Caregivers' vaccine hesitancy- a scoping review
Bibliographic record
Abstract
Aims/Background: Vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite its availability. COVID19 pandemic has increased public concerns towards vaccines hence influences the acceptance to the existing vaccination program in primary care. We aim to summarize the prevalence and factors associated with childhood vaccine hesitancy among caregivers. Methodology: This scoping review was conducted in accordance with PRISMA-ScR checklist. Scopus®, Cochrane Library and PubMed® databases were searched and filtered to include full-text English articles published from January 2016 to November 2021. Results: 83 articles were eligible out of 576 articles retrieved. Half were cross-sectional studies and published within the last 2 years. 39% articles were from USA, Canada and Italy. The mean prevalence of vaccine hesitancy was 25.8% (3%-50.6%). Caregivers’ factors which were belief, knowledge and attitude about health (78%), trust to health system (33.7%) and socio-demographic (32.5%) formed the major theme while other themes were less significant: contextual factors (13%), healthcare worker (9%), and vaccine’s specific (3%). Conclusion: An emerging issue during COVID19 pandemic especially in developed countries, vaccine hesitancy requires multi-interventional approach to increase caregivers’ confidence and competence in vaccination for their children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".