The International Paralympic Committee (IPC) mandates Paralympic Sports to develop evidence-based classification systems that allocate athletes into 'classes' according to the impact of their impairment on sport-specific performance. In wheelchair-basketball, a panel of classifiers assesses athlete's performance through observation. One key barrier to evidence-based classification is the absence of defined eligible impairments, including clear guidelines on how to assess them and their impact on wheelchair basketball performance. This study aims to reach expert consensus on issues specific to wheelchair basketball that can benefit from evidence-based classification. It offers recommendations for refining the classification manual, thus improving adherence to the IPC classification code. A three-round Delphi study was conducted with 29 experts in wheelchair basketball. The experts agreed with the new definition for the aim of wheelchair basketball classification, which is in line with the IPC code. Cases identified as having the highest risk for disagreement between classifiers included classifying players with upper limb deficiency or with impaired coordination. The panel failed to agree on changing the classification procedures and on defining the eligible impairment list. This study identifies issues specific to wheelchair basketball classification to be addressed in future research. Additional discussions need to take place to promote further resolution.

This study aimed to understand the sleeping habits of Israeli Paralympic Athletes as a pre-intervention stage to implement sleep hygiene programs. The Pittsburgh Sleep Quality Index questionnaire was used to assess sleep quality. The Epworth Sleepiness Scale was used to determine sleepiness throughout the day. Chronotype was detected using the Horne and Östberg Questionnaire. Paraathletes who were expected to represent Israel at the Tokyo 2020 games were approached via email. The surveys were collected online between April and August, 2018. Para-athletes (n = 52, male = 32, female = 20, mean age = 31.2y, SD = 11.9, from 13 different sport disciplines) completed the online surveys. One-way ANOVA test was used to compare sleep efficiency between the sleepy and non-sleepy groups. MANOVA test was performed to evaluate differences between sleep efficiency, daytime dysfunction and latency between the good and poor sleep quality groups. Non-parametric tests were conducted to analyze the association between the results of the three questionnaires and each sample characteristics. Under a third (31%, n=16) of the athletes slept between 6.5 to 7 hours per night, and a further 29% (n=15) slept less than 6 hours. From the MANOVA analysis, athletes with poor sleep quality had statistically significantly lower sleep efficiency (p=.028, F(1,50)=5.11, medium effect size: 𝜂 𝑝 2 =0.093), greater daytime dysfunction (p<.001, F(1,50)=14.19, large effect size: 𝜂 𝑝 2 =.221), and greater sleep latency (p<.001, F(1,50)=15.08, large effect size: 𝜂 𝑝 2 =.232), than athletes with good sleep quality.Of the athletes, 33% reported having 'moderate to excessive daytime sleepiness', 46% did not train at times that match their chronotype. The results of this study may aid in planning effective intervention methods to improve athletes' sleep quality.

Objectives Limited research exists on the sleep profiles of South African Para athletes. The aim of this study was to describe sleep quality, day-time sleepiness and chronotype of South African Para athletes, and to compare the relationship between sleep-related outcomes and demographic factors to athletes from a higher resourced country. Design A descriptive, cross-sectional survey was conducted. Sleep-related characteristics were assessed with the Pittsburgh Sleep Quality Index, Epworth Sleepiness scale and Morningness-Eveningness Questionnaire. Multiple regression models were run with and without country as independent variable. Results 124 South African athletes and 52 Israeli athletes were included. 30% of South African athletes presented with excessive daytime sleepiness, 35% slept 6 hours or less/night, and 52% reported poor sleep quality. 33% of Israeli athletes reported excessive daytime sleepiness, 29% slept 6 hours or less and 56% reported poor sleep quality. Chronotype was the only variable that differed significantly between countries (over-representation of morning types in South African athletes, and intermediate types in Israeli athletes). Intermediate chronotypes had significantly greater odds of excessive daytime sleepiness (p = 0.007) and poor sleep quality (p = 0.002) than morning types, irrespective of country. Conclusion The high prevalence of poor sleep among both South African and Israeli Para athletes warrants further investigation.