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: 9321482
• 负责人: Gerasimos Fergadiotis
• 金额: $ 13.58万
• 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 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9321482
• 关键词: Address; Affect; Agreement; Algorithms; Anomia; Aphasia; Archives; Chi-Square Tests; Classification; Clinical; Cognitive deficits; Communication impairment; Computational algorithm; Computers; Databases; Decision Making; Development; Diagnosis; Diagnostic; Disease; Engineering; Evaluation; Generations; Goals; Healthcare; Impairment; Individual; Logistics; Measurement; Measures; Modeling; Modernization; 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; data archive; handheld mobile device; health data; improved; improved outcome; 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（由申请人提供）：失名症是失语症的核心特征，失语症是一种每年影响约80，000人的疾病。需要敏感的变化指标来开发和评估新的失名症治疗方法，并为康复报销和政策决策提供基础。为了达到最佳效果，这些指标必须（i）在现代框架内进行验证，如项目反应理论，以增强其心理测量特性，（ii）产生有关严重程度和低反应负担的潜在认知缺陷的信息，（iii）支持重复评估，而不会对内部效度构成威胁，以及（iv）预测ICF活动水平的功能。这条研究路线的长期目标是最大限度地提高精确度，效率和实用性的词检索评估量化的变化，评估新的治疗方案，并根据当前的理论模型诊断损伤。为了实现这一目标，这项建议将集中在工程理论驱动，计算机自适应系统使用IRT评估失范。 项目反应理论是一个具有重要理论和实践价值的心理测量学框架。首先，它将观察到的测试项目的反应转换成具有区间属性的潜在特质分数。其次，它形式化了测量精度如何随人的能力而变化。第三，它支持计算机自适应测试（CAT）的算法，其中仅为特定患者选择和管理最具信息性的项目，从而减少测试时间。它还允许生成等效的测试表格，用于在多个场合评估同一个人，其分数以单一的通用量表表示。 这项建议有以下具体目标。具体目标1a是验证基于单参数逻辑IRT模型的费城神经元测验（PNT-CAT）的CAT版本，用于量化总体严重程度。具体而言，这一目标将确定CAT-PNT评分的准确性、无偏倚性以及与完整PNT表现的相关性。具体目标1b是确定增强CAT算法预测全PNT上的误差比例的能力。具体目标2的目标是验证PNT-CAT替代形式的等效性和精密度，以确定预期无变化时的稳定性。具体目标3将确定完整PNT与话语表现的关系，并评估使用CAT-PNT而不是完整PNT时关系强度的任何潜在退化。 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症状和结果”的认识一致。此外，它直接涉及2012-2016年NIDCD战略计划中确定的目标，包括通过使用“电子健康数据来开发有效和高效的诊断工具，以告知在做出有关医疗保健选择的决策时认真，明确和明智地使用当前最佳证据，以改善沟通障碍患者的结果。"

项目成果

Empirical Evaluation of Computer-Adaptive Alternate Short Forms for the Assessment of Anomia Severity.

• DOI: 10.1044/2019_jslhr-l-19-0213
• 发表时间: 2019-12
• 期刊: Journal of speech, language, and hearing research : JSLHR
• 作者: William D. Hula;G. Fergadiotis;Alexander M Swiderski;J. Silkes;Stacey Kellough