Capturing Cognitive Aging in Vivo: Application of a Neuropsychological Framework for Emerging Digital Tools

Abstract

As the global burden of dementia continues to plague our healthcare systems, efficient, objective, and sensitive tools to detect neurodegenerative disease and capture meaningful changes in everyday cognition are increasingly needed. Emerging digital tools present a promising option to address many drawbacks of current approaches, with contexts of use that include early detection, risk stratification, prognosis, and outcome measurement. However, conceptual models to guide hypotheses and interpretation of results from digital tools are lacking and are needed to sort and organize the large amount of continuous data from a variety of sensors. In this viewpoint, we propose a neuropsychological framework for use alongside a key emerging approach—digital phenotyping. The Variability in Everyday Behavior (VIBE) model is rooted in established trends from the neuropsychology, neurology, rehabilitation psychology, cognitive neuroscience, and computer science literature and links patterns of intraindividual variability, cognitive abilities, and everyday functioning across clinical stages from healthy to dementia. Based on the VIBE model, we present testable hypotheses to guide the design and interpretation of digital phenotyping studies that capture everyday cognition in vivo. We conclude with methodological considerations and future directions regarding the application of the digital phenotyping approach to improve the efficiency, accessibility, accuracy, and ecological validity of cognitive assessment in older adults.

Digital Health Technologies for Alzheimer’s Disease and Related Dementias: Initial Results from a Landscape Analysis and Community Collaborative Effort

“…The dominance of technologies assessing memory (short term, long term, working), executive function, attention, processing speed, verbal fluency, and visuospatial processing document an increasingly digital shift within neuropsychological assessment, illustrating the ongoing desire of clinicians to assess functional status in real world settings (39) even as they grapple with concerns around ecological validity (25, 40) and the conceptual and administrative challenges that occur when moving from a traditional test setting (administered in person by a trained clinician in a controlled environment) to remote assessment where variations in technology, computer literacy, and environmental factors, and the presence or lack of supervision by a trained observer must all be considered (40, 41). While further research is needed to assuage these concerns, data continues to emerge illustrating that innovative digital assessment modalities can successfully discriminate between healthy controls and individuals in early stages of Alzheimer’s disease (42).…”

“…DHTs focused on cognition and memory are unsurprisingly prevalent in our results. providing a "digital phenotype" [24] that captures a comprehensive in-situ portrait of someone's daily functional and cognitive status, providing a better window into a patient's emotional state, social patterns, and physical experiences to generate research insights and guide clinical care in ways that are meaningful to patients [25].…”

Diagnosing homo digitalis: towards a standardized assessment for digital tool competencies

“…Digital tool use has gained growing importance not only for the area of health improvement but also in medical diagnostics. For example, current literature discusses approaches that target cognitive digital phenotyping by capturing everyday cognition in vivo via digital tool use ( Hackett and Giovannetti, 2022 ). As some studies suggest that app use can predict cognitive performance decline ( Gordon et al, 2019 ), the idea of cognitive digital phenotyping would be, for example, to contribute to early diagnosis of dementia by evaluating a person’s app using behavior ( Hackett and Giovannetti, 2022 ).…”

“…For example, current literature discusses approaches that target cognitive digital phenotyping by capturing everyday cognition in vivo via digital tool use ( Hackett and Giovannetti, 2022 ). As some studies suggest that app use can predict cognitive performance decline ( Gordon et al, 2019 ), the idea of cognitive digital phenotyping would be, for example, to contribute to early diagnosis of dementia by evaluating a person’s app using behavior ( Hackett and Giovannetti, 2022 ). The inevitable growth in these approaches promises increasing gains and advantages but faces many challenges including participation of vulnerable groups.…”

Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases

“…Moreover, AI shows the potential to assist with the detection of early-stage dementia, offering cost-effective and objective methods [ 71 ]. Furthermore, an increasing array of Medtech tools are being developed to monitor daily routines and behaviors, capturing early cognitive changes indicative of NDs [ 72 ].…”