Scholarlink

<p>The informed consent (IC) process is essential in genetic testing, yet IC materials are often difficult to read and understand, influencing patients’ decision-making. Large language models may improve the accessibility and clarity of these materials. We used GPT-4 to generate IC materials for Non-Invasive Prenatal Testing (NIPT) and hereditary breast and ovarian cancer testing (BRCA) in English, German, Italian, and Greek, using zero-shot prompting and retrieval-augmented generation. Healthcare providers evaluated GPT-4-generated and human-generated materials using a previously published framework. GPT-4 performed well on structured components, such as explaining the purpose and benefits of testing, but struggled with nuanced ethical and contextual content. Respondents overall preferred human-written materials, underscoring limitations in current GPT-4-generated material for health communication in the genetic testing context. GPT-4’s performance in German, Italian and Greek was generally weaker than in English, highlighting potential language-specific challenges in GPT-4-generated IC content.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evaluating GPT-4’s ability to generate informed consent material for genetic testing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月3日

查看全文
  • Eirini Petrou,
  • Kelly E. Ormond,
  • Dominik Stammbach,
  • Elliott Ash,
  • Oliver Buchholz,
  • Effy Vayena

摘要

The informed consent (IC) process is essential in genetic testing, yet IC materials are often difficult to read and understand, influencing patients’ decision-making. Large language models may improve the accessibility and clarity of these materials. We used GPT-4 to generate IC materials for Non-Invasive Prenatal Testing (NIPT) and hereditary breast and ovarian cancer testing (BRCA) in English, German, Italian, and Greek, using zero-shot prompting and retrieval-augmented generation. Healthcare providers evaluated GPT-4-generated and human-generated materials using a previously published framework. GPT-4 performed well on structured components, such as explaining the purpose and benefits of testing, but struggled with nuanced ethical and contextual content. Respondents overall preferred human-written materials, underscoring limitations in current GPT-4-generated material for health communication in the genetic testing context. GPT-4’s performance in German, Italian and Greek was generally weaker than in English, highlighting potential language-specific challenges in GPT-4-generated IC content.