Peer Influence and Selection Mechanisms Underlying Adolescent Problem Behaviors

描述(由申请人提供)：众所周知，在青春期和成年期，与不正常的同龄人交往会增加使用药物、反社会行为和危险的性行为的风险。我们的目标是开发模型，预测暴露在给定青少年同伴社会环境中的此类问题的风险，并建议家长、学校和社区可用的实际预防措施。为了实现这一雄心勃勃但至关重要的预防目标，需要更多地了解同伴影响和选择如何以及何时发生。这个项目将检验理论和先前的研究表明，在14-17岁的青少年中，可能促进或抑制同龄人群体对药物使用、反社会行为和危险性行为的影响的机制。假说在很大程度上借鉴了社会学习理论，其基本前提是青少年饮酒、吸毒和其他不当行为在很大程度上是因为由此产生的社会回报。这个项目试图跟踪和模拟与这些经常相关的问题行为类别相关联的社会奖励偶发事件的影响。利用基于学校的纵向社交网络、生态瞬时评估(EMA)和调查方法的独特组合，我们试图从编程的iPod设备上的随机EMA中实时报告研究参与者的实际同伴动态的性质。测量包括情绪、对同伴受欢迎程度的感知、同伴受害、活动和父母因素(监控、规则制定和亲子关系)。这些主持人将从网络数据中了解社会关系的情景，并使用RSiena分析软件中实现的基于随机参与者的建模框架进行建模。该项目将直接促进NIDA的使命，即减少开始吸毒和酗酒(通常发生在青春期)和滥用/成瘾，以及伴随着可能使青少年接触艾滋病毒和其他严重健康危害的药物滥用生活方式的危险性行为。它还将有助于 基于社交网络的同辈关系和问题行为模型。

DESCRIPTION (provided by applicant): Affiliation with deviant peers is known to increase the risk of substance use, antisocial behavior, and risky sexual practices during adolescence and into adulthood. We aim to develop models that forecast the risk of such problems from exposure to a given adolescent peer social environment, and suggest practical preventative measures available to parents, schools, and communities. To achieve this ambitious but vital prevention goal, much more needs to be known about how and when peer influence and selection occur. This project will examine mechanisms that theory and prior research suggest may promote or inhibit peer group influence for substance use, antisocial behavior, and risky sex among adolescents age 14-17. Hypotheses draw heavily upon social learning theory, with the fundamental premise that adolescents who use alcohol and drugs and otherwise misbehave do so largely because of the resulting social rewards. This project seeks to track and model the effects of the social reward contingencies associated with these often-related classes of problem behaviors. Using a unique combination of school-based longitudinal social network, Ecological Momentary Assessment (EMA), and survey methodologies, we seek to identify the nature of study participants' actual peer dynamics, as reported in real time, from random EMAs on programmed iPod devices. Measures include mood, perceptions of peer popularity, peer victimization, activities, and parent factors (monitoring, rule setting, and parent-child relationship). These moderators will contextualize social relationships known from network data, and are modeled using the stochastic actor-based modeling framework as implemented in the RSiena analysis software. The project will directly contribute to NIDA's mission to reduce initiation of drug and alcohol use (which normally occurs during adolescence) and abuse/addiction, as well as the risky sexual practices accompanying a substance-abusing lifestyle that can expose youth to HIV and other serious health hazards. It will also contribute to social-network-based models of peer affiliations and problem behavior.