Predicting newborn birth outcomes with prenatal maternal health features and correlates in the United States: a machine learning approach using archival data.

Background: Newborns are shaped by prenatal maternal experiences. These include a pregnant person's physical health, prior pregnancy experiences, emotion regulation, and socially determined health markers. We used a series of machine learning models to predict markers of fetal growth and development-specifically, newborn birthweight and head circumference (HC).

Effects of a Digital Mental Health Intervention on Perceived Stress and Rumination in Adolescents Aged 13 to 17 Years: Randomized Controlled Trial.

Background: Although adolescents report high levels of stress, they report engaging in few stress management techniques. Consequently, developing effective and targeted programs to help address this transdiagnostic risk factor in adolescence is particularly important. Most stress management programs for adolescents are delivered within schools, and the evidence for these programs is mixed, suggesting a need for alternative options for stress management among adolescents.