Department of Psychology, Louisiana State University, 236 Audubon Hall, Baton Rouge, LA 70803, USA.
Schizophr Res. 2012 Sep;140(1-3):41-5. doi: 10.1016/j.schres.2012.07.001. Epub 2012 Jul 23.
There is growing awareness that reduced expressive behaviors (e.g., blunt affect, alogia, psychomotor retardation) are characteristic of a range of psychiatric conditions, including mood and schizophrenia-spectrum disorders. From a Research Domain Criteria (RDoC) perspective, it would be critical to determine whether these symptoms manifest similarly across diagnostic groups--as they may share common pathophysiological underpinnings. The present study employed computerized acoustic analysis of speech produced in reaction to a range of visual stimuli in 48 stable outpatients with schizophrenia and mood disorders to offer preliminary understanding of this issue. Speaking assessments were administered 1 week-apart to examine how temporal stability might vary as a function of clinical diagnosis and symptom severity. Speech characteristics generally did not differ between groups and were similarly, and for the most part, highly stable over time. Aspects of speech were significantly associated with severity of psychosis and negative symptoms, but not with clinical depression/anxiety severity. Moreover, stability of speech characteristics generally did not vary as a function of diagnostic group or clinical severity. The magnitudes of group differences were almost exclusively in the negligible to small range. Speech production was associated with social functioning deficits. In sum, these preliminary data suggest that speech variables tap a stable and clinically important facet of psychopathology that cut across diagnostic categories. Computerized acoustic analysis of speech appears to be a promising method for understanding the pathological manifestation of these variables.
人们越来越意识到,表达减少的行为(例如,情感迟钝、言语贫乏、运动迟缓)是一系列精神疾病的特征,包括情绪和精神分裂症谱系障碍。从研究领域标准(RDoC)的角度来看,确定这些症状是否在不同的诊断组中表现相似是至关重要的,因为它们可能具有共同的病理生理基础。本研究采用计算机化的语音分析技术,对 48 名稳定的精神分裂症和心境障碍门诊患者在一系列视觉刺激下产生的语音进行分析,初步探讨了这一问题。在 1 周的时间间隔内进行语音评估,以考察临床诊断和症状严重程度的变化如何影响时间稳定性。语音特征在组间没有差异,并且在很大程度上是相似的,并且在很长一段时间内都非常稳定。语音的某些方面与精神病和阴性症状的严重程度显著相关,但与临床抑郁/焦虑严重程度无关。此外,语音特征的稳定性通常不受诊断组或临床严重程度的影响。组间差异的幅度几乎完全在可忽略不计到小的范围内。言语产生与社交功能缺陷有关。总之,这些初步数据表明,言语变量反映了一种稳定且具有临床重要性的精神病理学特征,跨越了诊断类别。语音的计算机化声学分析似乎是理解这些变量病理性表现的一种很有前途的方法。