在心理健康中评估生成人工智能:对能力和局限性的系统审查
Liying Wang1,2, Tanmay Bhanushali3, Zhuoran Huang4
1Institute on Digital Health and Innovation, College of Nursing, Florida State University, 222 S Copeland St, Tallahassee, FL, 32306, United States, 1 (850) 644-3296.
JMIR mental health
|May 15, 2025
概括
生成型人工智能 (GenAI) 在心理健康,心理教育和情感意识方面表现有前途,但在诊断和用户参与方面存在局限性. 需要使用先进方法进行进一步的研究,以探索其在临床环境中的全部潜力.
科学领域:
- 心理健康技术 心理健康技术
- 医疗保健中的人工智能
- 数字精神病学数字精神病学
背景情况:
- 在COVID-19后,对心理健康服务的需求不断增长和专业人员短缺.
- 越来越多的人对利用大语言模型 (LLM) 来解决心理健康挑战越来越感兴趣.
- 生成型人工智能 (GenAI) 为增强心理健康护理提供提供提供了一个潜在的途径.
研究的目的:
- 系统地审查GenAI模型在心理健康应用中的功能.
- 评估GenAI在社会认知能力,心理健康结果和用户体验方面的表现.
- 为了确定目前的局限性和未来的研究方向,用于GenAI在心理健康.
主要方法:
- 在2023-2024年间发表的8项研究的系统审查.
- 包含原始研究与评估GenAI模型的实验设计.
- 评估社会认知能力,心理健康结果和用户体验,使用标准化尺度和定性分析.
主要成果:
- 基因AI模型 (例如,ChatGPT,Bard,Claude) 在心理教育和情感意识方面表现出强势.
- 在诊断准确度,文化能力和情感参与方面发现的局限性.
- 用户对可信度,准确性和缺乏情感联系表示担忧.
结论:
- 基因人工智能显示出潜力,但需要进一步开发临床心理健康应用.
- 建议采用先进的评估方法,如几次射击和思维链提示.
- 纵向研究和人类基准比较对于理解GenAI在综合心理健康护理中的作用至关重要.
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