Hostname: page-component-848d4c4894-p2v8j Total loading time: 0 Render date: 2024-05-12T00:46:09.125Z Has data issue: false hasContentIssue false

Neuropsychological correlates of instrumental activities of daily living in neurocognitive disorders: a possible role for executive dysfunction and mood changes

Published online by Cambridge University Press:  23 May 2018

Martina Amanzio
Affiliation:
Department of Psychology, University of Turin, Via Verdi 10, 10123 Turin, Italy European Innovation Partnership on Active and Healthy Ageing, Bruxelles, Belgium
Sara Palermo*
Affiliation:
Department of Psychology, University of Turin, Via Verdi 10, 10123 Turin, Italy
Milena Zucca
Affiliation:
Department of Neuroscience, University of Turin, Via Cherasco 15, 10126 Turin, Italy
Rosalba Rosato
Affiliation:
Department of Psychology, University of Turin, Via Verdi 10, 10123 Turin, Italy Unit of Cancer Epidemiology, Città della Salute e della Scienza Hospital and CPO Piemonte, Turin, Italy
Elisa Rubino
Affiliation:
Department of Neuroscience, University of Turin, Via Cherasco 15, 10126 Turin, Italy
Daniela Leotta
Affiliation:
Martini Hospital, Neurology Division, Via Tofane 71, 10100 Turin, Italy
Massimo Bartoli
Affiliation:
Department of Psychology, University of Turin, Via Verdi 10, 10123 Turin, Italy
Innocenzo Rainero
Affiliation:
Department of Neuroscience, University of Turin, Via Cherasco 15, 10126 Turin, Italy
*
Correspondence should be addressed to: Sara Palermo, Department of Psychology, University of Turin, Via Verdi 10, Turin 10124, Italy. E-mail: sara.palermo@unito.it.

Abstract

Since baseline executive dysfunction predicts worsening Instrumental Activities of Daily Living (i-ADL) over time and progression to Alzheimer's Disease (AD), we aimed to analyze the role of neuropsychological variables to outline which factors can contribute to functional impairment. Specific attention to executive functions (EFs) has been given.

A total of 144 subjects complaining of different cognitive deficits – ranging from “MCI likely due to AD” to “mild AD patients” – underwent an overall neuropsychological assessment. The Behavioral Assessment of the Dysexecutive Syndrome was used to analyze EFs. We conducted multiple linear regression analyses to study whether the level of independent living skills – assessed with the Lawton-scale – could be associated with cognitive and behavioral measurements.

We found a significant association between i-ADL and specific EFs measured by Rule Shift Cards (p = 0.04) and Modified Six Elements (p = 0.02). Moreover, considering i-ADL scores, we observed an involvement of mood changes and a reduced awareness of deficits in terms of Hamilton Depression Rating Scale (p = 0.02) and Awareness of Deficit Questionnaire – Dementia scale (p < 0.0001), respectively.

Our results suggest the importance of considering the association between a reduction in i-ADL and executive dysfunction in patients who have AD etiopathology, for which the ability to inhibit a response, self-monitoring, set-shifting and mood deflection play a key role. Besides, no straightforward associations between i-ADL scores and global cognition, memory, language comprehension, attention, and perspective taking abilities were found.

Type
Original Research Article
Copyright
Copyright © International Psychogeriatric Association 2018 

