Australian Veteran sexual health: '…you are the first person I've spoken to about it.'

Abstract: Background: Sexual health and functioning outcomes have been shown to be poor among veterans due to factors associated with military service, as well as barriers to healthcare access. However, there is currently limited research attempting to assess the scope and extent of these issues in the Australian context. Methods: Ten qualitative, semi-structured interviews were conducted with Australian professionals working within or adjacent to veteran sexual health and were analysed using inductive thematic analysis. Results: Sexual health and functioning issues commonly develop among Australian veterans due to a variety of physical, psychological and social factors. Factors include mental ill-health, physical illness and injury, use of medication, and relationship strain. These contribute to physiological dysfunctions, poor sexual behaviours and difficulties in forming healthy, meaningful intimate relationships. Barriers, such as lack of awareness and understanding, stigma, and structural barriers, were suggested to interfere with healthcare access and worsen outcomes. Key informants recommended increasing provider training, research and military support, as well as de-stigmatising sexual health issues. Conclusions: Veteran sexual health is not often on the radar of Australian health and research professionals. Our study is one of few studies in the Australian context, highlighting the need to conduct more research to better manage veteran sexual health and functioning needs.

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.