Construction of a short version of the Montreal Cognitive Assessment (MoCA) rating scale using Partial Least Squares analysis

Background The Montreal Cognitive Assessment (MoCA) rating scale is frequently used to assess cognitive impairments in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD). Objectives The aims of this study are to a) evaluate the construct validity of the MoCA and its subdomains or whether the MoCA can be improved by feature reduction, and b) develop a short version of the MoCA (MoCA-Brief). Methods We recruited 181 participants, divided into 60 healthy controls, 61 aMCI, and 60 AD patients. Results The construct reliability of the original MoCA was not optimal and could be improved by deleting one subdomain (Naming) and five items, namely Clock Circle, Lion, Digit Forward, Repeat 2 nd Sentence, and Place, which showed inadequate loadings on the extracted latent vectors. To construct the MoCA-Brief, the reduced model underwent further reduction and feature selection based on model quality data of the outer models. We produced a MoCA-Brief rating scale comprising five items, namely Clock Time, Subtract 7, Fluency, Month, and Year. The first latent vector extracted from these five indicators showed adequate construct validity with an Average Variance Extracted of 0.599, composite reliability of 0.822, Cronbach’s alpha of 0.832 and rho_A of 0.833. The MoCA-Brief factor score showed a strong correlation with the total MoCA score (r=0.98, p<0.001) and shows adequate concurrent, test-retest, and inter-rater validity. Conclusion The construct validity of the MoCA may be improved by deleting five items. The new MoCA-Brief rating scale deserves validation in independent samples and especially in other countries.