The shaping of moral injury among UK military veterans of the wars in Afghanistan and Iraq
Abstract: Objective Research on 'moral injury'-the psychological wound experienced by military personnel and other 'functionaries' whose moral values are violated-has proliferated in recent years. Many psychological researchers, including those in the UK, have subscribed to an increasingly individualised operationalisation of moral injury, with medicalised criteria that closely mirrors PTSD. This trend carries assumptions that have not been comprehensively verified by empirical research. This study aims to explore UK military veterans' experiences of, and challenges to, their moral values in relation to their deployment experiences, without prematurely foreclosing exploration of wider systemic influences. Method Twelve UK military veterans who served in Afghanistan and/or Iraq were interviewed, and the data were analysed thematically and reflexively. Results Three inter-related themes were generated: (1) 'you've been undermined', (2) 'how am I involved in this?' and (3) 'civilianised'. Conclusions The analysis suggests that several assumptions privileged in moral injury research may be empirically contradicted, at least in relation to the experiences of UK military veterans. These assumptions include that moral injury is exclusively driven by individual, episodic acts of commission and omission, invariably leads to guilt and necessarily bifurcates into variants of either perpetration or betrayal. Instead, participants understood the moral violations they experienced as socially contingent. Rather than 'treating' moral injury as a disorder of thinking and feeling located within an individual, the socially contextualised understanding of moral injury indicated by this study's findings may prompt the development of psychological and social interventions that understand moral injury as the fallout of what occurs between people and within systems.
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.