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ELECTRONIC DEVICES FOR COGNITIVE IMPAIRMENT SCREENING: A SYSTEMATIC LITERATURE REVIEW

Published online by Cambridge University Press:  18 September 2017

J. Antonio García-Casal
Affiliation:
University of Salamanca, Department of Research and Development, Iberian Research Psycho-sciences [email protected]
Manuel Franco-Martín
Affiliation:
University of Salamanca, Department of Psychiatry, Zamora Hospital
M. Victoria Perea-Bartolomé
Affiliation:
University of Salamanca
J. Miguel Toribio-Guzmán
Affiliation:
Department of Research and Development, Iberian Research Psycho-sciences Institute
Carlos García-Moja
Affiliation:
Department of Psychiatry, Burgos University Hospital
Miguel Goñi-Imizcoz
Affiliation:
Department of Neurology, Burgos University Hospital
Emese Csipke
Affiliation:
University CollegeLondon

Abstract

Objectives: The reduction in cognitive decline depends on timely diagnosis. The aim of this systematic review was to analyze the current available information and communication technologies-based instruments for cognitive decline early screening and detection in terms of usability, validity, and reliability.

Methods: Electronic searches identified 1,785 articles of which thirty-four met the inclusion criteria and were grouped according to their main purpose into test batteries, measures of isolated tasks, behavioral measures, and diagnostic tools.

Results: Thirty one instruments were analyzed. Fifty-two percent were personal computer based, 26 percent tablet, 13 percent laptop, and 1 was mobile phone based. The most common input method was touchscreen (48 percent). The instruments were validated with a total of 4,307 participants: 2,146 were healthy older adults (M = 73.59; SD = 5.12), 1,104 had dementia (M = 74.65; SD = 3.98) and 1,057 mild cognitive impairment (M = 74.84; SD = 4.46). Only 6 percent were administered at home, 19 percent reported outcomes about usability, and 22 percent about understandability. The methodological quality of the studies was good, the weakest methodological area being usability. Most of the instruments obtained acceptable values of specificity and sensitivity.

Conclusions: It is necessary to create home delivered instruments and to include usability studies in their design. Involvement of people with cognitive decline in all phases of the development process is of great importance to obtain valuable and user-friendly products. It would be advisable for researchers to make an effort to provide cutoff points for their instruments.

