Hostname: page-component-77c89778f8-gq7q9 Total loading time: 0 Render date: 2024-07-21T13:54:08.910Z Has data issue: false hasContentIssue false

Self-perceived Difficulties in Everyday Function Precede Cognitive Decline among Older Adults in the ACTIVE Study

Published online by Cambridge University Press:  11 August 2017

Sarah Tomaszewski Farias*
Affiliation:
Department of Neurology, University of California, Sacramento, California
Tania Giovannetti
Affiliation:
Department of Psychology, Temple University, Philadelphia, Pennsylvania
Brennan R. Payne
Affiliation:
Department of Psychology, University of Utah, Salt Lake City, Utah
Michael Marsiske
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
George W. Rebok
Affiliation:
Department of Mental Health, Johns Hopkins Center on Aging and Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
K. Warner Schaie
Affiliation:
Center for Integrated Brain Research (CIBR), Seattle Children’s Research Institute, University of Washington, Seattle, Washington
Kelsey R. Thomas
Affiliation:
VA San Diego Healthcare System and Department of Psychiatry, University of California, San Diego, California
Sherry L. Willis
Affiliation:
Center for Integrated Brain Research (CIBR), Seattle Children’s Research Institute, University of Washington, Seattle, Washington
Joseph M. Dzierzewski
Affiliation:
Departments of Epidemiology and Mental Psychology, Virginia Commonwealth University, Richmond, Virginia
Frederick Unverzagt
Affiliation:
Department of Neurology, Indiana University of Pennsylvania, Indiana, Pennsylvania
Alden L. Gross
Affiliation:
Johns Hopkins Center on Aging and Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
*
Correspondence and reprint requests to: Sarah Tomaszewski Farias, University of California, Davis, Department of Neurology 4860 Y Street, suite 3700 Sacramento CA 95817. E-mail: farias@ucdavis.edu

Abstract

Objectives: Careful characterization of how functional decline co-evolves with cognitive decline in older adults has yet to be well described. Most models of neurodegenerative disease postulate that cognitive decline predates and potentially leads to declines in everyday functional abilities; however, there is mounting evidence that subtle decline in instrumental activities of daily living (IADLs) may be detectable in older individuals who are still cognitively normal. Methods: The present study examines how the relationship between change in cognition and change in IADLs are best characterized among older adults who participated in the ACTIVE trial. Neuropsychological and IADL data were analyzed for 2802 older adults who were cognitively normal at study baseline and followed for up to 10 years. Results: Findings demonstrate that subtle, self-perceived difficulties in performing IADLs preceded and predicted subsequent declines on cognitive tests of memory, reasoning, and speed of processing. Conclusions: Findings are consistent with a growing body of literature suggesting that subjective changes in everyday abilities can be associated with more precipitous decline on objective cognitive measures and the development of mild cognitive impairment and dementia. (JINS, 2018, 24, 104–112)

