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三十五年来对衰老的计算机化认知评估——我们如今处于什么阶段?

Thirty-Five Years of Computerized Cognitive Assessment of Aging-Where Are We Now?

作者信息

Sternin Avital, Burns Alistair, Owen Adrian M

机构信息

Brain and Mind Institute, Department of Psychology, University of Western Ontario, London, ON N6A 3K7, Canada.

Division of Neuroscience & Experimental Psychology, Manchester Institute for Collaborative Research on Ageing, School of Social Sciences, University of Manchester, Manchester M13 9PL, UK.

出版信息

Diagnostics (Basel). 2019 Sep 6;9(3):114. doi: 10.3390/diagnostics9030114.

DOI:10.3390/diagnostics9030114
PMID:31489940
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6787729/
Abstract

Over the past 35 years, the proliferation of technology and the advent of the internet have resulted in many reliable and easy to administer batteries for assessing cognitive function. These approaches have great potential for affecting how the health care system monitors and screens for cognitive changes in the aging population. Here, we review these new technologies with a specific emphasis on what they offer over and above traditional 'paper-and-pencil' approaches to assessing cognitive function. Key advantages include fully automated administration and scoring, the interpretation of individual scores within the context of thousands of normative data points, the inclusion of 'meaningful change' and 'validity' indices based on these large norms, more efficient testing, increased sensitivity, and the possibility of characterising cognition in samples drawn from the general population that may contain hundreds of thousands of test scores. The relationship between these new computerized platforms and existing (and commonly used) paper-and-pencil tests is explored, with a particular emphasis on why computerized tests are particularly advantageous for assessing the cognitive changes associated with aging.

摘要

在过去35年里,技术的普及和互联网的出现带来了许多用于评估认知功能的可靠且易于实施的测试组合。这些方法对于影响医疗保健系统监测和筛查老年人群认知变化的方式具有巨大潜力。在此,我们回顾这些新技术,特别强调它们相对于传统“纸笔”评估认知功能方法的优势。主要优势包括完全自动化的施测和评分、在数千个常模数据点的背景下对个体分数的解读、基于这些大量常模纳入“有意义变化”和“效度”指标、更高效的测试、更高的敏感性,以及对可能包含数十万测试分数的普通人群样本进行认知特征描述的可能性。我们探讨了这些新的计算机化平台与现有的(且常用的)纸笔测试之间的关系,特别强调了计算机化测试在评估与衰老相关的认知变化方面特别有利的原因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/2ae139084554/diagnostics-09-00114-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/936c3bbb540e/diagnostics-09-00114-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/3c121c5c7064/diagnostics-09-00114-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/2ae139084554/diagnostics-09-00114-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/936c3bbb540e/diagnostics-09-00114-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/3c121c5c7064/diagnostics-09-00114-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d6c/6787729/2ae139084554/diagnostics-09-00114-g003.jpg

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