Validity and Reliability Study of Online Cognitive Tracking Software (BEYNEX)

Abstract

Background: Detecting cognitive impairment such as Alzheimer’s disease early and tracking it over time is essential for individuals at risk of cognitive decline. Objective: This research aimed to validate the Beynex app’s gamified assessment tests and the Beynex Performance Index (BPI) score, which monitor cognitive performance across seven categories, considering age and education data. Methods: Beynex test cut-off scores of participants (n = 91) were derived from the optimization function and compared to the Montreal Cognitive Assessment (MoCA) test. Validation and reliability analyses were carried out with data collected from an additional 214 participants. Results: Beynex categorization scores showed a moderate agreement with MoCA ratings (weighted Cohen’s Kappa = 0.48; 95% CI: 0.38–0.60). Calculated Cronbach’s Alpha indicates good internal consistency. Test-retest reliability analysis using a linear regression line fitted to results yielded R∧2 of 0.65 with a 95% CI: 0.58, 0.71. Discussion: Beynex’s ability to reliably detect and track cognitive impairment could significantly impact public health, early intervention strategies and improve patient outcomes.