Evaluating High-Frequency Automated Cognitive Tasks Across Immune-Mediated Inflammatory Disease and Neurodegenerative Disease Patients.

This analysis evaluates the feasibility and psychometric properties of daily digital cognitive assessments (DCAs) delivered on smartphones using data from the large, international Identifying Digital Endpoints to Assess FAtigue, Sleep and acTivities of daily living in Neurodegenerative disorders and Immune-mediated inflammatory diseases (IDEA-FAST) study. The data we analyse were collected from patients with neurodegenerative diseases (NDDs) and immune-mediated inflammatory diseases (IMIDs), and healthy controls (a subset who participated in all phases of the study, total N=977) in their own homes. These data were obtained alongside data from other devices that monitored physiology, kinematics, and sleep quality. Following a baseline visit, participants were remotely monitored via three scheduled daily sessions for 6-7 days in each of 4 active assessment phases (APs). APs were separated by 6-week intervals. Daily schedules comprised a morning psychomotor vigilance task (PVT) with eDiary, afternoon session (eDiary only), and an evening digit symbol substitution task (DSST) with eDiary. We evaluated session coverage using logistic mixed effects, test-retest reliability using ICCs, disease impacts on performance using linear mixed effect ANCOVA, and familiarisation using linear mixed effects. Overall coverage was 67.5% for the PVT and 77.0% for the DSST, with no significant differences between the healthy volunteers and disease cohorts. Coverage varied significantly by time-of-day (Evening > Morning > Afternoon), and improved with age, with an interaction revealing session time-of-day affected older participants less, all p < .001. Coverage was highest in AP 1 and reduced in subsequent APs. AP-day effects on coverage interacted significantly with AP, with a modest decline over AP 1, and the pattern reversed in APs 2-4. Baseline reliability was good (> .70) for both PVT mean reaction time and DSST total correct across all cohorts, and the movement-based measure from the DSST ranged [.55, .75], with lower values in the Parkinson's Disease and Primary Sjogren's Syndrome cohorts. Both tasks showed significant cohort effects, with performance in IMID cohorts intermediate between healthy controls and NDD. Longitudinal analysis revealed significant familiarisation effects in DSST. This was greatest in healthy controls, with significant attenuation of these effects in disease cohorts. No effect of familiarisation was seen in the PVT. Collectively, these results support the usefulness of at-home cognitive assessment on smartphones. Brief measures of cognition can be captured remotely in disease as well as controls with good adherence and sensitivity to distinguish known patient groups from healthy controls.