Department of Psychology, Indiana University-Purdue University Indianapolis, United States.
Department of Psychology, Louisiana State University, United States.
Psychiatry Res. 2018 Jan;259:63-67. doi: 10.1016/j.psychres.2017.09.078. Epub 2017 Sep 30.
Technological advancements have led to the development of automated methods for assessing semantic coherence in psychiatric populations. Latent Semantic Analysis (LSA) is an automated method that has been used to quantify semantic coherence in schizophrenia-spectrum disorders. The current study examined whether: 1) Semantic coherence reductions extended to psychometrically-defined schizotypy and 2) Greater cognitive load further reduces semantic coherence. LSA was applied to responses generated during category fluency tasks in baseline and cognitive load conditions. Significant differences between schizotypy and non-schizotypy groups were not observed. Findings suggest that semantic coherence may be relatively preserved at this point on the schizophrenia-spectrum.
技术进步导致了用于评估精神病患者群体语义连贯性的自动化方法的发展。潜在语义分析（LSA）是一种已被用于量化精神分裂症谱系障碍中语义连贯性的自动化方法。本研究考察了以下两点：1）语义连贯性的降低是否扩展到了心理定义的精神分裂症倾向；2）更大的认知负荷是否会进一步降低语义连贯性。在基线和认知负荷条件下，对类别流畅性任务中生成的反应应用了 LSA。在精神分裂症倾向和非精神分裂症倾向组之间没有观察到显著差异。研究结果表明，在精神分裂症谱系的这一点上，语义连贯性可能相对保持不变。
