The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Modeling of Longitudinal Academic Achievement Scores After Pediatric Traumatic Brain Injury
Abstract
In a prospective longitudinal study, academic achievement scores were obtained from youth 5 to 15 years of age who sustained mild-moderate (n = 34) or severe (n = 43) traumatic brain injuries (TBI). Achievement scores were collected from baseline to 5 years following TBI and were subjected to individual growth curve analysis. The models fitted age at injury, years since injury, duration of impaired consciousness, and interaction effects to Reading Decoding, Reading Comprehension, Spelling, and Arithmetic standard scores. Although scores improved significantly over the follow-up relative to normative data from the standardization sample of the tests, children with severe TBI showed persistent deficits on all achievement scores in comparison to children with mild-moderate TBI. Interactions of the slope and age parameters for the Arithmetic and Reading Decoding scores indicated greater increases over time in achievement scores of the children injured at an older age, but deceleration in growth curves for the younger children with both mild-moderate and severe TBI. These results are compatible with the hypothesis that early brain injuries disrupt the acquisition of some academic skills. Hierarchical regression models revealed that indexes of academic achievement obtained 2 years following TBI had weak relations with the duration of impaired consciousness and socioeconomic status. In contrast, concurrent cognitive variables such as phonological processing and verbal memory accounted for more variability in academic scores. Given the significant and persistent decrement in basic academic skills in youth with severe TBI, it is clear that head-injured youth require intensive, long-term remediation and intervention not only of the academic skills themselves, but also of those cognitive abilities that support the development and maintenance of reading and math.
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Citations
Cites
ASSESSMENT OF COMA AND IMPAIRED CONSCIOUSNESS
Teasdale, G., & Jennett, B. (1974) · The Lancet · doi:10.1016/s0140-6736(74)91639-0 · Cited by 13,215
Rapid “automatized” naming (R.A.N.): Dyslexia differentiated from other learning disabilities
Denckla, M. B., & Rudel, R. G. (1976) · Neuropsychologia · doi:10.1016/0028-3932(76)90075-0 · Cited by 1,457
The Development of Working Memory in Normally Achieving and Subtypes of Learning Disabled Children
Siegel, L. S., & Ryan, E. B. (1989) · Child Development · doi:10.2307/1131037 · Cited by 842
Cited by
Neurocognitive outcomes and recovery after pediatric TBI: meta-analytic review of the literature
Babikian, T., & Asarnow, R. (2009) · Neuropsychology · doi:10.1037/a0015268 · Cited by 557
Conklin, H. M., Luciana, M., Hooper, C. J., & Yarger, R. S. (2007) · Developmental Neuropsychology · doi:10.1207/s15326942dn3101_6 · Cited by 330
Anderson, V., Godfrey, C., Rosenfeld, J. V., & Catroppa, C. (2012) · PEDIATRICS · doi:10.1542/peds.2011-0311 · Cited by 224
Keenan, H. T., Presson, A. P., Clark, A. E., Cox, C. S., & Ewing-Cobbs, L. (2019) · Journal of Neurotrauma · doi:10.1089/neu.2018.5687 · Cited by 56
Self-citationWatson, W., Pedowitz, A., Nowak, S., Neumayer, C., Kaplan, E., & Shah, S. (2020) · Rehabilitation Psychology · doi:10.1037/rep0000309 · Cited by 10
Metadata
- Authors
- Ewing-Cobbs, L., Barnes, M., Fletcher, J. M., Levin, H. S., Swank, P. R., & Song, J.
- Venue
- Developmental Neuropsychology
- Publisher
- Informa UK Limited
- Published
- 2004-02
- Volume
- 25
- Issue
- 1-2
- Pages
- 107-133
- ISSN
- 1532-6942 (ISSN-L)
- 8756-5641
- OpenAlex
- W2074378484
- Cited by
- 226
- References
- 3
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.