Resiliency and Posttraumatic Growth Following Sexual Trauma in Women Veterans of Iraq and Afghan Wars
Abstract: Women veterans of Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) experience a myriad of traumatic stressors, including high rates of Military Sexual Trauma (MST). Furthermore, there is an upsurge in combat exposure, length and number of deployments, and/or perceived personal danger in these eras compared to women veterans of previous eras. These stressors can increase the risk of developing posttraumatic stress disorder (PTSD). Women veterans with combat exposure and/or MST experience PTSD differently than civilian women or military men, and therefore may require tailored and integrative treatments. Interventions that focus on resiliency and posttraumatic growth (PTG) may help decrease symptom presentation, increase quality of life, and reduce the utilization/cost of care. Moreover, resiliency-based interventions could offer a recovery-oriented framework that reinforces positive psychology constructs that may promote growth following trauma. To investigate these concepts, we interviewed four women from the OEF/OIF/OND eras who have experienced MST and/or received a diagnosis of PTSD. We explored four major areas: experiences of life after military, impact of trauma on factors that influence resiliency, helpful and unhelpful interventions for trauma recovery, and the concepts of resiliency and posttraumatic growth. These women generally felt a sense of lost identity following trauma and in post-military life, and they expressed a desire for therapy groups to support and foster connections to women with similar experiences. We also observed that they had a general understanding of resilience but lacked in-depth knowledge as it could apply to trauma recovery and welcomed opportunities to learn these skills in group settings. Keywords: ResiliencePos
Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.