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Modeling the Ecological Validity of Neurocognitive Assessment in Adults with Acquired Brain Injury

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Abstract

Neuropsychologists are increasingly asked to make judgments regarding treatment options and rehabilitation strategies in addition to evaluating the degree and scope of neuropsychological impairment following acquired brain injuries. The capacity to make informed clinical decisions relies upon research investigating the relationships between neuropsychological and psychosocial status (i.e., ecological validity). Unfortunately, much of this research employs exploratory analyses, an approach that can lead to theoretical ambiguity and ad-hoc interpretations. The current availability and accessibility of analytical tools, like structural equation modeling (SEM), however, permits the testing of specific hypotheses regarding ecological validity and promotes a-priori theory development. In the current study, a theory-driven model of the ecological validity of a neurocognitive assessment was tested against data obtained from individuals with acquired brain injury using SEM. The results provide confirmatory evidence for the ecological validity of neurocognitive constructs and empirical support for a theory-driven analytical approach to ecological validity research.

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References

  • Barth, J. T., Macciocchi, S. N., & Diamond, P. T. (1999). Mild head injury: Current research and clinical issues. In M. Rosenthal, E. R.Griffith, J. S. Dreutzer, & B. Pentland (Eds.), Rehabilitation of the adult and child with traumatic brain injury (3rd ed., pp. 471–502). Philadelphia, PA: F. A. Davis Company.

    Google Scholar 

  • Chaytor, N., & Schmitter-Edgercombe, M. (2003). The ecological validity of neuropsychological tests: A review of the literature on everyday cognitive skills. Neuropsychology Review, 13, 181–197.

    Article  PubMed  Google Scholar 

  • Cullum, C. M., Kuck, J., & Ruff, R. M. (1990). Neuropsychological assessment of traumatic brain injury in adults. In E. D. Bigler (Ed.), Traumatic brain injury (pp. 129–157). Austin, TX: Pro-Ed.

    Google Scholar 

  • Cushman, L. A. (1989). Correspondence between neuropsychological and functional ratings of perceptual neglect. Neuropsychology, 3, 103–109.

    Article  Google Scholar 

  • Dikmen, S., Machamer, J., Savoie, T., & Temkin, N. (1996). Life quality outcome in head injury. In I. Grant, & K. M. Adams (Eds.), Neuropsychological assessment of neuropsychiatric disorders (pp. 552–573). Oxford, NY: Oxford University Press.

    Google Scholar 

  • Drake, A., Gray, N., Yoder, S., Pramuka, M., & Llewellyn, M. (2000). Factors predicting return to work following mild traumatic brain injury: A discriminant analysis. Journal of Head Trauma Rehabilitation, 15, 1103–1112.

    Article  PubMed  CAS  Google Scholar 

  • Evans, J. J., Wilson, B. A., Needham, P., & Brentnall, S. (2003). Who makes good use of memory aids? Results of a survey of people with acquired brain injury. Journal of the International Neuropsychological Society, 9, 925–935.

    Article  PubMed  Google Scholar 

  • Farias, S. T., Harrell, E., Neumann, C., & Houtz, A. (2003). The relationship between neuropsychological performance and daily functioning in individuals with Alzheimer’s disease: Ecological validity of neuropsychological tests. Archives of Clinical Neuropsychology, 18, 655–672.

    Article  PubMed  Google Scholar 

  • Fleming, J. M., Strong, J., & Ashton, R. (1996). Self-awareness of deficits in adults with traumatic brain injury: How best to measure? Brain Injury, 10, 1–15.

    Article  PubMed  CAS  Google Scholar 

  • Gronwall, D. (1987). Advances in the assessment of attention and information processing after head injury. In H. S. Levin, J. Grafman, & H. M. Eisenberg (Eds.), Neurobehavioral recovery from head injury (pp. 355–371). New York: Oxford University Press.

