The Association Between Cognitive Functioning and Depression Severity: A Multiwave Longitudinal Remote Assessment Study

Abstract

Cognitive difficulties are prevalent in depression and are linked to various negative life outcomes such as psychosocial impairment, absenteeism, lower chance of recovery or remission, and overall poor quality of life. Thus, assessing cognitive functioning over time is key to expanding our understanding of depression. Recent methodological advances and the ubiquity of smartphones enable remote assessment of cognitive functioning through smartphone-based tasks and surveys. However, the association of smartphone-based assessments of cognitive functioning to depression severity remains underexplored. Using a dedicated mobile application for assessing cognitive functioning (THINC-it), we investigate within- and between-person associations between performance-based (attention, working memory, processing speed, attention switching) and self-report measures of cognitive functioning with depression severity in 475 participants from the RADAR-MDD (Remote Assessment of Disease and Relapse-Major Depressive Disorder) cohort study (t = 2036 observations over an average of 14 months of follow-up). At the between-person level, we found stronger negative associations between the self-reported cognitive functioning measure and depression severity (β = −0.649, p  < 0.001) than between the performance-based measures and depression severity (βs = −0.220 to −0.349, p_s  < 0.001). At the within-person level, we found negative associations between depression severity and the self-reported measure (β = −0.223, p  < 0.001), processing speed (β = −0.026, p = 0.032) and attention (β = −0.037, p = 0.003). These findings suggest that although THINC-it could adequately and remotely detect poorer cognitive performance in people with higher depressive symptoms, it was not capable of tracking within-person change over time. Nonetheless, repeatedly measuring self-reports of cognitive functioning showed more potential in tracking within-person changes in depression severity, underscoring their relevance for patient monitoring.