Systematic review and meta-analysis of interventions to increase the uptake of vaccines recommended during pregnancy
Bibliographic record
Abstract
Abstract Although immunization during pregnancy can protect mothers and their infants from vaccine-preventable morbidity and mortality, vaccination rates are often poor. We systematically reviewed the literature from inception to July 4, 2023, for randomized and non-randomized quasi-experimental studies estimating the effects of interventions to increase vaccination during pregnancy. Of 9331 studies screened, 36 met inclusion criteria, including 18 demand-side interventions, 11 supply-side interventions, and seven multi-level (demand and supply-side) interventions. Demand-side interventions commonly addressed patient education, showing modest improvement (pooled RR 1.18; 95% CI: 1.04, 1.33; I 2 = 63.1%, low certainty). Supply-side interventions commonly implemented Assessment-Feedback-Incentive-eXchange interventions with little improvement (pooled RR 1.13; 95% CI: 0.96, 1.33; I 2 = 94.0%, low certainty). Multi-level interventions were modestly effective in increasing vaccination (pooled RR 1.62; 95% CI: 1.09, 2.42; I 2 = 97%, very low certainty). Interventions identified in the literature mostly resulted in low to moderate increases in vaccination with likely high heterogeneity and low to very low certainty in the findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".