Social determinants of health and periodontal disease in U.S. adults: comparing generative AI-assisted outputs with human-led systematic review

Introduction Generative AI tools (GAI) are widely used to speed literature reviews, yet their fidelity and reliability for literature synthesis remain unclear. This study had two Objectives: 1) summarize the evidence on associations between social determinants of health (SDOH) and periodontal disease (PD) in U.S. adults. 2) comparatively evaluate how accurately GAI tools summarize evidence compared to a PRISMA-guided human review. Methods For the comparative analysis between a PRISMA-guided human systematic review and GAI tools, we selected the base models of ChatGPT-5.5, Gemini-3.5, and Perplexity. We conducted a search of five databases between January 2012 and December 2024, examining associations between SDOH and PD. A standardized prompt was used across all GAI tools. GAI output performance was evaluated using Checklist Coverage, Summary Fidelity, and Unsupported Content Score. Checklist Coverage assessed whether required checklist elements were included. Summary Fidelity Score assessed how well the outputs reflected the original content. Unsupported Content Score assessed whether the outputs introduced information not supported by the original study. Results Seven studies met the inclusion criteria. ChatGPT-5.5 and Gemini-3.5 showed high checklist completeness (98%, 96%) with moderate content fidelity scores (71%, 70%). Perplexity showed checklist coverage (40%) and fidelity (24%). Unsupported content (ChatGPT-5.5 14%, Gemini-3.5 12%; Perplexity not evaluated due to low checklist coverage and summary fidelity) was mainly observed in the areas of limitations and future directions. Discussion/conclusions GAI tools could help organize and generate quick, preliminary outputs, although they may not achieve the same level of rigor, consistency, and quality as a human-generated synthesis.