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修订版简易视觉空间记忆测试的老年人结构效度及扩展常模数据。

Construct validity and extended normative data for older adults for the Brief Visuospatial Memory Test, Revised.

作者信息

Kane Katherine D, Yochim Brian P

机构信息

Department of Psychology, University of Colorado at Colorado Springs, Colorado Springs, CO, USA

Department of Psychiatry and Behavioral Sciences, VA Palo Alto Healthcare System, Stanford University School of Medicine, Stanford, CA, USA.

出版信息

Am J Alzheimers Dis Other Demen. 2014 Nov;29(7):601-6. doi: 10.1177/1533317514524812. Epub 2014 Mar 6.

Abstract

PURPOSE

This study examined the construct validity of a visual memory test (Brief Visuospatial Memory Test, Revised [BVMT-R]) in a sample of older adults and provided normative data for adults aged 80+ years.

METHOD

The sample included 109 community-dwelling individuals (mean [M] age = 74.9 years, M education = 15.0 years, 62.4% female, and 97.2% European American).

PROCEDURES

Measures administered included the BVMT-R, California Verbal Learning Test, 2nd edition, and subtests of the Delis-Kaplan Executive Function System and Neuropsychological Assessment Battery.

RESULTS

The BVMT-R correlated highly with another measure of memory and less so with unrelated measures (e.g., verbal fluency). Age and education were significantly correlated with BVMT-R Total and Delayed Recall scores, with education as the strongest predictor. No significant differences were found for sex. Normative data were provided for adults aged 80 to 88 years (n = 29).

CONCLUSIONS

Adequate evidence was found for convergent validity and only partial support for discriminant validity. Normative data should continue to be stratified by age and also by formal education level.

摘要

目的

本研究在老年人群样本中检验了一种视觉记忆测试(简明视觉空间记忆测试修订版[BVMT-R])的结构效度,并为80岁及以上成年人提供了常模数据。

方法

样本包括109名居住在社区的个体(平均年龄=74.9岁,平均受教育年限=15.0年,女性占62.4%,非裔美国人占97.2%)。

程序

所实施的测量包括BVMT-R、加利福尼亚言语学习测试第二版,以及德利斯科-卡普兰执行功能系统和神经心理评估量表的子测试。

结果

BVMT-R与另一项记忆测量高度相关,与不相关测量(如言语流畅性)的相关性较低。年龄和受教育程度与BVMT-R总分及延迟回忆得分显著相关,其中受教育程度是最强的预测因素。未发现性别存在显著差异。为80至88岁成年人(n=29)提供了常模数据。

结论

发现了足够的证据支持聚合效度,但仅部分支持区分效度。常模数据应继续按年龄以及正规教育水平进行分层。

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