SBIR-STTR Award

Modeling Physiology and Behavior of Veterans to Avert Opioid Related Mortality Through Timely Intervention
Award last edited on: 2/14/2024

Sponsored Program
SBIR
Awarding Agency
NIH : NIDA
Total Award Amount
$1,088,662
Award Phase
2
Solicitation Topic Code
279
Principal Investigator
Ellie Gordon

Company Information

Behaivior LLC

4620 Henry Street
Pittsburgh, PA 15213
   (412) 719-5879
   hello@behaivior.com
   www.behaivior.com
Location: Single
Congr. District: 18
County: Allegheny

Phase I

Contract Number: 1R44DA053874-01A1
Start Date: 9/15/2022    Completed: 8/31/2023
Phase I year
2022
Phase I Amount
$253,479
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.

Public Health Relevance Statement:
Project Narrative With staggeringly high relapse and overdose rates and a dearth of treatment access and efficacy, the opioid epidemic is among the most pressing public health concerns of our time; drug craving states can be induced by a number of social, environmental, and contextual cues, there are often comorbidities with mental health issues, and other substance use disorders, and sustained, consistent, permanent behavior change is required to avert potential relapse events. An increasing body of literature identifies United States veterans as extremely vulnerable to opioid addiction and overdose, amongst other mental health related risks; the proposed work entails the development of precision opioid-use related intelligence which presents a unique opportunity to make an impact beyond aiding the process of addiction recovery, to help those struggling with other mental health challenges such as anxiety, PTSD, and suicidal ideation, and includes investigating the potential for physiological and behavioral monitoring of individuals with opioid addictions amongst the US Veteran population in order to improve adherence to treatment for opioid use disorder and aid in reintegration into civilian life. Behaivior will deliver real-time insights from internal and external factors that affect craving states based on wrist wearables and smartphone monitoring technology that can detect high-risk craving states and provide a trusted network of support individuals as well as care coordinators with just-in-time information to facilitate interventions which may avert life-threatening events, including overdoses or suicides.

