ArticleHealth promotion international2021
COVID-19, a tale of two pandemics: novel coronavirus and fake news messaging.
Article in Health promotion international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 107 citations in OpenAlex.
- When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025Pooled it
- Masks and respirators for prevention of respiratory infections: a state of the science review.Clinical microbiology reviews · 2024Pooled it
- Summarising data and factors associated with COVID-19 related conspiracy theories in the first year of the pandemic: a systematic review and narrative synthesis.BMC psychology · 2022Pooled it
- "Life as We Knew It": Continued Challenges in Getting Up-to-Date COVID-19 Vaccinations Amongst Black and Latinx Michigan Residents.Journal of racial and ethnic health disparities · 2025Article
- Social media in school health promotion: the need for institutional and professional development.Health promotion international · 2025Article
- Communication in disasters to support families with children with medical complexity and special healthcare needs: a rapid scoping review.Frontiers in public health · 2024Article
- Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society.PloS one · 2024Article
- Review
- Vaccine hesitancy and acceptance: an examination of predictive factors in COVID-19 vaccination in Saudi Arabia.Health promotion international · 2023Article
- An International Systematic Review Concerning the Effect of Social Media Exposure on Public Compliance with Infection Prevention and Control Measures During the COVID-19 Pandemic.Journal of infection prevention · 2023Review
- Article
- Protecting public's wellbeing against COVID-19 infodemic: The role of trust in information sources and rapid dissemination and transparency of information over time.Frontiers in public health · 2023Article
- Double-Bind of Recruitment of Older Adults Into Studies of Successful Aging via Assistive Information and Communication Technologies: Mapping Review.JMIR aging · 2022Review
- Review
- [Conspiracy theories and COVID-19: How do conspiracy beliefs arise?]L'Encephale · 2022Article
- Covid-19 vaccination BNT162b2 temporarily impairs semen concentration and total motile count among semen donors.Andrology · 2022Article
- Pseudoscience and fraudulent products for COVID-19 management.Environmental science and pollution research international · 2022Review
- Infodemic and fake news - A comprehensive overview of its global magnitude during the COVID-19 pandemic in 2021: A scoping review.International journal of disaster risk reduction : IJDRR · 2022Article
- Online information and support seeking during COVID-19 lockdown in Wuhan: implications for health promotion.Health promotion international · 2022Article
- Pandemic Experience of First Responders: Fear, Frustration, and Stress.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of COVID-19, caused by novel Coronavirus SARS-CoV-2, became a pandemic in just 10 weeks. Without effective medications or vaccines available, authorities turned toward mitigation measures such as use of face masks, school's closings, shelter-in-place, telework and social distancing. People found refuge on the internet and social media apps; however, there was a proliferation of instant messaging containing hoaxed, deliberate misleading information: fake news messaging (FNM). The aim of this study was to assess FNM through content analysis and to discriminate them in a proposed taxonomy structure. A sample of convenience of messages, memes, tweets or cartoons in several languages was selected from the most popular social media outlets, i.e. Facebook, WhatsApp, Twitter etc. More than 300 FNM were identified. Descriptive statistics were used for highlighting potential relationships between variables. Content analysis determined that FNM could be divided into Health- and non-health-related types. There are several sub-types considering, but not limited to, religious beliefs, politics, economy, nutrition, behaviors, prevention of the infection, the origin of the disease and conspiracy theories. The parallel FNM pandemic affected the response from an already debilitated public health system through the confusion created in the community and the erosion in the credibility of genuine media. Public health practitioners had to face people's unpredictable behaviors, panic, tensions with the communities and, in some cases, a hostile climate toward frontline workers. Public health practitioners must adjust ongoing and future health promotion and education interventions including plans to neutralize fake news messages.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.