Exploring Resiliency and Social Support as Protective Factors in the Treatment of Opioid Use Disorder in the Louisiana State Opioid Response (LaSOR) Project
Location
Center for Advanced Learning and Simulation (CALS)
Publication Date
April 2025
Start Date
17-4-2025 8:00 AM
Description
The Louisiana State Opioid Response (LaSOR 3) Project is a statewide program broadly aimed at combating the opioid epidemic. LSUHSC’s role in LaSOR is to recruit and consult with office-based providers who offer medications for individuals with opioid use disorder (OUD). In addition to medications, LaSOR patients also receive screening, brief intervention, and referrals to treatment. There is a well-established body of literature detailing how various risk factors such as trauma, risk-taking behavior, high economic stress, and other hardships are frequently associated with worse treatment outcomes. Trauma in particular has been linked to various negative health problems in adulthood, including depression and substance use. In contrast, protective factors are variables that are associated with a decrease in the likelihood of negative treatment outcomes. Protective factors are somewhat less understood and investigated than their negative counterparts. Here, we explored both intrinsic protective factors such as resilience, as well as extrinsic factors such as social support and whether they are associated with better treatment outcomes in our large sample of LaSOR patients. Our primary outcome variables here will be changes in patients’ anxiety and depression scores over time. These variables will be analyzed along with our protective factor measures. We predict that patients who have higher measured levels of protective factors will experience greater improvement in anxiety and depressive symptoms. Moreover, we hypothesize that patients with more protective factors will remain in treatment longer by analyzing dropout rates.
Recommended Citation
Franks, Bryan and Hamrick, Michelle LCSW, "Exploring Resiliency and Social Support as Protective Factors in the Treatment of Opioid Use Disorder in the Louisiana State Opioid Response (LaSOR) Project" (2025). Dept. of Psychiatry Research Symposium. 26.
https://digitalscholar.lsuhsc.edu/psych_rd/2025/presentations/26
Exploring Resiliency and Social Support as Protective Factors in the Treatment of Opioid Use Disorder in the Louisiana State Opioid Response (LaSOR) Project
Center for Advanced Learning and Simulation (CALS)
The Louisiana State Opioid Response (LaSOR 3) Project is a statewide program broadly aimed at combating the opioid epidemic. LSUHSC’s role in LaSOR is to recruit and consult with office-based providers who offer medications for individuals with opioid use disorder (OUD). In addition to medications, LaSOR patients also receive screening, brief intervention, and referrals to treatment. There is a well-established body of literature detailing how various risk factors such as trauma, risk-taking behavior, high economic stress, and other hardships are frequently associated with worse treatment outcomes. Trauma in particular has been linked to various negative health problems in adulthood, including depression and substance use. In contrast, protective factors are variables that are associated with a decrease in the likelihood of negative treatment outcomes. Protective factors are somewhat less understood and investigated than their negative counterparts. Here, we explored both intrinsic protective factors such as resilience, as well as extrinsic factors such as social support and whether they are associated with better treatment outcomes in our large sample of LaSOR patients. Our primary outcome variables here will be changes in patients’ anxiety and depression scores over time. These variables will be analyzed along with our protective factor measures. We predict that patients who have higher measured levels of protective factors will experience greater improvement in anxiety and depressive symptoms. Moreover, we hypothesize that patients with more protective factors will remain in treatment longer by analyzing dropout rates.