Project Terms:
Centers for Disease Control and Prevention; United States Centers for Disease Control; United States Centers for Disease Control and Prevention; Clinical Research; Clinical Study; comorbidity; co-morbid; co-morbidity; Cues; Data Reporting; data representation; Education; Educational aspects; Epidemic; Face; faces; facial; Gender Identity; Goals; Health Services Accessibility; Access to Care; access to health services; access to services; access to treatment; accessibility to health services; availability of services; care access; health service access; health services availability; service availability; treatment access; Human; Modern Man; Incidence; Income; Economic Income; Economical Income; Intelligence; Learning; Literature; Mental Health; Mental Hygiene; Psychological Health; Methodology; Military Personnel; Armed Forces Personnel; Military; military population; Physiologic Monitoring; Physiological Monitoring; mortality; Persons; Overdose; Painful; Pain; Patients; Cyclicity; Rhythmicity; Periodicity; well-being; wellbeing; Personal Satisfaction; Physiology; Production; Public Health; Racial Group; Racial Stocks; Race; Relapse; Risk; Safety; seal; Stress; PTSD; Post-Traumatic Neuroses; Posttraumatic Neuroses; Posttraumatic Stress Disorders; post-trauma stress disorder; posttrauma stress disorder; traumatic neurosis; Post-Traumatic Stress Disorders; Substance Use Disorder; fatal attempt; fatal suicide; intent to die; suicidality; Suicide; Survey Instrument; Surveys; Technology; Time; Treatment Protocols; Treatment Regimen; Treatment Schedule; United States; United States Substance Abuse and Mental Health Services Administration; SAMHSA; Substance Abuse and Mental Health Services Administration; Veterans; Work; Wrist; chronic pain; Data Set; Dataset; Caring; Custom; Injury; injuries; base; career; improved; Suicide prevention; Suicide precaution; prevent suicidality; prevent suicide; suicidality prevention; suicide intervention; Phase; Physiological; Physiologic; Training; insight; Individual; Recovery; Trust; Opiates; Opioid; mental status; mental state; tool; machine learned; Machine Learning; Life; programs; Suicidal thoughts; suicidal ideation; suicidal thinking; suicide ideation; thoughts about suicide; Feeling suicidal; suicidal; Event; System; Opiate Dependence; opioid addiction; opioid dependence; opioid dependent; Opiate Addiction; behavior change; drug craving; Performance; stressor; novel; research study; Self-Report; Patient Self-Report; help seeking; help-seeking behavior; General Public; General Population; Reporting; social; disease recurrence prevention; disorder recurrence prevention; recurrence prevention; relapse prevention; disorder later incidence prevention; Modeling; craving; stigma; social stigma; Intervention Strategies; interventional strategy; Intervention; Annual Reports; Cell Phone; Cellular Telephone; iPhone; smart phone; smartphone; Cellular Phone; Address; Adherence; Data; High Prevalence; Collection; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Monitor; Process; Development; developmental; Behavioral; suicide rate; Behavior monitoring; behavioral monitoring; predictive modeling; computer based prediction; prediction model; design; designing; severe mental illness; chronic mental illness; persistent mental illness; serious mental disorder; serious mental illness; severe mental disorder; Treatment Efficacy; intervention efficacy; therapeutic efficacy; therapy efficacy; Outcome; Population; Coupling; Resistance; resistant; addiction; addictive disorder; high risk; combat; overdose death; overdose fatalities; operation; personalized care; Precision care; individualized care; individualized patient care; personalized patient care; peer support; support network; opioid use disorder; opiate use disorder; opioid use; opiate consumption; opiate drug use; opiate intake; opiate use; opioid consumption; opioid drug use; opioid intake; cloud platform; cloud server; software as a service; negative affect; negative affectivity; substance misuse; opioid epidemic; opiate crisis; opioid crisis; opioid overdose; opiate overdose; opiate related overdose; opioid drug overdose; opioid induced overdose; opioid intoxication; opioid medication overdose; opioid poisoning; opioid related overdose; opioid toxicity; wearable sensor technology; body sensor; body worn sensor; wearable biosensor; wearable sensor; wearable system; wearable device; wearable electronics; wearable technology; care providers; primary care provider; opioid misuse; non-medical opioid use; nonmedical opioid use; opiate misuse; first responder; COVID-19 pandemic; COVID crisis; COVID epidemic; COVID pandemic; COVID-19 crisis; COVID-19 epidemic; COVID-19 global health crisis; COVID-19 global pandemic; COVID-19 health crisis; COVID-19 public health crisis; COVID19 crisis; COVID19 epidemic; COVID19 global health crisis; COVID19 global pandemic; COVID19 health crisis; COVID19 pandemic; COVID19 public health crisis; SARS-CoV-2 epidemic; SARS-CoV-2 global health crisis; SARS-CoV-2 global pandemic; SARS-CoV-2 pandemic; SARS-CoV2 epidemic; SARS-CoV2 pandemic; SARS-coronavirus-2 epidemic; SARS-coronavirus-2 pandemic; Severe Acute Respiratory Syndrome CoV 2 epidemic; Severe Acute Respiratory Syndrome CoV 2 pandemic; Severe acute respiratory syndrome coronavirus 2 epidemic; Severe acute respiratory syndrome coronavirus 2 pandemic; corona virus disease 2019 epidemic; corona virus disease 2019 pandemic; coronavirus disease 2019 crisis; coronavirus disease 2019 epidemic; coronavirus disease 2019 global health crisis; coronavirus disease 2019 global pandemic; coronavirus disease 2019 health crisis; coronavirus disease 2019 pandemic; coronavirus disease 2019 public health crisis; coronavirus disease crisis; coronavirus disease epidemic; coronavirus disease pandemic; coronavirus disease-19 global pandemic; coronavirus disease-19 pandemic; severe acute respiratory syndrome coronavirus 2 global health crisis; severe acute respiratory syndrome coronavirus 2 global pandemic; effectiveness evaluation; assess effectiveness; determine effectiveness; effectiveness assessment; evaluate effectiveness; military veteran; veteran population; remote intervention; remote monitoring; substance use; substance using; machine learning model; machine learning based model; Affect; Age; ages; Anxiety; Award; Behavior; Centers for Disease Control and Prevention (U.S.); CDC; Centers for Disease Control

Phase II

Contract Number: 4R44DA053874-02
Start Date: 9/15/2022    Completed: 1/31/2026
Phase II year
2024
Phase II Amount
$835,183
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.

