Organisational and Structural Drivers of Childhood Immunisation in the European Region: A Systematic Review
Bibliographic record
Abstract
Despite the implementation of widespread vaccination programs, the European Health Systems continue to experience care challenges attributable to organizational and structural issues. This study aimed to review the available data on aspects within the organizational and structural domains that might impact vaccination coverage. We searched a comprehensive range of databases from 1 January 2007 to 6 July 2021 for studies that reported quantitative or qualitative research on interventions to raise childhood vaccine coverage. Outcome assessments comprised organizational and structural factors that contribute to vaccine concern among pediatric parents, as well as data reported influencing the willingness to vaccinate. To analyze the risk of bias, the Ottawa, JBI's (Joanna Briggs Institute) critical appraisal tool, and Amstar quality assessment were used accordingly. The inclusion criteria were met by 205 studies across 21 articles. The majority of the studies were conducted in the United Kingdom (6), the European Union (3), and Italy (3). A range of interventions studied in primary healthcare settings has been revealed to improve vaccination coverage rates including parental engagement and personalization, mandatory vaccination policies, program redesign, supply chain design, administering multiple/combination vaccines, improved vaccination timing and intervals, parental education and reminders, surveillance tools and Supplemental Immunisation Activity (SIA), and information model.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".