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: 10466972
• 负责人: Gerasimos Fergadiotis
• 金额: $ 53.95万
• 依托单位: VETERANS HEALTH FOUNDATION
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10466972
• 关键词: Address; Affect; Agreement; Algorithms; American; Anomia; Aphasia; Aphasiology; Area; Assessment tool; Bayesian Method; Brain Injuries; Clinic; Clinical; Cognitive; Cognitive deficits; Computer Models; Computers; Data; Data Set; Development; Diagnosis; Diagnostic; Disease; Engineering; Equilibrium; Exhibits; Foundations; Frequencies; Future; Goals; Individual; Investigation; Length; Link; Measurement; Measures; Methods; Modeling; Modification; Names; National Institute on Deafness and Other Communication Disorders; Outcome; Participant; Patients; Persons; Philadelphia; Policies; Process; Production; Property; Psychometrics; Rehabilitation therapy; Research; Sampling; Severities; Specific qualifier value; Strategic Planning; Stroke; Structure; System; Techniques; Technology; Testing; Theoretical model; Time; Treatment Efficacy; Validation; Walkers; Work; Workload; archive data; archived data; base; clinical decision-making; clinical practice; computerized; efficacy research; experience; flexibility; improved; instrumentation; lexical; predictive modeling; predictive test; response; simulation; theories; treatment research

Project Summary/Abstract Anomia is a core feature of aphasia, a disorder affecting at least 2.5 million Americans. Assessment of naming ability is foundational to both research and clinical practice in aphasiology, but currently available naming tests have largely failed to capitalize on important advances in psychometric theory and practice over the past 50 years. Sensitive metrics are needed to support investigations of the cognitive mechanisms underlying anomia, clinical decision making, and treatment research. To be optimally useful, these metrics must be validated within a rigorous psychometric framework to (i) efficiently provide information about both overall severity and the underlying cognitive deficits in a unified framework, (ii) support repeated assessments without threatening internal validity or measurement precision, (iii) target both object and action naming, and (iv) easily integrate into computerized adaptive testing platforms. All current anomia tests lack at least one of these features. To remedy this gap, this project pursues three aims. First, to ease sharing of information across clinics and labs, and enhance the ability to conduct robust meta-analytic studies, five object picture-naming tests will be equated within an item response theory framework, and their scores will be expressed on the same metric. Further, to obviate the need for large samples in future item development, a model for predicting the difficulty of most picturable nouns will be refined and cross-validated. Just as the measurement of length does not depend on which ruler is used, measurement of anomia severity need not depend on which naming test is given. Second, to quantify the underlying cognitive deficits of anomia, a cognitive-psychometric model of anomia will be refined and evaluated to produce a measurement model that balances clinical utility, model-data fit, and fidelity to current theory. Third, given the increasingly recognized importance of action naming, a computer adaptive action naming test will be developed using item response theory by modeling action naming responses; regressing verb item difficulty parameters on relevant target properties; and, conducting real-data simulations to assess the precision of the computer adaptive test engine. This work will produce a powerful and flexible anomia assessment tool with utility for both research and clinical practice. Depending on user specifications, it will maximize diagnostic information and measurement precision while minimizing response burden. The aims of this project directly address goals identified in the NIDCD Strategic Plan for 2017-2021, including developing and refining techniques, technology, and instrumentation for improved diagnosis to aid in treatment and improve clinical outcomes.

项目摘要/摘要 异常是失语症的核心特征，这种疾病至少影响250万美国人。评估命名 能力是失语学研究和临床实践的基础，但目前可用的命名测试 在过去的50个 年。需要敏感的指标来支持对异常的认知机制的研究， 临床决策和治疗研究。为了获得最佳有用，必须对这些指标进行验证 严格的心理测量框架（i）有效地提供有关整体严重性和 统一框架中的基本认知缺陷，（ii）支持重复评估而不会威胁 内部有效性或测量精度，（iii）针对对象和动作命名，（iv）很容易整合 进入计算机化自适应测试平台。所有当前的异常测试至少缺乏这些功能之一。到 补救这个差距，该项目追求三个目标。 首先，减轻跨诊所和实验室的信息共享，并增强执行强大的能力 荟萃分析研究，将在项目响应理论中等同于五个对象图像命名测试 框架及其分数将以同一指标表达。此外，要消除对大的需求 未来项目开发中的样本，将完善用于预测大多数名词难度的模型 和交叉验证。正如长度的测量不取决于使用哪个标尺，测量 异常严重程度不必取决于给出哪个命名测试。 其次，要量化异常的潜在认知缺陷，这是一种认知心理模型 异常将进行完善和评估，以产生平衡临床实用程序模型数据的测量模型 适合当前理论。 第三，鉴于行动命名的重要性越来越大，计算机适应性动作 通过对动作命名响应进行建模，将使用项目响应理论开发命名测试；回归 相关目标属性上的动词项目难度参数；并且，进行真实数据模拟以评估 计算机自适应测试引擎的精度。 这项工作将产生一个强大而灵活的异构体评估工具，并具有用于研究的实用性和 临床实践。根据用户规格，它将最大化诊断信息和测量 精确度，同时减少响应负担。该项目的目的直接解决了在 NIDCD的2017 - 2021年战略计划，包括开发和完善技术，技术和 用于改进诊断的仪器，以帮助治疗和改善临床结果。