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A comparison of immersive virtual reality with traditional neuropsychological measures in the assessment of executive functions

Published online by Cambridge University Press:  09 May 2017

Sophie Melissa Clare Davison ,
Catherine Deeprose  and
Sylvia Terbeck
Sophie Melissa Clare Davison
Affiliation:
Department of Psychology, Faculty of Health and Human Sciences, University of Plymouth, Plymouth, UK
Catherine Deeprose*
Affiliation:
Department of Psychology, Faculty of Health and Human Sciences, University of Plymouth, Plymouth, UK
Sylvia Terbeck
Affiliation:
Department of Psychology, Faculty of Health and Human Sciences, University of Plymouth, Plymouth, UK
*
Dr. Catherine Deeprose, Department of Psychology, Faculty of Health and Human Sciences, University of Plymouth, Plymouth, England. Tel: +44 (0) 1752 585883; E-mail: catherine.deeprose@plymouth.ac.uk
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Abstract

Objective

This study investigated immersive virtual reality (IVR), as a novel technique to test executive function of healthy younger and older adults. We predicted IVR tasks to have greater predictive power than traditional measures when assessing age-related cognitive functioning due to the real-world validity of the tasks.

Methods

Participants (n=40) completed the Stroop colour–word test and the trail-making test (TMT) as traditional and commonly used assessments of executive functioning. Participants then completed three IVR tasks; a seating arrangement task, an item location task (both set in a virtual chemistry lab), and a virtual parking simulator.

Results

Younger adults completed significantly more parking simulator levels (p<0.001), placed significantly more objects (p<0.001), and located significantly more items than older adults (p<0.01), demonstrating higher levels of performance. Significant correlations were found between performance on traditional neuropsychological measures and IVR measures. For example, Stroop CW performance significantly correlated with the number of parking simulator levels completed (τ=0.43, p<0.01). This suggests that IVR measures assess the same underlying cognitive constructs as traditional tasks. In addition, IVR measures contributed a significant percentage of the explained variance in age.

Conclusion

IVR measures (i.e. number of parking simulator levels completed and number of objects placed in the seating arrangement task) were found to be stronger contributors than existing traditional neuropsychological tasks in predicting age-related cognitive decline. Future research should investigate the implementation of these real-world-based tasks in clinical groups given this promising initial work.

Keywords

ageingexecutive functionimmersive virtual realityneuropsychological assessment

Information

Type
Original Article
Information
Acta Neuropsychiatrica , Volume 30 , Issue 2 , April 2018 , pp. 79 - 89
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Copyright
© Scandinavian College of Neuropsychopharmacology 2017 

