Factors Associated With Vaccination Compliance in Southeast Asian Children: A Systematic Review
Bibliographic record
Abstract
Although vaccination coverage has reached a peak of 86% globally, around 19.9 million infants and children are yet to receive routine vaccinations-with Asia holding the highest prevalence of noncompliance. This implies notable gaps in vaccination coverage among some regions in the world. This study aims to analyze the factors associated with compliance toward childhood vaccination in Southeast Asia. A systematic review of observational studies was conducted using the following databases: PubMed, Scopus, and Cochrane. Included studies analyze factors affecting compliance with childhood vaccination in Southeast Asia, and assessed with Joanna Briggs Institute (JBI) and Newcastle-Ottawa Scale's criteria. Sixteen observational studies were included, with a total of 41 956 subjects, consisting of 15 cross-sectional studies and one case-control study. Our results suggested that parental personal-related, children and family status-related, socioeconomic, and health care-related factors strongly affected subjects' compliance with immunization. Prominent determinants were older maternal age, higher economics groups, parents in government or health care sectors, and frequent antenatal care visits. On the other hand, noncompliance were associated with younger age, large quantity of family members, lower economic groups, lower education, and unemployed parents. We hope that this comprehensive assessment thoroughly addresses challenges and inform strategies to raise compliance toward childhood vaccination in Southeast Asia.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".