Peer Influence and Selection Mechanisms Underlying Adolescent Problem Behaviors

描述（由申请人提供）：众所周知，与不正常的同龄人交往会增加青少年和成年期药物使用、反社会行为和危险性行为的风险。我们的目标是建立模型，预测暴露在特定的青少年同伴社会环境中出现此类问题的风险，并为家长、学校和社区提出切实可行的预防措施。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是如何以及何时发生的。本项目将考察理论和先前研究表明的机制，这些机制可能会促进或抑制14-17岁青少年对药物使用、反社会行为和危险性行为的同伴群体影响。这些假设很大程度上借鉴了社会学习理论，其基本前提是，使用酒精和毒品以及其他不良行为的青少年之所以这样做，主要是因为由此产生的社会奖励。这个项目试图追踪和模拟与这些经常相关的问题行为相关的社会奖励偶然性的影响。利用基于学校的纵向社会网络、生态瞬时评估（EMA）和调查方法的独特组合，我们试图确定研究参与者的实际同伴动态的性质，从编程iPod设备上的随机EMA实时报告。测量包括情绪、同伴受欢迎程度的感知、同伴受害、活动和父母因素（监控、规则设置和亲子关系）。这些审核员将从网络数据中了解社会关系，并使用RSiena分析软件中实现的基于随机行为者的建模框架进行建模。该项目将直接有助于国家药物开发协会的使命，即减少开始吸毒和酗酒（通常发生在青春期）和滥用/成瘾，以及伴随滥用药物的生活方式而发生的可能使青年感染艾滋病毒和其他严重健康危害的危险性行为。它也将有助于

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.