Posttraumatic stress disorder and interpersonal process in homeless veterans participating in a peer mentoring intervention: Associations with program benefit
Abstract: Homelessness among veterans has dropped dramatically since the expansion of services for homeless veterans in 2009, and now engaging homeless veterans in existing programs will be important to continuing to make progress. While one promising approach for engaging homeless veterans in care is involving peer mentors in integrated services, posttraumatic stress disorder (PTSD) may diminish the effects of peer mentorship. This mixed methods study examined how interpersonal and emotional processes in homeless veterans with and without PTSD impacted their capacity to engage in relationships with peer mentors. Four focus groups of 5-8 homeless male veterans (N = 22) were drawn from a larger multisite randomized trial. Qualitative analysis identified five primary themes: disconnectedness; anger, hostility, or resentment; connecting with others; positive view of self; and feeling like an outsider. Thematic comparisons between participants with and without a self-reported PTSD diagnosis, and between those who did and did not benefit from the peer mentor program, were validated by using quantitative methods. Disconnectedness was associated with self-reported PTSD diagnosis and with lack of program benefit; feeling like an outsider was associated with program benefit. Results suggest that disruption to the capacity to develop and maintain social bonds in PTSD may interfere with the capacity to benefit from peer mentorship. Social rules and basic strategies for navigating interpersonal relationships may differ somewhat within the homeless community and outside of it; for veterans who feel disconnected from the domiciled community, a formerly homeless veteran peer may serve as a critical "bridge" between the two social worlds.
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.