大型语言模型聊天机器人的广泛审查 酒精和其他药物健康信息的使用
Natasha Harding1, Nataly Bovopoulos1, Dotahn Caspi1
1Alcohol and Drug Foundation, Melbourne, Australia.
Drug and alcohol review
|November 6, 2025
概括
大型语言模型 (LLM) 聊天机器人对寻找酒精和毒品信息充满希望,但当前的研究强调了用户安全,准确性和遵守指南的重大挑战. 进一步调查对于安全有效的使用至关重要.
科学领域:
- 数字健康数字健康
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 在线寻找酒精和毒品信息 (AOD) 面临质量和可访问性挑战.
- 大型语言模型 (LLM) 聊天机器人为这些障碍提供了潜在的解决方案.
研究的目的:
- 审查有关聊天机器人用于寻找AOD健康信息的文献.
- 为了确定未来的LLM聊天机器人应用在AOD信息搜索中的好处,挑战和建议.
主要方法:
- 使用了一个范围审查方法.
- 在过去五年中对四个英语语言研究数据库进行系统搜索.
- 选了243篇文章,其中包括5项研究.
主要成果:
- 越来越多的人对LLM聊天机器人对AOD信息感兴趣,但证据有限.
- 优势包括准确性和用户体验;挑战涉及用户安全,转介,质量和遵守指南.
- 基于证据的回应得到了混合的结果;只有三项研究推聊天机器人.
结论:
- 有关LLM聊天机器人的准确性,用户安全性,可读性,证据基础和AOD查询质量的知识差距存在.
- 需要更多的研究来评估LLM在获取AOD信息方面的安全和非污名化应用.
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