Artificial Intelligence-Enabled, Real-time Risk Monitoring for Substance Use Recovery in Veterans: An Initial...

Area of Science:

• Digital health interventions
• Artificial intelligence in healthcare
• Substance use disorder treatment

Background:

• Substance use disorders (SUDs) are a significant issue for U.S. Military personnel and Veterans.
• Existing treatment methods may not fully address unique service-related risk factors.
• Behaivior's AI-powered platform integrates smartwatches for continuous monitoring and intervention.

Purpose of the Study:

• To evaluate the acceptability and effectiveness of a mobile health intervention for Veterans with SUDs.
• To assess the potential of AI and wearable technology in supporting SUD recovery.
• To explore the feasibility of real-time data analysis for proactive intervention.

Main Methods:

• User experience study with 10 Veterans with cocaine use disorder (surveys, interviews).
• Mobile health intervention study with 27 Veterans with opioid use disorder (4-week trial).
• Utilized IRB-approved protocols through the VA Pittsburgh Healthcare System, collecting self-report and wearable-monitored data.

Main Results:

• High participant preference for mobile health interventions (82.9% endorsement of wearable functions).
• Sufficient engagement and adherence with wearable data collection (over 8 hours/day monitoring).
• Preliminary efficacy signals showed a 29.6% return-to-opioid-use rate, with 3.3% positive opioid specimens.

Conclusions:

• Behaivior's technology shows potential for supporting SUD recovery in Veterans.
• The platform can synthesize real-time data to identify risk and inform providers.
• This approach may enhance health outcomes for Veterans and potentially active duty service members.