AUTHOR=Cattaneo Gabriele , Pachón-García Catherine , Roca Alba , Alviarez-Schulze Vanessa , Opisso Eloy , García-Molina Alberto , Bartrés-Faz David , Pascual-Leone Alvaro , Tormos-Muñoz Josep M. , Solana-Sánchez Javier 

TITLE=“Guttmann Cognitest”®, preliminary validation of a digital solution to test cognitive performance

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 14 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.987891

DOI=10.3389/fnagi.2022.987891

ISSN=1663-4365

ABSTRACT=Thanks to technological advances, the administration of cognitive assessments via digital solutions continues to increase, both in research and clinical practice. We have developed a mobile cognitive assessment, the "Guttmann Cognitest"®, which includes 7 computerized tasks designed to assess main cognitive functions and requires approximately 20 minutes to be completed. The purpose of the present study was to validate it against standard and more extensive, in-person neuropsychological assessments in the context of the Barcelona Brain Health Initiative cohort study. 
We studied 274 participants of the BBHI (126 women, mean age= 56.14, age range 44-69), who underwent an extensive in-person assessment, including a classical paper-and-pencil neuropsychological assessment and a cognitive assessment via the "Guttmann Cognitest"®. 
Principal component analysis indicated that “Guttmann Cognitest”® measured 4 main cognitive domains and convergent validity analysis demonstrated that cognitive performance correlated moderately with gold standard paper and pencil tests. Results also showed an expected negative correlation with age, a relation with educational level as well as a gender effect. Regression-based norming equations for the sample tested are also reported. 
Performing a cognitive assessment with this digital solution is feasible and potentially useful to gather information about cognitive functioning in clinical and experimental setting, specifically for cognitive assessment in large-scale samples.