A Novel Way of Measuring Dual-Task Interference: The Reliability and Construct Validity of the Dual-Task Effect Battery in Neurodegenerative Disease

Abstract

Background. Decreased automaticity is common among individuals with neurodegenerative disease and is often assessed using dual-task (DT) paradigms. However, the best methods for assessing performance changes related to DT demands remain inconclusive. Objective. To investigate the reliability and validity of a novel battery of DT measures (DT Effect—Battery (DTE-B)) encompassing three domains: task-specific interference, task prioritization, and automaticity. Methods. Data for this retrospective cross-sectional study included 125 participants with Parkinson’s disease (PD), 127 participants with Alzheimer’s disease (AD), and 84 healthy older adults. Reliability analyses were conducted using a subset of each population. DTE-B measures were calculated from single and DT performance on the Timed Up and Go test and a serial subtraction task. Construct validity was evaluated via associations within the DTE-B and with theoretically supported measures as well as known-groups validity analyses. Results. Good to excellent reliability was found for DTE-B measures of task interference (motor and cognitive DT effects) (ICCs≥.658) and automaticity (combined DT effect (cDTE)) (ICCs≥.938). Evidence for convergent validity was found with associations within the hypothesized constructs. Known-groups validity analyses revealed differences in the DTE-B among the healthy group and PD and AD groups ( ps≤.001), excepting task prioritization ( ps≥.061). Conclusions. This study provides evidence to support the DTE-B as a reliable measure of multiple constructs pertinent to DT performance. The cDTE demonstrated evidence to support its validity as a measure of automaticity. Further investigation of the utility of the DTE-B in both PD and AD, as well as other populations, is warranted.

A Perspective: Challenges in Dementia Research

“…This results in large test variances for individuals and reduces the precision of the assessment. A second solution is to start with a number of tests including quantitative psychophysical tests (that may be less dependent on education and language than traditional paper and pencil tests) [ 19 , 20 ] and use statistical techniques to find a limited combination of these test elements, which is minimally dependent on the factors that influence cognition in cognitively healthy people. This is not enough, however, because the ideal test should not only yield results that were similar in cognitively healthy people, but also be sensitive to the different phenotypes seen in cognitive disorders of differing etiology.…”