ChatGPT 在简化和改进疫苗接种知情同意书方面的潜在作用:在意大利开展的一项试点研究。

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES
Claudia Cosma, Alessio Radi, Rachele Cattano, Patrizio Zanobini, Guglielmo Bonaccorsi, Chiara Lorini, Marco Del Riccio
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本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential role of ChatGPT in simplifying and improving informed consent forms for vaccination: a pilot study conducted in Italy.

Objectives: Informed consent forms are important for assisting patients in making informed choices regarding medical procedures. Because of their lengthy nature, complexity and specialised terminology, consent forms usually prove challenging for the general public to comprehend. This pilot study aims to use Chat Generative Pretrained Transformer (ChatGPT), a large language model (LLM), to improve the readability and understandability of a consent form for vaccination.

Methods: The study was conducted in Italy, within the Central Tuscany Local Health Unit. Three different consent forms were selected and approved: the standard consent form currently in use (A), a new form totally generated by ChatGPT (B) and a modified version of the standard form created by ChatGPT (C). Healthcare professionals in the vaccination unit were asked to evaluate the consent forms regarding adequacy, comprehensibility and completeness and to give an overall judgement. The Kruskal-Wallis test and Dunn's test were used to evaluate the median scores of the consent forms across these variables.

Results: Consent forms A and C achieved the top scores in every category; consent form B obtained the lowest score. The median scores were 4.0 for adequacy on consent forms A and C and 3.0 on consent form B. Consent forms A and C received high overall judgement ratings with median scores of 4.0, whereas consent form B received a median score of 3.0.

Conclusions: The findings indicate that LLM tools such as ChatGPT could enhance healthcare communication by improving the clarity and accessibility of consent forms, but the best results are seen when these tools are combined with human knowledge and supervision.

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来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
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