An Abbreviated Montreal Cognitive Assessment (MoCA) for Dementia Screening

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 Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI), Alzheimer disease (AD), and normal aging. METHODS: 408 subjects (MCI n = 169, AD n = 87, and 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 cut-off 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.