Advertisement

Improving Accuracy for Identifying Cognitive Impairment

  • Grant L. Iverson
  • Brian L. Brooks
Chapter

Abstract

Deficit measurement is the sine qua non of neuropsychology. The risk, of course, is that we can be so focused on deficit measurement – and so focused on describing the nature and severity of a person’s cognitive impairment – that we can underappreciate human diversity and overattribute low or unexpected test scores to brain injury or disease. The North American psychometric tradition has long since attempted to minimize possible misattribution of low test scores through a reliance on the normal curve. However, clinicians know that overly formulaic reliance on the normal curve can result in false positive and false negative attributions of cognitive diminishment. Moreover, the normal curve relates to a single test score in relation to a theoretical normal population. Neuropsychologists never rely on single tests. Instead, we administer numerous tests and we interpret performance in combination, not in isolation. Thus, the principles of normative test score interpretation, applied to single test scores, are inherently limited when interpreting performance across a battery of tests.

Cognitive impairment can arise from a single cause or it can have a multifactorial etiology. There are a large number of medical, psychiatric, and neurological diseases, disorders, and conditions that can have an adverse affect on cognition. Clearly, the accurate identification and quantification of cognitive impairment is important in clinical practice, research, and in clinical trials. However, comprehensive, psychometrically-sophisticated guidelines for identifying and quantifying cognitive impairment, across a battery of tests, are not clearly outlined in the neuropsychological literature. The primary exception to this is the work of Reitan and Wolfson for the Halstead Reitan Neuropsychological Battery (Reitan RM, Wolfson D, The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation, Neuropsychology Press, Tucson, AZ, 1985; Reitan RM, Wolfson D, The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation, 2nd edn, Neuropsychology Press, Tucson, AZ, 1993) and Golden and colleagues for the Luria–Nebraska Neuropsychological Battery (Golden C, Purish A, Hammeke T, Manual for the Luria-Nebraska Neuropsychological Battery, Western Psychological Services, Los Angeles, 1985; Golden CJ, Freshwater SM, Vayalakkara J, The Luria-Nebraska neuropsychological battery, in Groth-Marnat G (ed), Neuropsychological assessment in clinical practice: A guide to test interpretation and integration, Wiley, New York, 2000, pp 263-289; Moses JA Jr, Golden CJ, Ariel R, Gustavson JL, Interpretation of the Luria-Nebraska neuropsychological battery (Vol 1), Grune and Stratton, New York, 1983). Considerable psychometric work has been done regarding how to interpret combinations of scores derived from these batteries.

The purpose of this chapter is to provide clinicians with psychometrically sophisticated information that is designed to improve their accuracy for identifying cognitive problems in daily practice. This chapter begins by presenting information on current definitions of cognitive impairment (Conceptualizing Cognitive Impairment). In the second section, we describe some of the various classification systems for conceptualizing cognitive impairment (Classifying Cognitive Impairment). Fundamental psychometric principles, derived from analyses on co-normed batteries of tests, are illustrated in the third section (Evaluating Cognitive Impairment: Five Psychometric Principles to Consider). In the final section, we present new psychometric criteria for identifying cognitive impairment across a battery of neuropsychological measures that adhere to the five psychometric rules (Identifying Cognitive Impairment: New Psychometric Criteria for Cognitive Disorder NOS).

