Secondary Analysis of Substance Use In Men

最近有充分记录的高风险人群中艾滋病毒新感染率的增加与 俱乐部毒品的普及，如摇头丸，氯胺酮，GHB，和甲基苯丙胺。本研究 通过系统地探索药物滥用的流行病学， 艾滋病毒感染高风险的男性。该应用程序将对现有数据进行广泛的分析 从伊利诺斯州芝加哥收集的三个不同概率样本集： 分析的重点是1996-1997年调查的男子抽样和1998 - 1999年调查的男子抽样。 2002-2003年;其他比较将采用作为一般人口一部分的被调查男子的抽样 2001-2002年药物使用情况研究。利用跨两个区域的并行工具和措施 芝加哥为基础的样本，详细的分析将比较和探索物质使用报告的有效性，以及 高风险和非高风险男性之间药物使用/滥用的相对流行率。遵循一 “认知逃避”概念框架，这个应用程序提供了一个独特的，及时的，和成本效益 有机会了解吸毒高发人群中吸毒流行率模式和趋势随时间的变化， 冒险的男人多变量模型将系统地研究药物使用和危险行为之间的联系; 随着时间的推移（跨不同数据集）的关联将被比较“。为了更好地理解这些 联系，我们将探索其他统计方法，以合并和调整调查答复， 关于高风险行为的问题/包括单参数项目反应理论（Rasch量表）和 协方差结构测量模型（使用LISREL和MPLUS）。反过来，这些缩放方法， 将用于改进和修订统计模型。这一应用将对公众产生重大影响。 通过进一步阐明药物滥用在艾滋病毒传播中的因果作用， 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.