Predictive Models of Alcohol Consumption

描述(申请人提供)：这项方法学研究的目标是开发和系统地测试个人酒精消费的预测模型。预测患者饮酒量的能力可能有助于个性化治疗计划。对于酗酒者来说，预测他们下一集的时间可以提供额外的意识，这可能有助于控制甚至防止整个情节。对于酗酒者，预测模型可以预测患者最清醒和对干预反应最敏感的治疗机会窗口。对于那些试图戒酒的人来说，预测下一次复发可以用来触发激励性访谈或其他及时的干预措施，以帮助防止复发。我们将分析两个数据集，其中包含酒精使用、压力和其他因素的个人日常记录的长时间序列(2年和6个月)。我们将采用开发的创新预测模型来预测未来的酒精消费，以及识别和解释各种日常使用模式。关于个人饮酒的数据非常有限，这是第一次旨在利用这些数据建立预测模型的研究。这项研究为该领域提供了一种创新的分析方法，可能为预防复发、提高治疗效率和加强对驱动日常使用模式变化的因素的理解提供临床意义。 公共卫生相关性：关于个人每日饮酒的数据对于了解酒精滥用/成瘾至关重要。这项研究是第一次利用这些数据建立预测模型。这项研究为该领域提供了一种创新的分析方法，可能为预防复发、提高治疗效率和加强对驱动日常使用模式变化的因素的理解提供临床意义。

DESCRIPTION (provided by applicant): The objective of this methodological study is to develop and systematically test predictive models of an individual's alcohol consumption. The ability to forecast alcohol consumption in patients can potentially help individualized treatment programs. For binge drinkers, predicting the timing of their next episode provides additional awareness that could help to control, or even to prevent, the entire episode. For heavy drinkers, predictive models can forecast the windows of treatment opportunity when the patient is most sober and responsive to intervention. For those who are attempting to quit drinking, forecasting the next relapse episode could be used to trigger motivational interviewing or other timely interventions that will help prevent the relapse. We will analyze two data sets containing long time series (2 years and 6 months) of individual daily records of alcohol use, stress, and other factors. We will adapt innovative predictive models developed to forecast future alcohol consumption as well as identify and explain a variety of daily use patterns. The data on individual alcohol consumption is very limited, and this is the first study aiming to build forecasting models using such data. This study offers the field a 'next step' with an innovative analysis approach that can possibly offer clinical implications for relapse prevention, increased treatment efficiency, and enhanced understanding of the factors driving the variety of daily patterns of use. PUBLIC HEALTH RELEVANCE: The data on daily individual alcohol consumption is critical for understanding alcohol abuse/addiction. This study is the first one to build forecasting models using such data. This study offers the field a 'next step' with an innovative analysis approach that can possibly offer clinical implications for relapse prevention, increased treatment efficiency, and enhanced understanding of the factors driving the variety of daily patterns of use.