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Introduction: Mental health of pregnant and post-partum women is sensitive to environmental factors. However, access to mental healthcare remains difficult, while little is known about protective factors nor about interactions between different exposures. Objectives: To explore on a large sample of women from the general population (i) the environmental and pregnancy characteristics independently associated with prenatal psychological distress and access to mental health care during pregnancy (ii) pathways between maternal, infant and parenthood vulnerabilities or risk/protective factors and postnatal depressive symtoms (PNDS) at 2 months post-partum (PP) Methods: The data from the French ELFE birth cohort were used. Available information about prenatal psychological status, access to mental health care and vulnerabilities-risk/protective factors for PNDS were collected during the maternity ward stay and at 2 months PP. PNDS were evaluated with the Edinburgh Postnatal Depression Scale (EPDS) at 2 months. Maternal/pregnancy characteristics independently associated with prenatal psychological distress and access to mental health care were explored using multivariate analyses. Pathways between risk/protective factors and PNDS at 2 months were investigated through Structural Equation Modeling. Results: Of the 15,143 mothers explored in the prenatal part of the study, 12.6% reported psychological distress (PPD), 25% had a prenatal consultation with a mental health specialist, 11% used psychotropic drugs of which 4% had no specialist follow-up. Decreased likelihood to consult a mental health specialist was found in young women, with intermediate educational level and born abroad. PPD was more frequent in women with very low economic status, alcohol/tobacco use, unplanned pregnancy, late pregnancy declaration, multiple and complicated pregnancy. In the postnatal part of the study (n=11,583) partner's perceived antenatal emotional support, consultation with a mental health specialist before pregnancy, financial difficulties, prenatal psychological distress and experience of pregnancy were directly associated with the severity of maternal PNDS at 2 months PP, as well as perceived postnatal support, infant's self-regulation skills, maternal ability to understand infant crying and infant hospitalisation. Conclusions: Perinatal professional support should begin antenatally and target the couple's prenatal functioning, with particular attention to women presenting history of psychiatric disorders, especially when of low socioeconomic status. After delivery, addressing infant and parenthood characteristics is recommended. Disclosure of Interest: None Declared [ABSTRACT FROM AUTHOR]

We present a magnetically shielded environment with a damping factor larger than 1×106 at the mHz frequency regime and an extremely low field and gradient over an extended volume. This extraordinary shielding performance represents an improvement of the state-of-the-art in the difficult regime of damping very low-frequency distortions by more than an order of magnitude. This technology enables a new generation of high-precision measurements in fundamental physics and metrology, including searches for new physics far beyond the reach of accelerator-based experiments. We discuss the technical realization of the shield with its improvements in design. [ABSTRACT FROM AUTHOR]

Illumination changes cause challenging problems for video surveillance algorithms, as objects of interest become masked by changes in background appearance. It is desired for such algorithms to maintain a consistent perception of a scene regardless of illumination variation. This work introduces a concept we call Big Background, which is a model for representing large, persistent scene features based on chromatic self-similarity. This model is found to comprise 50% to 90% of surveillance scenes. The large, stable regions represented by the model are used as reference points for performing illumination compensation. The presented compensation technique is demonstrated to decrease improper false-positive classification of background pixels by an average of 83% compared to the uncompensated case and by 25% to 43% compared to compensation techniques from the literature. [ABSTRACT FROM AUTHOR]

