Search

Purpose: A decline in youth running was observed at the start of the COVID-19 pandemic. We investigated whether the resumption of organized running after social distancing restrictions changed running habits or injury frequency in adolescent runners. Methods: Adolescents (age = 16.1 [2.1] y) who participated in long-distance running activities completed an online survey in the Spring and Fall of 2020. Participants self-reported average weekly running habits and whether they sustained an injury during the Fall 2020 season. Poisson regression models and 1-way analysis of variance compared running habits while Fisher exact test compared differences in frequencies of injuries during Fall 2020 among season statuses (full, delayed, and canceled). Results: All runners, regardless of season status, increased weekly distance during Fall 2020. Only runners with a full Fall 2020 season ran more times per week and more high-intensity runs per week compared with their Spring 2020 running habits. There were no differences in running volume or running-related injury frequency among Fall 2020 season statuses. Conclusions: There were no significant differences in running-related injury (RRI) frequency among runners, regardless of season status, following the resumption of cross-country. Health care providers may need to prepare for runners to increase running volume and intensity following the resumption of organized team activities. [ABSTRACT FROM AUTHOR]

Variable radius plot surveys can require updated estimates when the quality of previous estimates have declined over time. We developed a statistical estimator for this purpose that is the product of two estimators, one estimator is for the updated volume-to-basal-area ratio and the other estimator is for the updated basal area. Our estimator relies only on the surveyor identifying previously measured trees and does not require the identification of ingrowth, which simplifies its application. We also propose a variance estimator that relies on the bootstrap method. We investigate the point and variance estimators under repeated sampling of stem-mapped populations that include five measurements over a period of approximately 20 years. Based on 144 sampling scenarios, our estimator demonstrated relative biases ranging between −0.3% and 0.8%. The bootstrap variance estimator tended to be deflated, with relative absolute biases ranging between −8% and 4%. When revisiting one third of the initially installed plots, our estimator obtained relative root mean square errors within 1.6% of an independent resurvey effort that does not use the prior survey. This implies that our estimator can substantially reduce field work while producing surveys of approximately the same quality when updating prior surveys. [ABSTRACT FROM AUTHOR]

Context: Physical changes following activity are well documented, but there is limited information about self-reported outcomes around competitive matches. High training volumes and poor recovery could predispose athletes to overuse injury. The purpose of this study was to identify the changes in daily athlete health measures before, during, and after the day of each match in high- and low-volume groups. Design: Prospective cohort. Methods: Fifty-five soccer athletes (age: 19.8 [1.2] y, 26 males, 29 females) provided daily measures of readiness, physical fatigue, mental stress, sleep quality, and soreness intensity match days, days 1 (D01) and 2 (D02) following matches, and standard practice days. Participants were grouped into high volume and low volume, based off the minutes played during the season. Results: Soreness increased, readiness decreased, and fatigue increased on D01 compared with match days (P <.008) in the high-volume group. Between groups, the high-volume group demonstrated higher soreness on D01 and D02, lower readiness on D01 and D02, and lower fatigue on D01, compared with the low-volume group (P <.008). Conclusions: Soccer athletes demonstrate significant changes in self-reported athlete health variables around competitive matches. These changes are similar to physical outcomes, potentially indicating that the athlete health variables may be used to track athlete recovery from competition, potentially limiting the impact of overuse injuries. [ABSTRACT FROM AUTHOR]

Pexa, BS, Johnston, CD, Elder, EE, Ford, KR, Patterson, MQ, and Myers, JB. Pool-based surfboard elicits activation of posterior shoulder muscles during a surfing stroke. J Strength Cond Res 38(7): 1300–1304, 2024—Surfboard paddling may activate posterior shoulder muscles, which are critical to baseball pitchers’ injury risk and performance. The purpose of this study was to measure posterior shoulder muscle activation during different phases of the surf stroke (propulsion vs. recovery) on a pool-based surfboard. Twenty healthy active adult subjects completed a familiarization and testing session with the pool-based surfboard. During the testing session, electromyography (EMG) sensors were placed on 6 posterior shoulder muscles: latissimus dorsi, infraspinatus, posterior deltoid, upper trapezius, middle trapezius, and lower trapezius. Subjects completed 4 laps in a pool at 3 separate resistances (low, moderate, and heavy) in a randomized order. The peak EMG signal during each phase (propulsion and recovery) was recorded. A 2-way within subject ANOVA (resistance-by-phase) with post hoc Bonferroni’s corrections was used to identify differences in EMG activation. There was a significant main effect of phase for the latissimus dorsi (F 5 91.3, p, 0.001), upper trapezius (F 5 36.5, p, 0.001), middle trapezius (F 5 33.8, p, 0.001), and lower trapezius (F 5 21.6, p, 0.001). The latissimus dorsi demonstrated higher activation during the propulsion phase (p, 0.001), and all trapezius muscles demonstrated higher activation during the recovery phase (p, 0.001). There was a significant main effect of resistance for the posterior deltoid (F 5 3.4, p 5 0.043), with higher muscle activation in the low resistance trials compared with the heavy resistance trials (p 5 0.036). Recreationally active individuals demonstrate activation of the posterior shoulder when using a pool-based surfboard. This poolbased surfboard may be beneficial to activate the posterior musculature and may be more accessible than standard surfing to baseball athletes. [ABSTRACT FROM AUTHOR]

