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Cited by 157Reading and Literacy DevelopmentCognitive Abilities and TestingLanguage Development and Disorders

IV. NIH toolbox cognition battery (CB): measuring language (vocabulary comprehension and reading decoding)

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Gershon, Richard C, Slotkin, Jerry, Manly, Jennifer J, Blitz, David L, Beaumont, Jennifer L, Schnipke, Deborah, Wallner-Allen, Kathleen, Golinkoff, Roberta Michnick +4 more·2013·Monographs of the Society for Research in Child Development
DOI 10.1111/mono.12034PMC PMC7659464
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Abstract

Mastery of language skills is an important predictor of daily functioning and health. Vocabulary comprehension and reading decoding are relatively quick and easy to measure and correlate highly with overall cognitive functioning, as well as with success in school and work. New measures of vocabulary comprehension and reading decoding (in both English and Spanish) were developed for the NIH Toolbox Cognition Battery (CB). In the Toolbox Picture Vocabulary Test (TPVT), participants hear a spoken word while viewing four pictures, and then must choose the picture that best represents the word. This approach tests receptive vocabulary knowledge without the need to read or write, removing the literacy load for children who are developing literacy and for adults who struggle with reading and writing. In the Toolbox Oral Reading Recognition Test (TORRT), participants see a letter or word onscreen and must pronounce or identify it. The examiner determines whether it was pronounced correctly by comparing the response to the pronunciation guide on a separate computer screen. In this chapter, we discuss the importance of language during childhood and the relation of language and brain function. We also review the development of the TPVT and TORRT, including information about the item calibration process and results from a validation study. Finally, the strengths and weaknesses of the measures are discussed.

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  • The NIHTB-CB has demonstrated test-retest reliability (ICC 0.76 to 0.97) and convergent and discriminant validity.

    “The developers evaluated and described the psychometric soundness of each test, including test–retest reliability (intra-class correlation coefficients ranging from 0.76 to 0.97) as well as convergent and discriminant validity (Bauer et al., 2013; Carlozzi et al., 2013; Gershon et al., 2013; Tulsky et al., 2013; Zelazo et al., 2013).”

    From Cognitive weaknesses or impairments on the NIH toolbox cognition battery in children and adolescents: base rates in a normative sample and proposed methods for classification (2025) · cites this paper as Gershon et al., 2013

    The Results (TPVT and TORRT, Test–Retest Reliability; page unavailable) report ICCs of 0.81 and 0.97 for the two NIH Toolbox language tests. The Criterion Validity results report evidence of convergent and discriminant validity for both. This paper does not establish the cited range’s lower bound of 0.76 or evaluate every test in the battery. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 33

