ArticlePNAS nexus2025
Living health-promotion campaigns for communities in the United States: Decentralized content extraction and sharing through AI.
Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- The persuasive impact of attitudinal, behavioral, and combined message statements.Scientific reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
31 authors.
Funding
Abstract
Even though health-promotion campaigns can elicit behavioral change among constituents, these initiatives are generally implemented through expensive, centralized, unsystematic, and time-consuming efforts led by creatives and officials in federal and national agencies. Can advancements in AI provide systematic methods that generate living health campaigns out of social media posts generated by communities? Here, we report the success of an innovative method to automatically select actionable HIV prevention and testing messages from decentralized content on social media (e.g. X [formerly Twitter]). The method was assessed through computational methods, an online experiment with men who have sex with men, and a field experiment involving public health agencies and community-based organizations with jurisdiction in 42 counties in the United States. The computational analyses showed that the method is computationally successful. The results of the two experiments indicated that the resulting messages are perceived as more actionable, personally relevant, and effective, and the messages are six times as likely to be posted by agencies in United States counties.
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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.