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Construct validity of cognitive reserve in a multiethnic cohort: The Northern Manhattan Study

Published online by Cambridge University Press:  01 July 2009

KAREN L. SIEDLECKI ,
YAAKOV STERN ,
AARON REUBEN ,
RALPH L. SACCO ,
MITCHELL S.V. ELKIND  and
CLINTON B. WRIGHT
KAREN L. SIEDLECKI
Affiliation:
Cognitive Neuroscience Division, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
YAAKOV STERN*
Affiliation:
Cognitive Neuroscience Division, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
AARON REUBEN
Affiliation:
Cognitive Neuroscience Division, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
RALPH L. SACCO
Affiliation:
Division of Cognitive Disorders, Department of Neurology, Miller School of Medicine, University of Miami, Miami, Florida Evelyn F. McKnight Center for Age Related Memory Loss, Miller School of Medicine, University of Miami, Miami, Florida
MITCHELL S.V. ELKIND
Affiliation:
Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
CLINTON B. WRIGHT
Affiliation:
Division of Cognitive Disorders, Department of Neurology, Miller School of Medicine, University of Miami, Miami, Florida Evelyn F. McKnight Center for Age Related Memory Loss, Miller School of Medicine, University of Miami, Miami, Florida
*
*Correspondence and reprint requests to: Yaakov Stern, Cognitive Neuroscience Division, College of Physicians and Surgeons, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, 630 West 168th Street, New York, New York 10032. E-mail: [email protected]
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Abstract

Cognitive reserve is a hypothetical construct that has been used to inform models of cognitive aging and is presumed to be indicative of life experiences that may mitigate the effects of brain pathology. The purpose of this study was to evaluate the construct validity of cognitive reserve by examining both its convergent and its discriminant validity across three different samples of participants using structural equation modeling. The cognitive reserve variables were found to correlate highly with one another (thereby providing evidence of convergent validity), but demanding tests of discriminant validity indicated that, in two of the samples, the cognitive reserve construct was highly related to an executive functioning construct. (JINS, 2009, 15, 558–569.)

Keywords

Construct validityCognitionCognitive reserveExecutive functioningNeuropsychologyStructural equation modeling
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 4 , July 2009 , pp. 558 - 569
Copyright
Copyright © The International Neuropsychological Society 2009

