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Sensor-based Characterization of Depression — SENSCODE  

Unipolar Depression Clinical Trial

Official title:
Leveraging Artificial Intelligence for the Assessment of Severity of Depressive Symptoms

Clinical Trial Summary

This is a longitudinal study where individual with Major Depressive Disorder (MDD) will be monitored for 12 weeks. The study aims to develop an objective, sensor-based, algorithm able to detect the presence of depression as well as predict treatment response. Measurement-based treatment is considered optimal and the development of a valid passive, objective, behavioral and biological assessment of depressive symptoms that does not rely on clinician interviews will improve monitoring and ultimately improve treatment significantly.

Clinical Trial Description

In this longitudinal study 100 individuals with Major Depressive Disorder (MDD) will be monitored for 12 weeks. Data will include self-report surveys, in-person assessments, physiological features derived by wearable devices and socialization and activity data derived by mobile applications. The study will utilize advanced statistical methods to integrate different sources of passive sensor-based behavioral and physiological data to develop models able to detect depression and predict treatment response. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT04370002
Study type Observational
Source Massachusetts General Hospital
Contact
Status Recruiting
Phase
Start date January 28, 2020
Completion date November 30, 2024
View Details
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