Evidence map›Paper›PMID 33872185›Full record

ArticleJournal of medical Internet research2021

People's Willingness to Vaccinate Against COVID-19 Despite Their Safety Concerns: Twitter Poll Analysis.

Fabian Eibensteiner, Valentin Ritschl, Faisal A Nawaz, Sajjad S Fazel, Christos Tsagkaris, Stefan Tino Kulnik, Rik Crutzen, Elisabeth Klager, Sabine Völkl-Kernstock, Eva Schaden and 3 more

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
10.6field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 92 citations in OpenAlex.

  1. Pooled it
  2. Observational
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  19. Enhancing public trust in COVID-19 vaccination during ramadan 2022: A call for action.The International journal of health planning and management · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 6 countries.

Fabian Eibensteiner *Division of Pediatric Nephrology and Gastroenterology, Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-5012-3082
Valentin Ritschl *Section for Outcomes Research, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-8763-8215
Faisal A NawazCollege of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.ORCID 0000-0002-0701-7628
Sajjad S FazelDepartment of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.ORCID 0000-0002-6457-4017
Christos TsagkarisFaculty of Medicine, University of Crete, Heraklion, Greece.ORCID 0000-0002-4250-574X
Stefan Tino KulnikLudwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria.ORCID 0000-0001-5419-6713
Rik CrutzenLudwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria.ORCID 0000-0002-3731-6610
Elisabeth KlagerLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-0722-1255
Sabine Völkl-KernstockLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-1951-1893
Eva SchadenLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-7571-8680
Maria Kletecka-PulkerLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-4901-7930
Harald WillschkeLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-9093-7563
Atanas G AtanasovLudwig Boltzmann Institute for Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-2545-0967
Austrian Institute for Health Technology Assessment GmbH · ATUniversity of Vienna · ATMaastricht University · NLMohammed Bin Rashid University of Medicine and Health Sciences · AEStatistics Austria · ATUniversity of Calgary · CAUniversity of Crete · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOn January 30, 2020, the World Health Organization's Emergency Committee declared the rapid, worldwide spread of COVID-19 a global health emergency. Since then, tireless efforts have been made to mitigate the spread of the disease and its impact, and these efforts have mostly relied on nonpharmaceutical interventions. By December 2020, the safety and efficacy of the first COVID-19 vaccines were demonstrated. The large social media platform Twitter has been used by medical researchers for the analysis of important public health topics, such as the public's perception on antibiotic use and misuse and human papillomavirus vaccination. The analysis of Twitter-generated data can be further facilitated by using Twitter's built-in, anonymous polling tool to gain insight into public health issues and obtain rapid feedback on an international scale. During the fast-paced course of the COVID-19 pandemic, the Twitter polling system has provided a viable method for gaining rapid, large-scale, international public health insights on highly relevant and timely SARS-CoV-2-related topics.

objectiveThe purpose of this study was to understand the public's perception on the safety and acceptance of COVID-19 vaccines in real time by using Twitter polls.

methodsWe developed 2 Twitter polls to explore the public's views on available COVID-19 vaccines. The surveys were pinned to the Digital Health and Patient Safety Platform Twitter timeline for 1 week in mid-February 2021, and Twitter users and influencers were asked to participate in and retweet the polls to reach the largest possible audience.

resultsThe adequacy of COVID-19 vaccine safety (ie, the safety of currently available vaccines; poll 1) was agreed upon by 1579 out of 3439 (45.9%) Twitter users. In contrast, almost as many Twitter users (1434/3439, 41.7%) were unsure about the safety of COVID-19 vaccines. Only 5.2% (179/3439) of Twitter users rated the available COVID-19 vaccines as generally unsafe. Poll 2, which addressed the question of whether users would undergo vaccination, was answered affirmatively by 82.8% (2862/3457) of Twitter users, and only 8% (277/3457) categorically rejected vaccination at the time of polling.

conclusionsIn contrast to the perceived high level of uncertainty about the safety of the available COVID-19 vaccines, we observed an elevated willingness to undergo vaccination among our study sample. Since people's perceptions and views are strongly influenced by social media, the snapshots provided by these media platforms represent a static image of a moving target. Thus, the results of this study need to be followed up by long-term surveys to maintain their validity. This is especially relevant due to the circumstances of the fast-paced pandemic and the need to not miss sudden rises in the incidence of vaccine hesitancy, which may have detrimental effects on the pandemic's course.

Indexed as

COVID-19COVID-19 VaccinesFemaleHumansMalePandemicsPapillomavirus VaccinesPatient CompliancePublic HealthSARS-CoV-2Social MediaVaccinationCOVID-19 VaccinesPapillomavirus VaccinesconcerncoronavirusCOVID-19hesitancyopinionperceptionpublic healthsafetySARS-CoV-2social mediasurveyTwittervaccinationvaccination hesitancyvaccination willingnessvaccinevaccine confidencewillingness

Identifiers

PMID33872185
PMCPMC8086789
OpenAlexW3154586727

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.