Hostname: page-component-8448b6f56d-c4f8m Total loading time: 0 Render date: 2024-04-19T21:19:35.477Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment of information processing in working memory in applied settings: the paper & pencil memory scanning test

Published online by Cambridge University Press:  22 March 2007

WIM VAN DER ELST ,
MARTIN P. J. VAN BOXTEL ,
GERARD J. P. VAN BREUKELEN  and
JELLE JOLLES
WIM VAN DER ELST*
Affiliation:
Maastricht Brain and Behavior Institute, and European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
MARTIN P. J. VAN BOXTEL
Affiliation:
Maastricht Brain and Behavior Institute, and European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
GERARD J. P. VAN BREUKELEN
Affiliation:
Department of Methodology and Statistics, Maastricht University, Maastricht, The Netherlands
JELLE JOLLES
Affiliation:
Maastricht Brain and Behavior Institute, and European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
*
*Address for correspondence: Wim Van der Elst, Faculty of Medicine, Department of Psychiatry and Neuropsychology, Maastricht University, 6200 MD, Maastricht, The Netherlands. (Email: W.vanderelst@NP.unimaas.nl)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Sternberg's Memory Scanning Test (MST) is a useful paradigm for evaluating the speed and efficiency of information processing in working memory. Unfortunately, the classical MST has major drawbacks for use in applied settings such as the clinic. For example, its administration time is long and the test is too difficult for older people or people with cognitive disorders. It would be advantageous to have a test for the assessment of information processing in working memory for use in applied settings, for example in differential diagnostics in clinical settings.

Method

The MST was modified into a format that makes it more appropriate for use in the clinic, the Paper & Pencil MST (P&P MST). The influence of age and age-extrinsic factors on the P&P MST was evaluated in a large sample (n=1839) of healthy and cognitively intact adults (24–81 years) to establish the normal range of performance.

Results

Age and education affected all components of information processing in working memory. Gender did not affect the non-memory processing stages in the P&P MST, but affected the speed of memory scanning. An Age×Gender interaction was observed, which suggested that females who were aged below 55 scanned working memory faster than males, and vice versa for people aged above 55.

Conclusions

The established P&P MST norms provide a useful tool in applied settings when a person's memory scanning and non-memory processes in working memory are to be evaluated.

Type
Original Article
Information
Psychological Medicine , Volume 37 , Issue 9 , September 2007 , pp. 1335 - 1344
Copyright
Copyright © Cambridge University Press 2007

