View in EDS HTML Full Text PDF Full Text

Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.

Saved in:
Bibliographic Details
Title: Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.
Authors: Xu, Qi1,2,3 Cookies_white@outlook.com, Wang, Jing2, Chen, Xiaohui4, Wang, Jiale5, Li, Hanzhi1, Wang, Zheng6, Li, Weihan7, Gao, Jinliang7, Chen, Chen6, Gao, Yuwan8
Source: Journal of Medical Systems. 1/17/2025, Vol. 49 Issue 1, p1-10. 10p.
Subjects: Generative artificial intelligence, Patient education, Thyroid gland tumors, Data analysis, Readability (Literary style), Kruskal-Wallis Test, Cancer patients, Misinformation, Chi-squared test, Mann Whitney U Test, Descriptive statistics, Longitudinal method, Statistics, Data analysis software
Abstract: With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like ChatGPT for answers and advice. However, the effectiveness of ChatGPT in educating thyroid cancer patients remains unclear. We designed 50 questions covering key areas of thyroid cancer management and generated corresponding responses under four different prompt strategies. These answers were evaluated based on four dimensions: accuracy, comprehensiveness, human care, and satisfaction. Additionally, the readability of the responses was assessed using the Flesch-Kincaid grade level, Gunning Fog Index, Simple Measure of Gobbledygook, and Fry readability score. We also statistically analyzed the references in the responses generated by ChatGPT. The type of prompt significantly influences the quality of ChatGPT's responses. Notably, the "statistics and references" prompt yields the highest quality outcomes. Prompts tailored to a "6th-grade level" generated the most easily understandable text, whereas responses without specific prompts were the most complex. Additionally, the "statistics and references" prompt produced the longest responses while the "6th-grade level" prompt resulted in the shortest. Notably, 87.84% of citations referenced published medical literature, but 12.82% contained misinformation or errors. ChatGPT demonstrates considerable potential for enhancing the readability and quality of thyroid cancer patient education materials. By adjusting prompt strategies, ChatGPT can generate responses that cater to diverse patient needs, improving their understanding and management of the disease. However, AI-generated content must be carefully supervised to ensure that the information it provides is accurate. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Medical Systems is the property of Springer Nature 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: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 183076940
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Xu%2C+Qi%22">Xu, Qi</searchLink><relatesTo>1,2,3</relatesTo><i> Cookies_white@outlook.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jing%22">Wang, Jing</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Xiaohui%22">Chen, Xiaohui</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jiale%22">Wang, Jiale</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Li%2C+Hanzhi%22">Li, Hanzhi</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wang%2C+Zheng%22">Wang, Zheng</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Li%2C+Weihan%22">Li, Weihan</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Gao%2C+Jinliang%22">Gao, Jinliang</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Chen%22">Chen, Chen</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Gao%2C+Yuwan%22">Gao, Yuwan</searchLink><relatesTo>8</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Medical+Systems%22">Journal of Medical Systems</searchLink>. 1/17/2025, Vol. 49 Issue 1, p1-10. 10p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+education%22">Patient education</searchLink><br /><searchLink fieldCode="DE" term="%22Thyroid+gland+tumors%22">Thyroid gland tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Readability+%28Literary+style%29%22">Readability (Literary style)</searchLink><br /><searchLink fieldCode="DE" term="%22Kruskal-Wallis+Test%22">Kruskal-Wallis Test</searchLink><br /><searchLink fieldCode="DE" term="%22Cancer+patients%22">Cancer patients</searchLink><br /><searchLink fieldCode="DE" term="%22Misinformation%22">Misinformation</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Mann+Whitney+U+Test%22">Mann Whitney U Test</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like ChatGPT for answers and advice. However, the effectiveness of ChatGPT in educating thyroid cancer patients remains unclear. We designed 50 questions covering key areas of thyroid cancer management and generated corresponding responses under four different prompt strategies. These answers were evaluated based on four dimensions: accuracy, comprehensiveness, human care, and satisfaction. Additionally, the readability of the responses was assessed using the Flesch-Kincaid grade level, Gunning Fog Index, Simple Measure of Gobbledygook, and Fry readability score. We also statistically analyzed the references in the responses generated by ChatGPT. The type of prompt significantly influences the quality of ChatGPT's responses. Notably, the "statistics and references" prompt yields the highest quality outcomes. Prompts tailored to a "6th-grade level" generated the most easily understandable text, whereas responses without specific prompts were the most complex. Additionally, the "statistics and references" prompt produced the longest responses while the "6th-grade level" prompt resulted in the shortest. Notably, 87.84% of citations referenced published medical literature, but 12.82% contained misinformation or errors. ChatGPT demonstrates considerable potential for enhancing the readability and quality of thyroid cancer patient education materials. By adjusting prompt strategies, ChatGPT can generate responses that cater to diverse patient needs, improving their understanding and management of the disease. However, AI-generated content must be carefully supervised to ensure that the information it provides is accurate. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Medical Systems is the property of Springer Nature 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=183076940
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10916-024-02129-0
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 1
    Subjects:
      – SubjectFull: Generative artificial intelligence
        Type: general
      – SubjectFull: Patient education
        Type: general
      – SubjectFull: Thyroid gland tumors
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Readability (Literary style)
        Type: general
      – SubjectFull: Kruskal-Wallis Test
        Type: general
      – SubjectFull: Cancer patients
        Type: general
      – SubjectFull: Misinformation
        Type: general
      – SubjectFull: Chi-squared test
        Type: general
      – SubjectFull: Mann Whitney U Test
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Longitudinal method
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Data analysis software
        Type: general
    Titles:
      – TitleFull: Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Xu, Qi
      – PersonEntity:
          Name:
            NameFull: Wang, Jing
      – PersonEntity:
          Name:
            NameFull: Chen, Xiaohui
      – PersonEntity:
          Name:
            NameFull: Wang, Jiale
      – PersonEntity:
          Name:
            NameFull: Li, Hanzhi
      – PersonEntity:
          Name:
            NameFull: Wang, Zheng
      – PersonEntity:
          Name:
            NameFull: Li, Weihan
      – PersonEntity:
          Name:
            NameFull: Gao, Jinliang
      – PersonEntity:
          Name:
            NameFull: Chen, Chen
      – PersonEntity:
          Name:
            NameFull: Gao, Yuwan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 17
              M: 01
              Text: 1/17/2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 01485598
          Numbering:
            – Type: volume
              Value: 49
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Journal of Medical Systems
              Type: main
ResultId 1