تجزیه و تحلیل مشخصات خرده جمعیت و عوامل خطر برای زورگویی مدرسه ای

Abstract Drawing from a local sample of 1822 7th and 8th grade students, this study used Latent Class Analysis (LCA) and Latent Class Regression Analysis (LCRA) to identify sub-population profiles and risk factors for school bullying. Four sub-population profiles of school bullying risk were yielded from this approach. These profiles included students who presented little need for formal services as well as students who manifested needs for wrap-around support. Importantly, additional regression analyses related student membership in particular risk profile groups to the support they receive from peers, teachers, and parents. Several significant practice implications for bullying prevention and Response-to-Intervention (RTI) frameworks accompany the findings. Above all, school bullying interventions should be implemented with prudence because even the best intended ones carry the potential for harm.

1. Introduction School bullying is receiving increased attention in social and educational research, practice, and policy circles—and for good reason. When children are victimized by school bullying, sub-optimal outcomes often occur. These undesirable outcomes include academic difficulties (Cook, Williams, Guerra, Kim, & Sadek, 2010), psychological problems (Swearer, Song, Cary, Eagle, & Mickelson, 2001), and social relationship challenges (Graham et al., 2003 and Ladd, 2003). In the most severe instances, the untoward effects of bullying may contribute to suicidal ideation and student deaths (Mayer and Furlong, 2010 and Swearer et al., 2010). For these reasons, preventing bullying and its harmful correlates is an urgent priority. Of particular need are empirically-driven models that are action-oriented (Swearer et al., 2010). Action-oriented models help inform data-driven interventions that social workers, educators, and other professionals can use to address bullying in their own school communities (see also, Moss, 2012). This paper is structured accordingly. It advances an empirical model of four bullying-related “risk profiles,” i.e., data-driven descriptions of identifiable student sub-populations. When examined individually and collectively, the four risk profiles advanced in this paper offer practitioners and policy makers a more holistic and action-oriented view of school bullying than what is typically modeled in extant research. These risk profile findings are then augmented by an analysis of their relationship to the support students receive from their teachers, parents, and peers. This enriched understanding of bullying and its contextual influences paves the way for more targeted, comprehensive, and data-informed school-community interventions. In light of this purpose, the article begins with a description of the community in which data were collected, together with a brief characterization of the interventions used by social workers and other school-community leaders to prevent school bullying and enhance students' social-emotional well-being. Then, two kinds of research studies are reviewed. Descriptive research on school bullying (e.g., research on its operational features and prevalence) is presented first. Then, examples of research on the concomitant correlates, consequences, and risk factors for school bullying are summarized. This literature review sets the stage for this study's design, findings, and conclusions. 1.1. School-community and programmatic context Data from this study are drawn from a sample of 1822 7th and 8th grade students attending 10 middle schools in 10 school districts in New York State. Each of the students surveyed in this study attends a school that is involved in a county-wide, federally-funded Safe and Healthy Schools Grant for which the author is the primary evaluator. These schools serve students from urban, suburban, and rural backgrounds. The Safe and Healthy Schools Grant developed for this community includes multiple partnerships. The effort is led principally by a central school district agency known in New York as a Board of Cooperative Educational Services (BOCES). The local BOCES serves as the lead fiscal and administrative agent. This leadership is accompanied by social work and education services provided by Binghamton University, as well as a host of social work services and early intervention programs provided by the Youth Services Division of a local hospital. All services are provided in close collaboration with participating school districts. According to program documents, all grant services are guided by the currently-popular Response-To-Intervention (RTI) services framework (American Psychological Association Task Force, 2008). As a part of this RTI framework, all program services are developed in relation to a “three tiered” approach to service delivery. This service delivery approach endeavors to provide “universal” educational support and assistance (Tier 1) to about 80% of the student population; more intensive, small group interventions (Tier 2) to about 15% of students; and the most intensive services and supports (Tier 3) to 5% of the student population. Five primary program services constitute this community's particular RTI service model. These service elements are: (a) A school-wide Olweus bullying-prevention team, with technical support provided by the University's educational services team (e.g., Olweus, 2004); (b) weekly individual and group-focused services provided by master's level social work