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重新审视阿尔茨海默病命名准确性和错误的预测因素。

A fresh look at the predictors of naming accuracy and errors in Alzheimer's disease.

机构信息

University of Oviedo, Spain.

出版信息

J Neuropsychol. 2012 Sep;6(2):242-56. doi: 10.1111/j.1748-6653.2011.02025.x. Epub 2012 Jan 27.

DOI:10.1111/j.1748-6653.2011.02025.x
PMID:22284909
Abstract

In recent years, a considerable number of studies have tried to establish which characteristics of objects and their names predict the responses of patients with Alzheimer's disease (AD) in the picture-naming task. The frequency of use of words and their age of acquisition (AoA) have been implicated as two of the most influential variables, with naming being best preserved for objects with high-frequency, early-acquired names. The present study takes a fresh look at the predictors of naming success in Spanish and English AD patients using a range of measures of word frequency and AoA along with visual complexity, imageability, and word length as predictors. Analyses using generalized linear mixed modelling found that naming accuracy was better predicted by AoA ratings taken from older adults than conventional ratings from young adults. Older frequency measures based on written language samples predicted accuracy better than more modern measures based on the frequencies of words in film subtitles. Replacing adult frequency with an estimate of cumulative (lifespan) frequency did not reduce the impact of AoA. Semantic error rates were predicted by both written word frequency and senior AoA while null response errors were only predicted by frequency. Visual complexity, imageability, and word length did not predict naming accuracy or errors.

摘要

近年来,相当数量的研究试图确定物体的哪些特征及其名称可以预测阿尔茨海默病(AD)患者在图片命名任务中的反应。词的使用频率及其习得年龄(AoA)被认为是两个最具影响力的变量,高频、早习得的名称对命名的保留效果最佳。本研究使用一系列词频和 AoA 测量指标以及视觉复杂性、图像可识别性和词长作为预测指标,对西班牙语和英语 AD 患者的命名成功率预测因素进行了新的研究。使用广义线性混合模型的分析发现,命名准确性更好地由来自老年人的 AoA 评分预测,而不是由年轻人的传统评分预测。基于书面语料库的较旧频率测量比基于电影字幕中单词频率的更现代测量更能准确预测准确率。用累积(寿命)频率代替成人频率并不能降低 AoA 的影响。语义错误率由书面词汇频率和老年人 AoA 共同预测,而空响应错误仅由频率预测。视觉复杂性、图像可识别性和词长不能预测命名准确性或错误。

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