ArticlePloS one2023
iHeard STL: Development and first year findings from a local surveillance and rapid response system for addressing COVID-19 and other health misinformation.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Overcoming health misinformation in marginalized groups: a systematic review.International journal for equity in health · 2025Pooled it
- Digital and community-engaged approaches to improve research participant recruitment - Advice from forty convened experts.Journal of clinical and translational science · 2026Article
- Advocating for a community-centred model for responding to potential information harms.Nature human behaviour · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundThe U.S. Surgeon General and others have emphasized a critical need to address COVID-19 misinformation to protect public health. In St. Louis, MO, we created iHeard STL, a community-level misinformation surveillance and response system. This paper reports methods and findings from its first year of operation.
methodsWe assembled a panel of over 200 community members who answered brief, weekly mobile phone surveys to share information they heard in the last seven days. Based on their responses, we prioritized misinformation threats. Weekly surveillance data, misinformation priorities, and accurate responses to each misinformation threat were shared on a public dashboard and sent to community organizations in weekly alerts. We used logistic regression to estimate odds ratios (ORs) for associations between panel member characteristics and misinformation exposure and belief.
resultsIn the first year, 214 panel members were enrolled. Weekly survey response rates were high (mean = 88.3% ± 6%). Exposure to a sample of COVID-19 misinformation items did not differ significantly by panel member age category or gender; however, African American panel members had significantly higher reported odds of exposure and belief/uncertain belief in some misinformation items (ORs from 3.4 to 17.1) compared to white panel members.
conclusionsOur first-year experience suggests that this systematic, community-based approach to assessing and addressing misinformation is feasible, sustainable, and a promising strategy for responding to the threat of health misinformation. In addition, further studies are needed to understand whether structural factors such as medical mistrust underly the observed racial differences in exposure and belief.
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Registered trials
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.