Developing Early Markers of Cognitive Decline and Dementia Derived From Survey Response Behaviors: Protocol for Analyses of Preexisting Large-scale Longitudinal Data.
Developing Early Markers of Cognitive Decline and Dementia Derived From Survey Response Behaviors: Protocol for Analyses of Preexisting Large-scale Longitudinal Data.
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开发从调查反应行为得出的认知下降和痴呆症的早期标记：用于大规模纵向数据的分析方案。
DOI：
10.2196/44627
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发表时间：
2023-02-21
影响因子：
1.7
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中科院分区：
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越来越多的证据表明，日常功能的细微变化是预测认知能力下降和痴呆症的最早和最强烈的信号之一。调查是日常功能的一小部分；然而，完成一项调查是一项复杂且对认知要求很高的任务，需要注意力、工作记忆、执行功能以及短期和长期记忆。检查老年人的调查回应行为，其重点是调查对象如何完成调查，而不考虑问题所寻求的内容，可能是一种有价值但经常被忽视的资源，可以用来开发基于行为的认知衰退和痴呆症的早期标记，这种标记具有成本效益，不引人注目，并且可扩展，可用于大量人口样本。本文描述了一项由美国国家老龄化研究所资助的多年研究项目的方案，该项目旨在从老年人的调查反应行为中开发认知能力下降和痴呆的早期标志物。创建了两类指标，总结了老年人调查反应行为的不同方面。微妙的报告错误指数是从问卷的回答模式，在一些人口为基础的纵向老龄化研究。与此同时，para-data索引是从一个大型基于网络的小组研究的后端服务器上记录的计算机使用行为生成的，该研究被称为“了解美国研究”（UAS）。将对所创建的问卷答案模式和准数据指标的属性进行深入检查，以评估其并发效度、变化敏感性和预测效度。我们将使用个体参与者数据荟萃分析对指标进行综合，并进行特征选择，以确定预测认知能力下降和痴呆的指标的最佳组合。截至2022年10月，我们已经确定了15项纵向老龄化研究作为创建问卷答案模式指数的合格数据源，并从2014年中期至2015年期间进行的15项UAS调查中获得了准数据。共确定了20个问卷答案模式指数和20个准数据指数。我们进行了一项初步调查，以测试问卷回答模式和准数据指数对预测认知能力下降和痴呆的效用。这些早期的结果仅基于指数的一个子集，但暗示了我们预计将从许多不同研究中得出的多种行为指数的计划分析中得出的结果。调查反应行为是一种相对廉价的数据来源，但很少直接用于老年认知障碍的流行病学研究。这项研究有望开发出一种创新而非传统的方法，可以补充现有的旨在早期发现认知能力下降和痴呆的方法。derr1 - 10.2196/44627
Accumulating evidence shows that subtle alterations in daily functioning are among the earliest and strongest signals that predict cognitive decline and dementia. A survey is a small slice of everyday functioning; nevertheless, completing a survey is a complex and cognitively demanding task that requires attention, working memory, executive functioning, and short- and long-term memory. Examining older people’s survey response behaviors, which focus on how respondents complete surveys irrespective of the content being sought by the questions, may represent a valuable but often neglected resource that can be leveraged to develop behavior-based early markers of cognitive decline and dementia that are cost-effective, unobtrusive, and scalable for use in large population samples. This paper describes the protocol of a multiyear research project funded by the US National Institute on Aging to develop early markers of cognitive decline and dementia derived from survey response behaviors at older ages. Two types of indices summarizing different aspects of older adults’ survey response behaviors are created. Indices of subtle reporting mistakes are derived from questionnaire answer patterns in a number of population-based longitudinal aging studies. In parallel, para-data indices are generated from computer use behaviors recorded on the backend server of a large web-based panel study known as the Understanding America Study (UAS). In-depth examinations of the properties of the created questionnaire answer pattern and para-data indices will be conducted for the purpose of evaluating their concurrent validity, sensitivity to change, and predictive validity. We will synthesize the indices using individual participant data meta-analysis and conduct feature selection to identify the optimal combination of indices for predicting cognitive decline and dementia. As of October 2022, we have identified 15 longitudinal ageing studies as eligible data sources for creating questionnaire answer pattern indices and obtained para-data from 15 UAS surveys that were fielded from mid-2014 to 2015. A total of 20 questionnaire answer pattern indices and 20 para-data indices have also been identified. We have conducted a preliminary investigation to test the utility of the questionnaire answer patterns and para-data indices for the prediction of cognitive decline and dementia. These early results are based on only a subset of indices but are suggestive of the findings that we anticipate will emerge from the planned analyses of multiple behavioral indices derived from many diverse studies. Survey response behaviors are a relatively inexpensive data source, but they are seldom used directly for epidemiological research on cognitive impairment at older ages. This study is anticipated to develop an innovative yet unconventional approach that may complement existing approaches aimed at the early detection of cognitive decline and dementia. DERR1-10.2196/44627