Evaluating the influence of prompt formulation on the reliability and repeatability of ChatGPT in implant-supported prostheses
Language models (LLMs) such as ChatGPT are widely available to any dental professional. However, there is limited evidence to evaluate the reliability and reproducibility of ChatGPT-4 in relation to implant-supported prostheses, as well as the impact of prompt design on its responses. This constrains understanding of its application within this specific area of dentistry. The purpose of this study was to evaluate the performance of ChatGPT-4 in generating answers about implant-supported prostheses using different prompts. Thirty questions on implant-supported and implant-retained prostheses were posed, with 30 answers generated per question using general and specific prompts, totaling 1800 answers. Experts assessed reliability (agreement with expert grading) and repeatability (response consistency) using a 3-point Likert scale. General prompts achieved 70.89% reliability, with repeatability ranging from moderate to almost perfect. Specific prompts showed higher performance, with 78.8% reliability and substantial to almost perfect repeatability. The specific prompt significantly improved reliability compared to the general prompt. Despite these promising results, ChatGPT's ability to generate reliable answers on implant-supported prostheses remains limited, highlighting the need for professional oversight. Using specific prompts can enhance its performance. The use of a specific prompt might improve the answer generation performance of ChatGPT.
Authors
- Ana Suárez (ORCID: https://orcid.org/0000-0003-2448-6669)
- Margarita Gómez Sánchez (ORCID: https://orcid.org/0000-0002-8305-6354)
- Yolanda Freire (ORCID: https://orcid.org/0000-0002-0727-777X)
- Víctor Díaz‐Flores García (ORCID: https://orcid.org/0000-0001-6141-0546)
- Israel John Thuissard Vasallo
- Jaime Orejas Pérez (ORCID: https://orcid.org/0000-0001-9756-1709)
- Andrea Santamaría Laorden
- Ignacio Ortiz Collado
Institutions
- Universidad Europea de Madrid (ES)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1371/journal.pone.0323086
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62