探索LLMs在心理健康中的应用边界:一个系统的范围审查
Jinhua Yang1, Ting Liu2, Yiming Taclis Luo2
1The School of Humanities, Tongji University, Shanghai, China.
Frontiers in psychology
|March 16, 2026
概括
大型语言模型 (LLM) 在心理健康中显示出对查和增强护理的希望. 未来的研究必须侧重于专业化,多式联运一体化和安全临床部署的伦理框架.
科学领域:
- 人工智能的人工智能
- 心理健康技术 心理健康技术
- 计算语言学 计算语言学
背景情况:
- 大型语言模型 (LLM) 展示了先进的文本理解和生成能力.
- 在医疗保健,特别是心理健康中LLM的应用是一个新兴和复杂的领域,需要彻底调查.
- 本综述为未来关于心理健康LLM的研究和临床实践提供了一个框架.
研究的目的:
- 系统地覆盖目前LLMs在心理健康中的应用范围.
- 识别关键的研究趋势,现有的差距和伦理/实践边界.
- 为未来的研究和临床实施提供全面的概述.
主要方法:
- 遵守PRISMA-ScR系统范围审查指南.
- 在11个主要的学术数据库中进行了广泛的文献搜索.
- 在系统选后,包括29个相关文章.
主要成果:
- 在心理健康领域的LLM应用侧重于高通量查和临床增强.
- 转向专业模型 (例如BERT) 以提高在抑郁症等情况中的准确性.
- 确定的局限性包括文化不敏感,纵向数据的挑战和错误信息的风险.
结论:
- 法律学士可以充当"心理健康代理人",提供个性化的干预措施.
- 关键的挑战是通过专业化和多式联络整合来实现临床严谨性.
- 为了安全部署,需要紧急开发伦理和文化适应性框架.
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