## 4 Discussion
### Comparison with Previous Studies  
#### 4.1.1 Accuracy  
Several studies have evaluated the accuracy of responses generated by various LLM-based chatbots in relation to dental trauma, often using the IADT guidelines as a reference. In a study conducted by [PERSON] et al. [15], ChatGPT and Google Bard were assessed using 25 dichotomous questions on dental trauma, and both chatbots demonstrated an overall accuracy rate of 57.5% across 4500 responses. In another study by [PERSON] et al. [19],  
Figure 5: Correlation heatmap illustrating the relationships among accuracy, completeness, response time, and readability scores based on [PERSON]’s correlation coefficients (FRES: Flesch–Kincaid Reading Ease Score, FKGL: Flesch–Kincaid Grade Level, GFI: Gunning Fog Index, SMOG: Simple Measure of Gobbledygook Index, CLI: Coleman–Liau Index).  
the validity and reliability of chatbot-generated answers to frequently asked questions about dental trauma were evaluated across four chatbots (ChatGPT-3.5, Google Gemini, Bing, and Claude), with Claude significantly outperforming the others in both reliability and validity. Another investigation compared five models (ChatGPT-4, ChatGPT-3.5, two versions of Microsoft Copilot, and Google Gemini) using multiple-choice, fill-in-the-blank, and dichotomous formats [20]. Although no statistically significant differences were found among the models, their accuracy rates ranged from 46.7% to 76.7%, with ChatGPT versions and Gemini models performing better on multiple-choice and fill-in-the-blank formats than on dichotomous questions [20]. In a separate study, ChatGPT-3.5 was tested using 45 self-generated questions related to general dental trauma, intrusion, and avulsion and was reported to produce highly reliable responses [27]. In a study by [PERSON] et al. [28], ChatGPT-3.5, ChatGPT-4, and Gemini were compared in their responses to dental trauma questions, with ChatGPT-4 and Gemini demonstrating significantly higher accuracy than ChatGPT-3.5. In the present study, four different chatbots were evaluated based on their responses to 25 open-ended questions on TDIs in the primary dentition, with assessments conducted by independent pediatric dentists in accordance with the IADT guidelines. ChatGPT-4o, DeepSeek, and Claude 3.7 produced significantly more accurate responses than Gemini Advanced. Although there were no statistically significant differences in accuracy among the top three models, ChatGPT-4o achieved the highest overall accuracy. Although the differences in mean accuracy scores between the top-performing models may seem numerically small, they can still carry clinical significance--particularly in pediatric dental trauma cases. Even slight improvements in accuracy may help reduce the risk of misinformation or misinterpretation, especially when such tools are used by non-specialists, such as parents or general practitioners. Furthermore, when these tools are used repeatedly over time, small gains in accuracy may accumulate to support better clinical decisions and more effective patient education. Therefore, while statistical significance does not necessarily imply clinical importance, small but consistent differences in accuracy should not be underestimated. These findings are consistent with prior research indicating that the accuracy of chatbot-generated content can be influenced by factors such as question format, content type, and evaluation methodology. As such, the relative performance of chatbots in dental contexts appears to be context-dependent and may vary across studies.