Department of Psychology, Louisiana State University, United States.
Schizophr Res. 2013 Aug;148(1-3):111-6. doi: 10.1016/j.schres.2013.05.003. Epub 2013 May 29.
Diminished expression is a diagnostic feature of a range of schizophrenia-spectrum disorders/conditions and is often unresponsive to treatment, is present across premorbid, first episode and various clinical states, and is considered a poor prognostic indicator. Surprisingly, little is known about diminished expression. The present study sought to address this issue by evaluating a commercially-available computerized facial analysis software for understanding diminished expressivity. We analyzed natural facial expression from a series of laboratory interaction tasks in 28 individuals with psychometric schizotypy - defined as the personality organization reflecting a putative genetic schizophrenia liability, and 26 matched controls. We evaluated (a) feasibility - defined in terms of the number of video frames recognized by the software, (b) reliability - defined in terms of correlations between facial expression variables across the three laboratory interactions, and (c) construct validity - defined in terms of relationships to clinical variables. For most subjects (~80%), approximately three-quarters of the video frames were analyzable by the software; however, a minority of the videos were essentially unreadable. The facial expression variables showed excellent reliability across interaction conditions. In terms of construct validity, facial expression variables were significantly related to a measure of psychoticism, tapping subjective cognitive concerns and "first-rank" schizophrenia symptoms, but were generally not different between groups. Facial expression variables were generally not significantly related to measures of depression, anxiety, paranoia or, surprisingly, self-reported negative schizotypy. While computerized facial analysis appears to be a reliable and promising method of understanding diminished expressivity across the schizophrenia-spectrum, some work remains. Implications are discussed.
表达减退是一系列精神分裂症谱系障碍/病症的诊断特征，且通常对治疗无反应，存在于病前、首次发作和各种临床状态中，并被认为是预后不良的指标。令人惊讶的是，人们对表达减退知之甚少。本研究旨在通过评估一种商业面部分析软件来解决这个问题，以了解表达减退。我们分析了 28 名具有心理分裂特质的个体在一系列实验室互动任务中的自然面部表情，这些个体被定义为反映潜在遗传精神分裂症倾向的人格组织，以及 26 名匹配的对照组。我们评估了（a）可行性，定义为软件识别的视频帧数；（b）可靠性，定义为三个实验室互动中面部表情变量之间的相关性；（c）构念效度，定义为与临床变量的关系。对于大多数受试者（约 80%），软件可分析大约四分之三的视频帧；然而，少数视频几乎无法读取。面部表情变量在互动条件下具有极好的可靠性。在构念效度方面，面部表情变量与精神病度量表显著相关，该量表反映了主观认知问题和“一级”精神分裂症症状，但在组间通常没有差异。面部表情变量与抑郁、焦虑、偏执或令人惊讶的是，自我报告的消极精神分裂特质量表通常没有显著相关性。虽然计算机化的面部分析似乎是一种可靠且有前途的方法，可以了解精神分裂症谱系中的表达减退，但仍有一些工作要做。讨论了其影响。