Public Health Relevance Statement:
Project Narrative With staggeringly high relapse and overdose rates and a dearth of treatment access and efficacy, the opioid epidemic is among the most pressing public health concerns of our time; drug craving states can be induced by a number of social, environmental, and contextual cues, there are often comorbidities with mental health issues, and other substance use disorders, and sustained, consistent, permanent behavior change is required to avert potential relapse events. An increasing body of literature identifies United States veterans as extremely vulnerable to opioid addiction and overdose, amongst other mental health related risks; the proposed work entails the development of precision opioid-use related intelligence which presents a unique opportunity to make an impact beyond aiding the process of addiction recovery, to help those struggling with other mental health challenges such as anxiety, PTSD, and suicidal ideation, and includes investigating the potential for physiological and behavioral monitoring of individuals with opioid addictions amongst the US Veteran population in order to improve adherence to treatment for opioid use disorder and aid in reintegration into civilian life. Behaivior will deliver real-time insights from internal and external factors that affect craving states based on wrist wearables and smartphone monitoring technology that can detect high-risk craving states and provide a trusted network of support individuals as well as care coordinators with just-in-time information to facilitate interventions which may avert life-threatening events, including overdoses or suicides.

Project Terms:
Affect; Age; ages; Anxiety; Award; Behavior; Centers for Disease Control and Prevention (U.S.); Centers for Disease Control; Centers for Disease Control and Prevention; United States Centers for Disease Control; United States Centers for Disease Control and Prevention; Clinical Research; Clinical Study; comorbidity; co-morbid; co-morbidity; Cues; Data Reporting; data representation; data representations; Education; Educational aspects; Epidemic; Face; faces; facial; Gender Identity; Goals; Access to Care; access to health services; access to services; access to treatment; accessibility to health services; availability of services; care access; health service access; health services availability; service availability; treatment access; Health Services Accessibility; Modern Man; Human; Incidence; Economic Income; Economical Income; incomes; Income; Intelligence; Learning; Literature; Mental Hygiene; Psychological Health; Mental Health; Methodology; Armed Forces Personnel; Military; military population; Military Personnel; Physiological Monitoring; Physiologic Monitoring; mortality; Persons; Overdose; Painful; Pain; Patients; periodic; periodical; Periodicals; well-being; wellbeing; Personal Satisfaction; Physiology; Production; Public Health; Races; racial; racial background; racial origin; Race; Relapse; Risk; Safety; seal; Stress; PTSD; Post-Traumatic Neuroses; Posttraumatic Neuroses; post-trauma stress disorder; posttrauma stress disorder; traumatic neurosis; Post-Traumatic Stress Disorders; substance use and disorder; Substance Use Disorder; fatal attempt; fatal suicide; intent to die; suicides; Suicide; Survey Instrument; Surveys; Technology; Time; Treatment Regimen; Treatment Schedule; Treatment Protocols; United States; SAMHSA; Substance Abuse and Mental Health Services Administration; United States Substance Abuse and Mental Health Services Administration; Veterans; Work; Wrist; chronic pain; Data Set; Caring; injuries; Injury; career; improved; Suicide precaution; prevent suicidality; prevent suicide; suicidality prevention; suicide intervention; Suicide prevention; Phase; Physiologic; Physiological; Training; insight; Individual; Recovery; Trust; Opiates; Opioid; mental status; mental state; tool; machine based learning; Machine Learning; Life; programs; Suicidal thoughts; suicidal ideation; suicidal thinking; suicide ideation; thoughts about suicide; Feeling