Evidence map›Paper›PMID 42723875›Full record

ArticleFrontiers in public health2026

The Health Communications Assessment Checklist: a teaching tool for uncovering bias in the age of AI.

Rebecca H Ofrane, Taliah Canada, Amanda S Birnbaum

Abstract read
In one paragraph

Article in Frontiers in public health, 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
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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

3 authors.

Rebecca H OfraneDepartment of Public Health, College for Community Health, Montclair State University, Montclair, NJ, United States.
Taliah CanadaDepartment of Public Health, College for Community Health, Montclair State University, Montclair, NJ, United States.
Amanda S BirnbaumDepartment of Public Health, College for Community Health, Montclair State University, Montclair, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The COVID-19 pandemic highlighted significant failures in United States public health communications, which were often perceived as unclear and biased, particularly among racialized and marginalized groups. As generative artificial intelligence (genAI) becomes integrated into public health practice, there is an urgent need to train the workforce to recognize and mitigate the societal biases these tools can reproduce. This study describes the development and classroom testing of a tool designed to teach these critical evaluation skills. Methods: We developed the "Health Communications Assessment Checklist," a 14-question pedagogical tool based on the CommunicateHealth Framework for Equity-Centered Health Communication and the CDC's Guiding Principles for health equity. The checklist was tested during the 2024-2025 academic year in two graduate-level courses ( Results: Post-exercise surveys and classroom discussions indicated positive student engagement and self-reported skill-building in critical assessment. A key finding was that students leaned heavily on their diverse individual identities and lived experiences to identify subtle biases that the AI generated. Furthermore, the checklist acted as a self-assessment tool, helping students identify gaps in their own knowledge of communication implementation. Feedback led to iterative improvements of the tool. Conclusion: The Health Communications Assessment Checklist is a simple, modifiable, and promising pedagogical tool for public health education. By centering equity and reflexivity, it helps prepare the future workforce to critically manage AI-generated content, ensuring health communications are inclusive and effective in promoting health equity.

Indexed as

ChecklistCOVID-19Health CommunicationGenerative Artificial IntelligenceHumansPublic HealthSARS-CoV-2United Statesassessmentdiversity as an assethealth communicationteachinguse of technology innovation

Identifiers

PMID42723875
PMCPMC13558193

What OpenQuestion holds

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Registered trials

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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.