Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-25T01:03:30.664Z Has data issue: false hasContentIssue false

The impact of multiple sclerosis on patients’ performance on the Stroop Test: Processing speed versus interference

Published online by Cambridge University Press:  01 May 2009

DOUGLAS R. DENNEY*
Affiliation:
Department of Psychology, University of Kansas, Lawrence, Kansas
SHARON G. LYNCH
Affiliation:
Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas
*
*Correspondence and reprint requests to: Douglas R. Denney, Department of Psychology, University of Kansas, 1415 Jayhawk Boulevard, Lawrence, Kansas 66045-7556. E-mail: denney@ku.edu

Abstract

Deficits in multiple sclerosis (MS) patients’ performance on the Stroop Test have been attributed to problems with processing speed and selective attention. Data for 248 MS patients and 178 controls on all three trials of the Stroop were combined using various scoring formulas proposed for assessing processing speed, color difficulty, and interference. The greatest differences between patients and controls involved processing speed. Formulas purporting to measure interference yielded highly inconsistent results: Significant differences between groups were found on two of the most common measures but were in opposite directions. This contradiction stems from the failure of both measures to effectively control for processing speed when assessing interference. Three alternative measures, using relative, ratio, and residualized scores, offer much better indices of interference. When assessed with these alternative measures, interference increased with age, but no differences between patients and controls were found. Difficulties that MS patients have with the Stroop Test are confined to processing speed. (JINS, 2009, 15, 451–458.)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2009

