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Record W4410157649 · doi:10.70440/001c.137584

Childhood COVID-19 Vaccine Poster Project: A Resident-Led Advocacy Campaign

2025· article· en· W4410157649 on OpenAlexaff
Daniel Birkhead, Brandon Mogrovejo, Ashley Stephens, Laurie Gordon

Bibliographic record

VenueJournal of Health Advocacy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsColumbia College
FundersCenters for Disease Control and Prevention
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakPolitical scienceVirologyMedicineOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Background Vaccine hesitancy around the COVID-19 vaccine was apparent to pediatric providers even before a vaccine was approved for use in young children. Retrospective data confirmed this hesitation among families in the state of New York where, in 2021, 52% of children aged 5-17 had received a COVID-19 vaccine dose compared to over 96% of adults with uptake lagging primarily among racial and ethnic minority populations. Objective To shift the conversation around vaccination, a group of advocacy-focused pediatric residents joined forces as part of the New York Pediatric Residency Advocacy Coalition (NY PRAC) to address vaccine hesitancy and promote vaccine uptake for pediatric COVID-19 vaccines. Methods NY PRAC held virtual meetings to determine the best approach to disseminate COVID-19 vaccination information, partnered with a pediatric resident to design a visual message to drive patient families to access health literate information, and tracked the spread of accessed information. Qualitative and anecdotal feedback about use of the posters with patient families during clinic visits and hospitalizations were shared by residents at monthly NY PRAC meetings. Results Two versions of the COVID-19 vaccine poster with QR codes linked to vaccine information provided by the Centers for Disease Control and Prevention were developed, one in Spanish and one in English. Posters were disseminated to NY PRAC members, which included over 80 residents from over 20 residency programs throughout New York State, who displayed the posters in their respective clinics and hospitals. In the first 12 months of distribution (2021-2022), there were 332 scans of the QR codes: 233 in English and 99 in Spanish; and 107 scans included links to the NY COVID-19 vaccine sign-up page. Anecdotal feedback shared by NY PRAC members highlighted that the posters served as a stimulus for interactive conversations with patient families during health care visits about potential vaccine uptake. Conclusions This collaboration of pediatric residents through NY PRAC resulted in a poster-driven vaccine campaign that utilized technology to enhance patient education and health literacy and address vaccine hesitancy. The posters facilitated access to COVID-19 vaccine information for hundreds of individuals through >300 unique QR code scans and prompted deeper conversations with patient families, which anecdotally showed the impact that a simple poster can have. This collaboration also demonstrated successful collaborative advocacy efforts among pediatric residents and offers important lessons learned for further physician collaboration and future advocacy.

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)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0200.003

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 head0.025
GPT teacher head0.379
Teacher spread0.354 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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