on the experience of anti-bullying legislation in other countries, China adheres to the principle of prevention as a primary concern and intervention as a top priority in an effort to push for- ward the establishment of an anti-bullying campus. Under such circumstanc- es, this research regards a harmonious classroom climate and a positive school environment as the starting point to develop a sense of security, form social values (e.g., justice, unity, collaboration, and responsibility) amid cul- tivation of self-awareness, and eventually curb bullying behaviors on campus. At the micro level, teachers play an indispensable part in teaching students what to learn and how to shape values as they spend a large propor- tion of time listening to adolescents’ voices and building rapport (Schleicher, 2018). In this process, teachers’ role in assisting the young to identify bully- ing behaviors and timely stop victimization cannot be taken no notice of. Noteworthily, imperative to bullying intervention is teacher training, which means teachers’ skilled coping strategies relieve students’ anxiety in con- fronting bullying and help to form appropriate management styles of class- room learning (Di Stasio et al., 2016). As suggested in the study, teacher training is feasible in promoting a sense of school belonging, improving classroom disciplinary climate, and balancing the skills of cooperation and competition. For school climate, our study points to all stakeholders who join the entire school community in creating a caring, inclusive atmosphere, not only teachers and student victims in the forefront of this anti-bullying battle. Also in climate building, our findings have recognized social compar- ison and intense competition as crucial characteristics that deserve educa- Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1565 tional practitioners’ scrutiny and deliberation over their own teaching prac- tices (Di Stasio et al., 2016). However, the lingering impacts of the COVID-19 pandemic have made bullying patterns somewhat different. While strengthening online learning, the pandemic still secures cyberbullying as mentioned above. But the fact lies in that with the decrease in in-person bullying, cyberbullying follows a downward trend (Bacher-Hicks et al., 2021). This echoes previous evidence that cyberbullying rarely occurs independently of in-person bully- ing (Waasdorp & Bradshaw, 2015). In order to work out strategies for cop- ing with cyberbullying, close attention would be paid to such fundamental relationships in educational reforms and anti-bullying attempts as teacher- student interactions, peer-to-peer relations, classroom environments and school cultures (Vaillancourt et al., 2021). Therefore, this study may provide a route to the understanding of cyberbullying in China that in a sense repli- cates the patterns of in-person bullying and bullying victimization. Although it is still pending to see how a positive classroom climate plays a role in adapting the bullied to the school life, the emphasis upon multiple relations within the school system offers an angle to propose intervention measures aimed at achieving equity and inclusivity for all schoolchildren in the post- COVID-19 era. Note: 1. For the failed models (Model 3: the sense-of-belonging model and Model 4: the school-climate model), please refer to the online appendix for details. Acknowledgement We wish to express our sincere gratitude to Dr. Ryan Allen and Dr. Doug Havard, who have offered professional assistance and constructive suggestions during our research, upon the completion of this academic paper, and in the process of revision. Their will- ingness to spare the time and energy so generously has been very much appreciated. Our grateful thanks are also extended to our colleagues for their firm support and val- uable insight in the research. Finally, we would like to thank OECD for making the PISA database publicly available for researchers and their analyses. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 1566 References Adams, J., & Hannum, E. (2018). 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Available at: https://www.scmp.com/news/people- culture/social- welfare/article/3155602/teenage-boys- drowning-spotlights-chinas-bullying Received: 21 July 2022 Revised: 10 August 2022 Accepted: 18 August 2022 https://doi.org/10.1080/02602938.2017.1414146 https://doi.org/10.1080/02602938.2017.1414146 https://doi.org/10.1016/j.cedpsych.2010.03.002 https://doi.org/10.1016/j.cedpsych.2010.03.002 https://doi.org/10.1016/j.ssaho.2021.100151 http://global.chinadaily.com.cn/a/202111/19/WS6196fe63a310cdd39bc763f2.html http://global.chinadaily.com.cn/a/202111/19/WS6196fe63a310cdd39bc763f2.html https://www.aeseducation.com/blog/what-is-cooperative-learning-and-how-does-it-work https://www.aeseducation.com/blog/what-is-cooperative-learning-and-how-does-it-work https://www.scmp.com/news/people-culture/social-welfare/article/3155602/teenage-boys-drowning-spotlights-chinas-bullying https://www.scmp.com/news/people-culture/social-welfare/article/3155602/teenage-boys-drowning-spotlights-chinas-bullying https://www.scmp.com/news/people-culture/social-welfare/article/3155602/teenage-boys-drowning-spotlights-chinas-bullying https://www.scmp.com/news/people-culture/social-welfare/article/3155602/teenage-boys-drowning-spotlights-chinas-bullying Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 Appendix I Figure S1. Normal P-P Plot of Regression Standardized Residual. Note. The points did not lie in a reasonably straight diagonal line from bottom left to top right. This would suggest major deviations from normality and multiple regression analyses did not fit for statistics. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 Figure S2. Scatterplot of Standardized Residuals. Note. In the Scatterplot of the standardized residuals, the residuals appeared as a clear or systematic pattern, higher on one side than the other. This suggested that multiple regression analyses did not fit for statistics. Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 Table S1. Multiple Regression Analysis of Demographic, Teacher-support, Sense-of-belonging, School-climate, and Full-predictor Models. Variables Model 1 a, b Model 2 Model 3 c Model 4 d Model 5 e β β β β β Gender Age Grade Repetition ESCS .169‡ -.008 .048‡ -.050‡ .165‡ -.019‡ .047‡ -.025† .178‡ -.030‡ .043‡ -.012 .146‡ -.030‡ .045‡ -.016 .149‡ -.039‡ .039‡ .001 TEACHINT DIRINS PERFEED TEACHSUP -.113‡ -.019 .017 -.108‡ -.016 .009 .045‡ -.076‡ BELONG -.283‡ -.215‡ DISCLIMA -.208‡ -.169‡ PERCOOP PERCOMP -.153‡ .119‡ -.071‡ .112‡ Notes. *<.05, †p < .01, ‡ p < .001 a Demographic model, b Teacher-support model, c Sense-of-belonging model, d School-climate model, e Full-predictor model Zhu & Teng. (Shanghai & California). School Bullying Victimization in China. BECE, Vol.12, No. 1, 2022 Table S2. Logistic Regression Analysis of Sense-of-belonging and School-climate Models. Variables Model 3 a Model 4 b B S.E. Exp(B) B S.E. Exp(B) Gender Age Grade Repetition ESCS .568‡ -.136* .215† -.008 .039 .066 .081 .018 1.765 .873 1.239 .651 .457‡ -.158* .238† -.007 .039 .067 .082 .019 1.580 .854 1.269 .993 BELONG -.640‡ .026 .527 DISCLIMA -.409‡ .020 .664 PERCOOP PERCOMP -.344‡ .246‡ .021 .022 .709 1.279 Notes. *<.05, † p < .01, ‡ p < .001, a Sense of Belonging, b School Climate Preliminary assumption tests revealed that for Models 3 and 4, the Hosmer and Lemeshow Goodness of Fit Tests were not passed (significance values all below .05), suggesting no support for these two models. BECE_V12N1_Sep2022-Title-Teng BECE_V12N1_Sep2022-Maintext-Teng Supplementary-Appendix-BECE-V12N1-September2022-Teng