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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Italian Validation of the Screen for Cognitive Impairment in Psychiatry
Martino Belvederi Murri1, Federica Folesani2, Silvia Costa1
1Institute of Psychiatry, Department of Biomedical and Specialty Surgical Sciences, University of Ferrara, Via Fossato di Mortara 64, 44121, Ferrara, Italy.
Abstract:
Cognitive impairments have profound implications for the management of severe mental disorders; however, they are rarely assessed in everyday clinical practice due to constraints in time, resource and expertise. Novel and short instruments, such as the Screen for Cognitive Impairment in Psychiatry (SCIP), which overcome such limitations are greatly needed. The study aims to assess the validity and reliability, among healthy subjects, of the Italian translation of the SCIP, a brief, accessible tool to detect cognitive impairments among individuals suffering from mental disorders, as the first step to validate the instrument in clinical settings. One-hundred and twenty healthy subjects completed two of the three alternative forms of the SCIP. Cronbach Alpha (0.70) supported the reliability of the SCIP scores. Correlation coefficients supported the test-retest reliability of the tool. Learning effects were observed despite the use of alternative forms. Factor analysis indicated a two-factor solution explaining 55.4% of the total variance: the first factor ("memory") loading for VLT-I and VLT-D and less for WMT; the second factor ("executive function") loading for VFT and PST and less for WMT. The study proved the validity and reliability of the Italian version of the SCIP as a reliable and simple instrument to screen for cognitive impairment in the general population.

