How work‐related guilt informs parenting and adolescent psychological distress in military families
Abstract: The current study examined inconsistent discipline as a linking mechanism connecting parental guilt about work to adolescent psychological distress in military families. Military families may face tensions connected to competing demands of family and the military career, which can produce a sense of parental guilt. This guilt may contribute to poor parenting behaviors, such as inconsistent discipline, which can be detrimental for adolescents (e.g., leading to depression and anxiety). A structural equation model with data from 223 military families (i.e., active duty father, civilian mother, and adolescent) examined the associations among parental guilt, inconsistent discipline, and adolescent psychological distress. Active duty fathers' guilt and inconsistent discipline were related to their perceptions of adolescent psychological distress, whereas civilian mothers' guilt was indirectly related to both their own and their partner's perceptions of adolescent psychological distress through their inconsistent discipline. Inconsistent discipline is a parenting behavior related to parental guilt and adolescent psychological distress. More research is needed to better understand the nuances of military contexts for families. Inconsistent discipline is a specific, malleable parenting behavior with implications for prevention and intervention programs designed for military families as well as family-related policies in the military.
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.