148 research outputs found

    Differential psychological response to the COVID-19 pandemic in psychiatric inpatients compared to a non-clinical population from Germany

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    The COVID-19 pandemic is an inherently stressful situation, which may lead to adverse psychosocial outcomes in various populations. Yet, individuals may not be affected equally by stressors posed by the pandemic and those with pre-existing mental disorders could be particularly vulnerable. To test this hypothesis, we assessed the psychological response to the pandemic in a case-control design. We used an age-, sex- and employment status-matched case-control sample (n = 216) of psychiatric inpatients, recruited from the LMU Psychiatry Biobank Munich study and non-clinical individuals from the general population. Participants completed validated self-report measures on stress, anxiety, depression, paranoia, rumination, loneliness, well-being, resilience, and a newly developed index of stressors associated with the COVID-19 pandemic. Multiple linear regression analyses were conducted to assess the effects of group, COVID-19-specific stressors, and their interaction on the different psychosocial outcomes. While psychiatric inpatients reported larger mental health difficulties overall, the impact of COVID-19-specific stressors was lower in patients and not associated with worse psychological functioning compared to non-clinical individuals. In contrast, depressive symptoms, rumination, loneliness, and well-being were more strongly associated with COVID-19-specific stressors in non-clinical individuals and similar to the severity of inpatients for those who experienced the greatest COVID-19-specific stressor impact Contrary to expectations, the psychological response to the pandemic may not be worse in psychiatric inpatients compared to non-clinical individuals. Yet, individuals from the general population, who were hit hardest by the pandemic, should be monitored and may be in need of mental health prevention and treatment efforts

    The COVID-19 Pandemic Mental Health Questionnaire (CoPaQ): psychometric evaluation and compliance with countermeasures in psychiatric inpatients and non-clinical individuals

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    BACKGROUND The COVID-19 pandemic has greatly impacted people's lives across a broad spectrum of psychosocial domains. We report the development and psychometric evaluation of the self-report COVID-19 Pandemic Mental Health Questionnaire (CoPaQ), which assesses COVID-19 contamination anxiety, countermeasure necessity and compliance, mental health impact, stressor impact, social media usage, interpersonal conflicts, paranoid ideations, institutional & political trust, conspiracy beliefs, and social cohesion. Further, we illustrate the questionnaire's utility in an applied example investigating if higher SARS-Cov-2 infection rates in psychiatric patients could be explained by reduced compliance with preventive countermeasures. METHODS A group of 511 non-clinical individuals completed an initial pool of 111 CoPaQ items (Open Science Framework: https://osf.io/3evn9/ ) and additional scales measuring psychological distress, well-being, and paranoia to assess construct validity and lifetime mental health diagnosis for criterion validity. Factor structure was determined by exploratory factor analyses and validated by conducting confirmatory factor analysis in the accompanying longitudinal sample (n~= 318) and an independent psychiatric inpatient sample primarily admitted for major depressive-, substance abuse-, personality-, and anxiety disorders (n~= 113). Internal consistency was assessed by Cronbach's Alpha and McDonald's Omega. For the applied research example, Welch t-tests and correlational analyses were conducted. RESULTS Twelve out of 16 extracted subscales were retained in the final questionnaire version, which provided preliminary evidence for adequate psychometric properties in terms of factor structure, internal consistency, and construct and criterion validity. Our applied research example showed that patients exhibited greater support for COVID-19 countermeasures than non-clinical individuals. However, this requires replication in future studies. CONCLUSIONS We demonstrate that the CoPaQ is a comprehensive and valid measure of the psychosocial impact of the pandemic and could allow to a degree to disentangle the complex psychosocial phenomena of the pandemic as exemplified by our applied analyses

    Incremental k-core decomposition: algorithms and evaluation

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    A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. For a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms. © 2016, Springer-Verlag Berlin Heidelberg

    Inhaled budesonide for COVID-19 in people at high risk of complications in the community in the UK (PRINCIPLE): a randomised, controlled, open-label, adaptive platform trial

