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      Personal Narrative under Nationalism: Chinese COVID-19 Vaccination Expressions on Douyin

      , , , ,
      International Journal of Environmental Research and Public Health
      MDPI AG

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          Abstract

          Scholars are divided over whether narrative/storytelling occupies a central position in health-related behaviour or in the health-related issues discussed on social media platforms. This study explored Chinese COVID-19 vaccination expressions on Douyin, China’s biggest short-video sharing social media platform, and found that narration is still the most important tool employed by Chinese users when talking about COVID-19 vaccinations on Douyin, emphasizing nationalism and widespread optimism. Most of the narratives employed by Chinese users come from a first-person perspective. Nationalism, as manifested in the support expressed for national policies, rather than the external platform characteristics of memetics, makes the Chinese users’ expressions about COVID-19 vaccinations similar on Douyin. Douyin seems to have become a ‘pilgrimage platform’ for the Chinese public to express their patriotic sentiment and their trust in the country and the government.

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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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            Understanding interobserver agreement: the kappa statistic.

            Items such as physical exam findings, radiographic interpretations, or other diagnostic tests often rely on some degree of subjective interpretation by observers. Studies that measure the agreement between two or more observers should include a statistic that takes into account the fact that observers will sometimes agree or disagree simply by chance. The kappa statistic (or kappa coefficient) is the most commonly used statistic for this purpose. A kappa of 1 indicates perfect agreement, whereas a kappa of 0 indicates agreement equivalent to chance. A limitation of kappa is that it is affected by the prevalence of the finding under observation. Methods to overcome this limitation have been described.
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              The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users

              COVID-19 (Corona Virus Disease 2019) has significantly resulted in a large number of psychological consequences. The aim of this study is to explore the impacts of COVID-19 on people’s mental health, to assist policy makers to develop actionable policies, and help clinical practitioners (e.g., social workers, psychiatrists, and psychologists) provide timely services to affected populations. We sample and analyze the Weibo posts from 17,865 active Weibo users using the approach of Online Ecological Recognition (OER) based on several machine-learning predictive models. We calculated word frequency, scores of emotional indicators (e.g., anxiety, depression, indignation, and Oxford happiness) and cognitive indicators (e.g., social risk judgment and life satisfaction) from the collected data. The sentiment analysis and the paired sample t-test were performed to examine the differences in the same group before and after the declaration of COVID-19 on 20 January, 2020. The results showed that negative emotions (e.g., anxiety, depression and indignation) and sensitivity to social risks increased, while the scores of positive emotions (e.g., Oxford happiness) and life satisfaction decreased. People were concerned more about their health and family, while less about leisure and friends. The results contribute to the knowledge gaps of short-term individual changes in psychological conditions after the outbreak. It may provide references for policy makers to plan and fight against COVID-19 effectively by improving stability of popular feelings and urgently prepare clinical practitioners to deliver corresponding therapy foundations for the risk groups and affected people.
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                Author and article information

                Contributors
                Journal
                IJERGQ
                International Journal of Environmental Research and Public Health
                IJERPH
                MDPI AG
                1660-4601
                October 2022
                October 01 2022
                : 19
                : 19
                : 12553
                Article
                10.3390/ijerph191912553
                cf072861-ab76-4269-8414-652c50188d7c
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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