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一种用于评估失语症患者图片命名能力的认知心理计量学模型。

A cognitive psychometric model for assessment of picture naming abilities in aphasia.

机构信息

Department of Cognitive Sciences, University of California, Irvine.

Department of Communication Sciences and Disorders, University of South Carolina.

出版信息

Psychol Assess. 2018 Jun;30(6):809-826. doi: 10.1037/pas0000529. Epub 2018 Mar 19.

Abstract

Picture naming impairments are a typical feature of stroke-induced aphasia. Overall accuracy and rates of different error types are used to make inferences about the severity and nature of damage to the brain's language network. Currently available assessment tools for picture naming accuracy treat it as a unidimensional measure, while assessment tools for error types treat items homogenously, contrary to findings from psycholinguistic investigations of word production. We created and tested a new cognitive psychometric model for assessment of picture naming responses, using cognitive theory to specify latent processing decisions during the production of a naming attempt, and using item response theory to separate the effects of item difficulty and participant ability on these internal processing decisions. The model enables multidimensional assessment of latent picture naming abilities on a common scale, with a relatively large cohort for normative reference. We present the results of 4 experiments testing our interpretation of the model's parameters, as they apply to picture naming predictions, lexical properties of the items, statistical properties of the lexicon, and participants' scores on other tests. We also created a website for researchers and clinicians to analyze item-level data using our model, providing estimates of latent abilities and percentile scores, as well as credible intervals to help gauge the reliability of the estimated model parameters and identify meaningful changes. To the extent that the model is successful, the estimated parameter values may aid in treatment decisions and progress monitoring, or they may help elucidate the functional properties of brain networks. (PsycINFO Database Record

摘要

图像命名障碍是中风引起的失语症的典型特征。整体准确性和不同错误类型的比率被用来推断大脑语言网络损伤的严重程度和性质。目前用于图像命名准确性的评估工具将其视为单一维度的衡量标准,而用于错误类型的评估工具则将项目均质化处理,这与心理语言学对单词生成的研究结果相悖。我们创建并测试了一种新的认知心理计量学模型,用于评估图像命名反应,该模型使用认知理论来指定命名尝试过程中的潜在处理决策,并使用项目反应理论来分离项目难度和参与者能力对这些内部处理决策的影响。该模型能够在共同的量表上对潜在的图像命名能力进行多维评估,并具有较大的规范参考群体。我们介绍了 4 项实验的结果,这些实验检验了我们对模型参数的解释,这些参数适用于图像命名预测、项目的词汇特性、词汇的统计特性以及参与者在其他测试中的得分。我们还为研究人员和临床医生创建了一个网站,以便使用我们的模型分析项目级别的数据,提供潜在能力和百分位数得分的估计值,以及可信区间,以帮助评估估计模型参数的可靠性并识别有意义的变化。在模型成功的情况下,估计的参数值可能有助于治疗决策和进展监测,或者有助于阐明大脑网络的功能特性。

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