Open AccessConverting from the Montreal Cognitive Assessment to the Mini-Mental State Examination-2
Author(s) -
Hwabeen Yang,
Daehyuk Yim,
Moon Ho Park
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0254055
Subject(s) - montreal cognitive assessment , equating , intraclass correlation , reliability (semiconductor) , cognition , smoothing , mini–mental state examination , raw score , psychology , statistics , cognitive impairment , computer science , mathematics , psychometrics , psychiatry , raw data , power (physics) , physics , quantum mechanics , rasch model
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.