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Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
Peace builders research-combo
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Peace builders research-combo

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This bundle of articles covers all of Dr. Embry's bold and original studies related to the largest youth violence prevention study in the US during the 1990s.

This bundle of articles covers all of Dr. Embry's bold and original studies related to the largest youth violence prevention study in the US during the 1990s.

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  • 1. Major PeaceBuilders Research and Program Articles The following publications are attached, which provide information and background on the large-scale, community-based randomized control trial evaluating a theoretically-driven violence- prevention program, PeaceBuilders®. References Cited Embry, D. D., Flannery, D. J., Vazsonyi, A. T., Powell, K. E., & Atha, H. (1996). PeaceBuilders: A theoretically driven, school-based model for early violence prevention. American Journal of Preventive Medicine, 12(5, Suppl), 91. This paper describes the theory, experimental design and baseline findings of the randomized control group study. Krug, E. G., Brener, N. D., Dahlberg, L. L., Ryan, G. W., & Powell, K. E. (1997). The impact of an elementary school-based violence prevention program on visits to the school nurse. American Journal of Preventive Medicine, 13(6), 459-463. This paper reports on reductions in illnesses and injuries as measured by nurses’ office visits. This is possibly the first experimental proof of actual proximal reductions in violent injuries as a result of a violent-injury prevention effort. Flannery, D. J., Vazsonyi, A. T., Liau, A. K., Guo, S., Powell, K. E., Atha, H., et al. (2003). Initial behavior outcomes for the PeaceBuilders universal school-based violence prevention program. Developmental Psychology, 39(2), 292-308. The paper provides teacher and self-report outcomes using standardized measures related to social competence and aggression. Both measures have strong prediction for life-course aggression or resiliency. Vazsonyi, A. T., Belliston, L. M., & Flannery, D. J. (2004). Evaluation of a School- Based, Universal Violence Prevention Program: Low-, Medium-, and High-Risk Children. Youth Violence and Juvenile Justice, 2(2), 185-206. This paper reports on differential effects of the intervention for the most-high risk youth, based on baseline data. The People Magazine article from April 5, 1999 tells the story of the use of PeaceBuilders in Salinas, CA and other communities.
  • 2. Developmental Psychology Copyright 2003 by the American Psychological Association, Inc. 2003, Vol. 39, No. 2, 292–308 0012-1649/03/$12.00 DOI: 10.1037/0012-1649.39.2.292 Initial Behavior Outcomes for the PeaceBuilders Universal School-Based Violence Prevention Program Daniel J. Flannery Alexander T. Vazsonyi Kent State University Auburn University Albert K. Liau Shenyang Guo Kent State University University of North Carolina at Chapel Hill Kenneth E. Powell Henry Atha Centers for Disease Control and Prevention Pima County (AZ) Community Services Department Wendy Vesterdal Dennis Embry University of Arizona PAXIS Institute PeaceBuilders is a universal, elementary-school-based violence prevention program that attempts to alter the climate of a school by teaching students and staff simple rules and activities aimed at improving child social competence and reducing aggressive behavior. Eight matched schools (N 4,000 students in Grades K–5) were randomly assigned to either immediate postbaseline intervention (PBI) or to a delayed intervention 1 year later (PBD). Hierarchical linear modeling was used to analyze results from assess- ments in the fall and spring of 2 consecutive school years. In Year 1, significant gains in teacher-rated social competence for students in Grades K–2, in child self-reported peace-building behavior in Grades K–5, and reductions in aggressive behavior in Grades 3–5 were found for PBI but not PBD schools. Differential effects in Year 1 were also observed for aggression and prosocial behavior. Most effects were maintained in Year 2 for PBI schools, including increases in child prosocial behavior in Grades K–2. Implications for early universal school-based prevention and challenges related to evaluating large-scale prevention trials are discussed. Despite recent downturns in national rates of violence perpetra- significantly high levels (Snyder & Sickmund, 1999). The propor- tion by juveniles, a significant number of young people remain tion of young people who self-report having committed serious both perpetrators and victims of interpersonal violence (Dahlberg, acts of violence has also held steady since peaking in the early 1998; Mercy & Potter, 1996; Sickmund, Snyder, & Poe-Yamagata, 1990s (Snyder, 2000). 1997; Snyder & Sickmund, 1999). For example, though the overall Violence occurs at home, in neighborhoods, and at school. homicide rate in the United States has declined, rates for homicide Many recent studies illustrate the impact that exposure to violence and nonfatal injuries among children and adolescents remain at and victimization from violence have on mental health and behav- Daniel J. Flannery and Albert K. Liau, Institute for the Study and Injury Prevention and Control, Centers for Disease Control and Prevention, Prevention of Violence, Kent State University; Alexander T. Vazsonyi, Atlanta, Georgia. Department of Human Development and Family Studies, Auburn Univer- We gratefully acknowledge the contributions of Laura Williams, Kelly sity; Shenyang Guo, School of Social Work, University of North Carolina Wester, Laurie Biebelhausen, and Lara Belliston to data management and at Chapel Hill; Kenneth E. Powell, Centers for Disease Control and analysis. We also appreciate the comments of Thomas Simon on an earlier Prevention, Atlanta, Georgia; Henry Atha, Pima County Community Ser- version of the manuscript. We are grateful to the students, staff, and parents in the Sunnyside and Tucson unified school districts for their ongoing vices Department, Tucson, Arizona; Wendy Vesterdal, Department of support and participation. Family and Consumer Resources, University of Arizona; Dennis Embry, PeaceBuilders is a registered trademark of Heartsprings, Inc. The use of PAXIS Institute, Tucson, Arizona. trade names is for identification only and does not constitute endorsement Albert K. Liau is now at the Psychological Studies Group, National by the U.S. Public Health Service or the U.S. Department of Health and Institute of Education, Singapore. Kenneth E. Powell is now at the Georgia Human Services. Department of Human Resources, Division of Public Health, Atlanta, Correspondence concerning this article should be addressed to Daniel J. Georgia. Flannery, Institute for the Study and Prevention of Violence, Kent State This project was supported in part by Cooperative Agreements U81- University, 230 Auditorium Building, Kent, Ohio 44242. E-mail: CCU010038 – 03 and U81-CCU513508 – 01 from the National Center for dflanne1@kent.edu 292
  • 3. SPECIAL ISSUE: VIOLENCE PREVENTION 293 ior, including an increased risk for engaging in violent behavior Farrington, 1998; Tolan & Gorman-Smith, 1998; Tremblay et al., (Elliott, Hamburg, & Williams, 1998; Flannery, 1997; Singer, 1992, 1995; Walker, Colvin, & Ramsey, 1995) and for becoming Anglin, Song, & Lunghofer, 1995; Singer et al., 1999). Although antisocial adults (Eron & Huesmann, 1990). the risk of homicide victimization at school remains low (Kachur Promising studies exist showing that the developmental trajec- et al., 1996), levels of exposure to violence and victimization from tory of youth violence may be altered (CPPRG, 1999; Dahlberg, violence at school remain high, particularly for elementary and 1998; Englander-Golden, Jackson, Crane, Schwarzkopf, & Lyle, middle school children (Kaufman et al., 2000; Singer et al., 1999). 1989; Hawkins, 1995; Howard, Flora, & Griffin, 1999; Reid, While recent data suggest a decline in the number of students Eddy, Fetrow, & Stoolmiller, 1999; Stoolmiller et al., 2000; Trem- carrying weapons to school (7% of high school students were blay et al., 1991). Several studies have now demonstrated that found to have done so within the previous 30 days; Kann et al., aggressive behavior can be reduced by altering the social environ- 2000), the use of firearms and other weapons has heightened the ments at school (Farrell & Meyer, 1997; Gottfredson, 1997; lethality of violence among young people (Rushforth & Flannery, Greenberg, Kusche, Cook, & Quamma, 1995; Grossman et 1999) and has significantly increased the likelihood that specific al.,1997; Reid et al., 1999; Stoolmiller et al., 2000), particularly by conflicts will escalate into lethal exchanges (Fagan & Wilkinson, emphasizing rewards and praise for prosocial behavior (CPPRG, 1997). In fact, despite recent declines in gun use and lethal forms 1999; Walker et al., 1995) and improving social competence of violence, the proportion of young people involved in nonfatal (Hawkins, Catalano, Kosterman, Abbott, & Hill, 1999; O’Donnell, violence has not declined (Snyder, 2000). Arrest rates for aggra- Hawkins, Catalano, Abbott, & Day, 1995) while reducing cues that vated assaults remain almost 70% higher than they were in 1983, might increase hostility (Lochman & Dodge, 1994). and this is the offense most frequently captured in self-reports The Good Behavior Game (GBG) is one type of school-based of violence (U.S. Department of Health and Human Services prevention program that has established clear evidence of reduced [USDHHS], 2001). aggressive behavior and other forms of child and adolescent prob- The data are clear. Violence among young people remains a lem behavior such as tobacco use and poor academic achievement significant public health problem (USDHHS, 2001). Although (Kellam & Anthony, 1998; Kellam, Ling, Merisca, Hendricks, & many school and community-based violence prevention programs Ialongo, 1998; Salend, Reynolds, & Coyle, 1989). The GBG uses exist, relatively few have been rigorously evaluated (Sherman et classroom behavior management as the primary means of reducing al., 1997; Thornton, Craft, Dahlberg, Lynch, & Baer, 2000). If aggression and problem behavior. Student teams are rewarded by psychologists are to inform public policy and facilitate risk pre- teachers if no member of a team exhibits undesirable behaviors vention for young people, it is imperative that we identify, through while engaged in game sessions. Teachers begin by rewarding applied evaluation studies, programs that effectively prevent youth teams with tangible reinforcers and then gradually move to less violent behavior and its associated precursors (i.e., aggression) and tangible rewards. rigorously evaluate the behavioral outcomes associated with these The Linking the Interests of Families and Teachers (LIFT) interventions (Powell & Hawkins, 1996; Satcher, Powell, Mercy, program has also used the GBG as a core element of a 10-week & Rosenberg, 1996; USDHHS, 2001). In the present study, we universal preventive intervention strategy to reduce aggression and examined the potential impact of a universal elementary-school- increase social competence (Reid et al., 1999; Stoolmiller et al., based violence prevention program on student aggression and social competence. 2000). The overall intervention consisted of parent training, the GBG program, and systematic communication between teachers and parents. The intervention had immediate and significant ef- Preventive Interventions fects on physical aggression among students on the playground as The need to provide early prevention is illustrated by the mul- well as some impact on increased child social competence. Exam- titude of studies that show that violent behavior occurs along a ination of the LIFT program outcomes has also shown strong developmental continuum of behavioral severity (e.g., Flannery & differential effects of treatment, with children highest on aggres- Huff, 1999; Flannery & Williams, 1999; Tolan, Guerra, & Ken- sion at baseline benefiting the most from the intervention (Reid et dall, 1995; Tremblay, et al., 1992). The precursors to more serious al., 1999; Stoolmiller et al., 2000). These short-term and differen- violence perpetration in adolescence (e.g., homicide, assault) are tial effects on aggression are important to consider given the young children’s aggressive behaviors such as hitting, kicking, and pressure to demonstrate significant behavior change with relatively verbal insults and threats (Conduct Problems Prevention Research brief school-based interventions. Group [CPPRG], 1999; Dahlberg, 1998; Huesmann et al., 1996; Another program of research has been conducted by the Con- Huesmann & Moise, 1999; Singer & Flannery, 2000; Stoolmiller, duct Problems Prevention Research Group (CPPRG, 1999). The Eddy, & Reid, 2000; Tremblay, Pagani-Kurtz, Masse, Vitaro, & CPPRG has implemented and evaluated the Fast Track prevention Pihl, 1995). These are the triggers that can escalate interpersonal trial for conduct problem behavior for elementary school children conflict into violence and are the behaviors that need to be targeted at high risk for long-term antisocial behavior. Fast Track is a in preventive interventions in elementary schools. Young people developmentally based, long-term multicomponent and multisite without the skills and competencies to resolve conflicts or solve intervention that has been evaluated using a randomized design problems are at increased risk for violence victimization and with a nonintervention control group. After 1 year of intervention perpetration (Lochman & Dodge, 1994). Longitudinal research has (from kindergarten to Grade 1), the group found moderate positive consistently demonstrated that aggressive, peer-rejected children effects on children’s social competence and conduct problems, in first grade are at increased risk for engaging in delinquent, including child aggressive behavior, for children in the interven- violent behavior in adolescence (Hawkins et al., 2000; Loeber & tion schools compared with children in the control group.
