© 2014 American Psychological Association 1045-3830/14/$ 12.00 http://dx.doi.org/10.1037/spq0000073

School Psychology Quarterly 2014, Vol. 29, No. 3. 306-319

The Moderating Effects of School Climate on Bullying Prevention Efforts Sabina Low

Mark Van Ryzin

Arizona State University

Oregon Social Learning Center, Eugene, Oregon

Bullying prevention efforts have yielded mixed effects over the last 20 years. Program effectiveness is driven by a number of factors (e.g., program elements and implemen­ tation), but there remains a dearth of understanding regarding the role of school climate on the impact of bullying prevention programs. This gap is surprising, given research suggesting that bullying problems and climate are strongly related. The current study examines the moderating role of school climate on the impacts of a stand-alone bullying prevention curriculum. In addition, the current study examined 2 different dimensions of school climate across both student and staff perceptions. Data for this study were derived from a Steps to Respect (STR) randomized efficacy trial that was conducted in 33 elementary schools over a 1-year period. Schools were randomly assigned to intervention or wait-listed control condition. Outcome measures (pre-topost) were obtained from (a) all school staff, (b) a randomly selected subset of 3rd-5th grade teachers in each school, and (c) all students in classrooms of selected teachers. Multilevel analyses revealed that psychosocial climate was strongly related to reduc­ tions in bullying-related attitudes and behaviors. Intervention status yielded only 1 significant main effect, although, STR schools with positive psychosocial climate at baseline had less victimization at posttest. Policies/administrative commitment to bullying were related to reduced perpetration among all schools. Findings suggest positive psychosocial climate (from both staff and student perspective) plays a foun­ dational role in bullying prevention, and can optimize effects of stand-alone programs. Keywords: school climate, bullying, peer violence, prevention

Due to the high prevalence of bullying in schools and its strong relationship to adverse mental health and academic outcomes, there has been considerable growth in the number and dissemination of school-based bullying preven­ tion programs over the past 20 years (Espelage & Swearer, 2003). Part of this growth is spurred by states requiring schools to adopt policies and practices to assess and address bullying and harassment among students. However, policies alone or in combination with bullying preven­ tion curricula do not automatically translate to

This article was published Online First August 4, 2014. Sabina Low, T. Denny Sanford School of Social and Family Dynamics, Arizona State University; Mark Van Ryzin, Oregon Social Learning Center, Eugene, Oregon. Correspondence concerning this article should be ad­ dressed to Sabina Low, T. Denny Sanford School of Social and Family Dynamics, Arizona State University, Tempe, AZ 85287. E-mail: [email protected]

behavioral change and, ultimately, strong public health impact. Indeed, several recent meta­ analyses reveal that over the last decade, school-wide bullying prevention evaluations have demonstrated negligible to nonsignificant results (Merrel, Gueldner, Ross, & Isava, 2008; Smith, Schneider, Smith, & Ananiadou, 2004), with the more promising studies being based in Europe (Farrington & Ttofi, 2009). Studies on the effectiveness of bullying pre­ vention programs have tended to focus on fea­ tures and delivery of the programs as important determinants of their success (see Durlak & DuPre, 2008) with particular attention to imple­ mentation (Hirschstein, VanSchoiack, Frey, Snell, & MacKenzie, 2007; Low, Van Ryzin, Brown, Smith, & Haggerty, 2014; Olweus, 1991; Smith et al., 2004). Yet, as Orpinas (2009) articulated, such programs do not oper­ ate in a vacuum, and we may be limiting our knowledge of bullying prevention efforts (and 306

SCHOOL CLIMATE

how to optimize these efforts) if we ignore the broader context in which these programs are delivered. Orpinas (2009) argued that having a positive school climate is pivotal to reducing aggression, and a necessary foundation for any stand-alone bullying prevention efforts. Yet, few (if any) scholars have formally tested the moderating role of school climate on the effects of an adopted bullying prevention program, masking important information on whether and to what extent the larger environment shapes bullying prevention impacts. The current study aims to address this gap by examining the mod­ erating effects of school climate on the effec­ tiveness of Steps to Respect (STR; Committee for Children, 2005), a bullying prevention pro­ gram with demonstrated efficacy in reducing bullying behavior (Brown et al., 2011). School Climate and Bullying School climate refers to the culture, milieu, or character of a school, capturing its sense of community and overall organizational health (Cohen, McCabe, Michelli, & Pickeral, 2009; Hoy, Smith, & Sweetland, 2002). Climate is foundational to students’ values, behaviors, and peer group norms, and there is a robust litera­ ture suggesting relations between school cli­ mate and students’ academic achievement, commitment to school, and conduct problems (McEvoy & Welker, 2000; Mehta, Cornell, Fan, & Gregory, 2013). Climate has long been con­ sidered a critical component to targeting peer violence and aggression, and particularly bully­ ing, given that a systems framework is neces­ sary to assess and respond to the complex ori­ gins, manifestations, and underlying maintenance factors of bullying. Indeed, several studies have documented relations between positive school climate and reduced bullying and victimization (Guerra, Williams, & Sadek, 2011; MeyerAdams & Connor, 2008; Plank, Bradshaw, & Young, 2009), more prosocial responses to bul­ lying behavior (Lindstrom Johnson, Waasdorp, Debnam, & Bradshaw, 2013), greater willing­ ness to intervene (Syvertsen, Flanagan, & Stout, 2009), and greater willingness to seek help for bullying or threats of violence (Eliot, Cornell, Gregory, & Fan, 2010). In particular, the rela­ tional aspects of the community (e.g., connect­ edness, having trusting relationships with teach­ ers, availability of caring adults) has been

