Navigating pancreas transplant perceptions: assessing public sentiment and strategies using AI-driven analysis.

Background: Pancreas transplantation, a crucial treatment for diabetes, is underutilized due to its invasiveness, strict criteria, organ scarcity, and limited centers. This highlights the need for enhanced public education and awareness through digital health platforms.

Methods: We utilized Google's AI-driven, consensus-based model and Claude AI 3.0 Opus by Anthropic to analyze public perceptions of pancreas transplantation. The top 10 websites identified by Google as of April-May 2024 were reviewed, focusing on sentiment, consensus, content readability, and complexity to develop strategies for better public engagement and understanding using digital health technologies.

Results: The top 10 websites, originating from the US and UK, showed a neutral and professional tone, targeting medical professionals and patients. Complex content was updated between 2021 and 2024, with a readability level suitable for high school to early college students. AI-driven analysis revealed strategies to increase public interest and understanding, including incorporating patient stories, simplifying medical jargon, utilizing visual aids, emphasizing quality of life improvements, showcasing research progress, facilitating patient outreach, promoting community engagement, partnering with influencers, and regularly updating content through digital health platforms.

Conclusion: To increase interest in pancreas transplantation in the era of connected health, we recommend integrating real patient experiences, simplifying medical content, using visual explanations, emphasizing post-transplant quality-of-life improvements, highlighting recent research, providing outreach opportunities, encouraging community connections, partnering with influencers, and keeping information current through digital health technologies. These methods aim to make pancreas transplantation more accessible and motivating for a diverse audience, supporting informed decision-making.