  • 4. 294 FLANNERY ET AL. Several other programs of research have demonstrated child All children and staff in a school learn five simple rules via a behavior change in the areas of improved social competence or common language, which makes the intervention easy to learn and reductions in aggressive behavior in the classroom or on the maintain: (a) praise people, (b) avoid put-downs, (c) seek wise playground (e.g., Grossman et al., 1997; Hawkins et al., 1999; people as advisers and friends, (d) notice and correct hurts we Tremblay et al., 1995; also see Thornton et al., 2000; USDHHS, cause, and (e) right wrongs. To help students learn these principles, 2001). In the current study, we sought to expand on these studies PeaceBuilders includes (a) daily rituals related to its language and by examining the effects of an early elementary-school-based principles that are meant to foster a sense of belonging; (b) cues universal preventive intervention program called PeaceBuilders. and symbols that can be applied to diverse community settings; (c) This program attempts to alter individual child behavior—in par- specific prompts to “transfer” across people, behaviors, and time; ticular, to reduce aggressive behavior and increase social compe- and (d) new materials or strategies introduced for times and tence— by changing the culture or climate of an entire school. circumstances when positive behavior might otherwise decay (Em- There is some evidence that PeaceBuilders affects the incidence of bry, 1980; Embry et al., 1996; Stokes & Baer, 1977). assault-related and violent injury. Specifically, Krug and col- For example, staff and students are encouraged to use “praise leagues (Krug, Brener, Dahlberg, Ryan, & Powell, 1997) found notes” to pay attention to and reinforce positive, prosocial behavior that the frequency of injuries due to fighting for children in Grades in the classroom, at school, and at home. “Peace feet” might be K–5 whose schools were randomized to PeaceBuilders did not placed by the drinking fountains to encourage children not to cut increase over a 1-year period, although the incidence of injuries in line while waiting their turn, and students are sometimes sent to due to fighting for children in control schools increased 56% over the principal for kind acts or good deeds rather than just for the same period. Although these are meaningful archival data, we discipline problems (principal “preferrals”). PeaceBuilder rules report here on teacher and child self-reports of social competence and principles are prominently displayed throughout the school, and aggression, which have high predictive value for long-term and students complete activities from a specially designed comic prevention efforts (CPPRG, 1999; Tolan et al., 1995; Tremblay et book in which they are the designated hero (see Embry et al., al., 1995; Vazsonyi, Vesterdal, Flannery, & Belliston, 1999; 1996). Adults more actively monitor “hot spots” in school such as Walker et al., 1995). School is a logical public health setting for lunchrooms and hallways in between activities, praising prosocial changing the cognitive, social, and imitative characteristics of behavior. All of these strategies and activities are geared toward children at risk for violence. For example, schools can be thought creating a positive climate and culture in the entire school, with an of as large antecedent and reinforcement systems that can increase emphasis on reinforcement of positive behavior rather than simply or decrease antisocial and prosocial behavior (Mayer & Sulzer- the reduction of negative behavior. Azaroff, 1990). We still lack consistent evidence of whether a The training of teachers in the implementation of the present relatively low-cost, widely implemented universal preventive in- intervention had several phases, including a preintervention orien- tervention approach in the early elementary grades will lead to tation for all faculty and staff of the schools, a half-day training significant and sustainable behavior change. workshop on the basic PeaceBuilders model, and extensive site coaching (on average, 2 hr per week) in the first 3 to 4 months of The PeaceBuilders Program the intervention and then on an as-needed basis. All training and coaching were conducted by the model developer (Embry et al., PeaceBuilders is a universal school-wide violence prevention 1996) as a means of facilitating internal validity. Each participat- program for elementary schools (Grades K–5) implemented by all ing school also received specific in-service sessions on important staff and students in a school (Embry, Flannery, Vazsonyi, Powell, issues identified by staff (e.g., implementing activities with special & Atha, 1996). PeaceBuilders focuses on individual behavior needs children), periodic group forums to discuss successes and change in proximal interpersonal and social settings (Tolan & challenges to implementation, and occasional 1-day institutes that Guerra, 1994). The program incorporates an ongoing, long-term focused on applying and creating new materials and interventions. strategy to alter the climate and culture of the entire school (Embry Attendance was voluntary at the institutes and forums. Additional & Flannery, 1999; Embry et al., 1996; Flannery, 1997). The description of program materials and training is available else- intervention is purposely woven into the school’s everyday routine where (e.g., Embry et al., 1996). rather than presented as a time- or subject-limited curriculum. Thus, PeaceBuilders is not offered as a set number of sessions or Hypotheses hours per week but includes activities that can be implemented on a daily basis in any classroom by any teacher or staff person. Our hypothesis was that youth aggressive behavior would be Specifically, PeaceBuilders attempts to change characteristics of reduced by initiating prevention early in childhood and by increas- the setting (antecedents) that trigger aggressive, hostile behavior, ing children’s resilience and social competence. A dual focus on and it increases the daily frequency and salience of both live and reducing aggression and increasing social skills and competencies symbolic prosocial models. If there are more prosocial cues and is important because the prognosis for children with a combination models in a school and these behaviors are consistently reinforced of low social competence, aggressiveness, and poor emotional and and rewarded, then over time, child social competence will in- cognitive preparation is poor (CPPRG, 1999; Kellam, Mayer, crease and the frequency and intensity of aggressive behaviors will Rebok, & Hawkins, 1998; Tolan et al., 1995; Weissberg & Bell, decline. PeaceBuilders specifically rewards prosocial behaviors 1997). We also examined the differential effectiveness of the and provides strategies to avoid the differential or accidental intervention given evidence that treatment outcome effects may reinforcement of negative behaviors and conflict that sometimes vary depending on a child’s initial behavior status prior to partic- happens with conflict mediation programs (Webster, 1993). ipating in an intervention (Reid et al., 1999; Stoolmiller et al.,
  • 5. SPECIAL ISSUE: VIOLENCE PREVENTION 295 2000). We examined both short-term change in aggression and Time 2 in the spring of Year 1. All participating schools remained in the competence (compared with controls) over the 1st year of inter- study through the first 2 intervention years. vention and longer-term change in Year 2, when all schools received intervention. Specifically, in the 1st year, we expected Design and Procedure that children in the intervention-school group, compared with those in the control-school group, would report greater improve- Prior to baseline data collection, the eight project schools were matched into four pairs primarily on the basis of geographic proximity, but we also ments in social competence and greater reductions in aggressive considered the percentage of ethnic students, the percentage of students behavior. By the end of the 2 school years, when both groups were eligible for free or reduced-price lunch, and the percentage of students in receiving the intervention, we expected that, relative to baseline English as a Second Language (ESL) classrooms (see Table 1). School 2A levels, students in both conditions would exhibit significant in- contained fewer Hispanic and more Native American students than its creases in competence and prosocial behavior and decreases in comparison School 2B, but these schools were paired because of their close aggressive behavior. geographic proximity. Four schools were then randomly assigned as PeaceBuilders immediate intervention (PBI) schools and began the pro- Method gram in the fall of 1994 immediately following baseline data collection. The remaining schools began the PeaceBuilders program in 1995 after 1 The study protocol was approved by the Institutional Review Board for year of baseline data collection and are hereafter referred to as PeaceBuild- Human Subjects at the University of Arizona in Tucson and by the ers delayed (PBD) schools (see Figure 1). PBD schools received compen- respective schools’ research review committees. Parents were notified of sation in Year 1 ($1,000) as an incentive for them not to engage in any the project through letters mailed to their homes and by school-distributed PeaceBuilders program-related activities. newsletters. Parents were given the opportunity to withdraw their child We randomized at the school level because all students and staff in a from any data collection. Students were also informed that their participa- school were exposed to and participated in the intervention. Students in the tion was voluntary and were provided an opportunity for alternative class- four PBI schools were exposed to PeaceBuilders for a total of 2 school room activities if they chose not to take part. If a student was engaged in years, and PBD schools participated in the intervention for 1 school year another activity (e.g., band class), we returned to attempt to gather infor- between the fall and spring semesters of Year 2. Owing to limited re- mation at a later date. At the time of survey administration, students were sources, we did not collect any child self-report data from new kindergarten asked to give oral assent, and questions were answered regarding their students in Year 2, we collected Grades 1 and 2 child self-reports only for participation. All students received rewards such as stickers or pencils for students who had participated in Year 1, and we did not follow Year 1 fifth completing the surveys and interviews. graders into sixth grade. Further, students new to PBI schools in Year 2 of Eight elementary schools (Grades K–5) in Pima County, Arizona, were the intervention were not included in these analyses. selected from two large school districts to participate on the basis of having Students in Grades 3–5 completed 100-item self-report surveys at each high rates of juvenile arrests and histories of suspensions and expulsions. data collection point. Surveys were administered in classrooms of about 20 After we met with school administrators to discuss the purpose and scope students with at least two research assistants present to read the entire of the study, all schools that were initially contacted agreed to participate. survey aloud and to answer questions. This procedure resulted in few Schools were located in all areas of town, including some in the central city surveys with missing or incomplete data. Surveys were pilot tested in two and others on the outskirts of town. One of the eight schools consisted of elementary schools prior to data collection to assess the appropriateness of a pair of schools in the same neighborhood, a school for Grades K–2 and the items for young children. All child survey items were answered with a school for Grades 3–5 (approximately 1 block apart), and was treated as the anchors no, a little, or a lot. a single school for pairing, intervention, analysis, and discussion (School For students in Grades K–2, self-report data were collected through 2A). All of the other schools were self-contained Grades K–5 schools. One individual 20-item, face-to-face interviews. The 20 items were pilot tested school that was randomly assigned to the delayed intervention condition with same-age children. Owing to time constraints (we were only able to (School 1B) did not gather initial baseline data but joined the study at interview as many children as time permitted during a single class period), Table 1 School-Level Demographic Characteristics (%) of Matched Pairs Matched African Native Asian Free ESL schools Caucasian American Hispanic American American luncha pairsb 1A (n 704) 63.3 9.7 22.7 0.6 3.7 55 5 1B (n 551) 62.5 14.6 18.5 1.9 2.5 58 8 2A (n 817) 11.6 0.2 33.5 54.6 0.3 94 6 2B (n 377) 29.4 5.2 62.2 1.7 1.4 60 29 3A (n 550) 8.8 2.8 74.4 13.4 0.6 60 29 3B (n 573) 4.8 0.8 91.8 2.5 0.3 94 68 4A (n 327) 28.0 2.8 65.9 2.1 1.3 89 28 4B (n 780) 36.0 3.5 58.5 1.0 1.0 73 21 Note. “A” schools are those randomly assigned to the PeaceBuilders immediate (PBI) intervention, which occurred immediately after baseline data collection. “B” schools were assigned to the PeaceBuilders delayed (PBD) condition. a Percentage eligible for federally funded free or reduced-price lunch programs. b Students for whom English was their second language.
  • 6. 296 FLANNERY ET AL. Figure 1. Overview of project design, data collection, and intervention schedule. we randomly preselected 50% of students in each kindergarten, first-grade, 1,101) of students reported that “Mom” took care of them the most, 15% and second-grade class to be interviewed. Individual interviews, which reported “Dad,” 7% reported some other relative, and 2% each reported a took about 5– 8 min to complete, were conducted at a table outside of the stepparent or some other adult. According to parent reports at Time 2 (n child’s classroom in a quiet area. In Grades K–2 in the participating 809), 63% of children lived in homes with both parents present, 16% were schools, the classes averaged about 20 students per classroom. By ran- from mother-only homes, and 12% lived with “one parent and other domly preselecting half, we were attempting to target about 10 students per adults.” Parent reports of household incomes, although based on a sub- class. Although there were no refusals of children in Grades K–2 to sample of our families, were evenly distributed among the lower range of participate, on average we were able to complete 8 interviews per class, for socioeconomic groups: 22% reported an annual household income of an effective participation rate of 80%. Reasons for not interviewing all 10 $7,000 or less; 19%, an income between $7,000 and $15,000; 24%, an children included the following: Students were absent on the day of data income between $15,000 and $25,000; 23%, an income between $25,000 collection; students were engaged in an alternative school activity during and $40,000; and 12%, an income greater than $40,000 per year. The the time interviews were conducted (e.g., band class), or we ran out of time. majority of our parents had completed the equivalent of high school or less: Limited time and resources precluded our being able to interview children 15% completed less than ninth grade; 12% completed less than high at a later date. Self-report interviews in Year 2 were conducted only for school; 28% completed high school; 38% completed some college; and 7% available students who were interviewed in Year 1. Teachers continued to completed 4 or more years of college. Compared with 1990 U.S. Census report via surveys on all kindergarten, first-, and second-grade children in data, our sample was similar to the population of the metropolitan area their classrooms. (Pima County, AZ) on family composition, household income, and parent At the time of each data collection, teachers of children in Grades K– 5 level of education. The only exception was for child ethnicity. In general, completed a 45-item instrument for each student in their classes. Teachers our sample comprised higher percentages of minority children (and thus provided written consent prior to participation. For Grades 3–5, both fewer Caucasians) than were in the greater metropolitan area from which students and teachers answered questions on bubble scan sheets that the sample was drawn. contained preassigned identification codes for data-tracking purposes. No Student and teacher sample sizes are reported in Figure 2. Student names appeared on student data collection instruments. The preassigned ID response rates ranged from 86% to 93%, and teacher response rates from code allowed us to distribute numbered surveys to specific students on the 75% to 86%. Fewer than 1% of parents chose to withdraw their child from day of data collection as well as to link student and teacher data over time. any of the data collections. Similarly, fewer than 1% of children available All student and teacher surveys were available in both English and Spanish. at each data collection time refused to complete a survey or interview, Schools received compensation for their general funds depending on the usually citing disinterest. percentage of teachers who completed surveys (e.g., $300 for 90% teacher participation). Variables and Instrumentation Sample Demographic variables. Demographic information gathered from stu- dents included age, gender, and grade in school. Teachers reported on On average, students across the 2 years examined were mostly Hispanic children’s ethnicity by categorizing them into one of six groups: Hispanic, (51%), followed by Caucasians (28%), Native Americans (13%), African Caucasian, Native American, African American, Asian American, and Americans (6%), and Asian Americans (1.5%). Seventy-one percent (n other.
  • 7. SPECIAL ISSUE: VIOLENCE PREVENTION 297 Figure 2. Student and teacher sample sizes at each data collection point. The unit of randomization was the school. aOf the children selected to be sampled, only 50% of the students in Grades K–2 were targeted to participate in the child self-report portion of the study. Aggressive behavior. Teachers reported on child aggressive behavior 1991; Grossman et al., 1997). The 25-item Aggressive Behavior subscale using items adapted from the Aggressive Behavior subscale of Achen- asks teachers to rate child behavior on a 3-point scale in which 0 not bach’s (1991) Teacher Report Form (TRF). The TRF has been used true, 1 somewhat or sometimes true, and 2 very true or often true. The extensively as both a clinical screening instrument and in large survey items demonstrated high internal reliability ( .95 at baseline) in our research to assess child externalizing behavior problems (Achenbach, sample.
  • 8. Vazsonyi Youth Violence EVALUATION OF ARTICLEet al. / and Juvenile 10.1177/1541204003262224 Justice A VIOLENCE PREVENTION PROGRAM EVALUATION OF A SCHOOL-BASED, UNIVERSAL VIOLENCE PREVENTION PROGRAM: Low-, Medium-, and High-Risk Children Alexander T. Vazsonyi Lara M. Belliston Auburn University Daniel J. Flannery Kent State University The current investigation examined the differential effectiveness of PeaceBuilders, a large-scale, universal violence prevention program, on male and female youth identi- fied as low, medium, or high risk for future violence. It included eight urban schools ran- domly assigned to intensive intervention and wait-list control conditions. The current sample included N = 2,380 predominantly minority children in kindergarten through fifth grade. Results indicated differential effectiveness of the intervention, by level of risk; high-risk children reported more decreases in aggression and more increases in social competence in comparison to children at medium and low levels of risk. Findings add to a growing number of promising science-based prevention efforts that seek to reduce aggression and increase social competence; they provide encouraging evidence that relatively low-cost, schoolwide efforts have the potential to save society millions in victim, adjudication, and incarceration costs. Keywords: aggression; social competence; violence prevention; ethnicity Young people are the primary perpetrators, victims, and often witnesses of interper- sonal violence in our society (Snyder & Sickmund, 1999). Children who live in a climate of violence learn to suppress empathy and learn that violence is an acceptable means to achiev- ing their goals (Beland, 1996). This growing problem is evident in national crime statistics. Authors’ Note: A previous version of this article was presented at the 9th Biennial Meetings of the Society for Research on Adolescence in New Orleans (April 2002). This project was supported in part by cooperative agree- ments from the National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (#U81-CCU010038-03 and #U81-CCU513508-01), Atlanta, GA. We would like to thank Dennis Embry as well as students, staff, and parents in the Sunnyside and Tucson Unified School Districts for their participation. PeaceBuilders is a registered trademark of Heartsprings, Inc. The use of trade names is for identification only and does not constitute endorsement by the Public Health Service or the U.S. Department of Health and Human Ser- vices. Please address correspondence related to this article to Alexander T. Vazsonyi, Ph.D., Dept. of Human Development and Family Studies, 284 Spidle Hall, Auburn, AL 36849; e-mail: vazsonyi@auburn.edu. Youth Violence and Juvenile Justice, Vol. 2 No. 2, April 2004 185-206 DOI: 10.1177/1541204003262224 © 2004 Sage Publications 185