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    This is the final version. Available on open access from Elsevier via the DOI in this recordData sharing; Data can be shared with qualifying researchers who submit a proposal with a valuable research question as assessed by a committee formed from the trial management group, including senior statistical and clinical representation. A contract should be signed.Background A previous efficacy trial found benefit from inhaled budesonide for COVID-19 in patients not admitted to hospital, but effectiveness in high-risk individuals is unknown. We aimed to establish whether inhaled budesonide reduces time to recovery and COVID-19-related hospital admissions or deaths among people at high risk of complications in the community. Methods PRINCIPLE is a multicentre, open-label, multi-arm, randomised, controlled, adaptive platform trial done remotely from a central trial site and at primary care centres in the UK. Eligible participants were aged 65 years or older or 50 years or older with comorbidities, and unwell for up to 14 days with suspected COVID-19 but not admitted to hospital. Participants were randomly assigned to usual care, usual care plus inhaled budesonide (800 ÎŒg twice daily for 14 days), or usual care plus other interventions, and followed up for 28 days. Participants were aware of group assignment. The coprimary endpoints are time to first self-reported recovery and hospital admission or death related to COVID-19, within 28 days, analysed using Bayesian models. The primary analysis population included all eligible SARS-CoV-2-positive participants randomly assigned to budesonide, usual care, and other interventions, from the start of the platform trial until the budesonide group was closed. This trial is registered at the ISRCTN registry (ISRCTN86534580) and is ongoing. Findings The trial began enrolment on April 2, 2020, with randomisation to budesonide from Nov 27, 2020, until March 31, 2021, when the prespecified time to recovery superiority criterion was met. 4700 participants were randomly assigned to budesonide (n=1073), usual care alone (n=1988), or other treatments (n=1639). The primary analysis model includes 2530 SARS-CoV-2-positive participants, with 787 in the budesonide group, 1069 in the usual care group, and 974 receiving other treatments. There was a benefit in time to first self-reported recovery of an estimated 2·94 days (95% Bayesian credible interval [BCI] 1·19 to 5·12) in the budesonide group versus the usual care group (11·8 days [95% BCI 10·0 to 14·1] vs 14·7 days [12·3 to 18·0]; hazard ratio 1·21 [95% BCI 1·08 to 1·36]), with a probability of superiority greater than 0·999, meeting the prespecified superiority threshold of 0·99. For the hospital admission or death outcome, the estimated rate was 6·8% (95% BCI 4·1 to 10·2) in the budesonide group versus 8·8% (5·5 to 12·7) in the usual care group (estimated absolute difference 2·0% [95% BCI –0·2 to 4·5]; odds ratio 0·75 [95% BCI 0·55 to 1·03]), with a probability of superiority 0·963, below the prespecified superiority threshold of 0·975. Two participants in the budesonide group and four in the usual care group had serious adverse events (hospital admissions unrelated to COVID-19). Interpretation Inhaled budesonide improves time to recovery, with a chance of also reducing hospital admissions or deaths (although our results did not meet the superiority threshold), in people with COVID-19 in the community who are at higher risk of complications.National Institute for Health Research (NIHR)Wellcome Trus

    Combinatoriality in the vocal systems of nonhuman animals

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    A key challenge in the field of human language evolution is the identification of the selective conditions that gave rise to language's generative nature. Comparative data on nonhuman animals provides a powerful tool to investigate similarities and differences among nonhuman and human communication systems and to reveal convergent evolutionary mechanisms. In this article, we provide an overview of the current evidence for combinatorial structures found in the vocal system of diverse species. We show that considerable structural diversity exits across and within species in the forms of combinatorial structures used. Based on this we suggest that a fine‐grained classification and differentiation of combinatoriality is a useful approach permitting systematic comparisons across animals. Specifically, this will help to identify factors that might promote the emergence of combinatoriality and, crucially, whether differences in combinatorial mechanisms might be driven by variations in social and ecological conditions or cognitive capacities

