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Comparing Performance of Young Adults on a Computer-based Version of the Austin Maze and the Conventional Form of the Test

Published online by Cambridge University Press:  17 January 2013

Adam McKay ,
Shuzi Lee ,
Rene Stolwyk  and
Jennie Ponsford
Adam McKay*
Affiliation:
School of Psychology and Psychiatry, Monash University, Melbourne, Australia Monash-Epworth Rehabilitation Research Centre, Epworth Hospital, Melbourne, Australia Epworth Rehabilitation, Epworth Healthcare, Melbourne, Australia
Shuzi Lee
Affiliation:
School of Psychology and Psychiatry, Monash University, Melbourne, Australia
Rene Stolwyk
Affiliation:
School of Psychology and Psychiatry, Monash University, Melbourne, Australia
Jennie Ponsford
Affiliation:
School of Psychology and Psychiatry, Monash University, Melbourne, Australia Monash-Epworth Rehabilitation Research Centre, Epworth Hospital, Melbourne, Australia
*
Address for correspondence: Dr Adam McKay, School of Psychology and Psychiatry, Monash University, Clayton Campus, Wellington Road, Building 17, VIC 3800, Australia. E-mail: [email protected]
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Abstract

The Austin Maze has declined in use in both clinical and research contexts due to difficulties in accessing the conventional button-box form of the test. Computer-based versions of the Austin Maze offer a potential means of making the test more accessible, but as yet there is limited evidence regarding the equivalence of computer and conventional versions of the Austin Maze. The present study compared performance on a computer version of the Austin Maze by Bray and McDonald with performance on the traditional button maze in 63 participants aged 18–27 years. The results showed no differences between the computer and conventional versions in terms of mean scores and distributions, and performances on the two versions were significantly correlated. Examination of correlates found no relationship between Austin Maze performance and years of education or age for either version of the Austin Maze performance. Intellectual function was modestly associated with performance on the conventional version but not the computer version. Overall, these findings suggest that scores on the Bray and McDonald computer version of the Austin Maze produces comparable scores to the conventional form of the test and can be interpreted using existing normative data.

Keywords

Austin Mazecomputerequivalencevalidation
Type
Articles
Information
Brain Impairment , Volume 13 , Issue 3 , December 2012 , pp. 339 - 346
Copyright
Copyright © The Authors 2013

