Using Voice Biomarkers to Predict the Likelihood of Major Depressive Disorder

Using Voice Biomarkers to Predict the Likelihood of Major Depressive Disorder: A Multi-Site Fully Remote E-Clinical Validation Study

Major Depressive Disorder (MDD) is the leading cause of disability worldwide. Depression and anxiety disorders are among the most prevalent of all mental disorders, with an estimated annual prevalence of 9.7% and 18.1% respectively. It has been known for the last 100 years that depression and anxiety both likely affect vocal acoustic properties. In 1921, Emil Kraepelin, characterized depressed patient's voices as having a lower pitch, lower volume, lower rate of speech, more monotony of prosody as well as more hesitations, stuttering, and whispering. Mechanistically, it is possible that the neural circuitry involved in the pathophysiology of mood and anxiety disorders impinge upon the neural circuit involved in speech production, affecting qualities that include rate, prosody, speech latency and other paralinguistic features. Thus, acoustic features of speech may be one of the more readily accessible biomarkers for these conditions. Given this understanding, the investigators sought to develop a passive vocal biomarker instrument for depression and anxiety screening that could markedly expand access as well as standardize the quality of screening in primary care settings.

Using Voice Biomarkers to Predict the Likelihood of Major Depressive Disorder

Recruitment

Summary

Participation Requirements

Description

Tracking Information