From active duty to activism: How moral injury and combat trauma drive political activism and societal reintegration among Israeli Veterans

Abstract: Introduction: Moral injury (MI) is a severe form of combat trauma that shatters soldiers' moral bearings as the result of killing in war. Among the myriad ways that moral injury affects veterans' reintegration into civilian life, its impact on political and societal reintegration remains largely unstudied but crucial for personal, community, and national health. Methods: 13 in-depth interviews examine combat soldiers' exposure to potentially morally injurious events (PMIEs) that include killing enemy combatants, harming civilians, and betrayal by commanders, the military system, and society. Interviewees also described their political activities (e.g., voting, fundraising, advocacy, protest) and social activism (e.g., volunteering, teaching, charitable work). Interviewees also completed the Moral Injury Symptom Scale. Results: Two distinct narratives process PMIEs. In a humanitarian narrative, soldiers hold themselves or their in-group morally responsible for perpetrating, witnessing, or failing to prevent a morally transgressive act such as killing or injuring civilians or placing others at unnecessary risk. In contrast, a national security perspective blames an out-group for leaving soldiers with no choice but to act in ways that trigger moral distress. Associated with shame and guilt, the humanitarian perspective triggered amends-making and social activism after discharge. In contrast, a national security perspective associated with anger and frustration fostered protest and intense political activism. Discussion: Despite its harmful health effects, moral trauma and injury can drive intense political and social activism, depending upon the narrative veterans adopt to interpret PMIEs. Aside from moral injury's personal, familial, and social effects, moral injury drives veterans' return to the political arena of civil society. As such, veterans play a central role in politics and dramatically affect post-war policy in democratic nations following conflict.

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.