Baby Boot Camp: Facilitating Maternal Role Adaptation Among Military Wives
Abstract: Background: Current research suggests that women married to military service members may experience difficulty during the transition to motherhood attributable to the additional stressors of military life and inability to access traditional support systems. Objective: To test the effects of a nursing intervention on prenatal and postpartum maternal role adaptation among military wives. Methods: Primigravid military wives were assigned randomly to either a traditional childbirth education program (n = 47) or Baby Boot Camp (n = 44). The Baby Boot Camp is a 4-week childbirth-parenting preparation program based on a resilience paradigm. The strategies of Baby Boot Camp include identification of nontraditional external resources and development of internal resources to facilitate maternal role adaptation. The Prenatal Self-Evaluation Questionnaire, Personal Resource Questionnaire, and Resilience Scale were administered at baseline (32 to 37 weeks gestation), immediately after the intervention, and at 6 weeks postpartum. Results: The outcomes suggest that Baby Boot Camp strategies to enhance external and internal resources may have been successful in facilitating maternal role adaptation. An independent t-test showed that, as compared with the military wives who attended traditional childbirth education courses, the Baby Boot Camp participants experienced significantly greater prenatal and postpartum adaptation. As demonstrated by repeated measure analysis of variance, the Baby Boot Camp participants experienced an increase in external and internal resources immediately after the intervention. However, these differences in resources were not sustained at 6 weeks postpartum. Conclusions: The findings may lead to wider development and use of childbirth-parenting programs designed to meet the unique strengths and needs of the childbearing military wife.
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.