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Paul M. Vanderburgh and Ronald E. DeMeersman

The 12-Minute Stationary Cycle Ergometer Test (12MCET) has been developed and validated as an accurate VO2peak prediction test particularly for the injured (7). Prediction is based on body weight and total work done in 12 min at a resistance setting of 2.5 kp (men) and 2.0 kp (women) on the Monark cycle ergometer. In the development of the 12MCET a small number of subjects stated a preference for a higher resistance setting than 2.5 kp. The purpose of this study was to validate the use of the 12MCET with a resistance setting of 3.0 kp for a sample of 30 college-age men. When applied to the 12MCET, use of the 3.0 kp resistance setting overpredicted actual VO2peak by a mean of 175 ml • min−1 (p = .02). We concluded that the use of a 3.0 kp resistance setting for the 12MCET is inappropriate and that any resistance setting other than that prescribed should not be used without proper validation.

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Anne L. Adolph, Maurice R. Puyau, Firoz A. Vohra, Theresa A. Nicklas, Issa F. Zakeri and Nancy F. Butte

Purpose:

Given the unique physical activity (PA) patterns of preschoolers, wearable electronic devices for quantitative assessment of physical activity require validation in this population. Study objective was to validate uniaxial and triaxial accelerometers in preschoolers.

Methods:

Room calorimetry was performed over 3 hours in 64 preschoolers, wearing Actical, Actiheart, and RT3 accelerometers during play, slow, moderate, and fast translocation. Based on activity energy expenditure (AEE) and accelerometer counts, optimal thresholds for PA levels were determined by piecewise linear regression and discrimination boundary analysis.

Results:

Established HR cutoffs in preschoolers for sedentary/light, light/moderate and moderate/vigorous levels were used to define AEE (0.015, 0.054, 0.076 kcal·kg−1·min−1) and PA ratio (PAR; 1.6, 2.9, 3.6) thresholds, and accelerometer thresholds. True positive predictive rates were 77%, 75%, and 76% for sedentary; 63%, 61%, and 65% for light; 34%, 52%, and 49% for moderate; 46%, 46%, and 49% for vigorous levels. Due to low positive predictive rates, we combined moderate and vigorous PA. Classification accuracy was improved overall and for the combined moderate-to-vigorous PA level (69%, 82%, 79%) for Actical, Actiheart, and RT3, respectively.

Conclusion:

Uniaxial and triaxial accelerometers are acceptable devices with similar classification accuracy for sedentary, light, and moderate-to-vigorous levels of PA in preschoolers.

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Jonathan R. Kusins, Ryan Willing, Graham J.W. King and Louis M. Ferreira

A computational elbow joint model was developed with a main goal of providing complimentary data to experimental results. The computational model was developed and validated using an experimental elbow joint phantom consisting of a linked total joint replacement. An established in-vitro motion simulator was used to actively flex/extend the experimental elbow in multiple orientations. Muscle forces predicted by the computational model were similar to the experimental model in 4 out of the 5 orientations with errors less than 7.5 N. Valgus angle kinematics were in agreement with differences less than 2.3°. In addition, changes in radial head length, a clinically relevant condition following elbow reconstruction, were simulated in both models and compared. Both lengthening and shortening of the radial head prosthesis altered muscle forces by less than 3.5 N in both models, and valgus angles agreed within 1°. The computational model proved valuable in cross validation with the experimental model, elucidating important limitations in the in-vitro motion simulator’s controller. With continued development, the computational model can be a complimentary tool to experimental studies by providing additional noninvasive outcome measurements.

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Matthew T. Mahar, Gregory J. Welk, David A. Rowe, Dana J. Crotts and Kerry L. McIver

Background:

The purpose of this study was to develop and cross-validate a regression model to estimate VO2peak from PACER performance in 12- to 14-year-old males and females.

Methods:

A sample of 135 participants had VO2peak measured during a maximal treadmill test and completed the PACER 20-m shuttle run. The sample was randomly split into validation (n = 90) and cross-validation (n = 45) samples. The validation sample was used to develop the regression equation to estimate VO2peak from PACER laps, gender, and body mass.

Results:

The multiple correlation (R) was .66 and standard error of estimate (SEE) was 6.38 ml·kg−1·min−1. Accuracy of the model was confirmed on the cross-validation sample. The regression equation developed on the total sample was: VO2peak = 47.438 + (PACER*0.142) + (Gender[m=1, f=0]*5.134) − (body mass [kg]*0.197), R = .65, SEE = 6.38 ml·kg–1·min–1.

Conclusions:

The model developed in this study was more accurate than the Leger et al. model and allows easy conversion of PACER laps to VO2peak.

