Sexual risk taking among survivors of uS Military sexual assault: Associations with ptsd symptom severity and alcohol use
Abstract: Sexual risk taking may be heightened among U.S. service members and veterans reporting military sexual assault (MSA) exposure. MSA increases the risk for posttraumatic stress disorder (PTSD), which is a common correlate of sexual risk taking among civilians. PTSD may relate to sexual risk taking through its association with alcohol use, which increases impulsivity and risky behavioral engagement. Male survivors may be at notably higher risk given greater overall alcohol use and engagement in sexual risk taking relative to female survivors. This study assessed whether higher alcohol use mediated the association between PTSD and sexual risk taking among MSA survivors, and whether this effect differed by sex. Participants included 200 male and 200 female service members and veterans (age: M = 35.89, SD = 5.56) who completed measures of PTSD symptoms, alcohol use, sexual risk taking, and a demographic inventory. In a moderated mediation analysis using linear regression, higher PTSD severity was associated with higher alcohol use, and higher alcohol use was associated with higher sexual risk taking. A significant indirect effect of alcohol use was observed, which was stronger among men. To reduce sexual risk taking among MSA survivors, it may be beneficial to target PTSD symptoms and alcohol use with sex-specific interventions. This line of inquiry would be strengthened by longitudinal studies that explore the fluidity of these experiences to identify periods of elevated risk. Studies that examine alcohol use expectancies and sexual delay discounting could expand our understanding of these associations.
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.