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

Albert, M. S. et al. (2011). The diagnosis of mild cognitive impairment due to Alzheimers disease: recommendations from the national institute on aging-Alzheimers association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & Dementia, 7, 270279. doi: 10.1016/j.jalz.2011.03.008.Google Scholar
Albert, S. M., Bear-Lehman, J. and Anderson, S. J. (2015). Declines in mobility and changes in performance in the instrumental activities of daily living among mildly disabled community-dwelling older adults. Journal of Gerontology, Series A, Biological Science and Medical Science, 70, 7177. doi: 10.1093/gerona/glu088.Google Scholar
Allain, P. et al. (2007). A study of action planning in patients with Alzheimer's disease using the zoo map test. Revue Neurologique, 163, 222230.Google Scholar
Amanzio, M. et al. (2011). Unawareness of deficits in Alzheimer's disease: role of the cingulate cortex. Brain, 134, 10611076. doi: 10.1093/brain/awr020.Google Scholar
Amanzio, M., Geminiani, G., Leotta, D. and Cappa, S. (2008). Metaphor comprehension in Alzheimer's disease: novelty matters. Brain and Language, 107, 110.Google Scholar
Amanzio, M., Vase, L., Leotta, D., Miceli, R., Palermo, S. and Geminiani, G. (2013). Impaired awareness of deficits in Alzheimer's disease: the role of everyday executive dysfunction. Journal of the International Neuropsychological Society, 19, 6372. doi: 10.1017/S1355617712000896.Google Scholar
American Psychiatric Association (APA) (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th edn. Washington, DC: American Psychiatric Association Publishing.Google Scholar
Artaud, F., Singh-Manoux, A., Dugravot, A., Tzourio, C. and Elbaz, A. (2015). Decline in fast gait speed as a predictor of disability in older adults. Journal of American Geriatric Society, 63, 1129–36. doi: 10.1111/jgs.13442.Google Scholar
Bangen, K. J. et al. (2010). Complex activities of daily living vary by mild cognitive impairment subtype. Journal of the International Neuropsychological Society, 16, 630639. doi: 10.1017/S1355617710000330.Google Scholar
Bateman, R. J. et al. (2012). Clinical and biomarker changes in dominantly inherited Alzheimer's disease. New England Journal of Medicine, 367, 795804. doi: 10.1056/NEJMoa1202753.Google Scholar
Bech, P., Rafaelsen, O. J., Kramp, P. and Bolwig, T. G. (1978). The mania rating scale: scale construction and inter-observer agreement. Neuropharmacology, 17, 430431.Google Scholar
Boyle, P. A., Malloy, P. F., Salloway, S., Cahn-Weiner, D. A., Cohen, R. and Cummings, J. L. (2003). Executive dysfunction and apathy predict functional impairment in Alzheimer disease. American Journal of Geriatric Psychiatry, 11, 214–21.Google Scholar
Burton, C. L., Strauss, E., Hultsch, D. F. and Hunter, M. A. (2006). Cognitive functioning and everyday problem solving in older adults. Clinical Neuropsychologist, 20, 432452. doi: 10.1080/13854040590967063.Google Scholar
Cahn-Weiner, D. A. et al. (2007). Cognitive and neuroimaging predictors of instrumental activities of daily living. Journal of the International Neuropsychological Society, 13, 747757. doi: 10.1017/S1355617707070853.Google Scholar
Capezuti, E. A., Malone, M. L., Khan, A. K. and Baumann, S. L. (2017). The Encyclopedia of Elder Care: The Comprehensive Resource on Geriatric Health and Social Care, 4th edn. New York, NY: Springer Publishing Company.Google Scholar
Cools, R., Brouwer, W. H., De Jong, R. and Slooff, C. (2000). Flexibility, inhibition, and planning: frontal dysfunctioning in schizophrenia. Brain and Cognition, 108112.Google Scholar
da Costa Armentano, C. G., Porto, C. S., Nitrini, R. and Dozzi Brucki, S. M. (2013). Ecological evaluation of executive functions in mild cognitive impairment and Alzheimer disease. Alzheimer Disease & Associated Disorders, 27, 95101. doi: 10.1097/WAD.0b013e31826540b4.Google Scholar
De Renzi, E. and Vignolo, L. A. (1962). The token test: a sensitive test to detect receptive disturbances in aphasics. Brain, 85, 665678.Google Scholar
De Vriendt, P., Gorus, E., Cornelis, E., Velghe, A., Petrovic, M. and Mets, T. (2012). The process of decline in advanced activities of daily living: a qualitative explorative study in mild cognitive impairment. International Psychogeriatrics, 24, 974986. Doi: 10.1017/S1041610211002766.Google Scholar
