Football Team Social Structure and Perceived Support for Reporting Concussion Symptoms: Insights from a Social Network Analysis

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

Social network analysis (SNA) is a uniquely situated methodology to examine the social connections between players on a team, and how team structure may be related to self-reported team cohesion and perceived support for reporting concussion symptoms. Team belonging was positively associated with number of friendship ties (degree; r = .23, p < .05), intermediate ties between teammates (betweenness; r = .21, p < .05), and support from both teammates (r = .21, p < .05) and important others (r = .21, p < .05) for reporting concussion symptoms. Additionally, an SNA-derived measure of social influence, eigenvector centrality, was associated with football identity (r = .34, p < .01), and less support from important others (r = –.24, p < .05) regarding symptom reporting. Discussion focuses on why consideration of social influence dynamics may help improve concussion-related education efforts.

Wayment is with the Department of Psychological Sciences, Northern Arizona University, Flagstaff, AZ. Huffman, Lininger, and Doyle are with Northern Arizona University, Flagstaff, AZ.

Wayment (Heidi.Wayment@nau.edu) is corresponding author.
  • 1.

    Kerr ZY, Thomas LC, Simon JE, McCrea M, Guskiewicz KM. Association between history of multiple concussions and health outcomes among former college football players: 15-year follow-up from the ncaa concussion study (1999-2001). Am J Sports Med. 2018;46(7):1733–1741. PubMed ID: 29620911 doi:10.1177/0363546518765121

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    McCrea M, Hammeke T, Olsen G, Leo P, Guskiewicz K. Unreported concussion in high school football players: implications for prevention. Clin J Sport Med Off J Can Acad Sport Med. 2004;14(1):13–17. doi:10.1097/00042752-200401000-00003.

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

    Kroshus E, Garnett BR, Baugh CM, Calzo JP. Social norms theory and concussion education. Health Educ Res. 2015;30(6):1004–1013. PubMed ID: 26471918 doi:10.1093/her/cyv047

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    NCAA Academic and Membership Affairs Staff. 2016-2017 NCAA Division I Manual. Indianapolis, IN: NCAA; 2016.

  • 5.

    Meehan WP, Mannix RC, O’Brien MJ, Collins MW. The prevalence of undiagnosed concussions in athletes. Clin J Sport Med. 2013;23(5):339–342. PubMed ID: 23727697 doi:10.1097/JSM.0b013e318291d3b3

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

    Asken BM, McCrea MA, Clugston JR, Snyder AR, Houck ZM, Bauer RM. “Playing through it”: Delayed reporting and removal from athletic activity after concussion predicts prolonged recovery. J Athl Train. 2016;51(4):329–335. PubMed ID: 27111584 doi:10.4085/1062-6050-51.5.02

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

    Baugh CM, Kroshus E, Kiernan PT, Mendel D, Meehan WP III. Football players’ perceptions of future risk of concussion and concussion-related health outcomes. J Neurotrauma. 2017;34(4):790–797. PubMed ID: 27526721 doi:10.1089/neu.2016.4585

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

    LaRoche AA, Nelson LD, Connelly PK, Walter KD, McCrea MA. Sport-related concussion reporting and state legislative effects. Clin J Sport Med. 2016;26(1):33–39. PubMed ID: 25894530 doi:10.1097/JSM.0000000000000192.

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

    McCrory P, Meeuwisse W, Dvořák J, et al. Consensus statement on concussion in sport-the 5th International Conference on Concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017;51(11):838–847. doi:10.1136/bjsports-2017-097699

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

    Wasserman S, Faust K. Social Network Analysis: Methods and Applications. New York, NY: Cambridge University Press; 1994.

  • 11.

    Maya-Jariego I, Holgado D. Network analysis for social and community interventions. Psychosoc Interv. 2015;24(3):121–124. doi:10.1016/j.psi.2015.10.001

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

    Valente TW, Palinkas LA, Czaja S, Chu KH, Brown CH. Social network analysis for program implementation. PLOS ONE. 2015;10(6):e0131712. PubMed ID: 26110842 doi:10.1371/journal.pone.0131712

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

    Valente T. Social Networks and Health: Models, Methods, and Applications. Oxford, UK: Oxford University Press; 2010.

  • 14.

    Valente TW. Network interventions. Science. 2012;337(6090):49–53. PubMed ID: 22767921 doi:10.1126/science.1217330

  • 15.

    Rogers E. Diffusion of Innovations. New York, NY: Free Press; 2003.

  • 16.

    Borgatti S, Everett M, Johnson J. Analyzing Social Networks. Los Angeles, CA: Sage; 2013.

