701 research outputs found

    Regional differences in the quality of maternal and neonatal care during the COVID-19 pandemic in Portugal: results from the IMAgiNE EURO study

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    Objective: To compare women's perspectives on the quality of maternal and newborn care (QMNC) around the time of childbirth across Nomenclature of Territorial Units for Statistics 2 (NUTS-II) regions in Portugal during the COVID-19 pandemic. Methods: Women participating in the cross-sectional IMAgiNE EURO study who gave birth in Portugal from March 1, 2020, to October 28, 2021, completed a structured questionnaire with 40 key WHO standards-based quality measures. Four domains of QMNC were assessed: (1) provision of care; (2) experience of care; (3) availability of human and physical resources; and (4) reorganizational changes due to the COVID-19 pandemic. Frequencies for each quality measure within each QMNC domain were computed overall and by region. Results: Out of 1845 participants, one-third (33.7%) had a cesarean. Examples of high-quality care included: low frequencies of lack of early breastfeeding and rooming-in (8.0% and 7.7%, respectively) and informal payment (0.7%); adequate staff professionalism (94.6%); adequate room comfort and equipment (95.2%). However, substandard practices with large heterogeneity across regions were also reported. Among women who experienced labor, the percentage of instrumental vaginal births ranged from 22.3% in the Algarve to 33.5% in Center; among these, fundal pressure ranged from 34.8% in Lisbon to 66.7% in Center. Episiotomy was performed in 39.3% of noninstrumental vaginal births with variations between 31.8% in the North to 59.8% in Center. One in four women reported inadequate breastfeeding support (26.1%, ranging from 19.4% in Algarve to 31.5% in Lisbon). One in five reported no exclusive breastfeeding at discharge (22.1%; 19.5% in Lisbon to 28.2% in Algarve). Conclusion: Urgent actions are needed to harmonize QMNC and reduce inequities across regions in Portugal.info:eu-repo/semantics/publishedVersio

    The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

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    The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

    Quality of health care around the time of childbirth during the COVID-19 pandemic: Results from the IMAgiNE EURO study in Norway and trends over time

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    Objective: To describe maternal perception of the quality of maternal and newborn care (QMNC) in facilities in Norway during the first year of COVID-19 pandemic. Methods: Women who gave birth in a Norwegian facility from March 1, 2020, to October 28, 2021, filled out a structured online questionnaire based on 40 WHO standards-based quality measures. Quantile regression analysis was performed to assess changes in QMNC index over time. Results: Among 3326 women included, 3085 experienced labor. Of those, 1799 (58.3%) reported that their partner could not be present as much as needed, 918 (29.8%) noted inadequate staff numbers, 183 (43.6%) lacked a consent request for instrumental vaginal birth (IVB), 1067 (34.6%) reported inadequate communication from staff, 78 (18.6%) reported fundal pressure during IVB, 670 (21.7%) reported that they were not treated with dignity, and 249 (8.1%) reported experiencing abuse. The QMNC index increased gradually over time (3.68 points per month, 95% CI, 2.83– 4.53 for the median), with the domains of COVID-19 reorganizational changes and experience of care displaying the greatest increases, while provision of care was stable over time. Conclusion: Although several measures showed high QMNC in Norway during the first year of the COVID-19 pandemic, and a gradual improvement over time, several findings suggest that gaps in QMNC exist. These gaps should be addressed and monitored

    A synthesis of evidence for policy from behavioural science during COVID-19

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    Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

    A synthesis of evidence for policy from behavioural science during COVID-19

    Get PDF
    Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

    Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

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    A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

    Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV