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

Haomiao Jin; Doerte U Junghaenel; Bart Orriens; Pey-Jiuan Lee; Stefan Schneider

Journal paper

JMIR Research Protocols

2023

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.