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To investigate: (1) the injury epidemiology in an Australian academy; (2) how athletes transition through the high‐performance sport (HPS) pathway; and (3) why athletes leave this HPS program. This retrospective cohort study was conducted at an Australian HPS academy over a 4‐year period. Medical attention injuries were prospectively recorded. Injury incidence rates (IIR) and burden were calculated per 365 athlete‐days, according to sport, sex, and pathway level. Athlete pathway levels were mapped to the Foundations, Talent, Elite, and Mastery (FTEM) framework. Reasons for athletes transitioning out were reported. Four hundred and eighty‐one injuries were reported across 124 athletes at an IIR of 2.09 injuries per 365 athlete‐days (95% CI = 1.91–2.29). Most athletes (103, 83.1%) were injured at least once over the 4‐year period. IIRs increased (IRR = 1.17, 95% CI = 1.06–1.29, p = 0.001) as athletes progressed through the pathway. The most common reason for athlete attrition was deselection due to performance (n = 18), with 55.6% of these athletes sustaining an injury in the season prior to deselection. Injury burden was highest at E2 (119.5 days absence per 365 athlete‐days (95% CI = 62.18–229.67)) and lowest at T4 (30.47 days absence per 365 athlete‐days (95% CI = 21.98–42.24)). Injury occurrence is common across HPS, with IIRs increasing as athletes progressed to higher talent levels. Deselection due to poor performance was the main attrition factor, with more than half the deselected athletes impacted by injury prior to deselection. This study highlights an increased risk of deselection, following injury, and indicates the need for further development of prevention strategies targeting pathway athletes. [ABSTRACT FROM AUTHOR]

Purpose: Psychological stress is reported to be an important contributor to reduced sleep quality and quantity observed in elite athletes. The purpose of this study was to explore the association between psychological stress and sleep and to identify if specific aspects of sleep are disturbed. Methods: One hundred thirty-one elite athletes (mean [SD], male: n = 46, age 25.8 [4.1] y; female: n = 85, age 24.3 [3.9] y) from a range of sports completed a series of questionnaires in a 1-month period approximately 4 months before the 2016 Rio Olympic Games. Questionnaires included the Pittsburgh Sleep Quality Index; Recovery-Stress Questionnaire; Depression, Anxiety, and Stress Scale (DASS 21); and Perceived Stress Scale (PSS). Results: Regression analysis identified the PSS and DASS stress as the main variables associated with sleep. A PSS score of 6.5 or higher was associated with poor sleep. In addition, a PSS score lower than 6.5 combined with a DASS stress score higher than 4.5 was also associated with poor sleep. Univariate analyses on subcomponents of the Pittsburgh Sleep Quality Index confirmed that PSS is associated with lower sleep quality (t99 = 2.40, P =.018), increased sleep disturbances (t99 = 3.37, P =.001), and increased daytime dysfunction (t99 = 2.93, P =.004). DASS stress was associated with increased sleep latency (t94 = 2.73, P =.008), increased sleep disturbances (t94 = 2.25, P =.027), and increased daytime dysfunction (t94 = 3.58, P =.001). Conclusions: A higher stress state and higher perceived stress were associated with poorer sleep, in particular increased sleep disturbances and increased daytime dysfunction. Data suggest that relatively low levels of psychological stress are associated with poor sleep in elite athletes. [ABSTRACT FROM AUTHOR]

This study aimed to establish injury incidence rates (IIRs) and burden within an Australian male professional football club (n = 73) and to investigate longitudinal trends across five consecutive seasons (2016/17–2020/21). There was an overall IIR of 9.18 injuries per 1000 hours (h) (95% CI [7.89, 10.47]). The IIR was approximately seven times greater (rate ratio (RR): 6.85; 95% CI [5.13, 9.19]; p < 0.01) in matches (31.29 injuries per 1000 h; 95% CI [25.25, 37.33]) compared to training (4.49 injuries per 1000 h; 95% CI [3.51, 5.47]). The overall injury burden was 254.1 days lost per 1000 h (95% CI [220.9, 292.3]). Compared with the reference 2016/17 season, there were significant increases in minimal (RR: 6.94; 95% CI [1.27, 128.73]) and mild injuries (RR: 3.76; 95% CI [1.21, 16.39]) in season 2017/18 and decreases in moderate (RR: 0.40; 95% CI [0.19, 0.80]) and contact injuries (RR: 0.35; 95% CI [0.12, 0.90]) in season 2019/2020. Time-loss injury is common and represents a major burden in Australian male professional football, with injuries more frequently sustained during matches. Injury prevention practices should specifically be directed towards muscle/tendon and ligament injuries of the lower limb, particularly anterior cruciate ligament, ankle sprain and hamstring strain injuries. [ABSTRACT FROM AUTHOR]

In applied program settings, such as in natural environment control and education, performance evaluation is usually conducted by evaluators considering both self-comparison and comparison with peers. We have developed the performance outcome scoring template (POS-T) for assessments with high face-validity in these settings. POS-T puts achievements of individuals or groups in context, i.e. the resulting performance outcome score (POS) reflects a meaningful measure of performance magnitude with regards to internal and external comparisons. Development of a POS is performed in four steps supported by a statistical framework. Software is supplied for creation of scoring applications in different performance evaluation settings. We demonstrate the POS-T by evaluation of CO2 emissions reduction amongst 36 OECD member countries. [ABSTRACT FROM AUTHOR]