Coping Strategies of Older American Korean War Veterans: A Mixed Research Study
Abstract: For American Korean War veterans, military service during wartime is a major life-changing experience across their lifespan. Research on them, while they are still living, is critical to understanding how older veterans have dealt with social adjustment after the war and in their later lives. This study examined the impact of military experience and social support upon coping strategies of older veterans. Both surveys and focus groups were conducted to collect data from 20 American Korean War veterans and 22 older non-veterans. Our findings indicate that the American Korean War Veterans Association has been a critical source of social support for veteran participants, leading them into more adaptive coping strategies. Focusing upon positive adaptation after traumatic events is a recommended shift of practice for helping professionals. More implications of the activity professionals were discussed.
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.