De Vriendt, P., Mets, T., Petrovic, M. and Gorus, E. (2015). Discriminative power of the advanced activities of daily living (a-ADL) tool in the diagnosis of mild cognitive impairment in an older population. International Psychogeriatrics, 27, 14191427. Doi: 10.1017/S1041610215000563.Google Scholar
Dubois, B. et al. (2014). Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria. Lancet Neurology, 13, 614–29. doi: 10.1016/S1474-4422(14)70090-0.Google Scholar
Ellis, K. A. et al. (2013). Decline in cognitive function over 18 months in healthy older adults with high amyloid. Journal of Alzheimer's Disease, 34, 861871. doi: 10.3233/JAD-122170.Google Scholar
Espinosa, A. et al. (2009). Ecological assessment of executive functions in mild cognitive impairment and mild Alzheimer's disease. Journal of the International Neuropsychological Society, 15, 751757. doi: 10.1017/S135561770999035X.Google Scholar
Farias, S. T., Mungas, D. and Jagust, W. (2005). Degree of discrepancy between self and other‐reported everyday functioning by cognitive status: dementia, mild cognitive impairment, and healthy elders. International Journal of Geriatric Psychiatry, 20, 827834.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, 189198.Google Scholar
Freund, R. J., Littell, R. C. and Spector, P. C. (1986). SAS System for Linear Models. Cary, NC: SAS Institute Inc.Google Scholar
Gobbens, R. J. and van Assen, M. A. (2014). The prediction of ADL and IADL disability using six physical indicators of frailty: a longitudinal study in the Netherlands. Current Gerontology and Geriatric Research, 2014, 358137. doi: 10.1155/2014/358137.Google Scholar
Graf, C. (2008). The Lawton instrumental activities of daily living scale. American Journal of Nursing, 108, 5262. doi: 10.1097/01.NAJ.0000314810.46029.74.Google Scholar
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23, 5662.Google Scholar
Harrell, F. E., Lee, K. L., Califf, R. M., Pryor, D. B. and Rosati, R. A. (1984). Regression modelling strategies for improved prognostic prediction. Statistics in Medicine, 3, 143152.Google Scholar
Harrell, F. E., Lee, K. L. and Mark, D. B. (1996). Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in Medicine, 15, 361387.Google Scholar
Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A. and Martin, R. L. (1982). A new clinical scale for the staging of dementia. British Journal of Psychiatry, 140, 566572.Google Scholar
Hybels, C. F., Pieper, C. F. and Blazer, D. G. (2009). The complex relationship between depressive symptoms and functional limitations in community-dwelling older adults: the impact of subthreshold depression. Psychological Medicine, 39, 16771688. doi: 10.1017/S0033291709005650.Google Scholar
Jack, C. R. Jr. et al. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurology, 9, 119128. doi: 10.1016/S1474-4422(09)70299-6.Google Scholar
Jekel, K. et al. (2015). Mild cognitive impairment and deficits in instrumental activities of daily living: a sistematic review. Alzheimer's Research & Therapy, 7, 17. doi: 10.1186/s13195-015-0099-0.Google Scholar
Jungwirth, S., Zehetmayer, S., Hinterberger, M., Tragl, K. H. and Fischer, P. (2012). The validity of amnestic MCI and non-amnestic MCI at age 75 in the prediction of Alzheimer's dementia and vascular dementia. International Psychogeriatrics, 24, 959966. doi: 10.1017/S1041610211002870.Google Scholar
Kamiya, M., Sakurai, T., Ogama, N., Maki, Y. and Toba, K. (2014). Factors associated with increased caregivers’ burden in several cognitive stages of Alzheimer's disease. Geriatric & Gerontology International, 14 (Suppl. 2), 4555. doi: 10.1111/ggi.12260.Google Scholar
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, 914916.Google Scholar
Knopman, D. S. et al. (2012). Short-term clinical outcomes for stages of NIA-AA preclinical Alzheimer disease. Neurology, 78, 15761582. doi: 10.1212/WNL.0b013e3182563bbe.Google Scholar
Kondo, N., Kazama, M., Suzuki, K. and Yamagata, Z. (2008). Impact of mental health on daily living activities of Japanese elderly. Preventive Medicine, 46, 457462. doi: 10.1016/j.ypmed.2007.12.007.Google Scholar
Lawton, M. P. and Brody, E. M. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist, 9, 179186.Google Scholar
Lezak, M. D., Howieson, D. B. and Loring, D. W. (2004). Neuropsychological Assessment, 4th edn. New York: Oxford University Press.Google Scholar