Context: Women's volleyball requires frequent and repetitive jumping that when performed with altered biomechanics, including kinematic or kinetic asymmetry, may place the athlete at high risk for injury. This study identified and analyzed lower-extremity biomechanical asymmetries in college women's volleyball players during standard and sport-specific double-leg landing tasks. Design: Cross-sectional laboratory study. Methods: Eighteen female college volleyball players were analyzed using standard 3D motion capture techniques during a drop vertical jump and an unanticipated lateral reactive jump task. Repeated-measures multivariate analysis of variance identified asymmetries in kinematic and kinetic variables of each task. Results: Average symmetry indices ranged from 9.3% to 31.3% during the drop vertical jump and 11.9% to 25.6% during the reactive jump task. During the drop vertical jump, the dominant limb exhibited lower knee abduction moments (P =.03), ankle dorsiflexion moments (P =.02), ankle eversion moments (P =.003) and vertical ground reaction forces (P =.03), and greater ankle inversion moments (P =.001). Both kinematic (λ = 0.27, P =.03) and kinetic (λ = 0.12, P =.008) asymmetries were identified during the reactive jump task. The dominant limb exhibited greater peak knee flexion (P =.003) and ankle dorsiflexion (P =.02) angles, and greater ankle dorsiflexion (P =.005) and inversion (P =.03) moments than the nondominant limb. Conclusions: These asymmetries observed during double-leg landing tasks may predispose volleyball athletes to unilaterally higher ground reaction or muscle forces and ultimately a greater risk of injury during landing. [ABSTRACT FROM AUTHOR]

Introduction: Trunk and shoulder strength are consistently shown to be involved in performance limitations, as well as contributing to stability, power output, and reducing the risk of injury. Although their biomechanical interaction is a critical aspect for athletes, there is limited research on the relationship between trunk and shoulder strength in sports where upper body mechanics are critical for optimal performance. Purpose: This study examined the differences and relationships between trunk rotational strength and shoulder rotational strength among athletes participating in mixed martial arts (MMA), tennis, swimming, and baseball. Methods: Maximal voluntary contraction tests were performed to evaluate strength of 39 professional adult male athletes from disciplines of MMA (n = 6), tennis (n = 11), swimming (n = 11) and baseball (n = 11). Peak force data were used in sports comparison and relationship analysis between trunk and shoulder rotation strength parameters. Results: The findings revealed a complex and significant relationship between trunk and shoulder strength, with unique patterns for each athletic discipline. Tennis players exhibited a strong correlation between trunk bilateral differences and internal shoulder rotation, while other disciplines demonstrated a more balanced use of trunk asymmetry. Swimmers displayed the best interactions between trunk and shoulder overall, emphasizing the aquatic environment's biomechanical demands. In MMA, the strongest correlation was between shoulder internal and external rotation with the trunk, mainly due to the number of defensive movements in addition to offensive ones. Baseball pitchers showed a significant correlation between internal/external shoulder rotation strength ratio and trunk asymmetry. Conclusion: While no differences in peak force variables were found, unique relationships between trunk and shoulder rotational performance were discovered. The results suggest a long-term sport-specific adaptation of the trunk-shoulder interaction in sports that require upper limb power movements. It seems, that the relationship between the various parameters of trunk and shoulder was influenced by the movement stereotype of each sport. Therefore, recognition of sport-specific interactions is critical to the development of effective training programs that enhance performance and potentially reduce injury risk in different sports. Researchers and practitioners should focus on longitudinally monitoring fluctuations in TRS and SRS relationships throughout each sport season and examining potential associations with injury incidence. [ABSTRACT FROM AUTHOR]

