This study aimed to validate a simple field method for determining force– and power–velocity relationships and mechanical effectiveness of force application during sprint running. The proposed ...method, based on an inverse dynamic approach applied to the body center of mass, estimates the step‐averaged ground reaction forces in runner's sagittal plane of motion during overground sprint acceleration from only anthropometric and spatiotemporal data. Force– and power–velocity relationships, the associated variables, and mechanical effectiveness were determined (a) on nine sprinters using both the proposed method and force plate measurements and (b) on six other sprinters using the proposed method during several consecutive trials to assess the inter‐trial reliability. The low bias (<5%) and narrow limits of agreement between both methods for maximal horizontal force (638 ± 84 N), velocity (10.5 ± 0.74 m/s), and power output (1680 ± 280 W); for the slope of the force–velocity relationships; and for the mechanical effectiveness of force application showed high concurrent validity of the proposed method. The low standard errors of measurements between trials (<5%) highlighted the high reliability of the method. These findings support the validity of the proposed simple method, convenient for field use, to determine power, force, velocity properties, and mechanical effectiveness in sprint running.
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BFBNIB, FSPLJ, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
This study sought to lend experimental support to the theoretical influence of force-velocity (F-v) mechanical profile on jumping performance independently from the effect of maximal power output (P ...max ). 48 high-level athletes (soccer players, sprinters, rugby players) performed maximal squat jumps with additional loads from 0 to 100% of body mass. During each jump, mean force, velocity and power output were obtained using a simple computation method based on flight time, and then used to determine individual linear F-v relationships and P max values. Actual and optimal F-v profiles were computed for each subject to quantify mechanical F-v imbalance. A multiple regression analysis showed, with a high-adjustment quality (r²=0.931, P<0.001, SEE=0.015 m), significant contributions of P max , F-v imbalance and lower limb extension range (h PO ) to explain interindividual differences in jumping performance (P<0.001) with positive regression coefficients for P max and h PO and a negative one for F-v imbalance. This experimentally supports that ballistic performance depends, in addition to P max , on the F-v profile of lower limbs. This adds support to the actual existence of an individual optimal F-v profile that maximizes jumping performance, a F-v imbalance being associated to a lower performance. These results have potential strong applications in the field of strength and conditioning.
The objective of this study was to characterize the mechanics of maximal running sprint acceleration in high‐level athletes. Four elite (100‐m best time 9.95–10.29 s) and five sub‐elite (10.40–10.60 ...s) sprinters performed seven sprints in overground conditions. A single virtual 40‐m sprint was reconstructed and kinetics parameters were calculated for each step using a force platform system and video analyses. Anteroposterior force (FY), power (PY), and the ratio of the horizontal force component to the resultant (total) force (RF, which reflects the orientation of the resultant ground reaction force for each support phase) were computed as a function of velocity (V). FY‐V, RF‐V, and PY‐V relationships were well described by significant linear (mean R2 of 0.892 ± 0.049 and 0.950 ± 0.023) and quadratic (mean R2 = 0.732 ± 0.114) models, respectively. The current study allows a better understanding of the mechanics of the sprint acceleration notably by modeling the relationships between the forward velocity and the main mechanical key variables of the sprint. As these findings partly concern world‐class sprinters tested in overground conditions, they give new insights into some aspects of the biomechanical limits of human locomotion.
