Mental Health CAT (MH-CAT) for Community-Based Use

描述（由申请人提供）：精神障碍是美国最普遍的疾病之一，对个人和社会的负担是巨大的。然而，在社区卫生保健系统中，他们仍然普遍诊断不足。帮助全科医生（GP）识别和监测心理健康问题的一种方法是使用自我管理的患者问卷;然而，目前可用的工具要么非常冗长，要么缺乏个人决策所需的测量精度，不同工具的结果几乎没有可比性。计算机自适应测试（CAT）方法的出现有望解决这些问题，但为了促进其在临床实践中的广泛使用，必须开发和不断支持适当的软件解决方案。我们建议建立一个心理健康CAT（MH-CAT）作为一个全面的软件解决方案的一部分，适合在社区为基础的设置日常使用。MH-CAT将是一个高度敏感，易于使用的第一阶段筛查工具，以帮助全科医生识别和监测需要特殊精神卫生保健服务的患者。MH-CAT将与两个最常用的固定长度问卷（即，CES-D和MHI-5，代表SF-36的一个量表）。为了避免地板效应，并使该工具对有和没有心理健康问题的患者有意义，我们将包括测量疾病特异性症状的项目，以及积极的心理健康状态。在第一阶段，我们建议：（1）建立一个涵盖双相情感正常-抑郁症状连续体的试题库;（2）制定一个全面而灵活的 CAT软件解决方案，包括医生报告;（3）提供交叉校准方法来比较MH-CAT，MHI-5和CES-D之间的分数;以及（4）在社区环境中的现场测试中展示我们的CAT软件的可用性。为了实现这些目标，我们将使用基于项目反应理论（IRT）的方法来评估来自QualityMetric和兰德公司的13,547名患者和256个不同项目的现有数据源，以及来自现场测试中包括的60名患者的数据。在第二阶段，我们将测试MH-CAT与静态问卷相比的诊断敏感性和特异性，扩展测量以评估进一步的心理健康结构（焦虑，痛苦，认知障碍），包括额外的特征（即，评估治疗副作用），以促进工具的整合和广泛应用，并测试使用 仪器

DESCRIPTION (provided by applicant): Mental disorders are among the most prevalent conditions in the United States, and their burden for the individual and the society is tremendous. Nevertheless, they are still widely under-diagnosed in community based health care systems. One way to help general practitioners (GP) identify and monitor mental health problems is to use self-administered patient questionnaires; however, the instruments that are currently available are either very lengthy or lack the measurement precision sought for individual decision making, and results from different tools are hardly comparable. The advent of computer adaptive testing (CAT) methods promises to solve these problems, but to facilitate their wide-spread use in clinical practice, appropriate software solutions must be developed and constantly supported. We propose to build a Mental Health CAT (MH-CAT) as part of a comprehensive software solution suitable for daily use in community-based settings. The MH-CAT will be a highly sensitive, easy-to-use first stage screening tool to help GPs identify and monitor patients in need of special mental health care services. The MH-CAT will be downward comparable to two of the most frequently-used fixed-length questionnaires (i.e., the CES-D and the MHI-5, representing one scale of the SF-36). To avoid floor effects and to make the tool meaningful for patients with and without mental health problems, we will include items measuring disease specific symptoms, as well as positive mental health states. In Phase I we propose to: (1) construct an item bank covering a bipolar euthymic-depressive symptoms continuum; (2) develop a comprehensive and flexible CAT software solution, including a physician report; (3) provide a cross-calibration approach to compare scores between the MH-CAT, MHI-5 and CES-D; and (4) demonstrate the usability of our CAT software in a field test in a community-based setting. To achieve these aims, we will use methods based on item response theory (IRT) to evaluate existing data sources of 13,547 patients and 256 different items from QualityMetric and RAND Corporation, as well as data from 60 patients included in the field test. In Phase II, we will test the diagnostic sensitivity and specificity of the MH-CAT compared with static questionnaires, extend the measurement to assess further mental health constructs (anxiety, distress, cognitive impairment), include additional features (i.e., assessment of treatment side-effects) to facilitate integration and widespread application of the tool, and test the impact of using the instrument.