According to the journal Consortium Psychiatricum, this new data will contribute to improving the accuracy of diagnosis.
The journal notes that specialists from the Serbsky National Medical Research Center for Psychiatry and Addiction have developed a diagnostic model that accurately distinguishes between patients with schizophrenia, schizoaffective disorder, and healthy individuals, based on changes in brain electrical activity when recognizing others' facial expressions. The researchers identified two main weaknesses: a slower response time when recognizing happy faces and a reduced response to neutral expressions. The model achieved an accuracy rate of 73.3% in identifying these patients.
This study involved 86 volunteers, including 26 with schizophrenia, 26 with schizoaffective disorder, and 34 healthy individuals. Researchers recorded brain activity using electroencephalography (EEG) while participants performed a task of recognizing faces with happy, fearful, and neutral expressions. They then analyzed four key components of the brain's response, reflecting different stages of information processing, from initial perception to complex emotional understanding.
It should be noted that the traditional methods currently used to diagnose schizophrenia rely on clinical interviews and observation of patient behavior, while laboratory methods lack sufficient sensitivity to reach an accurate diagnosis.
