Evaluating the Quality of Health Information: Comparison of Human and Artificial Intelligence
AI models demonstrated moderate alignment with human-assigned DISCERN scores for IBS-related TikTok videos, but only when content was produced by non-medical creators. The weaker correlation for content produced by those with a medical background suggests limitations in current AI models' ability to interpret nuanced or technical health information. These findings highlight the need for further validation across broader topics, languages, platforms, and reviewer pools. If refined, AI-generated DISCERN scoring could serve as a scalable tool to help users assess the reliability of health information on social media and curb misinformation.
Authors
- Neha Pondicherry (ORCID: https://orcid.org/0000-0003-2300-7902)
- Subhankar Chakraborty (ORCID: https://orcid.org/0009-0004-0524-022X)
- Dhruva Arcot
Institutions
- Crest Middle School (US)
- The Ohio State University (US)
Publication Details
- Journal
- Neurogastroenterology & Motility
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1111/nmo.70164
- Primary Topic
- Health Literacy and Information Accessibility
- Type
- article
- Field-Weighted Citation Impact
- 0.00