Predicting the Trajectory of Absence-Drinking Dyads

描述（由申请人提供）：该申请提出了对治疗酗酒者的结果进行二次分析。它将使用1996年完成的一项大规模多地点酒精中毒治疗临床试验项目MATCH的数据，测试几种模型，以分析戒酒和饮酒行为随时间的变化。MATCH数据包含每名参与者在治疗开始后455天内每日消耗量的回顾性自我报告。该数据（N=1726）将解决与确定定义为戒酒/饮酒二元组的行为有关的研究目的，其中二元组是1天或多天不饮酒（戒酒）和1天或多天饮酒的序列。同时，将有可能确定参与者在随访期间的戒酒/饮酒二元模式作为治疗后行为轨迹。由于可以假设治疗后饮酒行为轨迹之间存在相似性（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，可以采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，这种方法将产生一个更好的了解一个人的变化，在既定的模式，随着时间的推移，饮酒，并导致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。目前常用的方法将酒精中毒治疗的结果视为二元事件（戒酒）或使用随访期间平均的频率（例如戒酒天数百分比（%））或强度（例如饮酒日的饮酒量）指标。这两种结果的方法都没有认识到和代表从旧行为（例如饮酒）到新行为（例如禁欲）的过渡中所涉及的试验和错误。MATCH数据为开发模型提供了机会，这些模型可以更好地代表临床试验中观察到的长期结果随访阶段，多次尝试禁欲。最重要的是，这些目标可以以最低的成本实现。

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.