  1. Burton CL, Strauss E, Hultsch DF, & Hunter MA (2006). Cognitive functioning and everyday problem solving in older adults. Clinical Neuropsychologist, 20(3), 432– 452. 16895857
  2. Caplan D, & Hildebrandt N (1988). Disorders of syntactic comprehension. Cambridge, MA: MIT Press.
  3. Cattell RB (1987). Intelligence: Its structure, growth and action. Amsterdam: Elsevier.
  4. Dunn LM, & Dunn DM (2007). Peabody picture vocabulary test (4th ed.). San Antonio, TX: Pearson.
  5. Fenson L, Dale PS, Reznick JS, Bates E, Thal DJ, & Pethick SJ (1994). Variability in early communicative development. Monographs of the Society for Research in Child Development, 59(5), 1– 173. 7845413
  6. Fisher C (1996). Structural limits on verb mapping: The role of analogy in children's interpretations of sentences. Cognitive Psychology, 31(1), 41– 81. 8812021
  7. Friederici AD, Rüschemeyer SA, Hahne A, & Fiebach CJ (2003). The role of left inferior frontal and superior temporal cortex in sentence comprehension: Localizing syntactic and semantic processes. Cerebral Cortex, 13(2), 170– 177. 12507948
  8. Gleason JB, & Ratner NB (2009). The development of language (7th ed.). Boston: Pearson/Allyn and Bacon.
  9. Grober E, & Sliwinski M (1991). Development and validation of a model for estimating premorbid verbal intelligence in the elderly. Journal of Clinical and Experimental Neuropsychology, 13(6), 933– 949. 1779032
  10. Hirsch C, & Wexler K (2007). The late acquisition of raising: What children seem to think about seem In Davies WD & Dubinsky S (Eds.), New horizons in the analysis of control and raising (pp. 35– 70). New York: Springer.
  11. Hirsh-Pasek K, & Golinkoff RM (1996). The origins of grammar: Evidence from early language comprehension. Cambridge, MA: MIT Press.
  12. Hirsh-Pasek K, Kochanoff AT, Newcombe N, & De Villiers J (2005). Using scientific knowledge to inform preschool assessment: Making the case for empirical validity. Society for Research in Child Development Social Policy Report, 19(1), 3– 19.
  13. Hurtado N, Marchman VA, & Fernald A (2008). Does input influence uptake? Links between maternal talk, processing speed and vocabulary size in spanish-learning children. Developmental Science, 11(6), 31. PMC2898277 19046145
  14. Kastner JW, May W, & Hildman L (2001). Relationship between language skills and academic achievement in first grade. Perceptual and Motor Skills, 92(2), 381– 390. 11361297
  15. Kucera H, & Francis WN (1967). Computational analysis of present-day American English. Providence: Brown University Press.
  16. Kuhl P, & Rivera-Gaxiola M (2008). Neural substrates of language acquisition Annual Review of Neuroscience, 31, 511– 534. 18558865
  17. Kuhl PK (2004). Early language acquisition: Cracking the speech code. Nature Reviews Neuroscience, 5(11), 831– 843. 15496861
  18. Manly JJ, Byrd DA, Touradji P, & Stern Y (2004). Acculturation, reading level, and neuropsychological test performance among african american elders. Applied Neuropsychology, 11(1), 37– 46. 15471745
  19. Marcus GF, Vijayan S, Bandi Rao S, & Vishton PM (1999). Rule learning by seven-month-old infants. Science, 283(5398), 77– 80. 9872745
  20. Meisinger EB, Bloom JS, & Hynd GW (2010). Reading fluency: Implications for the assessment of children with reading disabilities. Annals of Dyslexia, 60(1), 1– 17. 20033795
  21. National Research Council Committee on the Prevention of Reading Difficulties in Young Children, Snow CE, Burns MS, Griffin P, & National Research Council Commission on Behavioral Social Sciences Education (2002). Preventing reading difficulties in young children: Intellectual property in the information age (8th ed.). Washington, DC: National Academies Press.
  22. NICHD Early Child Care Research Network. (2005). Pathways to reading: The role of oral language in the transition to reading. Developmental Psychology, 41(2), 428– 442. 15769197
  23. Price CJ (1998). The functional anatomy of word comprehension and production. Trends in Cognitive Sciences, 2(8), 281– 287. 21227210
  24. Price CJ (2000). The anatomy of language: Contributions from functional neuroimaging. Journal of Anatomy, 197(3), 335– 359. 11117622 PMC1468137
  25. Rapcsak SZ, Henry ML, Teague SL, Carnahan SD, & Beeson PM (2007). Do dual-route models accurately predict reading and spelling performance in individuals with acquired alexia and agraphia? Neuropsychologia, 45(11), 2519– 2524. 17482218 PMC1988783
  26. Rey A (1958). L'Examen clinique en psychologie. Paris: Press Universitaire de France.
  27. Saffran JR, Aslin RN, & Newport EL (1996). Statistical learning by 8-month-old infants. Science, 274(5294), 1926– 1928. 8943209
  28. Schmidt FL, & Hunter J (2004). General mental ability in the world of work: Occupational attainment and job performance. Journal of Personality and Social Psychology, 86(1), 162– 173. doi: 10.1037/0022-3514.86.1.162 14717634 · DOI · Paper page
  29. Seymour HN, Roeper T, & de Villiers JG (2004). Conclusions, future directions, and implications for remediation. Seminars in Speech and Language, 25(1), 113– 115. 15088237
  30. Sternberg RJ (2004). Intelligence in humans In Charles S (Ed.), Encyclopedia of Applied Psychology (pp. 321– 328). New York: Elsevier.
  31. Tsao F-M, Liu H-M, & Kuhl PK (2004). Speech perception in infancy predicts language development in the second year of life: A longitudinal study. Child Development, 75(4), 1067– 1084. 15260865
  32. Wolf MS, Gazmararian JA, & Baker DW (2005). Health literacy and functional health status among older adults. Archives of Internal Medicine, 165(17), 1946– 1952. 16186463
  33. Ziegler JC, Castel C, Pech-Georgel C, George F, Alario FX, & Perry C (2008). Developmental dyslexia and the dual route model of reading: Simulating individual differences and subtypes. Cognition, 107(1), 151– 178. 17959161

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Authors
Gershon, R. C., Slotkin, J., Manly, J. J., Blitz, D. L., Beaumont, J. L., Schnipke, D., Wallner-Allen, K., Golinkoff, R. M., Gleason, J. B., Hirsh-Pasek, K., Adams, M. J., & Weintraub, S.
Affiliations
  • Northwestern University (US)
  • Columbia University (US)
  • University of Delaware (US)
  • Boston University (US)
  • Brown University (US)
ORCID
Venue
Monographs of the Society for Research in Child Development
Publisher
Oxford University Press (OUP)
Published
2013-08
Volume
78
Issue
4
Pages
49-69
ISSN
  • 0037-976X (ISSN-L)
  • 1540-5834
DOI
10.1111/mono.12034
PMC
PMC7659464
OpenAlex
W1893187780
Cited by
157
References
3
Citations by year
2026: 16 · 2025: 21 · 2024: 21 · 2023: 13 · 2022: 20 · 2021: 19 · 2020: 11 · 2019: 9 · 2018: 6 · 2017: 12 · 2016: 2 · 2015: 2 · 2014: 3 · 2013: 1 · 2012: 1
FWCI
5.51
Type
journal article
Language
en
Open access
Licence
Locations
  • Monographs of the Society for Research in Child Development (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (n01ag60007-17-0-2)
  • National Institute on Aging (N01 AG060007)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
Keywords
NIH Toolbox Cognition Battery, vocabulary comprehension, reading decoding, receptive vocabulary, language development, item calibration, test validation, cognitive assessment
MeSH terms
Adolescent, Adult, Aged, Child, Child, Preschool, Female, Humans, Language, Male, Middle Aged, National Institutes of Health (U.S.), Neuropsychological Tests, Reading, United States, Reproducibility of Results, Comprehension, Young Adult

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