The development and validation of a digital biomarker for remote assessment of Alzheimer's diseases risk

Abstract

Background Digital cognitive assessment is becoming increasingly widespread in ageing research and care, especially since the COVID-19 pandemic. Remote online collection provides opportunities for ageing and dementia professionals to collect larger datasets, increase the diversity of research participants and patients and offer cost-effective screening and monitoring methods for clinical practice and trials. However, the reliability of self-administered at-home tests compared to their lab-based counterparts often goes unexamined, compromising the validity of adopting such measures. Objective Our aim is to validate a self-administered web-based version of the visual short-term memory binding task (VSTMBT), a potential digital biomarker sensitive to Alzheimer's disease processes, suitable for use on personal devices. Methods A final cross-sectional sample of 37 older-adult (51–77 years) participants without dementia completed our novel self-administered version of the VSTMBT, both at home on a personal device and in the lab, under researcher-controlled conditions. Results ANOVA and Bayesian t-test found no significant differences between the task when it was remotely self-administered by participants at home compared to when it was taken under controlled lab conditions. Conclusions These results indicate the VSTMBT can provide reliable data when self-administered at-home using an online version of the task and on a personal device. This finding has important implications for remote screening and monitoring practices of older adults, as well as supporting clinical practices serving diverse patient communities. Future work will assess remote administration in older adults with cognitive impairment and diverse socio-economic and ethno-cultural backgrounds as well as a bench-to-bedside application.

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“…The extracted features are then fed into a machine learning classifier, such as neural networks (NN), decision tree, and support vector machine (SVM), to distinguish between PD and non-PD cases ( 90 , 92 , 97 ). Mobile technology and the use of digital markers has recently been successfully validated for the self-administered, at-home assessment of Alzheimer’s disease risk to allow remote screening to support clinical assessment ( 98 ). Another digital strategy that is currently being evaluated in a clinical trial in people with Alzheimer’s disease (NCT05027789), is what is termed a “Brain Boosters” intervention, which combines memory training and promotion of healthy lifestyle behaviors which are implemented and monitored using a digital application ( 99 ).…”