Remote Digital Measurement of Facial and Vocal Markers of Major Depressive Disorder Severity and Treatment Response: A Pilot Study

Abstract

Abstract Objectives Multiple machine learning-based visual and auditory digital markers have demonstrated associations between Major Depressive Disorder (MDD) status and severity. The current study examines if such measurements can quantify response to antidepressant treatment (ADT) with selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine uptake inhibitors (SNRIs). Methods Visual and auditory markers were acquired through an automated smartphone task that measures facial, vocal, and head movement characteristics across four weeks of treatment (with timepoints at baseline, 2 weeks, and 4 weeks) on ADT (n = 12). The Montgomery-Asberg Depression Rating Scale (MADRS) was collected concordantly through clinical interviews to confirm diagnosis and assess changes in MDD severity. Results Patient responses to ADT demonstrated clinically and statistically significant changes in the MADRS F(2,34) = 51.62, p <.0001. Additionally, patients demonstrated significant increases in multiple digital markers including facial expressivity, head movement, and amount of speech. Finally, patients demonstrated significant decreased frequency of fear and anger facial expressions. Conclusion Digital markers associated with MDD demonstrate validity as measures of treatment response.

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