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

IF 3.5 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Systems Pub Date : 2025-01-17 DOI:10.1007/s10916-024-02129-0
Qi Xu, Jing Wang, Xiaohui Chen, Jiale Wang, Hanzhi Li, Zheng Wang, Weihan Li, Jinliang Gao, Chen Chen, Yuwan Gao
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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.

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评估ChatGPT提示策略在加强甲状腺癌患者教育中的效果:一项前瞻性研究。
随着人工智能平台的兴起,患者越来越多地使用它们来获取信息,依靠ChatGPT等先进的语言模型来获得答案和建议。然而,ChatGPT在甲状腺癌患者教育中的有效性尚不清楚。我们设计了50个问题,涵盖甲状腺癌管理的关键领域,并在四种不同的提示策略下产生相应的回答。这些答案是基于四个方面进行评估的:准确性、全面性、人性化和满意度。此外,使用Flesch-Kincaid等级水平、Gunning Fog指数、Simple Measure of Gobbledygook和Fry可读性评分来评估回答的可读性。我们还对ChatGPT生成的响应中的引用进行了统计分析。提示的类型显著影响ChatGPT回复的质量。值得注意的是,“统计和参考”提示产生了最高质量的结果。针对“六年级水平”量身定制的提示生成了最容易理解的文本,而没有特定提示的回答则是最复杂的。此外,“统计和参考资料”提示产生了最长的回答,而“六年级水平”提示产生了最短的回答。值得注意的是,87.84%的引文引用了已发表的医学文献,但12.82%的引文包含错误信息或错误。ChatGPT在提高甲状腺癌患者教育材料的可读性和质量方面显示出相当大的潜力。通过调整及时的策略,ChatGPT可以产生满足不同患者需求的反应,提高他们对疾病的理解和管理。然而,人工智能生成的内容必须仔细监督,以确保其提供的信息是准确的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Medical Systems
Journal of Medical Systems 医学-卫生保健
CiteScore
11.60
自引率
1.90%
发文量
83
审稿时长
4.8 months
期刊介绍: Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician''s office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.
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