Negative Emotion Arousal and Altruism Promoting of Online Public Stigmatization on COVID-19 Pandemic.
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ABSTRACT:
SUBMITTER: Chen X
PROVIDER: S-EPMC8187574 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesThe goal of this study is to examine the role of altruism and sensitivity to public shame in individuals' willingness to pay for a COVID-19 vaccine.Study designWe apply expected utility theory to predict the role of individuals' altruism and public shame in the willingness to pay for vaccines. Subsequently, we test the prediction by using a unique cross-sectional survey.MethodsWe use online survey data collected from those aged 30-49 in Japan between June 18th and 25th, 2020 (n = 1686). The selection of respondents follows quota sampling with regard to age group, gender, and prefecture of residence. We employ an ordinary least square (OLS) model to regress respondents' willingness to pay for a hypothetically-effective vaccine for COVID-19 on binary indicators of altruism and sensitivity to public shame, as well as socio-demographic characteristics.ResultsThe willingness to pay for the vaccine is higher among those with stronger altruistic concerns and sensitivity to shaming.ConclusionVoluntary vaccinations may be inefficient, because the uptake of vaccines could be low for selfish individuals who often violate social distancing requirements. To improve the efficiency of vaccine uptake, some interventions, such as nudges and a vaccine passport, may be needed.
| S-EPMC8750826 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) has triggered an enormous number of discussion topics on social media Twitter. It has an impact on the global health system and citizen responses to the pandemic. Multiple responses (replies, favorites, and retweets) reflect the followers' attitudes and emotions towards these tweets. Twitter data such as these have inspired substantial research interest in sentiment and social trend analyses. To date, studies on Twitter data have focused on the associational relationships between variables in a population. There is a need for further discovery of causality, such as the influence of sentiment polarity of tweet response on further discussion topics. These topics often reflect the human perception of COVID-19. This study addresses this exact topic. It aims to develop a new method to unveil the causal relationships between the sentiment polarity and responses in social media data. We employed sentiment polarity, i.e., positive or negative sentiment, as the treatment variable in this quasi-experimental study. The data is the tweets posted by nine authoritative public organizations in four countries and the World Health Organization from December 1, 2019, to May 10, 2020. Employing the inverse probability weighting model, we identified the treatment effect of sentiment polarity on the multiple responses of tweets. The topics with negative sentiment polarity on COVID-19 attracted significantly more replies (69±49) and favorites (688±677) than the positive tweets. However, no significant difference in the number of retweets was found between the negative and positive tweets. This study contributes a new method for social media analysis. It generates new insight into the influence of sentiment polarity of tweets about COVID-19 on tweet responses.
| S-EPMC8903302 | biostudies-literature
Project description:Emotion recognition is a crucial task in Natural Language Processing (NLP) that enables machines to comprehend the feelings conveyed in the text. The task involves detecting and recognizing various human emotions like anger, fear, joy, and sadness. The applications of emotion recognition are diverse, including mental health diagnosis, student support, and the detection of online suspicious behavior. Despite the substantial amount of literature available on emotion recognition in various languages, Arabic emotion recognition has received relatively little attention, leading to a scarcity of emotion-annotated corpora. This article presents the ArPanEmo dataset, a novel dataset for fine-grained emotion recognition of online posts in Arabic. The dataset comprises 11,128 online posts manually labeled for ten emotion categories or neutral, with Fleiss' kappa of 0.71. It is unique in that it focuses on the Saudi dialect and addresses topics related to the COVID-19 pandemic, making it the first and largest of its kind. Python's packages were utilized to collect online posts related to the COVID-19 pandemic from three sources: Twitter, YouTube, and online newspaper comments between March 2020 and March 2022. Upon collection of the online posts, each one underwent a semi-automatic classification process using a lexicon of emotion-related terms to determine whether it belonged to the neutral or emotion category. Subsequently, manual labeling was conducted to further categorize the emotional data into fine-grained emotion categories. We anticipate that the ArPanEmo dataset will enrich Arabic NLP resources and help in the development of machine learning and deep learning tools to identify emotions in a given text. It will also contribute to developing systems that monitor online suspicious behaviors or mental health disorders. The final dataset is formatted in CSV, consisting of three columns: the number of the post, the post's text, and the corresponding emotion label. This format facilitates incorporating and utilizing the dataset in any machine learning research.
