Hostname: page-component-77c89778f8-sh8wx Total loading time: 0 Render date: 2024-07-18T18:26:24.176Z Has data issue: false hasContentIssue false
  • English
  • Français

Performance-based everyday functional competence measures across the adult lifespan: the role of cognitive abilities

Published online by Cambridge University Press:  09 June 2017

Erika Borella ,
Alessandra Cantarella ,
Emilie Joly ,
Paolo Ghisletta ,
Elena Carbone ,
Deborah Coraluppi ,
Federica Piras  and
Rossana De Beni
Erika Borella*
Affiliation:
Department of General Psychology, University of Padova, Padova, Italy
Alessandra Cantarella
Affiliation:
Department of General Psychology, University of Padova, Padova, Italy
Emilie Joly
Affiliation:
Department of Psychology, University of Geneva, Geneva, Switzerland
Paolo Ghisletta
Affiliation:
Department of Psychology, University of Geneva, Geneva, Switzerland Distance Learning University Switzerland, Sierre, Switzerland
Elena Carbone
Affiliation:
Department of General Psychology, University of Padova, Padova, Italy
Deborah Coraluppi
Affiliation:
Department of General Psychology, University of Padova, Padova, Italy
Federica Piras
Affiliation:
IRCCS Fondazione Santa Lucia, Roma, Italy
Rossana De Beni
Affiliation:
Department of General Psychology, University of Padova, Padova, Italy
*
Correspondence should be addressed to: Erika Borella, Department of General Psychology, University of Padova, Via Venezia 8, 35131 Padova, Italy. Phone: +39 049 8276622; Fax: + 39 049 8276600. Email: erika.borella@unipd.it.
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

The effects of age on the ability to manage everyday functioning, crucial to ensure a healthy aging process, have been rarely examined and when, self-report measures have been used. The aim of the present study was to examine age effects across the adult lifespan in everyday functioning with two performance-based measures: the Everyday Problems Test (EPT), and the Timed Instrumental Activities of Daily Living (TIADL) tasks. The role of some crucial cognitive abilities, i.e. working memory (WM), processing speed, reasoning, vocabulary, and text comprehension in the EPT and the TIADL were also assessed to see whether or not they have a similar influence (and to what extent) in accounting for age-related effects in these two performance-based measures.

Method:

Two hundred and seventy-six healthy participants, from 40 to 89 years of age were presented with the EPT, the TIADL, as well as WM, processing speed, reasoning, text comprehension, and vocabulary tasks.

Results:

Path models indicated an indirect effect of age and education on the EPT, which was mediated by all the cognitive variables considered, with WM and reasoning being the strongest predictors of performance. An indirect quadratic effect of age, but not of education, was found on the TIADL score, and an accelerated decline in processing speed mediated the relationship between age and the TIADL score.

Conclusion

This study revealed age-related effects in performance-based measures, which are mediated by different cognitive abilities depending on the measure considered. The findings highlight the importance of assessing everyday functioning even in healthy older adults.

Keywords

everyday life functioning measuresEveryday Problems Test (EPT)Timed Instrumental Activities of Daily Living (TIADL)tasksreasoningworking memoryprocessing speedaging
Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 12 , December 2017 , pp. 2059 - 2069
Copyright
Copyright © International Psychogeriatric Association 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

