Modeling Physiology and Behavior of Veterans to Avert Opioid Related Mortality Through Timely Intervention

对退伍军人的生理和行为进行建模，通过及时干预避免阿片类药物相关的死亡

• 批准号: 10481499
• 负责人: STEVEN D. FORMAN
• 金额: $ 25.35万
• 依托单位: BEHAIVIOR, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10481499
• 关键词: Address; Adherence; Affect; Age; Annual Reports; Anxiety; Award; Behavior; Behavior monitoring; Behavioral; COVID-19 pandemic; Caring; Cellular Phone; Centers for Disease Control and Prevention (U.S.); Clinical Research; Collection; Coupling; Cues; Custom; Data; Data Reporting; Data Set; Development; Education; Epidemic; Event; Face; Feeling suicidal; Gender Identity; General Population; Goals; Health Services Accessibility; High Prevalence; Human; Incidence; Income; Individual; Injury; Intelligence; Intervention; Learning; Life; Literature; Machine Learning; Mental Health; Methodology; Military Personnel; Modeling; Monitor; Opiate Addiction; Opioid; Outcome; Overdose; Pain; Patient Self-Report; Patients; Performance; Periodicity; Personal Satisfaction; Persons; Phase; Physiologic Monitoring; Physiological; Physiology; Population; Post-Traumatic Stress Disorders; Process; Production; Public Health; Race; Recovery; Relapse; Reporting; Resistance; Risk; Safety; Small Business Innovation Research Grant; Stress; Substance Use Disorder; Suicide; Suicide prevention; Surveys; System; Technology; Time; Training; Treatment Efficacy; Treatment Protocols; Trust; United States; United States Substance Abuse and Mental Health Services Administration; Veterans; Work; Wrist; addiction; base; behavior change; care providers; career; chronic pain; cloud platform; combat; comorbidity; craving; design; disorder later incidence prevention; drug craving; effectiveness evaluation; first responder; help-seeking behavior; high risk; improved; insight; machine learning model; mental state; military veteran; mortality; negative affect; novel; operation; opioid epidemic; opioid misuse; opioid overdose; opioid use; opioid use disorder; overdose death; peer support; personalized care; predictive modeling; programs; remote intervention; remote monitoring; research study; seal; severe mental illness; social; social stigma; software as a service; stressor; substance misuse; substance use; suicidal; suicide rate; support network; tool; wearable device; wearable sensor technology

Project Summary/Abstract Opioid addiction affects people of all races, ages, gender identities, education, and income levels across the United States. The epidemic has been intensifying in recent years, with relapse rates reaching close to 91% (Kadam et al., 2017) and provisional data from 2020 indicating the highest number of overdose deaths ever recorded in a year, over 88,000 (Centers for Disease Control and Prevention, 2020). Further, only 10-20% of people struggling with addiction receive care for their OUD (Substance Abuse and Mental Health Services Administration, 2020). An increasing body of literature exposes a population extremely vulnerable to opioid addiction and overdose: United States veterans. Veterans face unique challenges that predispose them to greater risk for misusing opioids such as higher prevalence of and more severe pain than the general population (Nahin, 2017), and the stresses and risks of deployment that often result in PTSD upon return to civilian life (Seal et al., 2012). Indeed, this group, though not monolithic, may be generally resistant to support; half of military personnel reported that they believe seeking help for mental health issues would harm their military career. Suicide rates continue to rise, faster in the veteran population than in the non-veteran population, even despite the decrease in the population proportion of veterans. In 2018, almost one in seven suicides in the U.S. was a veteran (“2020 National Veteran Suicide Prevention Annual Report”, 2020). Mental health issues have an effect on substance use disorders as well. Nationwide, the rate of overdose deaths in veterans increased by 65% from 2010 to 2016 (Lewei et al., 2019). The stressors of deployment during wartime that are often difficult to shake off upon return to civilian life, incidences of injuries resulting in severe and often chronic pain, and the nuances of military culture, combined with stigmas associated with OUD, perpetuate a detrimental cycle of addiction for veterans. To address this, we are proposing the development of a novel solution that addresses the mental health of veterans nationally via a first-of-its-kind remote monitoring and intervention software-as-a-service offering. Our system builds upon our technology stack and learnings from clinical studies on individuals with OUD. Given that substance use in the veteran population often precedes a deleterious cycle commonly resulting in serious and persistent mental illness (SPMI) and sometimes even suicide, advanced and real-time remote monitoring of the state of mental health would be an important indicator. This tool provides timely intervention that addresses OUD and further averts the progression of SPMI as well as suicidal tendencies.

项目总结/文摘