对比生成人工智能和心理健康专业人员临床决策与创伤暴露的人群:基于图片的实验研究
Katherine E Wislocki1, Sabahat Sami1, Gahl Liberzon1
1Department of Psychological Science, University of California, Irvine, 4201 Social and Behavioral Sciences Gateway, Irvine, CA, 92697, United States, 1 949-824-5574.
JMIR mental health
|October 14, 2025
概括
生成型人工智能 (GAI) 模型显示了一些与创伤相关的诊断掩盖偏见,但比心理健康专业人员少. 当创伤存在时,GAI模型在特定条件的诊断和治疗选择中表现出更高的准确性.
科学领域:
- 医疗保健中的人工智能
- 临床心理学 临床心理学
- 心理健康研究 心理健康研究
背景情况:
- 创伤暴露很常见,并与健康问题有关.
- 医疗保健专业人员可能会表现出诊断覆盖偏见,影响受创伤影响的个体.
- 生成型人工智能 (GAI) 在医疗保健中越来越多地使用,但其偏见尚未被检查.
研究的目的:
- 在边境GAI模型中评估与创伤相关的诊断覆盖.
- 将GAI模型的偏差与心理健康专业人员 (MHPs) 的偏差进行比较.
主要方法:
- 232个MHP和多个GAI模型 (Gemini,ChatGPT,Claude,Llama) 评估了带有和没有创伤史的 vignettes.
- 参与者和GAI模型做出了诊断和治疗偏好决定.
- 统计分析 (曼-惠特尼U,千平方) 进行了决策的比较.
主要成果:
- GAI模型显示了一些与创伤相关的诊断掩盖偏见,特别是在性创伤方面.
- 在任务之间,GAI模型的偏差明显低于MHPs.
- GAI模型在诊断和治疗强迫症和物质使用障碍的选择方面比MHP更准确.
结论:
- GAI模型展示了与创伤相关的诊断掩盖偏见,尽管不如MHPs.
- 在GAI中偏差水平因任务和模型而异.
- 了解和减轻GAI偏见对于负责任地实施心理健康护理至关重要.
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