Discrimination in the clinical diagnosis between patients with schizophrenia and healthy controls using eye movement and cognitive functions.

ABSTRACT

AIM: Eye movements and cognitive functions are significantly impaired in patients with schizophrenia. The authors aimed to develop promising clinical diagnostic markers that fit practical digital health applications in psychiatry using eye movement and cognitive function data from 1254 healthy individuals and 336 patients with schizophrenia. METHODS: Multivariate analyses using logistic regression were performed to confirm net performance of eye movements and cognitive functions scored using the Wechsler Adult Intelligence Scale, Third Edition, and Wechsler Memory Scale-Revised. The authors then examined the discrimination performance of pairs containing an eye movement and a cognitive function measure to search the pairs that would be effective in practical application for the discrimination according to the diagnostic criterion between the groups. RESULTS: Multivariate analyses confirmed that eye movements and cognitive functions were effective modalities for discriminating between patients with schizophrenia and healthy controls. The discriminant analyses of the pairs demonstrated that seven eye movement measures and seven scores from cognitive function tests showed high discrimination performance when paired with one measure from the other modality. Moreover, seven pairs of digit-symbol coding or symbol-search and eye movement measures had high and robust discrimination performance. CONCLUSION: Seven pairs of an eye movement and a cognitive function measure were effective, robust, and less time-consuming in assisting with clinical diagnosis by categorizing healthy individuals or patients with schizophrenia. These findings may help develop an objective auxiliary diagnosis method working even on portable devices, which facilitates the consistency of diagnosis, earlier intervention, and shared decision-making.