Luck, T., Luppa, M., Angermeyer, M. C., Villringer, A., Konig, H. H. and Riedel-Heller, S. G. (2011). Impact of impairment in instrumental activities of daily living and mild cognitive impairment on time to incident dementia: results of the Leipzig longitudinal study of the aged. Psychological Medicine, 41, 10871097. doi: 10.1017/S003329171000142X.Google Scholar
Marshall, G. A. et al. (2011a). Instrumental activities of daily living impairment is associated with increased amyloid burden. Dementia and Geriatric Cognitive Disorders, 31, 443450. doi: 10.1159/000329543.Google Scholar
Marshall, G. A. et al. (2011b). Executive function and instrumental activities of daily living in mild cognitive impairment and Alzheimer's disease. Alzheimer's & Dementia, 7, 300308. doi: 10.1016/j.jalz.2010.04.005.Google Scholar
Marshall, G. A. et al. (2014). Regional cortical thinning and cerebrospinal biomarkers predict worsening daily functioning across the Alzheimer disease spectrum. Journal of Alzheimer's Disease, 41, 719728. doi: 10.3233/JAD-132768.Google Scholar
McKhann, G. M. et al. (2011). The diagnosis of dementia 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, 263269. doi: 10.1016/j.jalz.2011.03.005.Google Scholar
Migliorelli, R. et al. (1995). Anosognosia in Alzheimer's disease: a study of associated factors. Journal of Neuropsychiatry and Clinical Neurosciences, 7, 338344.Google Scholar
Millar, D., Griffiths, P., Zermansky, A. J. and Burn, D. J. (2006). Characterizing behavioral and cognitive dysexecutive changes in progressive supranuclear palsy. Movement Disorders, 21, 199207.Google Scholar
Milnac, M. E. and Feng, M. C. (2016). Assessment of activities of daily living, self-care, and independence. Archives of Clinical Neuropsychology, 31, 506516. doi: 10.1093/arclin/acw049.Google Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A. and Wagner, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognitive Psychology, 41, 49100. doi: 10.1006/cogp.1999.0734.Google Scholar
Morris, J. C. et al. (2009). Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Archives Neurology, 66, 14691475. doi: 10.1001/archneurol.2009.269.Google Scholar
Murakami, et al. (2015). Modified six elements test: earlier diagnosis of the correlation between motor and executive dysfunction in Parkinson's disease without dementia. Neurology and Clinical Neuroscience, 3, 209214.Google Scholar
Nyunt, M. S., Lim, M. L., Yap, K. B. and Ng, T. P. (2012). Changes in depressive symptoms and functional disability among community-dwelling depressive older adults. International Psychogeriatrics, 24, 16331641. doi: 10.1017/S1041610212000890.Google Scholar
Ogama, N., Sakurai, T., Shimizu, A. and Toba, K. (2014). Regional white matter lesions predict falls in patients with amnestic mild cognitive impairment and Alzheimer's disease. Journal of the American Medical Directors Association, 15, 3641. doi: 10.1016/j.jamda.2013.11.004.Google Scholar
Ogama, N., Yoshida, M., Nakai, T., Niida, S, Toba, K. and Sakurai, T. (2016). Frontal white matter hyperintensity predicts lower urinary tract dysfunction in older adults with amnestic mild cognitive impairment and Alzheimer's disease. Geriatric & Gerontology International, 16, 167174. doi: 10.1111/ggi.12447.Google Scholar
Pereira, F. S., Yassuda, M. S., Oliveira, A. M. and Forlenza, O. V. (2008). Executive dysfunction correlates with impaired functional status in older adults with varying degrees of cognitive impairment. International Psychogeriatrics, 20, 11041115. doi: 10.1017/S1041610208007631.Google Scholar
Pérès, K. et al. (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
Petersen, R. C., Caracciolo, B., Brayne, C., Gauthier, S., Vesna Jelic, V. and Fratiglioni, L. (2014). Mild cognitive impairment: a concept in evolution. Journal of Internal Medicine, 2014 Mar, 275, 214228.Google Scholar
Petersen, R. C. and Negash, S. (2008). Mild cognitive impairment: an overview. CNS spectrums, 13, 4553.Google Scholar
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G. and Kokmen, E. (1999). Mild cognitive impairment: clinical characterization and outcome. Archives of Neurology, 56, 303308.Google Scholar
