No abstract

Generally, our findings suggest that the poor acceptability of IVR systems by older people could be improved by designing IVR algorithms that detect difficulties during an ongoing IVR exchange and direct people to different algorithms adapted for each person.

Interactive voice response (IVR) systems are computer programs, which interact with people to provide a number of services from business to health care. We examined the ability of an IVR system to administer and score a verbal fluency task (fruits) and the digit span forward and backward in 158 community dwelling people aged between 65 and 92 years of age (full scale IQ of 68–134). Only six participants could not complete all tasks mostly due to early technical problems in the study. Participants were also administered the Wechsler Intelligence Scale fourth edition (WAIS-IV) and Wechsler Memory Scale fourth edition subtests. The IVR system correctly recognized 90% of the fruits in the verbal fluency task and 93–95% of the number sequences in the digit span. The IVR system typically underestimated the performance of participants because of voice recognition errors. In the digit span, these errors led to the erroneous discontinuation of the test: however the correlation between IVR scoring and clinical scoring was still high (93–95%). The correlation between the IVR verbal fluency and the WAIS-IV Similarities subtest was 0.31. The correlation between the IVR digit span forward and backward and the in-person administration was 0.46. We discuss how valid and useful IVR systems are for neuropsychological testing in the elderly.

The impact of poorer auditory memory and working memory is compounded by programming practices that increase the demand on these abilities and create unnecessary difficulties. Successful use of IVR systems could eventually complement in person health services.

New editions of the Wechsler Adult Intelligence and Memory scales are now available. Yet, given the significant changes in these new releases and the skepticism that has met them, independent evidence on their psychometric properties is much needed but currently lacking. We administered the WAIS-IV and the Older Adult version of the WMS-IV to 145 older adults. We examined how closely our data matched the normative sample by comparing our scaled scores with those of the publisher and by evaluating interrelations among subtests using confirmatory factor analysis. Not surprisingly, scaled scores from our sample were somewhat higher than those from the normative sample on some tests. Factor analysis on our sample provided support for a higher-order model of the WAIS-IV/WMS-IV Older Adults battery combined. In addition, allowing some subtests to load on more than one factor significantly improved model fit. The best fitting model for our sample was also the best for the normative sample. Overall, the data suggest that the factor analysis models generated from the normative samples for the new WAIS-IV and WMS-IV are reliable.