Integrative Data Analysis to Predict Alcohol Clinical Course and Inform Practice

描述(由申请人提供)：尽管酒精治疗提供者采取了许多循证的行为和药物干预措施，但在治疗后饮酒仍然很常见，经常是在有问题的水平上。然而，关于谁酗酒复发的风险最大，在什么情况下无问题饮酒升级到治疗前的饮酒水平，或者相反，在最初的失误后大量饮酒减少，以及无问题饮酒何时在不需要额外干预努力的情况下得到解决，人们知之甚少。总的来说，酒精治疗后的变化机制还不是很清楚。为了解决这些认识上的差距，这项研究将建立一个关于接受酒精治疗的个人中成功酒精治疗结果的预测因素的经验知识库。研究目标的实现将为临床医生提供以规范为基础的指南，以在治疗期间识别“危险”个人，以及在治疗后饮酒时评估是否需要额外治疗的标准。为了制定这些指南和标准，将对参与四项由公共资金资助的四项酒精治疗研究的4,000多名个人(n=4,415)的酒精临床病程影响因素进行综合数据分析。为了刻画个体饮酒规范，本研究将借鉴复吸的动态理论模型来考虑酒精临床病程的复杂性，该模型强调易感因素和危险因素之间的交互作用对酒精临床病程的预测。这项研究的第一个目的是 检查个人饮酒模式和在治疗过程中和治疗后的不同时间点上再次饮酒的可能性，以及从再次饮酒转变为复发的可能性。本研究以饮酒概率为基础，探讨个体特征和治疗因素与个体行为和环境因素在预测酒精治疗结果中的相互作用程度。这项研究的结果将直接应用于临床实践，通过提供与治疗期间和治疗后一年内饮酒模式变化相关的个人特征、诱发事件和治疗可修改因素的指导。这些数据将使提供者能够预测治疗期间和治疗后的客户结果，并将提供实用的策略 关于可降低重新酗酒的可能性的步骤。这一结果还将帮助临床医生识别那些预测保持低风险饮酒轨迹的可能性更高的个人特征和环境因素。此外，研究得出的概率可用于开发基于经验的临床决策支持系统。这样的系统在酒精治疗领域是史无前例的，可以广泛传播给临床医生、计划评估者和政策制定者，以帮助改善酒精治疗决策和改善治疗结果。

DESCRIPTION (provided by applicant): In spite of the adoption of many evidence-based behavioral and pharmacological interventions by alcohol treatment providers it is still common for drinking to occur after treatment, frequently at problematic levels. Very little is known, however, about who is most at risk for heavy drinking relapses, under what conditions non- problematic drinking escalates to pre-treatment levels of drinking or, conversely, heavy drinking is reduced after an initial lapse, and when non-problematic drinking resolves without the need for additional intervention efforts. In general, the mechanisms of change following alcohol treatment are not well understood. To address these gaps in understanding, this study will build an empirical knowledge base of predictors of successful alcohol treatment outcomes among individuals who receive alcohol treatment. The achievement of study aims will provide clinicians with both normative-based guidelines to identify "at risk" individuals during treatment as well as criteria to evaluate the need for additional treatment when post treatment drinking occurs. To develop these guidelines and criteria, integrative data analysis of factors influencing alcohol clinical course among more than 4,000 individuals (n = 4,415) who participated in four publicly funded alcohol treatment studies will be conducted. In order to characterize individual drinking norms this study will consider the complexities of alcohol clinical course by drawing on a dynamic theoretical model of relapse that emphasizes the interaction between predispositions and risk factors in the prediction of alcohol clinical course. The first aim of this research is to examine individual patterns of drinking and the probabilities of lapsing at various time points during and following treatment, as well as the probabilities of transitioning from a lapse to relapse. Using these probabilities of drinking as the basis for defining unsuccessful and successful treatment outcomes, this research aims to examine the degree to which individual characteristics and treatment factors interact with individual behaviors and environmental factors in the prediction of alcohol treatment outcomes. The results from this study will be directly applicable to clinical practice by providing guidance on the individual characteristics, precipitating events, and treatment modifiable factors that are associated with changes in drinking patterns during treatment and one year following treatment. These data will allow providers to predict client outcomes during and after treatment and will offer practical strategies regarding steps that could reduce the likelihood of a return to heavy drinking. The results will also help clinicians identify those individual characteristics and environmental factors that predict a higher probability of maintaining a low-risk drinking trajectory. Moreover, the probabilities derived from the research can be used for the development of an empirically-based clinical decision making support system. Such a system, unprecedented in the alcohol treatment field, could be widely disseminated to clinicians, program evaluators, and policy makers in order to help improve alcohol treatment decision-making and improve treatment outcomes.