Hierarchical Modeling of Alcohol Treatment Outcomes of Group Therapy

描述（由申请人提供）：团体治疗是酒精或药物（AOD）障碍的一种中心治疗方式。客户往往被接纳为治疗小组根据滚动招生的基础上，使新成员进入该集团，而其他人离开。如果不能适当调整这种相关性，可能会导致治疗效果的统计检验有偏差，从而阻碍使AOD组治疗更有效的努力。滚动组的AOD治疗创新应通过改善客户端交互的复杂动态知识来指导。尽管滚动组在标准临床实践中无处不在，但研究人员在正确分析这些数据方面几乎没有指导。该项目的主要创新之处在于，我们为会议参与对成果的贡献开发了一个明确的模型。我们的模型利用会话之间的相似性，例如它们在时间上彼此接近以及参与客户端的重叠程度。我们这样做是通过使用统计技术开发的模型数据是相关的，由于采样单位的地理位置。我们利用测量地理位置之间的距离和测量会话的接近度之间的概念相似性。这些空间统计技术提供了一套丰富而强大的工具来模拟滚动组中客户结果之间的相关性。我们的分层（多层次）模型捕捉会话级的影响，并允许它们相互关联。该项目提供了一个独特的机会，将AOD治疗研究与最先进的统计建模相结合，为滚动治疗组数据开发适当的分析技术。具体目标是：1）开发一个分层建模框架，以估计滚动组入院对治疗结果的影响，该框架结合了最初为空间数据分析开发的方法; 2）扩展该建模框架，以测试客户结果是否随滚动治疗会话特征而变化，并确定哪些会话级别特征导致改善的客户结果; 3）开发和推广用于研究设计、样本量确定和滚动组研究分析的分析工具。 公共卫生相关性：这项拟议的研究项目与公共卫生有关，因为其最终目标是改善酒精和其他药物（AOD）障碍的群体治疗。受普遍存在的治疗AOD障碍的团体治疗的动机，该项目开发了一种统计方法，可用于测试AOD团体治疗在各种现实环境中的有效性。

DESCRIPTION (provided by applicant): Group therapy is a central treatment modality for alcohol or drug (AOD) disorders. Clients are often admitted to therapy groups under a rolling admissions basis, so that new members enter the group while others leave. Failure to properly adjust for this correlation could lead to biased statistical tests of treatment effects, thus impeding efforts to make AOD group therapy more effective. AOD treatment innovations for rolling groups should be guided by improved knowledge of the complex dynamics of client interactions. Despite the ubiquity of rolling groups in standard clinical practice, there is very little guidance available to researchers regarding proper analysis of these data. The key innovation of this project is that we develop an explicit model for the contribution of session participation on outcomes. Our model exploits similarities between sessions, such as their proximity to each other in time and the degree of overlap in participating clients. We do so by using statistical techniques developed to model data that are related due to geographic locations of sampled units. We take advantage of the conceptual similarity between measuring distance between geographic locations and measuring the closeness of sessions. These spatial statistical techniques provide a rich & powerful set of tools to model correlations among client outcomes in rolling groups. Our hierarchical (multilevel) models capture session-level effects and allow them to be correlated. This project provides a unique opportunity to integrate AOD treatment research with state-of-the-art statistical modeling to develop appropriate analytic techniques for rolling therapy group data. Specific Aims are to: 1) develop a hierarchical modeling framework to estimate the impact of rolling group admissions on treatment outcomes that incorporates methods initially developed for spatial data analysis; 2) extend this modeling framework to test whether client outcomes vary with rolling therapy session features and to identify which session-level features lead to improved client outcomes; 3) develop and disseminate analytic tools for study design, sample size determination, and analysis for rolling group studies. PUBLIC HEALTH RELEVANCE: This proposed research project is relevant to public health because its ultimate goal is to improve group-based treatments of alcohol and other drug (AOD) disorders. Motivated by the ubiquity of group therapy for treating AOD disorders, this project develops a statistical approach that can be used to test the effectiveness of AOD group therapies in a variety of realistic settings.