Assessing the Suitability of ChatGPT and DeepSeekAI for Parent's Education on Common Pediatric Respiratory Diseases
Year: 2025
Type: article
Abstract: Introduction Parental education on pediatric respiratory illnesses is essential to ensure timely care for children. With the increasing use of artificial intelligence (AI) in health communication, tools such as ChatGPT and DeepSeekAI offer potential for generating accessible and reliable educational material. Methodology A cross-sectional analysis was conducted using AI-generated educational content. Each response was assessed for word and sentence count, average words per sentence, syllables per word, readability (Flesch Reading Ease Score and Grade Level), similarity percentage (QuillBot), and reliability (modified Discern Score). Statistical analysis was performed using independent sample t-tests, with p<0.05 considered significant. Results DeepSeekAI responses were longer (mean word count: 422 vs. 333.75) and included more sentences. However, no statistically significant differences were found in any variable, including readability (Grade Level: 9.22 vs. 9.30; Ease Score: 41.17 vs. 40.97) and reliability (2.25 vs. 2.00). Similarity scores were also comparable between the two tools (36.02 vs 32.1). Conclusion Both ChatGPT and DeepSeekAI generated parent education materials of similar quality, readability, and reliability. The findings of this study suggest that either AI tools can be utilized for developing parental educational content for common pediatric respiratory conditions.
Source: Cureus
DOI: 10.7759/cureus.92434
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414267227