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References

1. Diamond, A. Executive functions. Ann Rev Psychol 2013;64:135–168.Google Scholar
2. Huizinga, M, Dolan, CV, Van Der Molen, MW. Age-related change in executive function: developmental trends and a latent variable analysis. Neuropsychologia. 2006;44:2017–2036.Google Scholar
3. Hongwanishkul, D, Happaney, KR, Lee, WS, Zelazo, PD. Assessment of hot and cool executive function in young children: age-related changes and individual differences. Dev Neuropsychol. 2005;28:617–644.CrossRefGoogle ScholarPubMed
4. Happé, F, Booth, R, Charlton, R, Hughes, C. Executive function deficits in autism spectrum disorders and attention-deficit/hyperactivity disorder: examining profiles across domains and ages. Brain Cogn 2006;61:25–39.CrossRefGoogle ScholarPubMed
5. Zelazo, PD, Craik, FI, Booth, L. Executive function across the life span. Acta psychologica. 2004;115:167–183.CrossRefGoogle ScholarPubMed
6. Baudic, S, Dalla Barba, G, Thibaudet, MC, Smagghe, A, Remy, P, Traykov, L. Executive function deficits in early Alzheimer’s disease and their relations with episodic memory. Arch Clin Neuropsychol 2006;21:15–21.CrossRefGoogle ScholarPubMed
7. Stroop, JR. Studies of interference in serial verbal reactions. J Exp Psychol 1935;18:643–662.Google Scholar
8. Battery, AI. Army individual test battery. Manual of directions and scoring. Washington, DC: War Department, Adjutant General’s Office, 1944.Google Scholar
9. Spieler, DH, Balota, DA, Faust, ME. Stroop performance in healthy younger and older adults and in individuals with dementia of the Alzheimer’s type. J Exp Psychol 1996;22:461–479.Google Scholar
10. West, R, Alain, C. Age-related decline in inhibitory control contributes to the increased Stroop effect observed in older adults. Psychophysiology. 2000;37:179–189.Google Scholar
11. Müller, LD, Guhn, A, Zeller, JB et al. Neural correlates of a standardized version of the trail making test in young and elderly adults: a functional near-infrared spectroscopy study. Neuropsychologia. 2014;56:271–279.Google Scholar
12. Tombaugh, TN. Trail making test A and B: normative data stratified by age and education. Arch Clin Neuropsychol 2004;19:203–214.CrossRefGoogle Scholar
13. Parsons, TD, Silva, TM, Pair, J, Rizzo, AA. Virtual environment for assessment of neurocognitive functioning: virtual reality cognitive performance assessment test. Stud Health Technol Inform 2008;132:351–356.Google Scholar
14. Karagiozis, H, Gray, S, Sacco, J, Shapiro, M, Kawas, C. The Direct Assessment of Functional Abilities (DAFA): a comparison to an indirect measure of instrumental activities of daily living. Gerontologist. 1998;38:113–121.Google Scholar
15. Elkind, JS, Rubin, E, Rosenthal, S, Skoff, B, Prather, P. A simulated reality scenario compared with the computerized Wisconsin Card Sorting Test: an analysis of preliminary results. Cyberpsychol Behav 2001;4:489–496.Google Scholar
16. Rizzo, AA, Schultheis, M, Kerns, KA, Mateer, C. Analysis of assets for virtual reality applications in neuropsychology. Neuropsychol Rehabil. 2004;14:207–239.Google Scholar
17. Rand, D, Rukan, SB, Weiss, PL, Katz, N. Validation of the virtual MET as an assessment tool for executive functions. Neuropsychol Rehabil. 2009;19:583–602.CrossRefGoogle ScholarPubMed
18. 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;44:1333–1347.Google Scholar
19. Kang, YJ, Ku, J, Han, K et al. Development and clinical trial of virtual reality-based cognitive assessment in people with stroke: preliminary study. Cyberpsychol Behav 2008;11:329–339.CrossRefGoogle ScholarPubMed
20. Jansari, AS, Froggatt, D, Edginton, T, Dawkins, L. Investigating the impact of nicotine on executive functions using a novel virtual reality assessment. Addiction. 2013;108:977–984.Google Scholar
21. Jansari, AS, Devlin, A, Agnew, R, Akesson, K, Murphy, L, Leadbetter, T. Ecological assessment of executive functions: a new virtual reality paradigm. Brain Impairment 2014;15:71–87.Google Scholar
22. Soar, K, Chapman, E, Lavan, N, Jansari, AS, Turner, JJ. Investigating the effects of caffeine on executive functions using traditional Stroop and a new ecologically-valid virtual reality task, the Jansari assessment of Executive Functions (JEF©). Appetite. 2016;105:156–163.Google Scholar
23. Renison, B, Ponsford, J, Testa, R, Richardson, B, Brownfield, K. Virtual library task. Melbourne, Victoria, Australia: Monash University, 2008.Google Scholar
24. Yamaguchi, T, Foloppe, DA, Richard, P, Richard, E, Allain, P. A dual-modal virtual reality kitchen for (re) learning of everyday cooking activities in Alzheimer’s disease. Presence 2012;21:43–57.Google Scholar
25. Werner, P, Rabinowitz, S, Klinger, E, Korczyn, AD, Josman, N. Use of the virtual action planning supermarket for the diagnosis of mild cognitive impairment. Dement Geriatr Cogn Disord 2009;27:301–309.Google Scholar
26. Shallice, TI, Burgess, PW. Deficits in strategy application following frontal lobe damage in man. Brain. 1991;114:727–741.CrossRefGoogle ScholarPubMed
27. Raspelli, S, Pallavicini, F, Carelli, L et al. Validating the neuro VR-based virtual version of the multiple errands test: preliminary results. Presence 2012;21:31–42.Google Scholar
28. Vourvopoulos, A, Faria, AL, Ponnam, K, Bermudez, I, Badia, S. RehabCity: design and validation of a cognitive assessment and rehabilitation tool through gamified simulations of activities of daily living. Proceedings of the 11th Conference on Advances in Computer Entertainment Technology. 2014, vol. 11, p. 26.Google Scholar
29. Trenerry, MR, Crosson, B, Deboe, J, Leher, WR. Stroop neuropsychological screening test. Lutz, FL: Psychological Assessment Resources, 1989.Google Scholar
30. Alaska Department of Administration. Trail making test parts A & B. Available at http://doa.alaska.gov/dmv/akol/pdfs/uiowa_trailmaking.pdf. Accessed 2 June 2016.Google Scholar
31. Lécuyer, A, Lotte, F, Reilly, RB, Leeb, R, Hirose, M, Slater, M. Brain-computer interfaces, virtual reality, and videogames. IEEE Comp 2008;41:66–72.Google Scholar
32. Oculus Rift Development Kit 2 (DK2). Available at https://www3.oculus.com/en-us/dk2/ Accessed 18 August 2016.Google Scholar
33. Salthouse, TA. The processing-speed theory of adult age differences in cognition. Psychol Rev. 1996;103:403–428.Google Scholar
34. VIRTUIX. Explore virtual worlds without limits. Available at http://www.virtuix.com/ Accessed 31 May 2016.Google Scholar