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根据词汇分数预测波士顿命名测试表现:解释的初步指南

Prediction of Boston Naming Test performance from vocabulary scores: preliminary guidelines for interpretation.

作者信息

Killgore W D, Adams R L

机构信息

University of Pennsylvania School of Medicine, USA.

出版信息

Percept Mot Skills. 1999 Aug;89(1):327-37. doi: 10.2466/pms.1999.89.1.327.

Abstract

Patients with limited education or underdeveloped vocabulary skills may perform below the normal range on the Boston Naming Test when compared to the original published norms, even in the absence of brain damage. To reduce the frequency of false positive dysnomic classifications of patients with limited vocabulary skills, we developed a score adjustment to account for the significant shared variance between scores on this test and the WAIS-R Vocabulary subtest. Vocabulary significantly predicted performance on the Boston Naming Test (r = .65, p < .0001) in a sample of 62 outpatients who had no objective evidence of brain damage. Linear regression was used to derive expected performance on the Boston Naming Test from Vocabulary scaled scores. Relative to the original published norms, scores based on the Vocabulary subtest cut-offs produced fewer false positives and more accurately classified group membership for patients with and without objectively verified brain damage. These performance predictions are offered as tentative guidelines to assist clinicians in evaluating the presence of naming deficits by controlling for the variance associated with knowledge of vocabulary.

摘要

与最初公布的常模相比,受教育程度有限或词汇技能发展不完善的患者在波士顿命名测试中的表现可能低于正常范围,即使在没有脑损伤的情况下也是如此。为了减少词汇技能有限的患者出现假阳性失命名分类的频率,我们开发了一种分数调整方法,以考虑该测试分数与韦氏成人智力量表修订版(WAIS-R)词汇子测试分数之间显著的共同方差。在62名无客观脑损伤证据的门诊患者样本中,词汇量显著预测了波士顿命名测试的表现(r = 0.65,p < 0.0001)。使用线性回归从词汇量表分数得出波士顿命名测试的预期表现。相对于最初公布的常模,基于词汇子测试临界值的分数产生的假阳性更少,并且对于有和没有客观证实脑损伤的患者,能更准确地对组归属进行分类。这些表现预测作为初步指南提供,以帮助临床医生通过控制与词汇知识相关的方差来评估命名缺陷的存在。

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