Identifying psychological outcomes in families of Five Eyes alliance armed forces Veterans: A systematic review
Abstract: Military service can affect the psychological health and well-being of ex-service members and their families. Most research prioritizes active duty families or Veterans, with spouses/intimate partners and adult children of Veterans often overlooked. This study reviewed all previous research on the psychological health of Veteran families within the Five Eyes alliance countries of Australia, Canada, New Zealand, the United Kingdom, and the United States. It found spouses/intimate partners had higher rates of anxiety, depression, and posttraumatic stress disorder (PTSD) compared to national rates and were more likely to feel distress when their Veteran partner had mental health issues. Adult children were at higher risk for anxiety, depression, alcohol/substance misuse, and PTSD compared to national rates. Four themes identified were: personal feelings and internal emotions, Veteran-oriented, help and support, and acting as a unit. Due to the scarce available research, further studies are needed to address psychological outcomes among military Veteran families.
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.