基于多维物品响应理论的认知功能的自适应测量
Robert D Gibbons1, Diane S Lauderdale2, Robert S Wilson3
1Departments of Medicine and Public Health Sciences and Center for Health Statistics University of Chicago Chicago Illinois USA.
Alzheimer's & dementia (New York, N. Y.)
|January 3, 2025
概括
使用多维物品响应理论 (MIRT) 的新计算机化适应性测试 (CAT) 提供了一种快速而精确的方法来评估老年人的认知功能. 这种工具在识别轻度认知障碍 (MCI) 和阿尔茨海默病 (AD) 风险方面表现有前途.
科学领域:
- 神经科学是一个神经科学.
- 心理测量 心理测量 心理测量
- 老年学是一门学科.
背景情况:
- 轻度认知障碍 (MCI) 影响高达20%的老年人,患上阿尔茨海默病 (AD) 的风险很大.
- 传统的认知评估是耗时的,需要专门的管理.
- 与衰老相关的认知能力下降可能在明显的损伤之前几十年开始.
研究的目的:
- 开发和验证第一个基于多维物件响应理论 (MIRT) 的计算机化适应性测试 (CAT),用于评估全球认知功能.
- 为成年人创建一个快速,准确和可重复的认知评估工具.
- 为一个原型CAT (pCAT-COG) 呈现结果.
主要方法:
- 使用多维物品响应理论 (MIRT) 框架开发了一种CAT (pCAT-COG) 原型.
- 在五个认知领域采样了项目:情节性记忆,语义记忆/语言,工作记忆,执行功能和处理速度.
- 使用双因素MIRT模型校准了57项数据库,并根据标准神经心理评估验证了pCAT-COG得分.
主要成果:
- 与单维模型相比,双因素MIRT模型显示出更好的适应性.
- pCAT-COG得分显示与年龄有显著的反相关性 (r = -0.44).
- 模拟适应性测试使用11项与全银行得分密切相关 (r = 0.94),区分MCI和没有认知障碍 (NCI) 具有很大的效果大小 (1.08 SD).
结论:
- 基于多维物件响应理论 (MIRT) 的CAT是评估全球认知障碍的可行和有效方法.
- 这项工作为具有更广泛措施的全面CAT-COG奠定了基础.
- 开发的工具可与长时间的面对面评估相提并论,适合广泛使用.
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