    Google Scholar 

  • Gruber, O., & Goschke, T. (2004) Executive control emerging from dynamic interactions between brain systems mediating language, working memory and attentional processes. Acta Psychologica, 115, 105–121.

    Article  PubMed  Google Scholar 

  • Heilbronner, R. L., Millsaps, C., Azrin, R., & Mittenberg, W. (1993). Psychometric properties of the Patient Competency Rating Scale. Journal of Clinical and Experimental Neuropsychology, 15, 67.

    Google Scholar 

  • Johansson, U., & Bernspång, B. (2001). Predicting return to work after brain injury using occupational therapy assessments. Disability and Rehabilitation, 23, 474–480.

    Article  PubMed  CAS  Google Scholar 

  • Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: User’s guide. Chicago, IL: Scientific Software.

    Google Scholar 

  • Kreutzer, J. S., Marwitz, J. H., Walker, W., Sander, A., Sherer, M., Bogner, J., et al. (2003). Moderating factors in return to work and job stability after traumatic brain injury. Journal of Head Trauma Rehabilitation, 18, 128–138.

    PubMed  Google Scholar 

  • Leathem, J. M., Murphy, L. J., & Flen, R. A. (1998). Self and informant-ratings on the Patient Competency Rating Scale in patients with traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 20, 694–705.

    Article  PubMed  CAS  Google Scholar 

  • Lezak, M. D. (1976). Neuropsychological assessment. New York, NY: Oxford University Press.

    Google Scholar 

  • Manoach, D. S., Sandson, T. A., & Weintraub, S. (1995). The developmental social-emotional processing disorder is associated with right hemisphere abnormalities. Neuropsychiatry, Neuropsychology and Behavioral Neurology, 8, 99–105.

    Google Scholar 

  • Marsh, N. V., & Knight, R. G. (1991). Relationship between cognitive deficits and social skill after head injury. Neuropsychology, 5, 107–117.

    Article  Google Scholar 

  • McHugo, G. J., Drake, R. E., Brunette, M. F., Xie, H., Essock, S. M., & Green, A. I. (2006). Enhancing validity in co-occurring disorders treatment research. Schizophrenia Bulletin, 32, 655–665.

    Article  PubMed  Google Scholar 

  • McSweeny, A. J., Grant, I., Heaton, R. K., Prigatano, G. P., & Adams, K. M. (1985). Relationship of neuropsychological status to everyday functioning in healthy and chronically ill persons. Journal of Clinical and Experimental Neuropsychology, 7, 281–291.

    PubMed  CAS  Google Scholar 

  • Miller, E. (1970). Simple and choice reaction time following severe head injury. Cortex, 6, 121–127.

    PubMed  CAS  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 9, 599–620.

    Article  Google Scholar 

  • Platt, J. R. (1964) Strong inference. Science, 146, 347–353.

    Article  PubMed  Google Scholar 

  • Powell, D. H., Kaplan, E. F., Whitla, D., Weintraub, S., Catlin, R., & Funkenstein, H. H. (1993). MicroCog assessment of cognitive functioning. San Antonio, TX: Harcourt Brace & Company, pp. 1–15.

    Google Scholar 

  • Prigatano, G. P. (1986). Neuropsychological rehabilitation after brain injury. Baltimore, MD: Johns Hopkins University Press.

    Google Scholar 

  • Prigatano, G. P. (1989). Work, love, and play after brain injury. Bulletin of the Menninger Clinic, 53, 414–431.

    PubMed  CAS  Google Scholar 

  • Prigatano, G. P., Altman, I. M., & O’Brien, K. P. (1990). Behavioral limitations that brain injured patients tend to underestimate. Clinical Neuropsychologist, 4, 163–176.

    Google Scholar 

  • Prigatano, G. P., & Klonoff, P. S. (1998). A clinician’s rating scale for evaluating impaired self-awareness and denial of disability after brain injury. Clinical Neuropsychologist, 12, 56–67.