Type
Assessments
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

1. Eurostat. European-Comission [Internet]. Eurostat publications and databases. 2016. http://ec.europa.eu/eurostat (accessed April 9, 2017).Google Scholar
2. Bruscoli, M, Lovestone, S. Is MCI really just early dementia? A systematic review of conversion studies. Int Psychogeriatr. 2004;16:129140.Google Scholar
3. Geldmacher, DS, Kirson, NY, Birnbaum, HG, et al. Implications of early treatment among Medicaid patients with Alzheimer's disease. Alzheimers Dement. 2014;10:214224.Google Scholar
4. Huntley, J, Gould, R, Liu, K, Smith, M, Howard, R. Do cognitive interventions improve general cognition in dementia? A meta-analysis and meta-regression. BMJ Open. 2015;5:e005247.Google Scholar
5. Yu, SY, Lee, TJ, Jang, SH, et al. Cost-effectiveness of nationwide opportunistic screening program for dementia in South Korea. J Alzheimers Dis. 2015;44:195204.Google Scholar
6. Furiak, NM, Kahle-Wrobleski, K, Callahan, C, et al. Screening and treatment for Alzheimer's disease: Predicting population-level outcomes. Alzheimers Dement. 2012;8:3138.Google Scholar
7. Snyder, PJ, Jackson, CE, Petersen, RC, et al. Assessment of cognition in mild cognitive impairment: A comparative study. Alzheimers Dement. 2011;7:338355.Google Scholar
8. Zygouris, S, Tsolaki, M. Computerized cognitive testing for older adults: A review. Am J Alzheimers Dis Other Demen. 2015;30:1328.Google Scholar
9. Wild, K, Howieson, D, Webbe, F, Seelye, A, Kaye, J. Status of computerized cognitive testing in aging: A systematic review. Alzheimers Dement. 2008;4:428437.Google Scholar
10. Kim, H, Hsiao, CP, Do, EYL. Home-based computerized cognitive assessment tool for dementia screening. J Amb Intel Smart Environ. 2012;4:429442.Google Scholar
11. Schlegel, RE, Gilliland, K. Development and quality assurance of computer-based assessment batteries. Arch Clin Neuropsychol. 2007;22 (Suppl):S49S61.Google Scholar
12. Tierney, Lermer MA. Computerized cognitive assessment in primary care to identify patients with suspected cognitive impairment. J Alzheimers Dis. 2010;20:823832.Google ScholarPubMed
13. ISO 9241-210 [Internet]. Ergonomics of human-system interaction - Part 210: Human-centred design for interactive systems: International Organization for Standardization; 2010. https://www.iso.org/obp/ui/#iso:std:iso:9241:-210:ed-1:v1:en (accessed July 14, 2016).Google Scholar
14. Zapata, BC, Fernandez-Aleman, JL, Idri, A, Toval, A. Empirical studies on usability of mHealth apps: A systematic literature review. J Med Syst. 2015;39:1.Google Scholar
15. Rauschenberger, M, Schrepp, M, Cota, MP, Olschner, S, Thomaschewski, J. Efficient measurement of the user experience of interactive products. How to use the user experience questionnaire (ueq). example: Spanish language version. IJIMAI. 2013;2:3945.CrossRefGoogle Scholar
16. Meiland, F, Innes, A, Mountain, G, et al. Technologies to support community-dwelling persons with dementia: A position paper on issues regarding development, usability, effectiveness and cost-effectiveness, deployment, and ethics. JMIR Rehabil Assist Technol. 2017;4:e1.Google Scholar
17. Span, M, Hettinga, M, Vernooij-Dassen, M, Eefsting, J, Smits, C. Involving people with dementia in the development of supportive IT applications: A systematic review. Ageing Res Rev. 2013;12:535551.Google Scholar
18. Jacova, C, McGrenere, J, Lee, HS, et al. C-TOC (Cognitive Testing on Computer): Investigating the usability and validity of a novel self-administered cognitive assessment tool in aging and early dementia. Alzheimer Dis Assoc Disord. 2015; 29:213221.Google Scholar
19. O'Halloran, JP, Kemp, AS, Salmon, DP, Tariot, PN, Schneider, LS. Psychometric comparison of standard and computerized administration of the Alzheimer's Disease Assessment Scale: Cognitive Subscale (ADASCog). Curr Alzheimer Res. 2011;8:323328.CrossRefGoogle ScholarPubMed
20. Solís-Rodríguez, A [Internet]. Estudio preliminar del cogval-senior, una nueva prueba informatizada para la detección de la demencia Alzheimer en personas mayores. Salamanca: Universidad de Salamanca; 2014. https://gredos.usal.es/jspui/handle/10366/124217 (accessed July 9, 2017).Google Scholar
21. Memoria, CM, Yassuda, MS, Nakano, EY, Forlenza, OV. Contributions of the Computer-Administered Neuropsychological Screen for Mild Cognitive Impairment (CANS-MCI) for the diagnosis of MCI in Brazil. Int Psychogeriatr. 2014:19.Google ScholarPubMed
22. Onoda, K, Hamano, T, Nabika, Y, et al. Validation of a new mass screening tool for cognitive impairment: Cognitive assessment for dementia, iPad version. Clin Interv Aging. 2013;8:353360.Google Scholar
23. Fredrickson, J, Maruff, P, Woodward, M, et al. Evaluation of the usability of a brief computerized cognitive screening test in older people for epidemiological studies. Neuroepidemiology. 2010;34:6575.Google Scholar