Diameter distributions and tree-lists provide information about forest stocks disaggregated by size and species and are key for informing forest management. Diameter distributions and tree-lists are multivariate responses, which makes the evaluation of methods for their prediction reliant on the use of dissimilarity metrics to summarize differences between observations and predictions. We compared four strategies for selection of k nearest neighbors (k-NN) methods to predict diameter distributions and tree-lists using LiDAR and stand-level auxiliary data and analyzed the effect of the k-NN distance and number of neighbors in the performance of the predictions. Strategies differed by the dissimilarity metric used to search for optimal k-NN configurations and the presence or absence of post-stratification. We also analyzed how alternative k-NN configurations ranked when tree-lists were aggregated using different DBH classes and species groupings. For all dissimilarity metrics, k-NN configurations using random-forest distance and three or more neighbors provided the best results. Rankings of k-NN configurations based on different dissimilarity metrics were relatively insensitive to changes on the width of the DBH classes and the definition of the species groups. The selection of the k-NN methods was clearly dependent on the choice of the dissimilarity metric. Further research is needed to find suitable ways to define dissimilarity metrics that reflect how forest managers evaluate differences between predicted and observed tree-lists and diameter distributions. Key words: tree-lists, diameter distributions, k-NN, Reynolds index, LiDAR. Les distributions de diametre et les listes d'arbres fournissent des informations sur les stocks forestiers, ventilees par taille et par espece, et sont des informations de gestion forestiere essentielles. Les distributions de diametre et les listes d'arbres sont influencees par plusieurs variables, par consequent l'evaluation des methodes servant a les predire depend de l'utilisation de mesures de dissimilarite pour exprimer les differences entre les observations et leurs predictions. Nous avons compare quatre strategies de selection des k plus proches voisins (k-NN) pour predire les distributions de diametre et les listes d'arbres a l'aide de donnees auxiliaires LiDAR et de peuplement. Nous avons egalement analyse les effets de la distance k-NN et du nombre de voisins sur la qualite des predictions. Les strategies differaient par la mesure de dissimilarite utilisee pour obtenir les configurations k-NN optimales et par l'utilisation, ou non, de la post-stratification. Nous avons egalement analyse le classement des differentes configurations de k-NN lorsque les listes d'arbres etaient agregees selon differentes classes de diametre et groupes d'especes. Pour toutes les mesures de dissimilarite, les configurations k-NN utilisant une distance fondee sur les forets d'arbres decisionnels et trois voisins ou plus ont donne les meilleurs resultats. Les classements des configurations k-NN fondees sur differentes mesures de dissimilarite etaient relativement insensibles aux modifications de : l'etendue des classes de diametre et la definition des groupes d'especes. Le choix des methodes k-NN dependait clairement du choix de la mesure de dissimilarite. Des recherches supplementaires sont necessaires pour trouver des moyens appropries de definir des mesures de dissimilarite qui refletent l'evaluation que font les amenagistes forestiers des differences entre les listes d'arbres et les distributions de diametre predites et observees. [Traduit par la Redaction] Mots-cles: liste d'arbres, distribution de diametre, k-NN, indice de Reynolds, LiDAR., 1. Introduction To make informed decisions, forest managers require information about the current state of the forest. Knowledge of the total stand volume or basal area is not enough for [...]

Background Delayed onset muscles soreness (DOMS) is an indication of muscle stress and trauma that develops from excessive musculoskeletal loads. Musculoskeletal loads can be measured with wearable devices, but there is limited research on specific training load metrics that most correlate with DOMS after activity. Purpose To determine the predictive capabilities of training load variables on the development of lower extremity DOMS in female collegiate soccer athletes throughout an entire season. Study Design Prospective Cohort Methods Twenty-seven collegiate female soccer athletes reported their lower extremity DOMS each day prior to all soccer activity. Participants wore Polar heart rate and global positioning monitors to capture training load measures. Pearson correlation coefficients were used to assess the relationships between the training load variables and change in DOMS when collapsed across dates. Separate linear mixed models were performed with the following day's DOMS as the outcome variable, training load and the current day's DOMS as predictor variables, and participants serving as random intercepts. Results All training load variables significantly predicted change in DOMS, with number of decelerations (ρ=0.72, p <0.001), minutes spent at greater than 80% of maximum heart rate (HRmax) (ρ=0.71, p <0.001), and distance (ρ=0.70, p <0.001) best correlating with change in DOMS. Linear mixed models revealed a significant interaction of all training load and current day's DOMS on the following day's DOMS (p<0.001), but number of decelerations, HRmax, and total number of accelerations demonstrated the highest coefficient of determination (R² marginal=33.2% - 29.2%, R² conditional= 46.9% - 44.8%). Conclusions Training load variables paired with the current day's DOMS significantly predict lower extremity DOMS in the future, with number of decelerations, accelerations, and HRmax best predicting future DOMS. Although this demonstrates that training load variables predict lower extremity DOMS, future research should incorporate objective measures of strength or jump kinetics to identify if similar relationships exist. Level of Evidence Level 3 [ABSTRACT FROM AUTHOR]