客观的语言测量可以捕捉抑郁症状和相关的认知困难
Micaela Wiseman1,2, Rachel Yep1, Madeline Wood Alexander1,3
1Sunnybrook Research Institute, Toronto, Canada.
Translational psychiatry
|November 19, 2025
概括
语音分析提供了抑郁症的客观生物标志物. 研究人员在患有严重抑郁症 (MDD) 的人群中发现了不同的语言和声学语音模式,这可能有助于诊断和评估认知功能.
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
- 神经科学是一个神经科学.
背景情况:
- 目前的抑郁症评估依赖于主观的尺度,如汉密尔顿抑郁症评分尺度 (HAMD-17).
- 需要客观的生物标志物来准确诊断和监测严重抑郁症 (MDD).
- 语音模式可能反映精神病的潜在情绪和认知状态.
研究的目的:
- 调查语音特征作为抑郁症状的客观生物标志物.
- 探索大抑郁症 (MDD) 语音特征与认知困难之间的关联.
- 为了确定语音分析是否可以将MDD个体与对照区分开来.
主要方法:
- 66名患有MDD的个体和54名对照人提供了语音样本,以响应标准化提示.
- 使用自然语言处理提取语言 (价值,情绪强度,代理) 和声学 (音调,语音速率,暂停) 特性.
- 分析包括ANCOVA用于组比较和线性回归用于与抑郁症严重程度和执行功能的关联.
主要成果:
- 与对照人群相比,患有MDD的个体表现出更多的负面价值,更高的情绪强度,以及在演讲中表现出更少的行动力.
- 抑郁的参与者也表现出较低的音调,较慢的语音速度,并增加了暂停.
- 几种语言特征与执行功能表现有显著的关联,但与抑郁症严重程度无关 (HAMD-17).
结论:
- 语音特征,包括语言和声学特征,可以客观地区分患有严重抑郁症 (MDD) 的个人.
- 这些语音标记显示出检测抑郁症状和相关的执行功能缺陷的潜力.
- 语音分析为精神病学评估提供了一个可扩展和客观的方法.
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