Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-24T03:28:30.120Z Has data issue: false hasContentIssue false
  • English
  • Français

Differences in the use of everyday technology among persons with MCI, SCI and older adults without known cognitive impairment

Published online by Cambridge University Press:  17 April 2017

Camilla Malinowsky ,
Anders Kottorp ,
Anders Wallin ,
Arto Nordlund ,
Eva Björklund ,
Ilse Melin ,
Anette Pernevik ,
Lena Rosenberg  and
Louise Nygård
Camilla Malinowsky*
Affiliation:
Division of Occupational Therapy, Department of Neurobiology, Care Science and Society (NVS), Karolinska Institutet, Stockholm, Sweden
Anders Kottorp
Affiliation:
Department of Occupational Therapy, University of Illinois at Chicago, Chicago, IL, USA
Anders Wallin
Affiliation:
Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
Arto Nordlund
Affiliation:
Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
Eva Björklund
Affiliation:
Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
Ilse Melin
Affiliation:
Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
Anette Pernevik
Affiliation:
Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
Lena Rosenberg
Affiliation:
Division of Occupational Therapy, Department of Neurobiology, Care Science and Society (NVS), Karolinska Institutet, Stockholm, Sweden
Louise Nygård
Affiliation:
Division of Occupational Therapy, Department of Neurobiology, Care Science and Society (NVS), Karolinska Institutet, Stockholm, Sweden
*
Correspondence should be addressed to: Camilla Malinowsky, Division of Occupational Therapy, Fack 23200, Karolinska Institutet, 141 83 Huddinge, Sweden. Phone: +468 524 837 52. Email: camilla.malinowsky@ki.se.
Get access

Abstract

Background:

To use valid subjective reports sensible to cognitive decline is vital to identify very early signs of dementia development. Use of everyday technology (ET) has been shown to be sensitive to differentiate adults with mild cognitive impairment (MCI) from controls, but the group with subjective cognitive impairment (SCI) has not yet been examined. This study aims to investigate and compare self-perceived ability in ET use and number of ETs reported as actually used in a sample of older adults with SCI, MCI, and older adults with no known cognitive impairment, i.e. controls.

Methods:

Older adults with MCI (n = 29), SCI (n = 26), and controls (n = 30) were interviewed with the short version of the Everyday Technology Use Questionnaire (S-ETUQ) to capture self-perceived ability in ET use and number of ETs used. To generate individual measures of ability to use ET, Rasch analysis was used. The measures were then compared group-wise using ANCOVA. The numbers of ETs used were compared group-wise with ANOVA.

Results:

Controls versus SCI and MCI differed significantly regarding ETs reported as used, but not SCI versus MCI. Similarly, in ability to use ET, controls versus SCI and MCI differed significantly but not SCI versus MCI.

Conclusions:

The significantly lower numbers of ETs reported as actually used and the lower ability in SCI and MCI groups compared to controls suggest that ET use is affected already in very minor cognitive decline. This indicates that self-reported ET use based on the S-ETUQ is sensitive to detect changes already in SCI.

Keywords

ADLcognitive impairment
Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 7 , July 2017 , pp. 1193 - 1200
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

