Overcoming barriers to childhood vaccination in a First Nations community: the impact of a home visiting program on vaccine uptake
Bibliographic record
Abstract
BACKGROUND: First Nations children in Canada experience lower vaccination coverage compared to the general population, yet research on vaccination confidence, access, and uptake in on-reserve communities remains limited. This study examines barriers to childhood vaccination and the role of the Early Years (EY) home visiting program in influencing uptake in Maskwacis, a First Nations Community in central Alberta. METHODS: Guided by community-based participatory research, data were collected with parents, through interviews (n = 23); EY home visitors who provide support to parents, through a review of case notes (n = 851 entries), a survey (n = 7), and focus groups (n = 3 with 18 participants); and health staff who administer vaccinations, through a survey (n = 5) and interviews (n = 4). Data were analyzed using qualitative content analysis. RESULTS: Participants identified multiple barriers to vaccination, including resource challenges preventing them from accessing appointments, limited information and misinformation about vaccinations, sociocultural concerns, fear of injections, negative healthcare experiences, and pandemic-related challenges. These barriers were often rooted in a distrust of healthcare systems and a strong desire amongst parents to protect their children. The EY program facilitated vaccination by providing parents with accurate information, assisting families with attending appointments, and fostering trusting relationships with parents. Central to these facilitators was reassurance parents received that vaccines are safe and important for their children’s health. CONCLUSIONS: The study offers key insights into barriers to childhood vaccination in an on-reserve First Nations community and the role of culturally grounded home visiting programs in facilitating confidence and access. The findings can inform strategies to strengthen vaccination uptake among First Nations children and families and advance health equity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".