The relationship between PTSD and chronic pain: Mediating role of coping strategies and depression
Abstract: People with chronic pain and comorbid posttraumatic stress disorder (PTSD) report more severe pain and poorer quality of life than those with chronic pain alone. This study evaluated the extent to which associations between PTSD and chronic pain interference and severity are mediated by pain-related coping strategies and depressive symptoms. Veterans with chronic pain were divided into 2 groups, those with (n = 65) and those without (n = 136) concurrent PTSD. All participants completed measures of pain severity, interference, emotional functioning, and coping strategies. Those with current PTSD reported significantly greater pain severity and pain interference, had more symptoms of depression, and were more likely to meet diagnostic criteria for a current alcohol or substance use disorder (all p-values <.01). Participants with PTSD reported more use of several coping strategies, including guarding, resting, relaxation, exercise/stretching, and coping self-statements. Illness-focused pain coping (i.e., guarding, resting, and asking for assistance) and depressive symptoms jointly mediated the relationship between PTSD and both pain interference (total indirect effect = 0.194, p < .001) and pain severity (total indirect effect = 0.153, p = .004). Illness-focused pain coping also evidenced specific mediating effects, independent of depression. In summary, specific pain coping strategies and depressive symptoms partially mediated the relationship between PTSD and both pain interference and severity. Future research should examine whether changes in types of coping strategies after targeted treatments predict improvements in pain-related function for chronic pain patients with concurrent PTSD.
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.