Psychological and Sociological Profile of Women Who Have Completed Elite Military Combat Training
Abstract: More than 75 women have successfully graduated from the U.S. Army Ranger Course since the integration of women into elite military combat training. This study sought to identify the psychological characteristics and sociological variables that contributed to their motivation and success. A guided interview and demographic and psychological questionnaires were used to assess characteristics of 13 women who successfully completed elite military combat training. Collectively, these women were college graduates and had well educated fathers, possessed high levels of grit and resiliency, and described themselves as self-competitive challenge seekers. These women all had a strong male influence in their lives. The characteristics of these pioneer women may be unique from subsequent cohorts as female participation in elite military combat training becomes the norm and as attitudes and experiences change for graduates of female combat training over time.
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.