The Experience of Veterans with Disabilities: A Grounded Theory Study on Coping with Trauma and Adapting to a new life
Abstract: Research and knowledge related to psychosocial processes experienced by Turkish Veterans with disabilities and the factors that facilitate adapting to life with a disability are insufficient. This study aims to explore the psychosocial processes and coping resources experienced by Turkish Veterans with disabilities. A grounded theory design was used in the study. Snowball sampling and theoretical sampling were used to recruit participants. In-depth interviews were conducted with 20 male participants. The data were analyzed through open, axial, and selective coding and formed into themes and categories. The results were explained within the framework of the following themes: the moment of returning from the threshold of death, treatment process, returning to life after war, acceptance, and holding on to life. The analysis revealed that the participants experienced problems, such as post-traumatic stress, the inadequacy of psychosocial functioning, social disapproval, and alienation during the adaptation to life after war. Further, coping resources such as positive personality traits, spiritual coping, making sense of experience, state assurance, and family and fellow Veterans support were found to facilitate the adaptation process.
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.