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北京版蒙特利尔认知评估量表作为轻度认知障碍的简易筛查工具:一项基于社区的研究。

The Beijing version of the Montreal Cognitive Assessment as a brief screening tool for mild cognitive impairment: a community-based study.

机构信息

Center on Ageing Psychology, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, 4A Datun Road, Chaoyang District, Beijing, 100101, China.

出版信息

BMC Psychiatry. 2012 Sep 25;12:156. doi: 10.1186/1471-244X-12-156.


DOI:10.1186/1471-244X-12-156
PMID:23009126
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3499377/
Abstract

BACKGROUND: A cross-sectional validation study was conducted in several urban and rural communities in Beijing, China, to evaluate the effectiveness of the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) as a screening tool to detect mild cognitive impairment (MCI) among Chinese older adults. METHODS: The MoCA-BJ and the Mini-Mental State Examination (MMSE) were administered to 1001 Chinese elderly community dwellers recruited from three different regions (i.e., newly developed, old down-town, and rural areas) in Beijing. Twenty-one of these participants were diagnosed by experienced psychiatrists as having dementia, 115 participants were diagnosed as MCI, and 865 participants were considered to be cognitively normal. To analyze the effectiveness of the MoCA-BJ, we examined its psychometric properties, conducted item analyses, evaluated the sensitivity and specificity of the scale, and compared the scale with the MMSE. Demographic and regional differences among our subjects were also taken into consideration. RESULTS: Under the recommended cut-off score of 26, the MoCA-BJ demonstrated an excellent sensitivity of 90.4%, and a fair specificity (31.3%). The MoCA-BJ showed optimal sensitivity (68.7%) and specificity (63.9%) when the cut-off score was lowered to 22. Among all the seven cognitive sub-domains, delayed recall was shown to be the best index to differentiate MCI from the normal controls. Regional differences disappeared when the confounding demographic variables (i.e., age and education) were controlled. Item analysis showed that the internal consistency was relatively low in both naming and sentence repetition tasks, and the diagnostic accuracy was similar between the MoCA-BJ and the MMSE. CONCLUSIONS: In general, the MoCA-BJ is an acceptable tool for MCI screening in both urban and rural regions of Beijing. However, presumably due to the linguistic and cultural differences between the original English version and the Chinese version of the scale, and the lower education level of Chinese older adults, the MoCA-BJ is not much better than the MMSE in detecting MCI, at least for this study sample. Further modifications to several test items of the MoCA-BJ are recommended in order to improve the applicability and effectiveness of the MoCA-BJ in MCI screening among the Chinese population.

摘要

背景:本研究在北京的几个城乡社区进行了一项横断面验证研究,旨在评估北京版蒙特利尔认知评估(MoCA-BJ)作为一种筛查工具,用于检测中国老年人中的轻度认知障碍(MCI)的有效性。

方法:MoCA-BJ 和简易精神状态检查(MMSE)被用于对来自北京三个不同地区(新开发地区、老城区和农村地区)的 1001 名中国老年社区居民进行测试。其中 21 名被经验丰富的精神科医生诊断为痴呆,115 名被诊断为 MCI,865 名被认为认知正常。为了分析 MoCA-BJ 的有效性,我们检验了其心理测量学特性,进行了项目分析,评估了该量表的灵敏度和特异性,并将其与 MMSE 进行了比较。我们还考虑了研究对象的人口统计学和地区差异。

结果:在推荐的 26 分 cutoff 评分下,MoCA-BJ 表现出了极好的灵敏度 90.4%,和一般的特异性(31.3%)。当 cutoff 评分降低至 22 时,MoCA-BJ 显示出最佳的灵敏度(68.7%)和特异性(63.9%)。在所有七个认知子领域中,延迟回忆被证明是区分 MCI 和正常对照组的最佳指标。当控制混杂的人口统计学变量(即年龄和教育)时,地区差异消失了。项目分析表明,在命名和句子重复任务中,内部一致性相对较低,MoCA-BJ 和 MMSE 的诊断准确性相似。

结论:总的来说,MoCA-BJ 是一种可接受的用于北京城乡地区 MCI 筛查的工具。然而,由于量表的原始英语版本和中文版本之间的语言和文化差异,以及中国老年人的教育水平较低,MoCA-BJ 在检测 MCI 方面并不比 MMSE 好多少,至少对于本研究样本是这样。建议对 MoCA-BJ 的几个测试项目进行修改,以提高 MoCA-BJ 在中国人群 MCI 筛查中的适用性和有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92c2/3499377/386ca4ba5eb7/1471-244X-12-156-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92c2/3499377/cc1b07d03b34/1471-244X-12-156-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92c2/3499377/386ca4ba5eb7/1471-244X-12-156-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92c2/3499377/cc1b07d03b34/1471-244X-12-156-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92c2/3499377/386ca4ba5eb7/1471-244X-12-156-2.jpg

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本文引用的文献

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