Allaire, J. C. and Marsiske, M. (1999). Everyday cognition: age and intellectual ability correlates. Psychology and Aging, 14, 627. doi: 10.1037/0882-7974.14.4.627.Google Scholar
Arbuckle, J. L. (2011). IBM SPSS Amos (Version 20.0) [Computer Software]. Chicago: IBM SPSS.Google Scholar
Borella, E., Cantarella, A., Carbone, E., Zavagning, M. and De Beni, R. (2017). Quotidiana-mente. La Valutazione dell'autonomia Funzionale e Dell'auto-percezione di Fallimenti Cognitivi in Adulti-anziani. [Assessing Functional Autonomy and Self-perceived Cognitive Failings in Adults]. Milan, Italy: FrancoAngeli.Google Scholar
Borella, E., Carretti, B. and De Beni, R. (2008). Working memory and inhibition across the adult life-span. Acta Psychologica, 128, 33–44. doi: 10.1016/j.actpsy.2007.09.008.Google Scholar
Borella, E., Ghisletta, P. and de Ribaupierre, A. (2011). Age differences in text processing: the role of working memory, inhibition and processing speed. Journal of Gerontology: Psychological Sciences, 66, 311–320. doi: 10.1093/geronb/gbr002.CrossRefGoogle ScholarPubMed
Burton, C. L., Strauss, E., Hultscha, D. F. and Huntera, M. A. (2006). Cognitive functioning and everyday problem solving in older adults. The Clinical Neuropsychologist, 3, 432–452. doi: 10.1080/13854040590967063.Google Scholar
Burton, C. L., Strauss, E., Bunce, D., Hunter, M. A. and Hultsch, D. F. (2009). Functional abilities in older adults with mild cognitive impairment. Gerontology, 5, 570–581. doi: 10.1159/000228918.Google Scholar
Cattell, R. B. and Cattell, H. E. P. (1963). Measuring Intelligence with the Culture Fair Tests. Champaign, IL: Institute for Personality and Ability Testing.Google Scholar
Crook, T., Bartus, R. T., Ferris, S. H., Whitehouse, P., Cohen, G. D. and Gershon, S. (1986). Age-associated memory impairment: proposed diagnostic criteria and measures of clinical change. Report of a National Institute of Mental Health Work Group. Developmental Neuropsychology 2, 261–276. doi: 10.1080/87565648609540348.Google Scholar
De Beni, R., Borella, E., Carretti, B., Marigo, C. and Nava, L. (2008). BAC. Portfolio per la Valutazione del Benessere e Delle Abilità Cognitive Nell'età Adulta e Avanzata. [The Assessment of Well-being and Cognitive Abilities in Adulthood and Aging]. Firenze: Giunti OS.Google Scholar
Diehl, M., Willis, S. L. and Schaie, K. W. (1995). Everyday problem solving in older adults: observational assessment and cognitive correlates. Psychology and Aging, 10, 478–491. doi: 10.1037/0882-7974.10.3.478.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). “Mini-Mental State”: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.CrossRefGoogle ScholarPubMed
Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A. and Jaffe, M. W. (1963). Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA, 185, 914–919. doi: 10.1001/jama.1963.03060120024016.Google Scholar
Kelaiditi, E. et al. (2013). Cognitive frailty: rational and definition from an (IANA/IAGG) international consensus group. The Journal of Nutrition, Health & Aging, 17, 726–734. doi: 10.1007/s12603-013-0367-2.Google Scholar
Kimbler, K. J. (2013). Everyday problem solving and instrumental activities of daily living: support for domain specificity. Behavioral Sciences, 1, 170–191. doi: 10.3390/bs3010170.CrossRefGoogle Scholar
Law, L. L., Barnett, F., Yau, M. K. and Gray, M. A. (2012). Measures of everyday competence in older adults with cognitive impairment: a systematic review. Age and Ageing, 41, 9–16. doi: 10.1093/ageing/afr104.Google Scholar
Lawton, M. P. and Brody, E. M. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. Nursing Research, 3, 278.Google Scholar
Marsiske, M. and Willis, S. L. (1995). Dimensionality of everyday problem solving in older adults. Psychology and Aging, 10, 269–283. doi: 10.1037/0882-7974.10.2.269.CrossRefGoogle ScholarPubMed
