语言情绪预测了抑郁症状的变化
Jihyun K Hur1, Joseph Heffner1, Gloria W Feng1
1Department of Psychology, Yale University, New Haven, CT 06510.
概括
在书面回复中分析语言情绪可以帮助预测未来的抑郁症症状. 人工智能工具,如大型语言模型 (LLM),在识别有恶化抑郁症风险的个体方面表现有前途.
科学领域:
- 精神病学是一个精神病学.
- 计算语言学 计算语言学
- 自然语言处理自然语言处理.
背景情况:
- 抑郁症是一个重要的公共卫生问题,需要预测工具.
- 以前的研究表明,抑郁症会影响语言使用,但预测能力尚不清楚.
研究的目的:
- 为了确定简短的书面反应中的语言情绪是否预测了抑郁症的变化.
- 为了比较人类评分器,LLM和LIWC对抑郁症症状变化的预测准确度.
主要方法:
- 两项研究涉及467名参与者,他们提供了书面答复,并完成了抑郁症评估 (PHQ-9).
- 人类评分员 (N=470),ChatGPT 3.5/4.0和LIWC.的书面答复的情绪分析.
- 通过风险决策任务和瞬间幸福度的测量量量度的情绪动态.
主要成果:
- 人类评分器和LLM评估的语言情绪预测了抑郁症状的三周增加.
- LIWC情绪分析没有预测症状变化.
- 语言情绪与当前情绪相关,但独立预测未来的症状变化.
结论:
- 使用人工智能工具对简短的书面反应进行情感分析,这是预测未来抑郁症的可扩展方法.
- 人工智能驱动的情绪分析与预测精神病症状变化的人类表现相匹配.
- 这种方法为早期识别和干预抑郁症提供了一个新的工具.
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