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Accepted for/Published in: JMIR Dermatology

Date Submitted: Jun 21, 2023
Open Peer Review Period: Jun 21, 2023 - Aug 16, 2023
Date Accepted: Feb 6, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Readability and Health Literacy Scores for ChatGPT-Generated Dermatology Public Education Materials: Cross-Sectional Analysis of Sunscreen and Melanoma Questions

Roster K, Kann RB, Farabi B, Gronbeck C, Brownstone N, Lipner SR

Readability and Health Literacy Scores for ChatGPT-Generated Dermatology Public Education Materials: Cross-Sectional Analysis of Sunscreen and Melanoma Questions

JMIR Dermatol 2024;7:e50163

DOI: 10.2196/50163

PMID: 38446502

PMCID: 10955394

ChatGPT Can Be Used to Generate Dermatology Public Educational Materials with Improved Readability and Health Literacy Scores: A Cross Sectional Analysis of Sunscreen and Melanoma Questions

  • Katie Roster; 
  • Rebecca B. Kann; 
  • Banu Farabi; 
  • Christian Gronbeck; 
  • Nicholas Brownstone; 
  • Shari R. Lipner

ABSTRACT

ChatGPT, an OpenAI language model, presents a potential opportunity to improve health literacy by generating accessible and understandable health information. We assessed the readability and health literacy of dermatology health information generated by ChatGPT compared to public educational dermatology resources from the American Academy of Dermatology Association's (AAD) website. Overall, we found that that readability of dermatology health information is often inadequate and demonstrate that ChatGPT may enhance readability and accessibility of dermatology public educational materials.


 Citation

Please cite as:

Roster K, Kann RB, Farabi B, Gronbeck C, Brownstone N, Lipner SR

Readability and Health Literacy Scores for ChatGPT-Generated Dermatology Public Education Materials: Cross-Sectional Analysis of Sunscreen and Melanoma Questions

JMIR Dermatol 2024;7:e50163

DOI: 10.2196/50163

PMID: 38446502

PMCID: 10955394

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.