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Injuries in professional soccer are a significant concern for teams, and they are caused amongst others by high training load. This cohort study describes the relationship between workload parameters and the occurrence of non-contact injuries, during weeks with high and low workload in professional soccer players throughout the season. Twenty-one professional soccer players aged 28.3 ± 3.9 yrs. who competed in the Iranian Persian Gulf Pro League participated in this 48-week study. The external load was monitored using global positioning system (GPS, GPSPORTS Systems Pty Ltd) and the type of injury was documented daily by the team's medical staff. Odds ratio (OR) and relative risk (RR) were calculated for non-contact injuries for high- and low-load weeks according to acute (AW), chronic (CW), acute to chronic workload ratio (ACWR), and AW variation (Δ-Acute) values. By using Poisson distribution, the interval between previous and new injuries were estimated. Overall, 12 non-contact injuries occurred during high load and 9 during low load weeks. Based on the variables ACWR and Δ-AW, there was a significantly increased risk of sustaining non-contact injuries (p < 0.05) during high-load weeks for ACWR (OR: 4.67), and Δ-AW (OR: 4.07). Finally, the expected time between injuries was significantly shorter in high load weeks for ACWR [1.25 vs. 3.33, rate ratio time (RRT)] and Δ-AW (1.33 vs. 3.45, RRT) respectively, compared to low load weeks. The risk of sustaining injuries was significantly larger during high workload weeks for ACWR, and Δ-AW compared with low workload weeks. The observed high OR in high load weeks indicate that there is a significant relationship between workload and occurrence of non-contact injuries. The predicted time to new injuries is shorter in high load weeks compared to low load weeks. Therefore, the frequency of injuries is higher during high load weeks for ACWR and Δ-AW. ACWR and Δ-AW appear to be good indicators for estimating the injury risk, and the time interval between injuries.
In the context of back pain, great emphasis has been placed on the importance of trunk stability, especially in situations requiring compensation of repetitive, intense loading induced during high-performance activities, e.g., jumping or landing. This study aims to evaluate trunk muscle activity during drop jump in adolescent athletes with back pain (BP) compared to athletes without back pain (NBP). Eleven adolescent athletes suffering back pain (BP: m/f: n = 4/7; 15.9 ± 1.3 y; 176 ± 11 cm; 68 ± 11 kg; 12.4 ± 10.5 h/we training) and 11 matched athletes without back pain (NBP: m/f: n = 4/7; 15.5 ± 1.3 y; 174 ± 7 cm; 67 ± 8 kg; 14.9 ± 9.5 h/we training) were evaluated. Subjects conducted 3 drop jumps onto a force plate (ground reaction force). Bilateral 12-lead SEMG (surface Electromyography) was applied to assess trunk muscle activity. Ground contact time [ms], maximum vertical jump force [N], jump time [ms] and the jump performance index [m/s] were calculated for drop jumps. SEMG amplitudes (RMS: root mean square [%]) for all 12 single muscles were normalized to MIVC (maximum isometric voluntary contraction) and analyzed in 4 time windows (100 ms pre- and 200 ms post-initial ground contact, 100 ms pre- and 200 ms post-landing) as outcome variables. In addition, muscles were grouped and analyzed in ventral and dorsal muscles, as well as straight and transverse trunk muscles. Drop jump ground reaction force variables did not differ between NBP and BP (p > 0.05). Mm obliquus externus and internus abdominis presented higher SEMG amplitudes (1.3–1.9-fold) for BP (p < 0.05). Mm rectus abdominis, erector spinae thoracic/lumbar and latissimus dorsi did not differ (p > 0.05). The muscle group analysis over the whole jumping cycle showed statistically significantly higher SEMG amplitudes for BP in the ventral (p = 0.031) and transverse muscles (p = 0.020) compared to NBP. Higher activity of transverse, but not straight, trunk muscles might indicate a specific compensation strategy to support trunk stability in athletes with back pain during drop jumps. Therefore, exercises favoring the transverse trunk muscles could be recommended for back pain treatment.
In the context of back pain, great emphasis has been placed on the importance of trunk stability, especially in situations requiring compensation of repetitive, intense loading induced during high-performance activities, e.g., jumping or landing. This study aims to evaluate trunk muscle activity during drop jump in adolescent athletes with back pain (BP) compared to athletes without back pain (NBP). Eleven adolescent athletes suffering back pain (BP: m/f: n = 4/7; 15.9 +/- 1.3 y; 176 +/- 11 cm; 68 +/- 11 kg; 12.4 +/- 10.5 h/we training) and 11 matched athletes without back pain (NBP: m/f: n = 4/7; 15.5 +/- 1.3 y; 174 +/- 7 cm; 67 +/- 8 kg; 14.9 +/- 9.5 h/we training) were evaluated. Subjects conducted 3 drop jumps onto a force plate (ground reaction force). Bilateral 12-lead SEMG (surface Electromyography) was applied to assess trunk muscle activity. Ground contact time [ms], maximum vertical jump force [N], jump time [ms] and the jump performance index [m/s] were calculated for drop jumps. SEMG amplitudes (RMS: root mean square [%]) for all 12 single muscles were normalized toMIVC (maximum isometric voluntary contraction) and analyzed in 4 time windows (100 ms pre- and 200 ms post-initial ground contact, 100 ms pre- and 200 ms post-landing) as outcome variables. In addition, muscles were grouped and analyzed in ventral and dorsal muscles, as well as straight and transverse trunk muscles. Drop jump ground reaction force variables did not differ between NBP and BP (p > 0.05). Mm obliquus externus and internus abdominis presented higher SEMG amplitudes (1.3-1.9-fold) for BP (p < 0.05). Mm rectus abdominis, erector spinae thoracic/lumbar and latissimus dorsi did not differ (p > 0.05). The muscle group analysis over the whole jumping cycle showed statistically significantly higher SEMG amplitudes for BP in the ventral (p = 0.031) and transverse muscles (p = 0.020) compared to NBP. Higher activity of transverse, but not straight, trunk muscles might indicate a specific compensation strategy to support trunk stability in athletes with back pain during drop jumps. Therefore, exercises favoring the transverse trunk muscles could be recommended for back pain treatment.
