Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-05T06:59:05.618Z Has data issue: false hasContentIssue false

Exploring the Factor Structure of the NIH Toolbox Cognition Battery in a Large Sample of 8-Year-Old Children in Aotearoa New Zealand

Published online by Cambridge University Press:  11 January 2021

Denise Neumann*
Affiliation:
School of Psychology, the University of Auckland, Auckland, New Zealand Centre for Longitudinal Research – He Ara ki Mua, the University of Auckland, Auckland, New Zealand
Elizabeth R. Peterson
Affiliation:
School of Psychology, the University of Auckland, Auckland, New Zealand Centre for Longitudinal Research – He Ara ki Mua, the University of Auckland, Auckland, New Zealand
Lisa Underwood
Affiliation:
Centre for Longitudinal Research – He Ara ki Mua, the University of Auckland, Auckland, New Zealand School of Population Health, the University of Auckland, Auckland, New Zealand
Susan M.B. Morton
Affiliation:
Centre for Longitudinal Research – He Ara ki Mua, the University of Auckland, Auckland, New Zealand School of Population Health, the University of Auckland, Auckland, New Zealand
Karen E. Waldie
Affiliation:
School of Psychology, the University of Auckland, Auckland, New Zealand Centre for Longitudinal Research – He Ara ki Mua, the University of Auckland, Auckland, New Zealand
*
*Correspondence and reprint requests to: Denise Neumann, PhD, School of Psychology, Faculty of Science, University of Auckland, Private Bag 92019, Auckland1142, New Zealand. E-mail: [email protected]

Abstract

Objective:

The objective of this study was to derive a factor structure of the measures of the National Institutes of Health (NIH) Toolbox Cognition Battery (CB) that is representative of cognitive abilities in a large ethnically diverse cohort of 8-year-old children in Aotearoa New Zealand.

Methods:

Our sample comprised of 4298 8-year-old children from the Growing Up in New Zealand study. We conducted exploratory and confirmatory factor analysis for the NIH Toolbox CB measures to discover the best-fitting factor structure in our sample. Measurement invariance of the identified model was tested across child’s gender, socio-economic status (SES), and ethnicity.

Results:

A three-dimensional factor structure was identified, with one factor of Crystallised Cognition (Reading and Vocabulary), and two distinguished factors of fluid cognition: Fluid Cognition I (Attention/Inhibitory Control, Processing Speed, and Cognitive Flexibility) and Fluid Cognition II (Working Memory, Episodic Memory). The results demonstrate excellent model fit, but reliability of the factors was low. Measurement invariance was confirmed for child’s gender. We found configural, but neither metric nor scalar, invariance across SES and the four major ethnic groups: European, Māori, Pacific Peoples, and Asian.

Conclusion:

Our findings show that, at the age of 8 years, fluid abilities are more strongly associated with one another than with crystallised abilities and that fluid abilities need to be further differentiated. This dimensional structure allows for comparisons across child’s gender, but evaluations across SES and ethnicity within the Aotearoa New Zealand context must be conducted with caution. We recommend using raw scores of the individual NIH Toolbox CB measures in future research.

Type
Regular Research
Copyright
Copyright © INS. Published by Cambridge University Press, 2021

