National Neuropsychological Network (NNN)

项目摘要 这项建议旨在建立一个国家神经心理学网络(NNN)，从四项临床研究开始 位于加利福尼亚州、佛罗里达州、佐治亚州和威斯康星州。NNN旨在收集临床诊断信息 遵循共享协议，收集具有代表性的神经心理(NP)工具的项目级数据，以及 将这些数据存放在nimh数据档案库(nda；https://data-archive.nimh.nih.gov/)，，更具体地说是 研究领域标准数据库(RDoCDb)。在网络中建立的基础设施侧重于点- Of-测试数据采集，使用iPad，利用领先测试供应商(Q- Interactive，来自Pearson)，并开发额外的软件来收集具体的额外措施 广泛用于临床神经心理学实验室和诊所，但在其他地方没有。神经网络 将在4年内收集10,000多个病例的数据，代表广泛的神经精神病学 疾病，反映全国范围内的人口，然后将所有数据存储在RDoCDb中。数据分析将 指定每个测试背后的潜在构造，由更大的电池代表的因素，并创建 关于新的单项测试和电池的建议。建议采用新颖的测试(简写形式和适应性测试)。 基于项目反应理论对每个测验进行建模，以期望的测量精度作为证据- 以临床决策为基础。新的电池提案将通过检查正负向来通知 每项测试的预测能力有助于在NP评估中出现关键的鉴别诊断问题。 电池和个人测试方案都将重点放在效率上，预计至少会增加一倍 效率的问题。NNN的目标是作为更多网络节点的核心和模板，这将在下一步实现 世代为共同规范新奇测试提供了一个全国性的平台，扩展到其他语言，并最终 设计新的程序，在大脑功能和现实世界适应性方面都得到验证 容量。

Project Summary This proposal aims to develop a National Neuropsychology Network (NNN), starting with four clinical research sites in California, Florida, Georgia, and Wisconsin. The NNN aims to gather clinical diagnostic information following a shared protocol, collect item-level data on representative neuropsychological (NP) instruments, and deposit these data in the NIMH Data Archive (NDA; https://data-archive.nimh.nih.gov/), more specifically in the Research Domains Criteria database (RDoCdb). The infrastructure established in the network focuses on point- of-testing data acquisition, using iPads, leveraging existing technology developed by a leading test vendor (Q- interactive, from Pearson), and developing additional software to collect specific additional measures that are widely used in clinical neuropsychology laboratories and clinics but which are not available elsewhere. The NNN will collect data on more than 10,000 cases over 4 years, representing a broad range of neuropsychiatric disorders, reflecting populations seen nationwide, and then deposit all data in RDoCdb. Data analyses will specify the latent constructs underlying each test, the factors represented by larger batteries, and create proposals for new individual tests and batteries. Novel tests (short forms and adaptive tests) will be suggested based on item-response theory modeling of each test, with desired precision of measurement for evidence- based clinical decision-making. Novel battery proposals will be informed by examining the positive and negative predictive power of each test to contribute to key differential diagnostic questions that arise in NP assessment. Both battery and individual test proposals will focus on efficiency, and are expected to yield at least a doubling of efficiency. The NNN aims to serve as a nucleus and template for additional network nodes, that will in its next generation offer a national platform for co-norming novel tests, expanding to other languages, and ultimately designing new procedures that are validated with respect to both brain function and real world adaptive capacities.