Can a Large Language Model Effectively Answer Parents’ Questions About Children’s Oral Health?

Résumé fourni par la source

Aim: This study aimed to evaluate the readability, quality, and temporal consistency of Turkish responses generated by ChatGPT to frequently asked questions in pediatric dentistry. Materials and Methods:Twenty open-ended questions were adapted from the frequently asked questions published on the American Academy of Pediatric Dentistry parent information page.Each question was submitted to ChatGPT (GPT-4, OpenAI, USA) in Turkish over seven consecutive days, three times per day, using a new chat session for each interaction, standardized prompts and default system settings.A total of 420 responses were analyzed.Readability was assessed using both the Ateşman and Çetinkaya-Uzun readability formulas, while response quality was evaluated using the Global Quality Score (GQS).Inter-day and intra-day comparisons were performed using repeated-measures ANOVA or Friedman tests according to the data distribution.Intraclass Correlation Coefficient (ICC) analysis was used to evaluate temporal consistency (α=0.05).Results: A significant intra-day variability in the readability scores was observed during the first four days for the Ateşman and Çetinkaya-Uzun formulas (p<0.05),whereas no significant differences were identified during Days 5-7.Between-day comparisons revealed statistically significant variations in readability scores for both formulations (p<0.001).Ateşman's scores were found to correspond to "moderate difficulty" and "easy" readability levels, while Çetinkaya-Uzun's scores indicated an "instructional reading level".By contrast, no significant intra-day or between-day differences were observed in the GQS scores (p=0.650), and overall quality scores remained consistently high throughout the study period.The ICC analyses demonstrated good-to-excellent consistency for readability and GQS measurements, with overall ICC values ranging between 0.906 and 0.961. Conclusion:The Turkish responses generated by ChatGPT to frequently asked questions in pediatric dentistry demonstrated moderate readability, high information quality, and good-to-excellent temporal consistency.However, due to the variability in readability scores across repeated assessments and over time, Large Language Models (LLMS) may serve as supportive tools for patient and parent education, however, human oversight remains necessary for the interpretation and clinical use of LLM-generated health information.

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