  • 17.

    Salim M, Brandao W, Camp O, Filipe J, eds. ICEIS 2018: Proceedings of the 20th International Conference on Enterprise Information Systems: Funchal, Madeira, Portugal, March 21-24, 2018. Vol. 1. Setúbal, Portugal: SCITEPRESS - Science and Technology Publications, Lda; 2018.

    • Search Google Scholar
    • Export Citation
  • 18.

    Mclean S, Salmon PM, Gorman AD, Dodd K, Solomon C. Integrating communication and passing networks in football using social network analysis. Sci Med Footb. 2019;3(1):29–35. doi:10.1080/24733938.2018.1478122

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Lusher D, Robins G, Kremer P. The application of social network analysis to team sports. Meas Phys Educ Exerc Sci. 2010;14(4):211–224. doi:10.1080/1091367X.2010.495559

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Kroshus E, Baugh CM, Daneshvar DH, Viswanath K. Understanding concussion reporting using a model based on the theory of planned behavior. J Adolesc Health. 2014;54(3):269–274.e2. doi:10.1016/j.jadohealth.2013.11.011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Register-Mihalik JK, Guskiewicz KM, McLeod TC, Linnan LA, Mueller FO, Marshall SW. Knowledge, attitude, and concussion-reporting behaviors among high school athletes: A preliminary study. J Athl Train. 2013;48(5):645–653.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Murdock JL, Strear MM, Jenkins-Guarnieri MA, Henderson AC. Collegiate athletes and career identity. Sport Educ Soc. 2016;21(3):396–410. doi:10.1080/13573322.2014.924920.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Brewer BW, Van Raalte JL, Linder DE. Athletic identity: Hercules’ muscles or Achilles heel? Int J Sport Psychol. 1993;24(2):237–254. doi:10.1177/104973239800800506

    • Search Google Scholar
    • Export Citation
  • 24.

    Podsakoff P, MacKenzie S. Organizational citizenship behaviors and sales unit effectiveness. J Mark Res. 1994;31(3):351–363. doi:10.1177/002224379403100303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Fransen K, Vanbeselaere N, De Cuyper B, Coffee P, Slater MJ, Boen F. The impact of athlete leaders on team members’ team outcome confidence: a test of mediation by team identification and collective efficacy. Sport Psychol. 2014;28(4):347–360. doi:10.1123/tsp.2013-0141

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26.

    Borgatti S, Everett M, Freeman L. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies; 2002.

  • 27.

    Borgatti S. Netdraw Network Visualization. Harvard, MA: Analytic Technologies; 2002.

  • 28.

    Craig DI, Lininger MR, Wayment HA, Huffman AH. Investigation of strategies to improve concussion reporting in American football. Res Sports Med. 2019:1–13. Ahead of Print. doi:10.1080/15438627.2019.1586706

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Borgatti, S.P., Everett, M.G., & Freeman, L.C. (2017). UCINET. In R. Alhajj & J. Rokne (Eds.), Encyclopedia of Social Network Analysis and Mining (pp. 237–259). New York, NY: Springer.

    • Search Google Scholar
    • Export Citation
  • 30.

    Wayment H, Craig D, Huffman A, Lininger M. A simple field-based tool to assess concussion reporting behavior: Implications for clinical practice and research. Am J Prev Med. 2019;56(2):323–330. PubMed ID: 30554973 doi:10.1016/j.amepre.2018.10.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Gesell SB, Barkin SL, Sommer EC, Thompson JR, Valente TW. Increases in network ties are associated with increased cohesion among intervention participants. Health Educ Behav. 2016;43(2):208–216. PubMed ID: 26286298 doi:10.1177/1090198115599397

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Lininger MR, Wayment HA, Craig DI, Huffman AH, Lane TS. Improving concussion-reporting behavior in National Collegiate Athletic Association Division I football players: Evidence for the applicability of the socioecological model for athletic trainers. J Athl Train. 2019;54(1):21–29. PubMed ID: 30721092 doi:10.4085/1062-6050-47-18

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Latkin CA, Knowlton AR. Social network assessments and interventions for health behavior change: A critical review. Behav Med. 2015;41(3):90–97. PubMed ID: 26332926 doi:10.1080/08964289.2015.1034645

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    McCann M, Broccatelli C, Moore L, Mitchell K. Distribution of sexual health knowledge and attitudes in adolescent social networks: social network analysis of data from the STIs and Sexual Health feasibility study. The Lancet. 2018;392:S60. doi:10.1016/S0140-6736(18)32047-6

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 481 481 53
PDF Downloads 155 155 13