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

Akshoomoff, N., Beaumont, J.L., Bauer, P.J., Dikmen, S.S., Gershon, R.C., Mungas, D., … Heaton, R.K. (2013). VIII. NIH Toolbox Cognition Battery (CB): Composite scores of crystallized, fluid, and overall cognition. Monographs of the Society for Research in Child Development, 78(4), 119132. doi: 10.1111/mono.12038 CrossRefGoogle ScholarPubMed
Atkinson, J., Salmond, C., & Crampton, P. (2014). NZDep2013 Index of Deprivation. Wellington: Department of Public Health, University of Otago.Google Scholar
Bauer, P.J., Dikmen, S.S., Heaton, R.K., Mungas, D., Slotkin, J., & Beaumont, J.L. (2013). III. NIH Toolbox Cognition Battery (CB): Measuring episodic memory. Monographs of the Society for Research in Child Development, 78(4), 3448.CrossRefGoogle ScholarPubMed
Bowden, S.C., Carstairs, J.R., & Shores, E.A. (1999). Confirmatory factor analysis of combined Wechsler Adult Intelligence Scale—Revised and Wechsler Memory Scale—Revised scores in a healthy community sample. Psychological Assessment, 11(3), 339.CrossRefGoogle Scholar
Carlozzi, N.E., Tulsky, D.S., Kail, R.V., & Beaumont, J.L. (2013). VI. NIH Toolbox Cognition Battery (CB): Measuring processing speed. Monographs of the Society for Research in Child Development, 78(4), 88102.CrossRefGoogle ScholarPubMed
Carroll, J.B. (1993). Human Cognitive Abilities: A Survey of Factor-Analytic Studies. Cambridge University Press.CrossRefGoogle Scholar
Casaletto, K.B., Umlauf, A., Beaumont, J., Gershon, R., Slotkin, J., Akshoomoff, N., & Heaton, R.K. (2015). Demographically corrected normative standards for the English version of the NIH toolbox cognition battery. Journal of the International Neuropsychological Society, 21(5), 378391.CrossRefGoogle ScholarPubMed
Cattell, R.B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245276. doi: 10.1207/s15327906mbr0102_10 CrossRefGoogle ScholarPubMed
Cattell, R.B. (1971). Abilities: Their Structure, Growth, and Action. Boston: Houghton Mifflin.Google Scholar
Chen, F.F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464504.CrossRefGoogle Scholar
Cheung, G.W., & Rensvold, R.B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233255.CrossRefGoogle Scholar
Commission, J.R.C.-E. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. OECD Publishing.Google Scholar
Gershon, R.C., Cella, D., Fox, N.A., Havlik, R.J., Hendrie, H.C., & Wagster, M.V. (2010). Assessment of neurological and behavioural function: The NIH Toolbox. The Lancet Neurology 9(2), 138139.CrossRefGoogle ScholarPubMed
Gershon, R.C., Cook, K.F., Mungas, D., Manly, J.J., Slotkin, J., Beaumont, J.L., & Weintraub, S. (2014). Language measures of the NIH toolbox cognition battery. Journal of the International Neuropsychological Society, 20(6), 642651.CrossRefGoogle ScholarPubMed
Haitana, T., Pitama, S., & Rucklidge, J.J. (2010). Cultural biases in the peabody picture vocabulary test-III: Testing tamariki in a New Zealand sample. New Zealand Journal of Psychology, 39(3), 2434.Google Scholar
Hayton, J.C., Allen, D.G., & Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7(2), 191205.CrossRefGoogle Scholar
Heaton, R.K., Akshoomoff, N., Tulsky, D., Mungas, D., Weintraub, S., Dikmen, S., … Slotkin, J. (2014). Reliability and validity of composite scores from the NIH Toolbox Cognition Battery in adults. Journal of the International Neuropsychological Society, 20(6), 588598.CrossRefGoogle ScholarPubMed
Horn, J.L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179185.CrossRefGoogle ScholarPubMed
Horn, J.L. (1970). Organization of data on life-span development of human abilities. In Life-Span Developmental Psychology (pp. 423466). Elsevier.CrossRefGoogle Scholar
Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal , 6(1), 155.CrossRefGoogle Scholar
Lee, S.T. (2018). Testing for measurement invariance: Does your measure mean the same thing for different participants? APS Observer, 31(8).Google Scholar
Li, S.-C., Lindenberger, U., Hommel, B., Aschersleben, G., Prinz, W., & Baltes, P.B. (2004). Transformations in the couplings among intellectual abilities and constituent cognitive processes across the life span. Psychological Science, 15(3), 155163.CrossRefGoogle ScholarPubMed
McDonald, R.P. (1999). Test Theory: A Unified Treatment. Mahwah, NJ: L. Erlbaum Associates.Google Scholar
Morton, S.M., Grant, C.C., Carr, P.E.A., Robinson, E.M., Kinloch, J.M., Fleming, C.J., … Liang, R. (2014). How do you recruit and retain a prebirth cohort? Lessons Learnt from Growing Up in New Zealand. Evaluation & the Health Professions, 37(4), 411433.CrossRefGoogle Scholar
Morton, S.M., Ramke, J., Kinloch, J., Grant, C.C., Carr, P.A., Leeson, H., … Robinson, E. (2015). Growing Up in New Zealand cohort alignment with all New Zealand births. Australian and New Zealand Journal of Public Health, 39(1), 8287.CrossRefGoogle ScholarPubMed
