Participants will be recruited to complete self reported surveys normally used as standards of care for screening and monitoring depression and anxiety symptom severity, provide a voice sample composed of an answer to open ended questions and then be assessed by a mental health professional using structured and clinically validated assessment tools for depression and anxiety. Their voice will be analyzed by machine learning models that predict the severity of depression and anxiety symptoms. The models' performance will be compared to the clinician assessments and how that correlation compares to a similar comparison between the clinician assessments with the self reported surveys. It is hypothesized that the performance of the machine learning models in assessing the severity of depression and anxiety symptoms is no worse than the self reported surveys when both are compared to clinician assessments. It is also hypothesized that presence or absence of the diagnoses of Major Depressive Disorder and Generalized Anxiety Disorder can be predicted better than chance by the analysis of the participant's voice sample using machine learning models.
Study Type
OBSERVATIONAL
Enrollment
540
Ellipsis Health
San Francisco, California, United States
Primary Outcome A
Extent of categorical agreement, measured in weighted kappa, between Ellipsis Health Software as a Medical Device severity of depression and clinician's rating of severity of depression.
Time frame: 4 days
Primary Outcome B
Extent of categorical agreement, measured in weighted kappa, between Ellipsis Health Software as a Medical Device severity of anxiety and clinician's rating of severity of anxiety.
Time frame: 4 days
Secondary Outcome A
Extent of agreement of presence, measured in the Equal Error Rate on the Receiver Operating Characteristic curve, between Ellipsis Health Software aa a Medical Device detection of Major Depressive Disorder and clinician's assessment for the diagnosis of Major Depressive Disorder, as expressed as Sensitivity and Specificity.
Time frame: 4 days
Secondary Outcome B
Extent of agreement of presence, measured in the Equal Error Rate on the Receiver Operating Characteristic curve, between Ellipsis Health Software as a Medical Device detection of Generalized Anxiety Disorder and clinician's assessment for the diagnosis of Generalized Anxiety Disorder, as expressed as Sensitivity and Specificity.
Time frame: 4 days
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