Psychometric Properties of a Novel Affective Bias Task and Its Application in Clinical and Nonclinical Populations

Abstract

To mitigate limitations of self-reported mood assessments, we introduce a novel affective bias task. The task quantifies instantaneous emotional state by leveraging the phenomenon of affective bias, in which people interpret external emotional stimuli in a manner consistent with their current emotional state. This study establishes task stability in measuring and tracking depressive symptoms in clinical and nonclinical populations. Initial assessment in a large nonclinical sample established normative ratings. Depressive symptoms were measured and compared with task performance in a nonclinical sample, as well as in a clinical cohort of individuals who were undergoing surgical evaluation for severe epilepsy. In both cohorts, a stronger negative affective bias was associated with a higher Beck Depression Inventory-II score. The affective bias task exhibited high stability and interrater reliability as well as construct validity in predicting depression levels in both cohorts, suggesting that the task is a reliable proxy for mood and a diagnostic tool for detecting depressive symptoms.