Development and validation of software for Internet and PC SCID administration

描述（由申请人提供）：本项目的总体目标是开发和验证用于计算机辅助管理DSM-IV轴I障碍（SCID）结构化临床访谈的软件-研究版。SCID一直被认为是产生准确的精神病诊断的黄金标准工具，但管理繁琐且昂贵。拟议的项目将开发以因特网为基础的软件，使联合诊断系统复杂的分支和诊断逻辑自动化，从而提高效率和方便使用。该软件将提供新的功能，大大改进以前开发计算机辅助SCID的尝试。第一阶段包括两项任务：开发一个数据库驱动的应用程序来管理SCID（Net SCID），并使用以前管理的纸质SCID数据对软件进行广泛测试。Net SCID软件的开发版本将允许在互联网、局域网或独立PC上进行管理。将进行广泛的软件测试，以确保Net SCID的分支和诊断逻辑与原始纸质SCID的分支和诊断逻辑一致。为了测试该软件，将使用双重数据输入程序来创建一个电子数据库，该数据库来自先前NIMH资助的R 01研究中收集的150份纸质SCID。将使用自动化脚本将响应引入Net SCID，以模拟实时管理并证明两种SCID形式之间的分支和诊断逻辑的等效性。软件测试将是一个迭代过程;当对Net SCID的分支和诊断逻辑进行纠正时，将重新测试所有测试用例。我们在第一阶段的成功标准是100%的协议与文件SCID的问题文本，分支结构和诊断逻辑。在第二阶段，我们将实施和测试互联网版本的SCID（包括临床医生版本），并开发新的功能，以提供一个完整的，用户友好的界面，自动生成的诊断报告，以及符合HIPAA的项目响应和诊断数据库，用于统计分析。我们还将在临床环境中根据纸质SCID直接验证Net SCID。拟议项目的目标是开发和验证一个用户友好，高效的软件应用程序，用于管理计算机辅助的DSM-IV-TR结构化临床面谈（SCID），使用互联网技术（Net SCID）。精神卫生研究人员和临床医生依赖于准确的精神病诊断，而SCID已被证明比其他获得DSM诊断的方法更准确和可靠。Net SCID将使SCID更易于使用，减少培训访问者、复制、管理和评分SCID以及存储和访问结果所需的资金和人力，从而促进这一黄金标准工具的广泛采用。这些改进将使更多的研究人员和临床医生能够定期使用SCID，提高精神病诊断的准确性，从而提高研究和患者护理的质量。

DESCRIPTION (provided by applicant): The overall aim of this project is to develop and validate software for computer-assisted administration of the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID) - Research Version. The SCID is consistently recognized as the gold standard instrument for generating accurate psychiatric diagnoses, but is cumbersome and expensive to administer. The proposed project will develop Internet-based software to automate the complex branching and diagnostic logic of the SCID, thereby increasing efficiency and ease of use. This software will offer new features that substantially improve upon previous attempts to develop a computer-assisted SCID. Phase I entails two tasks: development of a database-driven application to administer the SCID (Net SCID) and extensive testing of the software using data from previously administered paper SCIDs. Net SCID software will be developed in versions that allow for administration over the Internet, on a local area network (LAN), or on a standalone PC. Extensive software testing will be carried out to ensure that the Net SCID's branching and diagnostic logic is consistent with that of the original paper SCID. To test the software, double data entry procedures will be used to create an electronic database of item responses from 150 paper SCIDs collected in a previous NIMH-funded R01 study. Responses will be introduced into the Net SCID using an automated script to simulate live administration and demonstrate the equivalence of the branching and diagnostic logic between the two SCID forms. Software testing will be an iterative process; all test cases will be retested when corrections are made to the branching and diagnosis logic of the Net SCID. Our criterion for success in Phase I is 100% agreement with the paper SCID in question text, branching structure and diagnostic logic. In Phase II, we will implement and test Internet versions of variations of the SCID (including the Clinician Version) and develop new features to provide a complete, user- friendly interface, automatically generated diagnostic reports, and HIPAA-compliant databases of item responses and diagnoses for statistical analysis. We will also directly validate the Net SCID against the paper SCID in a clinical setting. The objective of the proposed project is to develop and validate a user-friendly, efficient software application for administering a computer-assisted Structured Clinical Interview for DSM-IV-TR (SCID), using Internet technology (Net SCID). Mental health researchers and clinicians rely upon accurate psychiatric diagnoses, and the SCID has been shown to be more accurate and reliable than other methods for obtaining DSM diagnoses. The Net SCID will facilitate widespread adoption of this gold standard instrument by making the SCID easier to use and reducing the money and labor required to train interviewers, to copy, administer, and score the SCID, and to store and access results. These improvements will allow more researchers and clinicians to use the SCID regularly, increasing the accuracy of psychiatric diagnoses and, consequently, resulting in a higher quality of research and care for patients.