The association of delivery during a war with the risk for postpartum depression, anxiety and impaired maternal-infant bonding, a prospective cohort study.

Objective: To examine the impact of war conditions on maternal mental health postpartum outcomes, specifically depression and anxiety, as well as on maternal-infant bonding (MIB).

Study Design: A prospective cohort study was performed on women who gave birth in a tertiary medical center during (October-November 2023) and before (March-May 2020) the Israel-Hamas War. All participants completed validated self-reported questionnaires: The Edinburgh Postnatal Depression Scale (EPDS ≥ 10), State-Trait Anxiety Inventory (STAI > 39) and the Postpartum Bonding Questionnaire (PBQ ≥ 26).

Cortico-limbic interactions and carotid atherosclerotic burden during chronic stress exposure.

Background And Aims: Chronic stress associates with cardiovascular disease, but mechanisms remain incompletely defined. Advanced imaging was used to identify stress-related neural imaging phenotypes associated with atherosclerosis.

Methods: Twenty-seven individuals with post-traumatic stress disorder (PTSD), 45 trauma-exposed controls without PTSD, and 22 healthy controls underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI).

AI and narrative embeddings detect PTSD following childbirth via birth stories.

Free-text analysis using machine learning (ML)-based natural language processing (NLP) shows promise for diagnosing psychiatric conditions. Chat Generative Pre-trained Transformer (ChatGPT) has demonstrated preliminary initial feasibility for this purpose; however, whether it can accurately assess mental illness remains to be determined. This study evaluates the effectiveness of ChatGPT and the text-embedding-ada-002 (ADA) model in detecting post-traumatic stress disorder following childbirth (CB-PTSD), a maternal postpartum mental illness affecting millions of women annually, with no standard screening protocol.

Persistence of collective memory of corporate bankruptcy events discussed on X (Twitter) is influenced by pre-bankruptcy public attention.

Collective attention and memory involving significant events can be quantitatively studied via social media data. Previous studies analyzed user attention to discrete events that do not change post-event, and assume universal public attention patterns. However, dynamic events with ongoing updates are common, yielding varied individual attention patterns.