Performance of Non-neurological Older Adults on the Wisconsin Card Sorting Test and the Stroop Color-Word Test: Normal Variability or Cognitive Impairment?

Abstract

There is currently no standard criterion for determining abnormal test scores in neuropsychology; thus, a number of different criteria are commonly used. We investigated base rates of abnormal scores in healthy older adults using raw and T-scores from indices of the Wisconsin Card Sorting Test and Stroop Color-Word Test. Abnormal scores were examined cumulatively at seven cutoffs including >1.0, >1.5, >2.0, >2.5, and >3.0 standard deviations (SD) from the mean as well as those below the 10th and 5th percentiles. In addition, the number of abnormal scores at each of the seven cutoffs was also examined. Results showed when considering raw scores, ∼15% of individuals obtained scores>1.0 SD from the mean, around 10% were less than the 10th percentile, and 5% fell >1.5 SD or <5th percentile from the mean. Using T-scores, approximately 15%-20% and 5%-10% of scores were >1.0 and >1.5 SD from the mean, respectively. Roughly 15% and 5% fell at the <10th and <5th percentiles, respectively. Both raw and T-scores>2.0 SD from the mean were infrequent. Although the presence of a single abnormal score at 1.0 and 1.5 SD from the mean or at the 10th and 5th percentiles was not unusual, the presence of ≥2 abnormal scores using any criteria was uncommon. Consideration of base rate data regarding the percentage of healthy individuals scoring in the abnormal range should help avoid classifying normal variability as neuropsychological impairment.

Considering the base rates of low performance in cognitively healthy older adults improves the accuracy to identify neurocognitive impairment with the Consortium to Establish a Registry for Alzheimer’s Disease-Neuropsychological Assessment Battery (CERAD-NAB)

“…2) may be used as an important supplement in clinical practice when assessing cognitive performance and aims to reduce diagnostic errors in clinical decision making. Our main results support a number of studies demonstrating that a substantial percentage of healthy children [37–39], healthy adults [40, 41], and healthy older adults [1, 3, 5, 15] will obtain scores that fall within abnormal ranges when multiple tests are administered.…”

“…Beside these methodological issues, possible explanations for low test performance among these healthy adults may be due to situational or personal factors such as motivational fluctuations, increased distractibility during testing, inattentiveness, and measurement error [20], or also longstanding personal weaknesses in certain areas or intraindividual cognitive variability across different cognitive domains [5, 42]. Another explanation of low scores in cognitively normal adults is the possibility of poor effort.…”

Screening for Neurocognitive Impairment in HIV Individuals: The Utility of the Montreal Cognitive Assessment Test

“…In order to diagnose cognitive impairment, an additional battery of neuropsychological testing were performed which included the Symbol digit modalities test [9] Stroop color and Word test [10] Wechsler adult intellegence-III subtests of Picture Completion [11] Matrix reasoning and Block design [11] and Vocabulary QQ [12] to evaluate various cognitive domains including attention/working memory; speed of information processing inhibition, language; and visuospatial construction. The screening instrument and the battery of neuropsychological tests were chosen based on several criteria: 1) valid and sensitive measures to assess the HIV associated subcortical neurocognitive dysfunction, 2) availablilty in English and Spanish versions, and 3) limited administration time to reduce the burden on the patients.…”

The Value of Bayes’ Theorem for Interpreting Abnormal Test Scores in Cognitively Healthy and Clinical Samples

“…However, there are other situations in neuropsychological assessment that require the use of Bayes' theorem to arrive at a probability estimate appropriate to answer common referral questions about the absence or presence of cognitive impairment. In recent years, an abundance of research has been published documenting the base rates of abnormal test scores in cognitively healthy populations (Binder, Iverson, & Brooks, 2009;Brooks, 2010Brooks, , 2011Brooks, Holdnack, & Iverson, 2011;Brooks, Iverson, & Holdnack, 2013;Brooks, Iverson, & White, 2009;Brooks, Iverson, Holdnack, & Feldman, 2008;Brooks, Iverson, Lanting, Horton, & Reynolds, 2012;Brooks, Iverson, Sherman, & Holdnack, 2009;Brooks, Sherman, & Iverson, 2010;Brooks, Strauss, Sherman, Iverson, & Slick, 2009;Crawford, Garthwaite, & Gault, 2007;Decker, Schneider, & Hale, 2012;Gunner, Miele, Lynch, & McCaffrey, 2012;Palmer, Boone, Lesser, & Wohl, 1998;Schretlen, Munro, Anthony, & Pearlson, 2003;Schretlen, Testa, Winicki, Pearlson, & Gordon, 2008). This research has been highly influential in helping neuropsychologists better understand that abnormal test scores are not pathognomonic of cognitive impairment, and that variables such as the chosen threshold for identifying abnormal test scores, the number of test scores derived from a battery, the correlations of these test scores with one another, and individual characteristics such as premorbid intellect can affect the frequency with which cognitively healthy individuals obtain abnormal scores in a neuropsychological test battery (Brooks, Iverson, & White 2009, 2011Crawford et al, 2007;Decker et al, 2012;Schretlen et al, 2008).…”