Predicting the Trajectory of Absence-Drinking Dyads

描述（由申请人提供）：该申请提出了对接受治疗的酗酒者结果的二次分析。它将使用MATCH项目的数据，该项目是1996年完成的一项大规模的多地点酒精中毒治疗临床试验，它将测试几种模型，以分析长期戒酒和饮酒行为的模式。MATCH数据包含每个参与者从治疗开始的455天内每日消费的回顾性自我报告。该数据（N=1726）将解决与确定被定义为戒酒/饮酒双元组的行为有关的研究目标，其中双元组是1天或更多天不饮酒（戒酒）和1天或更多天饮酒的序列。同时，在治疗后的行为轨迹中，将有可能确定参与者在随访期间的戒酒/饮酒模式。因为假设治疗后饮酒行为轨迹之间存在相似之处是可行的（持续戒酒是一种常见的可能性），因此尝试识别这些轨迹的同质分组是合理的。随后，病人的特征和环境因素（如治疗条件）可以用来区分分组轨迹的类别。一般的假设是，这种方法将更好地了解一个人在既定的饮酒模式中随着时间的推移而发生的变化，并更好地了解替代治疗策略的相对影响。该应用程序提出了一种概念化酒精中毒治疗结果的创新方法。目前通常采用的方法将酒精中毒治疗的结果作为二元事件（戒酒）或使用频率指标（例如百分比（%）戒酒日）或强度指标（例如饮酒日的饮酒量）在随访期间的平均。这两种方法都没有认识到，也没有表现出从一种旧行为（如饮酒）到一种新行为（如戒酒）转变过程中所经历的试错过程。MATCH数据提供了一个开发模型的机会，该模型可以更好地代表长期结果随访阶段的临床试验中观察到的情况，多次尝试禁欲。最重要的是，这些目标可以以最小的成本实现。

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.