Emerging Issues in Analyzing Group-Based Treatment Data under Open Enrollment

描述（由申请人提供）：毫无疑问，大多数用于治疗酒精滥用和依赖的社会心理干预措施都是以团体治疗的形式提供的。在许多情况下，治疗小组是通过公开登记或“滚动”入院来维持和补充的，即患者在不同时间进入正在进行的治疗小组，而其他成员则离开（由于毕业或辍学）。随着时间的推移，治疗组成员在疗程之间的变化过程（通常以非随机的方式发生）给研究者带来了独特的分析挑战，他们希望解释和理解开放入组治疗组所产生的依赖性，并在这种情况下对治疗效果进行适当的建模。在分析酒精治疗试验数据时，处理分组成员变化的困难被认为是许多研究者回避公开登记数据分析挑战的主要原因之一。为了避免这些困难，研究人员(a)忽略了滚动治疗组产生的依赖性（导致有偏的参数估计和/或标准误差），(b)设计了以个体为基础的干预措施（而不是群体）为中心的研究，或(c)设计了在一定时期后限制入组的研究（即“封闭”组）。这三种方法的主要成本是对治疗效果的不正确推断（即类型I和/或类型II错误）（在条件[a]下），以及如何进行治疗效果试验与如何在社区环境中进行治疗之间的脱节（在条件[b]和[c]下）。

DESCRIPTION (provided by applicant): There is little question that most psychosocial interventions used to treat alcohol abuse and dependence are delivered in a group therapy format. In many settings, therapy groups are sustained and replenished using open enrollment, or "rolling" admission, whereby patients enter ongoing therapy groups at various times, while other members leave (due to graduation or dropout). This process of session-to-session change in therapy group membership over time (usually occurring in a nonrandom fashion) creates unique analytic challenges for investigators who wish to account for and understand the dependencies created by open enrollment into therapy groups and for the proper modeling of treatment effects in this context. Difficulties in handling session-to-session changes in group membership in the analysis of alcohol treatment trial data have been cited as one of the major reasons that many investigators avoid the analytic challenges of open enrollment data. To avoid these difficulties, investigators have (a) ignored dependencies created by rolling treatment groups (leading to biased parameter estimation and/or standard errors), (b) designed studies that center on individual-based interventions (as opposed to groups), or (c) designed studies that restrict enrollment after a certain period (i.e., "closed" groups). The major costs of each of these three approaches are incorrect inferences concerning treatment effects (i.e., Type I and/or Type II errors) (under condition [a]) and a disconnect between how treatment efficacy trials are conducted and how treatment takes place in community settings (under conditions [b] and [c]). In the face of many of these analytic and design challenges, further development and dissemination of approaches to handle open enrollment data in the context of alcohol treatment trials (i.e., multiple membership models, pattern mixture models) are sorely needed. The purpose of this exploratory- developmental R21 project is to explore the utility of analytic frameworks that may serve as the foundation for handling open enrollment data for three specific design and/or analytic problems: (a) incorporation into common alcohol treatment trial designs, (b) modeling of mechanisms of treatment action in trials with open enrollment, and (c) statistical power analysis for various group-based alcohol treatment designs (e.g., group-based tx A versus group-based tx B, group tx versus individual tx) under open enrollment. This exploratory/developmental grant application will use a combination of statistical simulation modeling and data from an ongoing alcohol treatment trial with the ultimate goal of providing alcohol treatment researchers with clear pedagogical examples on how to analyze such data and providing guidelines for sample size estimation specifically for open enrollment trial designs.