307

associated with lower rates of aggression and victimization in schools (Corrigan, Klein, & Isaacs, 2010; Gregory et al., 2010) and greater likelihood of help-seeking behaviors (Gregory, Cornell & Fan, 2011). School Climate Can Facilitate Program Effectiveness Based on the aforementioned studies, there is accumulating evidence that creating and main­ taining a positive, trusting school climate can function as a form of bullying prevention. After all, climate affects norms and social interactions at the level of the school (e.g., commitment to academics, relations with parents), classroom (trusting relations with peers and teachers), and individual (enhanced willingness to report or intervene) that should theoretically combat the origins and maintenance of bullying (Eliot et al., 2010; Orpinas, 2009; Unnever & Cornell, 2004). However, climate may also function at different ecological levels to enhance the adop­ tion, commitment to, and implementation of prevention programs as well as the deployment of skills taught in bullying prevention programs. For example, Eliot, Cornell, Gregory, and Fan (2010) examined the role of climate among students participating in the Virginia High School Safety Study and found that positive school cli­ mate engendered more positive bystander behav­ ior. The authors concluded that fostering more positive and supportive relations may be valu­ able to engaging students in bullying prevention efforts. Similarly, Unnever and Cornell (2004) found that a positive psycho-social climate en­ courages help-seeking in schools in response to bullying or peer violence, which is a critical cornerstone to the success of stand-alone vio­ lence prevention programs. Bradshaw, Koth, Thornton, and Leaf (2009) found that schools with higher levels of organizational health (in­ dicated by leadership, academic emphasis, and staff climate) at baseline saw better implemen­ tation and greater improvement in organiza­ tional health over a 5-year trial of Positive be­ havioral Interventions and Supports (PBIS). Lastly, in a trial of Expect Respect, a bullying prevention program, the authors found that school climate served as a key mechanism (i.e., mediator) for behavior change (Meraviglia, Becker, Rosenbluth, Sanchez, & Roberston, 2003).

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Summary and Aims Taken together, prior research would suggest that the effects of bullying prevention programs shape, are shaped by, the school climate. How­ ever, few if any studies have examined the relationship between climate and bullying pre­ vention programming impact. Thus, the overar­ ching aim of the current article is to explore this relationship so as to better understand the inde­ pendent and or synergistic effects of the envi­ ronment in which bullying programs (or vio­ lence prevention programs more generally) are delivered. Specifically, we sought to answer two questions: (a) After controlling for inter­ vention status (STR), does school climate (op­ erationalized below) relate to decreases in bul­ lying behaviors and attitudes over time? and (b) Does school climate magnify the effects of a bullying intervention on bullying behaviors and attitudes? In addition to exploring these questions, the current study advances the field in three novel and important ways. First, we utilize both teacher/staff perceptions of climate as well as stu­ dent, to capture a broader and more diverse sampling of perspectives of school environ­ ment. Second, we recognize that climate is mul­ tidimensional, and contrast two related but po­ tentially distinct dim ensions of clim ate, relational (or psychosocial) and organizational (see Roeser, Eccles, & Sameroff, 2000). For this study, “staff psychosocial school climate” is operationalized as perceived relations with teachers, parents, and students, whereas the “or­ ganizational climate” component is captured by teacher/staff perceptions of policies and admin­ istrative commitment to bullying prevention. In contrast, “student psychosocial climate” mea­ sures students’ relationships with peers and teachers, and perceived connectedness to school. Third, use of multilevel modeling al­ lowed for us to examine the relations between climate and bullying outcomes as contextual­ ized (i.e., nested) within school demographic characteristics and intervention status. More­ over, multilevel modeling allowed for us to examine staff reports of climate as a settinglevel (Level 2) variable (Marsh et al., 2012), in contrast with student climate (which was as­ sessed at the individual level). The current study draws upon data from a 1-year elementary school bullying prevention

trial of STR. The STR program is based on a social-ecological model of bullying which views youth behavior as shaped by multiple factors within nested contextual systems at the school, peer, and individual levels (Swearer, Espelage, Vaillancourt, & Hymel, 2010). School-wide components are intended to foster a positive school climate and positive norms through a one-time teacher and staff training focused on improved monitoring of students and instruction on how to effectively intervene with students involved in bullying situations (i.e., coaching). Classroom curricula are in­ tended for the upper three elementary grades and seek to promote socially responsible norms and behavior and increase social-emotional skills. Lessons help students recognize bullying, increase empathy for students that are bullied, build friendship skills to increase protective so­ cial connections, improve assertiveness and communication skills to help students deter and report bullying, and teach appropriate bystander responses to bullying. A randomized controlled trial of STR (Brown, Low, Smith, & Haggerty, 2011) indicated positive main effects on student attitudes, bullying related behavior (e.g., social competence, physical bullying perpetration, positive bystander behavior), and school cli­ mate. In addition, when examining implemen­ tation as a moderator of program impact, Low, Van Ryzin, Brown, Smith, and Haggerty (2014) found that high levels of engagement (but not adherence to program components) was related to lower levels of school bullying problems, enhanced school climate and attitudes less sup­ portive of bullying. Notably, psychosocial cli­ mate was predictive of student engagement, though organizational climate was not. Drawing upon the previous findings from the STR study and the extant literature previously discussed, we hypothesized both main and mod­ eration effects for school climate. First, we ex­ pected climate to contribute to improved out­ comes regardless of intervention status. Second, we expected that intervention schools with more positive school climate would see greater program impact when compared with interven­ tion schools with less positive climate. Finally, we did not anticipate that climate as measured in terms of policies/administrative commitment (i.e., organizational climate) would have a sig­ nificant impact, either as a main effect or when interacted with intervention status. Finally, staff