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

REFERENCES

Bodling, A.M., Denney, D.R., & Lynch, S.G. (2008). Rapid serial processing in patients with multiple sclerosis: The role of peripheral deficits. Journal of the International Neuropsychological Society, 14, 646650.CrossRefGoogle ScholarPubMed
Caltagirone, C., Carlesimo, G.A., Fadda, L., & Roncacci, S. (1991). Cognitive function in multiple sclerosis: A subcortical pattern of neuropsychological impairment? Behavioural Neurology, 4, 129141.CrossRefGoogle ScholarPubMed
Capitani, E.M., Laiacona, M.M., Barbarotto, R.M., & Cossa, F.M. (1999). How can we evaluate interference in attentional tests? A study based on bi-variate non-parametric tolerance limits. Journal of Clinical and Experimental Neuropsychology, 21, 216228.CrossRefGoogle ScholarPubMed
Cronbach, L.J. & Furby, L. (1970). How we should measure change—or should we? Psychological Bulletin, 74, 6880.CrossRefGoogle Scholar
Cummings, J.L. & Benson, D.F. (1984). Subcortical dementia: Review of an emerging concept. Archives of Neurology, 41, 874879.CrossRefGoogle ScholarPubMed
Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Function System (D-KEFS). San Antonio, TX: The Psychological Corporation.Google Scholar
DeLuca, J., Chelune, G.J., Tulsky, D.S., Lengenfelder, J., & Chiaravalloti, N.D. (2004). Is speed of processing or working memory the primary information processing deficit in multiple sclerosis? Journal of Clinical and Experimental Neuropsychology, 26(4), 550562.CrossRefGoogle ScholarPubMed
Denney, D.R., Lynch, S.G., Parmenter, B.A., & Horne, N. (2004). Cognitive impairment in relapsing and primary progressive multiple sclerosis: Mostly a matter of speed. Journal of the International Neuropsychological Society, 10, 948956.CrossRefGoogle ScholarPubMed
Denney, D.R., Sworowski, L.A., & Lynch, S.G. (2005). Cognitive impairment in three subtypes of multiple sclerosis. Archives of Clinical Neuropsychology, 20, 967981.CrossRefGoogle ScholarPubMed
van Dijk, J.G., Jennekens-Schindel, A., Caekebeke, J.F.V., & Zwinderman, A.H. (1992). Are event-related potentials in multiple sclerosis indicative of cognitive impairment? Evoked and event-related potentials, psychometric testing and response speed: A controlled study. Journal of the Neurological Sciences, 109, 1824.CrossRefGoogle ScholarPubMed
Felmingham, K.L., Baguley, I.J., & Green, A.M. (2004). Effects of diffuse axonal injury on speed of information processing following severe traumatic brain injury. Neuropsychology, 18, 564571.CrossRefGoogle ScholarPubMed
Foong, J., Rozewicz, L., Quaghebeur, G., Davie, C.A., Kartsounis, L.D., Thompson, A.J., Miller, D.H., & Ron, M.A. (1997). Executive function in multiple sclerosis: The role of frontal lobe pathology. Brain, 120, 1526CrossRefGoogle ScholarPubMed
Golden, C.J. (1978). The Stroop Color and Word Test. Wood Dale, IL: Stoelting Company.Google Scholar
Jennekens-Schinkel, A., Lanser, J.B.K., van der Velde, E.A., & Sanders, E.A.C.M. (1990). Performances of multiple sclerosis patients in tasks requiring language and visuoconstruction: Assessment of outpatients in quiescent disease stages. Journal of the Neurological Sciences, 95, 89103.CrossRefGoogle ScholarPubMed
Jensen, A.R. (1965). Scoring the Stroop test. Acta Psychologica, 24, 398408.CrossRefGoogle ScholarPubMed
Kail, R. (1998). Speed of information processing in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 20, 98106.CrossRefGoogle ScholarPubMed
Kalmar, J., Bryant, D., Tulsky, D., & DeLuca, J. (2004). Information processing deficits in multiple sclerosis: Does choice of screening instrument make a difference? Rehabilitation Psychology, 49, 213218.CrossRefGoogle Scholar
Krupp, L.B., LaRocca, N.G., Muir-Nash, J., & Steinberg, A.D. (1989). The fatigue severity scale: Application to patients with multiple sclerosis and systemic lupus erythematosus. Archives of Neurology, 46, 11211123.CrossRefGoogle ScholarPubMed
Kujala, P., Portin, R., Revonsuo, A., & Ruutiainen, J. (1994). Automatic and controlled information processing in multiple sclerosis. Brain, 117, 11151126.CrossRefGoogle ScholarPubMed
Kujala, P., Portin, R., Revonsuo, A., & Ruutiainen, J. (1995). Attention related performance in two cognitively different subtypes of patients with multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 59, 7782.CrossRefGoogle Scholar
Kurtzke, J.F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33, 14441452.CrossRefGoogle ScholarPubMed
Lansbergen, M.M., Kenemans, J.L., & van Engeland, H. (2007). Stroop interference and attention-deficit/hyperactivity disorder: A review and meta-analysis. Neuropsychology, 21, 251262.CrossRefGoogle ScholarPubMed
Lynch, S.G., Dickerson, K.J., & Denney, D.R. (2007, October 12). Speeded information processing in multiple sclerosis: A comparison of two measures. Paper presented at the 23rd Annual Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), Prague, Czech Republic.Google Scholar
Macniven, J.A., Davis, C., Ho, M.Y., Bradshaw, C.M., Szabadi, E., & Constantinescu, C.S. (2008) Stroop performance in multiple sclerosis: Information processing, selective attention, or executive functioning? Journal of the International Neuropsychological Society, 14, 805814.CrossRefGoogle ScholarPubMed
McCarthy, M., Beaumont, J.G., Thompson, R., & Peacock, S. (2005). Modality-specific aspects of sustained and divided attentional performance in multiple sclerosis. Archives of Clinical Neuropsychology, 20, 705718.CrossRefGoogle ScholarPubMed
Parmenter, B.A., Denney, D.R., & Lynch, S.G. (2003). The cognitive performance of patients with multiple sclerosis during periods of high and low fatigue. Multiple Sclerosis, 9, 111118.CrossRefGoogle ScholarPubMed
Potter, D.D., Jory, S.H., Bassett, M.R., Barrett, K., & Mychalkiw, W. (2002). Effect of mild head injury on event-related potential correlates of Stroop task performance. Journal of the International Neuropsychological Society, 8, 828837.CrossRefGoogle ScholarPubMed
Pujol, J., Vendrell, P., Deus, J., Junque, C., Bello, J., Marti-Vilalta, J.L., & Capdevila, A. (2001). The effect of medial frontal and posterior parietal demyelinating lesions on Stroop interference. NeuroImage, 13, 6875.CrossRefGoogle ScholarPubMed
Rabbitt, P., Scott, M., Lunn, M., Thacker, N., Lowe, C., Pendleton, N., Horan, M., & Jackson, A. (2007). White matter lesions account for all age-related declines in speed but not in intelligence. Neuropsychology, 21, 363370.CrossRefGoogle ScholarPubMed
Radloff, L. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385401.CrossRefGoogle Scholar
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology, 41, 685691.CrossRefGoogle ScholarPubMed
Reicker, L.I., Tombaugh, T.N., Walker, L., & Freedman, M.S. (2007). Reaction time: An alternative method for assessing the effects of multiple sclerosis on information processing speed. Archives of Clinical Neuropsychology, 22, 655664.CrossRefGoogle ScholarPubMed
Ryan, L., Clark, C.M., Klonoff, H., Li, D., & Paty, D. (1996). Patterns of cognitive impairment in relapsing-remitting multiple sclerosis and their relationship to neuropathology on magnetic resonance images. Neuropsychology, 10, 176193.CrossRefGoogle Scholar
Salo, R., Henik, A., & Robinson, L.C. (2001). Interpreting Stroop interference: An analysis of differences between task versions. Neuropsychology, 15, 462471.CrossRefGoogle ScholarPubMed
Scarrabelotti, M. & Carroll, M. (1999). Memory dissociation and metamemory in multiple sclerosis. Neuropsychologia, 37, 13351350.CrossRefGoogle ScholarPubMed
Seignourel, P.J., Robins, D.L., Larson, M.J., Demery, J.A., Cole, M., & Perlstein, W.M. (2005). Cognitive control in closed head injury: Context maintenance dysfunction or prepotent response inhibition deficit? Neuropsychology, 19, 578590.CrossRefGoogle ScholarPubMed
Steiger, K.A., Denney, D.R., & Lynch, S.G. (2008, September 18). Information processing in multiple sclerosis: Accuracy versus speed. Paper presented at the World Congress for Treatment and Research in Multiple Sclerosis, Montreal, Canada.Google Scholar
Stroop, J.R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643661.CrossRefGoogle Scholar
Van den Burg, W., van Zomeren, A.H., Minderhoud, J.M., Prange, A.J.A., & Meijer, N.S.A. (1987). Cognitive impairment in patients with multiple sclerosis and mild physical disability. Archives of Neurology, 44, 494501.CrossRefGoogle ScholarPubMed
Vitkovitch, M., Bishop, S., Dancey, C., & Richards, A. (2002). Stroop interference and negative priming in patients with multiple sclerosis. Neuropsychologia, 40, 15601574.CrossRefGoogle ScholarPubMed
Ylikoski, R., Ylikoski, A., Erkinjuntti, T., Sulkava, R., Raininko, R., & Tilvis, R. (1993). White matter changes in healthy elderly adult persons correlate with attention and speed of processing. Archives of Neurology, 50, 818824.CrossRefGoogle Scholar