Evaluating pauses in natural speech is a promising strategy for improving reliability, validity, and efficiency in assessing cognitive functions in people with mild cognitive impairment (MCI) and Alzheimer’s dementia (AD).

We conducted a quantitative meta-analysis of studies employing automated pause analysis. We included measures of speaking rate for comparison.

We identified 13 studies evaluating pause measures and 8 studies of speaking rate in people with MCI (n’s = 276 & 109, respectively) and AD (n’s = 170 & 81, respectively) and healthy aged controls (n’s = 492 & 231, respectively). Studies evaluated speech across various tasks, including standard neuropsychological, reading, and free/conversational tasks. People with AD and MCI showed longer pauses than controls at approximately 1.20 and 0.62 standard deviations, respectively, though there was substantial heterogeneity across studies. A more modest effect, of 0.66 and 0.27 SDs, was observed between these groups in speech rate. The largest effects were observed for standardized memory tasks.

Of the many ways that speech can be objectified, pauses appear particularly important for understanding cognition in AD. Pause analysis has the benefit of being face valid, interpretable in ratio format as a reaction time, tied to known socio-cognitive functions, and relatively easy to measure, compute, and interpret. Automation of speech analysis can greatly expand the assessment of AD and potentially improve early identification of one of the most devastating and costly diseases affecting humans.