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Record W3212709196 · doi:10.1371/journal.pone.0258462

Individual determinants of COVID-19 vaccine hesitancy

2021· article· en· W3212709196 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePLoS ONE · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchOntario Ministry of Research and InnovationDepartment of Psychiatry, University of TorontoCentre for Addiction and Mental Health FoundationCentre for Addiction and Mental HealthNational Alliance for Research on Schizophrenia and DepressionUniversity of TorontoOntario Ministry of Health and Long-Term Care
KeywordsHerd immunityPublic healthDemographyMedicinePandemicCoronavirus disease 2019 (COVID-19)Confidence intervalVaccinationMental healthFamily medicineImmunologyPsychiatryDiseaseInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) vaccine hesitancy is a barrier to achieving herd immunity, and thus, a prominent public health concern. This study aimed to identify the determinants of COVID-19 vaccine hesitancy based on the World Health Organization's '3Cs' model (i.e., confidence, complacency, and convenience) in the United States (U.S.) and Canada. METHODS: Data from 7678 adults ages 18 or older were collected from the four most populous U.S. States, specifically New York, California, Florida, and Texas, and from English-speaking Canada at three timepoints, in May and July 2020, and March 2021 using a web-based survey (www.covid19-database.com). Sociodemographic information was collected, and comprehensive psychological assessments were administered. Univariate analyses were performed to identify the individual determinants of vaccine hesitancy, which were categorized as: 1) vaccine confidence, 2) vaccine complacency, 3) sociodemographic, and 4) other psychological factors. A series of models were computed using these categorizations. RESULTS: Mistrust of vaccine benefit (β(SE) = 0.67(0.01), p<0.001, partial η2 = 0.26) and lower perceived seriousness of COVID-19 (β(SE) = 0.68(0.02), p<0.001, partial η2 = 0.12) were the principal determinants of vaccine hesitancy. Right-wing political affiliation (β(SE) = 0.32(0.02), p<0.001, partial η2 = 0.03), higher risk propensity (β(SE) = 0.24(0.02), p<0.001, partial η2 = 0.03), and less negative mental health effects of the COVID-19 pandemic (β(SE) = 0.20(0.01), p<0.001, partial η2 = 0.03) were the main sociodemographic and psychological determinants. Other sociodemographic determinants included younger age, women, race, and employment status. Lack of vaccine confidence and complacency explained 38% and 21% of the variance in vaccine hesitancy, respectively; whereas, sociodemographic and psychological determinants explained 13% and 11% of the variance in vaccine hesitancy, respectively. DISCUSSION: Targeted and tailored public health interventions that enhance the public's confidence in vaccines and emphasize the risk and seriousness of COVID-19 may address COVID-19 vaccine hesitancy. Efforts directed toward specific marginalized and underserved groups may be required to promote vaccine confidence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.320
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it