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R. Randall Clark, Jacqueline M. Kuta and Robert A. Oppliger

Wisconsin has mandated minimal weight (MW) testing for high school wrestlers. In preparation, six MW predictions were cross-validated on 69 Wisconsin wrestlers (age 15.7±1.1 yrs, height 169.2±6.3 cm, weight 63.3±8.1 kg, percent fat 11.2±4.7%, and MW 58.9±6.9 kg). Minimal weight, defined as fat-free body/.93, determined by hydrostatic weighing (HW) and residual volume using 02 dilution, served as the criterion. Analyzed using repeated-measures ANOVA, statistically significant but clinically small (<1.3 kg) differences were shown in four of six predictions. Lohman 1, Lohman2, and Katch equations appear more appropriate with smaller mean differences, smaller total error, and higher correlations.

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Phillip C. Usera, John T. Foley and Joonkoo Yun

The purpose of this study was to cross-validate skinfold and anthropometric measurements for individuals with Down syndrome (DS). Estimated body fat of 14 individuals with DS and 13 individuals without DS was compared between criterion measurement (BOP POD®) and three prediction equations. Correlations between criterion and field-based tests for non-DS group and DS groups ranged from .81 – .94 and .11 – .54, respectively. Root-Mean-Squared-Error was employed to examine the amount of error on the field-based measurements. A MANOVA indicated significant differences in accuracy between groups for Jackson’s equation and Lohman’s equation. Based on the results, efforts should now be directed toward developing new equations that can assess the body composition of individuals with DS in a clinically feasible way.

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Deborah Kendzierski and Mara S. Morganstein

Structural equation modeling was used to test an extended version of the Kendzierski, Furr, and Schiavoni (1998) Physical Activity Self-Definition Model. A revised model using data from 622 runners fit the data well. Cross-validation indices supported the revised model, and this model also provided a good fit to data from 397 cyclists. Partial invariance was found across activities. In both samples, perceived commitment and perceived ability had direct effects on self-definition, and perceived wanting, perceived trying, and enjoyment had indirect effects. The contribution of perceived ability to self-definition did not differ across activities. Implications concerning the original model, indirect effects, skill salience, and the role of context in self-definition are discussed.

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Jorge Mota, Paula Santos, Sandra Guerra, José C. Ribeiro, José A. Duarte and James F. Sallis

The goal of this study was to validate an adapted version of the “weekly checklist” in a Portuguese population. The validity was assessed by comparing self-reports against the Computer Science and Application, Inc (CSA) monitor. The sample comprised 109 children (boys, n = 42; girls, n = 67), aged 8 to 16 years old. All subjects were volunteers from local schools (Oporto region). The weekly activity checklist was modestly (r = 0.30) but significantly (p < .01) correlated with the CSA. Girls (r = 40; p < .01) had higher correlations than boys (0.28; p < .05). When the values were analyzed by age, excluding the young subjects (<10 years old), the correlation values were slightly higher (r = 0.38; p < .01). The Portuguese version of the “weekly activity checklist” had similar reliability and validity as the original version. The measure appears to have lower validity in 8- and 9-year-old children.

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Jason S. Scibek and Christopher R. Carcia

The purpose of our study was to establish criterion-related validity and repeatability of a shoulder biomechanics testing protocol involving an electromagnetic tracking system (Flock of Birds [FoB]). Eleven subjects completed humeral elevation tasks in the sagittal, scapular, and frontal planes on two occasions. Shoulder kinematics were assessed with a digital inclinometer and the FoB. Intrasession and intersession repeatability for orthopedic angles, and humeral and scapular kinematics ranged from moderate to excellent. Correlation analyses revealed strong relationships between inclinometer and FoB measures of humeral motion, yet considerable mean differences were noted between the measurement devices. Our results validate use of the FoB for measuring humeral kinematics and establish our testing protocol as reliable. We must continue to consider factors that can impact system accuracy and the effects they may have on kinematic descriptions and how data are reported.

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Paul Rowe, Hans van der Mars, Joel Schuldheisz and Susan Fox

This study was conducted to validate the System for Observing Fitness Instruction Time (SOFIT) for measuring physical activity levels of high-school students. Thirty-five students (21 girls and 14 boys from grades 9-12) completed a standardized protocol including lying, sitting, standing, walking, running, curl-ups, and push-ups. Heart rates and Energy Expenditure, that is, oxygen uptake, served as concurrent validity criteria. Results indicate that SOFIT discriminates accurately among high-school students’ sedentary behaviors (i.e., lying down, sitting, standing) and moderate to vigorous physical activity behavior and is recommended for use in research and assessment of physical activity levels in physical education classes for this age group. Implications for use of SOFIT by both researchers and teachers in physical education are described, as well.