interns who are out-stationed at the school and supervised by grant-funded MSW's; (c) weekly evidence-based program services, such as Families and School Together (FAST), provided by social workers who staff the Youth Services Division of a local hospital; and (d) conventional pupil support services provided by school social workers and school guidance staff. At the time data were collected, the initiative under study had just finished the third of four years of funding. Sixty percent of the participating schools had trained school-based Olweus Bullying-Prevention teams and were implementing them according to the program's standards and training protocols. Two-thirds of the participating schools were receiving social work services from MSW interns and project-funded MSW's. Each district was receiving evidence-based youth and family services from the local hospital. All participating schools were using their school social worker to refer students to project services. Although each school developed and implemented their RTI model somewhat differently, the program universally prioritized those services and supports which could increase student awareness of bullying and minimize its harmful effects. Importantly, as program implementation progressed, most of the participating schools did more than just try to increase student awareness of bullying; they also encouraged students to intervene (e.g., to stop it directly or to seek assistance from a teacher or other adult) when bullying occurred. This encouragement was provided by school personnel through formal Tier 1 social work-led presentations, as well as through more informal measures, such as the posting of “stop bullying signs” that can be seen throughout the hallways of each participating school. These particular grant-related features provide an important opportunity for conducting practice and policy relevant research, since efforts to prevent bullying may to be modified “mid-stream” to accommodate students' heightened awareness of bullying and its consequences. This study capitalizes on this need and opportunity, with particular attention toward informing the design and development of more effective bullying prevention programs and policies.

5. Discussion and conclusions The purpose of the study was to explore a contextual and situated view of school bullying and accompanying risk factors. To accomplish this goal, Latent Class Analysis (LCA) was used to explore sub-population profiles of bullying and accompanied risk factors among 7th and 8th grade students. These students attended schools that were participating in a federally funded, countywide anti-bullying initiative. LCA yielded four principal “profiles” of bullying-related risk. The four sub-populations were described as: (a) Students with no or limited bully-related risk (No Risk, 39.4%); (b) victims of school bullying (Bully Victims, 32%); (c) students with prior victimization and perpetrator experiences (Perpetrator Victims, 16.6%); and, finally, (d) students with several bullying-related risks and challenges, including elevated risk for depression, externalizing problems, and school avoidance tendencies (Multiple Risk, 12%). When viewed in the round, these LCA profiles stand as important findings. Whereas prior research has classified students into victim, perpetrator, and victim–perpetrator groups (e.g., Cook et al., 2010 and Olweus, 2004), the LCA models yielded in this study diverge a bit from this familiar pattern. The key difference was the identification of two student groups characterized, in part, by both victim and perpetrator experiences. The “perpetrator only” profile found in much extant “status group” research was notably absent from our findings. Two primary explanations may be given for these unique profile findings. The first concerns the unique grant- and context-related features of the study's sample. As described earlier, this context involved professionals coaching students to intervene whenever bullying occurred. Thus, it is quite possible that students, who would have otherwise been classified strictly as “perpetrators,” may have faced unusual resistance or retaliation from other students when they tried to bully others, and in the process, became victimized themselves. A second possible explanation for these findings involves the inclusion of multiple indicators of student vulnerability into our LCA model. As Masyn (2013) suggests, the quality and characteristics of any LCA model is dependent upon the items employed as latent class indicators. Thus, an estimated LCA model, which did not include the indicators of depression, school avoidance, and aggression used in this study, may have yielded characteristically different profiles of bullying than those found in this article. Ultimately, future work is needed to evaluate the practical utility and overall stability of this study's risk profiles. As indicated by prior research, student's overall risks for bullying change as students get older (Pontzer, 2009), and these risks are especially dynamic during students' middle school years (Nylund et al., 2007a and Nylund et al., 2007b). For this reason, it may be necessary for evaluators and program leaders to assess students' strengths, needs, and risks at least twice every year. Only with such a continuous assessment process will students benefit from tailored interventions that best fit their personal strengths and needs. Under ideal conditions, such assessment data would be “fed forward” continuously as a part of an iterative program planning and development strategy. 