The need for para-cycling classification research
The need for para-cycling classification research
Nooijen CFa,b,*, Liljedahl Ja, Bjerkefors Aa, Arndt Ta, b a Swedish School of Sport and Health Sciences (GIH), Stockholm, Sweden b Karolinska Institutet, Stockholm, Sweden
*Corresponding author: Carla Nooijen; [email protected]
Abstract PURPOSE: The present para-cycling classification system is mostly based on expert opinion rather than on scientific evidence. In a valid classification system, one would expect demonstrable differences in performance between different sport classes. The aim of this study was to determine the differences in race performance between para-cycling classes at track world championships. METHODS: We used results from the men’s C1-C5 (C1 most impaired) 1 km time trials of the last 7 UCI World Championships on the track. The average race speed was calculated from the official race time results of the 5 fastest athletes. Additionally, we obtained able-bodied race results of the 2018 World Championships in Apeldoorn and expressed the para-cycling results as a percentage of the average race speed of the top 5 able-bodied athletes. Kruskal-Wallis tests with Mann-Whitney U post hoc tests were performed, correcting for multiple testing by adjusting the significance level to p<0.013. RESULTS: Overall median race speed was 50.5 km/hr. Para-cyclists in C1 reached 75% and athletes in C5 90% of able- bodied race speed. Descriptive statistics revealed a large variation in the C1 class, with a median speed of 44.8 km/h and interquartile range (IQR) of 4.2 km/h. Average race speeds between consecutive classes were found to be significantly different, except between C4 and C5. Median speed of C5 (53.4 km/h, IQR=2.9) was not significantly faster than C4 (52.1 km/h, IQR=2.8), U=447, p=0.05. CONCLUSIONS: Race performance between athletes in the C1 and C2, C2 and C3, and C3 and C4 classes showed marked differences while average race speed of athletes in C4 and C5 were almost comparable. The variation in race performance in C1 was large and further research is needed to explain this. These results stress the need for para-cycling classification research and an evidence-based classification system.
Keywords Para-cycling, cycling, Paralympic sports, classification
Introduction
Classification provides the structure to ensure that winning is not determined by the impairment but by the same factors that account for success in able-bodied sports (Tweedy, Beckman et al. 2014). Classification is sport-specific, as impairments affect performance in different sports to different extents. The need for para-cycling classification research
Para-cycling, which is governed by the international cycling federation (Union Cycliste Internationale: UCI), is the third largest Paralympic sport and is part of the Paralympic program. Para-cyclists with physical impairments compete in any of the three different disciplines bicycling, tricycling or handcycling. This study will focus on cycling classification, which consists of five classes (ranging from C1 to C5 where C1 is the most impaired)(UCI 2018). Eligible impairments for competing are impairments in muscle strength, range of motion, limb deficiency, leg length difference, and coordination impairments (hypertonia, ataxia and athethosis). Different impairments are mixed within the classes, e.g. an athlete with an upper limb amputation competes against an athlete with severe athethosis. Many para-cycling athletes ride a typical bicycle but depending on their impairment, the bicycle can be adjusted but only if the adjustment does not compromise safety.
Over the last decade para-cycling has developed vastly and today almost all competing athletes are cycling professionals. However, there is only limited scientific evidence for para-cycling classification and the system is thus mostly based on expert opinion. In a valid classification system, one would expect demonstrable differences in race performance between different sport classes. The aim of this study was to determine the differences in race performance between para-cycling classes at recent major international competitions.
Methods
As an indicator for race performance we used results from the men’s C1-C5 (C1 most impaired) 1 km time trial of the last 7 UCI World Championships on the track (UCI 2011-2018). For the first 5 athletes, average race speed was calculated from official race time results. We thus compared a total of 175 race speed results. Additionally, we obtained able-bodied results from the top 5 of the 2018 World Championships in Apeldoorn and expressed the para-cycling results as a percentage of the average race speed of able-bodied athletes. Kruskal-Wallis tests with Mann-Whitney U post hoc tests were performed, correcting for multiple testing by adjusting the significance level to p<0.013.
Results
Descriptive statistics are presented in Table 1 and in Figure 1. Comparison between classes as presented in Table 2 showed significant differences between consecutive classes, except when comparing race speeds of athletes in C4 and C5.
Table 1. Descriptive statistics
Median Interquartile range % of able-bodied
Class 1 44.8 4.2 75.4
Class 2 46.9 1.5 78.2
Class 3 50.5 1.3 84.5
Class 4 52.1 2.8 88.4
Class 5 53.5 2.9 89.7 The need for para-cycling classification research
Figure 1. Median race speed of the 1-km time trial per class
Table 2. Mann-Whitney U-test comparing differences in speed between classes. U p-value
Class 1-2 323 <0.01
Class 2-3 5 <0.01
Class 3-4 140 <0.01
Class 4-5 447 0.05
Conclusion and discussion
It was found that, the higher the class the faster the race speed, with pronounced differences between consecutive classes except between C4 and C5 athletes, which on average had almost comparable race speeds during the 1-km time trial. The race speed of C5 athletes was 90% of the able-bodied athletes’ race speed. Variation in race performance between athletes in C1 was large and future research is needed to give more insight into how athletes with different impairments compare both between and within classes. We recently started a large 4-year research project to work towards an evidence-based para-cycling classification system in close collaboration with UCI.
The need for para-cycling classification research
References
Tweedy SM, Beckman EM, Connick MJ (2014) Paralympic classification: conceptual basis, current methods, and research update. PMR 6: S11-17
Union Cycliste Internationale (2018). https://www.uci.org/para-cycling/classification
Union Cycliste Internationale (2011-2018) https://www.uci.org/para-cycling/results