Cognitive decline monitoring through a web-based application

Abstract

Cognitive decline usually begins after individuals reach maturity, which is more evident in late adulthood. Rapid and constant cognitive screenings allow early detection of cognitive decline and motivate individuals to participate in prevention interventions. Due to accelerated technological advances, cognitive screening and training are now available to the layperson using electronic devices connected to the internet. Large datasets generated by these platforms provide a unique opportunity to explore cognitive development throughout life and across multiple naturalistic environments. However, such data collection mechanisms must be validated. This study aimed to determine whether the data gathered by commercial visuospatial and phonological working memory tests (CogniFit Inc., San Francisco, USA) confirm the well-established argument that age predicts cognitive decline. Data from 3,212 participants (2,238 females) who were 45 years old or older were analyzed. A linear regression analysis explored the relationship between age and working memory while controlling for gender, sleep quality, and physical activity (variables that are known to affect working memory). We found that age negatively predicts working memory. Furthermore, there was an interaction between age and gender for visuospatial working memory, indicating that although male participants significantly outperformed females, the relationship between age and working memory differs for females and males. Our results suggest that the computerized assessment of visuospatial and phonological working memory is sensible enough to predict cognitive functions in aging. Suggestions for improving the sensitivity of self-reports are discussed. Further studies must explore the nature of gender effects on cognitive aging.

Keywords: age-associated cognitive decline; aging; cognitive decline; naturalistic environment; physical activity; sleep quality; working memory.