Evidence map›Paper›PMID 35162050›Full record

ArticleInternational journal of environmental research and public health2022

Primary Factors Influencing the Decision to Vaccinate against COVID-19 in the United States: A Pre-Vaccine Analysis.

Serkan Varol, Serkan Catma, Diana Reindl, Elizabeth Serieux

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 country.

Serkan VarolDepartment of Engineering Management, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA.ORCID 0000-0003-1771-3499
Serkan CatmaDepartment of Business Administration, University of South Carolina Beaufort, Bluffton, SC 29902, USA.ORCID 0000-0002-7996-1271
Diana ReindlDepartment of Nursing and Health Professions Business, University of South Carolina Beaufort, Bluffton, SC 29902, USA.
Elizabeth SerieuxInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98105, USA.
University of South Carolina Beaufort · USUniversity of Tennessee at Chattanooga · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because vaccine hesitancy is a dynamic trait, it is critical to identify and compare the contributing factors at the different stages of a pandemic. The prediction of vaccine decision making and the interpretation of the analytical relationships among variables that encompass public perceptions and attitudes towards the COVID-19 pandemic have been extensively limited to the studies conducted after the administration of the first FDA-approved vaccine in December of 2020. In order to fill the gap in the literature, we used six predictive models and identified the most important factors, via Gini importance measures, that contribute to the prediction of COVID-19 vaccine acceptors and refusers using a nationwide survey that was administered in November 2020, before the widespread use of COVID-19 vaccines. Concerns about (re)contracting COVID-19 and opinions regarding mandatory face covering were identified as the most important predictors of vaccine decision making. By investigating the vaccine acceptors and refusers before the introduction of COVID-19 vaccines, we can help public health officials design and deliver individually tailored and dynamic vaccination programs that can increase the overall vaccine uptake.

Indexed as

COVID-19VaccinesCOVID-19 VaccinesHumansPandemicsSARS-CoV-2United StatesVaccinationCOVID-19 VaccinesVaccinesCOVID-19 vaccinationmask mandatepredictive modelingvaccine hesitancy

Identifiers

PMID35162050
PMCPMC8834206
OpenAlexW4206057031

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.