Assessment of anomia: Improving efficiency and utility using item response theory

失范评估：利用项目反应理论提高效率和效用

• 批准号: 9022355
• 负责人: Gerasimos Fergadiotis
• 金额: $ 14.83万
• 依托单位: PORTLAND STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-22 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9022355
• 关键词: Address; Affect; Agreement; Algorithms; Anomia; Aphasia; Archives; Binding; Chi-Square Tests; Classification; Cognitive deficits; Communication impairment; Computational algorithm; Computers; Data; Databases; Decision Making; Development; Diagnosis; Diagnostic; Disease; Electronics; Engineering; Evaluation; Generations; Goals; Healthcare; Impairment; Individual; Logistics; Measurement; Measures; Modeling; Mosses; Names; National Institute on Deafness and Other Communication Disorders; Nature; Outcome; Participant; Patients; Performance; Persons; Philadelphia; Plant Roots; Policies; Property; Protocols documentation; Psycholinguistics; Psychometrics; Rehabilitation therapy; Research; Retrieval; Sampling; Severities; Strategic Planning; Symptoms; System; Testing; Theoretical model; Time; United States National Institutes of Health; base; handheld mobile device; health data; improved; novel therapeutics; prevent; prospective; public health relevance; response; simulation; theories; tool; trait

 DESCRIPTION (provided by applicant): Anomia is a core feature of aphasia, a disorder that affects approximately 80,000 people each year. Sensitive metrics of change are needed for the development and evaluation of new anomia treatments and to provide the basis for rehabilitation reimbursement and policy decisions. To be optimally useful, these metrics must (i) be validated within a modern framework, such as item response theory, to enhance their psychometric properties, (ii) yield information about severity and underlying cognitive deficits with low response burden, (iii) support repeated assessments without posing threats to internal validity, and (iv) predict functioning at the activity level of the ICF. The long-term goal of thisline of research is to maximize the precision, efficiency, and utility of word retrieval assessment for quantifying change, evaluating new therapeutic protocols, and diagnosing impairments in terms of current theoretical models. To achieve this goal, this proposal will focus on engineering a theoretically driven, computer-adaptive system using IRT for assessing anomia. IRT is a state-of-the-art psychometric framework with important theoretical and practical benefits. First, it transforms observed responses to test items into latent trait scores with interval properties. Second, it formalizes how measurement precision varies as a function of a person's ability. Third, it supports algorithms for computer adaptive testing (CAT), in which only the most informative items are selected and administered for a particular patient, thus reducing testing time. It also permits the generation of equivalent test forms for assessing the same person on multiple occasions with scores that are expressed on a single common scale. This proposal has the following Specific Aims. Specific Aim 1a is to validate a CAT version of the Philadelphia Naming Test (PNT-CAT) that is based on a 1-parameter logistic IRT model for quantifying overall severity. Specifically, this aim will determine the extent to which CAT-PNT scores are precise, unbiased, and correlated with performance on the full PNT. Specific Aim 1b is to determine the ability of an augmented CAT algorithm to predict error proportions on the full PNT. The goal of Specific Aim 2 is to verify the equivalence and precision of PNT-CAT alternate forms in order to determine stability when no change is expected. Specific Aim 3 will determine the relationship of the full PNT with discourse performance and assess any potential degradation of the strength of the relationship when CAT-PNT - instead of the full PNT - are used. Our overarching goal is consistent with the NIH Roadmap's recognition of the "pressing need to better quantify clinically important symptoms and outcomes". Further, it directly addresses goals identified in the NIDCD Strategic Plan for 2012-2016, including the development of effective and efficient diagnostic tools by using "electronic health data to inform the conscientious, explicit, and judicious use of current best evidence in making decisions about health care options to improve outcomes for individuals with communication disorders."

 描述（由适用提供）：异常症是失语症的核心特征，这种疾病每年影响约80,000人。开发和评估新的异常疗法需要变化的敏感指标，并为康复报销和政策决策提供基础。为了获得最佳有用，这些指标必须（i）在现代框架中进行验证，例如项目响应理论，以增强其心理测量特性，（ii）产生有关严重性和基本认知缺陷的信息，而认知缺陷率低，而响应率低，（iii）支持重复评估，而不必对内部有效性的威胁以及（iv）在活动级别上构成函数级别的功能。这项研究的长期目标是最大程度地提高单词检索评估的精度，效率和实用性，以量化变化，评估新的治疗方案和诊断性损害，从当前的理论模型来看。为了实现这一目标，该提案将使用IRT来评估异常症的IRT进行工程驱动的计算机自适应系统。 IRT是一个最先进的心理测量框架，具有重要的理论和实际好处。首先，它将观察到的对测试项目的响应转化为具有间隔属性的潜在特征分数。其次，它正式将测量精度与人的能力函数相关。第三，它支持用于计算机自适应测试（CAT）的算法，其中仅选择和为特定患者选择了最有用的项目，从而减少了测试时间。它还允许生成等效的测试表格，以多次评估同一人，其得分以单个共同规模表示。该建议具有以下特定目标。具体目标1A是验证基于1参数逻辑IRT模型的费城命名测试（PNT-CAT）的CAT版本，用于量化整体严重性。具体而言，此目标将确定CAT-PNT分数精确，公正并与完整PNT的性能相关的程度。特定的目标1B是确定增强猫算法预测完整PNT上错误比例的能力。特定目标2的目的是验证PNT-CAT替代形式的等效性和精度，以确定在预期不变时稳定性。特定的目标3将确定完整的PNT与话语表现的关系，并评估使用CAT -PNT而不是完整的PNT时，关系强度的任何潜在降解。我们的总体目标与NIH路线图对“迫切需要更好地量化临床重要的符号和结果”的认可是一致的。此外，它直接解决了2012 - 2016年NIDCD战略计划中确定的目标，包括开发有效和有效的诊断工具，通过使用“电子健康数据来告知认真，明确，明智地使用当前最佳证据，以在做出有关卫生保健方案的决策以改善交流障碍的人的现象。”