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Socioeconomic Status and Race Outperform Concussion History and Sport Participation in Predicting Collegiate Athlete Baseline Neurocognitive Scores

Published online by Cambridge University Press:  09 August 2017

Zac Houck
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Breton Asken
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
James Clugston
Affiliation:
Department of Community Health and Family Medicine, University of Florida, Gainesville, Florida
William Perlstein
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Russell Bauer
Affiliation:
Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida
Corresponding
E-mail address:

Abstract

Objectives: The purpose of this study was to assess the contribution of socioeconomic status (SES) and other multivariate predictors to baseline neurocognitive functioning in collegiate athletes. Methods: Data were obtained from the Concussion Assessment, Research and Education (CARE) Consortium. Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) baseline assessments for 403 University of Florida student-athletes (202 males; age range: 18–23) from the 2014–2015 and 2015–2016 seasons were analyzed. ImPACT composite scores were consolidated into one memory and one speed composite score. Hierarchical linear regressions were used for analyses. Results: In the overall sample, history of learning disability (β=−0.164; p=.001) and attention deficit–hyperactivity disorder (β=−0.102; p=.038) significantly predicted worse memory and speed performance, respectively. Older age predicted better speed performance (β=.176; p<.001). Black/African American race predicted worse memory (β=−0.113; p=.026) and speed performance (β=−.242; p<.001). In football players, higher maternal SES predicted better memory performance (β=0.308; p=.007); older age predicted better speed performance (β=0.346; p=.001); while Black/African American race predicted worse speed performance (β=−0.397; p<.001). Conclusions: Baseline memory and speed scores are significantly influenced by history of neurodevelopmental disorder, age, and race. In football players, specifically, maternal SES independently predicted baseline memory scores, but concussion history and years exposed to sport were not predictive. SES, race, and medical history beyond exposure to brain injury or subclinical brain trauma are important factors when interpreting variability in cognitive scores among collegiate athletes. Additionally, sport-specific differences in the proportional representation of various demographic variables (e.g., SES and race) may also be an important consideration within the broader biopsychosocial attributional model. (JINS, 2018, 24, 1–10)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

