Meta-Analysis of Family-Based Prevention Programs for Adolescent Substance Abuse

描述（由申请人提供）：物质的使用（即，烟草、酒精、大麻和可卡因、吸入剂等“硬性毒品”）对青少年的健康和幸福有严重影响。研究一直将基于家庭的因素，如父母的监督和父母与青少年的关系与青少年药物使用的开始和升级联系在一起，并且已经制定了许多基于家庭的预防方案，通过解决家庭系统内的根本问题来减少青少年药物使用。虽然这些方案被广泛认为是成功的，但在文献中有几个潜在的弱点。首先，总结该领域研究结果的研究通常基于传统的文献综述，这些文献综述基本上是主观的，因此无法提供经验的、客观的、可量化的项目有效性评估，同时控制可能影响结果的因素，如样本特征、研究设计、参与率和测量工具。其次，缺乏研究，调查为什么以家庭为基础的预防方案取得了成功，许多作者在该领域呼吁对这些方案的各个组成部分及其叠加或协同效应进行更多的研究。第三，最近的研究质疑，以家庭为基础的因素是否在整个青春期产生类似的影响（例如，父母的监督可能是对青少年早期而不是后期使用药物的更有效的威慑）。因此，这个R 03项目的第一个目标是使用元分析技术来评估青少年物质使用的家庭预防计划，以确定哪些计划组件与减少物质使用和/或改善养育子女的成功最密切相关。具体来说，我们将使用程序设计，课程和交付方法来预测父母和青少年行为的措施的影响大小。第二个目的是评估是否以家庭为基础的青少年物质使用预防计划的组成部分表现出相加或协同效应。具体来说，我们将研究单个成分是否预测结果的唯一方差（即，累加效应）或它们是否表现出彼此的显著相互作用（即，协同效应）。目的是评估各种样品（即，青年年龄和性别）和研究因素（例如，研究设计，自然减员）缓和项目组成部分和结果之间的联系（例如，父母监督方面的培训可能与减少药物使用有关，但在青春期早期更为明显）。R 03项目将带来许多好处。首先，荟萃分析使我们能够联合收割机结合研究结果，产生更大的统计功效，并获得受任何特定研究固有偏见影响较小的结果。第二，我们的项目将提供一个更好的了解这些计划是如何工作的，并将告知未来的预防工作，针对青少年物质使用。最后，我们的项目将确定最有利的平衡组件为给定的人口和情况，从而使设计师能够优化程序设计。

DESCRIPTION (provided by applicant): Use of substances (i.e., tobacco, alcohol, marijuana, and "hard drugs" such as cocaine, inhalants, etc.) has serious implications for adolescent health and well-being. Research has consistently linked family-based factors such as parental monitoring and parent-youth relationships with the initiation and escalation of substance use in adolescence, and numerous family-based prevention programs have been developed to reduce adolescent substance use by addressing the underlying issues within the family system. Although these programs are widely seen as successful, there are several underlying weaknesses in the literature. First, the research that summarizes the findings from the field has often been based upon conventional narrative reviews of the literature, which are essentially subjective and thus cannot provide an empirical, objective, quantifiable evaluation of program effectiveness while controlling for factors that can influence outcomes, such as sample characteristics, study design, rate of engagement, and measurement tools. Second, there is a lack of research that investigates exactly why family-based prevention programs have been successful, and numerous authors in the field have called for more research on the individual components of these programs and their additive or synergistic effects. Third, recent research has questioned whether family-based factors exert similar effects across the entirety of adolescence (e.g., parental monitoring may be a more effective deterrent of substance use in early rather than late adolescence). Thus, the first aim of this R03 project is to use meta-analyti techniques to evaluate family-based prevention programs for adolescent substance use to determine which program components are most strongly linked to success in reducing substance use and/or improving parenting. Specifically, we will use program design, curricula, and delivery methods to predict effect sizes on measures of parenting and adolescent behavior. The second aim is to evaluate whether components of family-based prevention programs for adolescent substance use exhibit additive or synergistic effects. Specifically, we will examine whether individual components predict unique variance in outcomes (i.e., additive effects) or whether they exhibit significant interactions with one another (i.e., synergistic effects). The thid aim is to evaluate the degree to which various sample (i.e., youth age and gender) and study factors (e.g., research design, attrition) moderate the link between program components and outcomes (e.g., training in parental monitoring may be associated with reduced substance use, but more strongly in early adolescence). This R03 project will provide many benefits. First, meta-analysis allows us to combine findings across studies, generate greater statistical power, and obtain results less affected by biases inherent in any given study. Second, our project will provide a stronger understanding of how these programs work and will inform future prevention efforts targeting adolescent substance use. Finally, our project will identify the most favorable balance of components for given populations and circumstances and thus enable designers to optimize program design.