Evaluation of an Artificial Intelligence-Generated Health Communication Material on Bird Flu Precautions

  • Ayokunle A. Olagoke
  • , Comfort Tosin Adebayo
  • , Joseph Ayotunde Aderonmu
  • , Emmanuel A. Adeaga
  • , Kimberly J. Johnson

Research output: Contribution to journalArticlepeer-review

Abstract

The 2025 avian influenza A(H5N1) outbreak has highlighted the urgent need for rapidly generated health communication materials during public health emergencies. Artificial intelligence (AI) systems offer transformative potential to accelerate content development pipelines while maintaining scientific accuracy and impact. We evaluated an AI-generated health communication material on bird flu precautions among 100 U.S. adults. The material was developed using ChatGPT for text generation based on CDC guidelines and Leonardo.AI for illustrations. Participants rated perceived message effectiveness, quality, realism, relevance, attractiveness, and visual informativeness. The AI-generated health communication material received favorable ratings across all dimensions: perceived message effectiveness (3.83/5, 77%), perceived message quality (3.84/5, 77%), realism (3.72/5, 74%), relevance (3.68/5, 74%), attractiveness (3.62/5, 74%), and visual informativeness (3.35/5 67%). Linear regression analysis revealed that all features significantly predicted perceived message effectiveness in unadjusted and adjusted models (p < 0.0001), e.g., multivariate analysis of outcome on perceived visual informativeness showed β = 0.51, 95% CI: 0.37–0.66, p < 0.0001. Also, mediation analysis revealed that visual informativeness accounted for 23.8% of the relationship between material attractiveness and perceived effectiveness. AI tools can enable real-time adaptation of prevention guidance during epidemiological emergencies while maintaining effective risk communication.

Original languageEnglish
Article number22
JournalZoonotic Diseases
Volume5
Issue number3
DOIs
StatePublished - Sep 2025

Keywords

  • artificial intelligence
  • avian influenza
  • health communication
  • perceived message effectiveness
  • public health

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