通过LLM重新思考心理测量:项目语义如何塑造心理问卷中的测量和预测.
Federico Ravenda1, Antonio Preti2, Michele Poletti3
1Euler Institute, Faculty of Informatics, Università della Svizzera italiana, Lugano, Switzerland. federico.ravenda@usi.ch.
Scientific reports
|October 24, 2025
概括
大型语言模型 (LLM) 显示,项目语义显著影响心理问卷结果. 这一发现表明需要重新审视我们如何设计和解释心理测量.
科学领域:
- 心理测量 心理测量 心理测量
- 计算语言学 计算语言学
- 心理测量 心理测量
背景情况:
- 心理学问卷依赖于语义上相关的项目来衡量潜在的构造.
- 问卷单项的固有语义结构可能会影响收集的数据,独立于底层构造.
- 项目语义在多大程度上影响了测量结果与经验相关性之间的关系是一个开放的认识论问题.
研究的目的:
- 介绍LLMs心理测量,一种新的范式,使用LLMs来调查项目语义对心理测量结果的影响.
- 测试这样的假设,即物品之间的语言相似性预测了它们的经验相关性,即使没有经验数据.
- 开发和验证一个模型 (PsychoLLM),利用项目语义来预测响应.
主要方法:
- 从已建立的心理学工具 (大5个性,DASS-42) 进行实证相关性矩阵的比较,与从LLMs.
- 开发PsychoLLM,一种神经架构,利用项目语义来预测问卷答案.
- 通过使用通用焦虑障碍-7 (GAD-7) 和患者健康问卷-9 (PHQ-9) 的数据集,验证了PsychoLLM.
主要成果:
- 在95%的DASS-42案例和82%的Big 5案例中,LLM准确地预测了项目相关性,在前3个语义上相似的项目中发现了最相关的项目.
- 心理学LLM在预测不同心理尺度 (GAD-7和PHQ-9) 之间的反应时,仅基于项目语义,达到70%的准确性.
- 该研究表明,项目语义对心理测量数据施加了可预测的结构.
结论:
- 项目语义对心理测量结果产生了显著的,以前被低估的影响.
- 可以利用LLM来揭示问卷中的先验语义结构,帮助设计问卷和评估数据质量.
- 这项研究需要重新评估心理学中的测量原则,考虑到语言特性在心理测量数据中的作用.
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