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Irene Pintado1, Karen Liller, PhD1, Kelli McCormack Brown, PhD, FASHA2, Karen M. Perrin, PhD, MPH, RN3, Robert J. McDermott, PhD1, and Getachew A. Dagne, PhD4. (1) Community and Family Health, University of South Florida College of Public Health, 13201 Bruce B. Downs Blvd., Tampa, FL 33612, 813-974-6685, ipintado@hsc.usf.edu, (2) College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd., MDC 56, Tampa, FL 33612-3805, (3) Dept. of Community and Family Health, University of South Florida, College of Public Health, 13201 Bruce B. Downs Blvd. MDC-56, Tampa, FL 33612, (4) Epidemiology and Biostatistics, University of South Florida College of Public Health, 13201 Bruce B. Downs Blvd, MDC 56, Tampa, FL 33612
Bullying has been identified as a problem that affects the physical and psychosocial health of aggressors and victims. Given the consequences for the bullies, victims, and the school environment, early intervention is important to minimize these risks. This study seeks to meet this need by analyzing the association of bullying behaviors and school climate perceptions of middle school students within the context of school and grade membership. A useful framework for understanding bullying is Bronfenbrenner’s ecological system theory. Within this framework, a bullying interaction occurs not only because of individual characteristics of the child who is bullying, but also because of actions of peers, teachers and staff; physical characteristics of the school environment; and student perceptions of these contextual factors. This study uses survey data to analyze the contextual effect of school and grade membership on student perceptions of school climate and bullying behaviors in five Sarasota County middle schools. Data sources include student-, school-, and grade-level data. Researchers gathered student- level data from a modified middle school YRBS survey the Sarasota School District administered to students, in December 2003. The school- and grade- level data were gathered from a questionnaire completed by a school administrator. Data will be analyzed within multilevel models, using SAS software. Multilevel approaches allow for analyzing non-independent data, such as data from students in grades, in schools. This method takes into account sources of non-independence as sources of variance, and thus accounts for the similarity inherent in clustering among individuals attending the same school.
Learning Objectives:
Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.