  • 9. 186 Youth Violence and Juvenile Justice Even though recent publications of the National Crime and Victimization Survey (NCVS) and Uniform Crime Reports (UCR) note continued decreases in violence over the past sev- eral years (U.S. Department of Justice [USDOJ], 2001a, 2001b), juvenile violence remains high. Although firearm-related homicides have decreased, the youth homicide rate has remained fairly stable; moreover, the overall youth violence index, assault with injury, and robbery with a weapon have increased (U.S. Department of Health and Human Services [USDHHS], 2001). In addition, a cross-national comparison shows that the rate of adoles- cent homicides involving a firearm is over 15 times higher in the United States than in 12 European countries combined (Centers for Disease Control and Prevention [CDC], 1997). Prevention and intervention efforts designed to ameliorate violence have identified a number of individual, family, school, peer, and community risk factors that contribute to delinquency and future violence (Andrews & Trawick-Smith, 1996; Consortium on the School-Based Promotion of Social Competence, 1994). Although many of these factors can help identify individuals at risk for problem behaviors, good prevention efforts need to tar- get risk factors most amenable to change, such as skills training, behavior monitoring and reinforcement, behavioral techniques for classroom management, and building school capacity (USDHHS, 2001). A number of individual-level risk factors can be targeted by violence prevention programs. Such factors include general offenses, substance use, aggression, problem behaviors, and antisocial attitudes (Gottfredson, 2001; USDHHS, 2001). Several of these risk factors are highly confounded with rates of deviance; however, the most salient behavioral predictor of later violence and delinquency is early aggression between ages 8 and 10 years (Farrington, 1987; Gottfredson, 2001; Hawkins et al., 1998; Lipsey & Derzon, 1998; Loeber & Dishion, 1983; O’Donnell, Hawkins, & Abbott, 1995; Viemerö, 1996; USDHHS, 2001). Furthermore, aggression in the school context is highly problematic during grade school as it violates peer group and social norms (Bierman & Montminy, 1993; Coie & Dodge, 1998). Cross-sectional research has demonstrated that childhood aggression can foretell official delinquency status (Vazsonyi, Vesterdal, Flannery, & Belliston, 1999). Longitudinal investigations have also demonstrated that aggressive behavior is relatively stable over time and part of a general pattern of antisocial behavior that is associated with later self-reported violence, arrests, and convictions for vio- lent offenses (Farrington, 1987; Lipsey & Derzon, 1998; Loeber, Farrington, Stouthamer- Loeber, Moffitt, & Caspi, 1998; Viemerö, 1996). Most violence and delinquency prevention research has focused on reducing aggres- sion; however, researchers have also emphasized protective factors that may interact with risk factors to buffer or reduce risk of future violence (Bierman, Miller, & Stabb, 1987; Coie & Koeppl, 1990; USDHHS, 2001). Individual-level factors that protect against delin- quency include a positive social orientation and an intolerant attitude toward interpersonal violence and deviance (USDHHS, 2001). Recent prevention efforts have targeted behav- ioral measures of social competence and prosocial skills (e.g., Blechman, 1996; O’Donnell et al., 1995). Children who lack these skills are more likely to rely on their negative pat- terns of interaction and demonstrate more negative behavioral outcomes (Ollendick, Weist, Borden, & Greene, 1992; Quinn, Mathur, & Rutherford, 1995; Walker & McConnell, 1988). However, few rigorous evaluation studies have been completed examining risk and protective factors of juvenile violence and deviance. A next important step for researchers is to identify how risk and protective factors work together to influence problem behaviors. Kupersmidt, Coie, and Dodge (1990) found that aggressiveness and social competence predicted delinquency in elementary school. Similarly, Hämäläinen and Pulkkinen (1995) found that rates of recidivism were greater for
  • 10. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 187 criminals who had been more aggressive and less prosocial when they were young. Con- versely, in a review of intervention programs, Coie and Koeppl (1990) observed that a num- ber of programs targeting aggressive, disruptive, and rejected children focused their pre- vention efforts on increasing prosocial behaviors and paid insufficient attention to reducing aggressive behaviors (e.g., Frey, Hirschstein, & Guzzo, 2000; Gottfredson, Gottfredson, & Skroban, 1998; Prinz, Blechman, & Dumas, 1994). Both behaviors must be changed to achieve intervention effectiveness (Blechman, 1996; Coie & Koeppl, 1990; Gresham & Elliott, 1987; USDHHS, 2001; Wasserman & Miller, 1998). Therefore, rigorous evaluation studies of programmatic efforts should focus on risk and protective factors, and they should evaluate how both of these behaviors change following an intervention. School-Based Violence Prevention Recent violence prevention efforts have shifted to large-scale, universal program- matic efforts (Powell et al., 1996). Although prevention efforts have occurred in multiple contexts, school-based interventions have several advantages (Catalano, Arthur, Hawkins, Berglund, & Olson, 1998; Gottfredson, 2001; USDHHS, 2001). For example, schools are an optimal setting for preventions and interventions; children spend a great deal of time at school with teachers and peers, and large groups of at-risk children can be easily targeted (Beland, 1996; Blechman, 1996). Effective strategies for universal school implementation include behavioral monitoring and reinforcement, classroom management, and skills train- ing; students receive direction from their primary teacher and support from other school staff members. This approach recognizes that behavior change takes time; it also recognizes that the total school atmosphere needs to change as reinforcements are implemented across school experiences (e.g., Farrell, Meyer, Kung, & Sullivan, 2001; Gottfredson, 2001; USDHHS, 2001). Several large-scale, school-based violence prevention programs targeting elementary school students have documented promising findings of program effectiveness (cf. the Stu- dents for Peace Project, Kelder et al., 1996; Orpinas et al., 2000). For example, the Resolv- ing Conflicts Creatively Program (RCCP) (Aber, Jones, Brown, Chaudry, & Samples, 1998) found that the program did not reverse negative or positive behavior patterns but sig- nificantly slowed the trajectories for increasing aggressiveness and decreasing social com- petence, particularly for students who were exposed to most of the programmatic compo- nents. Similarly, findings from the Fast Track prevention trial by the Conduct Problems Prevention Research Group (CPPRG) indicated that the program has decreased rates of conduct problems in children identified as being at high risk for behavior problems in kin- dergarten (baseline; 27% children with conduct problems in the intervention group vs. 37% in the control group; CPPRG, 2002). In another effort evaluating the effects of Peacemak- ers, Shapiro, Burgoon, Welker, and Clough (2002) found decreases in self-reported and teacher-reported aggressive behaviors as well as decreases in the number of disciplinary incidents and suspensions following program implementation. The study also indicated stronger program effects for boys than for girls and for younger children than older ones. Finally, teacher-reported data showed more consistent and stronger program effects than student data, although self-reported student data corroborated findings based on teacher reports. Additional programs require some discussion. Again focusing on a high-risk sample of children, the Metropolitan Area Child Study (MACS) (Eron, Huesmann, Spindler,
  • 11. 188 Youth Violence and Juvenile Justice Guerra, & Henry, 2002; Guerra, Eron, Huesmann, Tolan, & Van Acker, 1997) provided evidence of program effectiveness. Findings indicated that the program was most beneficial when it was administered during the early school years and where it was supported by a 2- year follow-up intervention. They also indicated that the intervention was equally effective for boys and girls; in fact, although median levels of aggression increased over time in inter- vention and control conditions, a significant number of children moved from clinical to nonclinical status for externalizing behavior problems following the intervention. The Responding in Peaceful and Positive Ways (RIPP) (Farrell & Meyer, 1997; Farrell, Meyer, & White, 2001) program and evaluation study provided evidence of a reduction in violent behaviors and less in-school suspensions following the intervention. The reduction in violent behaviors was most evident in students who had high levels of vio- lent behaviors at pretest, which indicated a differential programmatic effect. Finally, two studies evaluating Linking the Interests of Families and Teachers (LIFT) (Reid, Eddy, Fetrow, & Stoolmiller, 1999; Stoolmiller, Eddy, & Reid, 2000) found support for reducing young children’s physical playground aggression and increasing teacher rat- ings of peer-preferred behaviors. Differential effectiveness for reducing children’s aggres- sion were found over time, namely, that children with the highest levels of aggression at pretest showed more changes than children with lower pretest scores. To assess this differ- ential effectiveness, Stoolmiller et al. (2000) measured the effect sizes at four levels of aggression and found medium to high effect sizes for children with the highest levels of aggression at pretest. These findings are encouraging and are consistent with Durlak and Wells’ (1997) meta-analysis that showed that programs targeting reducing negative behaviors and pro- moting social competency show promise. These programs addressed a specific recommen- dation by Durlak and Wells (1997) and Weissberg and Bell (1997) to evaluate program suc- cess for at-risk populations. In particular, these studies started to address the differential effectiveness of programs, how well the programs work for children at risk for future vio- lence, rather than addressing main effects between intervention and control groups. Indeed, Stoolmiller et al. (2000) identified differential effectiveness as a key issue for universal pro- grams. However, researchers disagree on how to best determine risk for future delinquency. Because of low base rates, only a small number of children become classified as officially delinquent, approximately 5% to 6% of boys (Vazsonyi et al., 1999). RIPP, LIFT, and PeaceBuilders have addressed differential effectiveness utilizing regression methodol- ogy (Farrell, Meyer, & White, 2001; Flannery et al., 2003; Stoolmiller et al., 2000). In par- ticular, previous research on PeaceBuilders found differential effectiveness for teacher- reported aggression, self-reported aggression, and prosocial behavior. Based on these studies, the purpose of this article is to test the differential effective- ness hypothesis, namely, that programs have greater effects on children with high rates of problem behaviors as opposed to children with very low rates. Rather than utilizing a regression procedure, an alternative method for assessing differential effectiveness is to assign children to risk levels. In addition, instead of classifying children at risk by official delinquency status, risk determination should include more children by identifying vari- ables that predict delinquency that are not confounded with measures of delinquency (Loeber & Dishion, 1983). LeBlanc (1998) advocated using a “multiple-gating” procedure developed first by Loeber and Dishion (1983) that uses several assessments or predictors as screening gates. The first step is to apply the first predictor to the full sample, temporarily classifying children into risk and nonrisk samples by the primary factor. Subsequently, in the second step, children are maintained or dropped from the risk sample based on the sec-
  • 12. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 189 ond predictor. The result is that a larger number of children are classified at risk for a partic- ular outcome, which may be beneficial for determining how effective programs are for children most at risk for future problems. Thus, the current investigation examined the differential effectiveness of Peace- Builders on children identified as low, medium, or high risk for future problems. Children were classified by the multiple-gating procedure into three risk groups (low, medium, and high risk) based on teachers’ assessments of aggression and social competence. PeaceBuilders Violence Prevention Program PeaceBuilders is a schoolwide, universal violence prevention program that is theoret- ically based (Embry, Flannery, Vazsonyi, Powell, & Atha, 1996). The program attempts to change antecedents that trigger aggressive behavior, reward prosocial behavior, and pro- vide strategies to avoid reinforcing negative behavior. PeaceBuilders is organized around five main principles: (a) PeaceBuilders praise people, (b) PeaceBuilders avoid put-downs, (c) PeaceBuilders seek wise people, (d) PeaceBuilders notice hurts they have caused, and (e) PeaceBuilders right wrongs. The intervention structure uses several behavior techniques to promote change: symbolic and live models, role-plays and rehearsals, and group and individual rewards. The PeaceBuilders program was implemented in the school setting by teachers, prin- cipals, and other support staff. members Teachers use a variety of materials to help teach and encourage students to be PeaceBuilders: “I Help Build Peace” story/workbooks, medi- ation essays, Praise Boards (written records of positive events), games (The Peace Scout Game where anonymous scouts send secret notes), home notes, posters made by children, PeaceCards and secret notes. Teachers received an hour-long preintervention orientation, 3 to 4 hr of training workshops, and 2 hr of site coaching per week that occurred during the first 8 to 12 weeks of program implementation. Additional help sessions were offered when schools had specific questions regarding PeaceBuilders (Embry et al., 1996). The study design included nine project schools with children in kindergarten through fifth grades. One Grade K-2 school and one Grade 3-5 school were combined to form a sin- gle K-5 unit. These eight school units were then grouped into four matched pairs. Within the pairs, schools were randomly assigned as intervention (Wave 1) or wait-list control (Wave 2) schools. Baseline data (Time 1) for all schools were conducted in the fall of 1994. Wave 1 schools received the intervention following baseline, in the fall of 1994, and Wave 2 schools received the intervention in the fall of 1995. Data collection occurred every fall and spring for 2 years; Time 2 data collection occurred spring 1995, Time 3 data collection occurred fall 1995, and Time 4 data collection occurred spring 1996. A preliminary analysis of the effectiveness of PeaceBuilders compared children in an initial treatment versus delayed treatment condition. Children in both conditions had similar baseline levels of aggression and social competence. Hierarchical linear modeling deter- mined that children who received the intervention in the initial treatment condition showed significant increases in teacher-rated social competence and child self-reports of peace building as compared to the delayed treatment condition, over a 2-year period. Similarly, after 12 months, children in the delayed treatment condition showed significantly higher rates of aggression than children in the continuous treatment condition (Flannery et al., 2003). Whereas preliminary longitudinal analyses show some changes in children’s behav-
  • 13. 190 Youth Violence and Juvenile Justice iors because of PeaceBuilders interventions, these results need to be more carefully exam- ined, especially for children who vary in degree of risk for future violence at baseline. Risk status established through a multiple-gating procedure has been used to examine how level of risk subsequently predicts delinquency or externalizing behaviors in previous studies (Lipsey & Derzon, 1998; Lochman & The Conduct Problems Prevention Research Group, 1995; Loeber & Dishion, 1983; Patterson, Capaldi, & Bank, 1991); however, it has not been utilized in evaluation research. One exception is the MACS project, where Guerra et al. (1997) reported splitting children into two risk categories. The most recent reports of MACS program effects (Eron et al., 2002) focused on program effects in the high-risk group of children. Across violence prevention programs, program effectiveness has not been evaluated at multiple levels of risk. Therefore, the current investigation cannot make specific predictions about program effectiveness by level of risk based on previous work; at the same time, we did expect the greatest amount of change in high-risk youth and the smallest amount of change in low-risk youth. More specifically, we expected differential program effects on behavioral outcome measures by levels of risk. For example, we expected that children identified as high risk would show the greatest program effects in teacher-reported aggression and social compe- tence, and self-reported aggression and prosocial behavior. We also expected more modest program effects for children identified at medium risk for future violence and delinquency, and we expected very few program effects for children identified at low risk for future vio- lence and delinquency. Finally, we expected that we would find similar programmatic effects by levels of risk for boys and girls. Method Sample The sample for the current study is based on the PeaceBuilders violence prevention evaluation project conducted in the Tucson metropolitan area (Embry et al., 1996; Flannery et al., 2003; Vazsonyi et al., 1999). The targeted region had experienced an increase in vio- lent offenses from 1990 to 1993—increases in juvenile arrests for violent crimes and homi- cides, vandalism, and weapons violations. Juvenile arrests for total, property, and violent crimes continued to increase and peaked in 1995. Since 1995, juvenile arrests have been decreasing. However, property crimes have decreased at a higher rate than violent crimes, which are still high at similar levels as reported in 1990-1991 (Geospatial and Statistical Data Center [Geostat], 2003). In addition to community-wide efforts to increase social and cognitive competencies related to preventing violence, a comprehensive program, Peace- Builders, was implemented within two city school districts. Two school districts were chosen based on police crime maps; these maps identified areas with high levels of violent crimes and high neighborhood stress (e.g., domestic vio- lence, transition and mobility, poverty levels). Nine schools (one K-2 and 3-5 were com- bined to form one school unit) were invited for participation based on these data (Embry et al., 1996). Schools were matched into four pairs based on geographic proximity, student ethnicity, percentage of students eligible for free or reduced lunch, and percentage of stu- dents with English as their second language (Embry et al., 1996; see Table 1). It is important to note that some of the matched school pairs differed on key variables (e.g., student ethnic-
  • 14. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 191 TABLE 1 School Level Demographic Characteristics: Percentage of Ethnicity and Socioeconomic Variables School School School School School School School School 1A 1B 2A 2B 3A 3B 4A 4B (n = 704) (n = 551) (n = 817) (n = 377) (n = 550) (n = 573) (n = 327) (n = 780) African American 9.7 14.6 0.2 5.2 2.8 0.8 2.8 3.5 Asian/Pacific Islander 3.7 2.5 0.3 1.4 0.6 0.3 1.3 1.0 Hispanic 22.7 18.5 33.5 62.2 74.4 91.8 65.9 58.5 Native American 0.6 1.9 54.6 1.7 13.4 2.5 2.1 1.0 White 63.3 62.5 11.3 29.4 8.8 4.8 28.0 36.0 Free lunch 55 55 94 60 60 94 89 73 English as Second Language 5 8 6 29 29 68 28 21 NOTE: Schools were matched in pairs based on geographic proximity, student ethnicity, percentage of students eli- gible for free or reduced lunch, and percentage of students with English as their second language. Schools were ran- domly assigned to the initial intervention condition (A schools) or the wait-list control condition (B schools). ity). Schools were then randomly assigned to the initial intervention condition or the wait- list control condition. The sample included approximately 4,600 children from kindergarten through fifth grade. Of the total sample, 50% were Hispanic, 29% White, 15% Native American, 5% African American, and 1% Asian/Pacific Islander. Children were roughly evenly divided by sex between the intervention and wait-list control conditions. Figure 1 graphically pres- ents program intervention and data collection periods. One half of the schools received the PeaceBuilders intervention in the fall of the first year (Wave 1), while the other one half received the intervention during the following fall (Wave 2). For the current investigation, we focused on children in third through fifth grades who had teacher ratings of aggression and social competence and self-reports of aggression and prosocial behaviors at the base- line (Time 1). Data from children in both treatment conditions (Wave 1 and 2) were aggre- gated to permit a comparison of children’s pretest scores and posttest scores. Data at pretest were Time 1 data for Wave 1 children and Time 3 data for Wave 2 children. Data at posttest were Time 2 data for Wave 1 children and Time 4 data for Wave 2 children. ANOVAs com- paring pretest scores by Wave showed only one significant difference for female prosocial behavior; Wave 2 girls reported slightly higher prosocial behaviors at pretest than Wave 1 girls (F = 5.96, p < .05, d = .19). The total number of students enrolled in project schools in kindergarten through Grade 5 at initial data collection was N = 4,679. Some students were excluded from the sam- ple because of incomplete data. Teacher data were available on children in kindergarten through Grade 5. Complete teacher data (K-5) were collected from n = 2,380 children (M age = 8.5 years), a response rate of 50.8% (see Table 2). Because of cognitive and language ability, child self-report data were only available for Grades 3 through 5. Complete child self-report data (3-5) were obtained for n = 1,170 children (M age = 9.8 years), a response rate of 52.2% (see Table 2). The low response rates (as compared to Flannery et al., 2003) are due largely to the construction of this sample. First, to classify the students into risk cat- egories by teacher reports, the sample was limited to students with baseline teacher- reported data. Second, to compare pretest and posttest data, Wave 1 children had to have
  • 15. 192 Youth Violence and Juvenile Justice Figure 1. Overview of Project Design, Data Collection, and Intervention Schedule Time 1 and Time 2 data, whereas Wave 2 children had to have Time 3 and Time 4 data. Thus, students without child and/or teacher data at Time 1 and Time 3, for example, were dropped from the sample. This selection process did not appear to vary by sex or race. Approximately 50% of boys and girls were dropped, and race percentages ranged from 20% to 25% for all groups except Native Americans (41%). In addition to sample construc- tion issues, subject attrition rates were related to relatively high residential mobility within school districts. Procedures Data were collected by trained project staff members from teachers in Grades K through 5, and children in Grades 3 through 5. During regular school hours, children com- pleted in-class surveys administered by project staff members who read all questions aloud. The survey took approximately 1 hr to complete, and students received small incentives for their participation, such as stickers or pencils. Teachers completed surveys for each child in their classroom. They received data collection packets at the time of the student survey data collection. Each teacher received $20 for participation. In addition, the schools were eligi- ble for schoolwide incentives based on the number of teacher surveys returned ($300 to $500). During the initial phase of the project, data were collected at four points in time (two fall and two spring, in consecutive school years) for schools assigned to two intervention conditions. Schools in Wave 1 started the intervention immediately following baseline data collection. Schools in Wave 2 began the intervention about 1 year later following Time 3 data collection.