Mungas, D., Heaton, R., Tulsky, D., Zelazo, P.D., Slotkin, J., Blitz, D., … Gershon, R. (2014). Factor structure, convergent validity, and discriminant validity of the NIH Toolbox Cognitive Health Battery (NIHTB-CHB) in adults. Journal of the International Neuropsychological Society, 20(6), 579587.CrossRefGoogle Scholar
Mungas, D., Reed, B.R., Tomaszewski Farias, S., & DeCarli, C. (2005). Criterion-referenced validity of a neuropsychological test battery: Equivalent performance in elderly Hispanics and non-Hispanic Whites. Journal of the International Neuropsychological Society, 11(5), 620630. doi: 10.1017/S1355617705050745 CrossRefGoogle ScholarPubMed
Mungas, D., Widaman, K., Zelazo, P.D., Tulsky, D., Heaton, R.K., Slotkin, J., … Gershon, R.C. (2013). VII. NIH Toolbox Cognition Battery (CB): Factor structure for 3 to 15 year olds. Monographs of the Society for Research in Child Development, 78(4), 103118.CrossRefGoogle ScholarPubMed
Oakhill, J.V., Cain, K., & Bryant, P.E. (2003). The dissociation of word reading and text comprehension: Evidence from component skills. Language and Cognitive Processes, 18(4), 443468.CrossRefGoogle Scholar
Ogden, J.A., & McFarlane-Nathan, G.J.N. (1997). Cultural bias in the neuropsychological assessment of young Maori men. New Zealand Journal of Psychology, 26, 212.Google Scholar
Peng, P., Barnes, M., Wang, C., Wang, W., Li, S., Swanson, H.L., … Tao, S. (2018). A meta-analysis on the relation between reading and working memory. Psychological Bulletin, 144(1), 48.CrossRefGoogle ScholarPubMed
Rueda, M.R., Fan, J., McCandliss, B.D., Halparin, J.D., Gruber, D.B., Lercari, L.P., & Posner, M.I. (2004). Development of attentional networks in childhood. Neuropsychologia, 42(8), 10291040. doi: 10.1016/j.neuropsychologia.2003.12.012 CrossRefGoogle ScholarPubMed
Salthouse, T.A. & Meinz, E.J. (1995). Aging, inhibition, working memory, and speed. Journals of Gerontology, 50B(6), 297306.CrossRefGoogle Scholar
Schweizer, K. (2011).On the changing role of Cronbach’s α in the evaluation of the quality of a measure. European Journal of Psychological Assessment, 27(3), 143144.Google Scholar
Smith, G.E., Ivnik, R.J., Malec, J.F., Kokmen, E., Tangalos, E.G., & Kurland, L.T.J. (1992). Mayo’s Older Americans Normative Studies (MOANS): Factor structure of a core battery. Psychological Assessment, 4(3), 382.CrossRefGoogle Scholar
Spearman, C. (1961). “General Intelligence” Objectively Determined and Measured. In J. J. Jenkins & D. G. Paterson (Eds.), Studies in individual differences: The search for intelligence (pp. 59–73). Appleton-Century-Crofts. doi: 10.1037/11491-006 CrossRefGoogle Scholar
Statistics New Zealand. (2004). Report of the Review of the Measurement of Ethnicity. Wellington, New Zealand: Statistics New Zealand.Google Scholar
Statistics New Zealand. (2005). Statistical Standard for Ethnicity. Wellington, New Zealand: Statistics New Zealand.Google Scholar
Stone, L.L., Otten, R., Ringlever, L., Hiemstra, M., Engels, R.C., Vermulst, A.A., & Janssens, J.M. (2013). The parent version of the strengths and difficulties questionnaire. European Journal of Psychological Assessment, 29, 4450.CrossRefGoogle Scholar
Tulsky, D.S., Carlozzi, N.E., Chevalier, N., Espy, K.A., Beaumont, J.L., & Mungas, D. (2013). V. NIH toolbox cognition battery (CB): Measuring working memory. Monographs of the Society for Research in Child Development, 78(4), 7087.CrossRefGoogle ScholarPubMed
Van der Linden, M., Meulemans, T., Marczewski, P., & Collette, F. (2000). The relationships between episodic memory, working memory, and executive functions: The contribution of the prefrontal cortex. Psychologica Belgica, 40(4), 275297.CrossRefGoogle Scholar
Weintraub, S., Bauer, P.J., Zelazo, P.D., Wallner-Allen, K., Dikmen, S.S., Heaton, R.K., … Carlozzi, N.E. (2013). I. NIH Toolbox Cognition Battery (CB): introduction and pediatric data. Monographs of the Society for Research in Child Development, 78(4), 115.Google ScholarPubMed
Weintraub, S., Dikmen, S.S., Heaton, R.K., Tulsky, D.S., Zelazo, P.D., Bauer, P.J., … Wallner-Allen, K. (2013). Cognition assessment using the NIH Toolbox. Neurology, 80(11 Supplement 3), S54S64.CrossRefGoogle ScholarPubMed
White, I.R. & Carlin, J.B. (2010). Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Statistics in medicine, 29(28), 29202931.CrossRefGoogle ScholarPubMed
Williams, D.R. & Mohammed, S.A. (2013). Racism and health I: Pathways and scientific evidence. American Behavioral Scientist, 57(8), 11521173.CrossRefGoogle Scholar
Zelazo, P.D., Anderson, J.E., Richler, J., Wallner-Allen, K., Beaumont, J.L., & Weintraub, S. (2013). II. NIH Toolbox Cognition Battery (CB): Measuring executive function and attention. Monographs of the Society for Research in Child Development, 78(4), 1633.CrossRefGoogle Scholar
Supplementary material: PDF

Neumann et al. Supplementary Materials

Neumann et al. Supplementary Materials

Download Neumann et al. Supplementary Materials(PDF)
PDF 165.5 KB