Type
Special Section: Lifespan Neuropsychology
Copyright
Copyright © The International Neuropsychological Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Albert, M.S., DeKosky, S.T., Dickson, D., Dubois, B., Feldman, H.H., Fox, N.C., & Snyder, P.J. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7, 270279.CrossRefGoogle ScholarPubMed
Amariglio, R.E., Mormino, E.C., Pietras, A.C., Marshall, G.A., Vannini, P., Johnson, K.A., & Rentz, D.M. (2015). Subjective cognitive concerns, amyloid-ß, and neurodegeneration in clinically normal elderly. Neurology, 85, 5662.Google Scholar
Andersen, C.K., Wittrup-Jensen, K.U., Lolk, A., Andersen, K., & Kragh-Sørensen, P. (2004). Ability to perform activities of daily living is the main factor affecting quality of life in patients with dementia. Health and Quality of Life Outcomes, 2, 52.Google Scholar
Aretouli, E., & Brandt, J. (2010). Everyday functioning in mild cognitive impairment and its relationship with executive cognition. International Journal of Geriatric Psychiatry, 25, 224233.Google Scholar
Bollen, K. (1989). Structural equations with latent variables. New York: John Wiley.Google Scholar
Brandt, J. (1991). The Hopkins Verbal Learning Test: Development of a new memory test with six equivalent forms. The Clinical Neuropsychologist, 5, 125142.Google Scholar
Burdick, D.J., Rosenblatt, A., Samus, Q.M., Steele, C., Baker, A., Harper, M., & Rosenblatt, A. (2005). Predictors of functional impairment in residents of assisted-living facilities: The Maryland Assisted Living Study. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 60, 258264.Google Scholar
Burton, C.L., Strauss, E., Hultsch, D.F., & Hunter, M.A. (2006). Cognitive functioning and everyday problem solving in older adults. The Clinical Neuropsychologist, 20, 432452.Google Scholar
Cahn-Weiner, D., Tomaszewski Farias, S., Julian, L., Kramer, J.H., Reed, B.R., Mungas, D., & Wetzel, M. (2007). Cognitive and neuroimaging predictors of instrumental activities of daily living. Journal of International Neuropsychological Society, 13, 737757.Google Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Edition). Hillsdale, NJ: Lawrence Earlbaum Associates.Google Scholar
Eslinger, P.J., & Damasio, A.R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation patient EVR. Neurology, 35, 17311731.Google Scholar
Ekstrom, R., French, J., Harman, H., & Derman, D. (1976). Kit of factor-referenced cognitive tests, revised. Princeton, NJ: Educational Testing Service.Google Scholar
Fong, T.G., Gleason, L.J., Wong, B., Habtemariam, D., Jones, R.N., Schmitt, E.M., & Inouye, S.K. (2015). Cognitive and physical demands of activities of daily living in older adults: Validation of expert panel ratings. PM & R, 7, 727735.Google Scholar
Gerstorf, D., Lovden, M., Rocke, C., Smith, J., & Lindenberger, U. (2007). Well-being affects changes in perceptual speed in advanced old age: Longitudinal evidence for a dynamic link. Developmental Psychology, 43, 705718.CrossRefGoogle ScholarPubMed
Gonda, J., & Schaie, K. (1985). Schaie-Thurstone Mental Abilities Test: Word Series Test. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Gross, A.L., Rebok, G.W., Unverzagt, F.W., Willis, S.L., & Brandt, J. (2011). Cognitive predictors of everyday functioning in older adults: Results from the ACTIVE Cognitive Intervention Trial. Journal of Gerontology, Series B. Psychological Sciences and Social Sciences, 66, 557566.Google Scholar
Gross, A.L., Inouye, S.K., Rebok, G.W., Brandt, J., Crane, P.K., Parisi, J.M., & Brandeen-Roche, L (2012). Parallel but not equivalent: Challenges and solutions for repeated assessment of cognition over time. Journal of Clinical and Experimental Neuropsychology, 34, 758772.Google Scholar
Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional versus new alternatives. Structural Equation Modeling, 6, 155.Google Scholar
Jack, C.R. Jr., Knopman, D.S., Jagust, W.J., Shaw, L.M., Aisen, P.S., Weiner, M.W., & Trojanowski, J.Q. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurology, 9, 119128.Google Scholar
Jefferson, A.L., Paul, R.H., Ozonoff, A., & Cohen, R.A. (2006). Evaluating elements of executive functioning as predictors of instrumental activities of daily living (IADLs). Archives of Clinical Neuropsychology, 21, 311320.Google Scholar
Jobe, J.B., Smith, D.M., Ball, K., Tennstedt, S.L., Marsiske, M., Willis, S.L., & Kleinman, K. (2001). ACTIVE: A cognitive intervention trial to promote independence in older adults. Controlled Clinical Trials, 22, 453479.Google Scholar
Kiosses, D.N., & Alexopoulos, G.S. (2005). IADL functions cognitive deficits, and severity of depression: A preliminary study. American Journal of Geriatric Psychiatry, 13, 244249.Google Scholar
Landi, F., Tua, E., Onder, G., Carrara, B., Sgadari, A., Rinaldi, C., & Bernabei, R.. (2000). Minimum data set for home care: A valid instrument to assess frail older people living in the community. Medical Care, 38, 11841190.Google Scholar
Lau, K.M., Parikh, M., Harvey, D.J., Huang, C.J., & Tomaszewski Farias, S. (2016). Early cognitively based functional limitations predict loss of independence in instrumental activities of daily living in older adults. Journal of the International Neurological Socienty, 21, 688689. PMID:26391766.Google Scholar
McAlister, C., & Schmitter-Edgecombe, M. (2016). Everyday functioning and cognitive correlates in healthy older adults with subjective cognitive concerns. The Clinical Neuropsychologist, 30, 10871103.Google Scholar
Morris, J.C. (2012). Revised criteria for mild cognitive impairment may compromise the diagnosis of Alzheimer disease dementia. Archives of Neurology, 69(6), 700708.CrossRefGoogle ScholarPubMed
Morris, J.N., Fries, B.E., Steel, K., Idegami, N., Bernabei, R., Carpenter, G.I., & Topinkova, E. (1997). Comprehensive clinical assessment in community setting: Applicability of the MDS-HC. Journal of the American Geriatric Society, 45, 10171024.Google Scholar
Morris, J.N., Jones, R.N., Fries, B.E., & Hirdes, J.P. (2004). Convergent validity of minimum data set-based performance quality indicators in postacute care settings. American Journal of Medical Quality, 19, 242247.Google Scholar
Mortimer, J.A., Ebbitt, B., Jun, S.P., & Finch, M.D. (1992). Predictors of cognitive and functional progression in patients with probable Alzheimer’s disease. Neurology, 42, 16891689.Google Scholar
Muthén, L.K., & Muthén, B.O. (1998–2012). Mplus user’s guide: Seventh Edition. Los Angeles, CA: Muthén & Muthén.Google Scholar
Nygård, L. (2003). Instrumental activities of daily living: A stepping‐stone towards Alzheimer’s disease diagnosis in subjects with mild cognitive impairment? Acta Neurologica Scandinavica, 107(s179), 4246.Google Scholar
Owsley, C., Sloane, M., McGwin, G. Jr., & Ball, K. (2002). Timed instrumental activities of daily living tasks: Relationship to cognitive function and everyday performance assessments in older adults. The Gerontologist, 48, 254265.Google Scholar
Pérès, K., Helmer, C., Amieva, H., Orgogozo, J.-M., Rouch, I., Dartigues, J.-F., && Barberger-Gateau, P. (2008). Natural history of decline in instrumental activities of daily living performance over the 10 years preceding the clinical diagnosis of dementia: A prospective population-based study. Journal of the American Geriatrics Society, 56, 3744.Google Scholar
Prince, D., & Butler, D. (2007). Clarity final report: Aging in place in America. Nashville, TN: Prince Market Research.Google Scholar
Rebok, G.W., Ball, K., Guey, L.T., Jones, R.N., Kim, H.Y., King, J.W., & Willis, S.L. (2014). Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. Journal of the American Geriatric Society, 62, 1624.Google Scholar
Rey, A. (1964). L’examen clinique en psychologie. Paris, France: Presses Universitaires de France.Google Scholar
Rog, L.A., Quitania Park, L., Harvey, D.J., Huang, C.-J., Mackin, S., & Tomaszewski Farias, S. (2014). The independent contributions of cognitive impairment and neuropsychiatric symptoms to everyday function in older adults. The Clinical Neuropsychologist, 28, 215236.Google Scholar