SCHOOL CLIMATE

and students perceptions of climate have func­ tioned similarly in prior STR analyses (i.e., showed high correspondence in relations to out­ comes; see Brown et al., 2011; Low et al., 2014), and thus, we anticipated similar patterns of relations across reporters here. Method Participants Schools. The data for this study were de­ rived from a 1-year (pre to post) STR efficacy trial that was conducted in 33 elementary schools in north-central California. Based on power analyses using parameter estimates from Frey et al. (2005) and Jenson and Dietrich (2007) we targeted 34 schools for the trial. The 34 schools were matched into pairs within each geographic area using NCES data (http://www .ed-data.kl2.ca.us) on the characteristics of the school environment (e.g., total student enroll­ ment, change in student enrollment from 2006 to 2007, number of teachers), and characteris­ tics of the student population (e.g., percentage eligible for the free or reduced-price lunch pro­ gram, ethnic/racial percentages, and percentage of students for whom English was not their prim ary language). Schools within each matched pair were assigned randomly to either the intervention or wait-listed control condition using a random number table. Between random assignment and program implementation, two schools withdrew from the study (one because of turnover in leadership, and one because of building remodeling). One school was immedi­ ately replaced by another eligible school, which was an adequate match on all criteria. A re­ placement was not found, however, for the sec­ ond school, leaving us with 33 schools for the trial; the matching school was not removed to preserve statistical power. Overall, the schools had an average enrollment (school size) of 480 (SD = 170, range = 77-748) and an average free or reduced-lunch percentage of 43.45 (SD = 30.72, range = 0.00-99.00); interven­ tion and control schools were not significantly different on these measures, F (l, 31) = 2.09, ns, and F (l, 31) = .19, ns, respectively. Twen­ ty-five percent of the schools were from rural areas, 10% were from small towns, 50% were from suburban areas, and 15% were located in midsized cities. On average, 40% of students

309

received free or reduced-price lunch (SD = 29%). The mean number of students per school was 479 (SD = 111, range = 77-749 students) and the mean number of teachers per school was 24. School Staff. We asked all school staff from each of the 33 participating schools to voluntarily complete pretest and posttest ver­ sions of the School Environment Survey. School staff participants included all paid and volunteer staff including: administrators, teach­ ers, paraprofessionals, support staff, custodial and cafeteria personnel, and so forth. At pretest, 1,307 individuals completed a survey (77% of the total population of school staff). At posttest, 1,296 individuals (76%) completed a survey. Respondents represented school administrators (2.8%), teachers (58%), paraprofessionals (10%), cafeteria staff (3.3%), school counselors/psychologists (1.4%), custodial staff (1. 4%), bus drivers (0.7%), volunteers (0.1%), and other positions (7.6%). School staff participants were 90% female, 12% Hispanic, and 88% White. School staff averaged 46 years of age and worked at their schools a median of 3 to 5 years. Students. All students in each of the se­ lected classrooms were included in the target sample of 3,119 students for completion of the student survey; 2,940 (94%) provided data at both time points, which comprised the analytic sample for this study. Approximately half (50. 4%) of the analytic sample was male, 52.5% were White, and 6.6% were African American; 41.7% of students identified as of Hispanic or­ igin via self-report. Students ranged in age from 7 to 11 years, with 2.3% being age 7, 27.7% being age 8, 48.1% being age 9, 19.1% being age 10, and 2.8% being age 11 (M = 8.92, SD = .92). Surveys were conducted in class (proctored by research staff), and took approx­ imately one class period to complete. Students received a small gift worth about $5 for each interview they completed in the fall (pretest) and spring (posttest). Steps to Respect The program included 11 semiscripted skills lessons focusing on social-emotional skills for positive peer relations, emotion management, and recognizing, refusing, and reporting of bul­ lying behavior were delivered by teachers. Les-

310

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son topics included joining groups, distinguish­ ing reporting from tattling, and being a responsible bystander. Instructional strategies included direct instruction, large- and smallgroup discussions, skills practice, and games. Weekly lessons, totaling about 1 hr, were taught over 2 to 3 days. Overall, fidelity to the program was high. Third through sixth grade teachers’ ratings of school-wide implementation on a four-item scale (1 = poor, 4 = excellent) indi­ cated that, by the end of the school year, pro­ gram policies and procedures were well imple­ mented (M = 3.25, SD = 0.44). Teachers reported teaching 99.2% of all classroom skill lessons. Approximately 75% of students were exposed to at least 95% of all lessons and an additional 22% of students were exposed to between 75% and 94% of the lessons. Overall, program engagement (e.g., asking questions, volunteering) was high (M = 3.67, SD = .54). Across all lessons, 18% of teachers reported omitting one or more elements from a lesson. Despite this, a high percentage of teachers (92%) reported completing all objectives. Measures Student survey. Student pre- and posttest survey data (October and April, approximately) were collected using a revised version of the Colorado Trust’s Bullying Prevention Initiative Student Survey (Csuti, 2008a). The outcome

scales used in this study, the number of items per scale, scale coefficient alphas, intraclass correlations, and sample items for the posttest administrations of the survey are presented in Table 1. Scale scores for student survey mea­ sures were constructed as the mean of all non­ missing items. The school psychosocial climate construct is composed of three subscales for student climate, connectedness, and support. School environment survey. Pretest and posttest data were collected from school staff during school staff training sessions (in inter­ vention schools only) or during in-service meet­ ings using the School Environment Survey (SES). The SES is a brief (10-min), anonymous, paper-and-pencil survey, which was adapted for the current study from the Colorado Trust’s 3-year statewide Bullying Prevention Initiative (Csuti, 2008b). The SES was designed to par­ allel several of the measures collected from the student surveys to provide an alternative source of information on the social-ecological context of the school environment. School staffs were asked about their perceptions of their school’s climate, their school’s antibullying policies and strategies, and background demographic infor­ mation (age, gender, race/ethnicity, how many years they worked at the school, and their po­ sition at the school). Scale scores for outcome measures were created as the mean of all non­ missing items on the scale, and teacher reports

Table 1 Student Survey Measures Variable School climate (pre)

Bullying perpetration (post) Bullying victimization (post) Positive bystander behavior (post) Student attitudes against bullying (post) Student attitudes toward intervention in bullying incidents (post) Note.

