Associations among military sexual trauma, positive alcohol expectancies, and coping behaviors in female veterans
Abstract: Military sexual trauma (MST) is prevalent among female veterans and is associated with deleterious health outcomes. Adaptive coping strategies (e.g., emotional support) are associated with more positive outcomes, while maladaptive strategies (e.g., substance use) are associated with greater impairment. However, research on factors that influence specific coping strategy use is limited. For women with a history of MST, expectancies about the effects of alcohol may enhance the use of maladaptive and reduce the use of adaptive strategies. The present study tested this hypothesis. Associations among MST status and two coping behaviors (emotional support, substance use) in female veterans were examined and the mediating role of positive alcohol expectancies on these relationships was tested. A secondary analysis was conducted using self-report survey data from 186 female veterans in a Northeastern region. Measures included a brief screen for MST, the posttraumatic stress disorder (PTSD) Checklist for DSM-5, the Brief Cope, and the Brief Comprehensive Effects of Alcohol Questionnaire. Among all respondents, positive alcohol expectancies were significantly associated with greater substance use coping, while PTSD symptom severity was negatively associated with emotional support coping. Though women with MST reported greater positive alcohol expectancies and PTSD symptom severity, the direct effects of MST on coping were not significant. Mediation was not supported in our sample. Alcohol expectancies may be a viable target for intervention to reduce alcohol use as a maladaptive coping strategy among female veterans. Similarly, treatment targeting PTSD symptoms, regardless of MST status, is important for enhancing the use of adaptive coping strategies.
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.