MoCA in five Indian languages: A brief screening tool to diagnose dementia and MCI in a linguistically diverse setting

Abstract

INTRODUCTION AND OBJECTIVES: Early dementia diagnosis in low and middle-income countries (LMIC) is challenging due to limited availability of brief, culturally appropriate, and psychometrically validated tests. Montreal Cognitive Assessment (MoCA) is one of the most widely used cognitive screening tests in primary and secondary care globally. In the current study, we adapted and validated MoCA in five Indian languages (Hindi, Bengali, Telugu, Kannada, and Malayalam) and determined the optimal cut-off points that correspond to screening for clinical diagnosis of dementia and MCI. METHODS: A systematic process of adaptation and modifications of MoCA was fulfilled. A total of 446 participants: 214 controls, 102 dementia, and 130 MCI were recruited across six centers. RESULTS: Across five languages, the area under the curve for diagnosis of dementia varied from 0.89 to 0.98 and MCI varied from 0.73 to 0.96. The sensitivity, specificity and optimum cut-off scores were established separately for five Indian languages. CONCLUSIONS: The Indian adapted MoCA is standardized and validated in five Indian languages for early diagnosis of dementia and MCI in a linguistically and culturally diverse population.