利用自然语言处理来研究心理治疗中的情感连贯性
Dana Atzil-Slonim1, Amir Eliassaf1, Neha Warikoo2
1Department of Psychology, Bar-Ilan University.
Psychotherapy (Chicago, Ill.)
|January 18, 2024
概括
情绪连贯性,即情绪体验与表达之间的联系,对于功能至关重要. 这项研究使用自然语言处理 (NLP) 发现,负面情绪的连贯性预测了治疗中更好的客户结果.
科学领域:
- 心理学 心理学 心理学
- 计算语言学 计算语言学
- 心理治疗研究 心理治疗研究
背景情况:
- 情绪连贯性,即情绪体验与表达之间的对齐,对于心理功能至关重要.
- 自然语言处理 (NLP) 的进步使治疗对话中的自动情绪识别成为可能,从而允许对情绪连贯性的大规模分析.
- 之前关于情感连贯性的研究受限于样本大小和分析细粒度.
研究的目的:
- 在心理治疗对话中使用NLP模型自动标记客户的情绪.
- 调查口头表达和自我报告的情绪之间的连贯性.
- 检查情绪连贯性与治疗期间客户功能改善之间的关联.
主要方法:
- 利用最先进的情感识别模型 (基于变压器) 来标记来自872次转录治疗会的139,061个发言.
- 收集了客户自我报告的功能和情绪数据.
- 采用多层次建模来评估情感连贯性及其与功能变化的联系.
主要成果:
- NLP情感识别模型取得了中等的表现.
- 在客户口头表达和自我报告的情绪之间发现了显著的关联.
- 负面情绪的更大连贯性与整个治疗过程中改善的客户功能相关.
结论:
- 客户的主观情感体验与他们的口头表达之间存在联系,突出了这种情感连贯性对功能的重要性.
- NLP工具可以有效地分析心理治疗中的情感过程,为治疗结果提供新的见解.
- 负面情绪表达的连贯性对于积极的治疗变化显得尤为重要.
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