Evaluation of Chatbot Responses to Text-Based Multiple-Choice Questions in Prosthodontic and Restorative Dentistry

<b>Background/Objectives</b>: This study aims to evaluate the response accuracy and quality of three AI chatbots-GPT-4.0, Claude-2, and Llama-2-in answering multiple-choice questions in prosthodontic and restorative dentistry. <b>Methods</b>: A total of 191 text-based multiple-choice questions were selected from the prosthodontic and restorative dentistry sections of the United States Integrated National Board Dental Examination (INBDE) (n = 80) and the United Kingdom Overseas Registration Examination (ORE) (<i>n</i> = 111). These questions were inputted into the chatbots, and the AI-generated answers were compared with the official answer keys to determine their accuracy. Additionally, two dental specialists independently evaluated the rationales accompanying each chatbot response for accuracy, relevance, and comprehensiveness, categorizing them into four distinct ratings. Chi-square and post hoc Z-tests with Bonferroni adjustment were used to analyze the responses. The inter-rater reliability for evaluating the quality of the rationale ratings among specialists was assessed using Cohen's Kappa (κ). <b>Results</b>: GPT-4.0 (65.4%; <i>n</i> = 125/191) demonstrated a significantly higher proportion of correctly answered multiple-choice questions when compared to Claude-2 (41.9%; <i>n</i> = 80/191) (<i>p</i> < 0.017) and Llama-2 (26.2%; <i>n</i> = 50/191) (<i>p</i> < 0.017). Significant differences were observed in the answer accuracy among all of the chatbots (<i>p</i> < 0.001). In terms of the rationale quality, GPT-4.0 (58.1%; <i>n</i> = 111/191) had a significantly higher proportion of "Correct Answer, Correct Rationale" than Claude-2 (37.2%; <i>n</i> = 71/191) (<i>p</i> < 0.017) and Llama-2 (24.1%; <i>n</i> = 46/191) (<i>p</i> < 0.017). Significant differences were observed in the rationale quality among all of the chatbots (<i>p</i> < 0.001). The inter-rater reliability was very high (κ = 0.83). <b>Conclusions</b>: GPT-4.0 demonstrated the highest accuracy and quality of reasoning in responding to prosthodontic and restorative dentistry questions. This underscores the varying efficacy of AI chatbots within specialized dental contexts.

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Publication Details

Journal
Dentistry Journal
Published
2025-06-21
DOI
https://doi.org/10.3390/dj13070279
Citations
19
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
47.14
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article

Evaluation of Chatbot Responses to Text-Based Multiple-Choice Questions in Prosthodontic and Restorative Dentistry

Ollie Yiru Yu, Walter Yu Hang Lam, D Wang, J.J. Wang et al.
19 citations
Dentistry Journal
AI in Service Interactions
47.14
article

Evaluation of Chatbot Responses to Text-Based Multiple-Choice Questions in Prosthodontic and Restorative Dentistry

Ollie Yiru Yu, Walter Yu Hang Lam, D Wang, J.J. Wang, Tai-Chiu Hsung, Reinhard Chun Wang Chau, Khaing Myat Thu, Manuel Wing Ho Man
article en
19 citations

Abstract

<b>Background/Objectives</b>: This study aims to evaluate the response accuracy and quality of three AI chatbots-GPT-4.0, Claude-2, and Llama-2-in answering multiple-choice questions in prosthodontic and restorative dentistry. <b>Methods</b>: A total of 191 text-based multiple-choice questions were selected from the prosthodontic and restorative dentistry sections of the United States Integrated National Board Dental Examination (INBDE) (n = 80) and the United Kingdom Overseas Registration Examination (ORE) (<i>n</i> = 111). These questions were inputted into the chatbots, and the AI-generated answers were compared with the official answer keys to determine their accuracy. Additionally, two dental specialists independently evaluated the rationales accompanying each chatbot response for accuracy, relevance, and comprehensiveness, categorizing them into four distinct ratings. Chi-square and post hoc Z-tests with Bonferroni adjustment were used to analyze the responses. The inter-rater reliability for evaluating the quality of the rationale ratings among specialists was assessed using Cohen's Kappa (κ). <b>Results</b>: GPT-4.0 (65.4%; <i>n</i> = 125/191) demonstrated a significantly higher proportion of correctly answered multiple-choice questions when compared to Claude-2 (41.9%; <i>n</i> = 80/191) (<i>p</i> < 0.017) and Llama-2 (26.2%; <i>n</i> = 50/191) (<i>p</i> < 0.017). Significant differences were observed in the answer accuracy among all of the chatbots (<i>p</i> < 0.001). In terms of the rationale quality, GPT-4.0 (58.1%; <i>n</i> = 111/191) had a significantly higher proportion of "Correct Answer, Correct Rationale" than Claude-2 (37.2%; <i>n</i> = 71/191) (<i>p</i> < 0.017) and Llama-2 (24.1%; <i>n</i> = 46/191) (<i>p</i> < 0.017). Significant differences were observed in the rationale quality among all of the chatbots (<i>p</i> < 0.001). The inter-rater reliability was very high (κ = 0.83). <b>Conclusions</b>: GPT-4.0 demonstrated the highest accuracy and quality of reasoning in responding to prosthodontic and restorative dentistry questions. This underscores the varying efficacy of AI chatbots within specialized dental contexts.

Dentistry JournalVol. 13(7)
Hong Kong Chu Hai College (HK), University of Hong Kong (HK)
Openalex Percentile: Top 0%
AI in Service Interactions
47.14
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