Establishing the consistency of a voice recognition symbol digit modalities test analogue.

BACKGROUND: We previously demonstrated the convergent validity of a fully automated voice recognition analogue of the Symbol Digit Modalities Test (VR-SDMT) for evaluating processing speed in people with multiple sclerosis (pwMS). OBJECTIVE/METHODS: We aimed to replicate these results in 54 pwMS and 18 healthy controls (HCs), demonstrating the VR-SDMT's reliability. RESULTS: Significant correlations were found between the VR-SDMT and the traditional oral SDMT in the multiple sclerosis (MS) (r = -0.771, p < 0.001) and HC (r = -0.785, p < 0.001) groups. CONCLUSION: Taken collectively, our two studies demonstrate the reliability and validity of the VR-SDMT for assessing processing speed in pwMS.

A French Version of a Voice Recognition Symbol Digit Modalities Test Analog.

We previously showed that a fully automated voice recognition analog of the Symbol Digit Modalities Test (VR-SDMT) is sensitive in detecting processing speed deficits in people with multiple sclerosis (pwMS). We subsequently developed a French language version and administered it to 49 French-Canadian pwMS and 29 matched healthy control (HC) subjects. Significant correlations between the VR-SDMT and traditional oral SDMT were found in the MS (r = -0.716, p < 0.001) and HC (r = -0.623, p < 0.001) groups. These findings in French replicate our previous findings and confirm the utility of voice recognition software in assessing cognition in pwMS.

Taking the tester out of the SDMT: A proof of concept fully automated approach to assessing processing speed in people with MS.

BACKGROUND: One factor hindering the widespread use of cognitive testing for people with multiple sclerosis (pwMS) is the need for a tester to administer tests. OBJECTIVE: To undertake a proof of concept study assessing the feasibility of a fully automated speech recognition version of the Symbol Digit Modalities Test (auto-SDMT) in detecting abnormalities in processing speed in pwMS. METHODS: A sample of 50 pwMS and 32 matched healthy control (HC) subjects was tested with the auto-SDMT and the Brief International Cognitive Assessment for MS (BICAMS). RESULTS: The percentages of MS participants impaired on the auto-SDMT and the traditional oral SDMT were 34% and 32%, respectively. Excellent convergent validity was found between the two tests (MS: r = -0.806, p < 0.001 and HC: r = -0.629, p < 0.001). The auto-SDMT had a similar sensitivity and specificity to the traditional oral SDMT in predicting overall impairment on the BICAMS. CONCLUSION: The auto-SDMT is a sensitive measure for detecting processing speed deficits in pwMS. The test, the first entirely computer administrated oral response version of the SDMT, uses speech recognition technology, thereby eliminating the need for a human tester. Replication of the results is required in a larger representative sample of pwMS.