Augmenting research consent: should large language models (LLMs) be used for informed consent to clinical research? DOI Creative Commons
J.W.A. Allen, G. Owen Schaefer, Sebastian Porsdam Mann

et al.

Research Ethics, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 8, 2024

The integration of artificial intelligence (AI), particularly large language models (LLMs) like OpenAI’s ChatGPT, into clinical research could significantly enhance the informed consent process. This paper critically examines ethical implications employing LLMs to facilitate in research. offer considerable benefits, such as improving participant understanding and engagement, broadening participants’ access relevant information for increasing efficiency procedures. However, these theoretical advantages are accompanied by risks, including potential misinformation, coercion challenges accountability. Given complex nature research, which involves both written documentation (in form sheets forms) in-person conversations with a researcher, use raises significant concerns about adequacy existing regulatory frameworks. Institutional Review Boards (IRBs) will need consider substantial reforms accommodate LLM-based processes. We explore five LLM implementation, ranging from supplementary roles complete replacements current processes, recommendations researchers IRBs navigate landscape. Thus, we aim provide practical introduction settings considering factors understanding, accuracy, human oversight types applications consent.

Language: Английский

Advancing health equity: evaluating AI translations of kidney donor information for Spanish speakers DOI Creative Commons
Oscar A. Garcia Valencia, Charat Thongprayoon, Caroline C. Jadlowiec

et al.

Frontiers in Public Health, Journal Year: 2025, Volume and Issue: 13

Published: Jan. 27, 2025

Background Health equity and access to essential medical information remain significant challenges, especially for the Spanish-speaking Hispanic population, which faces barriers in accessing living kidney donation opportunities. ChatGPT, an AI language model with sophisticated natural processing capabilities, has been identified as a promising tool translating critical health into Spanish. This study aims assess ChatGPT’s translation efficacy ensure provided is accurate culturally relevant. Methods T his utilized ChatGPT versions 3.5 4.0 translate 27 frequently asked questions (FAQs) from English Spanish, sourced Donate Life America’s website. The translated content was reviewed by native nephrologists using standard rubric scale (1–5). assessment focused on linguistic accuracy cultural sensitivity, emphasizing retention of original message, appropriate vocabulary grammar, relevance. Results mean scores were 4.89 ± 0.32 GPT-3.5 5.00 0.00 GPT-4.0 ( p = 0.08). percentage excellent-quality translations (score 5) 89% 100% 0.24). sensitivity both 1.00). Similarly, achieved cases Conclusion demonstrates strong potential enhance improving patients’ LKD through sensitive translations. These findings highlight role mitigating healthcare disparities underscore need integrating AI-driven tools systems. Future efforts should focus developing accessible platforms establishing guidelines maximize AI’s impact equitable delivery patient education.

Language: Английский

Citations

0
Large language models for surgical informed consent: an ethical perspective on simulated empathy DOI Creative Commons
Pranab Rudra, Wolf‐Tilo Balke, Tim Kacprowski

et al.

Journal of Medical Ethics, Journal Year: 2025, Volume and Issue: unknown, P. jme - 110652

Published: March 12, 2025

Informed consent in surgical settings requires not only the accurate communication of medical information but also establishment trust through empathic engagement. The use large language models (LLMs) offers a novel opportunity to enhance informed process by combining advanced retrieval capabilities with simulated emotional responsiveness. However, ethical implications empathy raise concerns about patient autonomy, and transparency. This paper examines challenges consent, potential benefits limitations digital tools such as LLMs empathy. We distinguish between active empathy, which carries risk creating misleading illusion connection passive focuses on recognising signalling distress cues, fear or uncertainty, rather than attempting simulate genuine argue that should be limited latter, cues alerting healthcare providers anxiety. approach preserves authenticity human while leveraging analytical strengths assist surgeons addressing concerns. highlights how can ethically without undermining relational integrity essential patient-centred care. By maintaining transparency respecting irreplaceable role serve valuable support, replace, consent.

Language: Английский

Citations

0
Augmenting research consent: should large language models (LLMs) be used for informed consent to clinical research? DOI Creative Commons
J.W.A. Allen, G. Owen Schaefer, Sebastian Porsdam Mann

et al.

Research Ethics, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 8, 2024

The integration of artificial intelligence (AI), particularly large language models (LLMs) like OpenAI’s ChatGPT, into clinical research could significantly enhance the informed consent process. This paper critically examines ethical implications employing LLMs to facilitate in research. offer considerable benefits, such as improving participant understanding and engagement, broadening participants’ access relevant information for increasing efficiency procedures. However, these theoretical advantages are accompanied by risks, including potential misinformation, coercion challenges accountability. Given complex nature research, which involves both written documentation (in form sheets forms) in-person conversations with a researcher, use raises significant concerns about adequacy existing regulatory frameworks. Institutional Review Boards (IRBs) will need consider substantial reforms accommodate LLM-based processes. We explore five LLM implementation, ranging from supplementary roles complete replacements current processes, recommendations researchers IRBs navigate landscape. Thus, we aim provide practical introduction settings considering factors understanding, accuracy, human oversight types applications consent.

Language: Английский

Citations

1