Systematic evaluation of COVID-19 related Internet health rumors during the breaking out period of COVID-19 in China

From obligation to action: unraveling the roles of social responsibility and prosocial tendency in shaping Chinese doctors' vaccine hesitancy

Background

The hesitation of healthcare professionals towards vaccines is becoming increasingly concerning, potentially undermining public confidence in vaccination programs. This study aimed to investigate the relationship between social responsibility, Prosocial tendency, and vaccine hesitancy among Chinese doctors, and to identify demographic factors associated with vaccine hesitancy.

Method

A cross-sectional survey was conducted among 976 Chinese doctors. Participants completed a questionnaire to assess their sense of social responsibility, Prosocial tendency, and vaccine hesitancy. Demographic information, including age, gender, and marital status, was also collected. Correlation and mediation analyses were conducted to examine the relationships between the main variables.

Results

Social responsibility was negatively correlated with vaccine hesitancy (r=-0.564, P<0.01) and positively correlated with Prosocial tendency (r=0.519, P<0.01). Prosocial tendency was negatively correlated with vaccine hesitancy (r=-0.505, P<0.01) and partially mediated the relationship between social responsibility and vaccine hesitancy. Younger age, female gender, and unmarried status were associated with higher levels of vaccine hesitancy.

Conclusion

This study emphasized the important role of social responsibility and Prosocial tendency in reducing vaccine hesitancy among Chinese doctors. The findings suggest that interventions aimed at fostering a strong sense of social responsibility and promoting Prosocial tendency may effectively address vaccine hesitancy in this population. Additionally, targeted interventions focusing on young, female, and unmarried doctors may be necessary.

How can the collaborative participation of regulators, whistleblowers, and parties effectively promote rumor management in public health emergencies?

To effectively address the mental health risks associated with public health emergencies, it is crucial to actively manage rumors. This study explores the dynamic evolutionary process of rumor diffusion and its collaborative governance in public health emergencies. A game-theoretic model is constructed, involving three main actors: regulators, parties involved in public health emergencies (PIPHE), and whistle-blowers. The behaviors and game outcomes of each party are analyzed, and the effectiveness and feasibility of the model are validated through numerical simulations. The findings of this study reveal that various factors, such as regulatory costs, penalty income, reputation damage for regulators; image loss, reputation enhancement, penalty expenditure for PIPHE; and time costs, social responsibility, and reward income for whistle-blowers, all influence the behavioral choices and game equilibrium of each party. Optimization strategies for rumor governance are proposed in this study, including enhancing the sense of responsibility and capability among regulators, increasing transparency and credibility among PIPHE, and encouraging and protecting the participation of whistle-blowers. This study provides a comprehensive analytical framework for rumor governance in public health emergencies, contributing to improving the governance of public health emergencies and maintaining online public health orders for social sustainability.

Hot Topic Recognition of Health Rumors Based on Anti-Rumor Articles on the WeChat Official Account Platform: Topic Modeling

BACKGROUND

Social networks have become one of the main channels for obtaining health information. However, they have also become a source of health-related misinformation, which seriously threatens the public's physical and mental health. Governance of health-related misinformation can be implemented through topic identification of rumors on social networks. However, little attention has been paid to studying the types and routes of dissemination of health rumors on the internet, especially rumors regarding health-related information in Chinese social media.

OBJECTIVE

This study aims to explore the types of health-related misinformation favored by WeChat public platform users and their prevalence trends and to analyze the modeling results of the text by using the Latent Dirichlet Allocation model.

METHODS

We used a web crawler tool to capture health rumor-dispelling articles on WeChat rumor-dispelling public accounts. We collected information from health-debunking articles posted between January 1, 2016, and August 31, 2022. Following word segmentation of the collected text, a document topic generation model called Latent Dirichlet Allocation was used to identify and generalize the most common topics. The proportion distribution of the themes was calculated, and the negative impact of various health rumors in different periods was analyzed. Additionally, the prevalence of health rumors was analyzed by the number of health rumors generated at each time point.

RESULTS

We collected 9366 rumor-refuting articles from January 1, 2016, to August 31, 2022, from WeChat official accounts. Through topic modeling, we divided the health rumors into 8 topics, that is, rumors on prevention and treatment of infectious diseases (1284/9366, 13.71%), disease therapy and its effects (1037/9366, 11.07%), food safety (1243/9366, 13.27%), cancer and its causes (946/9366, 10.10%), regimen and disease (1540/9366, 16.44%), transmission (914/9366, 9.76%), healthy diet (1068/9366, 11.40%), and nutrition and health (1334/9366, 14.24%). Furthermore, we summarized the 8 topics under 4 themes, that is, public health, disease, diet and health, and spread of rumors.

CONCLUSIONS

Our study shows that topic modeling can provide analysis and insights into health rumor governance. The rumor development trends showed that most rumors were on public health, disease, and diet and health problems. Governments still need to implement relevant and comprehensive rumor management strategies based on the rumors prevalent in their countries and formulate appropriate policies. Apart from regulating the content disseminated on social media platforms, the national quality of health education should also be improved. Governance of social networks should be clearly implemented, as these rapidly developed platforms come with privacy issues. Both disseminators and receivers of information should ensure a realistic attitude and disseminate health information correctly. In addition, we recommend that sentiment analysis-related studies be conducted to verify the impact of health rumor-related topics.

Influence factors analysis of COVID-19 Prevention behavior of chinese Citizens: a path analysis based on the hypothetical model

BACKGROUND

Under the outbreak of Coronavirus disease 2019 (COVID-19), a structural equation model was established to determine the causality of important factors that affect Chinese citizens' COVID-19 prevention behavior.

METHODS

The survey in Qingdao covered several communities in 10 districts and used the method of cluster random sampling. The research instrument used in this study is a self-compiled Chinese version of the questionnaire. Of the 1215 questionnaires, 1188 were included in our analysis. We use the rank sum test, which is a non-parametric test, to test the influence of citizens'basic sociodemographic variables on prevention behavior, and the rank correlation test to analyze the influencing factors of prevention behavior. IBM AMOS 24.0 was used for path analysis, including estimating regression coefficients and evaluating the statistical fits of the structural model, to further explore the causal relationships between variables.

RESULTS

The result showed that the score in the prevention behavior of all citizens is a median of 5 and a quartile spacing of 0.31. The final structural equation model showed that the external support for fighting the epidemic, the demand level of health information, the cognition of (COVID-19) and the negative emotions after the outbreak had direct effects on the COVID-19 prevention behavior, and that negative emotions and information needs served as mediating variables.

CONCLUSIONS

The study provided a basis for relevant departments to further adopt epidemic prevention and control strategies.