Stories of transition: U.S. Veterans’ narratives of transition to civilian life and the important role of identity

Abstract: Introduction: To date, investigations of Veterans’ transition to civilian life after military service have tended to focus on the experiences of those with mental or physical health difficulties or on employment challenges and homelessness. This study aimed to gain a deep understanding of Veterans’ transition to civilian life, the challenges they face, and the adap-tive and maladaptive ways in which they manage them. Methods: A narrative approach was used to afford the Veterans an opportunity to share their experiences through their transition story. Six male Veterans residing in the Chicagoland area who had left the military between 1 and 12 years earlier were interviewed using a narrative approach. Results: Narrative analysis led to the emergence of three master narratives: narratives of the challenges, narratives of readiness, and narratives of continued military values. The narratives the Veterans shared highlighted not only the importance of practical readiness for transition but also the need for a fundamental addition to how Veteran transition is considered that includes psychological considerations of the impact on identity and the potential for existential crisis. Discussion: Appraising transition only in terms of measurable factors such as employment, living conditions, and health likely over-looks those experiencing psychological challenges and sub-clinical mental health difficulties. The proposed fundamental addition has implications for work with Veterans in various health care settings and for existing transition programs, including a consideration of the role of identity.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    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.