Data-Based Methods for Just-In-Time Adaptive Interventions in Alcohol Use

 说明(申请人提供)：本提案的目的是开发并实现利用数据优化流动干预措施的方法，旨在预防、治疗和支持酒精使用障碍的康复。在美国，酒精使用障碍的社会和个人成本非常高，但接受治疗的美国酒精使用障碍患者相对较少。通过智能手机等移动设备提供的干预措施可以增加预防、治疗和为康复中的个人提供支持的可获得性并降低成本。目前，数据在优化可通过移动设备提供的行为干预的时机和选择方面几乎没有什么用处。本项目的目标是(1)开发和评估数据分析方法和优化算法，这些方法和优化算法可以驻留在移动设备上，当个体体验移动干预并提供响应时，将优化对个人的行为干预的时间和选择；(2)开发数据分析方法和优化算法，可在涉及移动干预的临床研究之后使用，以进一步优化干预；以及(3)向临床科学界传播和说明开发的方法和算法，以最大限度地提高临床影响。我们建议进行数据分析方法/算法的技术开发，并使用模拟器在虚拟环境中测试和改进开发，该模拟器模仿涉及预防、治疗和康复酒精使用障碍的三项不同临床研究的数据。我们将与临床科学家就这些方法的教程进行合作，并传播数据。 通过举办座谈会和研讨会的分析方法。我们将开发数据分析/算法软件的初始版本，并使该软件可免费使用。

 DESCRIPTION (provided by applicant): The purpose of this proposal is develop, and bring to fruition, methods for using data to optimize mobile interventions aimed at preventing, treating and supporting the recovery from alcohol use disorders. Social and personal costs of alcohol use disorders in the US are very high, yet relatively few Americans with alcohol use disorders receive treatment. Interventions delivered via mobile devices, such as smartphones, can increase the availability and decrease the cost of both preventing, treating and providing support for individuals in recovery. At this time data has seen little use in optimizing the timing and selection of behavioral interventions that can be delivered via mobile devices. The goal of this project is (1) to develop and evaluate data analysis methods and optimization algorithms that can reside on the mobile device and that, as an individual experiences the mobile intervention and provides responses, will optimize the timing and selection of the behavioral intervention to the individual; (2) to develop data analysis methods and optimization algorithms that can be used following a clinical study involving the mobile intervention to further optimize the intervention; and (3) to disseminate and illustrate the developed methods and algorithms to the clinical science community so as to maximize clinical impact. We propose to conduct the technical development of the data analysis methods/algorithms and to test and refine the developments in a virtual environment using simulators that mimic the data from three different clinical studies involving prevention, treatment and recovery from alcohol use disorders. We will collaborate with clinical scientists on tutorials for these methods as well as disseminate the data analysis methods by conducting symposia and workshops. We will develop initial versions of the data analysis/algorithm software and make the software freely accessible.