  • 16. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 193 TABLE 2 Sample Description and Response Rates Low Medium High Not Risk Risk Risk Total Classified n n n n N % Teacher report (K-5) with baseline dataa (1,132) 1,147 1,099 1,301 3,547 4,679 75.8 Teacher report (K-5) with pretest/posttest scoresb 840 746 794 2,380 4,679 50.8 Males 455 341 376 1,172 2,380 49.2 Females 385 405 418 1,208 2,380 50.8 Child self-report (3-5) with pretest/posttest scoresb 443 332 395 1,170 2,243 52.2 Males 221 146 197 564 1,170 48.2 Females 222 186 198 606 1,170 51.8 Low Medium High Not Risk Risk Risk Classified % % % n Nd % c Ethnicity African American 20.1 21.8 18.4 39.7 174 3,086 5.6 Asian/Pacific Islander 20.4 40.8 22.4 16.3 49 3,086 1.6 Hispanic 25.6 25.8 24.7 23.8 1,540 3,086 49.9 Native American 40.8 18.7 18.1 22.3 497 3,086 16.1 White 24.0 28.2 21.7 26.2 826 3,086 26.8 NOTE: a. Baseline data for all children were collected at Time 1. b. Data at pretest were Time 1 data for Wave 1 children and Time 3 data for Wave 2 children. Data at posttest were Time 2 data for Wave 1 children and Time 4 data for Wave 2 children. c. Ethnicity statistics reported here were obtained from archival school records and are reported for students with baseline data. d. Ethnicity was available for 3,086 children out of the 4,679 children eligible with baseline data, 34.0% of the sam- ple was missing data on ethnicity. Measures Social competence (teacher report). The 19-item short-form version of the Walker- McConnell Scale of Social Competence (Walker & McConnell, 1995) measured social skills and school adjustment as rated by teachers. The instrument has been used in long- term follow-up studies and has predictive value, particularly for children with serious behavior problems (Fifeld, 1987; Hops, 1987). The scale includes three subscales: School Adjustment (e.g., “student attends to assigned tasks” and “produces work of acceptable quality given his or her skills”); Peer Preferred Behavior (e.g., “invites peers to play” and “shares laughter with peers”); and Teacher Preferred Behavior (e.g., “can accept not getting his or her way” and “compromises with peers when a situation calls for it”). Teachers rated each item on a 5-point scale from 1 = never to 5 = frequently (α = .95). The three subscales were summed to produce an overall Social Competence score (Flannery et al., 2003; Vazsonyi et al., 1999).
  • 17. 194 Youth Violence and Juvenile Justice Aggressive behavior (TRF). Physical and nonphysical aggressive behavior was mea- sured by the 25-item Achenbach’s Child Behavior Checklist Teacher Report Form (Achenbach, 1991; Flannery et al., 2003; Vazsonyi et al., 1999). Teachers were asked to recall children’s behavior over the past 2 months; examples include “The child argues a lot,” “The child gets in many fights,” and “The child threatens people.” Responses were given on a 3-point Likert-type scale, 0 = not true, 1 = somewhat true, or 2 = very true (α = .95). Prosocial behavior (child report). This 16-item scale was developed by the research team to measure how much children engaged in prosocial acts over the past 2 weeks (Flannery et al., 2003; Vazsonyi et al., 1999). Children responded to questions such as “I did things to help other kids,” “I smiled at others,” and “I apologized to a grown-up at school.” Responses were given on a 3-point scale, 1 = no, 2 = a little, and 3 = a lot (α = .92). Aggressive behavior (YSR). This scale consisted of nine items from the Delinquency and Aggression subscales of the Child Behavior Checklist-Youth Self Report (Achenbach, 1991; Flannery et al., 2003; Vazsonyi et al., 1999). Questions asked about physical and nonphysical aggression over the past 2 weeks, for example, “I teased other kids at school,” “I hit someone,” and “I tried to get other students to fight.” Responses were given on a 3- point Likert-type scale, 0 = no, 1 = a little, to 2 = a lot (α = .95). Plan of Analysis Initial descriptive statistics on teacher reports and child self-reports were computed for all children with baseline (Time 1) data. These data were used to classify children into three risk groups: low, medium, and high risk. Analyses for the current study were computed using general linear modeling (GLM). GLM covers a variety of linear models of analyses of variance and covariance, regression, and repeated measures models (Howell, 1992); it also adjusts for unequal cell sizes and pro- vides estimated marginal means (predicted estimates of the population marginal mean based on regression; Searle, Speed, & Milliken, 1980). GLM repeated-measures proce- dures account for variation in the pretest and posttest scores by computing a pooled value for multivariate tests and subsequently determines change over time using estimated marginal means (SPSS, 1999). To maximize sample size, GLM analyses were conducted separately by sex and by teacher and self-report data. Risk status was entered in the model as a between-subjects variable with three levels of risk. Age and race were also included in the model as covariates. Age was a continuous covariate, and race was a categorical covariate, namely, White versus non-White. Because of the inclusion of covariates in the model, GLM analy- ses were conducted in two steps (Winer, 1971). The first step ran the model with the covariates and reported the between-subjects portion of the model. The second step ran the model without the covariates and reported the within-subjects portion of the model. Subse- quently, pairwise comparisons were conducted based on the estimated marginal means. Because differences over time were hypothesized a priori, significant pairwise comparisons were reported regardless of the significance of the omnibus F statistic (Girden, 1992; Tabachnick & Fidell, 1989). One assumption of ANCOVA is that the regression coefficients are equal (Howell, 1992). A significant covariate would violate that assumption, usually invalidating the use of
  • 18. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 195 TABLE 3 Descriptive Statistics of Teacher Reports by Sex (N = 3,554) Males Females (n = 1,765) (n = 1,779) M SD Median M SD Median Social competence 3.49 .82 3.53 3.86 .76 3.89 Aggression (TRF) 1.45 .52 1.24 1.23 .38 1.04 NOTE: Social competence and aggression (TRF) are teacher-reports. TRF = Teacher Report Form of the Achenbach Child Behavior Checklist (Achenbach, 1991). ANCOVA for modeling data (Howell, 1992; G. Hudson, personal communication, March 8, 2002; SPSS, 2002). However, in the current study, the covariates included in the model were not treatment effects but naturally occurring variations in the population. Therefore, we were interested in the percentage of variance in the model explained by each of the covariates (Howell, 1992). For GLM repeated measures, this was done in two procedures: first by analyzing the slope and variance of the covariates for the pooled dependent variable (consistent with GLM multivariate tests) and subsequently by examining whether the covariate influenced change in the dependent variables over the course of the program by using change scores (Howell, 1992; G. Hudson, personal communication, March 8, 2002; SPSS, 2002; Tabachnick & Fidell, 1989). The second step of the analyses determined the effect of the program over time for each of the three risk groups after controlling for the effects of covariates. Pairwise comparisons of the estimated marginal means determined programmatic effects on children’s behaviors at different levels of risk. Results At-Risk Status Children’s at-risk status was determined by teacher-reported aggression and social competence scores collected at baseline. Low, medium, and high risk was defined by a multiple-gating procedure that utilized a median split of the two risk variables separately by sex (see Table 3). Boys and girls were classified as high risk if they had scores above the median in aggression and below the median for social competence; in other words, they exhibited high negative behaviors and few positive ones. Individuals were classified as low risk if they had scores below the median score for aggression; these children also reported high social com- petence scores. The medium-risk group was characterized by scores above the median in aggression and social competence or by scores below the median in aggression and social competence. In other words, these children exhibited a mixture of positive and negative behaviors (see Figure 2 for the multiple-gating procedure; see Table 3 for the number of children in each of the risk groups by sex; there were at least 125 children in each risk category for boys and girls).
  • 19. 196 Youth Violence and Juvenile Justice Figure 2. Multiple-Gating Procedure Winer Model Step 1: Inclusion of Covariates and Between-Subjects Variable The first step of the Winer model includes both covariates, age and race, and the inde- pendent variable, risk status. The results of the analyses are presented in Table 4. The first three columns report the multivariate F statistics for each dependent variable. The next four columns report the slope and percentage of variance explained by each of the covariates in the pooled dependent variable. The last four columns report the slope and percentage of variance explained by the covariates on the amount of change over time in each dependent variable. Significant effects for age were found for female social competence, male teacher- rated aggression, male and female prosocial behaviors, and male self-reported aggression. Significant effects for race were found only for female prosocial behavior as well as male and female self-reported aggression. Significant effects for risk as a covariate were found for male and female social competence, teacher-reported aggression, and self-reported aggression. No significant effects for risk were found for prosocial behavior. When analyzing the effects of the covariates on the pooled dependent variables, age accounted for a large percentage of the variance in prosocial behavior (8.9% girls, 12.8% boys). For both of these variables the slopes were negative; as age increased, prosocial behavior decreased. Age also accounted for 4.4% of the variance in male teacher-rated aggression and 3.2% of the variance in female social competence. Race accounted for very little variance in the dependent variables; the highest percentage of variance attributed to race was for male self-reported aggression (1.4%). Even though age and race accounted for some proportion of the variance in the pooled dependent variables, additional analyses needed to determine the percentage of variance these covariates explained in pre/post change scores. In these scores, age accounted for a small proportion of the variance in male (2.5%) and female (1.5%) changes of social competence and male self-reported aggression (1.5%). Race accounted for very little variability in change scores, namely, 1.7% of the
  • 20. TABLE 4 2 Winer Model (Step 1): Between-Subjects F Values, and Covariate Analyses Slope, and R Values for General Linear Modeling (GLM) model Pooled DV Change Scores Slope % Slope % Slope % Slope % Age Race Risk of Age Variance of Race Variance of Age Variance of Race Variance d d Fd F F β Age β Race β Age β Race Males a Social competence 2.45 1.35 381.40* –.001 1.82 –.004 0.07 –.063 2.54 .014 0.00 a,c Aggression (TRF) 6.21* 1.09 342.29* –.001 4.43 –.002 0.04 .001 0.11 .003 1.69 Prosocial behaviorb 108.11* 0.24 1.33 –.19 12.78 –.002 0.04 –.023 0.19 .037 0.11 Aggression (YSR)b,c 6.95* 7.64* 18.72* –.005 1.36 –.106 1.42 .056 1.53 .047 0.24 Females Social competencea 6.39* 1.67 318.00* –.002 3.23 –.004 0.05 –.044 1.45 .001 0.00 Aggression (TRF)a,c 0.29 0.82 208.51* .000 0.00 .002 0.04 .016 0.78 .047 0.54 Prosocial behaviorb 65.60* 4.40* 0.95 –.152 8.91 –.008 0.57 –.004 0.00 –.007 0.00 Aggression (YSR)b,c 2.04 5.89* 11.83* –.002 0.55 –.005 0.83 –.003 0.00 .037 0.32 a. Teacher reports of social competence and aggression are listed first, n ranges from 323 to 411. b. Child self-reports of prosocial behavior and aggression, n ranges from 125 to 194. c. TRF = Teacher Report Form of Achenbach’s Child Behavior Checklist; YSR = Youth Self-Report Form of Achenbach’s Child Behavior Checklist (Achenbach, 1991). d. Multivariate F statistic is significant at *p < .05. 197
  • 21. 198 Youth Violence and Juvenile Justice variance in male teacher-reported aggression changes. The second step of the analyses demonstrated significant changes over time in each of the three levels of risk. Therefore, a series of analyses was completed in the second step of the Winer model; results are reported in Table 5. Winer Model Step 2: Changes Over Time by Level of Risk High risk. Significant changes over time for children classified as high risk were found for male and female teacher-reported social competence and aggression scores; no significant changes over time were found for self-reported prosocial behavior or aggres- sion. These significant differences were in the hypothesized direction for social competence and aggression. Social competence scores for high-risk children increased significantly for boys (d = .36) and girls (d = .44). Teacher-rated aggression scores decreased significantly for boys (d = –.13) and girls (d = –.24). Medium risk. For children classified at medium-risk status, significant changes over time were found for male and female teacher-reported social competence. No significant changes over time were found for teacher-rated aggression or self-reported prosocial be- havior and aggression. As hypothesized, medium-risk teacher-rated social competence scores increased for boys (d = .34) and girls (d = .31). Low risk. For children classified at low risk, significant changes were found for male and female teacher-rated aggression. No significant changes were found for teacher-rated social competence or self-reported prosocial behavior and aggression. Contrary to hypothe- ses, teacher-reported aggression increased for boys (d = .31) and girls (d = .15). Discussion Based on criteria established by the surgeon general and the Centers for Disease Con- trol and Prevention, the PeaceBuilders (Embry et al., 1996) violence prevention program targets decreasing risk factors and increasing protective factors in a universal school-based program utilizing effective strategies for behavior change (USDHHS, 2001). The current investigation examined whether the PeaceBuilders violence prevention program had a dif- ferential effect on children’s behavioral outcomes by levels of risk (low, medium, and high); more specifically, we were interested in four outcomes, namely, teacher-reported aggression and social competence and self-reported aggression and prosocial behavior. In addition, we were interested in determining the effects of sex, age, and race on program effectiveness. Although researchers have classified children at risk for future problems in previous work (Lochman & The Conduct Problems Prevention Research Group, 1995; Patterson et al., 1991), most of these comparisons have considered children’s behavior differences at one point in time and not in the context of an intervention. Findings indicated that the effects of PeaceBuilders were not universal across risk categories. Significant behavior changes were found for children classified at high risk for future violence at baseline. Consistent with expectations and previous research on differen- tial effectiveness (Farrell, Meyer, & White, 2001; Flannery et al., 2003; Stoolmiller et al.,
  • 22. TABLE 5 Winer Model (Step 2): Pretest-Posttest Scores by Risk, Within-Subjects F Value, and Significant Pairwise Comparisons Low Risk Medium Risk High Risk Pretest Posttest Pretest Posttest Pretest Posttest Time Sig. Risk Pairwise M SD M SD M SD M SD M SD M SD Fd Comparisons d Males Social competencea 4.13 .56 4.18 .67 3.55 .63 3.78 .74 2.93 .57 3.16 .71 10.96* b,c Aggression (TRF)a,c 1.08 .18 1.15 .27 1.34 .39 1.36 .44 1.82 .51 1.75 .55 12.58* a,c Prosocial behaviorb 1.86 .54 1.82 .55 1.84 .55 1.72 .57 1.82 .59 1.80 .56 1.65 Aggression (YSR)b,c 1.26 .35 1.32 .39 1.35 .43 1.39 .46 1.53 .53 1.52 .51 1.55 Females Social competencea 4.44 .49 4.44 .60 3.93 .63 4.13 .65 3.29 .59 3.58 .72 25.54* b,c Aggression (TRF)a,c 1.02 .07 1.06 .17 1.12 .22 1.14 .24 1.48 .48 1.37 .43 28.14* a,c Prosocial behaviorb 2.17 .51 2.07 .53 2.10 .49 2.05 .50 2.13 .47 2.02 .55 0.58 Aggression (YSR)b,c 1.10 .24 1.12 .21 1.15 .29 1.17 .23 1.20 .32 1.23 .34 0.34 NOTE: a-low risk; b-medium risk; c-high risk. a. Teacher reports of social competence and aggression are listed first, n ranges from 341 to 455 for teacher-reports (Grades K-5) and from 146 to 222 for child self-reports (Grades 3-5). b. Child self-reports of prosocial behavior and aggression, n ranges from 125 to 194. c. TRF = Teacher Report Form of Achenbach’s Child Behavior Checklist; YSR = Youth Self-Report Form of Achenbach’s Child Behavior Checklist (Achenbach, 1991). d. F statistic and pairwise comparisons are significant at *p < .05. 199
