This study compared the relative accuracy, similarity, and average error of 7 prediction equations (Brzycki) for estimating 1-repetition maximum (1-RM) performance of older sedentary adults using Hammer Strength Iso-Lateral resistance exercise machines. Data were collected from 49 apparently healthy volunteers (26 males, 23 females) aged 53.55 ± 3.34 (mean ± SD) years. 1-RM scores were obtained for biceps curl, chest press, high latissimus dorsi (lat) pull, incline chest press, leg curl, leg extension, low lat pull, leg press, shoulder press, and triceps extension. Repetitions to fatigue (RTF) for each exercise were determined by assigning each subject a percentage of his or her 1-RM ranging from 50% to 90%. Subjects performed as many repetitions as possible with the predetermined resistance. Predicted 1-RM (1-RMP) was evaluated by relative accuracy (correlation between 1-RM and 1-RMP), similarity (paired t-test between 1-RM and 1-RMP), and average error (sqrt[Σ(1RMP -1RM) 2 /(n -1)]). Relative accuracy, similarity, and average error improved significantly and gender differences were minimal when RTF ≤ 10. Accuracy of prediction equations varied over different resistance exercises. The Mayhew, Ball, Arnold et al. (1992), Epley (1985, and Wathen (1994) formulas evidenced the lowest average error (AE) and highest relative accuracy over the resistance exercises examined; however, both absolute AE and AE expressed as a percent of mean 1-RM were quite high for all formulas over all exercises.

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The purpose of this investigation was to identify a deep-water running (DWR) style that most closely approximates terrestrial running, particularly relative to the lower extremities. Twenty intercollegiate distance runners (women, N = 12; men, N = 8) were videotaped from the right sagittal view while running on a treadmill (TR) and in deep water at 55-60% of their TR VO(2)max using 2 DWR styles: cross-country (CC) and high-knee (HK). Variables of interest were horizontal (X) and vertical (Y) displacement of the knee and ankle, stride rate (SR), VO(2), heart rate (HR), and rating of perceived exertion (RPE). Multivariate omnibus tests revealed statistically significant differences for RPE (p < 0.001). The post hoc pairwise comparisons revealed significant differences between TR and both DWR styles (p < 0.001). The kinematic variables multivariate omnibus tests were found to be statistically significant (p < 0.001 to p < 0.019). The post hoc pairwise comparisons revealed significant differences in SR (p < 0.001) between TR (1.25 +/- 0.08 Hz) and both DWR styles and also between the CC (0.81 +/- 0.08 Hz) and HK (1.14 +/- 0.10 Hz) styles of DWR. The CC style of DWR was found to be similar to TR with respect to linear ankle displacement, whereas the HK style was significantly different from TR in all comparisons made for ankle and knee displacement. The CC style of DWR is recommended as an adjunct to distance running training if the goal is to mimic the specificity of the ankle linear horizontal displacement of land-based running, but the SR will be slower at a comparable percentage of VO(2)max.

The Royal Canadian Mounted Police use the Physical Ability Requirement Evaluation (PARE) for screening applicants. The purposes of this investigation were to identify those field tests of physical fitness that were associated with PARE performance and determine which most accurately classified successful and unsuccessful PARE performers. The participants were 27 female and 21 male volunteers. Testing included measures of aerobic power, anaerobic power, agility, muscular strength, muscular endurance, and body composition. Multiple regression analysis revealed a three-variable model for males (70-lb bench press, standing long jump, and agility) explaining 79% of the variability in PARE time, whereas a one-variable model (agility) explained 43% of the variability for females. Analysis of the classification accuracy of the males' data was prohibited because 91% of the males passed the PARE. Classification accuracy of the females' data, using logistic regression, produced a two-variable model (agility, 1.5-mile endurance run) with 93% overall classification accuracy.