Using ChatGPT for Writing Articles for Patients' Education for Dermatological Diseases: A Pilot Study.
Using ChatGPT for Writing Articles for Patients' Education for Dermatological Diseases: A Pilot Study.
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DOI：
10.4103/idoj.idoj_72_23
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发表时间：
2023-07
影响因子：
1.7
通讯作者：
Podder I
中科院分区：
文献类型：
--
作者：
Mondal H;Mondal S;Podder I
病人教育是病人了解疾病和适当处理病情的重要策略。医生和学者经常为他们的病人制作定制的教育材料。一个基于人工智能（AI）的作家可以帮助他们写一篇文章。Chat Generative Pre-Trained Transformer（ChatGPT）是由OpenAI（openai.com）开发的会话语言模型。该模型可以生成类似人类的响应。我们的目的是评估ChatGPT生成的文本在患者教育中的适用性。我们要求ChatGPT列出常见的皮肤病。它提供了14种疾病的清单。我们使用疾病名称与具有疾病特定输入的应用程序匡威（例如，写一个关于痤疮的病人教育指南）。通过软件复制文本以检查字数、可读性和文本相似性。文本的准确性由皮肤科医生根据观察学习成果（SOLO）分类结构进行检查。对于易读性评分，我们将观察值与30分进行了比较。对于相似性指数，我们将观察值与15%进行比较，并采用单样本t检验进行检验。ChatGPT为皮肤病患者教育指南生成了一段377.43 ± 60.85字的文本。文本阅读容易度平均值为46.94 ± 8.23（P < 0.0001），表明该水平的文本容易被高中生和大学新生理解。文本相似性指数（27.07 ± 11.46%，P = 0.002）高于15%的预期限值。根据SOLO分类法，文本具有“关系”准确性水平。在目前的形式下，ChatGPT可以生成一段文本，用于患者的教育目的，易于理解。但是，相似性指数很高。因此，医生在使用ChatGPT生成的文本时应谨慎，并且在使用之前必须检查文本相似性。
Patients’ education is a vital strategy for understanding a disease by patients and proper management of the condition. Physicians and academicians frequently make customized education materials for their patients. An artificial intelligence (AI)-based writer can help them write an article. Chat Generative Pre-Trained Transformer (ChatGPT) is a conversational language model developed by OpenAI (openai.com). The model can generate human-like responses. We aimed to evaluate the generated text from ChatGPT for its suitability in patients’ education. We asked the ChatGPT to list common dermatological diseases. It provided a list of 14 diseases. We used the disease names to converse with the application with disease-specific input (e.g., write a patient education guide on acne). The text was copied for checking the number of words, readability, and text similarity by software. The text’s accuracy was checked by a dermatologist following the structure of observed learning outcomes (SOLO) taxonomy. For the readability ease score, we compared the observed value with a score of 30. For the similarity index, we compared the observed value with 15% and tested it with a one-sample t-test. The ChatGPT generated a paragraph of text of 377.43 ± 60.85 words for a patient education guide on skin diseases. The average text reading ease score was 46.94 ± 8.23 (P < 0.0001), and it indicates that this level of text can easily be understood by a high-school student to a newly joined college student. The text similarity index was higher (27.07 ± 11.46%, P = 0.002) than the expected limit of 15%. The text had a “relational” level of accuracy according to the SOLO taxonomy. In its current form, ChatGPT can generate a paragraph of text for patients’ educational purposes that can be easily understood. However, the similarity index is high. Hence, doctors should be cautious when using the text generated by ChatGPT and must check for text similarity before using it.