An Abbreviated Montreal Cognitive Assessment (MoCA) for Dementia Screening

Abstract

Objective The Montreal Cognitive Assessment (MoCA) is a cognitive screening instrument growing in popularity, but few studies have conducted psychometric item analyses or attempted to develop abbreviated forms. We sought to derive and validate a short form MoCA (SF;MoCA) and compare its classification accuracy to the standard MoCA and MMSE in mild cognitive impairment (MCI), Alzheimer disease (AD), and normal aging. Methods 408 subjects (MCI n=169, AD n=87, normal n=152) were randomly divided into derivation and validation samples. Item analysis in the derivation sample identified most sensitive MoCA items. Receiver Operating Characteristic (ROC) analyses were used to develop cutoff scores and evaluate the classification accuracy of the SF;MoCA, standard MoCA, and MMSE. Net Reclassification Improvement (NRI) analyses and comparison of ROC curves were used to compare classification accuracy of the three measures. Results Serial subtraction (Cramer's V=.408), delayed recall (Cramer's V=.702), and orientation items (Cramer's V=.832) were included in the SF;MoCA based on largest effect sizes in item analyses. Results revealed 72.6% classification accuracy of the SF; MoCA, compared with 71.9% for the standard MoCA and 67.4% for the MMSE. Results of NRI analyses and ROC curve comparisons revealed that classification accuracy of the SF;MoCA was comparable to the standard version and generally superior to the MMSE. Conclusions Findings suggest the SF;MoCA could be an effective brief tool in detecting cognitive impairment.

Defining and validating a short form Montreal Cognitive Assessment (s-MoCA) for use in neurodegenerative disease

“…The optimal cut-off score was <12. The s-MoCA performed nominally, but not statistically, better than a previous short form version of the MoCA in the AD and MCI sample 16 (table 3); the standard MoCA significantly outperformed the Horton et al s-MoCA (z=3.03, p=0.002). In accordance with previous studies, we show that the MoCA (0.83) and s-MoCA (0.82) have lower AUCs when differentiating AD from MCI; the difference in AUC was weak, but significant (z=2.04, p=0.04; see online supplementary figure S4).…”

“…The optimal cut-off score was <12. Both the standard MoCA (D=8.88, p<0.001) and the s-MoCA (D=6.97, p<0.001) had higher AUC as compared with the Horton et al 16 s-MoCA (table 3). The AUC for the Horton et al short form was under 0.50.…”

“…The optimal cut-off score of the s-MoCA was <12 and the classification accuracy was 64%; 2% higher than using the standard MoCA—likely due to the improvement in sensitivity. The s-MoCA outperformed a previous short form version of the MoCA 16 with higher AUC values (z=5.58, p<0.001) and had higher classification accuracy (table 3). Average scores on the standard MoCA and s-MoCA are shown in figure 2 for multiple neurological disorders.…”

“…Finally, the s-MoCA was compared with a recently published shortened version that was derived in an AD-only/MCI-only sample. 16 …”

“…14 Unlike the MMSE, which has several abbreviated forms, there is a dearth of psychometric analysis of item-wise performance on the MoCA. The three published brief versions of the MoCA suffer from small sample size, 1315 applicability within a limited clinical sample (vascular dementia 13 or Alzheimer’s type dementia 1516 only), and use of suboptimal psychometric techniques. Consequently, accurate generalisation of these brief forms to other neurological samples is challenging.…”