24. Tierney, M, Naglie, G, Upshur, R, et al. Feasibility and validity of the self-administered computerized assessment of mild cognitive impairment with older primary care patients. Alzheimer Dis Assoc Disord. 2014;28:311319.CrossRefGoogle ScholarPubMed
25. Brooker, D. What is person-centred care in dementia? Rev Clin Gerontol. 2003;13:215222.CrossRefGoogle Scholar
26. Schikhof, Y, Mulder, I, Choenni, S. Who will watch (over) me? Humane monitoring in dementia care. Int J Hum Comput Stud. 2010;68:410422.Google Scholar
27. Harrell, KM, Wilkins, SS, Connor, MK, Chodosh, J. Telemedicine and the evaluation of cognitive impairment: The additive value of neuropsychological assessment. J Am Med Dir Assoc. 2014;15:600606.Google Scholar
28. Sun, M, Burke, LE, Mao, ZH, et al. eButton: A wearable computer for health monitoring and personal assistance. Proc Des Autom Conf. 2014;2014:16.Google ScholarPubMed
29. Canini, M, Battista, P, Della Rosa, PA, et al. Computerized neuropsychological assessment in aging: Testing efficacy and clinical ecology of different interfaces. Comput Math Methods Med. 2014;2014:804723.CrossRefGoogle ScholarPubMed
30. Hassenzahl, M, Tractinsky, N. User experience-a research agenda. Behav Inf Technol. 2006;25:9197.Google Scholar
31. Allain, P, Foloppe, DA, Besnard, J, et al. Detecting everyday action deficits in Alzheimer's disease using a nonimmersive virtual reality kitchen. J Int Neuropsychol Soc. 2014;20:468477.CrossRefGoogle ScholarPubMed
32. Plancher, G, Tirard, A, Gyselinck, V, Nicolas, S, Piolino, P. Using virtual reality to characterize episodic memory profiles in amnestic mild cognitive impairment and Alzheimer's disease: Influence of active and passive encoding. Neuropsychologia. 2012;50:592602.Google Scholar
33. Weniger, G, Ruhleder, M, Lange, C, Wolf, S, Irle, E. Egocentric and allocentric memory as assessed by virtual reality in individuals with amnestic mild cognitive impairment. Neuropsychologia. 2011;49:518527.Google Scholar
34. Zygouris, S, Giakoumis, D, Votis, K, et al. Can a virtual reality cognitive training application fulfill a dual role? Using the virtual supermarket cognitive training application as a screening tool for mild cognitive impairment. J Alzheimers Dis. 2015;44:13331347.CrossRefGoogle ScholarPubMed
35. Friedman, TW, Yelland, GW, Robinson, SR. Subtle cognitive impairment in elders with Mini-Mental State Examination scores within the ‘normal’ range. Int J Geriatr Psychiatry. 2012;27:463471.Google Scholar
36. Lund, AM. Measuring usability with the USE Questionnaire. Usability Interface. 2001;8:36.Google Scholar
37. Rosenberg, L, Kottorp, A, Winblad, B, Nygård, L. Perceived difficulty in everyday technology use among older adults with or without cognitive deficits. Scand J Occup Ther. 2009;16:216226.Google Scholar
38. Lewis, JR. Psychometric evaluation of an after-scenario questionnaire for computer usability studies: The ASQ. ACM SIGCHI Bull. 1991;23:7881.Google Scholar
39. Lewis, JR, Sauro, J. The factor structure of the System Usability Scale. In: Kurosu, M, editor. Human centered design. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer; 2009. vol 5619.Google Scholar
40. Venkatesh, V, Morris, MG, Davis, GB, Davis, FD. User acceptance of information technology: Toward a unified view. MIS Q. 2003;27:425478.CrossRefGoogle Scholar
41. Baez, S, Couto, B, Herrera, E, et al. Tracking the cognitive, social, and neuroanatomical profile in early neurodegeneration: Type III Cockayne syndrome. Front Aging Neurosci. 2013;5:80.Google Scholar
42. Nygård, L, Starkhammar, S. The use of everyday technology by people with dementia living alone: Mapping out the difficulties. Aging Ment Health. 2007;11:144155.Google Scholar
43. Malinowsky, C, Almkvist, O, Kottorp, A, Nygard, L. Ability to manage everyday technology: A comparison of persons with dementia or mild cognitive impairment and older adults without cognitive impairment. Disabil Rehabil Assist Technol. 2010;5:462469.Google Scholar
44. Ismail, Z, Rajji, TK, Shulman, KI. Brief cognitive screening instruments: An update. Int J Geriatr Psychiatry. 2010;25:111120.Google Scholar
45. Bardram, JE, Hansen, TR, Mogensen, M, Soegaard, M. Experiences from real-world deployment of context-aware technologies in a hospital environment. UbiComp 2006: Ubiquitous Computing: Springer; 2006:369–386.Google Scholar
46. Ahmed, S, de Jager, C, Wilcock, G. A comparison of screening tools for the assessment of Mild Cognitive Impairment: Preliminary findings. Neurocase. 2012;18:336351.CrossRefGoogle ScholarPubMed
47. Liberati, G, Dalboni da Rocha, JL, van der Heiden, L, et al. Toward a brain-computer interface for Alzheimer's disease patients by combining classical conditioning and brain state classification. J Alzheimers Dis. 2012;31 (Suppl 3):S211S220.Google Scholar
48. Harrison, J. Internet screening of cognition as a method for recruiting to clinical trials in prodromal Alzheimer's disease. J Nutr Health Aging. 2013;17:778779.Google Scholar
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