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Modeling the structure of acute sport-related concussion symptoms: A bifactor approach
Department of Neurosurgery, Medical College of Wisconsin, Milwaukee Wisconsin, USA.
Steve Hicks School of Social Work, University of Texas at Austin, Austin, Texas, USA.
Department of Psychology, Florida State University, Tallahassee Florida, USA.
Department of Neurosurgery, Medical College of Wisconsin, Milwaukee Wisconsin, USA.
2018 (English)In: Journal of the International Neuropsychological Society, ISSN 1355-6177, E-ISSN 1469-7661, Vol. 24, no 8, p. 793-804Article in journal (Refereed) Published
Abstract [en]

Objectives: Concussions cause diverse symptoms that are often measured through a single symptom severity score. Researchers have postulated distinct dimensions of concussion symptoms, raising the possibility that total scores may not accurately represent their multidimensional nature. This study examined to what degree concussion symptoms, assessed by the Sport Concussion Assessment Tool 3 (SCAT3), reflect a unidimensional versus multidimensional construct to inform how the SCAT3 should be scored and advance efforts to identify distinct phenotypes of concussion.

Methods: Data were aggregated across two prospective studies of sport-related concussion, yielding 219 high school and college athletes in the acute (<48 hr) post-injury period. Item-level ratings on the SCAT3 checklist were analyzed through exploratory and confirmatory factor analyses. We specified higher-order and bifactor models and compared their fit, inter-pretability, and external correlates.

Results: The best-fitting model was a five-factor bifactor model that included a general factor on which all items loaded and four specific factors reflecting emotional symptoms, torpor, sensory sensitivities, and headache symptoms. The bifactor model demonstrated better discriminant validity than the counterpart higher-order model, in which the factors were highly correlated (r = .55-.91).

Conclusions: The SCAT3 contains items that appear unidimensional, suggesting that it is appropriate to quantify concussion symptoms with total scores. However, evidence of multidimensionality was revealed using bifactor modeling. Additional work is needed to clarify the nature of factors identified by this model, explicate their clinical and research utility, and determine to what degree the model applies to other stages of injury recovery and patient subgroups.

Place, publisher, year, edition, pages
Cambridge: Cambridge University Press, 2018. Vol. 24, no 8, p. 793-804
Keywords [en]
Head injury, Concussion, Sports, Exploratory factor analysis, Confirmatory factor analysis, Bifactor model, Hierarchical model, Higher-order factor model, Psychometric properties, Clinical phenotypes
National Category
Psychology
Identifiers
URN: urn:nbn:se:oru:diva-78654DOI: 10.1017/S1355617718000462ISI: 000455095800004PubMedID: 30079858OAI: oai:DiVA.org:oru-78654DiVA, id: diva2:1378932
Note

Funding Agencies:

United States Department of Health & Human Services National Institutes of Health (NIH) - USA 1R03NS100691-01

U.S. Army Medical Research & Materiel Command (USAMRMC) United States Department of Defense W81XWH-12-1-0004W81XWH-14-1-0561

United States Department of Health & Human Services National Institutes of Health (NIH) - USA 1UL1-RR031973(-01)

Available from: 2019-12-16 Created: 2019-12-16 Last updated: 2019-12-18Bibliographically approved

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Kramer, Mark

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