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Record W4408163194 · doi:10.1186/s12939-025-02424-3

The role of narratives in promoting vaccine confidence among Indigenous peoples in Canada, the United States, Australia, and New Zealand: a scoping review

2025· review· en· W4408163194 on OpenAlexafffundabout
R. W. Martell, Maurianne Reade, Lisa Boesch, D. Kaur, Sandeep Kumar, Michael McArthur, Marion Maar

Bibliographic record

VenueInternational Journal for Equity in Health · 2025
Typereview
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsNOSM UniversityLaurentian University
FundersCanadian Institutes of Health Research
KeywordsPsycINFOPsychological interventionGrey literaturePublic healthIndigenousMedicineHealth promotionMEDLINESystematic reviewNarrativePublic relationsMedical educationFamily medicinePolitical scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Many Indigenous youth and young adults in Canada, the United States, Australia, and New Zealand have reported low vaccine confidence, which has been linked to lower vaccination rates for COVID-19, MMR, HPV, DTaP-IPV-Hib, and pneumococcal conjugate vaccines. Narrative-based health promotion approaches, including those focused on strengthening vaccine confidence, have been used in public health interventions. Scoping reviews have become increasingly valued for their rigorous and reproducible exploration of evidence in public health research. The aim of this scoping review was to understand the extent and types of evidence related to the facilitators, challenges, and benefits of narrative-based health promotion approaches in vaccine confidence interventions within Indigenous populations. METHODS: This review adhered to the Joanna Briggs Institute (JBI) guidelines for scoping reviews using Covidence online software to streamline the review process. Database searches were conducted in MEDLINE, Embase, Web of Science, PsycINFO, and PubMed, as well as Google search to identify both academic and gray literature articles on the role of narratives in promoting vaccine confidence published between January 2000 and April 2024. Charted data were ranked in a numerical summary and analyzed using qualitative content analysis. The review process embraced a two-eyed seeing approach. RESULTS: The searches identified 306 records. After the screening process, 45 sources (35 peer-reviewed articles, eight gray literature, and two preprint articles) were included in the final review. The key facilitators of narrative-based approaches to promote vaccine confidence were community engagement, tailored and culturally safe interventions, and trusted messengers and sources of information. The challenges discussed in the literature were linked to mistrust of government and healthcare services and to misinformation narratives. The most frequently reported benefits were the development of community-based resources, culturally safe and relevant interventions, building trust and respectful relationships, and improved vaccination rates. CONCLUSION: This review confirmed the important contribution of narrative-based health promotion approaches in strengthening vaccine confidence among Indigenous populations. This finding underscores the importance of respecting Indigenous sovereignty and engaging community perspectives to repair trust and improve vaccination rates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.846
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0180.018
Science and technology studies0.0040.003
Scholarly communication0.0080.005
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.096
GPT teacher head0.475
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2025
Admission routes3
Has abstractyes

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