Methods to Compare Mechanisms of Action in Substance Use Programs

描述(由申请人提供)：这一R03小额拨款机制，由一位新的NIH首席调查员提交，将解决物质使用干预数据调解分析中的重要空白。指导程序开发的行为理论已经变得越来越复杂，导致了针对多个机制或被认为与使用有因果关系的介体的干预。中介分析有助于探索这些物质使用的途径以及干预措施在改变这些发展轨迹中的作用。关于调解的假设也变得更加复杂，现在经常包括调解效果如何相互比较的问题。这些中介效应的对比是项目评估的一个日益重要的方面，因为它们允许研究人员了解几种治疗或治疗成分的相对有效性。中介效应的比较可以帮助研究人员更有效地针对最显著的行为改变机制定制干预计划。在资源日益减少的情况下，这些信息对于制定具有成本效益的干预措施至关重要。不幸的是，在实践中，这些比较一直基于无效的度量标准，如所讨论的影响的绝对大小或其t得分。这种对不恰当方法的依赖可能会掩盖真正导致大多数行为变化的过程。同样，对特定于群体的中介效应的粗略比较可能表明，一个群体不会从某个组成部分中受益，这一结论可以通过更严格的统计检验来支持或驳斥。这项研究将为应用物质使用研究人员提供必要的工具，通过解决两个具体目标来适当地进行中介效果的比较。首先是一项广泛的模拟研究，它将检查所有五种已知对比测试(Wald、百分位数和偏差校正的自举、基于似然的置信度区间和虚拟潜变量测试)的统计特性。这些测试的统计特性(例如，功率、I类错误率)要么未知，要么不清楚，因此该信息将提供关于应当使用这些不同测试的情况(例如，假设类型、数据结构)的指导。模拟结果将为这项研究的第二部分提供信息：对来自两个多组分药物使用预防计划的现有预防数据全面应用对比方法。这两个方案都代表了许多预防设计，具有多个调解人和结果以及纵向自我报告数据收集等特点。这些特点，加上之前在两个数据集上的显著中介发现，使它们非常适合于如何制定和测试中介效果对比的教学演示。 与公共卫生相关：这项研究将增加公共卫生研究人员可用的工具，因为他们试图发现和改变物质使用的发生机制。对这些机制的比较，也称为中介效应，对于确定治疗和预防计划如何实现其效果以及基于性别和年龄等因素在不同群体之间的计划有效性差异非常重要。这项研究的结果将确定进行这些比较的最佳方法，并提供具体的教学实例，供应用物质使用的研究人员用来进行自己的评估。

DESCRIPTION (provided by applicant): This R03 small grant mechanism, submitted by a new NIH Principal Investigator, will address important gaps in mediation analysis of substance use intervention data. Behavioral theories guiding program development have become increasingly complex, resulting in interventions targeting multiple mechanisms, or mediators that are believed to be causally related to use. Mediation analysis has been instrumental in exploring these pathways to substance use and the role of interventions in altering these developmental trajectories. Hypotheses about mediation have also increased in complexity and now often include questions about how mediated effects compare to one another. These contrasts of mediated effects are an increasingly important aspect of program evaluation, as they allow researchers to understand the comparative effectiveness of several treatments or treatment components. Comparisons of mediated effects can help researchers more efficiently tailor intervention programs to the most salient mechanisms of behavior change. Such information is critical for developing cost-effective interventions in the face of decreasing availability of resources. Unfortunately, in practice these comparisons have been based on invalid metrics such as the absolute size of the effects in question or their t scores. Such reliance on improper methods can obscure the processes that truly account for the majority of behavior change. Similarly, crude comparisons of group-specific mediated effects may suggest that one group would not benefit from a component, a conclusion that could be supported or refuted by more stringent statistical examination. This study will provide applied substance use researchers with the tools needed to properly conduct comparisons of mediated effects by addressing two specific aims. First is an extensive simulation study that will examine the statistical properties of all five known contrast tests (Wald, percentile and bias-corrected bootstrap, likelihood-based confidence intervals, and a dummy latent variable test). The statistical properties (e.g., power, Type I error rate) of these tests are either unknown or unclear, so this information will provide guidance about the situations (e.g., types of hypotheses, data structures) in which these various tests should be employed. The simulation results will then inform the second component of this study: a thorough application of contrast methods to existing prevention data from two multicomponent substance use prevention programs. Both programs are representative of many prevention designs, with features such as multiple mediators and outcomes and longitudinal self-reported data collection. These features, together with previous findings of significant mediation in both data sets, make them well suited to a pedagogical demonstration of how to formulate and test mediated effect contrasts. PUBLIC HEALTH RELEVANCE: This study will increase the tools available to public health researchers as they attempt to uncover and change the mechanisms by which substance use occurs. Comparisons of these mechanisms, also called mediated effects, are important for determining how treatment and prevention programs achieve their effects and how program efficacy differs across groups based on factors such as gender and age. The results of this study will identify the best methods for making these comparisons and provide concrete pedagogical examples that applied substance use researchers can use to benefit their own evaluations.