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: 7792338
• 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 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7792338
• 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 Depression; 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; 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和最重要的目标是建立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金标准（最佳可用）测量进行比较来确定。尽管评估测量准确性的方法论基础已经制定，但许多重要且具有挑战性的统计问题尚未解决，特别是在心理健康研究中。其中包括：（1）目前大多数方法仅适用于完整的未删失数据，（2）这些方法仅适用于在相同尺度上进行两次测量的情况，（3）这些方法没有广泛用于构建新的仪器或开发仪器的解释标准。 出于心理健康研究的动机，我们首先提出了新的协议措施，评估协议存在不完整或删失的意见。与现有的措施，重点生存时间，新的指数定义的基础上双变量风险函数或生存过程，以解决处理删失的特殊需要，并回答有关的时间模式的协议（目标1）的问题。在第二个目标中，我们提议扩大一致的概念，从而能够评估不同尺度或不同类型的文书之间的对应关系。我们将开发创新的统计方法来衡量广义一致性，当（a）两个尺度都是连续的，（B）一个尺度是连续的，另一个是有序的（目标2）。基于目标2中开发的方法，我们将开发用于以下目的的方法：（a）根据分类量表找到连续量表的可解释的切割点;（B）通过在现有工具中找到项目的最佳线性组合来开发新的心理工具，以更准确地诊断糖尿病患者中的重度抑郁症（目标3）。最后，我们将通过开发方便用户的软件和建立一个网站来张贴出版物和附有用户手册的软件，向研究界宣传我们的工作（目标4）。 该提案旨在通过开发新的方法，结合现有的方法，并将这一努力目标对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，足以成为统计实践的普遍有用的贡献。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。我们开发方法，创造新的工具，易于使用的筛选抑郁症。我们还开发了分析方法，以确定是否可以用便宜，易于使用的仪器来代替昂贵，耗时的仪器来诊断抑郁症。