Identity and Remembrance in the New Zealand Ex-Prisoners of War Association after the Second World War
Abstract: Captivity was the antithesis of what soldiers expected to experience during the Second World War. New Zealanders who were captured had to reconcile the difference between traditional narratives of wartime heroism with their experience of confinement, which, for some, included assisting the enemy war effort through forced labour. This paper examines the New Zealand Ex-Prisoners of War (POW) Association’s quarterly newsletter and argues that the association was instrumental to the development and promotion of a more positive POW experience. Ex-POWs were usually reluctant to share their stories, but within the confines of this support network they felt comfortable in the knowledge that they were surrounded by people who understood what they had endured. This paper also argues that the hesitancy of ex-POWs to talk about their experiences left future generations ignorant to what captivity had been like. This was partly rectified by the enquiries made by relatives during the association’s final years.
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.