Comparison of ChatGPT-5 and DeepSeek V3 for Artificial Intelligence-Assisted Patient Education in Foot and Ankle Disorders
- 1Department of Orthopedics and Traumatology, Eskisehir City Hospital, 26080 Eskisehir, Turkey
- 2Department of Orthopedics and Traumatology, Cekirge State Hospital, 16090 Bursa, Turkey
- 3Department of Orthopedics and Traumatology, Ordu University Training and Research Hospital, 52200 Ordu, Turkey
Abstract
BACKGROUND: This study aims to compare the quality, reliability, and readability of information provided by artificial intelligence-based language models, ChatGPT-5 and DeepSeek V3, regarding foot and ankle disorders. METHODS: The quality, reliability, and readability of the texts generated by both AI models were analyzed using DISCERN, the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P), the Global Quality Score (GQS), and the CLEAR scoring system. DISCERN was used to assess information reliability, PEMAT-P to evaluate understandability and actionability, GQS to assess overall quality, and CLEAR to evaluate content quality and accuracy. Standardized questions were asked to both models for 35 different foot and ankle disorders, and the generated texts were evaluated by two independent orthopedic specialists using a blinded method. Readability analysis was performed using word count, the Flesch-Kincaid Grade Level (FKGL; required reading level), and the Flesch Reading Ease (FRE; ease of readability) scoring systems. RESULTS: < 0.05), indicating that ChatGPT-5 provides more reliable, comprehensive, and higher-quality information. DeepSeek V3 demonstrated better readability, producing simpler and more understandable content, as reflected in its lower FKGL score and higher FRE score. CONCLUSIONS: While ChatGPT-5 delivers more detailed and reliable health information, DeepSeek V3 offers simpler and more readable texts. Both models have distinct advantages for patient education. Future research should assess the impact of AI-generated health information on patient decision-making and its clinical application potential.
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BibTeX
@article{karagoz2026comparison,
title = {{Comparison of ChatGPT-5 and DeepSeek V3 for Artificial Intelligence-Assisted Patient Education in Foot and Ankle Disorders}},
author = {Bekir Karagöz and Hünkar Çağdaş Bayrak and Tolga Keçeci},
journal = {Journal of the American Podiatric Medical Association},
year = {2026},
month = may,
doi = {10.3390/japma116030033},
url = {https://doi.org/10.3390/japma116030033},
note = {CC BY},
}
RIS
TY - JOUR
TI - Comparison of ChatGPT-5 and DeepSeek V3 for Artificial Intelligence-Assisted Patient Education in Foot and Ankle Disorders
AU - Bekir Karagöz
AU - Hünkar Çağdaş Bayrak
AU - Tolga Keçeci
PY - 2026
DA - 2026/05/21
JO - Journal of the American Podiatric Medical Association
DO - 10.3390/japma116030033
UR - https://doi.org/10.3390/japma116030033
AB - BACKGROUND: This study aims to compare the quality, reliability, and readability of information provided by artificial intelligence-based language models, ChatGPT-5 and DeepSeek V3, regarding foot and ankle disorders. METHODS: The quality, reliability, and readability of the texts generated by both AI models were analyzed using DISCERN, the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P), the Global Quality Score (GQS), and the CLEAR scoring system. DISCERN was used to assess information reliability, PEMAT-P to evaluate understandability and actionability, GQS to assess overall quality, and CLEAR to evaluate content quality and accuracy. Standardized questions were asked to both models for 35 different foot and ankle disorders, and the generated texts were evaluated by two independent orthopedic specialists using a blinded method. Readability analysis was performed using word count, the Flesch-Kincaid Grade Level (FKGL; required reading level), and the Flesch Reading Ease (FRE; ease of readability) scoring systems. RESULTS: < 0.05), indicating that ChatGPT-5 provides more reliable, comprehensive, and higher-quality information. DeepSeek V3 demonstrated better readability, producing simpler and more understandable content, as reflected in its lower FKGL score and higher FRE score. CONCLUSIONS: While ChatGPT-5 delivers more detailed and reliable health information, DeepSeek V3 offers simpler and more readable texts. Both models have distinct advantages for patient education. Future research should assess the impact of AI-generated health information on patient decision-making and its clinical application potential.
SN - 1930-8264
SN - 8750-7315
ER -