MétaCan
Menu
Back to cohort
Record W4376645957 · doi:10.3389/fpubh.2023.1091015

Factors influencing parents’ hesitancy to vaccinate their children aged 5–11 years old against COVID-19: results from a cross-sectional study in Malaysia

2023· article· en· W4376645957 on OpenAlexaboutno aff
Roy Rillera Marzo, R. Chakraborty, Shean Yih Soh, Hui Zhu Thew, Collins Chong, Ching Sin Siau, Khairuddin Bin Abdul Wahab, Indang Ariati Ariffin, Shekhar Chauhan, Ken Brackstone, Bijaya Kumar Padhi, Petra Heidler

Bibliographic record

VenueFrontiers in Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationQuarter (Canadian coin)Cross-sectional studyMedicineMultivariate analysisHealth literacyDescriptive statisticsFamily medicinePopulationAffect (linguistics)DemographyPsychologyHealth careEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

Introduction Vaccination programs have been rolled out across the globe to contain and mitigate the spread of the COVID-19 infection. Until recently, such programs were limited to adults and the older population, thereby limiting children from getting vaccinated. Recently, the Malaysian government rolled out vaccination for children aged 5–11 years. However, there are certain factors that might affect vaccination uptake among children. This study explores factors influencing parents’ hesitancy to vaccinate children in Malaysia. Method A nationwide online cross-sectional convenience sampling survey from April 21, 2022 to June 3, 2022 was conducted. The study used descriptive statistics to inform about vaccine hesitancy among parents. Cross-tabulation was performed to calculate the frequency and percentage of vaccine hesitancy, quality of life, e-health literacy, and the 5C psychological antecedents of vaccination among parents with children 5-11 years in Malaysia. Graphical methods were used to portray the levels of e-health literacy and levels of 5C psychological antecedents of vaccination. The study used both bi-variate and multivariate analysis to understand the relationship between vaccine hesitancy and the socio-demo-economic factors, quality of life, e-health literacy and 5C psychological antecedents. Results Of 382 participants, almost one-third (33%) of participants reported vaccine hesitancy for their children. For 5C’s psychological antecedents of vaccination, around one quarter (26.96%) reported disagreement for confidence in vaccination, almost half (52.36%) reported disagreement for vaccination complacency, three-fifths (60.99%) reported vaccination constraint, one quarter (25.92%) reported calculation antecedent, and almost one-third reported disagreement over collective responsibility antecedent (25.92%). Chi-square test revealed that gender, employment status, and parents’ COVID-19 vaccination status were significantly associated ( p <0.05) with vaccine hesitancy among parents. Assessing the influence of transactional e-health literacy, only the communication component contained a significant association ( p <0.05). Among the 5C psychological antecedents, confidence, calculation, and collective responsibility were significantly associated ( p <0.05) with vaccine hesitancy. Parents with secondary [OR: 8.80; CI: 2.44−31.79, ( p <0.05)], post-secondary [OR: 5.21; CI: 2.10-13.41, ( p <0.05)], and tertiary education [OR: 6.77; CI: 2.25−20.35, ( p <0.05)] had significantly higher likelihood of vaccine hesitancy than those with primary education. Conclusion Highly educated parents are more skeptical and are more likely to perceive the vaccine as unsafe and ineffective for their children. It is critical to disseminate the required information about the vaccine safety to the educated group.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.349
Teacher spread0.279 · 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

Citations25
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Public HealthSame topicVaccine Coverage and HesitancyFrench-language works237,207