Alosco, M.L., Fedor, A.F., & Gunstad, J. (2014). Attention deficit hyperactivity disorder as a risk factor for concussions in NCAA division-I athletes. Brain Injury, 28(4), 472474.CrossRefGoogle ScholarPubMed
Andersson, H.W., Sommerfelt, K., Sonnander, K., & Ahlsten, G. (1996). Maternal child-rearing attitudes, IQ, and socioeconomic status as related to cognitive abilities of five-year-old children. Psychology Report, 79(1), 314. doi: 10.2466/pr0.1996.79.1.3 CrossRefGoogle ScholarPubMed
Asken, B.M., Sullan, M.J., Snyder, A.R., Houck, Z.M., Bryant, V.E., Hizel, L.P., & Bauer, R.M. (2016). Factors influencing clinical correlates of Chronic Traumatic Encephalopathy (CTE): A review. Neuropsychology Review, 26(4), 340363.CrossRefGoogle ScholarPubMed
Bailey, C.M., Samples, H.L., Broshek, D.K., Freeman, J.R., & Barth, J.T. (2010). The relationship between psychological distress and baseline sports-related concussion testing. Clinical Journal of Sport Medicine, 20(4), 272277. doi: 10.1097/JSM.0b013e3181e8f8d8 CrossRefGoogle ScholarPubMed
Blom, G. (1958). Statistical estimates and transformed beta-variables. New York: Wiley.Google Scholar
Bradley, R.H., Convyn, R.F., Burchinal, M., McAdoo, H.P., & Coll, C.G. (2001). The home environments of children in the United States. Part II: Relations with behavioral development through age thirteen. Child Development, 72(6), 18681886.CrossRefGoogle ScholarPubMed
Braveman, P.A., Cubbin, C., Egerter, S., Chideya, S., Marchi, K.S., Metzler, M., & Posner, S. (2005). Socioeconomic status in health research: One size does not fit all. Journal of the American Medical Association, 294(22), 28792888. doi: 10.1001/jama.294.22.2879 CrossRefGoogle ScholarPubMed
Broglio, S.P., McCrea, M., McAllister, T., Harezlak, J., Katz, B., & Hack, D., . . . CARE Consortium Investigators. (2017). A national study on the effects of concussion in collegiate athletes and US military service academy members: The NCAA–DoD Concussion Assessment, Research and Education (CARE) consortium structure and methods. Sports Medicine, 47, 14371451.CrossRefGoogle ScholarPubMed
Collins, M.W., Grindel, S.H., Lovell, M.R., Dede, D.E., Moser, D.J., Phalin, B.R., & McKeag, D.B. (1999). Relationship between concussion and neuropsychological performance in college football players. Journal of the American Medical Association, 282(10), 964970.CrossRefGoogle ScholarPubMed
Cook, N.E., Huang, D.S., Silverberg, N.D., Brooks, B.L., Maxwell, B., Zafonte, R., & Iverson, G.L. (2017). Baseline cognitive test performance and concussion-like symptoms among adolescent athletes with ADHD: Examining differences based on medication use. The Clinical Neuropsychologist, 112.CrossRefGoogle ScholarPubMed
Covassin, T., Swanik, C.B., Sachs, M., Kendrick, Z., Schatz, P., Zillmer, E., & Kaminaris, C. (2006). Sex differences in baseline neuropsychological function and concussion symptoms of collegiate athletes. British Journal of Sports Medicine, 40(11), 923927. discussion 927. doi: 10.1136/bjsm.2006.029496 CrossRefGoogle ScholarPubMed
Darling-Hammond, L. (2004). The color line in American education: Race, resources, and student achievement. Du Bois Review, 1(02), 213246.CrossRefGoogle Scholar
Derogatis, L.R. (2000). Brief symptom inventory 18. Minneapolis, MN: NCS Pearson.Google Scholar
Dotson, V.M., Kitner-Triolo, M., Evans, M.K., & Zonderman, A.B. (2008). Literacy-based normative data for low socioeconomic status African Americans. The Clinical Neuropsychologist, 22(6), 9891017.CrossRefGoogle ScholarPubMed
Dotson, V.M., Kitner-Triolo, M.H., Evans, M.K., & Zonderman, A.B. (2009). Effects of race and socioeconomic status on the relative influence of education and literacy on cognitive functioning. Journal of the International Neuropsychological Society, 15(04), 580589.CrossRefGoogle ScholarPubMed
Duncan, G.J., Brooks-Gunn, J., & Klebanov, P.K. (1994). Economic deprivation and early childhood development. Child Development, 65(2 Spec No), 296318.CrossRefGoogle ScholarPubMed
Duncan, G.J., & Magnuson, K.A. (2003). Off with Hollingshead: Socioeconomic resources, parenting, and child development. Child: Care Health and Development, 27(2), 97115.Google Scholar
Elbin, R.J., Kontos, A.P., Kegel, N., Johnson, E., Burkhart, S., & Schatz, P. (2013). Individual and combined effects of LD and ADHD on computerized neurocognitive concussion test performance: Evidence for separate norms. Archives of Clinical Neuropsychology, 28(5), 476484. doi: 10.1093/arclin/act024 CrossRefGoogle ScholarPubMed
Gerrard, P.B., Iverson, G.L., Atkins, J.E., Maxwell, B.A., Zafonte, R., Schatz, P., & Berkner, P.D. (2017). Factor structure of ImPACT® in adolescent student athletes. Archives of Clinical Neuropsychology, 32, 117122.CrossRefGoogle ScholarPubMed
Gottfried, A.W. (1985). Measures of socioeconomic status in child development research: Data and recommendations. Merrill-Palmer Quarterly (1982-), 8592.Google Scholar
Hollingshead, A.B. (1975). Four factor index of social status. New Haven, CT: Yale University.Google Scholar
