Consistency analysis and conversion model establishment of mini-mental state examination and montreal cognitive assessment in Chinese patients with Alzheimer’s disease

Frontiers in Psychology 13 (2022)
  Copy   BIBTEX

Abstract

BackgroundThe Chinese version of the Mini-Mental State Examination and the Beijing version of the Montreal Cognitive Assessment are the most commonly used scales to screen for Alzheimer’s disease among Chinese patients; however, their consistency varies according to populations and languages. Equivalent conversion of MMSE-C and MoCA-BJ scores is important for meta-analysis.Materials and methodsMMSE-C and MoCA-BJ scoring were performed on the enrolled patients with AD. Consistency analysis of MMSE-C and MoCA-BJ scores of patients in the conversion groups was performed. The circle-arc method was used to convert the MMSE-C scores of the conversion groups into MoCA-BJ scores, and the conversion formula was generated. The MMSE-C data of the verification group was converted to MoCA-BJ according to the formula, and the consistency analysis of the original MoCA-BJ of the verification group and the converted MoCA-BJ was performed to verify the conversion model.ResultsThe results of the consistency analysis of MMSE-C and MoCA-BJ in group A showed that the correlation coefficients of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.905, 0.874, 0.949, and 0.874, respectively, with high consistency and statistical significance. After applying the circle-arc method for equivalent conversion, the consistency analysis results of the original and the converted MoCA-BJ of the patients in group B of the total group, high education years subgroup, medium education years subgroup, and low education years subgroup were 0.891, 0.894, 0.781, 0.909, respectively, with high consistency and statistical significance.ConclusionWe established and validated a model of MMSE-C and MoCA-BJ score conversion for Chinese patients with AD using the circle-arc method. This model could be useful for multi-centers clinical trials and meta-analysis.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 92,611

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
Cognitive Aging: What We Fear and What We Know.I. I. Dan G. Blazer - 2018 - Perspectives in Biology and Medicine 60 (4):569-582.

Analytics

Added to PP
2022-10-02

Downloads
6 (#1,467,817)

6 months
3 (#984,719)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Hui Li
National University of Singapore

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references