Article

Should Australian football players wear custom-made mouthguards? Results from a group-randomised controlled trial

New South Wales Injury Risk Management Research Centre, University of New South Wales, Sydney, NSW 2052, Australia.
Injury Prevention (Impact Factor: 1.94). 09/2005; 11(4):242-6. DOI: 10.1136/ip.2004.006882
Source: PubMed

ABSTRACT Head/orofacial (H/O) injuries are common in Australian rules football. Mouthguards are widely promoted to prevent these injuries, in spite of the lack of formal evidence for their effectiveness.
The Australian football injury prevention project was a cluster randomized controlled trial to evaluate the effectiveness of mouthguards for preventing H/O injuries in these players. Setting and
Twenty three teams (301 players) were recruited from the largest community football league in Australia.
Teams were randomly allocated to either the MG: custom made mouthguard or C: control (usual mouthguard behaviours) study arm.
All injuries, participation in training and games, and mouthguard use were monitored over the 2001 playing season. Injury rates were calculated as the number of injuries per 1000 person hours of playing time. Adjusted incidence rate ratios were obtained from Poisson regression models.
Players in both study arms wore mouthguards, though it is unlikely that many controls wore custom made ones. Wearing rates were higher during games than training. The overall rate of H/O injury was 2.7 injuries per 1000 exposure hours. The rate of H/O injury was higher during games than training. The adjusted H/O injury incidence rate ratio was 0.56 (95% CI 0.32 to 0.97) for MG versus C during games and training, combined.
There was a significant protective effect of custom made mouthguards, relative to usual mouthguard use, during games. However, the control players still wore mouthguards throughout the majority of games and this could have diluted the effect.

Download full-text

Full-text

Available from: Paul McCrory, Aug 28, 2015
0 Followers
 · 
92 Views
  • Source
    • "Study teams were recruited into the larger study, even if some players did not give their informed consent for us to monitor them. This recruitment methodology has previously been used in another sports injury prevention RCT and shown to lead to unbiased recruitment of teams and players.37 41 51 "
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND: Knee injuries are a major injury concern for Australian Football players and participants of many other sports worldwide. There is increasing evidence from laboratory and biomechanically focused studies about the likely benefit of targeted exercise programmes to prevent knee injuries. However, there have been few international studies that have evaluated the effectiveness of such programmes in the real-world context of community sport that have combined epidemiological, behavioural and biomechanical approaches. OBJECTIVE: To implement a fully piloted and tested exercise training intervention to reduce the number of football-related knee injuries. In so doing, to evaluate the intervention's effectiveness in the real-world context of community football and to determine if the underlying neural and biomechanical training adaptations are associated with decreased risk of injury. SETTING: Adult players from community-level Australian Football clubs in two Australian states over the 2007-08 playing seasons. METHODS: A group-clustered randomised controlled trial with teams of players randomly allocated to either a coach-delivered targeted exercise programme or usual behaviour (control). Epidemiological component: field-based injury surveillance and monitoring of training/game exposures. Behavioural component: evaluation of player and coach attitudes, knowledge, behaviours and compliance, both before and after the intervention is implemented. Biomechanical component: biomechanical, game mobility and neuromuscular parameters assessed to determine the fundamental effect of training on these factors and injury risk. OUTCOME MEASURES: The rate and severity of injury in the intervention group compared with the control group. Changes, if any, in behavioural components. Process evaluation: coach delivery factors and likely sustainability.
    Injury Prevention 07/2009; 15(3):e1. DOI:10.1136/ip.2008.021279 · 1.94 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper proposes a new sports injury research framework, the Translating Research into Injury Prevention Practice framework, or TRIPP. This model builds on the fact that only research that can, and will, be adopted by sports participants, their coaches and sporting bodies will prevent injuries. Future advances in sports injury prevention will only be achieved if research efforts are directed towards understanding the implementation context for injury prevention, as well as continuing to build the evidence base for their efficacy and effectiveness of interventions. There is no doubt that intervention research in the sporting field can be difficult and many challenges need to be overcome; however, that should not be put up as a barrier towards undertaking it. Over the next few years, sports injury researchers will need to think carefully about the "best" study designs and analysis tools to achieve this. All reported sports injury studies, of whatever design, should include information on key implementation factors such as player/club recruitment rates and other biases as well as the rate of uptake of the interventions being tested, including reasons for use/non-use. However, it will only be broad research endeavours that adopt the TRIPP six-staged approach that will lead to real-world injury prevention gains.
    Journal of Science and Medicine in Sport 06/2006; 9(1-2):3-9; discussion 10. DOI:10.1016/j.jsams.2006.02.009 · 3.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Clustered, or dependent, data, arise commonly in sports medicine and sports science research, particularly in studies of sports injury and biomechanics, particularly in sports injury trials that are randomised at team or club level, in cross-sectional surveys in which groups of individuals are studied and in studies with repeated measures designs. Clustering, or positive correlation among responses, arises because responses and outcomes from the same cluster will usually be more similar than from different clusters. Study designs with clustering will usually required an increased sample size when compared to those without clustering. Ignoring clustering in statistical analyses can also lead to misleading conclusions, including incorrect confidence intervals and p-values. Appropriate statistical analyses for clustered data must be adopted. This paper gives some examples of clustered data and discusses the implications of clustering on the design and analysis of studies in sports medicine and sports science research.
    Journal of Science and Medicine in Sport 06/2006; 9(1-2):165-8. DOI:10.1016/j.jsams.2006.02.003 · 3.08 Impact Factor
Show more