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BFBNIB, FSPLJ, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
This substantive-methodological synergy applies evolving approaches to factor analysis to substantively important developmental issues of how five-factor-approach (FFA) personality measures vary with ...gender, age, and their interaction. Confirmatory factor analyses (CFAs) conducted at the item level often do not support a priori FFA structures, due in part to the overly restrictive assumptions of CFA models. Here we demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory factor analysis, overcomes these problems with the 15-item Big Five Inventory administered as part of the nationally representative British Household Panel Study (N = 14,021; age: 15-99 years, Mage = 47.1). ESEM fitted the data substantially better and resulted in much more differentiated (less correlated) factors than did CFA. Methodologically, we extended ESEM (introducing ESEM-within-CFA models and a hybrid of multiple groups and multiple indicators multiple causes models), evaluating full measurement invariance and latent mean differences over age, gender, and their interaction. Substantively the results showed that women had higher latent scores for all Big Five factors except for Openness and that these gender differences were consistent over the entire life span. Substantial nonlinear age effects led to the rejection of the plaster hypothesis and the maturity principle but did support a newly proposed la dolce vita effect in old age. In later years, individuals become happier (more agreeable and less neurotic), more self-content and self-centered (less extroverted and open), more laid back and satisfied with what they have (less conscientious, open, outgoing and extroverted), and less preoccupied with productivity.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ, UPUK
The aim of the present study was to examine the validity and reliability of metabolic power (P) estimated from locomotor demands during soccer-specific drills. 14 highly-trained soccer players ...performed a soccer-specific circuit with the ball (3×1-min bouts, interspersed with 30-s passive recovery) on 2 different occasions. Locomotor activity was monitored with 4-Hz GPSs, while oxygen update (VO2) was collected with a portable gas analyzer. P was calculated using either net VO2 responses and traditional calorimetry principles (PVO2, W.kg(-1)) or locomotor demands (PGPS, W.kg(-1)). Distance covered into different speed, acceleration and P zones was recorded. While PGPS was 29±10% lower than PVO2 (d<- 3) during the exercise bouts, it was 85±7% lower (d<- 8) during recovery phases. The typical error between PGPS vs. PVO2 was moderate: 19.8%, 90% confidence limits: (18.4;21.6). The correlation between both estimates of P was small: 0.24 (0.14;0.33). Very large day-to-day variations were observed for acceleration, deceleration and > 20 W.kg(-1) distances (all CVs > 50%), while average Po2 and PGPS showed CVs < 10%. ICC ranged from very low- (acceleration and > 20 W.kg(-1) distances) to-very high (PVO2). PGPS largely underestimates the energy demands of soccer-specific drills, especially during the recovery phases. The poor reliability of PGPS >20 W.kg(-1) questions its value for monitoring purposes in soccer.
Classroom context and climate are inherently classroom-level (L2) constructs, but applied researchers sometimes-inappropriately-represent them by student-level (L1) responses in single-level models ...rather than more appropriate multilevel models. Here we focus on important conceptual issues (distinctions between climate and contextual variables; use of classroom L2 rather than student-level L1 measures) and more appropriate multilevel models. To illustrate these issues, we consider the effects of two L2 classroom climate variables and one L2 classroom contextual variable on two L1 student-level outcomes for 2261 students in 128 classes. Through this example, we illustrate how to apply evolving doubly latent multilevel models to (a) evaluate the factor structure of L1 and L2 constructs based on multiple indicators of classroom climate and context measures, (b) control measurement error at L1 and L2, (c) control sampling error in the aggregation of L1 responses to form L2 constructs (the average of student-level responses to form classroom-level constructs), and (d) provide guidelines for appropriate analysis of classroom climate as an L2 construct.
Supplementary materials are available for this article. Go to the publisher's online edition of Educational Psychologist for the following free supplemental resources: Substantive basis of the present investigation and more detailed description of the methodology.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A recent article in the Journal of Management gives a critique of a Bayesian approach to factor analysis proposed in Psychological Methods. This commentary responds to the authors’ critique by ...clarifying key issues, especially the use of priors for residual covariances. A discussion is also presented of cross-loadings and model selection tools. Simulated data are used to illustrate the ideas. A reanalysis of the example used by the authors reveals a superior model overlooked by the authors.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
NEO instruments are widely used to assess Big Five personality factors, but confirmatory factor analyses (CFAs) conducted at the item level do not support their a priori structure due, in part, to ...the overly restrictive CFA assumptions. We demonstrate that exploratory structural equation modeling (ESEM), an integration of CFA and exploratory factor analysis (EFA), overcomes these problems with responses (
N
= 3,390) to the 60-item NEO-Five-Factor Inventory: (a) ESEM fits the data better and results in substantially more differentiated (less correlated) factors than does CFA; (b) tests of gender invariance with the 13-model ESEM taxonomy of full measurement invariance of factor loadings, factor variances-covariances, item uniquenesses, correlated uniquenesses, item intercepts, differential item functioning, and latent means show that women score higher on all NEO Big Five factors; (c) longitudinal analyses support measurement invariance over time and the maturity principle (decreases in Neuroticism and increases in Agreeableness, Openness, and Conscientiousness). Using ESEM, we addressed substantively important questions with broad applicability to personality research that could not be appropriately addressed with the traditional approaches of either EFA or CFA.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ, UPUK
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