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References

American Psychological Association. (1986). Guidelines for computer based tests and interpretations. Washington, DC: APA.Google Scholar
Barker, M.J., Greenwood, K.M., Jackson, M., & Crowe, S.F. (2005). An evaluation of persisting cognitive effects after withdrawal from long-term benzodiazepine use. Journal of the International Neuropsychological Society, 11 (3), 281–289.CrossRefGoogle ScholarPubMed
Bowden, S.C. (1988). Learning in young alcoholics. Journal of Clinical and Experimental Neuropsychology, 10 (2), 157–168.CrossRefGoogle ScholarPubMed
Bowden, S.C. (1989). Maze learning: Reliability and equivalence of alternate pathways. Clinical Neuropsychologist, 3 (2), 137–144.CrossRefGoogle Scholar
Bowden, S. C., Dumendzic, J., Hopper, J., Kinsella, G., Clifford, C., & Tucker, A. (1992). Healthy adults’ performance on the Austin Maze. Clinical Neuropsychologist, 6 (1), 43–52.CrossRefGoogle Scholar
Bray, R., & McDonald, S. (2010). Austin Maze. Sydney: Australian Society for the Study of Brain Impairment.Google Scholar
Bugbee, A.C.J. (1996). The equivalence of paper-and-pencil and computer-based testing. Journal of Research on Computing in Education, 28 (3), 282–299.CrossRefGoogle Scholar
Bugbee, A.C.J., & Bernt, F.M. (1990). Testing by computer: Findings in six years of use 1982–1988. Journal of Research on Computing in Education, 23 (1), 87–100.CrossRefGoogle Scholar
Bunderson, A.C., Inouye, D.K., & Olsen, J.B. (1989). The four generations of computerized educational measurement. In Linn, R.L. (Ed.), Educational measurement (3rd ed., pp. 367–407). New York: American Council on Education - Macmillan.Google Scholar
Choca, J., & Morris, J. (1992). Administering the Category Test by computer: Equivalence of results. Clinical Neuropsychologist, 6 (1), 9–15.CrossRefGoogle Scholar
Clayton, S.N., & Dunlap, W.P. (1987). Averaging correlation coefficients: Should Fisher's z transformation be used? Journal of Applied Psychology, 72 (1), 146–148.Google Scholar
Cohen, J.W. (1988). Statistical power analysis for the behavioural science (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.Google Scholar
Crook, T.H., Kay, G.G., & Larrabee, G.J. (2009). Computer-based cognitive testing. In Grant, I. & Adams, K.M. (Eds.), Neuropsychological assessment of neuropsychiatric and neuromedical disorders (3rd ed., pp. 84–100). New York, NY: Oxford University Press.Google Scholar
Crowe, S.F., Barclay, L., Brennan, S., Farkas, L., Gould, E., Katchmarsky, S., . . . Vayda, S. (1999). The cognitive determinants of performance on the Austin Maze. Journal of the International Neuropsychological Society, 5 (1), 1–9.CrossRefGoogle ScholarPubMed
Darby, D., & Walsh, K.W. (2005). Walsh's neuropsychology: A clinical approach (5th ed.). Edinburgh: Churchill Livingstone.Google Scholar
De Renzi, E. (1982). Disorders of space exploration and cognition. Chichester: Wiley.Google Scholar
Donnan, G.A., Bladin, P.F., Berkovic, S.F., Longley, W.A., & Saling, M.M. (1991). The stroke syndrome of striatocapsular infarction. Brain, 114 (Pt 1A), 51–70.Google ScholarPubMed
Ferguson, C.J. (2009). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40 (5), 532–538.CrossRefGoogle Scholar
Fowler, K.S., Saling, M.M., Conway, E.L., Semple, J.M., & Louis, W.J. (2002). Paired associate performance in the early detection of DAT. Journal of the International Neuropsychological Society, 8 (1), 58–71.CrossRefGoogle ScholarPubMed
Gunstad, J., Paul, R.H., Cohen, R.A., Tate, D.F., Spitznagel, M.B., & Gordon, E. (2007). Elevated body mass index is associated with executive dysfunction in otherwise healthy adults. Comprehensive Psychiatry, 48 (1), 57–61.CrossRefGoogle ScholarPubMed
Kane, R.L., & Kay, G.G. (1992). Computerized assessment in neuropsychology: A review of tests and test batteries. Neuropsychology Review, 3 (1), 1–117.CrossRefGoogle ScholarPubMed
Kinsella, G., Prior, M., Sawyer, M., Murtagh, D., Eisenmajer, R., Anderson, V., . . . Klug, G. (1995). Neuropsychological deficit and academic performance in children and adolescents following traumatic brain injury. Journal of Pediatric Psychology, 20 (6), 753–767.CrossRefGoogle ScholarPubMed
Llabre, M.M., Clements, N.E., Fitzhugh, K.B., Lancelotta, G., Mazzagatti, R.D., & Quinones, N. (1987). The effect of computer-administered testing on test anxiety and performance. Journal of Educational Computing Research, 3 (4), 429–433.CrossRefGoogle Scholar
Mattson, D., Berk, M., & Lucas, M.D. (1997). A neuropsychological study of prefrontal lobe function in the positive and negative subtypes of schizophrenia. Journal of Genetic Psychology, 158, 487–494.CrossRefGoogle ScholarPubMed
Mercer, W.N., Harrell, E., Miller, D.C., Childs, H.W., & Rockers, D.M. (1997). Performance of brain-injured versus healthy adults in three versions of the Category Test. Clinical Neuropsychologist, 11 (2), 174–179.CrossRefGoogle Scholar
Milner, B. (1965). Visually-guided maze learning in man: Effects of bilateral hippocampal, bilateral frontal, and unilateral cerebral lesions. Neuropsychologia, 3 (4), 317–338.CrossRefGoogle Scholar
Morrison, P., & Gates, G. (1988). Assessment of a microcomputer-based version of the Austin Maze. Journal of General Psychology, 115 (3), 307–314.CrossRefGoogle ScholarPubMed
Porteus, S.D. (1950). The Porteus Maze Test and intelligence (pp. vi, 194). Oxford, England: Pacific Books.Google Scholar
Russell, M., Goldberg, A., & O'Connor, K. (2003). Computer-based testing and validity: A look back into the future. Assessment in Education: Principles, Policy & Practice, 10 (3), 279–293.Google Scholar
Sullivan, K. (1997). Which tests do neuropsychologists use? Journal of Clinical Psychology, 53 (7), 657–661.3.0.CO;2-F>CrossRefGoogle ScholarPubMed
Tucker, A., Kinsella, G., Gawith, M., & Harrison, G. (1987). Performance on the Austin Maze: Steps towards normative data. Australian Psychologist, 22 (3), 353–359.CrossRefGoogle Scholar
Walsh, K.W. (1978). Neuropsychology: A clinical approach. Edinburgh: Churchill Livingstone.Google Scholar
Walsh, K.W. (1985). Understanding brain damage: a primer of neuropsychological evaluation. Edinburgh: Churchill Livingstone.Google Scholar
Wechsler, D. (2001). Wechsler Test of Adult Reading. San Antonio, Texas: Psychological Corporation.Google Scholar
Zimmerman, D.W. (1994). A note on the influence of outliers on parametric and nonparametric tests. Journal of General Psychology, 121 (4), 391–401.CrossRefGoogle Scholar