Keywords

Cognitive Impairment Mild Cognitive Impairment False Positive Rate Cutoff Score Intellectual Ability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association.Google Scholar
  2. Antinori, A., Arendt, G., Becker, J. T., Brew, B. J., Byrd, D. A., Cherner, M., et al. (2007). Updated research nosology for HIV-associated neurocognitive disorders. Neurology, 69(18), 1789–1799.PubMedCrossRefGoogle Scholar
  3. Ardila, A. (1995). Directions of research in cross-cultural neuropsychology. Journal of Clinical and Experimental Neuropsychology, 17(1), 143–150.PubMedCrossRefGoogle Scholar
  4. Axelrod, B. N., & Wall, J. R. (2007). Expectancy of impaired neuropsychological test scores in a non-clinical sample. International Journal of Neuroscience, 117(11), 1591–1602.PubMedCrossRefGoogle Scholar
  5. Beatty, W. W., Mold, J. W., & Gontkovsky, S. T. (2003). RBANS performance: influences of sex and education. Journal of Clinical and Experimental Neuropsychology, 25(8), 1065–1069.PubMedCrossRefGoogle Scholar
  6. 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, 31–46.Google Scholar
  7. Brickman, A. M., Cabo, R., & Manly, J. J. (2006). Ethical issues in cross-cultural neuropsychology. Applied Neuropsychology, 13(2), 91–100.PubMedCrossRefGoogle Scholar
  8. Bright, P., Jaldow, E., & Kopelman, M. D. (2002). The National Adult Reading test as a measure of premorbid intelligence: a comparison with estimates derived from demographic variables. Journal of the International Neuropsychological Society, 8(6), 847–854.PubMedCrossRefGoogle Scholar
  9. Brooks, B. L., Iverson, G. L., Holdnack, J. A., & Feldman, H. H. (2008). The potential for misclassification of mild cognitive impairment: A study of memory scores on the Wechsler Memory Scale-III in healthy older adults. Journal of the International Neuropsychological Society, 14(3), 463–478.PubMedCrossRefGoogle Scholar
  10. Brooks, B. L., Iverson, G. L., & White, T. (2007). Substantial risk of “Accidental MCI” in healthy older adults: Base rates of low memory scores in neuropsychological assessment. Journal of the International Neuropsychological Society, 13(3), 490–500.PubMedCrossRefGoogle Scholar
  11. Collaer, M. L., & Nelson, J. D. (2002). Large visuospatial sex difference in line judgment: possible role of attentional factors. Brain and Cognition, 49(1), 1–12.PubMedCrossRefGoogle Scholar
  12. Crawford, J. R., Garthwaite, P. H., & Gault, C. B. (2007). Estimating the percentage of the population with abnormally low scores (or abnormally large score differences) on standardized neuropsychological test batteries: a generic method with applications. Neuropsychology, 21(4), 419–430.PubMedCrossRefGoogle Scholar
  13. Donders, J., Zhu, J., & Tulsky, D. (2001). Factor index score patterns in the WAIS-III standardization sample. Assessment, 8(2), 193–203.PubMedCrossRefGoogle Scholar
  14. Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., et al. (2007). Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria – a position paper. Lancet Neurology, 6, 734–746.PubMedCrossRefGoogle Scholar
  15. Geary, D. C., Saults, S. J., Liu, F., & Hoard, M. K. (2000). Sex differences in spatial cognition, computational fluency, and arithmetical reasoning. Journal of Experimental and Child Psychology, 77(4), 337–353.CrossRefGoogle Scholar
  16. Golden, C., Purish, A., & Hammeke, T. (1985). Manual for the Luria-Nebraska neuropsychological battery. Los Angeles: Western Psychological Services.Google Scholar
  17. Golden, C. J., Freshwater, S. M., & Vayalakkara, J. (2000). The Luria-Nebraska neuropsychological battery. In G. Groth-Marnat (Ed.), Neuropsychological assessment in clinical practice: A guide to test interpretation and integration (pp. 263–289). New York: Wiley.Google Scholar
  18. Green, R. E., Melo, B., Christensen, B., Ngo, L. A., Monette, G., & Bradbury, C. (2008). Measuring premorbid IQ in traumatic brain injury: An examination of the validity of the Wechsler Test of Adult Reading (WTAR). Journal of Clinical and Experimental Neuropsychology, 30(2), 163–172.PubMedCrossRefGoogle Scholar
  19. Griffin, S. L., Mindt, M. R., Rankin, E. J., Ritchie, A. J., & Scott, J. G. (2002). Estimating premorbid intelligence: Comparison of traditional and contemporary methods across the intelligence continuum. Archives of Clinical Neuropsychology, 17(5), 497–507.PubMedGoogle Scholar
  20. Heaton, R. K., Grant, I., & Matthews, C. G. (1991). Comprehensive norms for an extended Halstead-Reitan battery: Demographic corrections, research findings, and clinical applications. Odessa: Psychological Assessment Resources, Inc.Google Scholar
