Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

We developed Multivariate Adaptive Regression Splines (MARS) machine learning models of chronic stressors using the Pregnancy Risk Assessment Monitoring System data (2012-2017) to predict preterm birth (PTB) more accurately and identify chronic stressors driving PTB among non-Hispanic (N-H) Black and N-H White pregnant women in the U.S. We trained the MARS models using 5-fold cross-validation, whose performance was evaluated with AUC.

Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model.

Background: Differential exposure to chronic stressors by race/ethnicity may help explain Black-White inequalities in rates of preterm birth. However, researchers have not investigated the cumulative, interactive, and population-specific nature of chronic stressor exposures and their possible nonlinear associations with preterm birth. Models capable of computing such high-dimensional associations that could differ by race/ethnicity are needed.

The Management of Posttraumatic Stress Disorder and Acute Stress Disorder: Synopsis of the 2023 U.S. Department of Veterans Affairs and U.S. Department of Defense Clinical Practice Guideline.

Description: The U.S. Department of Veterans Affairs (VA) and Department of Defense (DoD) worked together to revise the 2017 VA/DoD Clinical Practice Guideline for the Management of Posttraumatic Stress Disorder and Acute Stress Disorder.

End Users' Perceived Engagement with Clinical Dashboards: A Rapid Review.

Clinical dashboards are an emerging and fast-evolving technology used to support frontline clinicians' practice. Understanding end users' perceived engagement with clinical dashboards is essential to co-design, implementation, and adoption. There is a lack of literature exploring the integration of dashboards into clinical workflow.