Veterans’ Experiences of Successfully Managing Post-traumatic Stress Disorder
Abstract: Prevalence of post-traumatic stress disorder (PTSD) amongst UK veterans is higher than in the general population. However, prevalence figures do not reflect the complexity of this phenomenon and ways in which it may be bound up with veterans’ experiences of adjusting to civilian life. The purpose of this study was to explore veterans’ experiences of successfully managing PTSD. Design/methodology/approach: Semi-structured interviews were conducted with six veterans who had served in the UK armed forces, and analysed using interpretative phenomenological analysis. Three themes were developed: (1) accepting the problem, taking responsibility and gaining control; (2) talking to the right people; and (3) strategies, antidotes and circling back around. Managing PTSD appeared to be bound up with veterans’ experience of renegotiating their identity, where positive aspects of identity lost on leaving the military were rebuilt, and problematic aspects were challenged. Participants sought to speak about their difficulties with others who understood the military context. They felt that their experiences made them a valuable resource to others, and they connected this with a positive sense of identity and value. The findings suggest the importance of wider provision of peer support, and education for civilian health services on veterans’ needs. This study adds to our understanding of what meaningful recovery from PTSD may involve for veterans, in particular its potential interconnectedness with the process of adjusting to civilian life.
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.