Unethical Battlefield Conduct Reported by Soldiers Serving in the Iraq War
Abstract: Research involving military service members has shown a strong relationship between combat experiences and increased risk for posttraumatic stress disorder (PTSD) and other mental health problems. Comparatively little research has examined the relationship between combat experiences, PTSD, aggression, and unethical conduct on the battlefield, although news stories sometimes suggest links between unethical conduct and disorders such as PTSD. This study systematically examined whether unethical conduct is a proxy for aggression and whether specific combat experiences and PTSD are independently associated with unethical behavior. The results of this study indicate that aggression (β = 0.30) and specific combat experiences (particularly, witnessing war atrocities [β = 0.14] and fighting [β = 0.13]) are much more strongly associated with unethical conduct than is PTSD (β = 0.04)
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.