Covid-19 Vaccine Hesitancy and Under-Vaccination among Marginalized Populations in the United States and Canada: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Amid persistent disparities in Covid-19 vaccination and burgeoning research on vaccine hesitancy (VH), we conducted a scoping review to identify multilevel determinants of Covid-19 VH and under-vaccination among marginalized populations in the U.S. and Canada. METHODS: Using the scoping review methodology developed by the Joanna Briggs Institute, we designed a search string and explored 7 databases to identify peer-reviewed articles published from January 1, 2020-October 25, 2022. We combine frequency analysis and narrative synthesis to describe factors influencing Covid-19 VH and under-vaccination among marginalized populations. RESULTS: The search captured 11,374 non-duplicated records, scoped to 103 peer-reviewed articles. Among 14 marginalized populations identified, African American/Black, Latinx, LGBTQ+, American Indian/Indigenous, people with disabilities, and justice-involved people were the predominant focus. Thirty-two factors emerged as influencing Covid-19 VH, with structural racism/stigma and institutional mistrust (structural)(n = 71) most prevalent, followed by vaccine safety (vaccine-specific)(n = 62), side effects (vaccine-specific)(n = 50), trust in individual healthcare provider (social/community)(n = 38), and perceived risk of infection (individual)(n = 33). Structural factors predominated across populations, including structural racism/stigma and institutional mistrust, barriers to Covid-19 vaccine access due to limited supply/availability, distance/lack of transportation, no/low paid sick days, low internet/digital technology access, and lack of culturally- and linguistically-appropriate information. DISCUSSION: We identified multilevel and complex drivers of Covid-19 under-vaccination among marginalized populations. Distinguishing vaccine-specific, individual, and social/community factors that may fuel decisional ambivalence, more appropriately defined as VH, from structural racism/structural stigma and systemic/institutional barriers to vaccination access may better support evidence-informed interventions to promote equity in access to vaccines and informed decision-making among marginalized populations.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".