Feasibility of a Social Network Preventive Intervention

描述（由申请人提供）：在这个项目中，我们将开发一种创新的干预措施，以防止滥用药物和其他不健康的行为。有风险的学生有两个很容易识别和学校相关的特征——他们对学校没有强烈的依恋感，他们没有积极的朋友。这些特征也与其他风险和保护因素密切相关。先前的研究表明，聚集高危青少年只会增加他们的风险和越轨行为。我们提出了一种策略，将有风险的学生分配到低风险的群体中，以最大限度地提高他们与亲社会同伴发展友谊的潜力。我们将开发一种社会网络干预策略，将有风险的学生插入到学生的小群体中，增加他们获得积极社会接受的机会。在这个R34项目中，我们将：1。完善社会网络调查，评估学生的同年级朋友网络，与学校的联系，兴趣和价值观。2. 开发计算机应用程序，使我们能够测试一种识别有风险学生的方法。3. 开发计算机应用程序，使我们能够测试创建低风险群体的替代方法。（至少要考虑四种——聚类最亲密的朋友，使用纽曼-格文算法分组，弱链接聚类和高中心播种。）4. 开发计算机应用程序，使我们能够测试将有风险的学生纳入低风险群体的替代方法。（至少有两项需要考虑-匹配小组分数和匹配个人分数。）5. 收集学生的考前数据。6. 测试每一个选择，以确定有风险的学生，创建低风险组，并插入有风险

DESCRIPTION (provided by applicant): In this project we will develop an innovative intervention for preventing drug abuse and other unhealthy behaviors. At-risk students share two readily identifiable and school-relevant characteristics - they do not have a strong sense of attachment to school and they do not have positive friends. These characteristics are also strongly related to other risk and protective factors. Previous research demonstrates that congregating high-risk youth only increases their risk and deviance. We propose a strategy that will distribute at-risk students among low-risk groups in a way that maximizes the potential for them to develop friendships with prosocial peers. We will develop a social network intervention strategy that inserts at-risk students into small groups of students increasing their chances of positive social acceptance. In this R34 project we will: 1. Refine a social network survey that will assess students' network of within-grade friends, bonding to school, interests, and values. 2. Develop computer applications that will allow us to test a method for identifying at-risk students. 3. Develop computer applications that will allow us to test alternative methods for creating low-risk groups. (At least four are to be considered - Clustering Nearest Friends, Grouping using the Newman-Girvan algorithm, Weak-Link Clustering, and High-Centrality Seeding.) 4. Develop computer applications that will allow us to test alternative methods for inserting at-risk students into low-risk groups. (At least two are to be considered - Matching Group Scores and Matching Individual Scores.) 5. Collect pretest data from students. 6. Test each alternative for identifying at-risk students, creating low-risk groups, and inserting at- risk students into low-risk groups, comparing the effects of each in order to identify optimal methods for constructing social network intervention groups. 7. Conduct a pilot study of the intervention. We will provide one group of schools with intervention group lists and encourage them to convene groups as often as possible to provide opportunities for social interaction. A second group of schools will serve as delayed-treatment controls. 8. Posttest students and assess the relative effectiveness of the intervention for creating positive friendships among at-risk students and improving their bonding to school. Students in eight middle schools will complete surveys in the spring of two consecutive school years. Data collected during the first year will be used to test at-risk student identification, low-risk group formation, and at-risk student insertion algorithms. Four middle schools will adopt the team assignment intervention during the following school year. Students in all eight middle schools will again be surveyed at the end of the second year. We hypothesize that at-risk students in intervention schools will have more friends, will report increased bonding to school, and will have better attendance, less truancy, less school misbehavior, and improved academic performance compared to at-risk students in control schools. If successful, this intervention will be tested for efficacy of preventing drug use in subsequent randomized control research trials. PUBLIC HEALTH RELEVANCE: Drug abuse continues to be a challenging public health and social issue. Effective, cost- beneficial prevention programs that can be widely disseminated offer significant potential to reduce drug abuse throughout the United States.