R.E.S.I.L.I.E.N.C.E. A prevention and awareness training for military sexual violence: Intersectional approach

Abstract: In 1988, the Department of Defense initiated regular surveillance of sexual harassment and sexual assault victimization experiences among active-duty personnel. In 2005, the Sexual Assault Prevention and Response Office was established by the Department of Defense to centralize all efforts related to sexual assault. Despite efforts at prevention and response, in 2018, the numbers were still reportedly climbing, with 20,500 cases across military branches reporting sexual assault. The military is facing significant challenges regarding the reporting of sexual violence, establishing trust, creating a positive climate, and cultivating a supportive culture. Since Veteran Affairs employs a significant number of masters-level social workers, there is a vast reservoir of knowledge that can be tapped into to educate and train future military social workers and establish a highly skilled military social work workforce. This capstone project purpose is to offer a training program that offers an opportunity to incorporate trauma-informed, military-specific information, including recognizing the diverse social identities of those affected, which contribute to the heightened risk and vulnerability to sexual violence. This project was informed by systems theory, leadership theories including transformational leadership and experiential learning theory, and intersectionality. This project will use a quasi-experimental design including a pre and posttest, hypothesizing that the training participants will have an increase in knowledge and understanding of sexual violence prevention and awareness efforts after completing the training. This product aims to ensure that individuals from the community or the military actively participate in sexual violence prevention efforts and have a foundational understanding of its implications in social, political, and environmental contexts.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    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.

    Mental Health Peer reviewed