长期阿片类药物治疗中对患者担忧的生成人工智能驱动反应的有效性:跨模型评估
Giuliano Lo Bianco1, Christopher L Robinson2, Francesco Paolo D'Angelo3
1Anesthesiology and Pain Department, Foundation G. Giglio Cefalù, 90015 Palermo, Italy.
Biomedicines
|March 28, 2025
概括
像ChatGPT这样的生成人工智能显示出对长期阿片类药物治疗患者的教育有希望,显示出高可靠性和可理解性. 然而,准确性各不相同,特别是在复杂的主题上,这表明需要进一步开发人工智能和临床整合.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 患者教育 患者教育
背景情况:
- 长期治疗慢性疼痛的阿片类药物引起了患者对安全性,疗效和成的担忧.
- 清晰,准确的信息对于患者的理解和治疗坚持至关重要.
- 生成型人工智能为医疗保健机构的患者教育提供了一种新的方法.
研究的目的:
- 评估ChatGPT对患者关于长期阿片类药物治疗的常见问题的答案的可靠性,准确性和可理解性.
- 评估AI作为慢性疼痛管理患者教育工具的潜力.
主要方法:
- 一个专家小组策划了关于长期阿片类药物治疗的13个常见问题.
- 提示GPT-4.0作为一名医生回答问题.
- 疼痛医生和非医疗保健专业人员独立评估了使用利克特尺度的可靠性,准确性和可理解性.
主要成果:
- 聊天GPT响应实现了高可靠性 (5.2/6) 和良好的可理解性 (2.8/3).
- 准确度中等 (2.7/3),在阿片类药物耐受性和依赖性等技术方面表现较差.
- 大多数答案都达到或超过了可靠性和可理解性的预定义值.
结论:
- 像ChatGPT这样的AI工具具有重要的潜力,可以作为长期阿片类药物治疗的补充患者教育资源.
- 在处理高度技术或特定环境的查询方面存在局限性,需要人工智能改进和特定领域的培训.
- 医疗保健专业人员和人工智能开发人员之间的合作开发对于安全有效地整合到慢性疼痛管理中至关重要.
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