Piquard, A., Derouesné, C., Lacomblez, L. and Siéroff, E. (2004). Planning and activities of daily living in Alzheimer's disease and frontotemporal dementia. Psychologie Neuropsychiatrie du Vieillissement, 2, 147156.Google Scholar
Premack, D. and Woodruff, G. (1978). Does the chimpanzee have a theory of mind?. Behavioral and Brain Sciences, 1, 515526.Google Scholar
Rentz, D. M. et al. (2010). Cognition, reserve, and amyloid deposition in normal aging. Annals of Neurology, 67, 5364. doi: 10.1002/ana.21904.Google Scholar
Reuben, D. B., Laliberte, L., Hiris, J. and Mor, V. (1990). A hierarchical exercise scale to measure function at the advanced activities of daily living (AADL) level. Journal of the American Geriatrics Society, 38, 855861.Google Scholar
Rodrigues Gouveia, P. A., Dozzi Brucki, S. M., Fleury Malheiros, S. M. and Bueno, O. F. A. (2007). Disorders in planning and strategy application in frontal lobe lesion patients. Brain and Cognition, 63, 240246.Google Scholar
Rosen, W. G., Mohs, R. C. and Davis, K. L. (1984). A new rating scale for Alzheimer's disease. American Journal of Psychiatry, 141, 13561364.Google Scholar
Royall, D. R. et al. (2007). The cognitive correlates of functional status: a review from the committee on research of the american neuropsychiatric association. Journal of Neuropsychiatry and Clinical Neurosciences, 19, 249265. doi: 10.1176/jnp.2007.19.3.249.Google Scholar
Sahin, A. et al. (2015). Factors affecting daily instrumental activities of the elderly. Turkish Journal of Medical Sciences, 45, 13531359.Google Scholar
Schlotzhauer, S. D. and Littell, R. C. (1987). SAS System for Elementary Statistical Analysis. Cary, NC: SAS Institute Inc.Google Scholar
Seidel, D., Brayne, C. and Jagger, C. (2011). Limitations in physical functioning among older people as a predictor of subsequent disability in instrumental activities of daily living. Age and Ageing, 40, 463469. doi: 10.1093/ageing/afr054.Google Scholar
Shallice, T. I. M. and Burgess, P. W. (1991). Deficits in strategy application following frontal lobe damage in man. Brain, 114, 727741.Google Scholar
Song, H. J., Meade, K., Akobundu, U. and Sahyoun, N. R. (2014). Depression as a correlate of functional status of com- munity-dwelling older adults: utilizing a short-version of 5-item geriatric depression scale as a screening tool. Journal of Nutrition, Health & Aging, 18, 765770. doi: 10.1007/s12603-014-0452-1.Google Scholar
Sperling, R. A. et al. (2011). Toward defining the preclinical stages of 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, 280292. doi: 10.1016/j.jalz.2011.03.003.Google Scholar
Spinnler, H. and Tognoni, G. (1987). Standardizzazione italiana e taratura di test neuropsicologici. Italian Journal of Neurological Sciences. Milan: Masson Italia Periodici.Google Scholar
Synn, A. et al. (2018). Mental states in moving shapes: distinct cortical and subcortical contributions to theory of mind impairments in dementia. Journal of Alzheimer's Disease, 61, 521535. doi: 10.3233/JAD-170809.Google Scholar
Tabert, M. H. et al. (2002). Functional deficits in patients with mild cognitive impairment: prediction of AD. Neurology, 58, 758764.Google Scholar
Tomaszewski, F. S. et al. (2009). Longitudinal changes in memory and executive functioning are associated with longitudinal change in instrumental activities of daily living in older adults. Clinical Neuropsychologist, 23, 446461. doi: 10.1080/13854040802360558.Google Scholar
Villemagne, V. L. et al. (2013). Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurology, 12, 357367. doi: 10.1016/S1474-4422(13)70044-9.Google Scholar
Wilson, B. A., Alderman, N., Burgess, P. W., Emslie, H. and Evans, J. J. (1996). BADS: Behavioural Assessment of the Dysexecutive Syndrome. Bury St. Edmonds, UK: Thames Valley Test Company.Google Scholar
Wood, R. L. and Liossi, C. (2007). The relationship between general intellectual ability and performance on ecologically valid executive tests in a severe brain injury sample. Journal of the International Neuropsychological Society, 13, 9098.Google Scholar
Yoshita, M. et al. (2006). Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology, 67, 21922198. doi: 10.1212/01.wnl.0000249119.95747.1f.Google Scholar
Supplementary material: File

Amanzio et al. supplementary material

Amanzio et al. supplementary material 1

Download Amanzio et al. supplementary material(File)
File 232.4 KB