Assessing readability of explanations and reliability of answers by GPT-3.5 and GPT-4 in non-traumatic spinal cord injury education.
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| Title: | Assessing readability of explanations and reliability of answers by GPT-3.5 and GPT-4 in non-traumatic spinal cord injury education. |
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| Authors: | García-Rudolph, Alejandro1,2,3 alejandropablogarcia@gmail.com, Sanchez-Pinsach, David1,2,3, Wright, Mark Andrew1,2,3, Opisso, Eloy1,2,3, Vidal, Joan1,2,3 |
| Source: | Medical Teacher. Aug2025, Vol. 47 Issue 8, p1336-1343. 8p. |
| Subject Terms: | *Educational tests & measurements, *Evaluation, *Generative artificial intelligence, *Medical education, *Readability (Literary style), *Textbooks, *Certification, *Educational technology, Success, Research evaluation, Spinal cord injuries, Descriptive statistics, Reliability (Personality trait), Chatbots |
| Abstract: | Purpose: Our study aimed to: i) Assess the readability of textbook explanations using established indexes; ii) Compare these with GPT-4's default explanations, ensuring similar word counts for direct comparisons; iii) Evaluate GPT-4's adaptability by simplifying high-complexity explanations; iv) Determine the reliability of GPT-3.5 and GPT-4 in providing accurate answers. Material and methods: We utilized a textbook designed for ABPMR certification. Our analysis covered 50 multiple-choice questions, each with a detailed explanation, focusing on non-traumatic spinal cord injury (NTSCI). Results: Our analysis revealed statistically significant differences in readability scores, with the textbook achieving 14.5 (SD = 2.5) compared to GPT-4's 17.3 (SD = 1.9), indicating that GPT-4's explanations are generally more complex (p < 0.001). Using the Flesch Reading Ease Score, 86% of GPT-4's explanations fell into the 'Very difficult' category, significantly higher than the textbook's 58% (p = 0.006). GPT-4 successfully demonstrated adaptability by reducing the mean readability score of the top-nine most complex explanations, maintaining the word count. Regarding reliability, GPT-3.5 and GPT-4 scored 84% and 96% respectively, with GPT-4 outperforming GPT-3.5 (p = 0.046). Conclusions: Our results confirmed GPT-4's potential in medical education by providing highly accurate yet often complex explanations for NTSCI, which were successfully simplified without losing accuracy. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 186774714 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Assessing readability of explanations and reliability of answers by GPT-3.5 and GPT-4 in non-traumatic spinal cord injury education. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22García-Rudolph%2C+Alejandro%22">García-Rudolph, Alejandro</searchLink><relatesTo>1,2,3</relatesTo><i> alejandropablogarcia@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Sanchez-Pinsach%2C+David%22">Sanchez-Pinsach, David</searchLink><relatesTo>1,2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Wright%2C+Mark+Andrew%22">Wright, Mark Andrew</searchLink><relatesTo>1,2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Opisso%2C+Eloy%22">Opisso, Eloy</searchLink><relatesTo>1,2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Vidal%2C+Joan%22">Vidal, Joan</searchLink><relatesTo>1,2,3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Teacher%22">Medical Teacher</searchLink>. Aug2025, Vol. 47 Issue 8, p1336-1343. 8p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Educational+tests+%26+measurements%22">Educational tests & measurements</searchLink><br />*<searchLink fieldCode="DE" term="%22Evaluation%22">Evaluation</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Medical+education%22">Medical education</searchLink><br />*<searchLink fieldCode="DE" term="%22Readability+%28Literary+style%29%22">Readability (Literary style)</searchLink><br />*<searchLink fieldCode="DE" term="%22Textbooks%22">Textbooks</searchLink><br />*<searchLink fieldCode="DE" term="%22Certification%22">Certification</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink><br /><searchLink fieldCode="DE" term="%22Success%22">Success</searchLink><br /><searchLink fieldCode="DE" term="%22Research+evaluation%22">Research evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Spinal+cord+injuries%22">Spinal cord injuries</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability+%28Personality+trait%29%22">Reliability (Personality trait)</searchLink><br /><searchLink fieldCode="DE" term="%22Chatbots%22">Chatbots</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: Our study aimed to: i) Assess the readability of textbook explanations using established indexes; ii) Compare these with GPT-4's default explanations, ensuring similar word counts for direct comparisons; iii) Evaluate GPT-4's adaptability by simplifying high-complexity explanations; iv) Determine the reliability of GPT-3.5 and GPT-4 in providing accurate answers. Material and methods: We utilized a textbook designed for ABPMR certification. Our analysis covered 50 multiple-choice questions, each with a detailed explanation, focusing on non-traumatic spinal cord injury (NTSCI). Results: Our analysis revealed statistically significant differences in readability scores, with the textbook achieving 14.5 (SD = 2.5) compared to GPT-4's 17.3 (SD = 1.9), indicating that GPT-4's explanations are generally more complex (p < 0.001). Using the Flesch Reading Ease Score, 86% of GPT-4's explanations fell into the 'Very difficult' category, significantly higher than the textbook's 58% (p = 0.006). GPT-4 successfully demonstrated adaptability by reducing the mean readability score of the top-nine most complex explanations, maintaining the word count. Regarding reliability, GPT-3.5 and GPT-4 scored 84% and 96% respectively, with GPT-4 outperforming GPT-3.5 (p = 0.046). Conclusions: Our results confirmed GPT-4's potential in medical education by providing highly accurate yet often complex explanations for NTSCI, which were successfully simplified without losing accuracy. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/0142159X.2024.2430365 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 1336 Subjects: – SubjectFull: Educational tests & measurements Type: general – SubjectFull: Evaluation Type: general – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Medical education Type: general – SubjectFull: Readability (Literary style) Type: general – SubjectFull: Textbooks Type: general – SubjectFull: Certification Type: general – SubjectFull: Educational technology Type: general – SubjectFull: Success Type: general – SubjectFull: Research evaluation Type: general – SubjectFull: Spinal cord injuries Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Reliability (Personality trait) Type: general – SubjectFull: Chatbots Type: general Titles: – TitleFull: Assessing readability of explanations and reliability of answers by GPT-3.5 and GPT-4 in non-traumatic spinal cord injury education. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: García-Rudolph, Alejandro – PersonEntity: Name: NameFull: Sanchez-Pinsach, David – PersonEntity: Name: NameFull: Wright, Mark Andrew – PersonEntity: Name: NameFull: Opisso, Eloy – PersonEntity: Name: NameFull: Vidal, Joan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0142159X Numbering: – Type: volume Value: 47 – Type: issue Value: 8 Titles: – TitleFull: Medical Teacher Type: main |
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