Today we give you our second conversation with Dr. Andrew Kiselica regarding aspects of neuropsychological test interpretation, with the current discussion focusing on multivariate base rates.
About Andrew
Dr. Kiselica is a board-certified clinical neuropsychologist and Associate Professor in the Institute of Gerontology at the University of Georgia. He studies how we can leverage everyday technologies, like smartphones and smart speakers, to improve the lives of persons with Alzheimer’s disease and related dementias (ADRD) and their care partners. Specifically, he has developed a novel behavioral intervention called Technology Assistance in Dementia (Tech-AiD), which empowers people with ADRD and their care partners to use digital technologies to reach personalized care goals. His other research interests include developing and validating advanced techniques for early detection of ADRD symptoms and improving understanding of the relationship between stress and cognitive decline. Dr. Kiselica also provides clinical services, education, and outreach to diverse older adults through the Cognitive Aging Research and Education (CARE) Center at the University of Georgia.
Resources
Clinical Reference Guide – Base Rates of Low Test Scores in Healthy Adults
References
Aita, S. L., Moncrief, G. G., Greene, J., Trujillo, S., Carrillo, A., Iwanicki, S., . . . Roth, R. M. (2023). Univariate and Multivariate Base rates of score elevations, reliable change, and inter-rater discrepancies in the BRIEF-A standardization samples. Assessment, 30(2), 390-401.
Binder, L. M., Iverson, G. L., & Brooks, B. L. (2009). To err is human: “Abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology, 24(1), 31-46.
Brooks, B. L., Holdnack, J. A., & Iverson, G. L. (2016). To change is human: “Abnormal” reliable change memory scores are common in healthy adults and older adults. Archives of Clinical Neuropsychology, 31(8), 1026-1036.
Iverson, G. L., & Karr, J. E. (2021). Improving the methodology for identifying mild cognitive impairment in intellectually high-functioning adults using the NIH toolbox cognition battery. Frontiers in Psychology, 12, 724888.
Jak, A. J., Bondi, M. W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D. P., & Delis, D. C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. The American Journal of Geriatric Psychiatry, 17(5), 368-375.
Karr, J. E., Garcia-Barrera, M. A., Holdnack, J. A., & Iverson, G. L. (2020). The other side of the bell curve: Multivariate base rates of high scores on the delis-Kaplan executive function system. Journal of the International Neuropsychological Society, 26(4), 382-393.
Karr, J. E., Hakun, J. G., Elbich, D. B., Pinheiro, C. N., Schmitt, F. A., & Segerstrom, S. C. (2024). Detecting cognitive decline in high-functioning older adults: The relationship between subjective cognitive concerns, frequency of high neuropsychological test scores, and the frontoparietal control network. Journal of the International Neuropsychological Society, 30(3), 220-231.
Kiselica, A. M., Karr, J. E., Mikula, C. M., Ranum, R. M., Benge, J. F., Medina, L. D., & Woods, S. P. (2024). Recent advances in neuropsychological test interpretation for clinical practice. Neuropsychology review, 34(2), 637-667.
Kiselica, A. M., Webber, T. A., & Benge, J. F. (2020). Using multivariate base rates of low scores to understand early cognitive declines on the uniform data set 3.0 Neuropsychological Battery. Neuropsychology, 34(6), 629–640.
Litvan, I., Goldman, J. G., Tröster, A. I., Schmand, B. A., Weintraub, D., Petersen, R. C., . . . Williams‐Gray, C. H. (2012). Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Movement disorders, 27(3), 349-356.