  • 23. 200 Youth Violence and Juvenile Justice 2000), high-risk children showed the most significant changes over time; teacher-reported aggression decreased, whereas teacher-rated social competence increased. Moreover, these effects were found for boys and girls. However, no positive program effects were found for either of the self-reported variables, prosocial behavior and aggression. For medium-risk children, only teacher-rated social competence increased, whereas no effects were found for teacher- or self-reported aggression. Findings for children classified at low risk showed unexpected changes over time, namely, increases in teacher-reported aggression. At the same time, these children maintained their relatively high levels of social competence. In addition, though aggression increased, the levels of aggression still remained substantially below medium- and high-risk groups, scores that would continue to result in low-risk classification. In conclusion, the findings from the current evaluation effort are encouraging. Together with other recent efforts (e.g., CPPRG, 2002; Eron et al., 2002; Farrell, Meyer, & White, 2001; Shapiro et al., 2002), large-scale universal violence prevention programs such as PeaceBuilders show promise for changing children’s behaviors, in particular for chang- ing risk and protective factors for future violence (cf., CPPRG, 2002). Our findings add to a growing number of investigations that have provided evidence on differential program effi- cacy for high-risk children and youth (e.g., CPPRG, 2002; Eron et al., 2002; Farrell, Meyer, Kung, & Sullivan, 2001); they suggest that students classified at high risk for future behav- ior problems significantly decreased on measures of aggression and increased on measures of social competence. In addition to differential program effectiveness being examined via regression methodology as shown by previous work, the current study demonstrated differ- ential effectiveness through the multiple-gating procedure that utilized two variables for risk classification, presence of negative and lack of positive behaviors at baseline. Future evaluation research should continue to evaluate the effectiveness of violence prevention programs in children who are most at risk. Limitations of the Current Study A number of limitations require some discussion. One important consideration is the insider versus outsider perspective. In the current study, teachers reported more significant behavior changes than did children’s self-reports similar to Shapiro et al. (2002). However, in the current study, no significant results were found by risk level in the differential effec- tiveness of PeaceBuilders for aggression or prosocial behavior. Findings by Stanger and Lewis (1993) based on comparisons of behavior ratings between teacher, child, and parent reports on the Child Behavior Checklist have some important implications for the current study. They found that children generally report more problems than do teachers; they sug- gested that one possible reason for this is that teachers rate behaviors only during school hours, whereas children rate their behaviors across contexts. In addition, they suggested that teachers attend to externalizing behaviors, such as aggression, differently than do chil- dren, because these behaviors cause management problems and may be more salient for the teachers than children. It may be that teachers attended to children’s changed behavior within the school environment, whereas children attended to their behaviors in school and in other contexts outside of schools with siblings or peers. Thus, the differential effective- ness of PeaceBuilders would be limited in generalizability to the school environment. Another issue requiring discussion is the one of quasi-experimental design. The cur- rent study did not contain a true control condition. Due to Institutional Review Board (IRB)
  • 24. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 201 requirements and practical considerations, all children received the intervention at some point, thus creating a wait-list control condition, where one half of the students received the intervention 1 year later. Children in this latter condition did complete data collections prior to the intervention and may have been aware of PeaceBuilders prior to actual inter- vention at their school. With quasi-experimental designs, the study is compromised because program effects cannot be clearly determined; however, quasi-experimental design emphasizes the ecological context and optimizes generalizability because programs are evaluated as they are implemented (Henrich, Brown, & Aber, 1999). Third, without comparing change over time among students classified in risk categories in intervention and control conditions, we could not determine whether changes in reported behaviors were due to regression to the mean. Therefore, one plausible explanation for our findings could include regression to the mean. Fourth, the current study was limited by participant attrition. The PeaceBuilders eval- uation study was conducted in high-risk neighborhoods that experienced very high residen- tial mobility that limited the number of students with longitudinal data (for a discussion, see Flannery et al., 2003). A final limitation is that results may be attributable to teacher bias. Additional analyses conducted by Belliston (2000) and Flannery et al. (2003) have docu- mented varied fidelity of implementation. However, analyses have indicated that fidelity of implementation did not affect the differential effectiveness of the program by risk category. Conclusions/Implications Universal, school-based programs such as PeaceBuilders show promise for reducing aggression and increasing social competence (Flannery et al., 2003; Shapiro et al., 2002). Such relatively low-cost programs that attempt to blanket the school population have important policy implications in that spending only a few hundred dollars per child during elementary school might save the criminal justice system millions later on, when individu- als enter it during adolescence and adulthood (Cohen, 1998). Specifically, Cohen (1998) estimated the costs of a criminal on society based on calculations such as mean number of offenses, victim cost of crime, cost of investigation and adjudication, incarceration, fore- gone earnings, and opportunity cost of time. He noted that the benefits of programs that reduce crime might exceed the cost estimates computed, in terms of affecting large social problems, reducing fear of crime, reducing private security measures, or changing lifestyle due to decreased risk of victimization (e.g., walking vs. taking a cab). Cohen estimated that, for a juvenile career, the present lifetime costs range between U.S.$80,000 and $325,000; for an adult offender, $1.2 million, total costs ranging from $1.3 to $1.5 million for juvenile and adult career offenses. When combining comorbid problems of criminality, drug use, and high school dropout, costs to society range from $1.7 to $2.3 million (Cohen, 1998). In contrast, the entire PeaceBuilders project budget for project administration, project devel- opment, project implementation, training, follow-ups, evaluation design, and data collec- tion and analysis cost less than $200 per child over the project’s 3-year period. Thus, the cost of the program is minimal compared to potential costs due to a life of crime and vio- lence. Universal programs such as PeaceBuilders seem effective and cost-efficient because they can reach an entire population of children, not only children at risk. By reaching a greater number of children, such programs change the school climate, reduce the number of classroom disruptions, and ultimately reduce the total number of children at risk for future violence.
  • 25. 202 Youth Violence and Juvenile Justice REFERENCES Aber, J. L., Jones, S. M., Brown, J. M., Chaudry, N., & Samples, F. (1998). Resolving conflict cre- atively: Evaluating the developmental effects of a school-based violence prevention program in a neighborhood and classroom context. Development and Psychopathology, 10, 187-213. Achenbach, T. M. (1991). Manual for the Child Behavior Checklist/4-18 and 1991 Profile. Burlington: University of Vermont Department of Psychiatry. Andrews, L., & Trawick-Smith, J. (1996). An ecological model for early childhood violence preven- tion. In R. L. Hampton & P. Jenkins (Eds.), Prevention violence in America. Issues in chil- dren’s and families’ lives (pp. 233-261). Thousand Oaks, CA: Sage. Beland, K. R. (1996). A school-wide approach to violence prevention. In R. L. Hampton, P. Jenkins, & T. P. Gullotta (Eds.), Preventing violence in America (pp. 209-231). Thousand Oaks, CA: Sage. Belliston, L. M. (2000). The impact of the PeaceBuilders school-based violence prevention program on low, medium, and high-risk children. Unpublished master’s thesis, Auburn University, Alabama. Bierman, K. L., Miller, C. L., & Stabb, S. D. (1987). Improving the social behavior and peer accep- tance of rejected boys: Effects of social skill training with instructions and prohibitions. Jour- nal of Consulting and Clinical Psychology, 55, 194-200. Bierman, K. L., & Montminy, H. P. (1993). Developmental issues in social-skills assessment and intervention with children and adolescents. Behavior Modification, 17, 229-254. Blechman, E. A. (1996). Coping, competence, and aggression prevention: II. Universal school-based prevention. Applied and Preventive Psychology, 5(1), 19-35. Catalano, R. F., Arthur, M. W., Hawkins, J. D., Berglund, L., & Olson, J. J. (1998). Comprehensive community- and school-based interventions to prevent antisocial behavior. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 248-283). Thousand Oaks, CA: Sage. Centers for Disease Control and Prevention. (1997). Rates of homicide, suicide, and firearm-related death among children—26 industrialized countries. Morbidity and Mortality Weekly Report, 46(5), 101-105. Cohen, M. A. (1998). The monetary value of saving a high-risk youth. Journal of Quantitative Crimi- nology, 14(1), 5-33. Coie, J. D., & Dodge, K. A. (1998). Aggression and antisocial behavior. In W. Damon (Ed.), Hand- book of child psychology (pp. 780-845). New York: John Wiley. Coie, J. D., & Koeppl, G. K. (1990). Adapting intervention to the problems of aggressive and disrup- tive rejected children. In S. R. Asher & J. D. Coie (Eds.), Peer rejection in childhood (pp. 309- 337). Cambridge, UK: Cambridge University Press. Conduct Problems Prevention Research Group. (2002). Evaluation of the first 3 years of the Fast Track prevention trial with children at risk for adolescent conduct problems. Journal of Abnor- mal Child Psychology, 30(1), 19-35. Consortium on the School-Based Promotion of Social Competence. (1994). The school-based promo- tion of social competence: Theory, research, practice, and policy. In R. J. Haggerty, L. R. Sherrod, N. Garmezy, & M. Rutter (Eds.), Stress, risk and resilience in children and adoles- cents (pp. 268-316). Cambridge, UK: Cambridge University Press. Durlak, J. A., & Wells, A. M. (1997). Primary prevention mental health programs for children and adolescents: A meta-analytic review. American Journal of Community Psychology, 25(2), 115- 152.
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  • 27. 204 Youth Violence and Juvenile Justice Hops, H. (1987). Behavior correlates of positive and negative sociometric status among same-sex children. (Available from Oregon Research Institute, 149 W. 12th Avenue, Eugene, OR 97401) Howell, D. C. (1992). Statistical methods for psychology (3rd ed.). Belmont, CA: Duxbury. Kelder, S. H., Orpinas, P., McAlister, A., Frankowski, R., Parcel, G. S., & Friday, J. (1996). The Students for Peace Project: A comprehensive violence-prevention program for middle school students. American Journal of Preventive Medicine, 12(5), 22-30. Kupersmidt, J. B., Coie, J. D., & Dodge, K. A. (1990). The role of poor peer relations in the develop- ment of disorder. In S. R. Asher & J. D. Coie (Eds.), Peer rejection in childhood (pp. 309-337). Cambridge, UK: Cambridge University Press. LeBlanc, M. (1998). Screening of serious and violent juvenile offenders: Identification, classification, and prediction. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 167-193). Thousand Oaks, CA: Sage. Lipsey, M. W., & Derzon, J. H. (1998). Predictors of violent or serious delinquency in adolescence and early adulthood: A synthesis of longitudinal research. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 248-283). Thousand Oaks, CA: Sage. Lochman, J. E., & The Conduct Problems Prevention Research Group. (1995). Screening of child behavior problems for prevention programs at school entry. Journal of Consulting and Clinical Psychology, 63(4), 549-559. Loeber, R., & Dishion, T. (1983). Early predictors of male delinquency: A review. Psychological Bul- letin, 94(1), 68-99. Loeber, R., Farrington, D. P., Stouthamer-Loeber, M., Moffitt, T. E., & Caspi, A. (1998). The devel- opment of male offending: Key findings from the first decade of the Pittsburgh Youth Study. Studies on Crime and Crime Prevention, 7(2), 141-171. O’Donnell, J., Hawkins, J. D., & Abbott, R. D. (1995). Predicting serious delinquency and substance use among aggressive boys. Journal of Consulting and Clinical Psychology, 63(4), 529-537. Ollendick, T. H., Weist, M. D., Borden, C., & Greene, R. W. (1992). Sociometric status and academic, behavioral, and psychological adjustment: A five-year longitudinal study. Journal of Consult- ing and Clinical Psychology, 60(1), 80-87. Orpinas, P., Kelder, S., Frankowski, R., Murray, N., Zhang, Q., & McAlister, A. (2000). Outcome evaluation of a multi-component violence prevention program for middle schools: The Stu- dents for Peace Project. Health Education Research, 15, 45-58. Patterson, G. R., Capaldi, D., & Bank, L. (1991). An early starter model for predicting delinquency. In D. J. Pepler & K. H. Rubin (Eds.), The development and treatment of childhood aggression (pp. 139-168). Hillsdale, NJ: Lawrence Erlbaum. Powell, K. E., Dahlberg, L. L., Friday, J., Mercy, J. A., Thornton, T., & Crawford, S. (1996). Preven- tion of youth violence: Rationale and characteristics of 15 evaluation projects. American Jour- nal of Preventive Medicine, 12(5), 1-2. Prinz, R. J., Blechman, E. A., & Dumas, J. E. (1994). An evaluation of peer coping–skills training for childhood aggression. Journal of Clinical Child Psychology, 23(2), 193-203. Quinn, M. M., Mathur, S. R., & Rutherford, R. B. (1995). Early identification of antisocial boys: A multi-method approach. Education and Treatment of Children, 18(3), 272-281. Reid, J. B., Eddy, J. M., Fetrow, R. A., & Stoolmiller, M. (1999). Description and immediate impacts of a preventive intervention for conduct problems. American Journal of Community Psychol- ogy, 27(4), 483-517. Searle, S. R., Speed, F. M., & Milliken, G. A. (1980). Population marginal means in the linear model: An alternative to least squares means. American Statistician, 34(4), 216-221.
  • 28. Vazsonyi et al. / EVALUATION OF A VIOLENCE PREVENTION PROGRAM 205 Shapiro, J. P., Burgoon, J. D., Welker, C. J., & Clough, J. B. (2002). Evaluation of the Peacemakers Program: Prevention for students in grades four through eight. Psychology in the Schools, 39(1), 87-100. Snyder, H. N., & Sickmund, M. (1999). Juvenile offenders and victims: 1999 national report. Wash- ington, DC: Office of Juvenile Justice and Delinquency Prevention. SPSS. (1999). SPSS 10.0 syntax reference guide. Chicago: Author. SPSS. (2002). AnswerNet solution #100010254. Available at www.spss.com Stanger, C., & Lewis, M. (1993). Agreement among parents, teachers, and children on internalizing and externalizing behavior problems. Journal of Clinical Child Psychology, 22(1), 107-115. Stoolmiller, M., Eddy, J. M., & Reid, J. B. (2000). Detecting and describing preventive intervention effects in a universal school-based randomized trial targeting delinquent and violent behavior. Journal of Consulting and Clinical Psychology, 68(2), 296-306. Tabachnik, B. G., & Fidell, L. S. (1989). Using multivariate statistics. New York: Harper & Row. U.S. Department of Health and Human Services. (2001). Youth violence: A report of the surgeon gen- eral. Rockville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; Substance Abuse and Mental Health Services Administration, Center for Mental Health Services; and National Institutes of Health, National Institute of Mental Health. U.S. Department of Justice. (2001a). Crime index trends, 2000 preliminary figures. Available at www.fbi.gov/pressrel/pressrel01/ucrprelim2000.htm U. S. Department of Justice. (2001b). Four measures of serious violent crime. Available at www. ojp.usdoj.gov/bjs/glance/tables/4meastab.htm Vazsonyi, A. T., Vesterdal, W. J., Flannery, D. J., & Belliston, L. M. (1999). The utility of child self- reports and teacher ratings in classifying children’s official delinquency status. Studies of Crime and Crime Prevention, 8(2), 1-20. Viemerö, V. (1996). Factors in childhood that predict later criminal behavior. Aggressive Behavior, 22(2), 87-97. Walker, H. M., & McConnell, S. R. (1988). The Walker-McConnell Scale of Social Competence and School Adjustment: A social skills rating scale for teachers. Austin, TX: PRO-ED. Walker, H. M., & McConnell, S. R. (1995). The Walker-McConnell Scale of Social Competence and School Adjustment (SSCSA). Florence, KY: Thomson Learning. Wasserman, G. A., & Miller, L. S. (1998). The prevention of serious and violent juvenile offending. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 197-247). Thousand Oaks, CA: Sage. Weissberg, R. P., & Bell, D. N. (1997). A meta-analytic review of primary prevention programs for children and adolescents: Contributions and caveats. American Journal of Community Psy- chology, 25(2), 207-214. Winer, B. J. (1971). Statistical principles in experimental design (2nd ed.). New York: McGraw-Hill. Alexander T. Vazsonyi is an associate professor of human development and family studies at Auburn University. He received his Ph.D. from the University of Arizona. His research interests include etiological risk factors in adolescent problem behaviors, deviance, and violence. Recent publications have appeared in the Journal of Research in Crime and Delinquency, the Journal of Quantitative Criminology, and Criminal Justice and Behavior.
