Methods for Prediction of Core or Lower Extremity Injury Among High School Football Players as a Strategy for Longitudinal Reduction of Injury Risk

in International Journal of Athletic Therapy and Training
Restricted access

Purchase article

USD $24.95

Student 1 year subscription

USD $74.00

1 year subscription

USD $99.00

Student 2 year subscription

USD $141.00

2 year subscription

USD $188.00

Poor neuromechanical control and rapid fatigue of the core muscles are associated with elevated risk for core or lower extremity (CLE) injury. The purpose of this study was to identify preparticipation screening measures associated with both previous and subsequent CLE injuries among high school football players. Self-reported CLE injury history, core muscle endurance, and postural balance were strongly associated with CLE injury. Our findings demonstrated that the same risk categorization cut-points predicted both injury within the previous 12 months and subsequent season injury. Preseason screening results can be used to estimate CLE injury susceptibility among high school football players.

Marisa A. Colston is the department head of Health and Human Performance, and faculty member for the Graduate Athletic Training Program, University of Tennessee at Chattanooga, Chattanooga, TN. Gary B. Wilkerson is a professor with the Graduate Athletic Training Program, University of Tennessee at Chattanooga, Chattanooga, TN. Hillary Dreyfus is with Kennesaw State University, Kennesaw, GA. Ryan Ross is with the Denver Broncos Football Club, Englewood, CO. Luke Donovan, PhD, MEd, University of North Carolina at Charlotte, is the report editor for this article.

Address author correspondence to Marisa A. Colston at Marisa-Colston@utc.edu.
International Journal of Athletic Therapy and Training
Article Sections
References
  • 1.

    Comstock RDCurrie DWPierpoint LA. Summary Report: National High School Sports-Related Injury Surveillance Study – 2015–2016 School Year. Center for Injury Research and Policy, Nationwide Children’s Hospital Research Institute: Columbus, OH; 2016.

    • Search Google Scholar
    • Export Citation
  • 2.

    Kerr ZYSimon JEGrooms DRRoos KGCohen RPDompier TP. Epidemiology of football injuries in the national collegiate athletic association, 2004–2005 to 2008–2009. Orthop J Sports Med. 2016;4(9):2325967116664500. PubMed ID: 27635412 doi:10.1177/2325967116664500

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Chalmers DJ. Injury prevention in sport: not yet part of the game? Inj Prev. 2002;8(suppl 4):IV22IV25. PubMed ID: 12460952

  • 4.

    Hertel J. Research training for clinicians: the crucial link between evidence-based practice and third-party reimbursement. J Athl Train. 2005;40(2):6970. PubMed ID: 15970951

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    van Mechelen WHlobil HKemper HC. Incidence, severity, aetiology, and prevention of sports injuries: a review of concepts. Sports Med. 1992;14(2):8299. PubMed ID: 1509229 doi:10.2165/00007256-199214020-00002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Hagglund MWalden MEkstrand J. Previous injury as a risk factor for injury in elite football: a prospective study over two consecutive seasons. Br J Sports Med. 2006;40:767772. doi:10.1136/bjsm.2006.026609

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Steffen KMyklebust GAnderson TEHolme I. Self-reported injury history and lower limb function as risk factors for injuries in female youth soccer. Am J Sports Med. 2008;36(4):700708. PubMed ID: 18227233 doi:10.1177/0363546507311598

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Wilkerson GBColston MABaker CS. A sport fitness index for assessment of sport-related injury risk. Clin J Sport Med. 2016;26(5):423428. PubMed ID: 26657821 doi:10.1097/JSM.0000000000000280

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Wilkerson GBColston MA. A refined prediction model for core and lower extremity sprains and strains among collegiate football players. J Athl Train. 2015;50:643650. PubMed ID: 25844856 doi:10.4085/1062-6050-50.2.04

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Wilkerson GBGiles JLSeibel DK. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study. J Athl Train. 2012;47:264272. PubMed ID:22892407 doi:10.4085/1062-6050-47.3.17

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Zazulak BTHewett TEReeves NPGoldberg BCholewicki J. Deficits in neuromuscular control of the trunk predict knee injury risk: a prospective biomechanical-epidemiologic study. Am J Sports Med. 2007;35(7):11231130. PubMed ID: 17468378 doi:10.1177/0363546507301585

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Plisky PJRauh MJKaminski TWUnderwood FB. Star excursion balance test as a predictor of lower extremity injury in high school basketball players. J Orthop Sports Phys Ther. 2006;36(12):911919. PubMed ID: 17193868 doi:10.2519/jospt.2006.2244

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Ford AGribble PAPfile KR. Star excursion balance test as a predictor of ankle and knee injuries in collegiate football athletes [abstract]. J Athl Train. 2012;47(suppl 3):44.

    • Search Google Scholar
    • Export Citation
  • 14.

    Stiffler MRBell DRSanfilippo JLHetzel SJPickett KAHeiderscheit BC. Star excursion balance test anterior asymmetry is associated with injury status in division I collegiate athletes. J Orthop Sports Phys Ther. 2017;47(5):339346. PubMed ID: 28355980 doi:10.2519/jospt.2017.6974

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Bruce SLRush JRTorres MMLipscomb KJ. Test-retest and interrater reliability of core muscular endurance tests used for injury risk screening. Int J Athl Train Ther. 2017;22(2):1420. doi:10.1123/ijatt.2016-0001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Moons KGAltman DGReitsma JBet al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W173. PubMed ID: 25560730 doi:10.7326/M14-0698

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Bahr R. Why screening tests to predict injury do not work and probably never will…: a critical review. Br J Sports Med. 2016;50:776780. PubMed ID: 27095747 doi:10.1136/bjsports-2016-096256

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Hides JAStanton WR. Can motor control training lower the risk of injury for professional football players? Med Sci Sport Exerc. 2014;46(4):762768. doi:10.1249/MSS.0000000000000169

    • Crossref
    • Search Google Scholar
    • Export Citation
Article Metrics
All Time Past Year Past 30 Days
Abstract Views 34 34 24
Full Text Views 5 5 1
PDF Downloads 0 0 0
Altmetric Badge
PubMed
Google Scholar