Evidence map›Paper›PMID 40579633›Full record

ArticleJournal of racial and ethnic health disparities2026

The English-Only Nature of Vaccine Deservedness and Harms of Racialized Administrative Burdens.

Sayil Camacho, Carolyn J Heinrich, Montrell Sanders, Mary-Margaret McGowan

Abstract read
In one paragraph

Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sayil CamachoLatina Futures 2050 Lab, University of California, Los Angeles (UCLA), 193 Haines Hall, Los Angeles, CA, 90095-1544, USA. sasayil@g.ucla.edu.ORCID 0000-0003-0765-6961
Carolyn J HeinrichPeabody College of Education and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203, USA.ORCID 0000-0002-7731-9138
Montrell SandersDepartment of Public Policy and Administration, Rutgers University-Camden, 401 Cooper Street, Camden, NJ, 08102, USA.
Mary-Margaret McGowanPeabody College of Education and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite extensive efforts to facilitate COVID-19 vaccine access and achieve a 70% vaccination rate, race-based disparities and barriers to vaccine access continue to persist in the United States. To investigate discrimination among Limited-English Proficient (LEP) populations, we conducted a paired audit test field experiment. Testers with identical gender and immigration status, but differing in racial and language profiles, inquired about vaccine access in all 50 states through the Department of Health and Major Vaccine Sites, using phone, email, and web-based chat communication. The results show that Spanish-speaking testers faced additional systemic barriers, were more likely to encounter overt racialized and judgmental language, and experienced heightened scrutiny regarding their identity. These findings highlight both macro-level communication infrastructure and micro-level interactions that contribute to ongoing disparities in healthcare access.

Indexed as

COVID-19 VaccinesHealthcare DisparitiesHealth Services AccessibilityLimited English ProficiencyRacismFemaleHumansMaleUnited StatesCOVID-19 VaccinesHealthcare equityLimited English Proficient (LEP) populationsRacialization and discriminationStructural humility

Identifiers

PMID40579633
PMCPMC13346158

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.