| S-EPMC10654532 | biostudies-literature
Project description: Not available
| S-EPMC8438352 | biostudies-literature
Project description:This study evaluated how news with positive and negative content about COVID-19, as well as a relaxation pause, affect the emotional state. We also investigated the association between emotional state and practicing meditation/yoga, physical activity or having a mental disease. For that, a sample of 717 participants, recruited through social media, were randomly assigned to listen to negative or positive news about COVID-19. After that, both groups were guided through a short relaxation pause. Their emotional state was measured before they listened to the audios and after each audio. Mixed linear models were used to evaluate the effects of news group, relaxation pause, mental health and well-being practices. Negative news worsened their emotional state, whereas positive news improved it. A brief relaxation pause improved the effects of negative news content and may mitigate the effects of this valence of information. Practicing physical activity, meditation/yoga was associated with better emotional responses.
| S-EPMC8529560 | biostudies-literature
Project description:BackgroundThe outbreak and global spread of COVID-19 was accompanied by an increase in reports of stigmatization of Chinese and Asian-looking people. The behavioral immune system provides a framework for stigmatization in response to infectious disease threats. Specifically, stigmatization might increase with rising levels of infectious disease threat. The present study aimed to examine this hypothesis during the early phase of the COVID-19 pandemic.MethodsAs part of the "EUCLID" project ( https://euclid.dbvis.de ), a total of 5011 persons from Germany were surveyed via an online-questionnaire between February 2nd and April 3rd, 2020, covering the progression of the COVID-19 pandemic over three time periods which were defined by critical events.ResultsThere was no evidence for an increase in the stigmatization of Chinese and Asian-looking people across three topics, that is personal proximity, air travel, and medical measures upon arrival from China.ConclusionsThe present findings provide good news in that participants showed an adaptive response to the infectious disease threat rather than displaying increased stigmatization. Further research is necessary to specify the conditions that increase the risk of stigmatization in response to infectious disease threats.
| S-EPMC8253234 | biostudies-literature
Project description:Background We conducted this randomized controlled trial (RCT) to evaluate the effectiveness and safety of moxibustion at Sanyinjiao (SP6) acupoint for treatment of negative mood and sleep quality in healthcare workers during the 2019 coronavirus disease (COVID-19). Methods A total of 180 participants were divided in a 1:1 ratio into two groups, the treatment group (for moxibustion) and the control group (for no treatment). The treatment group had a 30-minute moxibustion therapy once a day for two weeks, followed by a two-week follow-up. The Hamilton Anxiety Scale (HAMA) was used to assess the degree of the participants' anxiety, and the Patient Health Questionnaire-9 (PHQ-9) was utilized to examine their depressed condition. The Maslach Burnout Inventory-General Survey (MBI-GS) was used to measure the level of burnout among healthcare workers. To determine the severity of insomnia, the Sleep Dysfunction Rating Scale (SDRS) was utilized. At baseline, week 2, and week 4, all scales were evaluated. Results Compared to the control group, The treatment group improved more significantly in the HAMA at week 2 (MD = -19.01, 95% CI: -21.89 to -16.14; P<0.001) and at week 4 follow-up visits (MD = -8.96, 95% CI: -11.19 to -6.73; P<0.001). A subgroup study of HAMA scores revealed that position and education had significant impact on treatment effectiveness. During the 2-week intervention period, the treatment group showed more significant improvements in depressive symptoms measured by PHQ-9 (13.00±2.41 vs. 15.60±3.65; P<0.001), work burnout symptoms measured by MBI-GS (MD = -11.88, 95% CI, -15.73 to -8.03; P<0.001), and insomnia symptoms measured by SDRS (MD = -2.45, 95% CI, -4.24 to -0.66; P<0.01). There were no significant adverse effects reported. Conclusion Moxibustion at SP6 may be an effective treatment to improve anxiety, depression, sleep quality, and quality of life for healthcare workers during COVID-19. Trial registration Chinese Clinical Trial Registry (ChiCTR): ChiCTR-2200059327.
