Assessments for depression, anxiety, and other behavioral/mental health conditions range from paper-based self-assessment surveys to brief online surveys as part of the student health check-in process. Student mental health is a rising concern, and mental health clinics lack needs more tools to manage caseload and ensure students are properly diagnosed.
Goals and Objectives
Leverage passive monitoring via mobile technology (geolocation, levels of communication) or voice analysis to identify students with depression, post-traumatic stress disorder (PTSD), or other behavioral or mental health conditions. Address behavioral and mental health issues that impact the treatment of chronic conditions.
Mobile devices, AI-enabled mobile apps to collect and analyze geodata and communication patterns, AI-enabled voice recognition and voice print analysis tools/machine learning, and predictive analytics
Use Case Summary
Passive monitoring uses nonintrusive technology to improve the detection of depression, PSTD, and other behavioral and mental health conditions; the accuracy of diagnosis; and appropriateness of care plans and enables quantifiable monitoring of the mental health status over time.