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Converting from the Montreal Cognitive Assessment to the Mini-Mental State Examination-2

Hwabeen Yang, Daehyuk Yim, Moon Ho Park

2021PLoS ONE21 citationsDOIOpen Access PDF

Abstract

OBJECTIVE: The Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination-2 (MMSE-2) are useful psychometric tests for cognitive screening. Many clinicians want to predict the MMSE-2 score based on the MoCA score. To facilitate the transition from the MoCA to the MMSE-2, this study developed a conversion method. METHODS: This study retrospectively examined the relationship between the MoCA and MMSE-2. Overall, 303 participants were evaluated. We produced a conversion table using the equipercentile equating method with log-linear smoothing. Then, we evaluated the reliability and accuracy of this algorithm to convert the MoCA to the MMSE-2. RESULTS: MoCA scores were converted to MMSE-2 scores according to a conversion table that achieved a reliability of 0.961 (intraclass correlation). The accuracy of this algorithm was 84.5% within 3 points difference from the raw score. CONCLUSIONS: This study reports a reliable and easy conversion algorithm for transforming MoCA scores into converted MMSE-2 scores. This method will greatly enhance the utility of existing cognitive data in clinical and research settings.

Topics & Concepts

Montreal Cognitive AssessmentEquatingIntraclass correlationReliability (semiconductor)CognitionSmoothingMini–Mental State ExaminationRaw scorePsychologyStatisticsCognitive impairmentComputer scienceMathematicsPsychometricsPsychiatryRaw dataRasch modelPhysicsQuantum mechanicsPower (physics)Dementia and Cognitive Impairment ResearchTraumatic Brain Injury ResearchPsychological Testing and Assessment
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