Moral transgression during the Vietnam War: a path analysis of the psychological impact of veterans’ involvement in wartime atrocities
Abstract: Background and Objectives: Involvement in wartime combat often conveys a number of deleterious outcomes, including posttraumatic stress disorder (PTSD), depression, hostility, aggression, and suicidal ideation. Less studied is the effect of engagement in wartime atrocities, including witnessing and perpetrating abusive violence. Design and Methods: This study employed path analysis to examine the direct effects of involvement in wartime atrocities on hostility, aggression, depression, and suicidal ideation independent of combat exposure, as well as the indirect effects via guilt and PTSD symptom severity among 603 help-seeking male Vietnam War veterans. Results: Involvement in wartime atrocities was predictive of increased guilt, PTSD severity, hostility, aggression, depressive symptoms, and suicidal ideation after controlling for overall combat exposure. Combat-related guilt played a minor role in mediating the effect of atrocity involvement on depression and suicidal ideation. PTSD severity had a larger mediational effect. However, it still accounted for less than half of the total effect of involvement in wartime atrocities on hostility, aggression, and suicidal ideation. Conclusions: These findings highlight the heightened risk conveyed by involvement in wartime atrocities and suggest that the psychological sequelae experienced following atrocity involvement may extend well beyond guilt and PTSD.
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.