A prospective study of health problems at the 2018 17/U and 19/U Australian National Netball Championships with comparison of surveillance methodology - Smyth, E. A.; Piromalli, L.; Antcliff, A.; Newman, P.; Waddington, G.; Weissensteiner, J. R.; Drew, M. K. (Journal of Science and Medicine in Sport, 2020)
To investigate the incidence, site, nature and cause of injuries sustained during and four weeks following the 2018 Australian National Netball Championships (ANNC`s) using medical attention and self-report surveillance tools. Design: Prospective cohort study. Method: Injuries were recorded prospectively using medical attention and self-report data collection methods. One hundred and ninety-two athletes competed at the 2018 ANNC`s with 96 athletes in each age group (17/U & 19/U). Results: There were 103 medical attention injuries sustained by 80 athletes resulting in an incidence rate of 89.4 per 1000 player hours. The most frequently recorded medical attention injury diagnoses across both age groups were lateral ankle ligament sprain (n = 14, 13.6%), foot blisters (n = 11, 10.7%), and lumbar pain (n = 10, 9.7%). Ankle sprains (n = 4), anterior cruciate ligament (ACL) ruptures (n = 3) and concussion (n = 3) recorded as the highest sports incapacity injuries. The self-report data collection revealed that 46 (27.2%) athletes arrived at the tournament with an existing self-reported injury/illness and 57 (39.3%) athletes had a self-reported injury/illness at the conclusion of the ANNC (RR 1.44 95%CI 1.05-1.99, p = 0.030). Conclusion: There are no recent studies reporting injury rates specifically in pre-elite netball players. This study found an incidence rate of 89.4 per 1000 player hours. Ankle sprains are the highest medical attention and sports-incapacity injury in pre-elite netball athletes. Foot blisters and low back pain also feature in the highest medical attention injuries and ACL rupture and concussion were high sports incapacity injuries at the ANNC`s. Finally, combining both the medical attention and self-report injury/illness data collection methods identified more injuries/illnesses than the use of one method alone.