Marsiske, M. and Margrett, J. A. (2006). Everyday problem solving and decision making. In Birren, J. E. and Schaie, K. W. (eds.), Handbook of the Psychology of Aging, vol. 6 (pp. 315–342). Cambridge, MA: Elsevier Academic Press.Google Scholar
Martyr, A. and Clare, L. (2012). Executive function and activities of daily living in Alzheimer's disease: a correlational meta-analysis. Dementia and Geriatric Cognitive Disorders, 33, 189–203. doi: 10.1159/000338233.CrossRefGoogle ScholarPubMed
Moore, D. J., Palmer, B. W., Patterson, T. L. and Jeste, D. J. (2007). A review of performance-based measures of functional living skills. Journal of Psychiatric Research, 41, 97–118. doi: 10.1016/j.jpsychires.2005.10.008.Google Scholar
Owsley, C., Sloane, M., McGwin, J. G. and Ball, K. (2002). Timed instrumental activities of daily living tasks: relationship to cognitive function and everyday performance assessments in older adults. Gerontology, 4, 254–265. doi: 10.1159/000058360.Google Scholar
Panza, F. et al. (2015). Targeting cognitive frailty: clinical and neurobiological roadmap for a single complex phenotype. Journal of Alzheimer's Disease, 47, 793–813. doi: 10.3233/JAD-150358.CrossRefGoogle ScholarPubMed
Saczynski, J. S., Beiser, A., Seshadri, S., Auerbach, S., Wolf, P. A. and Au, R. (2010). Depressive symptoms and risk of dementia. The Framingham Heart Study. Neurology, 75, 35–41. doi: 10.1212/WNL.0b013e3181e62138.Google Scholar
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 3, 403–428. doi: 10.1037/0033-295X.103.3.403.CrossRefGoogle Scholar
Salthouse, T. A. and Babcock, R. L. (1991). Decomposing adult age differences in working memory. Developmental Psychology, 27, 763. doi: 10.1037/0012-1649.27.5.763.Google Scholar
Wadley, V. G., Okonkwo, O., Crowe, M. and Ross-Meadows, L. A. (2008). Mild cognitive impairment and everyday function: evidence of reduced speed in performing instrumental activities of daily living. The American Journal of Geriatric Psychiatry, 5, 416–424. doi: 10.1097/01.JGP.0000310780.04465.13.CrossRefGoogle Scholar
Willis, S. L. (1993). Test Manual for the Everyday Problems Test for Cognitively Challenged Elderly. University Park, PA: The Pennsylvania State University.Google Scholar
Willis, S. L. and Marsiske, M. (1993). Manual for the Everyday Problems Test. University Park: Department of Human Development and Family Studies, Pennsylvania State University.Google Scholar
Willis, S. L. (1996). Everyday cognitive competence in elderly persons: conceptual issues and empirical findings. The Gerontologist, 5, 595–601. doi: 10.1093/geront/36.5.595.Google Scholar
Willis, S. L. and Marsiske, M. (1991). Life-span perspective on practical intelligence. In Tupper, D. E. and Cicerone, K. D. (eds.), The Neuropsychology of Everyday Life: Issues in Development and Rehabilitation (pp. 183–198). Norwell, MA: Kluwer Academic.Google Scholar
Willis, S. L., Jay, G. M., Diehl, M. and Marsiske, M. (1992). Longitudinal change and the prediction of everyday task competence in the elderly. Research on Aging, 14, 68–91. doi: 10.1177/0164027592141004.Google Scholar
Willis, S. L. and Schaie, K. W. (1986). Training the elderly on the ability factors of spatial orientation and inductive reasoning. Psychology and Aging, 3, 239–247. doi: 10.1037/0882-7974.1.3.239.CrossRefGoogle Scholar
Winblad, B. et al. (2004). Mild cognitive impairment– – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246. doi: 10.1111/j.1365-2796.2004.01380.x.Google Scholar
Yam, A. and Marsiske, M. (2013). Cognitive longitudinal predictors of older adults' self-reported IADL function. Journal of Aging and Health, 25, 163S–185S. doi: 10.1177/0898264313495560.Google Scholar