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      Association of compassion and empathy with prosocial health behaviors and attitudes in a pandemic

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          Abstract

          This investigation examined how dispositional compassion and empathy were associated with prosocial behaviors and attitudes in the SARS-CoV-2 pandemic. Every two weeks from March 22 to June 15, 2020, we fielded a survey to a new cohort of adults in the U.S. Compassion related to whether one stayed home to protect others, more hours spent staying home and distancing from others, and more frequent mask wearing in public, in the past two weeks. Compassion also related to greater perceived ability to help others who were negatively affected. Empathy related to more endorsement of understanding others’ fear of COVID-19, and less endorsement of the view that others were overreacting to COVID-19. There was an interaction between empathy and political ideology, suggesting that empathy may matter for understanding others’ fear among those with more conservative-leaning beliefs. Empathy also related to greater understanding that sheltering-in-place helps prevent the spread of COVID-19. Findings suggest that messaging and interventions to increase compassion and empathy may promote public health behaviors during a pandemic regardless of political orientation. Targeting empathy may be one way to reach individuals with more conservative political beliefs, and it is important to use an evidence-based approach accounting for political party differences in motivated reasoning.

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          Using social and behavioural science to support COVID-19 pandemic response

          The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.
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            The Health Belief Model: a decade later.

            Since the last comprehensive review in 1974, the Health Belief Model (HBM) has continued to be the focus of considerable theoretical and research attention. This article presents a critical review of 29 HBM-related investigations published during the period of 1974-1984, tabulates the findings from 17 studies conducted prior to 1974, and provides a summary of the total 46 HBM studies (18 prospective, 28 retrospective). Twenty-four studies examined preventive-health behaviors (PHB), 19 explored sick-role behaviors (SRB), and three addressed clinic utilization. A "significance ratio" was constructed which divides the number of positive, statistically-significant findings for an HBM dimension by the total number of studies reporting significance levels for that dimension. Summary results provide substantial empirical support for the HBM, with findings from prospective studies at least as favorable as those obtained from retrospective research. "Perceived barriers" proved to be the most powerful of the HBM dimensions across the various study designs and behaviors. While both were important overall, "perceived susceptibility" was a stronger contributor to understanding PHB than SRB, while the reverse was true for "perceived benefits." "Perceived severity" produced the lowest overall significance ratios; however, while only weakly associated with PHB, this dimension was strongly related to SRB. On the basis of the evidence compiled, it is recommended that consideration of HBM dimensions be a part of health education programming. Suggestions are offered for further research.
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              Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 July 2022
                2022
                22 July 2022
                : 17
                : 7
                : e0271829
                Affiliations
                [1 ] Herbert Wertheim School of Public Health and Longevity Science, UC San Diego, La Jolla, CA, United States of America
                [2 ] Center for Empathy and Technology, T. Denny Sanford Institute for Empathy and Compassion, University of California, San Diego, La Jolla, CA, United States of America
                Universitat de Valencia, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-1315-8387
                Article
                PONE-D-22-03478
                10.1371/journal.pone.0271829
                9307157
                35867687
                03d2559d-a256-466f-af71-9ee3b23b402c
                © 2022 Karnaze et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 February 2022
                : 7 July 2022
                Page count
                Figures: 2, Tables: 2, Pages: 16
                Funding
                Funded by: Center for Empathy and Technology, Institute for Empathy and Compassion, UC San Diego
                Award Recipient :
                This work was supported, and data collection was funded by the Center for Empathy and Technology within the T. Denny Sanford Institute for Empathy and Compassion at the University of California San Diego ( https://empathyandcompassion.ucsd.edu/centers/center-for-empathy-and-technology/index.html). This work was also supported by NIH/NCATS Colorado CTSA Grant Number UL1 TR002535. The use of REDCap for this work was supported by NIH/NCATS Colorado CTSA Grant Number UL1 TR002535. Its contents are the authors’ sole responsibility and do not necessarily represent official NIH views. There was no additional external funding received for this study.
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