An Integrative Approach to Control Group Creation for Prevention Research

 描述(由申请人提供)：该SBIR项目的目标是开发一种创建算法生成的控制组的方法。这些病例将由具有两个特征的合成病例组成：(1)测试前与任何预防治疗组可能出现的相似之处；(2)随时间的变化模式，密切模拟酒精和药物使用发展的正常过程。酒精和毒品预防领域是一个非常成熟的领域，拥有丰富的数据资源，可以为此目的而使用。值得注意的是，许多学校和社区的疗效研究在随机对照试验中使用了对照组。其他病因学和流行病学研究也收集了类似的数据。考虑到可供分析的大量数据，现在可以对青少年饮酒和吸毒的开始进行建模。我们建议从以前的研究中收集数据，并开发可以用来预测酒精和药物使用开始的统计模型。将开发一种算法，该算法将创建与治疗组的人口统计学相匹配的综合对照病例，并预先测试中介变量得分，然后估计未来的药物使用。这种方法的几个好处是可以预期的。酒精和毒品预防研究人员和从业人员将能够使用这一方法来测试传播干预措施的有效性，并快速评估新的和替代预防干预措施的潜力。具体地说，这种方法将提供一种手段来评估酒精和毒品预防计划的有效性，这些计划在不能随机化的情况下传播。这种方法还将通过减少招聘、学科保留、现场数据收集和前测不对等的挑战，使评估新的和调整后的项目变得更容易，这些挑战在L课堂、学校和社区被分配到条件时经常发生。

 DESCRIPTION (provided by applicant): The goal of this SBIR project is to develop a method for creating algorithmically generated control groups. These will be composed of synthetic cases that have two characteristics: (1) pretest similarity to whatever prevention treatment group may present itself and (2) patterns of change over time that closely mimic the normal course of alcohol and drug use development. The field of alcohol and drug prevention is one that has significantly matured and has rich data resources that can be employed to this end. Notably, numerous school and community efficacy studies have employed control groups in randomized control trials. Additional etiological and epidemiological studies have collected similar data. Given the large amount of data available for analysis, it is now possible to model the onset of alcohol and drug use among adolescents. We propose to gather data from previous studies and develop statistical models that can be used to predict the onset of alcohol and drug use. An algorithm will be developed that will create integrative control cases to match to a treatment group's demographics and pretest mediating variable scores and then estimate future drug use. Several benefits of this method are anticipated. Alcohol and drug prevention researchers and practitioners will be able to use this approach to test the effectiveness of disseminated interventions and to quickly evaluate the potential of new and alternative prevention interventions. Specifically, this method will provide a means to evaluate the effectiveness of alcohol and drug prevention programs that are disseminated when randomization cannot occur. This method will also make evaluating new and adapted programs easier by reducing the challenges of recruitment, subject retention, and onsite data collection and pretest non-equivalence that often occur when l classrooms, schools and communities are assigned to condition.