Number of Coefficient items alpha ICC 15

.87



7

.87

.07

4

.75

.04

5

.71

.05

7

.87

.04

4

.79

.08

ICC = intraclass correlation.

Sample item/response options This is a close-knit school where everyone looks out for each other; students in my school are willing to help each other. (1 = Strongly disagree to 4 = Strongly agree) I teased or said mean things to certain students. (1 = Never to 5 = A lot) A particular student or group of students pushed, shoved, tripped, or picked a fight with me. (1 = Never to 5 = A lot) I ignored rumors or lies that I heard about other students. (1 = Never to 5 = A lot) How okay is it when students tease weaker students in front of others? (1 = Extremely wrong to 5 = Very okay) How okay is it when students defend others who are being shoved around by strong students? (1 = Extremely wrong to 5 = Very okay)

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SCHOOL CLIMATE

were averaged across school. The two SES measures used in this study were as follows: Organizational climate was measured by eight items from the School Antibullying Poli­ cies and Strategies scale that asked school staff about how much their school was doing with regard to policies and strategies to prevent bul­ lying (e.g., Demonstrating administrator com­ mitment and leadership to address bullies, bul­ lied, and bystanders). Responses were recorded on a 4-point Likert-type scale ranging from (1 = Not at all to 4 = A lot, M = 2.83, SD = .76). Coefficient alpha for this measure was .93. Psychosocial school climate was measured by seven items that asked school staff how much they were connected or bonded, or shared the same values with each other, with students, and with parents (e.g. Staff in this school can be trusted.). Responses were recorded on a 4-point Likert-type scale ranging from 1 = Strongly disagree to 4 = Strongly agree (M = 3.46, SD = .47). Coefficient alpha for this measure was .91. School characteristics. Data on school size and the demographic characteristics of stu­ dents were obtained from the National Center for Educational Statistics (NCES; http://www .ed-data.kl2.ca.us). The following variables were used as school-level predictors of bullying outcomes: total student enrollment (M = 479, SD = 180); percentage eligible for the free or reduced-price lunch program (M = 40, SD = 29); and percentage White (M = 50, SD = 30).

Robust standard errors were used to address any issues with non-normality. School size was di­ vided by 100 before being entered into the anal­ yses. Models were estimated using Restricted Maximum Likelihood analysis, which can pro­ vide unbiased estimates in the presence of miss­ ing data. The tenability of regression assump­ tions was evaluated with each model, but no significant violations were found (not pre­ sented). To examine moderation, staff-report climate and policy variables were multiplied with inter­ vention condition at Level 2, or in the case of student-report climate, we calculated a cross­ level interaction. If interaction effects between climate and intervention condition were not sig­ nificant, models were rerun without the interac­ tion effects in order to examine main effects of climate and the intervention independently (to maximize power). For example, students’ selfreported level of bullying at posttest was re­ gressed upon (a) pretest levels of bullying, (b) levels of Staff Psychosocial Climate (PCLM) measured at pretest, and (c) school size (SZE), school-level percentage of White students (WHT) and eligible for free or reduced-price lunch (FRL), intervention condition (STR), and the interaction term (INT); this is illustrated in the following model: Model 1: Level 1 (Student) POST - BULLYING = poj + (3!j(PRE - BULLYING) + e

Statistical Analyses Level 2 (School) In order to assess the unique effects of cli­ mate (after controlling for intervention status), as well as the moderating effects of climate on intervention status, hierarchical linear models (HLM 7.0; Raudenbush & Bryk, 2002), were conducted wherein the student outcome mea­ sures were regressed on pretest staff (Level 2) and student-report climate (at Level 1), with school intervention status and characteristics at Level 2. The impacts of student-reported and staffreported climate were examined in separate models, and each outcome was examined sepa­ rately according to standard HLM practice. Variables were grand-mean centered and ran­ dom effects were included in all model equa­ tions to account for variability across schools.

Poj = 7oo + Voi(SZE) + yo2(WHT) + 7o3(FRL) + y0A(STR) + 7os(PCLM) + y06(INT) + noj Pij = Vio + 7 n (SZE) + 7|2(WHT) + y ,3(FRL) +7,4(5-77?) + 715(PCLM) + y16(INT) + uX} To examine moderation by student-report cli­ mate, students’ self-reported level of bullying at posttest was regressed upon (a) pretest levels of bullying; (b) levels of Student- Perceived Psy­ chosocial Climate (PCLM) measured at pretest; and (c) school size (SZE), school-level percent­ age of White students (WHT) and eligible for free or reduced-price lunch (FRL), and inter­ vention condition (STR); this is illustrated in the following model:

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LOW AND VAN RYZIN

Model 2: Level 1 (Student) POST - BULLYING = (30j + P ^P R E - BULLYING) + P2j(PCLM) + e Level 2 (School)

