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: 10032557
• 负责人: Gerasimos Fergadiotis
• 金额: $ 61.36万
• 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/10032557
• 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; base; clinical decision-making; clinical practice; computerized; data archive; 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 失语症是失语症的一个核心特征，失语症是一种至少影响250万美国人的疾病。命名评估 能力是失语症研究和临床实践的基础，但目前可用的命名测试 在很大程度上未能利用过去50年来心理测量学理论和实践的重要进展 好几年了。需要敏感的指标来支持对精神失常背后的认知机制的调查， 临床决策和治疗研究。为了达到最佳效果，必须在以下范围内验证这些指标 严格的心理测量框架，以(I)有效地提供有关总体严重性和 统一框架中的潜在认知缺陷，(2)支持重复评估，而不构成威胁 内部有效性或测量精度，(Iii)目标对象和动作命名，以及(Iv)容易集成 进入计算机化的自适应测试平台。目前所有的失范测试都缺乏这些特征中的至少一个。至 弥补这一差距，这个项目追求三个目标。 第一，简化诊所和实验室之间的信息共享，并增强执行可靠的 元分析研究，五个物体图片命名测试将被等同于项目反应理论 框架，他们的分数将以相同的标准表示。此外，为了消除对大型 在未来的项目开发中，将改进预测大多数可想象名词难度的模型 并进行交叉验证。正如长度的测量不取决于使用哪种尺子一样，测量 异常的严重程度不需要取决于进行了哪一项命名测试。 其次，为了量化精神失调症的潜在认知缺陷，一个认知-心理测量模型 Anomia将被改进和评估，以产生一个平衡临床效用、模型数据的测量模型 符合并忠实于当前的理论。 第三，鉴于动作命名的重要性日益得到认可，计算机自适应动作 命名测试将使用项目反应理论，通过对动作命名反应进行建模来开发；回归 动词项难度参数对相关目标属性的影响；以及，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失范评估工具，具有研究和 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，同时最大限度地减少响应负担。该项目的目标直接针对 NIDCD 2017-2021年战略计划，包括开发和提炼技术、技术和 用于改进诊断的仪器，以帮助治疗和改善临床结果。