  21. Heaton, R. K., Miller, S. W., Taylor, M. J., & Grant, I. (2004). Revised comprehensive norms for an expanded Halstead-Reitan battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults professional manual. Lutz: Psychological Assessment Resources.Google Scholar
  22. Heaton, R. K., Taylor, M. J., & Manly, J. (2003). Demographic effects and use of demographically corrected norms with the WAIS-III and WMS-III. In D. S. Tulsky, D. H. Saklofske, G. J. Chelune, R. K. Heaton, R. J. Ivnik, R. Bornstein, A. Prifitera, & M. Ledbetter (Eds.), Clinical interpretation of the WAIS-III and WMS-III (pp. 183–210). San Diego: Academic.Google Scholar
  23. Herlitz, A., Nilsson, L. G., & Backman, L. (1997). Gender differences in episodic memory. Memory & Cognition, 25(6), 801–811.CrossRefGoogle Scholar
  24. Horton, A. M., Jr. (1999). Above-average intelligence and neuropsychological test score performance. International Journal of Neuroscience, 99(1–4), 221–231.PubMedCrossRefGoogle Scholar
  25. Ingraham, L. J., & Aiken, C. B. (1996). An empirical approach to determining criteria for abnormality in test batteries with multiple measures. Neuropsychology, 10, 120–124.CrossRefGoogle Scholar
  26. Iverson, G. L., & Brooks, B. L. (in press). New psychometric criteria for DSM-IV cognitive disorder NOS. Journal of the International Neuropsychological Society.Google Scholar
  27. Iverson, G. L., Brooks, B. L., & Ashton, V. L. (2008). Cognitive impairment: Foundations for clinical and forensic practice. In M. P. Duckworth, T. Iezzi, & W. O’Donohue (Eds.), Motor vehicle collisions: Medical, psychosocial, and legal consequences (pp. 243–309). Amsterdam: Academic.Google Scholar
  28. Iverson, G. L., Brooks, B. L., & Holdnack, J. A. (2008). Misdiagnosis of cognitive impairment in forensic neuropsychology. In R. L. Heilbronner (Ed.), Neuropsychology in the courtroom: Expert analysis of reports and testimony (pp. 243–266). New York: Guilford Press.Google Scholar
  29. Iverson, G. L., Brooks, B. L., White, T., & Stern, R. A. (2008). Neuropsychological Assessment Battery (NAB): Introduction and advanced interpretation. In A. M. Horton Jr. & D. Wedding (Eds.), The neuropsychology handbook (3rd ed., pp. 279–343). New York: Springer Publishing Inc.Google Scholar
  30. Ivnik, R. J., Makec, J. F., Smith, G. E., Tangolos, E. G., & Peterson, R. C. (1996). Neuropsychological tests’ norms above age 55: COWAT, BNT, MAE Token, WRAT-R Reading, AMNART, STROOP, TMT, and JLO. The Clinical Neuropsychologist, 10, 262–278.CrossRefGoogle Scholar
  31. Maddrey, A. M., Cullum, C. M., Weiner, M. F., & Filley, C. M. (1996). Premorbid intelligence estimation and level of dementia in Alzheimer’s disease. Journal of the International Neuropsychological Society, 2(6), 551–555.PubMedCrossRefGoogle Scholar
  32. Manly, J. J., & Echemendia, R. J. (2007). Race-specific norms: using the model of hypertension to understand issues of race, culture, and education in neuropsychology. Archives of Clinical Neuropsychology, 22(3), 319–325.PubMedCrossRefGoogle Scholar
  33. Morgan, E. E., Woods, S. P., Scott, J. C., Childers, M., Beck, J. M., Ellis, R. J., et al. (2007). Predictive Validity of Demographically Adjusted Normative Standards for the HIV Dementia Scale. Journal of Clinical and Experimental Neuropsychology, 20, 1–8.Google Scholar
  34. Moses, J. A., Jr., Golden, C. J., Ariel, R., & Gustavson, J. L. (1983). Interpretation of the Luria-Nebraska neuropsychological battery (Vol. 1). New York: Grune and Stratton.Google Scholar
  35. Norman, M. A., Evans, J. D., Miller, W. S., & Heaton, R. K. (2000). Demographically corrected norms for the California Verbal Learning Test. Journal of Clinical and Experimental Neuropsychology, 22(1), 80–94.PubMedCrossRefGoogle Scholar
  36. O’Bryant, S. E., O’Jile, J. R., & McCaffrey, R. J. (2004). Reporting of demographic variables in neuropsychological research: trends in the current literature. The Clinical Neuropsychologist, 18(2), 229–233.PubMedCrossRefGoogle Scholar
  37. Palmer, B. W., Boone, K. B., Lesser, I. M., & Wohl, M. A. (1998). Base rates of “impaired” neuropsychological test performance among healthy older adults. Archives of Clinical Neuropsychology, 13(6), 503–511.PubMedGoogle Scholar
  38. Paolo, A. M., Ryan, J. J., Troster, A. I., & Hilmer, C. D. (1996). Utility of the Barona demographic equations to estimate premorbid intelligence: Information from the WAIS-R standardization sample. Journal of Clinical Psychology, 52(3), 335–343.PubMedCrossRefGoogle Scholar
  39. Patton, D. E., Duff, K., Schoenberg, M. R., Mold, J., Scott, J. G., & Adams, R. L. (2003). Performance of cognitively normal African Americans on the RBANS in community dwelling older adults. The Clinical Neuropsychologist, 17(4), 515–530.PubMedCrossRefGoogle Scholar