  • 29. 206 Youth Violence and Juvenile Justice Lara M. Belliston is currently a doctoral candidate in the Department of Human Devel- opment and Family Studies at Auburn University. Her research interests include adoles- cent development, family relationships, and program evaluation. Daniel J. Flannery, Ph.D., is a professor of justice studies and director of the Institute for the Study and Prevention of Violence at Kent State University. He received his Ph.D. in 1991 in clinical psychology from The Ohio State University. He was coeditor (with C. R. Huff) of Youth Violence: Prevention, Intervention and Social Policy (1999). His primary areas of interest are in youth violence prevention, the link between violence and mental health, and program evaluation.
  • 30. 298 FLANNERY ET AL. Child self-report of aggressive behavior in Grades 3–5 was assessed assessed degree of satisfaction or effectiveness of the program, such as using items generated specifically for this study. The 9-item scale con- “PeaceBuilders is easy to use” or “Overall, my school has implemented the tained items such as “I hit someone” or “I put down other kids” that were PeaceBuilders curriculum,” answered on a 4-point scale ranging from rated on a 3-point scale ranging from no (1) to a lot (3). The scale strongly agree (1) to strongly disagree (4). Teachers were also asked to demonstrated adequate internal consistency ( .86 at baseline). Children indicate the total number of core PeaceBuilders materials they used in their in Grades K–2 answered yes or no to five items assessing whether they got classrooms. These included the Action Guide, reproducible binders (sep- into trouble at school, if they ever got into fights, and if they ever cut in line arate lessons on PeaceBuilders rules), the “I Help Build Peace” storybook, ( .66 at baseline). praise notes in class, praise notes sent home, “First Aid for Anger,” the Social competence. Teachers rated child social competence using the Playground Guide, and the Intensive PeaceBuilders Guide. elementary school version (Grades K-6) 19-item short form of the Walker– McConnell (W-M) Scale of Social Competence and School Adjustment (Walker, Irvin, Noell, & Singer, 1992; Walker & McConnell, 1995). The Analysis Plan W-M scale has three subscales: School Adjustment (7 items), Peer- Preferred Behaviors (7 items), and Teacher-Preferred Behaviors (5 items). After presenting correlation data on the relationship between teacher- The School Adjustment subscale assesses adaptive social– behavioral com- and child-reported outcomes, we provide some descriptive data on the level petencies highly valued by teachers within classroom instructional con- of program implementation and teacher training. We then present data on texts. Peer-Preferred Behaviors reflect peer values concerning forms of sample attrition within and between school years and its relation to internal social behavior that govern peer dynamics and social relations within validity (differential attrition by intervention group) and external validity free-play settings. Teacher-Preferred Behaviors reflect teacher ratings of (characteristics lost to the sample). Then we turn to our main analytic questions of year-to-year differences in the immediate and delayed inter- sensitivity, empathy, cooperation, self-control, and socially mature forms ventions’ effects on our outcomes of interest. We conducted two main of behavior in peer relations. Teachers responded to such items as “appro- types of analyses to address our specific hypotheses regarding school-year priately copes with aggression from others” on a 5-point Likert scale changes in behavior outcomes relative to baseline. ranging from never (1) to frequently (5). The W-M scale has demonstrated First, we constructed a three-level hierarchical linear model (Version 5, high internal consistency and test–retest reliability and correlates with Bryk & Raudenbush, 1992) to examine change in behavior assessed at four other teacher and child self-report measures of social competence (Walker points in time over 2 school years. The three levels of the model reflect & McConnell, 1995). In the present sample, the internal consistency of the change over time (Level 1), individual effects (Level 2), and school effects W-M scale was high ( .95 at baseline). The W-M scale has been used (Level 3). The model was constructed to examine both short-term (Year 1) in other preventive intervention studies with elementary-school-age chil- and longer term (Year 2) change in outcomes after controlling for baseline dren to differentiate behavior outcomes between treatment groups (e.g., levels and student gender. Because there was not continuous intervention Reid et al., 1999). over the summer months, we decided to model our effects by creating a Prosocial behavior. Prosocial behavior for children in Grades 3–5 was series of dummy variables for each data collection time point (Neter, measured with a 16-item instrument designed for this study. The items Wasserman, & Kutner, 1983), with baseline as the reference (spring of assessed child self-reported empathy, caring, helpfulness, and support of Year 1 Time 2, fall of Year 2 Time 3, spring of Year 4 Time 4). others. Sample items include “I helped adults at school without being Specifically, we first examined change from baseline to the spring semester asked” and “I helped other kids.” Children responded to each item using a (Time 2) in Year 1 for PBI schools and PBD schools. We also examined 3-point scale that included no (1), a little (2), and a lot (3). The scale items differences in Year 2 between schools with 2 years of intervention (PBI loaded on a single factor (eigenvalue 6.34) and displayed high internal schools) and schools with 1 year of intervention (PBD schools). In PBI consistency ( .92 at baseline). Children in Grades K–2 answered yes, schools, we expected the most significant changes to occur at Time 2, sometimes or no, not really to six questions assessing sharing, helpfulness, after 1 year of intervention. saying “thank you,” and saying “I’m sorry” ( .51 at baseline). Hierarchical linear modeling (HLM) has several advantages for the Peace-building behavior. Child self-report of peace-building behavior analysis of longitudinal data. First, responses on any outcome variable in Grades 3–5 was assessed with three items: “I helped build peace at from the same individual over time will be correlated, thus violating the school,” “I told other kids they were peace builders,” and “I earned rewards assumption about independent sample observations embedded in most for peace building.” Responses on the 3-point scale ranged from no to a lot. statistical models dealing with cross-sectional data, and HLM takes this The three items loaded on a single factor (eigenvalue 1.86) and dem- correlation into account. This intraclass correlation also needs to be taken onstrated adequate internal consistency ( .72 at baseline). Children in into account when school is used as the unit of assignment to condition Grades K–2 responded yes or no to four items about building peace such (Koepke & Flay, 1989; Murray & Wolfinger, 1994; Piper, Moberg, & as “I helped build peace at school” and “I earned rewards for peace King, 2000; Rooney & Murray, 1996). Second, when applying conven- building.” This yes/no scale demonstrated marginal internal consistency tional linear models to analyzing longitudinal data, one generally under- ( .58 at baseline). estimates the standard errors of the impacts and therefore may erroneously Teacher training. Immediately after teachers participated in an in- assume statistical significance. HLM effectively handles this problem as service training session, workshop or institute, they completed a 10-item well as others inherent in longitudinal data, such as varying times between survey designed to assess the clarity and effectiveness of the training and observations, unequal groups at each data point over time, and the need to their impressions of whether the materials and program would be easy or control for the effects of potentially confounding independent variables difficult to implement. Sample items, rated on a 5-point scale ranging from (Bryk & Raudenbush, 1992; Diggle, Liang, & Zeger, 1994; Lindsey, strongly agree to strongly disagree, included “The basic philosophy behind 1993). These advantages make HLM more appropriate than the more PeaceBuilders is easy to understand”; “The training provided for the conventional repeated measures analyses used in longitudinal studies. program was clear, effective and easy to follow”; and “As an intervention The second main analytic approach was a differential analysis on Year 1 program, PeaceBuilders will be difficult to implement.” baseline to Time 2 data for all outcome variables. Because of our delayed Implementation and fidelity. In the spring of Year 2 (Time 4), teachers intervention model, Year 1 was the only period in which we had interven- completed an 8-item survey that assessed their use and implementation of tion schools compared with nonintervention schools. Our analytic proce- program materials. Some items assessed frequency of use, such as “I use dure followed the protocol developed by Stoolmiller et al. (2000) and the PeaceBuilders curriculum in my classroom” answered on a 5-point examined the extent to which intervention effectiveness depended on an scale including daily (1), occasionally (3), and not at all (5). Other items individual’s initial (baseline) status on an outcome of interest.
  • 31. SPECIAL ISSUE: VIOLENCE PREVENTION 299 Although we expected some gender differences between students at Level of Implementation and Fidelity baseline (e.g., boys being more aggressive, girls being more socially competent), we did not expect differences on outcomes between schools at A total of 190 teachers (98%) completed a spring 1996 (Time 4) baseline. In general, we expected the PBI and PBD schools to be signifi- self-assessment of their use of intervention materials in their cantly different at Time 2 (spring of Year 1) and perhaps at Time 3 (fall of classrooms. Teachers completing the survey were distributed Year 2) because PBD schools would have just begun their interventions. across all participating schools and grades and represented all We expected that the PBI and PBD schools might be significantly different participating teachers of Grades K–5 in each school. Teachers from each other at Time 4 (spring of Year 2), although we expected all scores at Time 4 to reflect improvement (e.g., in social competence) or were equally divided between immediate- and delayed- decline (e.g., in aggressive behavior) relative to baseline. intervention schools. The majority of teachers surveyed indicated that they used the PeaceBuilders curriculum in their classrooms on a daily (48%) or weekly (32%) basis. Nearly all teachers (98%) Results strongly agreed or agreed that “Overall, my school has imple- mented the PeaceBuilders curriculum,” 53% rated implementation Zero-Order Correlations Among Outcome Variables as “extensive,” and 43% rated implementation as “moderate.” Teachers were also consistent in their agreement that the interven- In preliminary analyses, we examined the zero-order correla- tion “has decreased the level of violence in our school” (94%) and, tions among outcome variables.1 The two main outcomes of in- conversely, that “PeaceBuilders has increased prosocial interac- terest, child social competence and aggression, were significantly tions in my class and in our school” (94%). Regarding the total related; teacher-rated aggression was negatively related to teacher- number of program materials used, teachers reported, on average, rated social competence, r(1613) .56, p .001, at baseline. that they used at least four of the eight core sets of materials in This relationship was largely unchanged over the four data collec- their classrooms. Teachers in the PBD schools reported, more than tion points, and the correlation ranged from .55 to .66. For did teachers in the PBI schools, that during Year 2 they were more children in Grades K–2, there were small to moderate relationships likely to use program materials daily (compared with weekly), at baseline between child self-reported prosocial behavior and 2 (4, N 190) 14.64, p .01. aggression, r(650) .03, ns; between aggression and peace- building behaviors, r(650) .08, p .05; and between proso- cial and peace-building behaviors, r(650) .25, p .001. For Attrition self-reports of children in Grades 3–5, the strongest relationship was between peace building and prosocial behavior, r(1879) We first calculated attrition within each intervention year (from .69, p .001. Relationships between aggressive behavior and baseline to Time 2 in Year 1 and from Time 3 to Time 4 in Year prosocial behavior, r(1886) .23, p .001, and between peace 2) and between Years 1 and 2 to determine rates of attrition and to building and aggressive behavior, r(1879) .13, p .001, were determine whether there was differential attrition by intervention not as strong. Teacher reports of aggression were related to child group. We also examined differences in outcomes between stu- self-reports of aggression at baseline, r(1316) .34, p .001, but dents with baseline-only data and those with baseline data plus at rather modestly given the large sample size. The correlations least one additional data point over the 2-year period. In a second between age and most outcome variables were statistically signif- set of analyses, we examined demographic characteristics related icant but weak, ranging from r(674) .01, ns for child self-reports to attrition between PBI and PBD schools. Finally, we examined of peace-building behavior to r(1878) .25, p .001 for child our two main outcomes of interest, teacher-rated social compe- self-reports of prosocial behavior in Grades 3–5. Correlations at tence and aggression, to determine whether children lost from the baseline between age and social competence and between age and sample after baseline were different from those children who aggression were significant but low, averaging .08 ( p .01). remained part of the sample. All attrition analyses on outcomes were conducted separately for the Grades K–2 and Grades 3–5 samples.2 Teacher Satisfaction With Training Within each intervention year, the average rate of attrition (fall data but no spring data) was 12% in Year 1 and 17% in Year 2. All regular and special education teachers in participating Between-years attrition was 32% for students in Grades K–2 (331 schools participated in the half-day workshops (n 194). Over of 1,037 students) and 28% for students in Grades 3–5 (231 of the 2 years of intervention, training questionnaires were gathered from a total of 134 teachers (69%), 57 of whom were from PBI 1 schools (43%) and the remainder of whom (n 77) were from These zero-order correlations do not take into consideration intragroup PBD schools. Overall, 93% of teachers indicated they “strongly correlation among students within classes and therefore serve only a agreed” or “agreed” that the basic philosophy behind the Peace- descriptive and exploratory purpose. 2 Builders intervention was easy to understand. Seventy-seven per- To corroborate our attrition analyses, we also conducted logistic re- cent agreed or strongly agreed that the training provided was clear, gressions with attrition status as the outcome variable. We ran regressions with grade, gender, intervention-group membership, Grades K–2 teacher- effective, and easy to follow, and 83% agreed or strongly agreed rated social competence and aggression, as well as Grades 3–5 teacher- that the ideas would be easy to use in the classroom. Three of four rated social competence and aggression as independent variables. The teachers who completed surveys believed that “PeaceBuilders will results of these regression analyses were consistent with the analysis of be very successful as an intervention” and strongly agreed or variance and chi-square results reported here. To control for possible agreed that “The school administration stands behind this inter- variation due to grade or gender, we also ran regressions controlling for vention effort 100 percent.” those variables, and the results remained the same.
  • 32. 300 FLANNERY ET AL. 814). We did not include new kindergarten students in Year 2, nor (as opposed to the delayed intervention, or PBD). Adding the error did we track Year 1 fifth-grade students into Year 2. For all term (u00j) to the intercept equation at the school level (Level 3) students assessed at baseline, 169 (10%) of 1,615 students (Grades takes into account the autocorrelation within schools—namely, the K–2) and 120 (9.5%) of 1,140 students (Grades 3–5) had no other nonindependence of students within a school. data over the 2-year period. In determining the specification of our model, we followed the Students in Grades K–2 with baseline-only data (those lost to recommendation of Snijder and Bosker (1999) by first testing the attrition) were rated by teachers at baseline as more aggressive, significance of random effects in our models. The models with F(1, 1612) 11.05, p .01, and less socially competent, F(1, significant random effects were then compared using Akaike’s 1611) 7.09, p .01, than were students who remained part of information criterion (AIC) and Schwarz’s Bayesian criterion the study sample. Students in Grades 3–5 with baseline-only data (SBC). These criteria measure whether specifying additional ran- were also rated by their teachers as more aggressive, F(1, dom effects improves fit if the models under comparison have the 1258) 14.70, p .01, and less socially competent, F(1, same structure of fixed effects. A larger value of AIC or SBC is an 1258) 13.60, p .01, than were students who remained part indication of better fit (Littell, Milliken, Stroup, & Wolfinger, of the study sample. Rates of attrition from baseline were not 1996; see also Guo & Hussey, 1999). The model with the random significantly different by gender, grade, or intervention-group specification above emerged most consistently as the model with membership for either children in Grades K–2, 2(1, N the largest likelihood function, and the best fit to the data, com- 1,615) 0.804, p .05, or children in Grades 3–5, 2(1, pared with all the other models that we explored.3 N 1,260) 0.389, p .05. The fixed effects presented in Tables 2 and 3 illustrate semester effects that reflect differences (not taking into account other fac- Behavior Outcomes tors such as intervention) on outcomes over time. Individual ef- fects reflect Level 2 gender differences at baseline, and the school HLM was our main analytic approach to examining school-level effects reflect differences between PBI and PBD schools at base- effects. We used a three-level hierarchical linear model, with the line. As shown in Tables 2 and 3, the random effects are statisti- first level representing change over time, the second level repre- cally significant, which indicates that specifying such extra hetero- senting individual student differences (gender), and the third level geneity to control for intragroup correlation is necessary. School representing differences between schools. The model examined effects reflect baseline differences in outcomes between PBI and differences between schools after controlling for baseline levels of PBD schools. The Level 3 effects are Semester School interac- behavior ( 0ij) and gender. The Level 1 model was specified as tion effects. These results show, after controlling for baseline (Level 1) and gender (Level 2), how immediate-intervention Y hij 0ij 1ij T2 2ij T3 3ij T4 ehij. schools compared with delayed-intervention schools on the out- The Level 2 model was specified as comes of interest at each subsequent point in time: spring of Year 1 (Time 2), fall of Year 2 (Time 3), and spring of Year 2 (Time 4). 0ij 00j 01j MALE r0ij To address the issue of floor effects in the aggression scales, we log-transformed aggression scale scores for both teacher and child 1ij 10j reports (Cohen & Cohen, 1983; cf. Stoolmiller et al., 2000). For r2ij example, at baseline, for Grades K–2 and Grades 3–5 teacher- 2ij 20j reported aggression, teachers identified 33% and 37% of the chil- 3ij 30j r3ij. dren, respectively, as not engaging in any aggressive behavior. At baseline, for Grades K–2 and Grades 3–5 child self-reported ag- The Level 3 model was specified as 00j 000 001 PBI u00j 3 To determine the best Level 2 random effects specification for our model, we ran all possible permutations of random effects for all 10 of the 01j 010 outcome variables. Following the recommendation of Snijder and Bosker (1999), we started by testing the significance of random effects in our 10j 100 101 PBI models. We found two models had significant random effects for most of PBI the outcome variables. Model A (the model we used) had significant 20j 200 201 random effects for nine of the outcome variables, and Model B (with only PBI. one random effect at Level 2 for the intercept) had significant random 30j 300 301 effects for all 10 of the outcome variables. To determine which model 0ij represents the intercept or baseline. T2 represents data provided a better fit to the data, we then compared the models using the collected in the spring of Year 1 (Time 2), T3 represents data AIC and the SBC. For example, for Grades K–2 teacher-rated competence, collected in the fall of Year 2 (Time 3), and T4 represents data for Model A, AIC 20,936 and SBC 20,943, and for Model B, collected in the spring of Year 2 (Time 4). The Level 1 error term, AIC 21,077 and SBC 21,072. Model A had consistently larger AIC and SBC values than Model B for all 10 outcome variables. Thus, ehij, is assumed to be normally distributed with a zero mean and a Model A emerged most consistently as the model with the largest likeli- constant variance. At Level 2, MALE is the dichotomous gender hood function, and the best fit to the data, compared with all the other variable equal to 1 if the child was a boy and 0 if the child was a models that we explored. However, for one of the outcome variables, girl. The Level 2 random effects r0ij, r2ij, and r3ij are assumed to be Grades K–2 child-reported peace-building behavior, we used Model B, normally distributed with a zero mean and a constant variance. The because two of the random effects at Level 2 for Model A were not variable PBI represents the PeaceBuilders immediate intervention significant.
