Predicting the Trajectory of Absence-Drinking Dyads

描述(由申请人提供)：本申请建议对接受治疗的酗酒者的结果进行二次分析。它将使用Project Match的数据，这是一项大规模的多地点酒精中毒治疗临床试验，于1996年完成，以测试几个模型，用于分析戒酒模式和饮酒行为随时间的变化。配对数据包含每个参与者自接受治疗起455天期间的每日消耗量的回顾自我报告。这些数据(N=1726)将解决与识别被定义为禁酒/饮酒二元组的行为有关的研究目标，其中二元组是指1天或更多天不饮酒(禁酒)和1天或更多天饮酒的序列。同时，有可能将参与者在随后的一段时间内的戒酒/饮酒模式识别为治疗后的行为轨迹。因为可以假设治疗后的饮酒行为轨迹之间会有相似之处(持续禁欲是一种常见的可能性)，所以尝试确定这些轨迹的同质分组是合理的。随后，可以使用客户特征和环境因素(例如，治疗条件)来尝试区分分组轨迹的类别。一般的假设是，这种方法将更好地理解一个人随着时间的推移改变既定饮酒模式的情况，并更好地理解替代治疗策略的相对影响。这项应用提供了一种将酒精中毒治疗结果概念化的创新方法。目前普遍采用的方法将酒精中毒治疗的结果处理为二元事件(禁酒)或使用频率指标(例如戒酒天数百分比)或强度指标(例如饮酒日饮酒)。这两种结果方法都没有认识到并代表了从旧行为(如饮酒)向新行为(如禁欲)转变过程中的尝试和错误。Match数据提供了一个开发模型的机会，这些模型可以更好地代表在临床试验中可以观察到的东西，以及长期结果跟踪阶段，多次戒酒尝试。最重要的是，可以以最低成本实现这些目标。

DESCRIPTION (provided by applicant): The application proposes a secondary analysis of outcome from treated alcoholics. It will use data from Project MATCH, a large-scale multi-site clinical trial of treatments for alcoholism completed in 1996, to test several models for analyzing patterns of abstinence and drinking behaviors over time. The MATCH data contains for each participant retrospective self-reports of daily consumption over a period of 455 days from treatment entry. This data (N=1726) will address research aims concerned with the identification of behaviors defined as abstinence/drinking dyads, where a dyad is the sequence of 1 or more days of not drinking (abstinence) and 1 or more days of drinking. Concurrently, it will be possible to identify a participant's pattern of abstinence/drinking dyads over the follow-up period as post-treatment behavior trajectories. Because it is feasible to suppose that there will be similarities among the post-treatment drinking behavior trajectories (continual abstinence is 1 common possibility), it is reasonable to attempt to identify homogeneous groupings of these trajectories. Subsequently, client characteristics and environmental factors (e.g. treatment conditions) can be employed in the attempt to discriminate between the classes of grouped trajectories. The general hypothesis is that this method will yield a better understanding of a person's change in established patterns of drinking over time and result in a better understanding of the relative impact of alternative treatment strategies. The application presents an innovative way of conceptualizing alcoholism treatment outcome. Methods commonly employed currently treat outcome from alcoholism treatment as either a binary event (abstinent-drinking) or use indicators of frequency (e.g. percent (%) days abstinent) or intensity (e.g. drinks on a drinking day) averaged over the follow-up period. Both of these approaches to outcome fail to recognize and represent the trial and error involved in the transition from an old behavior (e.g. drinking) to a new behavior (e.g. abstinence). The MATCH data provides an opportunity to develop models that better represent what is observable in clinical trials with long-term outcome follow-up phases, multiple attempts at abstinence. Most importantly these objectives can be achieved at minimum cost.