  40. Petersen, R. C., Smith, G. E., Ivnik, R. J., Kokmen, E., & Tangalos, E. G. (1994). Memory function in very early Alzheimer’s disease. Neurology, 44(5), 867–872.PubMedCrossRefGoogle Scholar
  41. Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild cognitive impairment: clinical characterization and outcome. Archives of Neurology, 56(3), 303–308.PubMedCrossRefGoogle Scholar
  42. Randolph, C. (1998). Repeatable battery for the assessment of neuropsychological status manual. San Antonio: The Psychological Corporation.Google Scholar
  43. Reitan, R. M., & Wolfson, D. (1985). The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation. Tucson: Neuropsychology Press.Google Scholar
  44. Reitan, R. M., & Wolfson, D. (1993). The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation (2nd ed.). Tucson: Neuropsychology Press.Google Scholar
  45. Reynolds, C. R., & Kamphaus, R. W. (2003). Reynolds intellectual assessment scales and Reynolds intellectual screening test professional manual. Lutz: Psychological Assessment Resources.Google Scholar
  46. Rosselli, M., & Ardila, A. (2003). The impact of culture and education on non-verbal neuropsychological measurements: a critical review. Brain and Cognition, 52(3), 326–333.PubMedCrossRefGoogle Scholar
  47. Ryan, E. L., Baird, R., Mindt, M. R., Byrd, D., Monzones, J., & Bank, S. M. (2005). Neuropsychological impairment in racial/ethnic minorities with HIV infection and low literacy levels: effects of education and reading level in participant characterization. Journal of the International Neuropsychological Society, 11(7), 889–898.PubMedCrossRefGoogle Scholar
  48. Schmidt, S. L., Oliveira, R. M., Rocha, F. R., & Abreu-Villaca, Y. (2000). Influences of handedness and gender on the grooved pegboard test. Brain and Cognition, 44(3), 445–454.PubMedCrossRefGoogle Scholar
  49. Schretlen, D. J., Testa, S. M., Winicki, J. M., Pearlson, G. D., & Gordon, B. (2008). Frequency and bases of abnormal performance by healthy adults on neuropsychological testing. Journal of the International Neuropsychological Society, 14(3), 436–445.PubMedCrossRefGoogle Scholar
  50. Sheslow, D., & Adams, W. (2003). Wide range assessment of memory and learning (Administration and technical manual 2nd ed.). Wilmington: Wide Range, Inc.Google Scholar
  51. Steinberg, B. A., Bieliauskas, L. A., Smith, G. E., & Ivnik, R. J. (2005a). Mayo’s Older Americans Normative Studies: Age- and IQ-Adjusted Norms for the Trail-Making Test, the Stroop Test, and MAE Controlled Oral Word Association Test. The Clinical Neuropsychologist, 19(3–4), 329–377.PubMedGoogle Scholar
  52. Steinberg, B. A., Bieliauskas, L. A., Smith, G. E., Ivnik, R. J., & Malec, J. F. (2005b). Mayo’s Older Americans Normative Studies: Age- and IQ-Adjusted Norms for the Auditory Verbal Learning Test and the Visual Spatial Learning Test. The Clinical Neuropsychologist, 19(3–4), 464–523.PubMedGoogle Scholar
  53. Stern, R. A., & White, T. (2003). Neuropsychological assessment battery. Lutz: Psychological Assessment Resources.Google Scholar
  54. Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary (3rd ed.). New York: Oxford University Press.Google Scholar
  55. The Psychological Corporation. (2001). Wechsler test of adult reading manual. San Antonio: Psychological Corporation.Google Scholar
  56. Tremont, G., Hoffman, R. G., Scott, J. G., & Adams, R. L. (1998). Effect of intellectual level on neuropsychological test performance: A response to Dodrill (1997). The Clinical Neuropsychologist, 12, 560–567.CrossRefGoogle Scholar
  57. Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: a meta-analysis and consideration of critical variables. Psychological Bulletin, 117(2), 250–270.PubMedCrossRefGoogle Scholar
  58. Warner, M. H., Ernst, J., Townes, B. D., Peel, J., & Preston, M. (1987). Relationships between IQ and neuropsychological measures in neuropsychiatric populations: within-laboratory and cross-cultural replications using WAIS and WAIS-R. Journal of Clinical and Experimental Neuropsychology, 9(5), 545–562.PubMedCrossRefGoogle Scholar
  59. Wechsler, D. (1997a). Wechsler adult intelligence scale (3rd ed.). San Antonio: Psychological Corporation.Google Scholar
  60. Wechsler, D. (1997b). Wechsler memory scale (3rd ed.). San Antonio: The Psychological Corporation.Google Scholar
  61. White, T., & Stern, R. A. (2003). Neuropsychological assessment battery: Psychometric and technical manual. Lutz: Psychological Assessment Resources.Google Scholar
  62. World Health Organization. (1992). International statistical classification of diseases and related health problems (10th ed.). Geneva, Switzerland: World Health Organization.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.British Columbia Mental Health & AddictionsUniversity of British ColumbiaVancouverCanada

Personalised recommendations