Capturing Learning Curves With the Multiday Boston Remote Assessment of Neurocognitive Health (BRANCH): Feasibility, Reliability, and Validity

Objective: Unsupervised remote digital cognitive assessment makes frequent testing feasible and allows for measurement of learning over repeated evaluations on participants’ own devices. This provides the opportunity to derive individual multiday learning curve scores over short intervals. Here, we report feasibility, reliability, and validity, of a 7-day cognitive battery from the Boston Remote Assessment for Neurocognitive Health (Multiday BRANCH), an unsupervised web-based assessment. Method: Multiday BRANCH was administered remotely to 181 cognitively unimpaired older adults using their own electronic devices. For 7 consecutive days, participants completed three tests with associative memory components (Face–Name, Groceries–Prices, Digit Signs), using the same stimuli, to capture multiday learning curves for each test. We assessed the feasibility of capturing learning curves across the 7 days. Additionally, we examined the reliability and associations of learning curves with demographics, and traditional cognitive and subjective report measures. Results: Multiday BRANCH was feasible with 96% of participants completing all study assessments; there were no differences dependent on type of device used (t = 0.71, p =.48) or time of day completed (t = −0.08, p =.94). Psychometric properties of the learning curves were sound including good test–retest reliability of individuals’ curves (intraclass correlation = 0.94). Learning curves were positively correlated with in-person cognitive tests and subjective report of cognitive complaints. Conclusions: Multiday BRANCH is a feasible, reliable, and valid cognitive measure that may be useful for identifying subtle changes in learning and memory processes in older adults. In the future, we will determine whether Multiday BRANCH is predictive of the presence of preclinical Alzheimer’s disease.