Poj = Too + Yoi(SZE) + y02(WHT) + 7 o3(FRL) + Yo4(STR) + u0i

Pij = 7io + Yn(SZE) + y 12(WHT) + 7 13(FRL) + y u (STR) + uVj Pzj = 720 + 72i(SZE) + y22(WHT) + 723(FRL) + 724(STR) + «2j In this model, the interaction between studentreport climate and intervention condition does not require the insertion of an interaction effect; rather, this effect is captured by 724, a fixed effect representing a cross-level interaction. Missing Data 6For the SES and student survey instru­ ments, 39.3% and 11.5% of school staff and students, respectively, were missing 67% or more of items on at least one of each survey’s scales. A statistical comparison of partici­ pants that had missing scale data versus those who did not have missing scale data indicated that rates of missingness did not differ by partic­ ipants’ gender, race/ethnic group, age, grade, or intervention status (all ps > .05). Rates of missing scale data, however, were significantly different by geographic area, with one area demonstrating lower rates of missing data than the other two geographic areas, x2(E N = 3,048) = 4.81 , p < .05. To account for the missing data at the scale level, we conducted multiple imputation anal­ yses (Graham, 2009) using NORM version 2.03 (Schafer, 1999), separately for each of the three surveys. To preserve the unique variance-covariance structures of the data by intervention status, we conducted separate imputation analyses for experimental and control schools. Imputation analyses included all respective outcome measures, partici­ pants’ background demographic information,

and dummy-coded indicator variables repre­ senting the matching of schools into pairs. Forty imputed data sets were created for each survey by intervention status group. Imputed data sets were combined subsequently to in­ clude both intervention and control groups for analysis of outcome measures. Results Correlations and sample descriptive data for all variables at Level 1 are provided in Table 2. The bullying measures demonstrated significant stability across time (i.e., from pretest to post­ test). Descriptive data for the schools (i.e., size, free or reduced-price lunch) is presented in the Method section. Descriptive data for staffreport climate is as follows: psychosocial cli­ mate (M = 3.33, SD = .20, range = 2.86 to 3.74); organizational climate (M = 2.85, SD = .33, range = 2.27 to 3.47). The two staff mea­ sures of climate were significantly correlated, r = .59, p < .001, but were not correlated with size, ethnicity, or free or reduced-price lunch, with the following exceptions: psychosocial cli­ mate was correlated free or reduced-price lunch, r = —.56, p < .001, and with percentage White, r = .63, p < .001. Staff Psychosocial Climate To evaluate the effects of staff-report psycho­ social climate, we initially fit a model evaluat­ ing whether staff-report climate moderated the effect of the intervention on student-report out­ comes (as in Model 1); the results are presented in Table 3. Victimization was the only outcome that demonstrated a significant interaction effect (effect size, R2 = .24); the negative coefficient for this effect indicated that a more positive psychosocial school climate, as reported by the teachers and staff, was associated with a larger drop in student-reported victimization at post­ test. Because the interaction term was significant for only one outcome, we removed it and reran the models (excluding the model for victimiza­ tion) in order to obtain an estimate of the main effect of staff-report psychosocial climate; the results are presented in Table 4. Staff-report psychosocial climate was linked with a variety of improvements in student outcomes by post­ test, including lower levels of bullying perpe-

313

SCHOOL CLIMATE Table 2

Correlations and Sample Descriptives fo r Level 1 Variables From Student Survey 1

1. School climate (pre) 2. Bullying perpetration (pre) 3. Bullying victim (pre) 4. Positive bystander behavior (pre) 5. Student attitude against (pre) 6. Student attitude intervention (pre) 7. Bullying perpetration (post) 8. Bullying victim (post) 9. Positive bystander behavior (post) 10. Student attitude against (post) 11. Student attitude intervention (post)



M SD > < .05.

* > < .0 1 .

2

-.30*** -.22*** -.0 2

3

— .33*** -.0 2

.20*** -.16***

4

-.20**’

.42*** .16***

-.19***

| g***

.17***

_

jq***

.12*** 1.27 2.99 .46 1.78

8

7

9

10

11

— .44’**



.18*** .04* -.18*’* -.10*** .47*** -.08*** -.06** -.07***

.13*** -.11***

.10***

6



.15*** -.14*** -.12*** -.27*** -.19*** -.16***

5



1 bU\

Variable

.33*** -.09*** -.1 6 ’**

-.07*** -.07***

.16***

— .27**' .02



.09*** -.08**'' -.05*

-.09*** -.15*** .15*** .23*** -.0 3 2.30 1.61 2.11 2.36 3.70 1.04 .50 .98 1.87 .90



-.19***

.32’*’*



-.09*** 3? * * . * .58**'* — 2.64 3.53 3.02 2.16 1.04 .52 1.41 1.11

* * > < .0 0 1 .

tration and higher levels of positive bystander behavior (the effect for attitudes against bully­ ing was marginal). Effects sizes ranged were in the medium range (R 2 = .2 4 -2 5 ).

Staff Organizational Climate We then ran similar models for teacher reports of school organizational climate; these models were similar to Model 1 but made use of organi­ zational climate rather than psychosocial climate.

We initially fit a model evaluating whether staffreport organizational climate moderated the effect of the intervention on student-report outcomes; the results indicated no significant interactions. Thus, we removed the interaction terms and reran the models in order to obtain estimates of the main effect of organizational climate; the results are presented in Table 5. Staff-report organizational climate was linked with a decrease in bullying perpetration at posttest (R2 = .43).