Rycroft, S.S., Giovannetti, T., Divers, R., & Hulswit, J. (2017). Sensitive performance-based assessment of everyday action in older and younger adults. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 118.Google Scholar
Schmitter-Edgecombe, M., Parsey, C., & Cook, D.J. (2011). Cognitive correlates of functional performance in older adults: Comparison of self-report, direct observation, and performance-based measures. Journal of the International Neuropsychological Society, 17(05), 853864.Google Scholar
Seligman, S.C., Giovannetti, T., Sestito, J., & Libon, D.J. (2014). A new approach to the characterization of subtle errors in everyday action: Implications for mild cognitive impairment. The Clinical Neuropsychologist, 28(1), 97115.Google Scholar
Shallice, T.I.M., & Burgess, P.W. (1991). Deficits in strategy application following frontal lobe damage in man. Brain, 114(2), 727741.Google Scholar
Small, G.W., McDonnell, D.D., Brooks, R.L., & Papadoupoulos, G. (2002). The impact of symptom severity on the cost of Alzheimer’s disease. Journal of the American Geriatric Society, 50, 321327.Google Scholar
Tennstedt, S.L., & Unverzagt, F.W. (2013). The ACTIVE study: Study overview and major findings. Journal of Aging and Health, 25, S3S20.Google Scholar
Thurstone, L., & Thurstone, T. (1949). Examiner manual for the SRA Primary Mental Abilities Test (Form 10–14). Chicago, IL: Science Research Associates.Google Scholar
Tomaszewski Farias, S., Chou, E., Harvey, J.D., Mungas, D., Reed, B., DeCarli, C., & Beckett, L. (2013). Longitudinal trajectories of everyday function by diagnostic status. Psychology of Aging, 28, 1071075.Google Scholar
Tomaszewski Farias, S., Mungas, D., Hinton, L., & Haan, M. (2011). Demographic, neuropsychological, and functional predictors of rate of longitudinal cognitive decline in Hispanic older adults. American Journal of Geriatric Psychiatry, 19, 440450.CrossRefGoogle Scholar
Tomaszewski Farias, S.T., Mungas, D., Reed, B.R., Harvey, D., Cahn-Weiner, D., & DeCarli, C. (2006). MCI is associated with deficits in everyday functioning. Alzheimer Disease and Associated Disorders, 20, 217.Google Scholar
Tucker-Drob, E.M. (2011). Neurocognitive functions and everyday functions change together in old age. Neuropsychology, 25, 368377.CrossRefGoogle ScholarPubMed
Willis, S.L. (1996). Everyday cognitive competence in elderly persons: Conceptual issues and empirical findings. The Gerontologist, 36, 595601.Google Scholar
Willis, S.L., Tennstedt, S.L., Marsiske, M., Ball, K., Elias, J., Koepke, K.M., & Wright, E. (2006). Long-term effects of cognitive training on everyday functional outcomes in older adults. Journal of the American Medical Association, 296, 28052814.Google Scholar
Wilson, B., Cockburn, J., & Baddeley, A. (1985). The Rivermead Behavioural Memory Test. Bury St. Edmunds, England: Thames Valley Test Company.Google Scholar
Supplementary material: File

Tomaszewski Farias supplementary material

Table S1

Download Tomaszewski Farias supplementary material(File)
File 14.7 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S2

Download Tomaszewski Farias supplementary material(File)
File 17.7 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S3

Download Tomaszewski Farias supplementary material(File)
File 19.8 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S4

Download Tomaszewski Farias supplementary material(File)
File 15.1 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S5

Download Tomaszewski Farias supplementary material(File)
File 16.4 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S6

Download Tomaszewski Farias supplementary material(File)
File 16.6 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S7

Download Tomaszewski Farias supplementary material(File)
File 16.6 KB
Supplementary material: File

Tomaszewski Farias supplementary material

Table S8

Download Tomaszewski Farias supplementary material(File)
File 15.1 KB