Remote Digital Measurement of Facial and Vocal Markers of Major Depressive Disorder Severity and Treatment Response: A Pilot Study - Abbas, Anzar; Sauder, Colin; Yadav, Vijay; Koesmahargyo, Vidya; Aghjayan, Allison; Marecki, Serena; Evans, Miriam; Galatzer-Levy, Isaac R. (Frontiers in Digital Health, 2021)
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 = 18). MDD diagnosis was confirmed using the Mini International Neuropsychiatric Interview (MINI) and the Montgomery-Asberg Depression Rating Scale (MADRS) was collected concordantly to 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 significantly decreased frequency of fear and anger facial expressions. Conclusion: Digital markers associated with MDD demonstrate validity as measures of treatment response.