Pediatric fellowship programs have conducted virtual interviews since the start of the COVID-19 pandemic in 2020. In this national survey of fellowship program directors and fellows interviewed in-person and virtually, fellowship program directors and fellows formed accurate impressions, regardless of format, but our data did not clearly support one interview format over another., Competing Interests: Declaration of Competing Interest The study was supported by the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). APPD LEARN provided assistance with survey dissemination, data collection, and analysis. The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background/objective: Useful feedback and evaluation are critical to a medical trainee's development. While most academic physicians understand that giving feedback to learners is essential, many do not consider the components of feedback to be truly useful, and there are barriers to implementation. We sought to use a quick reader (QR) system to solicit feedback for trainees in two pediatric subspecialties (pediatric critical care and neonatal-perinatal medicine) at one institution to increase the quality and quantity of feedback received., Methods: New valuations were modified from the existing evaluations and imported into online systems with QR code capability. Each fellow was given a QR code linking to evaluations and encouraged to solicit feedback and evaluations in a variety of clinical settings and scenarios. Evaluation numbers and quality of evaluations were assessed and compared both pre- and post-intervention., Results: There were increases in the number of evaluations completed for both the pediatric critical care fellows and the neonatal-perinatal medicine fellows. There was no overall change in the quality of written evaluations received. Satisfaction with the evaluation system improved for both faculty and fellows of both training programs., Conclusion: In our critical care units, we were successfully able to implement a QR code-driven evaluation for our fellows that improved access for the faculty and offered the ability of the learner to solicit evaluations, without compromising the number or quality of evaluations. What's new: Quick reader (QR) codes can be used by learners to solicit evaluations and feedback from faculty. They can increase the quantity of written evaluations received without affecting their quality., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Kane et al.)

Background: While scientific knowledge of post-COVID-19 condition (PCC) is growing, there remains significant uncertainty in the definition of the disease, its expected clinical course, and its impact on daily functioning. Social media platforms can generate valuable insights into patient-reported health outcomes as the content is produced at high resolution by patients and caregivers, representing experiences that may be unavailable to most clinicians., Objective: In this study, we aimed to determine the validity and effectiveness of advanced natural language processing approaches built to derive insight into PCC-related patient-reported health outcomes from social media platforms Twitter and Reddit. We extracted PCC-related terms, including symptoms and conditions, and measured their occurrence frequency. We compared the outputs with human annotations and clinical outcomes and tracked symptom and condition term occurrences over time and locations to explore the pipeline's potential as a surveillance tool., Methods: We used bidirectional encoder representations from transformers (BERT) models to extract and normalize PCC symptom and condition terms from English posts on Twitter and Reddit. We compared 2 named entity recognition models and implemented a 2-step normalization task to map extracted terms to unique concepts in standardized terminology. The normalization steps were done using a semantic search approach with BERT biencoders. We evaluated the effectiveness of BERT models in extracting the terms using a human-annotated corpus and a proximity-based score. We also compared the validity and reliability of the extracted and normalized terms to a web-based survey with more than 3000 participants from several countries., Results: UmlsBERT-Clinical had the highest accuracy in predicting entities closest to those extracted by human annotators. Based on our findings, the top 3 most commonly occurring groups of PCC symptom and condition terms were systemic (such as fatigue), neuropsychiatric (such as anxiety and brain fog), and respiratory (such as shortness of breath). In addition, we also found novel symptom and condition terms that had not been categorized in previous studies, such as infection and pain. Regarding the co-occurring symptoms, the pair of fatigue and headaches was among the most co-occurring term pairs across both platforms. Based on the temporal analysis, the neuropsychiatric terms were the most prevalent, followed by the systemic category, on both social media platforms. Our spatial analysis concluded that 42% (10,938/26,247) of the analyzed terms included location information, with the majority coming from the United States, United Kingdom, and Canada., Conclusions: The outcome of our social media-derived pipeline is comparable with the results of peer-reviewed articles relevant to PCC symptoms. Overall, this study provides unique insights into patient-reported health outcomes of PCC and valuable information about the patient's journey that can help health care providers anticipate future needs., International Registered Report Identifier (irrid): RR2-10.1101/2022.12.14.22283419., (©Elham Dolatabadi, Diana Moyano, Michael Bales, Sofija Spasojevic, Rohan Bhambhoria, Junaid Bhatti, Shyamolima Debnath, Nicholas Hoell, Xin Li, Celine Leng, Sasha Nanda, Jad Saab, Esmat Sahak, Fanny Sie, Sara Uppal, Nirma Khatri Vadlamudi, Antoaneta Vladimirova, Artur Yakimovich, Xiaoxue Yang, Sedef Akinli Kocak, Angela M Cheung. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.09.2023.)