Albert, M. S. et al. (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 and Dementia, 7, 270–279. doi: 10.1016/j.jalz.2011.03.008.CrossRefGoogle ScholarPubMed
Auer, S. and Reisberg, B. (1997). The GDS/FAST staging system. International Psychogeriatrics, 9, 167–171. doi: 10.1017/S1041610297004869.CrossRefGoogle ScholarPubMed
Bond, T. G. and Fox, C. M. (2007). Applying the Rasch Model: Fundamental Measurement in the Human Sciences. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Caselli, R. J. et al. (2014). Subjective cognitive decline: self and informant comparison. Alzheimer's and Dementia, 10, 93–98. doi: 10.1016/j.jalz.2013.01.003.CrossRefGoogle Scholar
Eckerström, M. et al. (2013). Sahlgrenska academy self-reported cognitive impairment questionnaire (SASCI-Q) – a research tool discriminating between subjectively cognitively impaired patients and healthy controls. International Psychogeriatrics, 25, 420–430. doi: 10.1017/S1041610212001846.CrossRefGoogle ScholarPubMed
Fallahpour, M., Kottorp, A., Nygård, L. and Larsson Lund, M. (2014). Perceived difficulty in use of everyday technology in persons with acquired brain injury of different severity: a comparison with controls. Journal of Rehabilitation Medicine, 46, 635–641. doi: 10.2340/16501977-1818.CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). “Mini mental state examination”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. doi: 10.1016/0022-3956(75)90026-6.CrossRefGoogle Scholar
Fragkiadaki, S. Kontaxopoulou, D., Beratis, I. N., Andronas, N., Economou, A. and Yannis, G. (2016). Self-awareness of cognitive efficiency: differences between healthy elderly and patients with mild cognitive impairment (MCI). Journal of Clinical and Experimental Neuropsychology, 38, 1144–1157. doi: 10.1080/13803395.2016.1198469.CrossRefGoogle ScholarPubMed
Frank, L., Lenderking, W. R., Howard, K. and Cantillon, C. (2011). Patient self-report for evaluating mild cognitive impairment and prodromal Alzheimer's disease. Alzheimer's Research & Therapy, 3, 35. doi: 10.1186/alzrt97.CrossRefGoogle ScholarPubMed
Garcia-Ptacek, S. et al. (2014). Subjective cognitive impairment subjects in our clinical practice. Dementia and Geriatic Cognitive Disorders Extra, 4, 419–430. doi: 10.1159/000366270.CrossRefGoogle ScholarPubMed
Hedman, A., Nygård, L., Almkvist, O. and Kottorp, A. (2015). Amount and type of everyday technology use over time in older adults with cognitive impairment. Scandinavian Journal of Occupational Therapy, 22, 196–206. doi: 10.3109/11038128.2014.982172.CrossRefGoogle ScholarPubMed
Hedman, A., Nygård, L., Malinowsky, C., Almkvist, O. and Kottorp, A. (2016). Changing everyday activities and technology use in mild cognitive impairment, British Journal of Occupational Therapy, 79, 111–119. doi: 10.1177/0308022615586800.CrossRefGoogle Scholar
Jekel, K. et al. (2015). Mild cognitive impairment and deficits in instrumental activities of daily living: a systematic review. Alzheimer´s Research & Therapy, 7, 17. doi: 10.1186/s13195-015-0099-0.CrossRefGoogle ScholarPubMed
Jessen, F. et al. (2014). A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimer's & Dementia, 10, 844–852. doi: 10.1016/j.jalz.2014.01.001.CrossRefGoogle ScholarPubMed
Kottorp, A. and Nygård, L. (2011). Development of a short-form assessment for detection of subtle activity limitations: can use of everyday technology distinguish between MCI and Alzheimer's disease? Expert Review of Neurotherapeutics, 11, 647–655. doi: 10.1586/ern.11.55.CrossRefGoogle ScholarPubMed
Linacre, J. M. (2016). Winsteps – Rasch Model Computer Program (Version 3.91.0). Chicago, IL. www.winsteps.com.Google Scholar
Mitchell, A. J. (2009). A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment. Journal of Psychiatric Research, 43, 411–431. doi: 10.1016/j.jpsychires.2008.04.014.CrossRefGoogle ScholarPubMed
Morris, J. C. (1997). Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. International Psychogeriatrics, 9, 173–176,CrossRefGoogle ScholarPubMed
Nygård, L. (2012). Manual to the Questionnaire about Everyday Technology in Home and Society: Everyday Technology Use Questionnaire (ETUQ). Stockholm: Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Division of Occupational Therapy.Google Scholar
Nygård, L., Pantzar, M., Uppgard, B. and Kottorp, A. (2012). Detection of disability in older adults with MCI or Alzheimer's disease through assessment of perceived difficulty in using everyday technology: a replication study. Aging & Mental Health, 16, 361–371. doi: 10.1080/13607863.2011.605055.CrossRefGoogle ScholarPubMed
Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194. doi: 10.1111/j.1365-2796.2004.01388.x.CrossRefGoogle ScholarPubMed
Rabin, L. A. et al. (2015). Subjective cognitive decline in older adults: an overview of self-report measures used across 19 international research studies. Journal of Alzheimer's Disease, 48, S63–S86. doi:10.3233/JAD-150154.CrossRefGoogle Scholar
Reisberg, B. et al. (2008). The pre-mild cognitive impairment, subjective cognitive impairment stage of Alzheimer's disease. Alzheimer's & Dementia, 4, S98–S108. doi: 10.1016/j.jalz.2007.11.017.CrossRefGoogle ScholarPubMed
Roberts, R. and Knopman, D. S. (2013). Classification and epidemiology of MCI. Clinics in Geriatric Medicine, 29, 753–772. doi: 10.1016/j.cger.2013.07.003.CrossRefGoogle ScholarPubMed
Rosenberg, L., Nygård, L. and Kottorp, A. (2009). Everyday technology use questionnaire (ETUQ) – psychometric evaluation of a new assessment of competence in technology use. OTJR: Occupation, Participation and Health, 29, 52–62. doi: 10.3928/15394492-20090301-05.Google Scholar
Rosenberg, P. B. and Lyketsos, C. G. (2008). Mild cognitive impairment: searching for the prodrome of Alzheimer's disease. World Psychiatry, 7, 72–78. doi: 10.1002/j.2051-5545.2008.tb00159.x.CrossRefGoogle ScholarPubMed
Royal, D. R., Mahurin, R. K. and Gray, G. F. (1992). Bedside assessment of executive cognitive impairment: the executive interview. Journal of the American Geriatrics Society, 40, 1221–1226. doi: 10.1111/j.1532-5415.1992.tb03646.x.CrossRefGoogle Scholar
Ryd, C., Nygård, L., Malinowsky, C., Öhman, A. and Kottorp, A. (2015). Associations between activities of daily living and everyday technology. Scandinavian Journal of Occupational Therapy, 22, 33–42. doi: 10.3109/11038128.2014.964307.CrossRefGoogle ScholarPubMed
Statistical Package for Social Sciences (2015). Version 23.0. Chicago: SPSS Inc.Google Scholar
Stewart, R (2012). Subjective cognitive impairment. Current Opinion in Psychiatry, 25, 445–450.CrossRefGoogle ScholarPubMed
Wallin, A. et al. (1996). Stepwise comparative status analysis (STEP): a tool for identification of regional brain syndromes in dementia. Journal of Geriatric Psychiatry and Neurology, 9, 185–199. doi: 10.1177/089198879600900406.CrossRefGoogle ScholarPubMed
Wallin, A. et al. (2016). The Gothenburg MCI study: design and distribution of Alzheimer's disease and subcortical vascular disease diagnoses from baseline to 6-year follow up. Journal of Cerebral Blood Flow & Metabolism, 36, 114–131. doi: 10.1038/jcbfm.2015.147.CrossRefGoogle Scholar