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. Presentation formats consisted of text only, numeric only, gradient number line, and segmented number line. For each format viewed, participants answered questions regarding each outcome. RESULTS: Five hundred four participants (mean age 31 years) completed the survey. For the risk classification question, performance was high (93%) with no significant differences between presentation formats. There were main effects of risk level (all P < .001) such that participants perceived higher risk, were more likely to agree to treatment, and more trusting in their obstetrics team as the risk level increased, but we found inconsistencies in which presentation format corresponded to the highest perceived risk, trust, or behavioral intention. The gradient number line was the most preferred format (43%). DISCUSSION AND CONCLUSION: All formats resulted high accuracy related to the classification outcome (primary), but there were nuanced differences in risk perceptions, behavioral intentions, and trust. Investigators should choose health data visualizations based on the primary goal they want lay audiences to accomplish with the ML risk score.

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). We examined DNAm on eight candidate stress genes to compare physically and psychologically stressed participants to healthy (low stress) participants. We found unique CpGs that were differentially methylated in stressed women early- and mid-pregnancy compared to the healthy group, though none remained significant after FDR correction. Both physical and psychological stress were associated with hypomethylation at two consecutive CpG sites on NR3C1 in early pregnancy and one CpG site on NR3C1 in mid-pregnancy before adjustment. Stress was also associated with hypomethylation at two CpG sites on FKBP5 in early and mid-pregnancy but were no longer significant after FDR adjustment. Though we did not find statistically significant differences in DNAm during pregnancy between stressed and healthy women in this sample, signals were consistent with previous findings. Future work in larger samples should further examine the associations between stress and DNAm in pregnancy as this mechanism may explain underlying perinatal health inequities.

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. This bias may harm pregnant and birthing people by centering positions of power and privilege and by reflecting cultural priorities in the United States, including judgments of demographic and reproductive health characteristics. This commentary builds on relationship-centered care and reproductive justice frameworks to analyze the role and use of language in pregnancy and birth care in the United States, particularly regarding people with marginalized identities. We describe the use of language in written documentation, verbal communication, and behaviors associated with caring for pregnant people. We also present recommendations for change, including alternative language at the individual, clinician, hospital, health systems, and policy levels. We define birth as the emergence of a new individual from the body of its parent, no matter what intervention or pathology may be involved. Thus, we propose a cultural shift in hospital-based care for birthing people that centers the birthing person and reconceptualizes all births as physiologic events, approached with a spirit of care, partnership, and support.

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. Eligible studies had quantitative designs that analyzed urinary incontinence as the exposure or outcome variable. Critical appraisal was performed using the Joanna Briggs Institute Critical Appraisal Checklists. RESULTS: Ten studies were included. Most studies had methodological weaknesses in the measurement of conditions. Comorbidities affecting the neurologic, cardiovascular, psychologic, respiratory, endocrine, genitourinary, and musculoskeletal systems were found to be associated with urinary incontinence. CONCLUSION: Existing literature suggests that comorbidities and urinary incontinence are interrelated. Further research is needed to examine symptoms, shared mechanisms, and directionality of relationships to generate clinical phenotypes, evidence-based holistic care guidelines, and improve outcomes.

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. adults reporting female sex at birth focused on bioethical considerations for AI-based technologies in mental healthcare, stratifying by previous pregnancy. Survey respondents (n = 258) were open to AI-based technologies in mental healthcare but concerned about medical harm and inappropriate data sharing. They held clinicians, developers, healthcare systems, and the government responsible for harm. Most reported it was "very important" for them to understand AI output. More previously pregnant respondents reported being told AI played a small role in mental healthcare was "very important" versus those not previously pregnant (P = .03). We conclude that protections against harm, transparency around data use, preservation of the patient-clinician relationship, and patient comprehension of AI predictions may facilitate trust in AI-based technologies for mental healthcare among women.