Extending an Open-Source Integrated Data Management Platform to Anxiety Disorders

描述(由申请人提供)：此应用程序的目标是通过提供满足他们需求的开源、集成数据管理平台，使焦虑症研究人员能够在整个研究生命周期中更有效地管理、共享和重新调整他们的研究数据的用途。心理健康研究已经变得更加复杂、协作和跨学科，共享和重新利用数据以供复制和二次分析对科学进步变得越来越重要。这些趋势需要一个数据管理系统，使研究人员能够在整个数据管理生命周期中持续集成跨研究和站点的异类数据，从而使数据成为可再生的资源，而不是一次性资源。尽管目前还没有合适的技术用于焦虑症的研究，但开源的自闭症研究交换数据库(RexDB)已经很接近了。用于自闭症的RexDB是第一个强大的开源系统，以满足自闭症研究人员的综合生命周期数据管理需求。我们建议对RexDB进行关键改进，以支持三种主要类型的焦虑研究：(1)干预性研究(如临床试验)；(2)与临床试验同时进行的辅助研究；以及(3)对参与者进行跟踪的纵向研究 一项或多项临床试验(例如，综合患者登记)。为了实现我们的总体目标，我们将：(A)通过与四个评估点的利益攸关方接触，明确定义软件要求，确定用户需要的功能；(B)交付软件的初步版本，使用户能够为焦虑研究配置强大的数据管理系统；(C)通过从每个评估网站征求定期的利益相关者反馈和可用性测试，实施和评估新功能，通过灵活、迭代的软件开发过程解决主要差距；以及(D)在焦虑症研究人员中建立一个活跃的用户社区。一种满足焦虑症需求的数据管理系统可能会在行为和心理健康研究的广泛范围内推广。成功将加速研究，并通过将研究数据转化为共享的、可再生的资源，增加NIH在精神健康方面花费的每一美元研究的价值。

DESCRIPTION (provided by applicant): The goal of this application is to empower anxiety disorders researchers to manage, share, and repurpose their research data more effectively throughout the research lifecycle by delivering an open--source, integrated data management platform that meets their needs. Mental health research has become more complex, collaborative, and interdisciplinary and sharing and repurposing data for replication and secondary analyses have become increasingly important to the advancement of science. These trends require a data management system that enables researchers to continuously integrate heterogeneous data across studies and sites throughout the data management lifecycle, allowing the data to be a renewable, rather than a disposable, resource. Although appropriate technology does not yet exist for anxiety disorders research, the open--source Research Exchange Database (RexDB) for autism comes close. RexDB for autism is the first robust, open--source system to meet the integrated lifecycle data management needs of autism researchers. We propose to make critical enhancements to RexDB that support three major types of anxiety research: (1) interventional research (such as clinical trials); (2) ancillary stuies conducted alongside clinical trials; and (3) longitudinal studies that follow up on participants in one or more clinical trials (e.g., integrated patient registries). To achieve our overarching aim, we will: (a) identify the features users need by engaging with stakeholders at four evaluation sites to clearly define software requirements;(b) deliver a preliminary version of the software tha empowers users to configure a robust data management system for anxiety research;; (c) implement and evaluate new features by soliciting regular stakeholder feedback and usability testing from each of the evaluation sites, addressing major gaps via an agile, iterative software development process; and (d) build an active community of users among anxiety disorders researchers. A data management system that meets the needs of anxiety disorders researchers will likely generalize across a broad spectrum of behavioral and mental health research. Success will accelerate research and increase the value of every research dollar spent by the NIH on mental health by transforming research data into a shared, renewable resource.