Comparison of different artificial intelligence tools’ answers to questions related to early intervention: ChatGPT versus Gemini
Revista da Associacao Medica Brasileira, cilt.72, sa.3, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 72 Sayı: 3
- Basım Tarihi: 2026
- Doi Numarası: 10.1590/1806-9282.20251434
- Dergi Adı: Revista da Associacao Medica Brasileira
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
- Anahtar Kelimeler: Artificial intelligence, Early intervention, Health communication, Readability
- Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet
Özet
OBJECTIVE: The aim of this study was to assess the quality and readability of ChatGPT and Gemini’s responses to frequently asked questions about early intervention for individuals with at-risk infants. METHODS: Ten frequently asked questions about early intervention were selected by three researchers (a child development specialist, a physiotherapist, and a midwife) from a list generated by ChatGPT and Gemini. Questions were sent to ChatGPT version 4.0 and Gemini 1.5, and initial responses were recorded without follow-up queries. Ten independent experts (two special education specialists, two child development specialists, two physiotherapists, two midwives, and two pediatricians) The quality of ChatGPT and Gemini’s responses was assessed using a four-grade rating system. Readability levels were analyzed using the Flesch-Kincaid Grade Level through WordCalc software. RESULTS: One of the answers given by ChatGPT was of higher quality than Gemini (p=0.025), while one answer given by Gemini was of higher quality than ChatGPT (p=0.033). The answers to the other questions were of similar quality, with Gemini having a lower level. CONCLUSION: This study compares the quality and readability of the answers given by artificial intelligence-based language models to demonstrate their potential to appeal to different user groups. While the models generally provided answers of similar quality, quantitative differences in readability were observed, suggesting potential suitability for different audiences. These findings contribute to understanding the role of AI tools in health communication.