Digital phenotyping of depression during pregnancy using self-report data.

Background: Depression is a common pregnancy complication yet is often under-detected and, subsequently, undertreated. Data collected through mobile health tools may be used to support the identification of depression symptoms in pregnancy.

Methods: An observational cohort study of 2062 pregnancies collected self-reports of patient history, mood, pregnancy-specific symptoms, and written language using a prenatal support app.

A Model for Engaging Citizen Scientists: A Community-Partnered Research Collaboration to Address Inequities for Black Birthing People.

Purpose: Co-creation of a citizen-science research initiative with a collaborative team of community members and university-based scientists to address regional disparities in maternal and fetal health outcomes for Black birthing people.

Description: Citizen scientist-led projects, where community members actively contribute to each discovery step, from setting a research agenda to collecting data and disseminating results, can extend community participatory research initiatives and help reconceptualize traditional research processes. The Pregnancy Collaborative is a citizen-science research initiative and one of nine scientific committees of The Pittsburgh Study-a longitudinal, community-partnered study designed to bring together collaborators to improve child thriving.

Predicting first time depression onset in pregnancy: applying machine learning methods to patient-reported data.

Purpose: To develop a machine learning algorithm, using patient-reported data from early pregnancy, to predict later onset of first time moderate-to-severe depression.

Methods: A sample of 944 U.S.

Benefits, Harms, and Stakeholder Perspectives Regarding Opioid Therapy for Pain in Individuals With Metastatic Cancer: Protocol for a Descriptive Cohort Study.

Background: Opioids are a key component of pain management among patients with metastatic cancer pain. However, the evidence base available to guide opioid-related decision-making in individuals with advanced cancer is limited. Patients with advanced cancer or cancer that is unlikely to be cured frequently experience pain.

Decision-making and Treatment Preferences Surrounding Bacteriuria in Nonpregnant Women: A Qualitative Investigation.

Introduction And Hypothesis: Best practices suggest nontreatment for asymptomatic bacteriuria in a nonpregnant population, yet there is little literature on patient preference or understanding of asymptomatic bacteriuria treatment. We hypothesize that there might be core factors that affect antibiotic preferences and care-seeking decisions for urinary tract infection and asymptomatic bacteriuria in a postmenopausal population.

Methods: We performed semi-structured interviews with postmenopausal individuals who had been previously treated for at least one patient-reported urinary tract infection.