The differential effects of a governmental debunking campaign concerning COVID-19 vaccination misinformation

Beyond misinformation: developing a public health prevention framework for managing information ecosystems

The COVID-19 pandemic has highlighted how infodemics (defined as an overabundance of information, including misinformation and disinformation) pose a threat to public health and could hinder individuals from making informed health decisions. Although public health authorities and other stakeholders have implemented measures for managing infodemics, existing frameworks for infodemic management have been primarily focused on responding to acute health emergencies rather than integrated in routine service delivery. We review the evidence and propose a framework for infodemic management that encompasses upstream strategies and provides guidance on identifying different interventions, informed by the four levels of prevention in public health: primary, secondary, tertiary, and primordial prevention. On the basis of a narrative review of 54 documents (peer-reviewed and grey literature published from 1961 to 2023), we present examples of interventions that belong to each level of prevention. Adopting this framework requires proactive prevention and response through managing information ecosystems, beyond reacting to misinformation or disinformation.

Trust in public health institutions moderates the effectiveness of COVID-19 vaccine discussion groups on Facebook

BACKGROUND

Distrust and partisan identity are theorized to undermine health communications. We examined the role of these factors on the efficacy of discussion groups intended to promote vaccine uptake.

METHOD

We analyzed survey data from unvaccinated Facebook users (N = 371) living in the US between January and April 2022. Participants were randomly assigned to Facebook discussion groups (intervention) or referred to Facebook's COVID-19 Information Center (control). We used Analysis of Covariance to test if the intervention was more effective at changing vaccination intentions and beliefs compared to the control in subgroups based on participants' partisan identity, political views, and information trust views.

RESULTS

We found a significant interaction between the intervention and trust in public health institutions (PHIs) for improving intentions to vaccinate (P = .04), intentions to encourage others to vaccinate (P = .03), and vaccine confidence beliefs (P = .01). Among participants who trusted PHIs, those in the intervention had higher posttest intentions to vaccinate (P = .008) and intentions to encourage others to vaccinate (P = .002) compared to the control. Among non-conservatives, participants in the intervention had higher posttest intentions to vaccinate (P = .048). The intervention was more effective at improving intentions to encourage others to vaccinate within the subgroups of Republicans (P = .03), conservatives (P = .02), and participants who distrusted government (P = .02).

CONCLUSIONS

Facebook discussion groups were more effective for people who trusted PHIs and non-conservatives. Health communicators may need to segment health messaging and develop strategies around trust views.

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis

BACKGROUND

This research extends prior studies by the Finnish Institute for Health and Welfare on pandemic-related risk perception, concentrating on the role of trust in health authorities and its impact on public health outcomes.

OBJECTIVE

The paper aims to investigate variations in trust levels over time and across social media platforms, as well as to further explore 12 subcategories of political mistrust. It seeks to understand the dynamics of political trust, including mistrust accumulation, fluctuations over time, and changes in topic relevance. Additionally, the study aims to compare qualitative research findings with those obtained through computational methods.

METHODS

Data were gathered from a large-scale data set consisting of 13,629 Twitter and Facebook posts from 2020 to 2023 related to COVID-19. For analysis, a fine-tuned FinBERT model with an 80% accuracy rate was used for predicting political mistrust. The BERTopic model was also used for superior topic modeling performance.

RESULTS

Our preliminary analysis identifies 43 mistrust-related topics categorized into 9 major themes. The most salient topics include COVID-19 mortality, coping strategies, polymerase chain reaction testing, and vaccine efficacy. Discourse related to mistrust in authority is associated with perceptions of disease severity, willingness to adopt health measures, and information-seeking behavior. Our findings highlight that the distinct user engagement mechanisms and platform features of Facebook and Twitter contributed to varying patterns of mistrust and susceptibility to misinformation during the pandemic.

CONCLUSIONS

The study highlights the effectiveness of computational methods like natural language processing in managing large-scale engagement and misinformation. It underscores the critical role of trust in health authorities for effective risk communication and public compliance. The findings also emphasize the necessity for transparent communication from authorities, concluding that a holistic approach to public health communication is integral for managing health crises effectively.

A Cross-Sectional Factor Analysis of COVID-19 and Influenza Vaccination Decisions in a Racially Diverse Western Pennsylvania Community

INTRODUCTION

Influenza and COVID-19 vaccination rates remain suboptimal, demanding new community-centric approaches that improve targeted counseling and increase vaccine uptake. Notably, racially diverse communities show high vaccine hesitancy, yet most existing vaccine studies focus on white, college-educated cohorts.

OBJECTIVE

Here, we identify factors influencing vaccination decisions of patients at Turtle Creek Primary Care clinic in Turtle Creek, PA, a racially-diverse borough.

DESIGN

A retrospective mixed-methods study of the predominantly non-white patient population at Turtle Creek Primary Care clinic, a clinic caring for >70% minority patients.

RESULTS

Fourteen factors emerged that patients reported were crucial to vaccine decision-making. Of these factors, top reasons for COVID-19 vaccine hesitancy were trust in vaccines, vaccine side effects, perceived vaccine knowledge, and faith/religion. Top reasons for influenza vaccine hesitancy were perceived need, vaccine side effects, trust in vaccines, and habitual behaviors. We also uncovered correlations between vaccine decision factors and sociodemographic factors. Participants > 65-years-old were more likely to cite personal safety in choosing to get the COVID-19 vaccine, while non-white participants were more likely to cite others' safety. Participants > 65-years-old were also more likely to cite personal safety in influenza vaccine decision-making, and non-female participants were more likely to cite perceived need for influenza vaccines.

CONCLUSIONS

These data uncover targetable factors contributing to vaccine hesitancy and aid in developing community-centered, personalized vaccine education approaches in Turtle Creek and analogous minority communities.