Table 3

Multilevel Models o f Staff-Report Psychosocial Climate (With Interaction Terms) Bullying perpetration Predictors (all assessed at pretest) Baseline measure School level School size (enrollment) Ethnicity (% White) SES (% FRL) Intervention condition Psychosocial climate (staff) Intervention X Climate Effect size (interaction)

.44 (.03)*** .00 (.03) -.009 (.002)**’ -.005 (.002)** 1.27(1.24) -.4 3 (.34) -.4 3 (.37) .04

Victimization .46 (.02)*** .00 (.04) .001 (.002) .001 (.002) 2.58 (.92)** .34 (,18)+ -.8 0 (.28)** .24

Positive bystander behavior

Attitudes against bullying

.38 (.02)***

.19 (.03)***

.01 (.02) .003 (.001)* .001 (.001) 1.33 (.81) .65 (.17)*** -.4 2 (.24) .04

Note. SES = School Environment Survey; FRL = free or reduced-price lunch. > < .1 0 .

> < .0 5 .

* > < .0 1 .

* * > < .0 0 1 .

.09 (.04)* .004 (.003) -.001 (.003) 2.85 (2.10) 1.17 (.53)* -.8 4 (.63) .07

Attitudes toward intervention .26 (.03)*** .07 (.03)* .002 (.002) -.004 (,002)t 1.72(1.58) .77 (.40)+ -.5 0 (.47) .00

314

LOW AND VAN RYZIN

Table 4 Multilevel Models fo r Staff-Report Psychosocial Climate (Without Interactions) Bullying perpetration Predictors (all assessed at pretest) Baseline measure School level School size (enrollment) Ethnicity (% White) SES (% FRL) Intervention condition Psychosocial climate (staff) Effect size (climate)

Positive bystander behavior

Attitudes against bullying



.38 (.02)***

.19 (.03)"*

— — — — — —

.01 (.02) .003 (.001)+ .001 (.001) -.0 6 (.06) .43 (.19)* .25

Victimization

.44 (.03)*" .00 (.03) -.009 (.002)*" -.005 (.002)** -.1 5 (.0 8 / -.6 4 (.26)* .24

.08 (.04)* .003 (.003) -.001 (.003) .05 (.13) .74 (,42)f .08

Attitudes toward intervention .26 (.03)*" .07 (.03)’ .002 (.002) -.0 0 4 (,002)t .05 (.10) .50 (.31) .06

Note. SES = School Environment Survey; FRL = free or reduced-price lunch. Because the Victimization model had a significant interaction term, it was not rerun to examine main effects. > < . 1 0 . *p < .05. * > < . 0 1 . * * > < .0 0 1 .

Student-Report Psychosocial Climate Finally, to evaluate the effects of studentreport climate on intervention outcomes, we ran a model with student reports of climate at Level 1 (while including the intervention condition at Level 2) and a cross-level (Climate X Interven­ tion Status) interaction. The results are pre­ sented in a single table (see Table 6) because there were no significant cross-level interac­ tions. Although no cross-level interactions with intervention condition were significant, studentreport psychosocial climate was linked with a variety of improvements in student outcomes by posttest, including lower levels of bullying per­ petration and victimization and higher levels of positive bystander behavior, attitudes against

bullying and attitudes toward bullying interven­ tion. As shown in the table, effect sizes for climate effects ranged from small to medium (.08-21). There was one significant interven­ tion effect on bullying perpetration. Discussion Social-ecological theory is a guiding tenet of bullying prevention, insofar as bullying is a school-wide problem (see Mehta et al., 2013; Unnever & Cornell, 2004). Just as much as bullying creates a climate of fear, mistrust and intimidation, several studies suggest that a sup­ portive, fair and respectful school climate pro­ vides a host environment that engenders the

Table 5 Multilevel Model fo r Staff-Report Organizational Climate Bullying perpetration .44 (.03)***

-.01 .001 .001 -.0 8 .01

(.02) (.002) (.002) (.06) (.09) .00

.39 (.02)"*

.18 (.03)***

.01 (.02) .004 (.001)" .000 (.001) -.0 6 (.06) .10 (.09) .00

O

.01 (.02) -.001 (.002) -.003 (,002)f -.1 5 (,08)+ -.3 8 (.10)"* .43

.46 (.02)*"

Attitudes against bullying

60 O

Predictors (all assessed at pretest) Baseline measure School level School size (enrollment) Ethnicity (% White) SES (% FRL) Intervention condition Organizational climate (staff) Effect size (climate)

Victimization

Positive bystander behavior

.005 (.003) -.002 (.003) .05 (.13) .20 (.22) .00

Attitudes toward intervention .26 (.03)*" .06 (.04)f .003 (.003) -.005 (.003) .05 (.08) .14 (.18) .00

Note. SES — School Environment Survey; FRL — free or reduced-price lunch. The interaction term between Organiza­ tional Climate and Intervention Condition was not significant in any model. > < . 1 0 . > < . 0 5 . * > < . 0 1 . * * > < .0 0 1 .

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SCHOOL CLIMATE

Table 6 Multilevel Model fo r Student-Report Psychosocial Climate

Predictors (all assessed at pretest) Baseline measure Psychosocial climate (students) Effect size (climate) School level School size (enrollment) Ethnicity (% White) SES (% FRL) Intervention condition

Bullying perpetration .44 (.03)*** -.21 (.06)*** .21 -.0 1 -.0 1 0 -.0 0 4 -.1 6

(.02) (.002)*** (.002)t (.08)*

Victimization

Positive bystander behavior

Attitudes against bullying

.45 (.02)*** -.1 3 (.04)** .14

.40 (.02)*** .20 (.05)*** .10

.29 (.03)*** .59 (.07)*** .14

-.0 1 (.02) .001 (.002) .001 (.002) -.0 9 (.05)

.01 (.02) .004 (.001)* .000 (.001) -.0 7 (.07)