5.1. Risk factors for risk profile membership Our LCRA models revealed several important risk factors for belonging to the risk profile groups yielded from LCA. Specifically, the results indicate that, on average, students who present the greatest vulnerability for bullying-related challenges tend to experience less support from their teachers than students who have limited or no experiences with bullying (Nation et al., 2008). Importantly, the findings also suggest that students who are vulnerable to bullying-related dynamics may present different needs for parental support and assistance. For instance, students in the MR group may need additional emotional support from parents and caregivers. Students in the BV and PV profile groups might require additional instrumental assistance when trouble arises at home, school, or in the community. Finally, the results indicate that student ethnicity is associated with membership in particular risk profile groups. Specifically, findings indicate that ethnic minorities, including African Americans and Hispanics, may not be conditioned to simply “take it” when involved in bullying-related episodes and/or dynamics (Peskin et al., 2006). Instead, our findings suggest that, when compared to White students, ethnic minorities who are not Asian are significantly more likely to respond actively to bullying, social intimidation, and social exclusion. 3 When viewed in the round, these findings help frame the importance of students' social support in preventing and addressing bullying-related dynamics and challenges. In the following sections, we highlight the theoretical and practical import of student's peer support networks in developing the (social) organizational infrastructure needed to combat bullying and its correlates. 5.2. Implications for student risk, peer networks, and bystander interventions One of the more popular approaches to bullying prevention involves the development of school policies and practices which empower students to positively intervene on behalf of victims of school bullying (Bowllan, 2011 and Olweus, 2004). These “bystander approaches” are designed with the understanding that school bullying is often witnessed by multiple student actors. As such, a chief goal of the bystander approach is to educate students on the negative impacts and consequences of bullying, with the idea that more informed students may become more motivated and/or empowered to prevent it. Once educated, the next step typically involves helping students intervene when bullying occurs. Here, two primary intervention targets are especially salient. The first involves encouraging students to intervene on behalf of victims of school bullying, even if they don't know them very well (Bowllan, 2011 and Olweus, 2004). The second involves coaching students to find a teacher, or another adult at the school, whenever they witness behaviors that merit adult intervention or assistance (Olweus, 2004). Although these twin interventions make intuitive sense on the drawing board, our results present important working challenges to their effective implementation. One example of this challenge concerns the behavioral tendencies of students who belong to the NR profile group. Because these students present no prior risks for bullying, they are often viewed as ideal providers of bystander support (Olweus, 2004). However, in this study, NR students represented the least likely candidates to provide such support. In fact, additional post-hoc analyses suggest that the vast majority (66%) of these students do not engage in such behaviors at all. A second challenge to effectively implementing bystander supports involves the behavioral patterns of students who belong to the MR and PV risk profile groups. As demonstrated through LCRA, these students are among the most likely candidates to provide protective support and assistance to victimized peers, with MR students being nearly 5 times as likely as the NR group to provide protective assistance with high frequency. Given the Safe and Healthy School initiative's emphasis on peer and bystander interventions, the protective practices of these students stand as important findings. At the same time, the prior histories of aggression exhibited by members of these groups provide just room for caution. After all, it is not hard to imagine how students with prior histories of difficulty might face school disciplinary action, troublemaker label, or student retaliation if their efforts to protect others were channeled inappropriately; or if they were undertaken without sufficient adult support or guidance. Sadly, our LCRA models indicate that, on average, students who belong to the MR and PV profiles receive low degrees of teacher support than other students. For this reason, not only may these students be particularly prone to aggressively defend their peers (e.g., Nation et al., 2008) they may be vulnerable to intervene without adult assistance. Ultimately, these findings and dynamics highlight the complex challenges facing bystander approaches and interventions. These challenges include the difficulties school communities may face engaging and incentivizing NR students to participate in bystander programs, and they also highlight needs for special intervention supports designed specifically for students with prior behavioral challenges. Absent such targeted support, it is tenable to question whether efforts to heighten student awareness and sensitivity about bullying stand to benefit the most vulnerable students, or whether they carry the potential to cause them harm (e.g., Dishion, 2000 and Dishion et al., 1999). 