  • 33. SPECIAL ISSUE: VIOLENCE PREVENTION 301 Table 2 Hierarchical Linear Modeling Results: Teacher Ratings of Child Social Competence and Aggressive Behaviors Coefficients (standard errors) Kindergarten–2nd grade 3rd–5th grade teacher ratings teacher ratings Social Log Social Log Fixed effects competence aggression competence aggression Semester effects Baseline 72.12*** (1.25) 1.49*** (.008) 73.28*** (0.94) 1.46*** (.007) Spring Year 1 2.52*** (0.51) 0.013** (.004) 1.39** (0.49) 0.020*** (.004) Fall Year 2 0.31 (0.75) 0.017** (.006) 0.08 (0.69) 0.005 (.005) Spring Year 2 2.24** (0.78) 0.011† (.006) 0.12 (0.66) 0.009† (.005) Individual effects Gender: boy (Reference: 7.12*** (0.57) 0.061*** (.005) 7.22*** (0.53) 0.070*** (.004) girl) School effects (baseline) PBI (Reference: PBD) 2.27 (1.77) 0.034* (.010) 0.94 (1.18) 0.006 (.010) Semester School interaction effects Spring Year 1 PBI 3.05*** (0.66) 0.006 (.005) 1.06† (0.62) 0.017** (.005) Fall Year 2 PBI 8.20*** (1.08) 0.014† (.008) 4.98*** (0.95) 0.026*** (.007) Spring Year 2 PBI 7.17*** (1.10) 0.009 (.008) 6.24*** (0.88) 0.019** (.007) Random effects variance Level 2, r0ij 157*** .011*** 162*** .012*** Level 2, r2ij 134*** .009*** 146*** .004*** Level 2, r3ij 138*** .008*** 84.6*** .004*** Level 3, u00j 4.66*** .000*** 1.71*** .000*** Note. PBI PeaceBuilders immediate-intervention schools; PBD PeaceBuilders delayed-intervention schools. † p .10. * p .05. ** p .01. *** p .001. Table 3 Hierarchical Linear Modeling Results: Child Self-Report of Aggressive, Prosocial, and PeaceBuilding Behaviors Coefficients (standard errors) Kindergarten–2nd grade self-report 3rd–5th grade self-report Fixed effects Log aggression Prosocial PeaceBuilding Log aggression Prosocial PeaceBuilding Semester effects Baseline 0.27*** (.01) 5.71*** (.05) 3.43*** (.06) 1.00*** (.01) 33.60*** (.58) 5.50*** (.13) Spring Year 1 0.01 (.01) 0.05 (.05) 0.01 (.06) 0.01 (.00) 0.18 (.30) 0.32*** (.07) Fall Year 2 0.01 ( .02) 0.05 (.06) 0.23** (.07) 0.01** (.00) 1.10** (.35) 0.71*** (.09) Spring Year 2 0.03† ( .02) 0.02 (.06) 0.17* (.10) 0.000 (.01) 1.00** (.37) 0.40*** (.09) Individual effects Gender: boy (Reference: girl) 0.09*** (.01) 0.11** (.03) 0.11** (.04) 0.06*** (.00) 4.00*** (.26) 0.63*** (.06) School effects (baseline) PBI (Reference: PBD) 0.02 (.02) 0.02 (.06) 0.03 (.07) 0.02 (.01) 1.40 (.78) 0.03 (.17) Semester School interaction effects Spring Year 1 PBI 0.02 (.02) 0.10 (.07) 0.19* (.08) 0.003 (.01) 0.77* (.39) 0.71*** (.10) Fall Year 2 PBI 0.02 (.03) 0.19* (.09) 0.02 (.09) 0.001 (.01) 0.38 (.47) 0.36** (.12) Spring Year 2 PBI 0.01 (.03) 0.19* (.08) 0.01 (.10) 0.001 (.01) 1.1* (.50) 0.11 (.12) Random effects variance Level 2, r0ij .021*** .108*** .158*** .007*** 36.0*** 1.58*** Level 2, r2ij .012*** .120* NA .002*** 14.4*** 1.20*** Level 2, r3ij .011*** .087** NA .005*** 24.6*** 1.72*** Level 3, u00ij .000 .002* .002* .000*** .947*** .044*** Note. PBI PeaceBuilders immediate-intervention schools; PBD PeaceBuilders delayed-intervention schools; NA not applicable. † p .10. * p .05. ** p .01. *** p .001.
  • 34. 302 FLANNERY ET AL. gression, 31% and 44% of the students, respectively, reported not School interaction effects. For example, a significant Time 2 engaging in any aggressive behavior. School interaction would indicate that, with baseline and gender Baseline effects. With only one exception, students in PBI and differences controlled, the PBI schools were significantly different PBD schools were not significantly different from each other at from the PBD schools at Time 2. These effects are illustrated for baseline (see school effects for baseline in Tables 2 and 3). significant outcomes in Figure 3 (teacher data) and Figure 4 (child Teachers rated students in Grades K-2 in the PBI schools as self-report data). slightly lower in aggressive behavior overall than students in the Time 2. At Time 2 (spring of Year 1), compared with students PBD schools (see Table 2). in PBD schools, teachers rated students in PBI schools as signif- As expected, there were several gender differences at baseline. icantly higher in social competence (for Grades K–2; effects were Teachers rated boys as significantly lower in social competence marginal for students in Grades 3–5, p .10) and significantly and higher in aggressive behavior than girls at baseline. This effect lower in log aggression (for Grades 3–5; see Table 2 for coeffi- was consistent for both students in Grades K–2 and students in cients). Compared with students in PBD schools, students in PBI Grades 3–5 (see Table 2). Child self-reports of gender differences schools reported significantly greater peace-building behavior (for at baseline showed that among students in Grades K–2 and Grades both Grades K–2 and Grades 3–5; see Table 3 for coefficients) but 3–5, boys rated themselves as significantly more aggressive, less self-reported less prosocial behavior (Grades 3–5). prosocial, and lower in peace-building behavior than did girls (see Time 3. At Time 3 (fall of Year 2), compared with students in Table 3). PBD schools, teachers rated students in Grades K–2 and Grades Intervention effects. Given the unique design of our evalua- 3–5 in PBI schools as significantly higher in social competence tion, in which the PBI schools received the intervention during and significantly lower on log aggression, although the effects Year 1 and Year 2 but the comparison PBD schools received the were stronger for students in Grades 3–5 ( p .001) than for those intervention only during Year 2, our hierarchical linear model in Grades K–2 ( p .10; see Table 2). Compared with students in outlined above enabled us to examine the effects of the interven- PBD schools, students in PBI schools reported significantly greater tion at each data collection point (Time 2, Time 3, and Time 4) peace-building behavior (Grades 3–5) and prosocial behavior relative to baseline by examining the cross-level Semester (Grades K–2; see Table 3 for coefficients). Figure 3. Means for teacher-reported social competence and aggression for PeaceBuilders immediate- intervention and PeaceBuilders delayed-intervention schools at baseline, Time 2, Time 3, and Time 4.
  • 35. SPECIAL ISSUE: VIOLENCE PREVENTION 303 Figure 4. Means for child self-reported peace-building and prosocial behavior for PeaceBuilders immediate- intervention and PeaceBuilders delayed-intervention schools at baseline, Time 2, Time 3, and Time 4. Time 4. At Time 4 (spring of Year 2), compared with students teacher-rated dependent variables, we found significantly different in PBD schools, teachers rated the students in PBI schools as slopes for Grades 3–5 log aggression, t(1174) 3.84, p .001. significantly higher in social competence (Grades K–2 and Grades For child self-reported dependent variables, we found significantly 3–5) and lower on log aggression (Grades 3–5 students only; see different slopes for Grades K–2 peace-building behavior, t(649) Table 2 for coefficients). Compared with students in PBD schools, 2.46, p .05; Grades K–2 prosocial behavior, t(649) 2.48, students in PBI schools reported significantly greater prosocial p .05; Grades 3–5 prosocial behavior, t(1494) 1.97, p .05; behavior in Grades K–2 but lower prosocial behavior in Grades and Grades 3–5 aggression, t(1494) 14.19, p .001. There were 3–5 (see Table 3). no differential effects for social competence, Grades K–2 teacher- Differential effects. We conducted a series of linear regres- reported or child self-reported aggression, or Grades 3–5 child sions to examine the potential for differential effectiveness of the self-reported peace-building behavior. intervention—namely, that treatment effects would vary depend- We can illustrate the difference on aggression by mapping the ing on an individual student’s initial status on an outcome at effect sizes for aggression scores at four points: 1, 0 (mean), 1, baseline. We conducted differential analyses only for Year 1 data and 2 SDs above the mean for the baseline sample. The mean (from baseline to Time 2) because this was the only year in which we had intervention (PBI) and nonintervention (PBD) comparison difference is computed by plugging the preintervention score into groups. We conducted differential analyses on all main outcomes the fitted equation for both groups and then subtracting the pre- of interest. dicted intervention mean from the predicted control mean (Stool- Following the protocol developed by Stoolmiller et al. (2000), miller et al., 2000). The obtained effect sizes for teacher-reported we conducted a linear regression of Time 2 (spring of Year 1) Grades 3–5 log aggression were .00, .26, .52, and .78, respectively, scores on baseline scores. We were interested in whether the and those for child self-reported Grades 3–5 log aggression were regression slopes would significantly differ. If the slopes are not .17, .08, .02, and .12, respectively. Thus, the effect size (i.e., parallel, this is evidence that treatment effects vary according to treatment effect) was larger for students with higher aggression initial status (or that the treatment is differentially effective). For scores at baseline.
  • 36. 304 FLANNERY ET AL. For peace-building and prosocial behavior, we can illustrate the linear model that accounted for school-level differences and vari- effect sizes at four points: 2, 1, 0 (mean), and 1 SD above the ability in individual student change over time. mean, because we would expect children lower at baseline to From a policy perspective, it is important that early preventive increase their positive behavior after intervention. The obtained intervention focus on increasing positive skills and competencies effect sizes were .48, .27, .07 and .13, respectively, for Grades as well as reducing aggressive and other problem behaviors. These K–2 child self-reported peace-building behavior. Similarly, for skills lay the groundwork for success in school, positive adult– Grades K–2 prosocial behavior, the obtained effect sizes were .57, child and peer relations, and long-term child adjustment and resil- .38, .18, and .01, respectively. For Grades 3–5 child self-reported iency. Interventions should contain strategies specifically designed prosocial behavior, the obtained effect sizes were .27, .16, .05, and to accomplish both of these behavioral goals in order to increase .06, respectively. The effect size was larger for students with the chances of sustained behavior change over time (Mayer, But- lower baseline peace-building and prosocial behavior scores, sug- terworth, Nafpaktitis, & Sulzer-Azaroff, 1983; Tolan et al., 1995; gesting a bigger treatment effect for increases in positive behavior Tremblay et al., 1995). Developmentally, children who display for students who were lower at baseline. aggressive and socially incompetent behavior at school are also at high risk for rejection by their normative peer group. This in- creases their risk of associating with other deviant or rejected Discussion peers, which in turn increases their risk of subsequent delinquency and other conduct problems (CPPRG, 1999; Reid et al., 1999). This study examined the initial behavior outcomes of Peace- The fact that we found effects for students both in Grades K–2 Builders, a universal school-based preventive intervention pro- and Grades 3–5 also underscores the importance of providing gram focused on reducing aggressive behavior and increasing preventive intervention services early in elementary school. The social competence. We examined behavior change over 1 school majority of school-based violence prevention programs are in year in which half of our randomly assigned schools received middle schools (e.g., Farrell & Meyer, 1997; Orpinas, Parcel, immediate intervention and half received no intervention. We also McAlister, & Frankowski, 1995) or high schools (Howard et al., examined change in Year 2, when the immediate-intervention 1999), but there is ample evidence that intervening earlier in schools continued treatment and the control schools received in- elementary school can have greater effects on both educational tervention for the first time. In general, we found consistent outcomes and risk behaviors than can waiting to intervene later behavior effects in Year 1, with students in Grades K–2 in the (CPPRG, 1999; Dolan et al., 1993; Kellam & Anthony, 1998; immediate-intervention schools being rated significantly higher by Tremblay et al., 1995) and that early and continued intervention in teachers on social competence than control students (moderate the elementary grades can help put children on a positive devel- effects were obtained for students in Grades 3–5). Third- to fifth- opmental course that is maintained through high school (Hawkins grade students in the immediate-intervention schools were also et al., 1999). rated by teachers as significantly less aggressive than students in This study also reinforces the need to consider the potential nonintervention schools. As expected, students in the immediate- differential effects of preventive intervention trials (Stoolmiller et intervention condition also rated themselves higher on peace- al., 2000). Although we found some significant effects for all building behaviors (Grades K–5) than control students. These children exposed to the intervention, which is important for uni- behavior changes occurred in intervention schools during Year 1, versal prevention efforts (compared with targeted interventions when no significant change in behavior was observed in noninter- that focus on high-risk youth), we also found larger treatment vention schools. effects for youth in Grades 3–5 who were higher on aggression at Effects for increases in social competence and declines in baseline. We found these differential effects for both teacher- teacher-reported aggressive behavior were maintained for all stu- reported and child self-reported aggression. We did not, however, dents in Grades K–5 in immediate-intervention schools in the fall see differential effects for the aggressive behavior of younger of Year 2. Higher levels of peace building (Grades 3–5) and children (Grades K–2) even though teacher-rated aggression of prosocial behavior (Grades K–2) were also maintained at Time 3 children in Grades K–2 was the only significant school-level and at Time 4 (Grades K–2 for prosocial). At Time 4 (spring of difference at baseline. We did find differential effects for child Year 2), students from immediate-intervention schools were still self-reported prosocial behavior despite finding significant de- rated higher on social competence, higher on prosocial behavior clines overall in prosocial behavior for children in Grades 3–5. (Grades K–2), and lower on aggression (Grades 3–5) relative to Children who were the least prosocial at baseline improved the students in delayed-intervention schools. Our overall findings are most after 1 year of intervention. In general, effect sizes were in consistent with previous studies that have demonstrated the effi- the moderate range (.27–.78) for the children at highest risk at cacy of elementary-school-based universal prevention programs baseline, defined here as 2 SD above the sample mean. Effects for increasing social competence and reducing aggressive behavior for children closer to the sample mean at baseline were not as (CPPRG, 1999; Grossman et al., 1997; Kellam, Ling, et al., 1998; dramatic. As Battistich and colleagues (Battistich, Schaps, Reid et al., 1999). The one trend that ran counter to expectations Watson, Solomon, & Lewis, 2000) and others (Stoolmiller et al., was for older students’ (Grades 3–5) prosocial behavior. At both 2000; Vazsonyi et al., 1999) have pointed out, however, few Time 2 and Time 4, students in the immediate-intervention schools children in early elementary school have begun to show serious rated themselves as less prosocial than students in the delayed- conduct problems. We adjusted for low base rates of aggression in intervention schools. In general, however, we found consistent our models and still found significant effects for aggressive be- intervention effects for social competence and aggression. These havior. Even small early differences may lead to large preventive effects were realized using a conservative three-level hierarchical effects as children mature, a position that is consistent with models
