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Updated: Nov 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Neurocognitive Impairment in Severe Mental Illness. Comparative study with Spanish Speaking Patients
Gabriel G De la Torre1, Sandra Doval2,3, David López-Sanz2,4
1Neuropsychology and Experimental Psychology Lab, University of Cadiz, 11510 Puerto Real, Spain.
Background:
Serious mental illness (SMI) represents a category of psychiatric disorders characterized by specific difficulties of personal and social functioning, derived from suffering severe and persistent mental health problems.
Aims:
We wanted to look into differences in cognitive performance among different SMI patients.
Methods:
Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) screening was applied in one sample of SMI patients (n = 149) and another of healthy comparison participants (n = 35). Within the SMI sample, three different subsamples were formed: one with 97 patients with schizophrenia, a second with 29 patients with mood disorders, and a third with 23 patients with personality disorder. We performed a comparative study within and between groups.
Results:
Analysis of covariance was performed. Significant differences were found for cognitive functioning including attention and memory.
Conclusions:
RBANS can be recommended for the detection of neurocognitive deficits in psychiatric disorders, especially in Schizophrenia.
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