Tuesday, 6 June 2017

Factor structure of the Montreal Cognitive Assessment items in a sample with early Parkinson's disease

Useful data from the PPMI study looking at the various components of the MoCA and how these change in the early stages of PD after diagnosis... this may have relevance for an even earlier stage of PD, prior to diagnosis, and this is a focus of some of the work we are doing at the moment.

Parkinsonism Relat Disord. 2017 May 25. pii: S1353-8020(17)30189-X. doi: 10.1016/j.parkreldis.2017.05.023. [Epub ahead of print]

Benge JF, Balsis S, Madeka T, Uhlman C, Lantrip C, Soileau MJ.

http://www.prd-journal.com/article/S1353-8020(17)30189-X/fulltext

INTRODUCTION: The Montreal Cognitive Assessment (MoCA) is a frequently utilized cognitive screening tool that has attractive clinical attributes when utilized in individuals with Parkinson's disease. However, the construct validity of this instrument has not been well-characterized in Parkinson's samples. The purpose of this study is to explore the underlying factor structure of the MoCA in individuals with early stage Parkinson's disease.

METHOD: Item responses from the MoCA in 357 individuals with Parkinson's disease from the Parkinson's Progression Markers Initiative were analyzed first for frequency of errors and polychoric inter item correlations. This correlation matrix was then analyzed with exploratory factor analysis.

RESULTS: Omitting items with ceiling effects, three factors emerged which explained the majority of the variance. These factors were reflective of executive dysfunction, memory, and verbal attention. Scores on the MoCA and all of its subscales were significantly different between individuals with Parkinson's disease-no cognitive impairment and those who met criteria for mild cognitive impairment.

CONCLUSIONS: In keeping with prior studies in Parkinson's disease, executive dysfunction seems to underpin performance of many items of the MoCA. Implications of this finding both in terms of optimizing the MoCA for use in this population and further steps to validate the constructs behind the MoCA are discussed.

No comments:

Post a Comment