Method Development of Agreement Measures and Applications in Mental Health

协议措施的方法开发及其在心理健康中的应用

• 批准号: 7599207
• 负责人: AMITA K. MANATUNGA
• 金额: $ 27.9万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7599207
• 关键词: Address; Agreement; Area; Biological Phenomena; Biomedical Research; Caring; Categories; Clinical; Communities; Computer software; Data; Depression screen; Development; Diabetes Mellitus; Diagnosis; Disease; Education; Event; Foundations; Goals; Gold; Guidelines; Health; Major Depressive Disorder; Manuals; Measurement; Measures; Medical; Mental Health; Methodology; Methods; Outcome; Outcome Measure; Patients; Pattern; Population; Process; Property; Psyche structure; Publications; Research; Research Project Grants; Severities; Severity of illness; Statistical Methods; Statistical Models; Testing; Text; Time; Weight; Work; analytical method; base; depression; design; hazard; improved; indexing; innovation; instrument; interest; method development; psychologic; public health relevance; user friendly software; web site

DESCRIPTION (provided by applicant): A fundamental and foremost objective in biomedical research is to establish accurate, valid measurements of the clinical disease of interest. The accuracy and validity of such disease measurements are commonly established by assessing similarity between measurements made on a subject by multiple observers/time points or by comparing with some gold standard (best available) measurement. Although the foundation of the methodology for assessing accuracy of measurements has been formulated, many important and challenging statistical issues have not yet been resolved, particularly in mental health studies. These include: (1) most current methods are derived only for complete uncensored data, (2) the methods are applicable only when both measurements are made on the same scale, and (3) the methods are not widely used for constructing new instruments or developing interpretation criteria of instruments. Motivated by studies in mental health, we first propose new agreement measures for assessing agreement in the presence of incomplete or censored observations. Unlike existing measures that focus on survival times, the new indices are defined based on bivariate hazard functions or survival processes to address the special needs for handling censoring and to answer questions regarding the temporal pattern of agreement (Aim 1). In the second Aim, we propose to broaden the concept of agreement, thereby allowing for the assessment of the correspondence between instruments on different scales or of different types. We will develop innovative statistical methods to measure the broad sense agreement when (a) both scales are continuous and (b) one scale is continuous and the other is ordinal (Aim 2). Based on the methods developed in Aim 2, we will develop methods for (a) finding interpretable cut-points of a continuous scale in terms of a categorical scale and (b) developing a new psychological instrument by finding an optimal linear combination of items in an existing instrument for more accurate diagnosis of major depression among diabetes patients (Aim 3). Finally, we will disseminate our work to research communities by developing user-friendly software and creating a web site to post publications and software with user manuals (Aim 4). This proposal is designed to improve analytic methods for mental health research by developing new methodology, incorporating existing methodology and by targeting this effort toward important scientific mental health studies. These developments will directly benefit mental health research, but they are ubiquitous enough to be generally useful contributions to statistical practice. PUBLIC HEALTH RELEVANCE: The proposed research project will develop new analytical methods for improving the accuracy of measurements in mental health studies. We develop methods for creating new instruments that are easy to use for screening depression. We also develop analytic methods to determine whether expensive, time consuming instrument can be replaced by inexpensive, easy-to-use instrument for diagnosing depression.

描述（由申请人提供）：生物医学研究的一个基本且最重要的目标是建立对感兴趣的临床疾病的准确、有效的测量。这种疾病测量的准确性和有效性通常是通过评估多个观察者/时间点对受试者进行的测量之间的相似性或通过与一些黄金标准（最佳可用）测量进行比较来确定的。尽管评估测量准确性的方法基础已经制定，但许多重要且具有挑战性的统计问题尚未得到解决，特别是在心理健康研究中。其中包括：（1）大多数当前方法仅针对完整的未经审查的数据得出，（2）这些方法仅适用于在相同规模上进行两种测量的情况，以及（3）这些方法并未广泛用于构建新仪器或制定文书的解释标准。 受心理健康研究的推动，我们首先提出了新的一致性衡量标准，用于在存在不完整或审查的观察结果的情况下评估一致性。与关注生存时间的现有指标不同，新指数是根据二元风险函数或生存过程定义的，以满足处理审查的特殊需求并回答有关协议时间模式的问题（目标 1）。在第二个目标中，我们建议扩大协议的概念，从而允许评估不同规模或不同类型的工具之间的对应关系。我们将开发创新的统计方法来衡量广义一致性，当（a）两个量表都是连续的并且（b）一个量表是连续的而另一个是序数的（目标2）时。基于目标 2 中开发的方法，我们将开发以下方法：（a）根据分类量表找到连续量表的可解释切点；以及（b）通过找到项目的最佳线性组合来开发新的心理工具。用于更准确地诊断糖尿病患者重度抑郁症的现有工具（目标 3）。最后，我们将通过开发用户友好的软件并创建一个网站来发布出版物和带有用户手册的软件，从而向研究社区传播我们的工作（目标 4）。 该提案旨在通过开发新的方法、结合现有的方法以及将这项工作瞄准重要的科学心理健康研究来改进心理健康研究的分析方法。这些发展将直接有利于心理健康研究，但它们无处不在，足以对统计实践做出普遍有用的贡献。公共卫生相关性：拟议的研究项目将开发新的分析方法，以提高心理健康研究测量的准确性。我们开发了创建易于用于筛查抑郁症的新仪器的方法。我们还开发了分析方法，以确定昂贵、耗时的仪器是否可以被廉价、易于使用的抑郁症诊断仪器取代。