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This paper uses an ecological perspective to explore the risk factors associated with bullying behaviors among a representative sample of adolescents aged 11-14 (n = 9816; X = 12.88; s = .9814). Data derived from the Health Behavior in School Children: WHO Cross-National Survey were used to model the relationship between bullying and media effects, peer and family support systems, self-efficacy, and school environment. Overall, the results of this study suggest that bullying increases among children who watch television frequently, lack teacher support, have themselves been bullied, attend schools with unfavorable environments, have emotional support from their peers, and have teachers and parents who do not place high expectations on their school performance. In addition, we found an inverse relationship between being Asian or African American, feeling left out of school activities and bullying. Our results lend support to the contention that bullying arises out of deficits in social climate, but that social support systems mediate bullying behavior irrespective of the student's racial/ethnic characteristics, parental income levels or media influences. Because the number of friends and the ability to talk to these friends increases the likelihood of bullying, we suggest that bullying is not simply an individual response to a particular environment but is a peer-group behavior. We conclude that limiting television viewing hours, improving student's abilities to access family support systems and improving school atmospheres are potentially useful interventions to limit bullying behavior.

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CrimeStat III is a spatial statistics program for the analysis of crime incident locations. The program has three main components: (1) the Spatial Description component allows the user to conduct analyses regarding spatial distribution of data, (2) the Spatial Modeling component allows the user to analyze the spatial behavior of data, and (3) the Crime Travel Demand Modeling component allows the user to analyze the behavior of potential serial offenders. Overall, CrimeStat III is fairly easy to use once an initial familiarity has been established with the software. This can be accomplished through the manual or the intuitive GUI. Currently, the only significant restriction to the utility of the software is its reliance on the Windows operating system. This review provides a discussion of technical utilization of the software, and a look at how this software is useful in a practical manner for the spatial data analysis of crime.