Jones, N.S., Walter, K.D., Caplinger, R., Wright, D., Raasch, W.G., & Young, C. (2014). Effect of education and language on baseline concussion screening tests in professional baseball players. Clinical Journal of Sport Medicine, 24(4), 284288.CrossRefGoogle ScholarPubMed
Kaplan, G.A., Turrell, G., Lynch, J.W., Everson, S.A., Helkala, E.L., & Salonen, J.T. (2001). Childhood socioeconomic position and cognitive function in adulthood. International Journal of Epidemiology, 30(2), 256263.CrossRefGoogle ScholarPubMed
Kontos, A.P., Elbin, R.J., Covassin, T., & Larson, E. (2010). Exploring differences in computerized neurocognitive concussion testing between African American and White athletes. Archives of Clinical Neuropsychology, 25, 734744.CrossRefGoogle ScholarPubMed
Korenman, S., Miller, J.E., & Sjaastad, J.E. (1995). Long-term poverty and child development in the United States: Results from the NLSY. Children and Youth Services Review, 17(1), 127155.CrossRefGoogle Scholar
Krieger, N., Williams, D.R., & Moss, N.E. (1997). Measuring social class in US public health research: Concepts, methodologies, and guidelines. Annual Review of Public Health, 18(1), 341378.CrossRefGoogle ScholarPubMed
Larrabee, G.J., Binder, L.M., Rohling, M.L., & Ploetz, D.M. (2013). Meta-analytic methods and the importance of non-TBI factors related to outcome in mild traumatic brain injury: Response to Bigler et al.(2013). The Clinical Neuropsychologist, 27(2), 215237.CrossRefGoogle Scholar
Littleton, A.C., Schmidt, J.D., Register-Mihalik, J.K., Gioia, G.A., Waicus, K.M., Mihalik, J.P., & Guskiewicz, K.M. (2015). Effects of attention deficit hyperactivity disorder and stimulant medication on concussion symptom reporting and computerized neurocognitive test performance. Archives of Clinical Neuropsychology, 30(7), 683693.CrossRefGoogle ScholarPubMed
Lovell, M., Collins, M., Podell, K., Powell, J., & Maroon, J. (2000). ImPACT: Immediate post-concussion assessment and cognitive testing. Pittsburgh, PA: NeuroHealth Systems, LLC.Google Scholar
Maerlender, A., Flashman, L., Kessler, A., Kumbhani, S., Greenwald, R., Tosteson, T., & McAllister, T. (2013). Discriminant construct validity of ImPACT™: A companion study. The Clinical Neuropsychologist, 27(2), 290299.CrossRefGoogle ScholarPubMed
Manly, J.J., Byrd, D.A., Touradji, P., & Stern, Y. (2004). Acculturation, reading level, and neuropsychological test performance among African American elders. Applied Neuropsychology, 11(1), 3746.CrossRefGoogle ScholarPubMed
Manly, J.J., Jacobs, D.M., Touradji, P., Small, S.A., & Stern, Y. (2002). Reading level attenuates differences in neuropsychological test performance between African American and White elders. Journal of the International Neuropsychological Society, 8(03), 341348.CrossRefGoogle ScholarPubMed
McCrea, M., Broshek, D.K., & Barth, J.T. (2015). Sports concussion assessment and management: Future research directions. Brain Injury, 29(2), 276282. doi: 10.3109/02699052.2014.965216 CrossRefGoogle ScholarPubMed
McCrory, P., Meeuwisse, W., Dvorak, J., Aubry, M., Bailes, J., Broglio, S., & Castellani, R.J. (2017). Consensus statement on concussion in sport—the 5th international conference on concussion in sport held in Berlin, October 2016. British Journal of Sports Medicine, bjsports-2017-097699.Google Scholar
NCAA College Sport Racial and Gender Report Card. (2015). Retrieved from http://www.tidesport.org/nfl-rgrc.html.Google Scholar
Nelson, L.D., LaRoche, A.A., Pfaller, A.Y., Lerner, E.B., Hammeke, T.A., Randolph, C., & McCrea, M.A. (2016). Prospective, head-to-head study of three computerized neurocognitive assessment tools (CNTs): Reliability and validity for the assessment of sport-related concussion. Journal of the International Neuropsychological Society, 22(1), 24.CrossRefGoogle ScholarPubMed
Pastor, P.N. (2009). Diagnosed attention deficit hyperactivity disorder and learning disability: US, 2004-2006: Data from the National Health Interview Survey. Collingdale, PA: DIANE Publishing.Google Scholar
Shuttleworth-Edwards, A.B., Kemp, R.D., Rust, A.L., Muirhead, J.G., Hartman, N.P., & Radloff, S.E. (2004). Cross-cultural effects on IQ test performance: A review and preliminary normative indications on WAIS-III test performance. Journal of Clinical and Experimental Neuropsychology, 26(7), 903920.CrossRefGoogle ScholarPubMed
Stamm, J.M., Bourlas, A.P., Baugh, C.M., Fritts, N.G., Daneshvar, D.H., Martin, B.M., & Stern, R.A. (2015). Age of first exposure to football and later-life cognitive impairment in former NFL players. Neurology, 84(11), 11141120. doi: 10.1212/WNL.0000000000001358 CrossRefGoogle ScholarPubMed
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47(10), 20152028.CrossRefGoogle ScholarPubMed
Williams, D.R. (1997). Race and health: Basic questions, emerging directions. Annals of Epidemiology, 7(5), 322333.CrossRefGoogle ScholarPubMed

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