| S-EPMC10448013 | biostudies-literature
Project description:The Last Aid course aims to teach public palliative care by increasing public awareness and empowering people about the role of the individual in the death of loved ones. The Covid-19 pandemic, however, has altered educational methods prohibiting classroom settings. Therefore, an online course was created to enable continued and safe public palliative care education. A mixed-methods study was performed to examine the feasibility of delivering the Last Aid course online. Data collection included participant questionnaires with qualitative and quantitative data, observations and a focus group discussion. Data were analyzed using descriptive analysis and qualitative description. In total, 15 online Last Aid courses were held, 174 participants took part in the study and 92 completed questionnaires were included. Findings revealed overall course satisfaction for the online courses in line with previous findings for classroom teaching. The online platform enabled course participation from people previously unable or unwilling to attend, namely caregivers to dying relatives and younger people. Instructors displayed an ability to teach online. However, some instructors expressed frustration over reduced interaction and technical challenges, which was echoed by participant ratings showing that many lacked social networking with fellow participants. Nonetheless, this pilot study demonstrates the feasibility of the online Last Aid course. Attention must be given to increasing both participant-to-participant and instructor-to-participant interaction. More research on the long-term effects of Last Aid courses is needed.
| S-EPMC7914870 | biostudies-literature
Project description:BackgroundThroughout history, people have soothed their fear of disease outbreaks by searching for someone to blame. Such was the case with the April 2009 H1N1 flu outbreak. Mexicans and other Latinos living in the US were quickly stigmatized by non-Latinos as carriers of the virus, partly because of news reports on the outbreak's alleged origin in Mexican pig farms.MethodsIn this exploratory study we examined the psychological processes of cue convergence and associative priming, through which many people likely conflated news of the H1N1 outbreak with pre-existing cognitive scripts that blamed Latino immigrants for a variety of social problems. We also used a transactional model of stress and coping to analyze the transcripts from five focus groups, in order to examine the ways in which a diverse collection of New England residents appraised the threat of H1N1, processed information about stereotypes and stigmas, and devised personal strategies to cope with these stressors.ResultsTwelve themes emerged in the final wave of coding, with most of them appearing at distinctive points in the stress and coping trajectories of focus group participants. Primary and secondary appraisals were mostly stressful or negative, with participants born in the USA reporting more stressful responses than those who were not. Latino participants reported no stressful primary appraisals, but spoke much more often than Whites or Non-Hispanic Blacks about negative secondary appraisals. When interactions between participants dealt with stigmas regarding Latinos and H1N1, Latinos in our focus groups reported using far more negative coping strategies than Whites or Non-Hispanic Blacks. When discussions did not focus on stereotypes or stigmas, Latino participants spoke much more often about positive coping strategies compared to members of these same groups.ConclusionsParticipants in all five focus groups went through a similar process of stress and coping in response to the threat of H1N1, though individual responses varied by race and ethnicity. Stigmatization has often been common during pandemics, and public health and emergency preparedness practitioners can help to mitigate its impacts by developing interventions to address the social stressors that occur during outbreaks in highly-localized geographic regions.
| S-EPMC3907032 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies.ObjectiveThis study aims to use online search data (Baidu Index) to monitor the public's attention and verify internet search engines' function in public attention monitoring of public health emergencies.MethodsWe collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention's temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis.ResultsThe Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases.ConclusionsThe national public's demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public's attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.
| S-EPMC7584450 | biostudies-literature