The US framework for understanding, preventing, and caring for the mental health needs of service members who served in combat in Afghanistan and Iraq: a brief review of the issues and the research
Abstract: This paper reviews the psychological health research conducted in the United States in support of combat veterans from Iraq and Afghanistan, using the Military Psychological Health Research Continuum, which includes foundational science, epidemiology, etiology, prevention and screening, treatment, follow-up care, and services research. The review is limited to those studies involving combat veterans and military families. This review discusses perplexing issues regarding the impact of combat on the mental health of service members such as risk and resilience factors of mental health, biomarkers of posttraumatic stress syndrome (PTSD), mental health training, psychological screening, psychological debriefing, third location decompression, combat and suicide, the usefulness of psychotherapy and drug therapy for treating PTSD, role of advanced technology, telemedicine and virtual reality, methods to reduce stigma and barriers to care, and best approaches to the dissemination of evidence-based interventions. The mental health research of special populations such as women, National Guardsmen and reservists, and military families is also presented. The review concludes by identifying future areas of research.
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.