Gambling problems among United Kingdom armed forces veterans: Associations with gambling motivation and posttraumatic stress disorder
Abstract: Military service, mental health, and gambling activities and motivations as predictors of problem gambling in a sample of UK AF veterans. Age-and-gender matched veterans (n = 1,037) and non-veterans (n = 1,148) completed an online survey of problem gambling, gambling motivation, mental health (depression and anxiety), and posttraumatic stress disorder (PTSD). Past year problem gambling rates were higher in veterans compared to non-veterans. Veteran status predicted increased problem gambling risk. The relationship between problem gambling and gambling to cope with distress was significantly stronger among veterans. Veterans experiencing PTSD and complex PTSD (C-PTSD) were at increased risk of problem gambling. Overall, the present, findings contribute further international evidence that veterans are a population vulnerable to problem gambling. Veterans with PTSD or C-PTSD are most at-risk and may engage in problematic gambling to escape/avoid distress. Routine screening for gambling problems should be undertaken with current and former military personnel, and further research is needed on the interplay between gambling motivation and veterans’ mental health.
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.