    Measurement of the dependence of transverse energy production at large pseudorapidity on the hard-scattering kinematics of proton-proton collisions at √s=2.76 TeV with ATLAS

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    The relationship between jet production in the central region and the underlying-event activity in a pseudorapidity-separated region is studied in 4.0 pb-1 of s=2.76 TeV pp collision data recorded with the ATLAS detector at the LHC. The underlying event is characterised through measurements of the average value of the sum of the transverse energy at large pseudorapidity downstream of one of the protons, which are reported here as a function of hard-scattering kinematic variables. The hard scattering is characterised by the average transverse momentum and pseudorapidity of the two highest transverse momentum jets in the event. The dijet kinematics are used to estimate, on an event-by-event basis, the scaled longitudinal momenta of the hard-scattered partons in the target and projectile beam-protons moving toward and away from the region measuring transverse energy, respectively. Transverse energy production at large pseudorapidity is observed to decrease with a linear dependence on the longitudinal momentum fraction in the target proton and to depend only weakly on that in the projectile proton. The results are compared to the predictions of various Monte Carlo event generators, which qualitatively reproduce the trends observed in data but generally underpredict the overall level of transverse energy at forward pseudorapidity

    Measurement of W boson angular distributions in events with high transverse momentum jets at s√= 8 TeV using the ATLAS detector

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    The W boson angular distribution in events with high transverse momentum jets is measured using data collected by the ATLAS experiment from proton–proton collisions at a centre-of-mass energy at the Large Hadron Collider, corresponding to an integrated luminosity of . The focus is on the contributions to processes from real W emission, which is achieved by studying events where a muon is observed close to a high transverse momentum jet. At small angular separations, these contributions are expected to be large. Various theoretical models of this process are compared to the data in terms of the absolute cross-section and the angular distributions of the muon from the leptonic W decay.Fil: Aaboud, M.. UniversitĂ© Mohamed Premier and LPTPM; MarruecosFil: Aad, G.. Aix-Marseille UniversitĂ© ; FranciaFil: Abbott, B.. Oklahoma State University; Estados UnidosFil: Abdallah, J.. Academia Sinica; ChinaFil: Abdinov, O.. Azerbaijan Academy of Sciences; AzerbaiyĂĄnFil: Alconada Verzini, MarĂ­a Josefina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Alonso, Francisco. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Arduh, Francisco Anuar. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Dova, Maria Teresa. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Hoya, JoaquĂ­n. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Monticelli, Fernando Gabriel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Wahlberg, Hernan Pablo. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de FĂ­sica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂ­sica La Plata; ArgentinaFil: Bossio Sola, Jonathan David. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Marceca, Gino. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Otero y Garzon, Gustavo Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Piegaia, Ricardo Nestor. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Sacerdoti, Sabrina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Instituto de FĂ­sica de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de FĂ­sica de Buenos Aires; ArgentinaFil: Zibell. A.. Julius-Maximilians-UniversitĂ€t ; AlemaniaFil: Zieminska, D.. Indiana University; Estados UnidosFil: Zimine, N. I.. Joint Institute for Nuclear Research; RusiaFil: Zimmermann, C.. UniversitĂ€t Mainz ; AlemaniaFil: Zimmermann, S.. Albert-Ludwigs-UniversitĂ€t ; AlemaniaFil: Zinonos, Z.. Georg-August-UniversitĂ€t ; AlemaniaFil: Zinser, M.. UniversitĂ€t Mainz ; AlemaniaFil: Ziolkowski, M.. UniversitĂ€t Siegen ; AlemaniaFil: Ćœivković, L.. University of Belgrade ; SerbiaFil: Zobernig, G.. University of Wisconsin; Estados UnidosFil: Zoccoli, A.. UniversitĂ  di Bologna ; ItaliaFil: Nedden, M. zur. Humboldt University; AlemaniaFil: Zurzolo, G.. UniversitĂ  di Napoli; ItaliaFil: Zwalinski, L.. Cern - European Organization For Nuclear Research; SuizaFil: The ATLAS Collaboration. No especifica
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