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

Archibald, C. J. & Fisk, J. D. (2000). Information processing efficiency in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology 22, 686–701.CrossRefGoogle ScholarPubMed
Belsley, D. A., Kuh, E. & Welsch, R. E. (1980). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. Wiley: New York.CrossRefGoogle Scholar
Brand, N. & Jolles, J. (1987). Information processing in depression and anxiety. Psychological Medicine 17, 145–153.CrossRefGoogle ScholarPubMed
Capitani, E. (1997). Normative data and neuropsychological assessment. Common problems in clinical practice and research. Neuropsychological Rehabilitation 7, 295–309.CrossRefGoogle Scholar
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20, 37–46.CrossRefGoogle Scholar
Cook, R. D. & Weisberg, S. (1982). Residuals and Influence in Regression. Chapman and Hall: London.Google Scholar
De Bie, S. E. (1987). Standaardvragen 1987: Voorstellen voor uniformering van vraagstellingen naar achtergrondkenmerken en interviews [Standard questions 1987: Proposal for uniformization of questions regarding background variables and interviews]. Leiden University Press: Leiden, The Netherlands.Google Scholar
Ferraro, F. T. & Balota, D. A. (1999). Memory scanning performance in healthy young adults, healthy older adults, and individuals with dementia of the Alzheimer type. Aging, Neuropsychology, and Cognition 6, 260–272.CrossRefGoogle Scholar
Folstein, M. F., Folstein, S. E. & McHugh, P. R. (1975). Mini-Mental State: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 12, 189–198.CrossRefGoogle Scholar
Hayslip, B. & Panek, P. E. (1989). Adult Development and Aging. Harper & Row: New York.Google Scholar
Jolles, J., Houx, P. J., Van Boxtel, M. P. J. & Ponds, R. W. H. M. (1995). Maastricht Aging Study: Determinants of Cognitive Aging. Neuropsych Publishers: Maastricht, The Netherlands.Google Scholar
MacCallum, R. C., Zhang, S., Preacher, K. J. & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods 7, 19–40.CrossRefGoogle ScholarPubMed
Marquardt, D. W. (1980). You should standardize the predictor variables in your regression models. Journal of the American Statistical Association 75, 87–91.Google Scholar
Meinz, E. J. & Salthouse, T. A. (1998). Is age kinder to females than to males? Psychonomic Bulletin & Review 5, 56–70.CrossRefGoogle Scholar
Mitrushina, M. N., Boon, K. B. & D'Elia, L. F. (1999). Handbook of Normative Data for Neuropsychological Assessment. Oxford University Press: New York.Google Scholar
Møller, J. T., Cluitmans, P., Rasmussen, L. S., Houx, P. J., Rasmussen, H., Canet, J., Rabbitt, P., Jolles, J., Larsen, K., Hanning, C. D., Langeron, O., Johnson, T., Lauven, P. M., Kristensen, P. A., Biedler, A., van Beem, H., Fraidakis, O., Silverstein, J. H., Beneken, J. E. W. & Gravenstein, J. S. (1998). Long-term postoperative cognitive dysfunction in the elderly: ISPOCD1 study. The Lancet 351, 857–861.CrossRefGoogle ScholarPubMed
Naus, M. J., Cermak, L. S. & DeLuca, D. (1977). Retrieval processes in alcoholic Korsakoff patients. Neuropsychologia 5, 737–742.CrossRefGoogle Scholar
Poewe, W., Berger, W., Benke, T. & Schelosky, L. (1991). High-speed memory scanning in Parkinson's disease: adverse effects of levodopa. Annals of Neurology 29, 670–673.CrossRefGoogle ScholarPubMed
Stern, Y., Zarahn, E., Hilton, H. J., Flynn, J., DeLaPaz, R. & Rakitin, B. (2003). Exploring the neural basis of cognitive reserve. Journal of Clinical and Experimental Neuropsychology 25, 691–701.CrossRefGoogle ScholarPubMed
Sternberg, S. (1966). High-speed memory scanning in human memory. Science 153, 652–654.CrossRefGoogle ScholarPubMed
Sternberg, S. (1975). Memory scanning: new findings and current controversies. Quarterly Journal of Experimental Psychology 27, 1–32.CrossRefGoogle Scholar
Storandt, M., Botwinick, J., Danziger, W. L., Berg, L. & Hughes, C. P. (1984). Psychometric differentiation of mild senile dementia of the Alzheimer type. Archives of Neurology 41, 497–499.CrossRefGoogle ScholarPubMed
UNESCO (1976). International Standard Classification of Education (ISCED). United Nations Educational, Scientific and Cultural Organisation (UNESCO): Paris.Google Scholar
Van Breukelen, G. J. P. & Vlaeyen, J. W. S. (2005). Norming clinical questionnaires with multiple regression: the Pain Cognition List. Psychological Assessment 17, 336–344.CrossRefGoogle ScholarPubMed
Van der Elst, W., Van Boxtel, M. P. J., Van Breukelen, G. P. J. & Jolles, J. (2006). The Letter Digit Substitution Test: normative data for 1858 healthy participants aged 24–81 from the Maastricht Aging Study (MAAS): influence of age, education, and sex. Journal of Clinical and Experimental Neuropsychology 28, 998–1009.CrossRefGoogle Scholar
Watkins, M. W. & Pacheco, M. E. (2000). Interobserver agreement in behavioural research: importance and calculation. Journal of Behavioral Education 10, 205–212.CrossRefGoogle Scholar
Wechsler, D. (1981). Manual for the Wechsler Adult Intelligence Scale – Revised. Psychological Corporation: New York.Google Scholar
Wickens, C. D., Braune, R. & Stokes, A. (1987). Age differences in the speed and capacity of information processing: 1. A dual-task approach. Psychology & Aging 2, 70–80.CrossRefGoogle ScholarPubMed