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Updated: May 20, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Mini-Mental-37 test for dementia screening in the Spanish population: an analysis using the Rasch Model
Gerardo Prieto1, Israel Contador, Esther Tapias-Merino
1Departamento de Psicología Básica, Psicobiología y Metodología de las Ciencias del Comportamiento, Universidad de Salamanca, Spain.
Abstract:
Our aim was to analyze the psychometric properties of the Mini-Mental State Examination-37 using the Rasch Model (RM) in order to identify the cognitive domains that optimize detection of dementia in the Spanish population. All participants (n = 3955) were part of the NEDICES (Neurological Disorders in Central Spain) cohort study designed to detect dementia in persons aged 65 years and older. Clinical diagnosis of dementia (n = 178) was established by consensus of expert neurologists according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Results indicate that the items on the MMSE-37 have a good fit with the assumptions of the RM. None of the items on the MMSE-37 exhibits differential item functioning in relation to the groups. The items that assess orientation, attention, and language (repetition and comprehension) are those that best enable us to discriminate between the group with dementia and the group without dementia. The implications of the education and other sociodemographic characteristics of the population are discussed.

