Multilevel determinants of Covid-19 vaccine hesitancy and undervaccination among marginalized populations in the United States: A scoping review
Newman, P. A.; Nyoni, T.; Allan, K.; Fantus, S.; Dinh, D.; Tepjan, S.; Reid, L.; Guta, A.
Show abstract
BackgroundAmid persistent disparities in Covid-19 vaccination, we conducted a scoping review to identify multilevel determinants of Covid-19 vaccine hesitancy (VH) and undervaccination among marginalized populations in the U.S. MethodsWe utilized the scoping review methodology developed by the Joanna Briggs Institute and report all findings according to PRISMA-ScR guidelines. We developed a search string and explored 7 databases to identify peer-reviewed articles published from January 1, 2020-October 31, 2021, the initial period of U.S. Covid-19 vaccine avails.comability. We combine frequency analysis and narrative synthesis to describe factors influencing Covid-19 vaccination among marginalized populations. ResultsThe search captured 2,496 non-duplicated records, which were scoped to 50 peer-reviewed articles: 11 (22%) focused on African American/Black people, 9 (18%) people with disabilities, 4 (8%) justice-involved people, and 2 (4%) each on Latinx, people living with HIV/AIDS, people who use drugs, and LGBTQ+ people. Forty-four articles identified structural factors, 36 social/community, 27 individual, and 40 vaccine-specific factors. Structural factors comprised medical mistrust (of healthcare systems, government public health) and access barriers due to unemployment, unstable housing, lack of transportation, no/low paid sick days, low internet/digital technology access, and lack of culturally and linguistically appropriate information. Social/community factors including trust in a personal healthcare provider (HCP), altruism, family influence, and social proofing mitigated VH. At the individual level, low perceived Covid-19 threat and negative vaccine attitudes were associated with VH. DiscussionThis review indicates the importance of identifying and disaggregating structural factors underlying Covid-19 undervaccination among marginalized populations, both cross-cutting and population-specific--including multiple logistical and economic barriers in access, and systemic mistrust of healthcare systems and government public health--from individual and social/community factors, including trust in personal HCPs/clinics as reliable sources of vaccine information, altruistic motivations, and family influence, to effectively address individual decisional conflict underlying VH as well as broader determinants of undervaccination.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- “Where the truth really lies”: Listening to voices from African American communities in the Southern States about COVID-19 vaccine information and communication 96%
- COVID-19 vaccine hesitancy in diverse groups in the UK - is the driver economic or cultural in student populations? 96%
- Social patterning and stability of COVID-19 vaccination acceptance in Scotland: Will those most at risk accept a vaccine? 96%
Similar papers in this journal
- COVID-19 Vaccine Hesitancy among Marginalized Populations in the U.S. and Canada: Protocol for a Scoping Review 99%
- COVID-19 vaccine access and attitudes among people experiencing homelessness from pilot mobile phone survey in Los Angeles, CA 96%
- Determinants of the COVID-19 Vaccine Hesitancy Spectrum 95%
Similar papers in this journal
- A “step too far” or “perfect sense”? A qualitative study of British adults’ views on mandating COVID-19 vaccination and vaccine passports 96%
- Parental attitudes towards mandatory vaccination; a systematic review 96%
- The social experience of participation in a COVID-19 vaccine trial: Subjects’ motivations, others’ concerns, and insights for vaccine promotion 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.