Secondary Analysis of Substance Use In Men

最近有充分证据表明，高危人群中艾滋病毒新感染率的上升与 俱乐部毒品的流行，如MDMA、氯胺酮、GHB和甲基苯丙胺。这项研究 寻求通过系统地探索药物滥用的流行病学来进一步了解这些联系 在感染艾滋病毒的高危男性中。该应用程序将对现有数据进行广泛的分析 从伊利诺伊州芝加哥获得的三种不同概率样本收集的集合：主要比较 分析的重点是1996-1997年调查的男性样本和#年调查的额外样本 2002-2003年；其他比较将使用作为一般人口一部分的接受调查的男性样本 2001-2002年药物使用情况调查。利用平行的工具和措施跨越两个 芝加哥的样本，详细的分析也将比较和探索物质使用报告的有效性 如高危男性和非高危男性之间的药物使用/滥用的相对流行率。由一名 “认知逃避”的自负框架，这一应用提供了独特的、及时的、高性价比的 有机会了解物质使用流行模式和趋势随时间的变化 冒险家。多变量模型将系统地检验药物使用和危险行为之间的联系； 将比较随时间变化的关联性(跨不同数据集)。为了更好地理解这些 联系，我们将探索其他统计方法，以组合和衡量调查答复 关于高风险行为的问题/包括单参数项目反应理论(Rasch Scaling)和 协方差结构计量模型(使用LISREL和Mplus)。反过来，这些扩展方法， 将用于改进和修订统计模型。这项申请将对公众产生重大影响 政策，进一步阐明药物滥用在艾滋病毒传播中的因果作用，从而有助于指导未来 艾滋病毒预防和干预工作。

Recent well-documented increases in the rate of new HIV infections in high risk populations coincide with the spreading popularity of club drugs such as MDMA, ketamine, GHB, & methamphetamine. This research seeks to further understand these linkages by systematically exploring the epidemiology of substance abuse among men at high risk for HIV infection. This application will conduct extensive analyses of existing data sets collected on three different probability samples obtained from Chicago, Illinois: The maincomparative analyses focus on a sample of men surveyed in 1996-1997 and an additional sample of men surveyed in 2002-2003; additional comparisons will employ a sample of men surveyed as a part of a general population study of drug use in 2001-2002. Taking advantage of parallel instruments and measures across two Chicago-based samples, detailed analyses will compare and explore substance use reporting validity as well as the relative prevalence of substance use/abuse between high-risk and non-high-risk men. Guided by a "cognitive escape" conceputal framework, this application provides a unique, timely, and cost-effective opportunity for understanding shifts in substance use prevalence patterns and trends over time among high- risk men. Multivariate models will systematically examine associations between drug use and risk behavior; associations over time (across different data sets) will be compared'. In order to better understand these linkages, we will explore alternative statistical approaches for combining and scaling survey responses to questions about high risk behavior/including single parameter item response theory (Rasch Scaling) and covariance structure measurement models (using LISREL and MPLUS). These scaling approaches, in turn, will be used to refine and revise statistical models. This application will have a significant impact on public policy by further articulating the causal role of drug abuse in the spread of HIV, thus helping to guide future HIV prevention and intervention efforts.