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Record W4408507801 · doi:10.1177/13591053251323502

Factors associated with parents’ hesitancy to vaccinate their children against COVID-19: The moderator role of parental anxiety

2025· article· en· W4408507801 on OpenAlexafffundabout
Josée Richard, Anik Dubé, Jalila Jbilou, Mylène Lachance‐Grzela

Bibliographic record

VenueJournal of Health Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversité de Moncton
FundersNew Brunswick Innovation Foundation
KeywordsModerationAnxietyPsychologyCoronavirus disease 2019 (COVID-19)PandemicMedicineClinical psychologyDevelopmental psychologyPsychiatrySocial psychologyDisease

Abstract

fetched live from OpenAlex

The aim of this study was to examine the factors that influenced parental hesitancy toward vaccinating children against COVID-19 in the months leading up to the launch of the pediatric vaccination campaign. We examined whether parental anxiety moderated the relationships between parents' access to vaccine information, choice overload, perceived freedom of choice, mistrust toward authorities, and hesitancy toward vaccinating children against COVID-19. A sample of 440 Canadian parents of children aged 1-16 years completed questionnaires. Results revealed that having less access to information and perceiving greater freedom in decision-making increased hesitancy among parents, especially when they reported experiencing anxiety in their parental role. Mistrust of authorities and choice overload were linked to greater hesitancy about vaccination. However, these links were not moderated by the reported parental anxiety. Considering that there will likely be more pandemics in the future, our study has pertinent implications for the healthcare community.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.378
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes3
Has abstractyes

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