Psychometric Properties of a Novel Affective Bias Task and its Application in Clinical and Non-Clinical Populations

To mitigate limitations in self-reported mood assessments, we introduce a novel affective bias task (ABT). 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 non-clinical populations. Initial assessment in a large non-clinical sample established normative ratings. Depressive symptoms were tracked relative to task performance in a non-clinical sample, as well as in a clinical cohort undergoing surgical evaluation for severe epilepsy. In both cohorts, a stronger negative affective bias was associated with higher Beck Depression Inventory (BDI-II) scores. The ABT exhibits high stability and interrater reliability, as well as construct validity in predicting depression levels in both cohorts, suggesting the task as a reliable proxy for mood and a diagnostic tool for detecting depressive symptoms.