Impact of paternal deployment to the conflicts in Iraq and Afghanistan and paternal post-traumatic stress disorder on the children of military fathers
Abstract: Background: Little is known about the social and emotional well-being of children whose fathers have been deployed to the conflicts in Iraq/Afghanistan or who have post-traumatic stress disorder (PTSD). Aims: To examine the emotional and behavioural well-being of children whose fathers are or have been in the UK armed forces, in particular the effects of paternal deployment to the conflicts in Iraq or Afghanistan and paternal PTSD. Method: Fathers who had taken part in a large tri-service cohort and had children aged 3–16 years were asked about the emotional and behavioural well-being of their child(ren) and assessed for symptoms of PTSD via online questionnaires and telephone interview. Results: In total, 621 (67%) fathers participated, providing data on 1044 children. Paternal deployment to Iraq or Afghanistan was not associated with childhood emotional and behavioural difficulties. Paternal probable PTSD were associated with child hyperactivity. This finding was limited to boys and those under 11 years of age. Conclusions: This study showed that adverse childhood emotional and behavioural well-being was not associated with paternal deployment but was associated with paternal probable 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.