Ambulatory Methods for Measuring Cognitive Change

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Project Summary Accurate and sensitive measurement of cognitive change is required to advance understanding of normative cognitive aging and neurocognitive impairments, such as Alzheimer's disease. Unfortunately, methodological barriers that constrain temporal precision and introduce confounds in impede progress in the study of cognitive change. Mobile assessment approaches afford novel opportunities to overcome these barriers by mitigating geographic, space and personnel constraints imposed by in-person cognitive testing. We believe that using mobile technology to assess cognition “anytime, anyplace” holds great potential to transform biomedical research by improving detection and accurate monitoring of cognitive change. We will develop cognitive tests and software for use in ecological momentary assessment (EMA) measurement burst studies, an intensive longitudinal design which involves bursts of frequent, repeated assessments in naturalistic environments. We will also use mobile assessments to enhance traditional longitudinal designs by incorporating novel designs features (e.g., double- baseline assessments), and by increasing the frequency of longitudinal assessments. In response to RFA-AG-18-012, we propose to develop infrastructure for the Mobile Monitoring of Cognitive Change (M2C2) that will provide the research community with open, flexible, and usable tools to enable scientific progress that depends on the sensitive and accurate measurement of cognitive change. We will build this infrastructure by accomplishing the following aims. First, we will establish rapid iterative piloting and test development procedures that accelerate our capacity to prototype, deploy, evaluate, and optimize candidate mobile cognitive tests to meet psychometric, accessibility, and engagement benchmarks (Aim 1: Iterative Design & Piloting). Second, evaluate reliability, construct validity, and longitudinal validity of mobile cognitive testing procedures (Aim 2: Reliability & Validity) in a racially diverse probability sample. Third, we replicate psychometric results in an independent, nationally representative probability based sample, and create nationally representative norms (Aim 3: Replication). And fourth, we will test our pipeline and procedures for incorporating new measures into the mobile assessment infrastructure by evaluating novel measures for inclusion that are nominated by investigators outside of our immediate research team (Aim 4: Extension).