Internet Rumors During the COVID-19 Pandemic: Dynamics of Topics and Public Psychologies

Internet access during COVID-19 and depressive symptoms in middle-aged and older adults: Evidence from a quasi-experimental study in China

BACKGROUND

Amid the COVID-19 pandemic, the mental health of middle-aged and older adults has become an increasing concern, and the role of the internet in addressing this public health crisis has drawn the attention of researchers. This study evaluated the impact of internet access during COVID-19 on depressive symptoms among middle-aged and older adults.

METHODS

Data were derived from China Health and Retirement Longitudinal Study (CHARLS) 2018 and 2020. Difference-in-differences analysis was performed to compare changes in depressive symptoms between the internet users during COVID-19 and those who didn't have access to the internet before and during the pandemic.

RESULTS

We found that internet access during COVID-19 pandemic significantly reduced middle-aged and older adults' depressive symptoms. Further investigation identified the underlying mechanisms through which internet access helps in alleviating depressive symptoms by reducing the likelihood of experiencing negative emotions about COVID-19. Heterogeneity analyses showed that rural residents and middle-aged individuals benefited more from internet access during the pandemic.

CONCLUSIONS

Since internet access can alleviate middle-aged and older adults' depressive symptoms amidst public health crisis, policy makers should focus on enhancing their access to the internet.

Decline in and recovery of fertility rates after COVID-19-related state of emergency in Japan

INTRODUCTION

The COVID-19 pandemic led to a decline in fertility rates worldwide. Although many regions have experienced a temporary drop in fertility rates with the spread of the infection, subsequent recovery has varied across countries. This study aimed to evaluate the impact of COVID-19 infection rates and regional sociodemographic factors on the recovery of fertility rates in Japan following the state of emergency.

METHODS

This study examined prefectural fertility data from before the COVID-19 pandemic to forecast fertility rates up to 2022 using a seasonal autoregressive integrated moving average model. A regression analysis was conducted on fertility rates during the first state of emergency and the subsequent recovery rate with respect to the number of new COVID-19 cases and sociodemographic factors specific to each prefecture.

RESULTS

During the first state of emergency, the monthly fertility rate decreased by an average of -13.8% (SD: 6.26, min: -28.78, max: 0.15) compared with the previous year. Over the following 22 months, the average fertility recovery rate was +2.31% (SD: 3.57; min: -8.55, max: 19.54). Multivariate analysis of the impact of the pandemic on fertility changes during the first emergency indicated a negative correlation between new COVID-19 cases per capita and the proportion of nuclear households. No significant correlation was found between fertility recovery rate and new COVID-19 cases or emergency duration. When classifying fertility rate fluctuation patterns before and after the emergency into four clusters, variations were noted in the proportion of the elderly population, marriage divorce rate and the number of internet searches related to pregnancy intentions across the clusters.

CONCLUSIONS

No association was found between pregnancy intentions related to the spread of infection, such as the number of new cases and the fertility recovery rate following the first state of emergency. Differences in the patterns of decline and recovery during the pandemic were observed based on population composition and internet searches for infection and pregnancy across different prefectures.

Knowledge, attitude, and practice of Iranian health care workers about infodemic management: a cross-sectional descriptive study

BACKGROUND

Misinformation (infodemics) can hinder effective healthcare delivery. This study assessed Iranian healthcare workers' (HCWs) knowledge, attitude, and practice (KAP) regarding infodemic management (IM).

METHOD

A cross-sectional survey using a self-reported questionnaire (KAPIM) distributed via convenience sampling to 1890 HCWs across all Iranian Medical Sciences Universities.

RESULTS

The results showed that healthcare workers demonstrated overall KAP scores with a mean of 3.38 out of 5. Knowledge scores were 63.01%, attitude scores were 74.23%, and practice scores were lower at 55.76%. There were positive correlations between age and work experience with both knowledge and attitude scores.

CONCLUSION

These findings suggest a gap between HCWs' knowledge/attitude and practice regarding IM. Targeted interventions emphasizing practical skills are needed. Considering demographics and regional variations is crucial when developing training programs for enhanced infodemic preparedness across the Iranian healthcare system.

Online rumors during the COVID-19 pandemic: co-evolution of themes and emotions

Introduction

During public health emergencies, online rumors spread widely on social media, causing public information anxiety and emotional fluctuations. Analyzing the co-evolution patterns of online rumor themes and emotions is essential for implementing proactive and precise governance of online rumors during such events.

Methods

Rumor texts from mainstream fact-checking platforms during the COVID-19 pandemic were collected and analyzed in phases based on the crisis lifecycle theory. The LDA topic model was applied to analyze the distribution of rumor themes at different stages. The Baidu AI Sentiment Analysis API was used to study the emotional tendencies of rumors at different stages. Line graphs were utilized to analyze the co-evolution characteristics of rumor themes and emotions.

Results

During the COVID-19 pandemic, the themes of online rumors can be categorized into five types: epidemic prevention and control, panic-inducing, production and livelihood, virus dissemination, and social figures. These themes exhibited repetition and fluctuation at different stages of the pandemic. The emotions embedded in pandemic-related online rumors evolved with the progression of the pandemic. Panic-inducing rumors co-evolved with negative emotions, while epidemic prevention and control rumors co-evolved with positive emotions.

Conclusion

The study results help to understand the public's focus and emotional tendencies at different stages of the COVID-19 pandemic, thereby enabling targeted public opinion guidance and crisis management.

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.

Characteristics of Collective Resilience and Its Influencing Factors from the Perspective of Psychological Emotion: A Case Study of COVID-19 in China

Collective resilience is the ability of human beings to adapt and collectively cope with crises in adversity. Emotional expression is the core element with which to characterize the psychological dimension of collective resilience. This research proposed a stage model of collective resilience based on the temporal evolution of the public opinions of COVID-19 in China's first anti-pandemic cycle; using data from hot searches and commentaries on Sina Weibo, the changes in the emotional patterns of social groups are revealed through analyses of the sentiments expressed in texts. A grounded theory approach is used to elucidate the factors influencing collective resilience. The research results show that collective resilience during the pandemic exhibited an evolutionary process that could be termed, "preparation-process-recovery". Analyses of expressed sentiments reveal an evolutionary pattern of "positive emotion prevailing-negative emotion appearing-positive emotion recovering Collective resilience from a psycho-emotional perspective is the result of "basic cognition-intermediary condition-consequence" positive feedback, in which the basic cognition is expressed as will embeddedness and the intermediary conditions include the subject behavior and any associated derived behavioral characteristics and spiritual connotation. These results are significant both theoretically and practically with regard to the reconstruction of collective resilience when s' force majeure' event occur.

Research on the Public Opinion Guidance Mechanism of Major Public Health Incidents

Public opinion guidance plays a crucial role in the management of major public health incidents, and thus, exploring its mechanism is conducive to the comprehensive governance of social security. This study conducts a case study on the anti-pandemic public opinion guidance and analyzes the public opinion representation and the internal mechanism of public opinion guidance in the context of the COVID-19 in China. The findings suggest that the public opinion on the COVID-19 manifested a three-stage progressive and stable tendency and witnessed the strength of China, specifically, benefiting from the systematic and complete integration and release mechanism for anti-pandemic information, the three-dimensional mechanism for the dissemination of knowledge related to pandemic prevention and health, the innovative disclosure mechanism for precise information, and diversified channels for international public opinion guidance. The guidance mechanism proposed in this study provides significant suggestions for the public opinion guidance of global major public health incidents in future.