Computational linguistic analysis applied to a semantic fluency task to measure derailment and tangentiality in schizophrenia. (May 2018) - Pauselli, Luca; Halpern, Brooke; Cleary, Sean D.; Ku, Benson S.; Covington, Michael A.; Compton, Michael T.
Abstract: Although rating scales to assess formal thought disorder exist, there are no objective, high-reliability instruments that can quantify and track it. This proof-of-concept study shows that CoVec, a new automated tool, is able to differentiate between controls and patients with schizophrenia with derailment and tangentiality. According to ratings from the derailment and tangentiality items of the Scale for the Assessment of Positive Symptoms, we divided the sample into three groups: controls, patients without formal thought disorder, and patients with derailment/tangentiality. Their lists of animals produced during a one-minute semantic fluency task were processed using CoVec, a newly developed software that measures the semantic similarity of words based on vector semantic analysis. CoVec outputs were Mean Similarity, Coherence, Coherence-5, and Coherence-10 . Patients with schizophrenia produced fewer words than controls. Patients with derailment had a significantly lower mean number of words and lower Coherence-5 than controls and patients without derailment. Patients with tangentiality had significantly lower Coherence-5 and Coherence-10 than controls and patients without tangentiality. Despite the small samples of patients with clinically apparent thought disorder, CoVec was able to detect subtle differences between controls and patients with either or both of the two forms of disorganization. Highlights: Semantic fluency tasks might contain hidden data about formal thought disorder. Animal lists during a 1-minute semantic fluency task were processed using a new software measuring word similarity. CoVec is a new tool that may be able to detect formal thought disorder in semantic fluency tasks.