5.2.1. Enhancing socially supportive interventions Findings from this study implicate needs for bystander programs and RTI service models to be supplemented by a new genus of programs, services, and supports. Importantly, social workers and other health and human service workers can and should serve as key agents and leaders for this novel, social work. For instance, social workers that have training in community building can develop activities that target enhanced interactions not only within peer networks, but across them as well. Given the reported tendency of bullying to cluster within peer groups ( Espelage et al., 2003), these activities may be needed to help students develop the confidence they need to support others that they don't know very well. They may also be critical for schools where peer networks are stratified according to other important features, such as neighborhood/gang affiliation, social class, and/or ethnicity ( Orfield, Kuscera, & Siegel-Hawley, 2012). In addition to fostering “horizontal” peer connections across student groups, this study highlights the need for social workers to enhance “vertical” social-emotional connections between students and their teachers. This need is especially pronounced for those students who are struggling with bullying-related experiences and challenges. By fostering relational ties and bonds between these students and their teachers, social workers may help develop the (interpersonal and inter-professional) relationships needed to better identify, and then respond to, students' diverse social-emotional and learning-related needs (e.g., Olweus, 2004). However, for such relational practices and benefits to take hold, school social workers will need to extend their work beyond a strict clinical orientation. For bullying prevention programs and RTI efforts, this may involve less time devoted to Tier 2 or Tier 3 clinical services (in the school guidance office) and more time spent engaging students, teachers, and school administrators in the hallways, classrooms, lunchrooms, and playgrounds where social networks, school climates and cultures, as well as informal policies develop. By pursuing this vital, grass–roots Tier 1 work, social workers may not only better realize the goals of bullying prevention programs and accompanied RTI frameworks, they may become a more indelible school resource in the process. 6. Future research Although the LCA approach utilized in this study holds promise for identifying bullying-related challenges and risks, there are several limitations to this study's design which merit close attention. These limitations double as future research needs. To begin, this study highlights needs for researchers to better examine the relationship between the risk profiles culled through LCA and students peer support networks and affiliations. Specifically, the quality of this study's analyses and conclusions would have been improved significantly had the research team asked students about the number of friends they have who: (a) Experienced bullying; and/or (b) participated in bullying behaviors, either as perpetrators, witnesses, or both. Our analyses would also have been strengthened had we captured students' social standing relative to their peer group and peer networks (see Espelage et al., 2003). By better attending to these social features, future research will be better poised to help school-community leaders develop more responsive and ecologically-valid interventions. A second research need involves a closer examination of the relationship between student use of RTI services and risk profile membership. In particular, more robust attention to the ways that low-income students, especially low-income minority students, access and interpret these services is needed, as our data indicates that student response to bullying may be conditioned by cultural background and mores. What's more, given the increased attention toward RTI models and approaches in recent years (e.g. APA, 2008), how these services are accessed, used, and interpreted by particular student sub-groups figures to be central to the development of more effective and comprehensive range of learning supports. Finally, given this study's vulnerability for self-report and selection bias, several other measures and constructs should be considered for future studies. Students' personal appearance represents one such variable, since research has shown that students who are overweight and/or perceived as physically weak are particularly vulnerable for bullying (Cook et al., 2010). Student's social class and sexual orientation represent key others, especially the way they may interact with students' ethnicity and/or gender to influence bullying-related risk (Swearer et al., 2010). In addition, school-level predictors, including teacher reports, should be included in future models, as research, policy, and practice can be enhanced by better attending to the socio-ecological features and processes of school bullying. Ultimately, these recommendations, and the design limitations from which they are derived, help highlight the exploratory nature of the present research. All of this study's results should therefore be considered preliminary until replicated with a broader cross-section of students, using a more comprehensive array of controls.