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References

REFERENCES

Albert, M.S., Jones, K., Savage, C.R., Berkman, L., Seeman, T., Blazer, D., & Rowe, J.W. (1995). Predictors of cognitive change in older persons: MacArthur studies of successful aging. Psychology and Aging, 10, 578–589.CrossRefGoogle ScholarPubMed
Arbuckle, J.L. (2003). Amos 5.0. Chicago, IL: SPSS.Google Scholar
Buschke, H. & Fuld, P.A. (1974). Evaluating storage, retention, and retrieval in disordered memory and learning. Neurology, 24, 1019–1025.CrossRefGoogle ScholarPubMed
Cattell, R.B. (1987). Intelligence: Its structure, growth and action. Amsterdam, The Netherlands: Elsevier.Google Scholar
Christensen, H. (2001). What cognitive changes can be expected with normal ageing? The Australian and New Zealand Journal of Psychiatry, 35, 768–775.Google Scholar
Christensen, H., Korten, A.E., Jorm, A.F., Henderson, A.S., Jacomb, P.A., Rodgers, B., & MacKinnon, A.J. (1997). Education and decline in cognitive performance: Compensatory but not protective. International Journal of Geriatric Psychiatry, 12, 323–330.3.0.CO;2-N>CrossRefGoogle Scholar
D’Elia, L.F., Satz, P., Uchiyama, C.L., & White, T. (1996). Color Trails Test. Professional manual. Odessa, FL: Psychological Assessment Resources.Google Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (2000). California Verbal Learning Test-second edition: Adult version. Manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Del Ser, T., González-Montalvo, J., Martínez-Espinosa, S., Delgado-Villapalos, C., & Bermejo, F. (1997). Estimation of pre-morbid intelligence in Spanish people with the Word Accentuation Test and its application to the diagnosis of dementia. Brain and Cognition, 33, 343–356.Google Scholar
Dunn, L.M. & Dunn, L.M. (1997). Examiner’s manual for the Peabody Picture Vocabulary Test-third edition. Circle Pines, MN: American Guidance Service.Google Scholar
Evans, D.A., Hebert, L.E., Beckett, L.A., Scherr, P.A., Albert, M.S., Chown, M.J., Pilgrim, D.M., & Taylor, J.O. (1997). Education and other measures of socioeconomic status and risk of incident Alzheimer disease in a defined population of older person. Archives of Neurology, 54, 1399–1405.Google Scholar
Farmer, M.E., Kittner, S.J., Rae, D.S., Bartko, J.J., & Regier, D.A. (1995). Education and change in cognitive function: The epidemiologic catchment area study. Annals of Epidemiology, 5, 1–7.Google Scholar
Flowers, K.A. & Robertson, C. (1985). The effect of Parkinson’s disease on the ability to maintain a mental set. Journal of Neurology, Neurosurgery, and Psychiatry, 48, 517–529.Google Scholar
Folstein, M., Folstein, S., & McHugh, P. (1975). “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., & Curtiss, G. (1993). Wisconsin Card Sorting Test manual-revised and expanded. Lutz, FL: Psychological Assessment Resource.Google Scholar
Horn, J.L. (1982). The aging of human abilities. In Wolman, B.B. (Ed.), Handbook of developmental psychology (pp. 847–870). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Hu, L.-T. & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55.Google Scholar
Letenneur, L., Commenges, D., Dartigues, J.F., & Barberger-Gateau, P. (1994). Incidence of dementia and Alzheimer’s disease in elderly community residents of south-western France. International Journal of Epidemiology, 23, 1256–1261.Google Scholar
Matthews, C.G. & Klove, H. (1964). Instruction manual for the Adult Neuropsychology Test Battery. Madison, WI: University of Wisconsin Medical School.Google Scholar
Nelson, H.E. (1982). National Adult Reading Test. Windsor, UK: NFER-Nelson.Google Scholar
Prabhakaran, S., Wright, C.B., Yoshita, M., Delapaz, R., Brown, T., DeCarli, C., & Sacco, R.L. (2008). Prevalence and determinants of subclinical brain infarction: The Northern Manhattan Study. Neurology, 70, 425–430.CrossRefGoogle ScholarPubMed
Qiu, C.X., Backman, L., Winblad, B., Aguero-Torres, H., & Frtiglioni, L. (2001). The influence of education on clinical diagnosed dementia: Incidence and mortality data from the Kungsholmen Project. Archives of Neurology, 58, 2034–2039.Google Scholar
Raven, J. (1962). Advanced progressive matrices, set II. London, UK: H.K. Lewis.Google Scholar
Reitan, R.M. & Wolfson, D. (1993). The Halstead–Reitan Neuropsychological Test Battery: Theory and clinical interpretation (2nd ed.). Tucson, AZ: Neuropsychology Press.Google Scholar
Sacco, R.L., Boden-Albala, B., Abel, G., Lin, I-F., Elkind, M., Hauser, W.A., Paik, M.C., & Shea, S. (2001). Race-ethnic disparities in the impact of stroke risk factors: The northern Manhattan stroke study. Stroke, 32, 1725–1731.CrossRefGoogle ScholarPubMed
Salthouse, T.A. (2004). What and when of cognitive aging. Current Directions in Psychological Science, 13, 140–144.CrossRefGoogle Scholar
Salthouse, T.A. (2006). Mental exercise and mental aging. Perspectives on Psychological Science, 1, 68–87.Google Scholar
Salthouse, T.A., Atkinson, T.M., & Berish, D.E. (2003). Executive functioning as a potential mediator of age-related cognitive decline in normal adults. Journal of Experimental Psychology. General, 132, 566–594.Google Scholar
Salthouse, T.A., Berish, D.E., & Siedlecki, K.L. (2004). Construct validity and age sensitivity of prospective memory. Memory & Cognition, 32, 1133–1148.CrossRefGoogle ScholarPubMed
Siedlecki, K.L., Salthouse, T.A., & Berish, D.E. (2005). Is there anything special about the aging of source memory? Psychology and Aging, 20, 19–32.CrossRefGoogle ScholarPubMed
Spearman, C. (1904). “General intelligence” objectively determined and measured. The American Journal of Psychology, 15, 8–20.Google Scholar
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448–460.CrossRefGoogle ScholarPubMed
Stern, Y. (in press ). Cognitive reserve. Neuropsychologia.Google Scholar
Stern, Y., Gurland, B., Tatemichi, T.K., Tang, M.X., Wilder, D., & Mayeux, R. (1994). Influence of education and occupation on the incidence of Alzheimer’s disease. The Journal of the American Medical Association, 271, 1004–1010.CrossRefGoogle ScholarPubMed
Stern, Y., Tang, M.X., Denaro, J., & Mayeux, R. (1995). Increased risk of mortality in Alzheimer’s disease patients with more advanced educational and occupational attainment. Annals of Neurology, 37, 590–595.CrossRefGoogle ScholarPubMed
Valenzuela, M.J. & Sachdev, P. (2005). Brain reserve and dementia: A systematic review. Psychological Medicine, 35, 1–14.Google Scholar
Wechsler, D. (1981). Wechsler Adult Intelligence Scale-Revised. New York: The Psychological Corporation.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale-third edition. San Antonio, TX: The Psychological Corporation.Google Scholar
White, L., Katzman, R., Losonczy, K., Salive, M., Wallace, R., Berkman, L., Taylor, J., Fillenbaum, G., & Havlik, R. (1994). Association of education with incidence of cognitive impairment in three established populations for epidemiologic studies of the elderly. Journal of Clinical Epidemiology, 47, 363–374.Google Scholar
Wilkinson, G.S. (1993). The Wide Range Achievement Test: Manual (3rd ed.). Wilmington, DE: Wide Range.Google Scholar
Wright, C.B., Festa, J.R., Paik, M.C., Schmiedigen, A., Brown, T.R., Yoshita, M., DeCarli, C., Sacco, R., & Stern, Y. (2008). White matter hyperintensities and subclinical infarction: Associations with psychomotor speed and cognitive flexibility. Stroke, 39, 800–805.Google Scholar
Zhang, M., Katzman, R., Salmon, D., Jin, H., Cai, G., Wang, Z., Qu, G., Grant, I., Yu, E., Levy, P., Klauber, M.R., & Liu, W.T. (1990). The prevalence of dementia and Alzheimer’s disease in Shanghai, China: Impact of age, gender and education. Annals of Neurology, 27, 428–437.Google Scholar