  • 37. SPECIAL ISSUE: VIOLENCE PREVENTION 305 of the developmental progression of conduct problems and violent mented, it was maintained over time with no prespecified end point behavior (CPPRG, 1999; Reid et al., 1999; Tolan et al., 1995). to the intervention. Third, PeaceBuilders focused on universal Although a specific focus on variations in the fidelity of treat- prevention with children beginning in kindergarten. Persistent ment implementation is beyond the scope of this article, we pro- behavioral change is more likely to occur when children are vide some evidence (a) that the program was implemented as younger, the behavior is more malleable, and the intervention is designed and was provided by teachers with reasonable intensity, maintained over time (Tolan et al., 1995). (b) that teachers were satisfied with their training and program Conducting program evaluation on a large number of students in materials, and (c) that students seemed to acquire the skills that predominantly urban, mobile school populations presents many were emphasized as part of the school-based program (e.g., peace- empirical and practical challenges not easily overcome. Attrition building behavior). First, over 90% of teachers who responded to can have an adverse impact on behavioral outcomes, especially if surveys indicated that the philosophy behind the program was easy longitudinal samples are not large enough to provide adequate to understand, and over 80% believed the ideas would be easy to power to detect treatment effects over a long period of time. use in the classroom. It is extremely important that teachers un- Attrition in our sample was not negligible, although our rates are derstand the reason they are implementing a particular curriculum comparable to those of other studies conducted with higher risk, or activity and the intended impact of the intervention. If the frequently mobile students and families (Hansen, Tobler, & Gra- materials are difficult to implement, few teachers will take the time ham, 1990). or effort to adapt them. There exist too many demands on already Large-scale intervention studies also face attrition by teachers or busy teachers for them to implement complicated programs that attrition at the school level, with schools sometimes dropping out they do not understand or support. It is imperative that psycholo- of a project. This may occur because of changes in administrators, gists continue to evaluate the implementation and effectiveness of changes in school district policy, reductions in resources, changing scientifically based, easy-to-implement, and cost-effective preven- academic demands (e.g., proficiency testing), or changes in teacher tion programs. Few violence prevention programs systematically staff to the point that there no longer exists a majority who are focus on the importance of staff training or on assessing the willing to participate in training, to complete data collection in- fidelity of program implementation (Flannery & Seaman, 2001). struments, or to implement a program (e.g., CPPRG, 1999; Reid et Another indicator of program implementation was the survey al., 1999). Although we had no schools drop out of our study in the that teachers completed at the end of the 2nd year of intervention, first 2 years, we did have one control school delay data collection when all teachers surveyed had been trained and had been imple- until the spring of the 1st year. There is a need to balance the gains menting the curriculum for at least 1 school year. Nearly all from doing large-scale preventive interventions with the limita- teachers in project schools completed the surveys, and 8 of 10 tions in research design and method that occur when attempting to reported that they used materials in their classrooms on a regular bridge science and practice (Flannery & Huff, 1999). basis. In some ways, observed changes in peace-building behavior Limits also exist on the extent to which one can control a child’s also acted as a validity check that the program was being imple- exposure to other school and community programs or events that mented as intended. There was also strong consensus that the may influence the outcome behavior being examined. We took program had been integrated at the school level. In fact, by the end several steps to limit the cohort’s degree of exposure to the of the 2nd year, both participating school districts had formally adopted the program as part of their regular curriculum. intervention. For example, PBD schools agreed not to implement For two of our outcomes of interest, peace-building behavior the PeaceBuilders program during the 1st year, and we removed and prosocial behavior, the data suggest a potential “summer from our sample children in the PBI condition in Year 2 who were effect” in that students in the delayed-intervention schools self- not also present in Year 1. reported a significant increase in behavior at Time 3 (fall of Year Methodologically, there exist significant challenges to doing 2) relative to baseline. At least two factors may explain these large-scale preventive intervention work. Every school we ap- “spikes,” which were not realized for aggression or social compe- proached about participating in the project expressed a high need tence. First, most teachers in the PBD schools received training for immediate intervention and was uneasy about the prospect of immediately at the beginning of the school year (given their even a 1-year nonintervention period. Despite our strategy of interest in implementation). Teacher and student survey data were offering monetary incentives to schools to remain in a 1-year gathered about 1 month into the fall semester, so most students in control condition, it was difficult to withhold interventions from the PBD condition had at least some initial exposure to the inter- schools that had a need for immediate help. Matters were further vention. Second, peace-building and prosocial behaviors are the complicated when we not only wanted to withhold intervention but most intervention-specific behaviors we assessed, so an increase in also requested detailed survey data from teachers and students. child self-reports may reflect a response to initial intervention This influenced our design over the course of the multiyear lon- exposure. gitudinal study because of the absence of an ongoing noninterven- Several important characteristics, particularly those related to tion control or comparison group. the likelihood of observing systematic behavior change, separate Another methodological challenge is presented by the increased PeaceBuilders from other school-based violence prevention pro- emphasis on school-level (i.e., climate or culture changing) pre- grams. First, the focus of PeaceBuilders was to alter the entire ventive interventions. Programs limited to a few schools may school climate, not just individual risk factors. Second, Peace- compromise their chances of finding significant effects on behav- Builders was implemented in the immediate-intervention schools ior because of problems of limited sample size (e.g., the unit of for a longer period than is the case for most other time- or analysis is the school rather than the individual child; see Battistich curriculum-limited prevention programs, and once it was imple- et al., 2000; Stoolmiller et al., 2000) and because individual
  • 38. 306 FLANNERY ET AL. students in a school are not independent of each other with regard Embry, D. D., & Flannery, D. J. (1999). Two sides of the coin: Multilevel to the potential effects of a universal prevention program. prevention and intervention to reduce youth violent behavior. In D. Despite the limitations inherent in applied evaluation research, Flannery & C. R. Huff (Eds.), Youth violence: Prevention, intervention this project also had many strengths. The sample was large and and social policy (pp. 47–72). Washington, DC: American Psychiatric ethnically diverse and included a significant number of Hispanic Press. and Native American children, two groups rarely sampled in Embry, D. D., Flannery, D. J., Vazsonyi, A. T., Powell, K. E., & Atha, H. (1996). PeaceBuilders: A theoretically driven, school-based model for longitudinal studies of violence prevention programs. The children early violence prevention. American Journal of Preventive Medicine, were younger and covered a broader age range than the children Supplement to 12(5), 91–100. found in many other previous longitudinal evaluations (e.g., Gross- Englander-Golden, P., Jackson, J., Crane, K., Schwarzkopf, A., & Lyle, P. man et al., 1997; but see CPPRG, 1999), and the schools were (1989). Communication skills and self-esteem in prevention of destruc- from both urban and nonurban districts. Although our focus here tive behavior. Adolescence, 14, 481–501. was on the first 2 years of exposure to the intervention, we have Eron, L., & Huesmann, R. (1990). The stability of aggressive behavior— continued to gather outcome data from the children as they mature even unto the third generation. In M. Lewis & S. Miller (Eds.), Hand- through middle school (Grades 6 – 8), over a 5-year period. As- book of developmental psychopathology (pp. 147–156). New York: sessing outcomes such as aggression, delinquent and violent be- Plenum Press. havior, and violence exposure/victimization as a function of years Fagan, J., & Wilkinson, D. (1997). Firearms and youth violence. In D. of exposure to intervention may yield more information about the Stoff, J. Breiling, & J. Maser (Eds.), Handbook of antisocial behavior effects of age of first exposure, developmental trajectories for (pp. 551–566). New York: Wiley. subgroups of children (e.g., high-aggressive youth with low social Farrell, A., & Meyer, A. (1997). The effectiveness of a school-based competence vs. high-aggressive youth with high social compe- curriculum for reducing violence among urban sixth-grade students. American Journal of Public Health, 87, 979 –984. tence), or differences in program effectiveness related to child Flannery, D. J. (1997). School violence: Risk, preventive interventions, and gender or history of exposure to violence (Flannery, 2000). policy. New York: Columbia University and ERIC Clearinghouse on In sum, this evaluation of a universal preventive intervention Urban Education. program for children in Grades K–5 showed significant improve- Flannery, D. J. (2000, August). Longitudinal effectiveness of the Peace- ments in child social competence and peace-building behavior, as Builders universal school-based violence prevention program. Paper well as reductions in aggressive behavior, after 1 year of interven- presented at the 108th Annual Convention of the American Psycholog- tion relative to students in nonintervention schools. These effects ical Association, Washington, DC. were largely maintained in a 2nd year of intervention. It is also Flannery, D., & Huff, C. R. (Eds.). (1999). Youth violence: Prevention, important to examine the differential effects of treatment on ag- intervention and social policy. 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  • 39. SPECIAL ISSUE: VIOLENCE PREVENTION 307 Hawkins, J. D. (1995). Controlling crime before it happens: Risk-focused Risk factors and successful interventions for serious and violent juvenile prevention. National Institute of Justice Journal, 229, 10 –18. offenders. Studies on Crime and Crime Prevention, 7, 7–30. Hawkins, J. D., Catalano, R. F., Kosterman, R., Abbott, R., & Hill, K. G. Mayer, G. R., Butterworth, T., Nafpaktitis, M., & Sulzer-Azaroff, B. (1999). Preventing adolescent health-risk behavior by strengthening (1983). Preventing school vandalism and improving discipline: A three protection during childhood. Archives of Pediatric Adolescent Medicine, year study. Applied Behavior Analysis, 16, 355–369. 153, 226 –234. Mayer, G. R., & Sulzer-Azaroff, B. (1990). Interventions for vandalism. In Hawkins, J. D., Herrenkohl, T., Farrington, D., Brewer, D., Catalano, R., G. Stoner, M. R. Shinn, & H. M. Walker (Eds.), Interventions for Harachi, T., & Cothern, L. (2000, April). 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  • 40. 308 FLANNERY ET AL. Snijder, T., & Bosker, R. (1999). Multilevel analysis: An introduction to competent? Psychiatry: Journal for the Study of Interpersonal Pro- basic and advanced multilevel modeling. Thousand Oaks, CA: Sage. cesses, 54, 148 –161. Snyder, H. N. (2000). Special analyses of FBI serious violent crimes data. Tremblay, R. E., Pagani-Kurtz, L., Masse, L. C., Vitaro, F., & Pihl, R. O. Pittsburgh, PA: National Center for Juvenile Justice. (1995). A bimodal preventive intervention for disruptive kindergarten Snyder, H. N., & Sickmund, M. (1999). Juvenile offenders and victims: boys: Its impact through mid-adolescence. Journal of Consulting and 1999 national report. Washington, DC: U. S. Department of Justice, Clinical Psychology, 63, 560 –568. Office of Justice Programs, Office of Juvenile Justice and Delinquency U. S. Department of Health and Human Services. (2001). Youth violence: Prevention. A report of the Surgeon General (Report prepared by the U.S. Depart- Stokes, T. F., & Baer, D. M. (1977). An implicit technology of general- ment of Health and Human Services for the Office of the Surgeon ization. Applied Behavior Analysis, 12, 285–310. General in partnership with the Centers for Disease Control, National Stoolmiller, M., Eddy, J. M., & Reid, J. (2000). Detecting and describing Center for Injury Prevention and Control; the National Institutes of preventive intervention effects in a universal school-based randomized Health, National Institute of Mental Health; and the Substance Abuse trial targeting delinquent and violent behavior. Journal of Consulting and Mental Health Services Administration, Center for Mental Health Services). Rockville, MD: U. S. Public Health Service, Office of the and Clinical Psychology, 68, 296 –306. Surgeon General. Thornton, T. N., Craft, C. A., Dahlberg, L. L., Lynch, B. S., & Baer, K. Vazsonyi, A. T., Vesterdal, W. J., Flannery, D. J., & Belliston, L. (1999). (2000). Best practices of youth violence prevention: A sourcebook for The utility of child self reports and teacher ratings in classifying official community action. Atlanta, GA: Centers for Disease Control and Pre- delinquency status. Studies on Crime and Crime Prevention, 8(2), 225– vention, National Center for Injury Prevention and Control. 244. Tolan, P. H., & Gorman-Smith, D. (1998). Development of serious and Walker, H. M., Colvin, G., & Ramsey, E. (1995). Anti-social behavior in violent offending careers. In R. Loeber & D. Farrington (Eds.), Serious schools: Strategies and best practices. Pacific Grove, CA: Brooks/Cole. and violent juvenile offenders: Risk factors and successful interventions Walker, H. M., Irvin, L., Noell, J., & Singer, G. (1992). A construct score (pp. 68 – 85). Thousand Oaks, CA: Sage. approach to the assessment of social competence. Behavior Modifica- Tolan, P. H., & Guerra, N. G. (1994). What works in reducing adolescent tion, 16, 448 – 474. violence: An empirical review of the field. Boulder, CO: Center for the Walker, H. M., & McConnell, S. R. (1995). The Walker-McConnell Scale Study and Prevention of Violence. of Social Competence and School Adjustment (SSCSA). Florence, Ken- Tolan, P. H., Guerra, N. G., & Kendall, P. C. (1995). A developmental tucky: Thomson Learning. perspective on antisocial behavior in children and adolescents: Toward Webster, D. W. (1993). The unconvincing case for school-based conflict a unified risk and intervention framework. Journal of Consulting and resolution programs for adolescents. Health Affairs, 12, 126 –141. Clinical Psychology, 63, 579 –584. Weissberg, R. P., & Bell, D. N. (1997). A meta-analytic review of primary Tremblay, R., Masse, B., Perron, D., LeBlanc, M., Schwartzman, A., & prevention programs for children and adolescents: Contributions and Ledingham, J. (1992). Early disruptive behavior, poor school achieve- caveats. American Journal of Community Psychology, 25, 207–214. ment, delinquent behavior, and delinquent personality: Longitudinal analyses. Journal of Consulting and Clinical Psychology, 60, 64 –72. Received November 7, 2000 Tremblay, R., McCord, J., Boileau, H., Charlebois, P., Gagnon, C., Le- Revision received April 22, 2002 blanc, M. & Larivee, S. (1991). Can disruptive boys be helped to become ´ Accepted May 3, 2002
  • 41. Dr. Embry salutes these people and organizations Dr. Embry honors these people and organizations in in Salinas who have made the success possible of Tucson and nationally who have made the success his first generation work: possible of his first generation work: The children, teachers & families of Salinas The children, staff and families of Tucson Unified School Allan Styles, the former mayor Districts Anna Cabrillio, current mayor Dr. Daniel Flannery, Kent State University, Kent, Ohio The late Dr. Oscar Loya, superintendent of Alisal Unified Dr. Alex Vazsonyi, Dept. of Psychology, Auburn University School District Dr. Ken Powell, formerly the science officer for the National Patricia Skelton, Healthy Start Director, Salinas City Unified Center for Injury Prevention, Centers for Disease Control Lupe Garcia, Partners for Peace City Coordinator Barbara LaWall, The Pima County Attorney Rev. Ken Feske, Partners for Peace, education coordinator The Tucson Police Department & The Pima County Sheriff Bob Rice, former general manager, KSBW-Channel 8 Department Elizabeth Murdoch, former owner, KSBW-Channel 8 Dr. Kris Boswoth, Smith Endowed Professor, College of Education, University of Arizona Diana Jacobsen, Monterey Public Health Department Dr. Linda Dahlberg, Jennifer Friday, Dr. Tom Simon, Jim Mercy, Bill Deeb, former principal of Alisal Community School Dr. Mark Rosenberg, the National Center for Injury Prevention, Jorge Rifa, Assistant City Manager Centers for Disease Control Dan Nelson, Chief of Police Jeff Sales & Mindy Blake, KOLD TV Channel 13, Tucson "Sarge" Ernie Williams, Juvenile Hall The Arizona Daily Star and the Tucson Citizen Salinas Valley Community Hospital Captain Danny Sharp, Tucson Police Department Natividad County Hospital Tom Rose, Hawaii, Hawaii The Californian Dr. David Satcher, Surgeon General of the United States Laurie Singer, mentor teacher Dr. George Comerci, past president of the American Academy of Dena Ruiz Eastwood, former KSBW anchor Pediatrics And many others who have lived the peace builders pledge. The scores of students and volunteers who collect data on one of the largest studies in the US on youth violence Inland Agency, Riverside, CA

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