Skip to main navigation Skip to search Skip to main content

Validation of conversion between mini-mental state examination and montreal cognitive assessment

Michael Lawton*, Meike Kasten, Margaret T. May, Brit Mollenhauer, Martina Schaumburg, Inga Liepelt-Scarfone, Walter Maetzler, Eva Juliane Vollstedt, Michele T.M. Hu, Daniela Berg, Yoav Ben-Shlomo

*Corresponding author for this work

Abstract

Introduction: Harmonizing data across cohorts is important for validating findings or combining data in meta-analyses. We replicate and validate a previous conversion of MoCA to MMSE in PD. Methods: We used five studies with 1,161 PD individuals and 2,091 observations measured with both the MoCA and MMSE. We compared a previously published conversion table using equipercentile equating with log-linear smoothing to our internally derived scores. Results: Both conversions found good agreement within and across the studies when comparing true and converted MMSE (mean difference: 0.05; standard deviation: 1.84; median difference: 0; interquartile range: -1 to 1, using internal conversion). Conclusions: These results show that one can get a reliable and valid conversion between two commonly used measures of cognition in PD studies. These approaches need to be applied to other scales and domains to enable large-scale collaborative analyses across multiple PD cohorts.

Original languageEnglish
JournalMovement Disorders
Volume31
Issue number4
Pages (from-to)593-596
Number of pages4
ISSN0885-3185
DOIs
Publication statusPublished - 01.04.2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Research Areas and Centers

  • Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

Fingerprint

Dive into the research topics of 'Validation of conversion between mini-mental state examination and montreal cognitive assessment'. Together they form a unique fingerprint.

Cite this