Influenza vaccine uptake among adults living with young children
Bibliographic record
Abstract
Background: Many studies report vaccine uptake among young adults aged 18 to 49 years is low. In Canada, the National Advisory Committee on Immunization (NACI) recommends influenza vaccination for adults in contact with young children, however vaccination rates for this specific population are missing. An estimate is required to identify appropriate public health interventions. The objective of this study was to describe recent trends in influenza vaccination uptake among Canadian adults aged 18 to 49 years old living with or without young children.Methods: The Canadian Community Health Survey (2013-2014) dataset, available for public use was used after grouping individuals by influenza vaccination uptake within the past year in adults aged 18 to 49 years. The relationship between living in a household with young children and influenza vaccination uptake was examined using a multivariable logistic regression model.Results: Among Canadian adults aged 18 to 49 years, the influenza vaccination uptake was 24.1% in adult household contacts with young children compared to 18.2% in those without young children (p<.0001). After adjusting for socio-demographic characteristics and self-perceived health, we determined that vaccine uptake was associated with living in a household with young children (adjusted OR: 1.30 [95%CI: 1.17-1.44]). While socio-demographic characteristics and self-perceived health greatly influenced influenza vaccination uptake, we also found marital status was a strong influencer of influenza vaccine uptake (adjusted OR: 1.31 [95%CI: 1.16-1.48]). Conclusion: Overall, influenza vaccination uptake among caregiving adults is low. Increased vaccine uptake was associated with living in a household with one or more young children. Targeted education and vaccination programs are required to improve uptake of the influenza vaccine in this age group.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".