Purpose: To examine the effects of loaded (LPJT) versus unloaded plyometric jump training (UPJT) programs on measures of muscle power, speed, change of direction (CoD), and kicking-distance performance in prepubertal male soccer players. Methods: Participants (N = 29) were randomly assigned to a LPJT group (n = 13; age = 13.0 [0.7] y) using weighted vests or UPJT group (n = 16; age = 13.0 [0.5] y) using body mass only. Before and after the intervention, tests for the assessment of proxies of muscle power (ie, countermovement jump, standing long jump); speed (ie, 5-, 10-, and 20-m sprint); CoD (ie, Illinois CoD test, modified 505 agility test); and kicking-distance were conducted. Data were analyzed using magnitude-based inferences. Results: Within-group analyses for the LPJT group showed large and very large improvements for 10-m sprint time (effect size [ES] = 2.00) and modified 505 CoD (ES = 2.83) tests, respectively. For the same group, moderate improvements were observed for the Illinois CoD test (ES = 0.61), 5- and 20-m sprint time test (ES = 1.00 for both the tests), countermovement jump test (ES = 1.00), and the maximal kicking-distance test (ES = 0.90). Small enhancements in the standing long jump test (ES = 0.50) were apparent. Regarding the UPJT group, small improvements were observed for all tests (ES = 0.33-0.57), except 5- and 10-m sprint time (ES = 1.00 and 0.63, respectively). Between-group analyses favored the LPJT group for the modified 505 CoD (ES = 0.61), standing long jump (ES = 0.50), and maximal kicking-distance tests (ES = 0.57), but not for the 5-m sprint time test (ES = 1.00). Only trivial between-group differences were shown for the remaining tests (ES = 0.00-0.09). Conclusion: Overall, LPJT appears to be more effective than UPJT in improving measures of muscle power, speed, CoD, and kicking-distance performance in prepubertal male soccer players.
Strategic management is the deliberate engagement of an administration with the challenges of fulfilling its mission and ensuring and improving its ability to act by clarifying measures of success, an understanding of how to influence patterns of action, and organiza-tional learning. In this respect, it is not just about planning, but about an understanding of the emerging strategies of the administration in fulfilling its tasks and the use of opportunities for performance improvement, taking into account stakeholder expectations, resource base and organizational capabilities.
Evaluating the performance of self-adaptive systems (SAS) is challenging due to their complexity and interaction with the often highly dynamic environment. In the context of self-healing systems (SHS), employing simulators has been shown to be the most dominant means for performance evaluation. Simulating a SHS also requires realistic fault injection scenarios. We study the state of the practice for evaluating the performance of SHS by means of a systematic literature review. We present the current practice and point out that a more thorough and careful treatment in evaluating the performance of SHS is required.
Purpose Paradoxical leadership (PL) is an emerging perspective to understand how leaders help followers deal with paradoxical demands. Recently, the positive relationship between PL and follower performance was established. This paper builds on and extends this research by interpreting PL as sensegiving and developing theory about mediation in the relationship between PL and adaptive and proactive performance. Design/methodology/approach The paper develops a new measure for PL as sensegiving and provides a test of the mediation model with data from two different sources and two measurement times in a German company. Findings Multilevel mediation analysis (N = 154) supports the mediation model. Originality/value The paper presents sensegiving about paradox as a core element of PL, which informs the choice of change-readiness as mediator. This study also develops and validates a scale to measure PL in future research.
We examined state evaluation anxiety, trait evaluation anxiety, and neuroticism in relation to New Zealand first-year university students' (n = 234) task performance on either a test or essay assessment. For both assessment types, the underlying components of state evaluation anxiety (cognitive worry, emotionality, and distraction) reflect linear-as opposed to nonlinear-associations with task performance. Results of several regression models show differential effects of both state evaluation anxiety and neuroticism on task performance depending on the assessment type. The multi-dimensionality of anxiety and its relative contribution on task performance across authentic types of assessment are discussed.
The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8–18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.
Background:
COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.
Objective:
The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.
Methods:
We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.
Results:
Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.
Conclusions:
We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.