Montreal Cognitive Assessment (MoCA) and Digit Symbol Substitution Test (DSST) as a screening tool for evaluation of cognitive deficits in schizophrenia

Cognitive deficit is one of the core features of schizophrenia and is associated with poor functional outcomes. There is a lack of validated criteria to screen and monitor cognitive deficits in schizophrenia. This study aimed to evaluate the concurrent validity and sensitivity of MoCA (Montreal Cognitive Assessment) and DSST (Digit Symbol Substitution Test) in identifying cognitive deficits in Schizophrenia comparing with a comprehensive MCCB [MATRICS (Measurement And Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery] equivalent battery. We did clinical and cognitive assessments on 30 patients with schizo-phrenia and 30 age and gender-matched healthy controls. The Cronbach's Alpha of MoCA was 0.839, and on adding the DSST, it increased to 0.859. In stepwise binary logistic regression, adding DSST to MoCA improved the prediction of cognitive impairment as defined by a comprehensive battery with 86.7% classification accu-racy. Receiver operating characteristic curve analysis suggested a score of 25 of MoCA and 59 of DSST as an optimal cut-off in identifying severe cognitive deficits with an additional MoCA cut-off of 27 for identifying mild cognitive deficits. Combined MoCA and DSST is a sensitive and quick method to screen for neurocognitive deficits in schizophrenia.

Automated summary

Cognitive deficit is a core feature of schizophrenia and is associated with poor functional outcomes. This study evaluated the validity and sensitivity of MoCA and DSST in identifying cognitive deficits in schizophrenia. The results showed that combining MoCA and DSST is a sensitive and quick method for screening neurocognitive deficits in schizophrenia.