Evidence map›Paper›PMID 34336426›Full record

ArticleCureus2021

Role of Information Technology in COVID-19 Vaccination Drive: An Analysis of the COVID-19 Global Beliefs, Behaviors, and Norms Survey.

Debjyoti Talukdar, Kire Stojkovski, Daniel B Suarez, Madan Mohan Gupta

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors at 3 institutions in 4 countries.

Debjyoti TalukdarCollege of Pharmacy, Teerthanker Mahaveer College of Pharmacy, Moradabad, IND.
Kire StojkovskiSports Medicine, Faculty of Medical Science, Goce Delčev University of Štip, Shtip, MKD.
Daniel B SuarezIntegrative Medicine, Urbanización Trigal Centro, Valencia, VEN.
Madan Mohan GuptaSchool of Pharmacy, Faculty of Medical Sciences, The University of the West Indies at St. Augustine, St. Augustine, TTO.
Institute for Integrative Systems Biology · ESGoce Delcev University · MKTeerthanker Mahaveer University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the onset of the COVID-19 pandemic, information technology has played a critical role in healthcare. A broad spectrum of information technology tools and applications played an essential role to create awareness of the COVID-19 vaccination drive and its health benefits. Research conducted by Massachusetts Institute of Technology (MIT) in collaboration with information technology platforms like Facebook with inputs from World Health Organization (WHO), John Hopkins University (JHU), and Global Outbreak Alert and Response Network (GOARN) shows that 65.06% of people all over the globe are willing to get vaccinated. Vaccine acceptance depends upon social norms and human behavior. These organizations conducted the global survey in over 60 countries with a sample size of 437,236 responses. The international survey was organized using a pre-registered randomized experiment demonstrating the role of technology in reaching out to people based in diverse communities and evaluating their beliefs, behavior, and social norms. The study shows that vaccine acceptance can vary due to descriptive norms. All the respondents in the study were adults with access to the internet. Moreover, a large proportion of the population thinks that the COVID-19 pandemic is a viable threat to the community and preventive measures need to be taken including vaccination drives to eradicate the menace. The survey consisted of five blocks involving questions related to healthcare, demographics, vaccines, knowledge, and information exposure. Sampling and weighting were done using a pool of 3,000 respondents over two weeks, and weights were provided per respondent to represent the target population as a whole. It reduces the representation error and minimizes non-response biases.

Indexed as

covid-19covid-19 vaccine surveyinformation technologymit vaccine surveysars ncov-2vaccine

Identifiers

PMID34336426
PMCPMC8310678
OpenAlexW3163421273

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.