.08 (.03)* .004 (.003) -.001 (.002) .03 (.12)

Attitudes toward intervention .31 (.03)*** .20 (.06)** .08 .05 (.03) .003 (.003) -.005 (.003) .03 (.08)

Note, SES = School Environment Survey; FRL = free or reduced-price lunch. The cross-level interaction between Intervention Condition and Student-Report Climate was not significant for any outcome. > < .10. > < . 0 5 . * > < . 0 1 . * * > < .0 0 1 .

norms, behaviors, and attitudes/values that are incompatible with aggressive behavior (Bryk & Driscoll, 1988; Gottfredson et al., 2005; Zaykowski & Gunter, 2012), including bullying as a specific subclass (Guerra et al., 2011; Meyer-Adams & Connor, 2008; Nansel et al., 2001). Additionally, a handful of studies sug­ gest that a positive psychosocial climate is piv­ otal to the success of violence prevention pro­ grams (Bradshaw et al., 2009; Eliot et al., 2010; Meraviglia et al., 2003). Yet, few of these stud­ ies have been specific to bullying prevention (where context is particularly critical), and most have utilized single reporters, have a limited sampling of bullying (and related) outcomes, and have not utilized multilevel modeling. In addition to addressing these methodological limitations, there remains a paucity of studies that disentangle the relation between context (i.e., climate) and bullying prevention program­ ming, as if these were orthogonal to each other. Doing so will provide valuable information for theory building and prevention. The current article is predicated on the belief that in order to understand how bullying pre­ vention programs work (or fail to work), we must understand the broader context and eluci­ date the role of the host environment, or school climate. Scholars can agree that context matters with bullying prevention, but the novel contri­ bution of the current study is examining how bullying prevention programs (in this case, STR) work in conjunction with existing school climate. The goals of the current study were to examine the main effects of climate (i.e., psy­

chosocial and organizational dimensions) and STR, as well as the moderating role of school climate on the impact of STR. Specifically, we examined whether the effects of STR were strengthened by positive school climate (i.e., a synergistic or interactive effect), or whether the relation between STR and outcomes was largely nonconditional upon climate. Findings from the current article yield a consistent pattern, across both student and staff reports, wherein the psy­ chosocial dimension of climate is predictive of positive changes in bullying attitudes and be­ havior, but does not appear to enhance STR intervention effects. For example, students who reported more positive psychosocial climate, re­ gardless of intervention group, also endorsed stronger attitudes toward intervention and atti­ tudes against aggression, as well as improved bystander behavior; students’ perceived psy­ chosocial climate also predicted lower levels of victimization and perpetration. In the case of staff perceptions, more positive psychosocial climate was related to lower levels of perpetra­ tion and improved bystander behavior. In only one instance, climate demonstrated a synergistic effect with STR: staff-report psychosocial cli­ mate appeared to strengthen the effects of STR on student-report victimization. Interestingly, when the effects of STR and climate are con­ sidered simultaneously (e.g., Table 4), most of the main effects of intervention condition are nonsignificant, even though they were found to be significant previously (Brown et al., 2011); a reminder of the potent role of environment. In sum, our results also suggest that bullying pro-

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grams such as STR may have a smaller impact on bullying behaviors and attitudes in schools that already possess positive psychosocial cli­ mates. At the same time, it is important to not di­ minish the synergistic effect between staffreport psychosocial climate and reduced victim­ ization among STR intervention schools. This finding suggests that intervention schools with more supportive psychosocial communities will see greater program impacts on student-report victimization. Positive psychosocial environ­ ments may not only model and reinforce more pro-social behavior, but there is literature sug­ gesting that supportive school climates corre­ spond with greater levels of critical coping skills among students, such as seeking help from adults, because youth feel safer (Williams & Cornell, 2006; Wilson & Deanne, 2001). Thus, positive school climates may serve as an importance bridge between skill acquisition and skill deployment, to the extent that these skills are contingent upon on having trusting, caring relationships with adults. Because STR can significantly and positively impact school climate (both staff and student report; Brown et al., 2011), it may be that the effects of STR (and, by extension, other bully­ ing prevention programs) are mediated by school climate. In other words, the effects of STR on bullying behavior and attitudes may come about due to an STR-generated improve­ ment in psychosocial climate. With only two waves of data, we were not able to adequately evaluate this hypothesis, but it presents an in­ triguing topic for future research. Furthermore, these data do not preclude what is likely a recursive relationship between bullying and psychosocial climate, in which climate leads to reductions in bullying behavior, which in turn improves the psychosocial climate. Thus, trans­ actional models (with ample time points) would be a significant contribution to the field of bul­ lying prevention. In contrast to the relationship aspects of cli­ mate, the organizational component (i.e., school policies/administrative commitment) was not as strongly related to attitudes and bystander be­ havior or victimization, but did predict less bully perpetration over a 1-year period. This was the case for all schools, regardless of inter­ vention condition. Administrative leadership and commitment may help create norms

