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Record W4392953382 · doi:10.1186/s13104-024-06739-2

Factors associated with vaccine hesitancy against COVID-19 among adults in Europe: a descriptive study analysis applying socio-ecological framework

2024· article· en· W4392953382 on OpenAlexfundno aff
Megumi Nagase

Bibliographic record

VenueBMC Research Notes · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
FundersYork University
KeywordsLogistic regressionDemographyCoronavirus disease 2019 (COVID-19)Descriptive statisticsVaccinationMedicineRegression analysisSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakEnvironmental healthImmunologyDiseaseVirologyStatisticsInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

Abstract Objective This study aimed to explore the factors associated with COVID-19 vaccine hesitancy in Europe among adults by using the Socio-Ecological Model. Results This cross-sectional study used secondary data collected from respondents residing in 27 EU countries at the time of May 2021. The outcome was vaccine hesitancy against COVID-19, and the total sample size of 23,606 was analysed by binary logistic regression, as well as McKelvey and Zavonoia’s R 2 . After adding each level of variables, the model found the significant and increased association with vaccine hesitancy in younger age groups (21–39 years and 40–60 years vs. 65 years+), who left full-time education at a young age (16–19 years), those with manual jobs, those with children at home, individuals residing in small towns, and beliefs related to the vaccine. Together, the levels explained 49.5% of the variance associated with vaccine hesitancy, and the addition to each variable layer increased the variance. This highlights the need to consider broad factors at multiple levels to enhance vaccine acceptance and uptake.

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.

How this classification was reachedexpand

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)0.005
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.011
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.224
GPT teacher head0.434
Teacher spread0.210 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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