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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]

The Low Energy Availability in Females Questionnaire (LEAF-Q) was validated to identify risk of the female athlete triad (triad) in female endurance athletes. This study explored the ability of the LEAF-Q to detect conditions related to low energy availability (LEA) in a mixed sport cohort of female athletes. Data included the LEAF-Q, SCOFF Questionnaire for disordered eating, dual-energy X-ray absorptiometry-derived body composition and bone mineral density, Mini International Neuropsychiatric Interview, blood pressure, and blood metabolic and reproductive hormones. Participants were grouped according to LEAF-Q score (≥8 or <8), and a comparison of means was undertaken. Sensitivity, specificity, and predictive values of the overall score and subscale scores were calculated in relation to the triad and biomarkers relevant to LEA. Fisher's exact test explored differences in prevalence of these conditions between groups. Seventy-five athletes (18–32 years) participated. Mean LEAF-Q score was 8.0 ± 4.2 (55% scored ≥8). Injury and menstrual function subscale scores identified low bone mineral density (100% sensitivity, 95% confidence interval [15.8%, 100%]) and menstrual dysfunction (80.0% sensitivity, 95% confidence interval [28.4%, 99.5%]), respectively. The gastrointestinal subscale did not detect surrogate markers of LEA. LEAF-Q score cannot be used to classify athletes as "high risk" of conditions related to LEA, nor can it be used as a surrogate diagnostic tool for LEA given the low specificity identified. Our study supports its use as a screening tool to rule out risk of LEA-related conditions or to create selective low-risk groups that do not need management as there were generally high negative predictive values (range 76.5–100%) for conditions related to LEA. [ABSTRACT FROM AUTHOR]

Objectives: To assess the effect of multiple high-risk-scenario (HRS) exposures on noncontact injury prediction in elite Australian footballers. Design: Retrospective cohort study. Methods: Sessional workload data (session rating of perceived exertion, global positioning system–derived distance, sprint distance, and maximum velocity) from 1 club (N = 60 players) over 3 seasons were collated; several established HRSs were also defined. Accumulated HRS sessional exposures were calculated retrospectively (previous 1–8 wk). Noncontact injury data were documented. Univariate and multivariate Poisson regression models determined injury incidence rate ratios (IRRs) while accounting for moderating effects (preseason workload volume and playing experience). Model performance was evaluated using receiver operating characteristics (area under curve). Results: Very low (0–8 sessions: IRR = 5.76; 95% confidence interval [CI], 1.69–19.66) and very high (>15 sessions: IRR = 4.70; 95% CI, 1.49–14.87) exposures to >85% of an individual's maximal velocity over the previous 8 wk were associated with greater injury risk compared with moderate exposures (11–12 sessions) and displayed the best model performance (area under curve = 0.64). A single session corresponding to a very low chronic load condition over the previous week for all workload variables was associated with increased injury risk, with sprint distance (IRR = 3.25; 95% CI, 1.95–5.40) providing the most accurate prediction model (area under curve = 0.63). Conclusions: Minimal exposure to high-velocity efforts (maximum speed exposure and sprint volume) was associated with the greatest injury risk. Being underloaded may be a mediator for noncontact injury in elite Australian football. Preseason workload and playing experience were not moderators of this effect. [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]