Hostname: page-component-745bb68f8f-cphqk Total loading time: 0 Render date: 2025-01-09T00:41:23.906Z Has data issue: false hasContentIssue false
  • English
  • Français

Performance on the African neuropsychology battery using the learning ratio in a sample of healthy Congolese

Published online by Cambridge University Press:  10 May 2023

Jean Ikanga ,
Zinat Taiwo Open the ORCID record for Zinat Taiwo [Opens in a new window] ,
Ketrin Lengu ,
Emmanuel Epenge ,
Herve Esambo ,
Guy Gikelekele ,
Christian Esselakoy Open the ORCID record for Christian Esselakoy [Opens in a new window] ,
Immaculée Kavugho ,
Samuel M. Mampunza  and
Dustin Hammers
...Show all authors
Jean Ikanga*
Affiliation:
Emory University, School of Medicine, Department of Rehabilitation Medicine, Atlanta, GA, USA University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Zinat Taiwo
Affiliation:
Georgia State University, Department of Psychology, Atlanta, GA, USA
Ketrin Lengu
Affiliation:
Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
Emmanuel Epenge
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Herve Esambo
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Guy Gikelekele
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Christian Esselakoy
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Immaculée Kavugho
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Samuel M. Mampunza
Affiliation:
University of Kinshasa, Department of Psychiatry, Kinshasa, the Democratic Republic of the Congo
Dustin Hammers
Affiliation:
Indiana University, Department of Neurology, Indianapolis, USA
Anthony Stringer
Affiliation:
Emory University, School of Medicine, Department of Rehabilitation Medicine, Atlanta, GA, USA
Robert J. Spencer
Affiliation:
Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
*
Corresponding author: Jean Ikanga, email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

Using the African Neuropsychology Battery (ANB), we seek to develop normative data by examining the demographic effects for two learning process scores: initial learning (Trial One) and learning ratio (LR, the percentage of items learned relative of to-be-learned material following Trial 1).

Methods:

Healthy participants from the Democratic Republic of Congo completed the four memory tests of the ANB: the African Story Memory Test (ASMT), African List Memory Test (ALMT), African Visuospatial Memory Test (AVMT), and African Contextual Visuospatial Memory Test (ACVMT). We developed indices of learning for each subtest, as well as aggregate learning indices for Trial 1 and LR, and composite indices examining verbal, visual, contextual, and noncontextual learning, and grand indices comprising all four subtests.

Results:

Trial 1 and LR scores each demonstrated acceptable intercorrelations across memory tests. We present normative data for Trial 1 and LR by age and education.

Conclusion:

These data provide normative standards for evaluating learning in Sub-Saharan Africa.

Keywords

assessmentlearningmemoryneurocognitive testssub-Saharan AfricaANBcultural neuropsychology
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 29 , Issue 5 , June 2023 , pp. 503 - 511
Copyright
Copyright © INS. Published by Cambridge University Press, 2023

