Kristian P Nitsch1, Kaitlin B Casaletto2, Noelle E Carlozzi3, David S Tulsky4, Allen W Heinemann5, Robert K Heaton6. 1. Department of Psychology, Illinois Institute of Technology. 2. Department of Neurology, University of California, San Francisco. 3. Department of Physical Medicine and Rehabilitation, University of Michigan. 4. Center on Assessment Research and Translation, University of Delaware. 5. Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine. 6. Department of Psychiatry, University of California, San Diego.
Abstract
OBJECTIVE: The association between demographic characteristics and neurocognitive performance is well established; however, clinicians may have difficulty selecting when to use uncorrected versus demographically corrected scores. We compared these score types in individuals with traumatic brain injury (TBI) and stroke, on the National Institutes of Health Toolbox-Cognition Battery (NIHTB-CB). RESEARCH METHOD: Adults with TBI and stroke were demographically matched to controls, and completed the NIHTB-CB. Published "corrected scores" are adjusted for age, education, sex, and race/ethnicity; "uncorrected scores" were created using census data to represent the average adult in the U.S. RESULTS: Effect sizes for the TBI and stroke groups versus controls were larger using corrected scores compared with uncorrected scores for the fluid composite (uncorrected to corrected effect sizes: TBI: d = 0.66, p < .001 to 0.83, p < .001; stroke d = 0.97, p < .001 to 1.10, p < .001). For the crystallized composite, effect sizes for the TBI and stroke groups versus controls were smaller and nonsignificant using corrected scores (uncorrected to corrected effect sizes: TBI d = 0.23, p = .03 to 0.20, p = .06; stroke d = 0.40, p < .001 to 0.17, p = .09). In the injury groups, demographic characteristics accounted for up to 33% of variance in uncorrected scores (p < .001), but <5% of variance in corrected scores (p > .06). CONCLUSIONS: Corrected scores were more sensitive to neurocognitive impairments in the brain-injured groups. Corrected scores have the advantage of controlling for variance associated with premorbid factors rather than changes in neurological functioning; are more helpful in characterizing acquired neurocognitive changes; and can aid in the interpretation of test performance. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
OBJECTIVE: The association between demographic characteristics and neurocognitive performance is well established; however, clinicians may have difficulty selecting when to use uncorrected versus demographically corrected scores. We compared these score types in individuals with traumatic brain injury (TBI) and stroke, on the National Institutes of Health Toolbox-Cognition Battery (NIHTB-CB). RESEARCH METHOD: Adults with TBI and stroke were demographically matched to controls, and completed the NIHTB-CB. Published "corrected scores" are adjusted for age, education, sex, and race/ethnicity; "uncorrected scores" were created using census data to represent the average adult in the U.S. RESULTS: Effect sizes for the TBI and stroke groups versus controls were larger using corrected scores compared with uncorrected scores for the fluid composite (uncorrected to corrected effect sizes: TBI: d = 0.66, p < .001 to 0.83, p < .001; stroke d = 0.97, p < .001 to 1.10, p < .001). For the crystallized composite, effect sizes for the TBI and stroke groups versus controls were smaller and nonsignificant using corrected scores (uncorrected to corrected effect sizes: TBI d = 0.23, p = .03 to 0.20, p = .06; stroke d = 0.40, p < .001 to 0.17, p = .09). In the injury groups, demographic characteristics accounted for up to 33% of variance in uncorrected scores (p < .001), but <5% of variance in corrected scores (p > .06). CONCLUSIONS: Corrected scores were more sensitive to neurocognitive impairments in the brain-injured groups. Corrected scores have the advantage of controlling for variance associated with premorbid factors rather than changes in neurological functioning; are more helpful in characterizing acquired neurocognitive changes; and can aid in the interpretation of test performance. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Authors: Jennifer J Manly; Diane M Jacobs; Pegah Touradji; Scott A Small; Yaakov Stern Journal: J Int Neuropsychol Soc Date: 2002-03 Impact factor: 2.892
Authors: Philip David Zelazo; Jacob E Anderson; Jennifer Richler; Kathleen Wallner-Allen; Jennifer L Beaumont; Sandra Weintraub Journal: Monogr Soc Res Child Dev Date: 2013-08
Authors: Kaitlin B Casaletto; Anya Umlauf; Jennifer Beaumont; Richard Gershon; Jerry Slotkin; Natacha Akshoomoff; Robert K Heaton Journal: J Int Neuropsychol Soc Date: 2015-06-01 Impact factor: 2.892
Authors: Michael C Diehr; Mariana Cherner; Tanya J Wolfson; S Walden Miller; Igor Grant; Robert K Heaton Journal: J Clin Exp Neuropsychol Date: 2003-06 Impact factor: 2.475
Authors: Sandra Weintraub; Sureyya S Dikmen; Robert K Heaton; David S Tulsky; Philip D Zelazo; Patricia J Bauer; Noelle E Carlozzi; Jerry Slotkin; David Blitz; Kathleen Wallner-Allen; Nathan A Fox; Jennifer L Beaumont; Dan Mungas; Cindy J Nowinski; Jennifer Richler; Joanne A Deocampo; Jacob E Anderson; Jennifer J Manly; Beth Borosh; Richard Havlik; Kevin Conway; Emmeline Edwards; Lisa Freund; Jonathan W King; Claudia Moy; Ellen Witt; Richard C Gershon Journal: Neurology Date: 2013-03-12 Impact factor: 9.910
Authors: Yue Ma; Cynthia M Carlsson; Michelle L Wahoske; Hanna M Blazel; Richard J Chappell; Sterling C Johnson; Sanjay Asthana; Carey E Gleason Journal: J Int Neuropsychol Soc Date: 2020-10-05 Impact factor: 2.892
Authors: Abigail S Greene; Xilin Shen; Stephanie Noble; Corey Horien; C Alice Hahn; Jagriti Arora; Fuyuze Tokoglu; Marisa N Spann; Carmen I Carrión; Daniel S Barron; Gerard Sanacora; Vinod H Srihari; Scott W Woods; Dustin Scheinost; R Todd Constable Journal: Nature Date: 2022-08-24 Impact factor: 69.504