25 research outputs found

    Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

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    At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

    National identity predicts public health support during a global pandemic (vol 13, 517, 2022) : National identity predicts public health support during a global pandemic (Nature Communications, (2022), 13, 1, (517), 10.1038/s41467-021-27668-9)

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    Publisher Copyright: © The Author(s) 2022.In this article the author name ‘Agustin Ibanez’ was incorrectly written as ‘Augustin Ibanez’. The original article has been corrected.Peer reviewe

    Author Correction: National identity predicts public health support during a global pandemic

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    Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27668-9, published online 26 January 2022

    Hammett Correlation in the Accelerated Formation of 2,3-Diphenylquinoxalines in Nebulizer Microdroplets

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    The accelerated formation of 2,3-diphenylquinoxalines in microdroplets generated in a nebulizer has been investigated by competition experiments in which equimolar quantities of 1,2-phenylenediamine, C6H4(NH2)2, and a 4-substituted homologue, XC6H3(NH2)2 [X = F, Cl, Br, CH3, CH3O, CO2CH3, CF3, CN or NO2], or a 4,5-disubstituted homologue, X2C6H2(NH2)2 [X = F, Cl, Br, or CH3], compete to condense with benzil, (C6H5CO)2. Electron-donating substituents (X = CH3 and CH3O) accelerate the reaction; in contrast, electron-attracting substituents (X = F, Cl, Br and particularly CO2CH3, CN, CF3 and NO2) retard it. A structure–reactivity relationship in the form of a Hammett correlation has been found by analyzing the ratio of 2,3-diphenylquinoxaline and the corresponding substituted-2,3-diphenylquinoxaline, giving a ρ value of −0.96, thus confirming that the electron density in the aromatic ring of the phenylenediamine component is reduced in the rate-limiting step in this accelerated condensation. This correlation shows that the phenylenediamine acts as a nucleophile in the reaction
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