Mental Health Disorders and Alcohol Misuse Among UK Military Veterans and the General Population: A Comparison Study
Abstract: For a small minority of personnel, military service can have a negative impact on their mental health. Yet no studies have assessed how the mental health of UK veterans (who served during the recent operations in Afghanistan or Iraq) compares to non-veterans, to determine if they are at a disadvantage. We examine the prevalence of mental disorders and alcohol misuse in UK veterans compared to non-veterans. Methods: Veteran data were taken from the third phase of the King's Centre for Military Health Research cohort study (n = 2917). These data were compared with data on non-veterans taken from two large general population surveys: 2014 Adult Psychiatric Morbidity Survey (n = 5871) and wave 6 of the UK Household Longitudinal Study (UKHLS, n = 22 760). Results: We found that, overall, UK veterans who served at the time of recent military operations were more likely to report a significantly higher prevalence of common mental disorders (CMD) (23% v. 16%), post-traumatic stress disorder (PTSD) (8% v. 5%) and alcohol misuse (11% v. 6%) than non-veterans. Stratifying by gender showed that the negative impact of being a veteran on mental health and alcohol misuse was restricted to male veterans. Being ill or disabled was associated with a higher prevalence of CMD and PTSD for both veterans and non-veterans.
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.