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（通过应用程序证明）：一种失语症的核心特征，每年影响大约80,000人的疾病有用的是，这些指标必须（i）在现代框架的删除特性中得到验证，（ii）产生有关严重性和基础认知的信息，而认知的基础低一些响应负担，（iii）支持重复的屁股而不损害人类的有效性，以及（iv）在ICF的活动水平上预测该研究的目标是当前的校正，并且单词检索评估的实用性用于量化变化，评估新的治疗方案并诊断障碍。使用IRT来评估ITHIRT效果的心理测量框架。在特定的患者时期，选定的允许同等测试形式的形式形式形式形式形式形式形式形式形式的人在多幅度的情况下表现出来的分数。验证基于1参数逻辑IRT模型的CAT版本，该模型可严格量化整体的量化。 o确定增强猫算法在整个PNT上预测误差比例。当使用CAT -PNT-使用我们的总体目标时，具有话语表现的全部PNT并评估关系的强度直接解决NIDCD 2012 - 2016年NIDCD战略计划中确定的目标，即通过“形成认真，明确，明智地使用库伦的最佳证据来开发有效的诊断工具沟通障碍。

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