Differing perspectives on artificial intelligence in mental healthcare among patients: a cross-sectional survey study.

Introduction: Artificial intelligence (AI) is being developed for mental healthcare, but patients' perspectives on its use are unknown. This study examined differences in attitudes towards AI being used in mental healthcare by history of mental illness, current mental health status, demographic characteristics, and social determinants of health.

Methods: We conducted a cross-sectional survey of an online sample of 500 adults asking about general perspectives, comfort with AI, specific concerns, explainability and transparency, responsibility and trust, and the importance of relevant bioethical constructs.

Secondary Qualitative Analysis of Stigmatizing and Nonstigmatizing Language Used in Hospital Birth Settings.

Objective: To more clearly understand the use of stigmatizing and nonstigmatizing language in electronic health records in hospital birth settings and to broaden the understanding of discrimination and implicit bias in clinical care.

Design: A secondary qualitative analysis of free-text clinical notes from electronic health records.

Setting: Two urban hospitals in the northeastern United States that serve patients with diverse sociodemographic characteristics during the perinatal period.

Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing.

Objective: To identify stigmatizing language in obstetric clinical notes using natural language processing (NLP).

Materials And Methods: We analyzed electronic health records from birth admissions in the Northeast United States in 2017. We annotated 1771 clinical notes to generate the initial gold standard dataset.

Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.

Background: The application of artificial intelligence (AI) to health and health care is rapidly increasing. Several studies have assessed the attitudes of health professionals, but far fewer studies have explored the perspectives of patients or the general public. Studies investigating patient perspectives have focused on somatic issues, including those related to radiology, perinatal health, and general applications.

A systematic review of community-based interventions to address perinatal mental health.

Little is known about the scope and effectiveness of community-based interventions to address maternal perinatal mental health in the US. We searched PubMed, CINAHL, and PsychINFO in January 2024 to conduct a systematic review of studies using community-based interventions for maternal mental health from pregnancy to 1 year postpartum in the US. We reviewed 22 quantitative studies, and assessed methodological quality and effectiveness of interventions.

An evaluation of conceptual frameworks to improve reproductive health outcomes among women with physical disabilities.

Aim(s): To identify and evaluate conceptual frameworks intended to guide reproductive health research among women with physical disabilities.

Design: Discussion paper.

Methods: We identified and evaluated frameworks related to the reproductive health of women with physical disabilities using modified criteria by Fawcett and DeSanto-Madeya with constructs from the International Classification of Functioning, Disability, and Health.

Stress and DNA Methylation of Blood Leukocytes among Pregnant Latina Women.

Latinas experience physical and psychological stressors in pregnancy leading to increased morbidity and higher risk for adverse birth outcomes. Epigenetic changes, including DNA methylation (DNAm), have been proposed as markers to create more refined risk stratification, yet few of these studies have examined these changes in Latinas. We conducted a secondary analysis of stored blood leukocytes of Latina women (n = 58) enrolled in a larger National Institutes of Health funded R01 project (2011-2016).

Visualizing machine learning-based predictions of postpartum depression risk for lay audiences.

Objectives: To determine if different formats for conveying machine learning (ML)-derived postpartum depression risks impact patient classification of recommended actions (primary outcome) and intention to seek care, perceived risk, trust, and preferences (secondary outcomes).

Materials And Methods: We recruited English-speaking females of childbearing age (18-45 years) using an online survey platform. We created 2 exposure variables (presentation format and risk severity), each with 4 levels, manipulated within-subject.

The Power of Language in Hospital Care for Pregnant and Birthing People: A Vision for Change.

Language is commonly defined as the principal method of human communication made up of words and conveyed by writing, speech, or nonverbal expression. In the context of clinical care, language has power and meaning and reflects priorities, beliefs, values, and culture. Stigmatizing language can communicate unintended meanings that perpetuate socially constructed power dynamics and result in bias.

Comorbidities of community-dwelling older adults with urinary incontinence: A scoping review.

Background: Identifying comorbidities is a critical first step to building clinical phenotypes to improve assessment, management, and outcomes.

Objectives: 1) Identify relevant comorbidities of community-dwelling older adults with urinary incontinence, 2) provide insights about relationships between conditions.

Methods: PubMed, Cumulative Index of Nursing and Allied Health Literature, and Embase were searched.

Women's perspectives on the use of artificial intelligence (AI)-based technologies in mental healthcare.

This study aimed to evaluate women's attitudes towards artificial intelligence (AI)-based technologies used in mental health care. We conducted a cross-sectional, online survey of U.S.