Examining Changes in Posttraumatic Stress Disorder Symptoms and Substance Use Among a Sample of Canadian Veterans Working with Service Dogs: An Exploratory Patient- Oriented Longitudinal Study
Abstract: Comorbid posttraumatic stress disorder (PTSD) and substance use (SU) is a growing health concern among Canadian veterans. Veterans are increasingly seeking symptom relief for PTSD and comorbid SU by engaging service dogs (SDs). Despite promising results, the efficacy of SDs in aiding veterans warrants further investigation. An exploratory patientoriented, longitudinal, time-series, mixed-methods research design was employed with a sample of five Canadian veterans matched with SDs from AUDEAMUS, Inc. PTSD and SU were measured at six time points over 1 year with the Posttraumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual for Mental Disorders, 5th Edition (PCL-5), Drug Use Screening Inventory Revised Substance Use Subscale (DUSI-R SU), and one-onone semi-structured interviews. There were clinically significant decreases in the veterans’ PTSD scores with the PCL-5. Interview content complemented these results. Veterans offered accounts of ways in which their SDs directly supported and helped manage their PTSD and related symptoms. While DUSI-R SU scale changes were non-significant, during interviews each veteran reported a decrease in their use of opioids and alcohol, while some reported an increase in their use of medical cannabis. However, veterans also highlighted ways in which their SDs sometimes contributed to increases in their PTSD and related symptoms, as well as their SU. This was particularly evident during the early stages of training and bonding. This study makes an important contribution to the emerging field examining the potential benefit of SDs for veterans diagnosed with PTSD. Additionally, this study is novel in its identification of the SDs beneficial contributions to veterans’ comorbid problematic use of substances.
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.