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

Aretouli, E., & Brandt, J. (2010). Episodic memory in dementia: Characteristics of new learning that differentiate Alzheimer’s, Huntington’s, and Parkinson’s diseases. Archives of Clinical Neuropsychology, 25, 396–409.CrossRefGoogle ScholarPubMed
Benedict, R. H., Schretlen, D., Groninger, L., & Brandt, J. (1998). Hopkins verbal learning test-revised: Normative data and analysis of inter-form and test-retest reliability. The Clinical Neuropsychologist, 12, 43–55.CrossRefGoogle Scholar
Benedict, R. H. B. (1997). Brief visuospatial memory test-revised: Professional manual. Psychological Assessment Resources, Inc.Google Scholar
Bondi, M. W., Monsch, A. U., Galasko, D., Butters, N., Salmon, D. P., & Delis, D. C. (1994). Preclinical cognitive markers of dementia of the Alzheimer type. Neuropsychology, 8, 374.CrossRefGoogle Scholar
Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (2000). California verbal learning test: Adult version. The Psychological Corporation.Google Scholar
Delis, D. C., Kramer, J. H., & Ober, B. A. (2017). California verbal learning test (CVLT-3). Pearson.Google Scholar
Gifford, K. A., Phillips, J. S., Samuels, L. R., Lane, E. M., Bell, S. P., Liu, D., Hohman, T. J., Romano, R. R., Fritzsche, L. R., Lu, Z., Jefferson, A. L., & Alzheimer’s Disease Neuroimaging Initiative. (2015). Associations between verbal learning slope and neuroimaging markers across the cognitive aging spectrum. Journal of the International Neuropsychological Society, 21, 455–467.CrossRefGoogle ScholarPubMed
Hammers, D. B., Duff, K., & Spencer, R. J. (2021a). Demographically corrected normative data for the HVLT-R, BVMT-R, and aggregated learning ratio values in a sample of older adults. Journal of Clinical and Experimental Neuropsychology, 43, 290–300.CrossRefGoogle Scholar
Hammers, D. B., Suhrie, K., Dixon, A., Gradwohl, B. D., Archibald, Z. G., King, J. B., Spencer, R. J., Duff, K., & Hoffman, J. M. (2021b). Relationship between a novel learning slope metric and Alzheimer’s disease biomarkers. Neuropsychology, Development, and Cognition B: Aging, Neuropsychology, and Cognition, 1–21. https://doi.org/10.1080/13825585.2021.1919984 Google ScholarPubMed
Hammers, D. B., Suhrie, K., Dixon, A., Gradwohl, B. D., Duff, K., & Spencer, R. J. (2021c). Validation of HVLT-R, BVMT-R, and RBANS learning slope scores along the alzheimer’s continuum. Archives of Clinical Neuropsychology, 1–13.Google Scholar
Ikanga, J. N., Breiman, R., Nahab, F., Mampunza, S. S., & Stringer, A. Y. (2019). Prediction of the performance of a new battery for the assessment of cognitive function in Sub-Saharan Africa. International Neuropsychological Society, New York, N.Y.Google Scholar
Ikanga, J., Basterfield, C., Taiwo, Z., Bragg, P., Bartlett, A., Howard, C., Robert, S., & Stringer, A. Y. (2022). The reliability of the African neuropsychology battery in persons of African descent. Archives of Clinical Neuropsychology, 37, 839–848. https://doi.org/10.1093/arclin/acac003 CrossRefGoogle ScholarPubMed
Kaplan, E. (1988). The process approach to neuropsychological assessment. Aphasiology, 2, 309–311.CrossRefGoogle Scholar
Lu, H., Ni, X., Fung, A. W. T., & Lam, L. C. W. (2020). Mapping the proxies of memory and learning function in senior adults with high performing, normal aging and neurocognitive disorders. Journal of Alzheimer’s Disease, 64, 815–826.CrossRefGoogle Scholar
Mast, B. T., & Allaire, J. C. (2006). Verbal learning and everyday functioning in dementia: An application of latent variable growth curve modeling. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 61, P167–P173.CrossRefGoogle ScholarPubMed
Rabin, L. A., Paolillo, E., & Barr, W. B. (2016). Stability in test-usage practices of clinical neuropsychologists in the United States and Canada over a 10-year period: A follow-up survey of INS and NAN members. Archives of Clinical Neuropsychology, 31, 206–230.CrossRefGoogle Scholar
Shing, Y. L., & Brod, G. (2016). Effects of prior knowledge on memory: Implications for education. Mind, Brain and Education, 10, 153–161.CrossRefGoogle Scholar
Small, S. A., Ysai, W. Y., DeLaPaz, R., Mayeux, R., & Stern, Y. (2002). Imaging hippocampal function across the human life span: Is memory decline normal or not. Annals of Neurology, 51, 290–295.CrossRefGoogle ScholarPubMed
Spencer, R. J., Gradwohl, B. D., Williams, T. F., Kordovski, V. M., & Hammers, D. B. (2020). Developing learning slope scores for the repeatable battery for the assessment of neuropsychological status. Applied Neuropsychology: Adult, 1–7. https://doi.org/10.1080/23279095.2020.1791870 Google ScholarPubMed
Thomas, K. R., Eppig, J., Edmonds, E. C., Jacobs, D. M., Libon, D. J., Au, R., Salmon, D. P., Bondi, M. W., & Alzheimer’s Disease Neuroimaging Initiative. (2018). Word-list intrusion errors predict progression to mild cognitive impairment. Neuropsychology, 32, 235–245.CrossRefGoogle ScholarPubMed
Wechsler, D. (1998). Wechsler memory scale. The Psychological Corporation.Google Scholar
Weintraub, S., Wicklund, A. H., & Salmon, D. P. (2012). The neuropsychological profile of Alzheimer disease. Perspectives in Medicine, 2012, 1–18.Google Scholar
Welsh, K., Butters, N., Hughes, J., Mohs, R., & Heyman, A. (1991). Detection of abnormal memory decline in mild cases of Alzheimer’s disease using CERAD neuropsychological measures. Archives of Neurology, 48, 278–281.CrossRefGoogle ScholarPubMed