Release and Demand of Public Health Information in Social Media During the Outbreak of COVID-19 in China

Retrospecting Digital Media Use, Negative Emotions, and Trust Gaps During the COVID-19 Pandemic in China: Cross-Sectional Web-Based Survey

BACKGROUND

Retrospecting the trust gaps and their dynamics during the pandemic is crucial for understanding the root causes of postpandemic challenges and offers valuable insights into preparing for future public health emergencies. The COVID-19 pandemic eroded people's trust in strangers and acquaintances, while their trust in family members remained relatively stable. This resulted in 2 trust gaps, namely, the family members-strangers trust gap and the family members-acquaintances trust gap. Widening trust gaps impede social integration and undermine the effective management of public health crises. However, little is known about how digital media use shaped trust gaps during a pandemic.

OBJECTIVE

This study aims to investigate the relationships between digital media use, negative emotions, the family members-strangers trust gap, and the family members-acquaintances trust gap during the COVID-19 pandemic in China. We test the mediating role of negative emotions between digital media use and 2 trust gaps and compare the indirect effect of digital media use on 2 trust gaps through negative emotions.

METHODS

A cross-sectional web-based survey was conducted in China between January 31, 2020, and February 9, 2020. A total of 1568 adults participated in the survey. Questions related to digital media use, negative emotions, trust in family members, trust in acquaintances, and trust in strangers during the pandemic were asked. Regression analyses were performed to test the associations between the examined variables. We used a 95% bootstrap CI approach to estimate the mediation effects.

RESULTS

Digital media use was positively associated with negative emotions (B=0.17, SE 0.03; P<.001), which in turn were positively associated with the family members-strangers trust gap (B=0.15, SE 0.03; P<.001). Likewise, digital media use was positively associated with negative emotions (B=0.17, SE 0.03; P<.001), while negative emotions were positively associated with the family members-acquaintances trust gap (B=0.08, SE 0.03; P=.01). Moreover, the indirect effect of digital media use on the family members-strangers trust gap (B=0.03, SE 0.01; 95% CI 0.01-0.04) was stronger than that on the family members-acquaintances trust gap (B=0.01, SE 0.01; 95% CI 0.003-0.027).

CONCLUSIONS

The results demonstrate that negative emotions resulting from the frequent use of digital media are a key factor that accounts for the widening trust gaps. Considering the increasing reliance on digital media, the findings indicate that the appropriate use of digital media can prevent the overamplification of negative emotions and curb the enlargement of trust gaps. This may help restore social trust and prepare for future public health crises in the postpandemic era.

Analyzing public demands on China's online government inquiry platform: A BERTopic-Based topic modeling study

This study aims to enhance governmental decision-making by leveraging advanced topic modeling algorithms to analyze public letters on the "People Call Me" online government inquiry platform in Zhejiang Province, China. Employing advanced web scraping techniques, we collected publicly available letter data from Hangzhou City between June 2022 and May 2023. Initial descriptive statistical analyses and text mining were conducted, followed by topic modeling using the BERTopic algorithm. Our findings indicate that public demands are chiefly focused on livelihood security and rights protection, and these demands exhibit a diversity of characteristics. Furthermore, the public's response to significant emergency events demonstrates both sensitivity and deep concern, underlining its pivotal role in government emergency management. This research not only provides a comprehensive landscape of public demands but also validates the efficacy of the BERTopic algorithm for extracting such demands, thereby offering valuable insights to bolster the government's agility and resilience in emergency responses, enhance public services, and modernize social governance.

Public health agencies' use of social media for communication during pandemics: a scoping review of the literature

Public health agencies (PHAs) have increasingly incorporated social media into their communication mix during successive pandemics in the 21st century. However, the quality, timing, and accuracy of their health messages have varied significantly, resulting in mixed outcomes for communication, audience engagement, and pandemic management. This study aimed to identify factors influencing the effectiveness of pandemic-related health messages shared by PHAs on social media and to report their impact on public engagement as documented in the literature. A scoping literature review was conducted following a predefined protocol. An electronic search of 7 relevant databases and 5 grey literature repositories yielded 9,714 papers published between January 2003 and November 2022. Seventy-three papers were deemed eligible and selected for review. The results underscored the insufficiency of social media guidance policies for PHAs. Six themes were identified: message source, message topic, message style, message timing, content credibility and reliability, and message recipient profile. These themes encompassed 20 variables that could inform PHAs' social media public health communication during pandemics. Additionally, the findings revealed potential interconnectedness among the variables, and this study concluded by proposing a conceptual model that expands upon existing theoretical foundations for developing and evaluating pandemic-related health messaging.

Risk perception of COVID-19 among college students in China: Latent profile analysis

Background

The outbreak of the new coronavirus-2019 (COVID-19) has had a significant impact on people's mental and physical health. Meanwhile, people's perceptions of risk may influence their emotional states and preventative behavior during an epidemic. Previous research have revealed the diversity and uniqueness of risk perception, and college students may have a different perspective on risk perception. The objective of this study was to describe the subtypes of risk perception for COVID-19 among college students in China, identify the subtypes' traits, and investigate their affecting variables.

Methods

College students from 10 Chinese provinces participated in a cross-sectional study (n = 2,000) that from January 16 to 30, 2022. The latent profiles and influencing factors for risk perception were investigated using latent profile analysis, one-way analysis of variance, and multinomial logistical regression.

Results

The sample group of this survey was 1,946 students, and the response rate was 97.3%. The best model was suggested to consist of three profiles: "neutral risk perception" (20.3%), "perception seriously without susceptible" (52.8%), and "low risk perception" (26.9%). Risk perception of COVID-19 was positively associated with attention to negation information (r = 0.372, p < 0.01), anxiety (r = 0.232, p < 0.01), and depression (r = 0.241, p < 0.01), and negatively associated with perceived social support (r = -0.151, p < 0.01). Logistic-regressions analyses mainly revealed that the risk perception of three profiles related to having chronic diseases (OR = 2.704, p < 0.01), medical major (OR = 0.595, p < 0.01; OR = 0.614, p < 0.05), without having COVID-19 confirmed cases around (OR = 0.539, p < 0.01), attention to negative information (OR = 1.073, p < 0.001; OR = 1.092, p < 0.001), and perceived social support (OR = 0.0.975, p < 0.01).

Conclusions

The level of risk perception for COVID-19 among Chinese college students was unsatisfactory, and the risk perception of COVID-19 had significant group characteristics and heterogeneity. Colleges and public health practitioners could have a theoretical and empirical basis to implement risk perception intervention efforts by identifying latent subgroups during the COVID-19 epidemic.