Protocol for Designing a Model to Predict the Likelihood of Psychosis From Electronic Health Records Using Natural Language Processing and Machine Learning.

Introduction: Rapid identification of individuals developing a psychotic spectrum disorder (PSD) is crucial because untreated psychosis is associated with poor outcomes and decreased treatment response. Lack of recognition of early psychotic symptoms often delays diagnosis, further worsening these outcomes.

Methods: The proposed study is a cross-sectional, retrospective analysis of electronic health record data including clinician documentation and patient-clinician secure messages for patients aged 15-29 years with ≥ 1 primary care encounter between 2017 and 2019 within 2 Kaiser Permanente regions.

Perspectives from women who engaged in prenatal and postpartum cannabis use in a U.S. State with legal non-medical use.

Evidence suggests fetal risks are associated with cannabis use during pregnancy. Yet, insights into women's decision-making and cannabis use during pregnancy are limited. This study explored these concepts with postpartum women who used cannabis during and after pregnancy.

Getting through the day: a pilot qualitative study of U.S. women's experiences making decisions about anti-nausea medication during pregnancy.

Background: Nausea during pregnancy affects 80% of pregnant women and can severely affect women's functioning and quality of life. Women often have difficulty deciding whether to take anti-nausea medications due to concern about medication risks. This paper foregrounds U.

"It's a Very Big Burden on Me": Women's Experiences Using Insulin for Gestational Diabetes.

Objectives Gestational Diabetes Mellitus (GDM) affects hundreds of thousands of women each year. Many require medications to manage their blood glucose levels. Only insulin is approved by the U.