Evidence map›Paper›PMID 35255881›Full record

Observational studyBMC public health2022

COVID-19 vaccine perceptions in the initial phases of US vaccine roll-out: an observational study on reddit.

Navin Kumar, Isabel Corpus, Meher Hans, Nikhil Harle, Nan Yang, Curtis McDonald, Shinpei Nakamura Sakai, Kamila Janmohamed, Keyu Chen, Frederick L Altice and 13 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
11.8field-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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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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

23 authors at 10 institutions in 3 countries.

Navin KumarSection of Infectious Diseases, Yale School of Medicine, New Haven, CT, USA. Navin.kumar@yale.edu.
Isabel CorpusYale College, New Haven, CT, USA.
Meher HansYale College, New Haven, CT, USA.
Nikhil HarleYale College, New Haven, CT, USA.
Nan YangDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Curtis McDonaldDepartment of Statistics, Yale University, New Haven, CT, USA.
Shinpei Nakamura SakaiDepartment of Statistics, Yale University, New Haven, CT, USA.
Kamila JanmohamedYale College, New Haven, CT, USA.
Keyu ChenSection of Infectious Diseases, Yale School of Medicine, New Haven, CT, USA.
Frederick L AlticeSection of Infectious Diseases, Yale School of Medicine, New Haven, CT, USA.
Weiming TangUniversity of North Carolina Project-China, Guangzhou, China.
Jason L SchwartzDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.
S Mo Jones-JangDepartment of Communications, Boston College, Boston, MA, USA.
Koustuv SahaMicrosoft Research Lab, Montreal, Québec, Canada.
Shahan Ali MemonNew York University, Abu Dhabi, UAE.
Chris T BauchDepartment of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.
Munmun De ChoudhurySchool of Interactive Computing, Georgia Tech, Atlanta, GA, USA.
Orestis PapakyriakopoulosCenter for Information Technology Policy, Princeton University, Princeton, NJ, USA.
Joseph D TuckerUniversity of North Carolina Project-China, Guangzhou, China.
Abhay GoyalDepartment of Computer Science, Stony Brook University, New York, NY, USA.
Aman TyagiEngineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA.
Kaveh KhoshnoodDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Saad OmerYale Institute for Global Health, New Haven, CT, USA.
Yale University · USUniversity of North Carolina at Chapel Hill · USBoston College · USCarnegie Mellon University · USGeorgia Institute of Technology · USMicrosoft Research Montréal (Canada)New York University · USPrinceton University · USStony Brook University · USUniversity of Waterloo · CA

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

backgroundOpen online forums like Reddit provide an opportunity to quantitatively examine COVID-19 vaccine perceptions early in the vaccine timeline. We examine COVID-19 misinformation on Reddit following vaccine scientific announcements, in the initial phases of the vaccine timeline.

methodsWe collected all posts on Reddit (reddit.com) from January 1 2020 - December 14 2020 (n=266,840) that contained both COVID-19 and vaccine-related keywords. We used topic modeling to understand changes in word prevalence within topics after the release of vaccine trial data. Social network analysis was also conducted to determine the relationship between Reddit communities (subreddits) that shared COVID-19 vaccine posts, and the movement of posts between subreddits.

resultsThere was an association between a Pfizer press release reporting 90% efficacy and increased discussion on vaccine misinformation. We observed an association between Johnson and Johnson temporarily halting its vaccine trials and reduced misinformation. We found that information skeptical of vaccination was first posted in a subreddit (r/Coronavirus) which favored accurate information and then reposted in subreddits associated with antivaccine beliefs and conspiracy theories (e.g. conspiracy, NoNewNormal).

conclusionsOur findings can inform the development of interventions where individuals determine the accuracy of vaccine information, and communications campaigns to improve COVID-19 vaccine perceptions, early in the vaccine timeline. Such efforts can increase individual- and population-level awareness of accurate and scientifically sound information regarding vaccines and thereby improve attitudes about vaccines, especially in the early phases of vaccine roll-out. Further research is needed to understand how social media can contribute to COVID-19 vaccination services.

Indexed as

COVID-19Social MediaVaccinesCOVID-19 VaccinesHumansSARS-CoV-2COVID-19 VaccinesVaccinesComputationalCOVID-19MisinformationRedditVaccine

Identifiers

PMID35255881
PMCPMC8899002
OpenAlexW4220847937

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.