How Correct is AI for Infant Safe Sleep Advice? Evaluating Accuracy of ChatGPT, Gemini, and Claude Against AAP Guidelines.

Objective

Since the 1994 "Back to Sleep" campaign, pediatricians have promoted evidence-based infant safe sleep practices to reduce sleep-related infant deaths. However, caregivers increasingly seek guidance online. We sought to determine the accuracy of large language model (LLM) responses to caregiver questions about infant safe sleep, compared with the American Academy of Pediatrics' (AAP) 2022 recommendations.

Design

Nine caregiver questions adapted from Reddit New Parents forum were mapped to core AAP safe sleep topics. Each was entered into three LLMs: ChatGPT 5, Gemini 2.5 Flash, and Claude Sonnet 4.5, three times within the same day to assess stability. Three reviewers scored responses on a 0-2 scale for accuracy (primary outcome), completeness, and empathy. Stability reflected similarity across repeated responses. Readability was calculated using the Flesch-Kincaid grade level. Mean scores were compared using descriptive statistics, analysis of variance, and post hoc testing.

Results

Mean accuracy varied significantly across models. Gemini had the highest accuracy score (mean 1.85), followed by Claude (1.44), and ChatGPT (1.30). Gemini was significantly more accurate than ChatGPT (p=0.01). All models scored high in empathy (2). There were no significant differences in completeness and stability between models. ChatGPT had the lowest average readability, with all models' reading levels between grades seven to nine (7.64 vs 9.15 vs 8.82, p=0.01). Direct guideline questions yielded higher accuracy than nuanced questions.

Conclusion

LLMs offer inconsistently accurate but empathetic infant safe sleep advice with frequent deviations from AAP recommendations. Pediatric oversight and collaboration with technology developers are essential to ensure safe, evidence-based information for families.