Peer Influence and Selection Mechanisms Underlying Adolescent Problem Behaviors

描述（由申请人提供）：众所周知，与越轨的同龄人交往会增加青春期和成年期的物质使用、反社会行为和危险性行为的风险。我们的目标是开发模型，预测这些问题的风险，从接触到一个给定的青少年同龄人的社会环境，并提出切实可行的预防措施，家长，学校和社区。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。这个项目将研究理论和先前的研究表明，可能会促进或抑制同龄人群体的影响，物质使用，反社会行为，和危险的性行为，在14-17岁的青少年的机制。这些假说大量借鉴了社会学习理论，其基本前提是，青少年酗酒、吸毒或其他行为不端的行为主要是因为由此产生的社会奖励。该项目旨在跟踪和模拟与这些经常相关的问题行为类别相关的社会奖励突发事件的影响。使用一个独特的组合，以学校为基础的纵向社会网络，生态瞬时评估（EMA），和调查方法，我们试图确定研究参与者的实际同行动态的性质，报告在真实的时间，从随机EMA编程的iPod设备。措施包括情绪，同伴受欢迎的看法，同伴受害，活动，和父母的因素（监测，规则设置，和亲子关系）。这些主持人将从网络数据中已知的社会关系的上下文，并使用随机演员为基础的建模框架中实现的RSiena分析软件进行建模。该项目将直接促进国家药物开发署的使命，即减少开始吸毒和酗酒（通常发生在青春期）和滥用/成瘾，以及伴随药物滥用生活方式的危险性行为，这些行为可能使青年人感染艾滋病毒和其他严重的健康危害。它还将协助 基于社交网络的同伴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.