    Google Scholar 

  • Raskin, S. A., Mateer, C. A., & Tweeten, R. (1998). Neuropsychological assessment of individuals with mild traumatic brain injury. Clinical Neuropsychologist, 12, 21–30.

    Google Scholar 

  • Raykov, T., & Marcoulides, G. A. (2000). A first course in structural equation modeling. Lawrence Earlbaum & Associates: Mahwah, NJ: Lawrence Erlbaum Associates, Publishers, pp. 6–56.

    Google Scholar 

  • Sarno, S., Erasmus, L., Lipp, B., & Schlaegel, W. (2003). Multisensory integration after traumatic brain injury: A reaction time study between pairings of vision, touch, and audition. Brain Injury, 17, 413–426.

    Article  PubMed  Google Scholar 

  • Sbordone, R. J. (1996). Ecological validity: Some critical issues for the neuropsychologist. In R.J. Sbordone, & C.D. Long (Eds.), Ecological validity of neuropsychological testing (pp. 15–40). Delray Beach, FL: GR Press/St Lucie Press, Inc.

    Google Scholar 

  • Sbordone, R. J., & Guilmette, T. J. (1999). Ecological validity: Prediction of everyday and vocational functioning from neuropsychological test data. In J. J. Sweet (Ed.), Forensic neuropsychology: Fundamentals and practice. Studies on neuropsychology, development, and cognition. (pp. 227–254). Netherlands: Swets & Zeitlinger Publishers.

    Google Scholar 

  • Sbordone, R. J., Liter, J. C., & Pettler-Jennings, P. (1995). Recovery of function following severe traumatic brain injury: A retrospective 10-year follow up. Brain Injury, 9, 285–299.

    PubMed  CAS  Google Scholar 

  • Sbordone, R. J., & Purisch, A. D. (1996). Hazards of blind analysis of neuropsychological test data in assessing cognitive disability: The role of psychological pain and other confounding factors. Neurorehabilitation, 7, 15–26.

    Article  Google Scholar 

  • Shamary-Tsoory, S. G., Tomer, R., Berger, B. D., & Aharon-Peretz, J. (2003). Characterization of empathy deficits following prefrontal brain damage: The role of the right ventromedial prefrontal cortex. Journal of Cognitive Neuroscience, 15, 324–337.

    Article  Google Scholar 

  • Stout, J. C., Ready, R. E., Grace, J., Malloy, P. F., & Paulsen, J. S. (2003a). Factor analysis of the Frontal Systems Behavior Scale (FrSBe). Assessment, 10, 79–85.

    Article  PubMed  Google Scholar 

  • Stout, J. C., Wyman, M. F., Johnson, S. A., Peavy, G. M., & Salmon, D. P. (2003b). Frontal behavioral syndromes and functional status in probable Alzheimer disease. American Journal of Geriatric Psychiatry, 11, 683–686.

    Article  PubMed  Google Scholar 

  • Vogel, J. J., Bowers, C. A., & Vogel, D. S. (2003). Cerebral lateralization of spatial abilities: A meta-analysis. Brain & Cognition, 52, 197–204.

    Article  Google Scholar 

  • West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with non-normal variables: Problems and remedies. In R. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • Williams, J. M. (1996). A practical model of everyday memory assessment. In R. Sbordone, & C. Long (Eds.), Ecological validity of neuropsychological testing (pp. 129–145). Delray Beach, FL: GR Press/St. Lucie Press.

    Google Scholar 

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Acknowledgement

We are grateful to Dr. R. Sbordone, for his helpful comments and consultation regarding this research.

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Correspondence to Paul D. Kieffaber.

Appendices

Appendix A: Items Removed from the PCRS

   

Appendix B: Factor Structure Matrix for the Patient Competency Rating Scale

   

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Kieffaber, P.D., Marcoulides, G.A., White, M.H. et al. Modeling the Ecological Validity of Neurocognitive Assessment in Adults with Acquired Brain Injury. J Clin Psychol Med Settings 14, 206–218 (2007). https://doi.org/10.1007/s10880-007-9075-6

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