wherein violence is less normative; or it may be that this construct is a proxy for the disciplinary climate of the school, implying that bullying behavior receives stronger corrective action from staff. It is important to note that we did not gather more detailed information about other programs/practices adopted by administration, and policies were not evaluated for merit; thus, it is difficult to disentangle staff commitment from genuine evidence-based or “gold stan­ dard” practices. In other words, because many schools have antibullying policies in place, higher levels of staff-report organizational cli­ mate may represent something as simple as staff “buy-in” to school policy. The marked contrast between main effects of climate versus intervention status suggests that bullying prevention is not a simple or quick fix. Rather, the current data validate a socialecological or comprehensive approach to vio­ lence prevention (Espelage & Swearer, 2003) and suggest that establishing a positive school climate is foundational to reducing violence and aggressive behavior. A positive psychosocial climate appears to not only elevate the skill levels among students, but in some cases, may enhance (or facilitate) behavioral changes from stand-alone prevention programs such as STR. Because improvement in skills doesn’t automat­ ically translate to behavioral change, our results suggest that one way in which psychosocial climate may facilitate bullying curriculum is via relationships, insofar as supportive, trusting re­ lationships provide a context (characterized by more connectedness and a greater sense of safety) wherein students are more likely to uti­ lize or apply their acquired skills. In addition, facilitation of behavioral changes may happen at the programmatic level (see Orpinas, 2009). That is, staff/teachers who feel they are part of a positive, close school community may show greater adoption of programs and more efforts at engaging students in the curriculum. Of course, both of these are hypothetical mediational mechanisms that warrant further analysis but were not addressed in the current study. Consistent with our hypothesis, it is notewor­ thy that there was generally strong overlap across reporters in the observed pattern of rela­ tions. This was the case, despite slightly differ­ ent constructs and different methodological ap­ proaches (i.e., aggregated at school level for staff, vs. individual level for students). In this

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study, the psychosocial climate scales across reporters were not identical, but both were meaningfully related to bullying behavior and attitudes, suggesting that they both tapped the same core construct. It is also important to highlight that we assessed climate in multilevel models, wherein we controlled for several school-level demographic factors that corre­ lated significantly with psychosocial climate (i.e., ethnicity and socioeconomic status), so our measurement approach departs from what scholars have done previously. Despite strong similarities in relations between climate and bullying behavior across reporters/perspectives, the only moderating effect was specific to staffreport perceptions of psychosocial climate. One could argue that staff climate captured a more diverse set of relations, that is, between staff, parents, and students. Thus, perhaps staff per­ ceptions reflect a broader, more comprehensive view of the social environment, although other scholars have found the opposite (i.e., that staff perceived climate is driven more by classroom characteristics; Mitchell et ah, 2010). Or, per­ haps the social culture among teachers, and between teachers and parents, is particularly salient for understanding and unpacking the ef­ fects of stand-alone bullying prevention pro­ grams. Further studies on the specific aspects of climate that are driving behavioral change are needed, and will help in more precise targeting of prevention strategies. It remains an important public health pri­ ority to understand the nature and timing of shifts in peer violence and aggression in schools and how stand-alone programs oper­ ate dynamically in response to their host en­ vironments. The field could also benefit from a deeper understanding of the mutuality be­ tween the different dimensions of climate and bullying behavior within schools, given the translational value of such knowledge. In­ deed, there remains a gap between research validating a social-ecological approach to bullying prevention and the number of “mul­ titiered,” “whole school,” or “comprehen­ sive,” programs that target and promote pos­ itive social-interactions across different microcontexts. Current limitations of our study notwithstanding, our findings cannot only spark dialogue about how bullying pre­ vention programs operate (or are optimized) within a given ecology, but also have impor­

tant implications for school decision makers around factors of adoption, efficiency, and resource allocation. References Bradshaw, C. P., Koth, C. W., Thornton, L. A., & Leaf, P. J. (2009). Altering school climate through school-wide positive behavioral interventions and supports: Findings from a group-randomized ef­ fectiveness trial. Prevention Science, 10, 100-115. doi: 10.1007/sl 1121-008-0114-9 Brown, E. C., Low, S., Smith, B. H., & Haggerty, K. P. (2011). Outcomes from a school-randomized controlled trial of Steps to Respect: A Bullying Prevention Program. School Psychology Review, 40, 423-443. Bryk, A. S., & Driscoll, M. E. (1988). The high school as community: Contextual influences and consequences fo r students and teachers. Madison, WI: National Center on Effective Secondary Schools, University of Wisconsin. Cohen, J., McCabe, L., Michelli, N. M., & Pickeral, T. (2009). School climate: Research, policy, prac­ tice, and teacher education. The Teachers College Record, 111, 180-213. Committee for Children. (2005). Steps to respect: A bullying prevention program. Seattle, WA: Com­ mittee for Children. Corrigan, M. W., Klein, T. J., & Isaacs, T. (2010). Trust us: Documenting the relationship of stu­ dents’ trust in teachers to cognition, character, and climate. Journal o f Research in Character Educa­ tion, 8(2), 61-73. Csuti, N. (2008a). The Colorado trust bullying pre­ vention initiative student survey. Retrieved from http ://w ww.coloradotrust. org/attachments/0001/ 4051/B PI_Student_Survey.pdf Csuti, N. (2008b). The Colorado trust bullying pre­ vention initiative student survey. Retrieved from http://www.coloradotrust.org/attachments/0001/ 4051/BPI_Student_Survey.pdf Durlak, J. A., & DuPre, E. P. (2008). Implementation matters: A review of research on the influence of implementation on program outcomes and the fac­ tors affecting implementation. American Journal o f Community Psychology, 41, 327-350. doi: 10.1007/sl 0464-008-9165-0 Eliot, M., Cornell, D., Gregory, A., & Fan, X. (2010). Supportive school climate and student willingness to seek help for bullying and threats of violence, Journal o f School Psychology, 48, 533-553. doi: 10.1016/j .j sp.2010.07*001 Espelage, D. L., & Swearer, S. M. (2003). Research on school bullying and victimization: What have we learned and where do we go from here? School Psychology Review, 32, 365-383. Retrieved from

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The moderating effects of school climate on bullying prevention efforts.

Bullying prevention efforts have yielded mixed effects over the last 20 years. Program effectiveness is driven by a number of factors (e.g., program e...
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