suicidal; suicidality; suicidal; Event; System; Opiate Dependence; opioid addiction; opioid dependence; opioid dependent; Opiate Addiction; behavior change; drug craving; Performance; stressor; novel; research study; Self-Report; Patient Self-Report; help seeking; help-seeking behavior; General Public; General Population; Reporting; social; disease recurrence prevention; prevent relapse; recurrence prevention; relapse prevention; Modeling; craving; stigma; social stigma; Intervention Strategies; interventional strategy; Intervention; Annual Reports; Cellular Phone; Cell Phone; Cellular Telephone; Mobile Phones; iPhone; smart phone; smartphone; Address; Adherence; Data; High Prevalence; Collection; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Monitor; Process; Development; developmental; Behavioral; suicide rate; Behavior monitoring; behavioral monitoring; predictive modeling; computer based prediction; prediction model; design; designing; severe mental illness; persistent mental illness; serious mental disorder; serious mental illness; severe mental disorder; chronic mental illness; Treatment Efficacy; intervention efficacy; therapeutic efficacy; therapy efficacy; Outcome; Population; Coupling; Resistance; resistant; addiction; addictive disorder; high risk; combat; overdose death; overdose fatalities; operation; operations; personalized care; Precision care; individualized care; individualized patient care; personalized patient care; peer support; support network; opioid use disorder; opiate use disorder; opioid use; opiate consumption; opiate drug use; opiate intake; opiate use; opioid consumption; opioid drug use; opioid intake; cloud platform; cloud server; software as a service; negative affect; negative affectivity; substance misuse; opioid epidemic; opiate crisis; opioid crisis; opioid overdose; opiate overdose; opiate related overdose; opioid drug overdose; opioid induced overdose; opioid intoxication; opioid medication overdose; opioid poisoning; opioid related overdose; opioid toxicity; body sensor; body worn sensor; wearable biosensor; wearable sensor; wearable sensor technology; wearable electronics; wearable system; wearable technology; wearable tool; wearables; wearable device; care providers; non-medical opioid use; nonmedical opioid use; opiate misuse; opioid misuse; first responder; COVID crisis; COVID epidemic; COVID pandemic; COVID-19 crisis; COVID-19 epidemic; COVID-19 global health crisis; COVID-19 global pandemic; COVID-19 health crisis; COVID-19 public health crisis; COVID19 crisis; COVID19 epidemic; COVID19 global health crisis; COVID19 global pandemic; COVID19 health crisis; COVID19 pandemic; COVID19 public health crisis; SARS-CoV-2 epidemic; SARS-CoV-2 global health crisis; SARS-CoV-2 global pandemic; SARS-CoV-2 pandemic; SARS-CoV2 epidemic; SARS-CoV2 pandemic; SARS-coronavirus-2 epidemic; SARS-coronavirus-2 pandemic; Severe Acute Respiratory Syndrome CoV 2 epidemic; Severe Acute Respiratory Syndrome CoV 2 pandemic; Severe acute respiratory syndrome coronavirus 2 epidemic; Severe acute respiratory syndrome coronavirus 2 pandemic; corona virus disease 2019 epidemic; corona virus disease 2019 pandemic; coronavirus disease 2019 crisis; coronavirus disease 2019 epidemic; coronavirus disease 2019 global health crisis; coronavirus disease 2019 global pandemic; coronavirus disease 2019 health crisis; coronavirus disease 2019 pandemic; coronavirus disease 2019 public health crisis; coronavirus disease crisis; coronavirus disease epidemic; coronavirus disease pandemic; coronavirus disease-19 global pandemic; coronavirus disease-19 pandemic; severe acute respiratory syndrome coronavirus 2 global health crisis; severe acute respiratory syndrome coronavirus 2 global pandemic; COVID-19 pandemic; assess effectiveness; determine effectiveness; effectiveness assessment; evaluate effectiveness; examine effectiveness; effectiveness evaluation; veteran population; military veteran; remote intervention; remote monitoring; substance using; substance use; machine learning based model; machine learning model