Utilizing digital predictive biomarkers to identify Veteran suicide risk

Area of Science:

• Digital health
• Biomarkers
• Mental health

Background:

• Veteran suicide is a critical public health issue in the U.S., with an average of 17.2 daily deaths reported in 2020.
• Current suicide risk screening methods for Veterans are limited, necessitating innovative approaches.
• Integrating personal behavior risk factors is key for effective suicide risk tracking.

Purpose of the Study:

• To review and evaluate digital predictive biomarkers for Veteran suicide risk.
• To explore the utility of digital technologies in real-time identification of suicidal ideation.
• To assess the potential of digital biomarkers in improving suicide screening and intervention.

Main Methods:

• Review of existing literature on digital predictive biomarkers related to suicide risk.
• Evaluation of biomarkers such as sleep vital signs, sleep disturbance, sleep quality, and speech pattern recognition.
• Assessment of the reliability, fidelity, and frequency of data collection via digital technologies.

Main Results:

• Digital technologies offer a reliable means to frequently measure risk factors throughout daily life.
• Specific digital biomarkers, including sleep patterns and speech recognition, show potential for identifying behavioral patterns indicative of suicide risk.
• These biomarkers can be integrated to enhance real-time screening and assessment of Veteran suicidal ideation.

Conclusions:

• Digital predictive biomarkers represent a promising avenue for innovative Veteran suicide risk screening.
• Combining various digital biomarkers can lead to more accurate diagnosis and severity assessments.
• Optimized intervention strategies for healthcare providers can be developed through enhanced digital screening tools.