There is no clear agreement regarding the ideal combination of factors needed to optimize postactivation potentiation (PAP) after a conditioning activity. Therefore, a meta-analysis was conducted to evaluate the effects of training status, volume, rest period length, conditioning activity, and gender on power augmentation due to PAP. A total of 141 effect sizes (ESs) for muscular power were obtained from a total of 32 primary studies, which met our criteria of investigating the effects of a heavy preconditioning activity on power in randomized human trials. The mean overall ES for muscle power was 0.38 after a conditioning activity (p < 0.05). Significant differences were found between moderate intensity (60-84%) 1.06 and heavy intensity (>85%) 0.31 (p < 0.05). There were overall significant differences found between single sets 0.24 and multiple sets 0.66 (p < 0.05). Rest periods of 7-10 minutes (0.7) after a conditioning activity resulted in greater ES than 3-7 minutes (0.54), which was greater than rest periods of >10 minutes (0.02) (p < 0.05). Significant differences were found between untrained 0.14 and athletes 0.81 and between trained 0.29 and athletes. The primary findings of this study were that a conditioning activity augmented power output, and these effects increased with training experience, but did not differ significantly between genders. Moreover, potentiation was optimal after multiple (vs. single) sets, performed at moderate intensities, and using moderate rest periods lengths (7-10 minutes).

The primary objective of this investigation was to identify which components of endurance training (e.g., modality, duration, frequency) are detrimental to resistance training outcomes. A meta-analysis of 21 studies was performed with a total of 422 effect sizes (ESs). Criteria for the study included were (a) compare strength training alone to strength plus endurance training (concurrent) or to compare combinations of concurrent training; (b) the outcome measures include at least one measure of strength, power, or hypertrophy; and (c) the data necessary to calculate ESs must be included or available. The mean ES for hypertrophy for strength training was 1.23; for endurance training, it was 0.27; and for concurrent training, it was 0.85, with strength and concurrent training being significantly greater than endurance training only. The mean ES for strength development for strength training was 1.76; for endurance training, it was 0.78; and for concurrent training, it was 1.44. Strength and concurrent training was significantly greater than endurance training. The mean ES for power development for strength training only was 0.91; for endurance training, it was 0.11; and for concurrent training, it was 0.55. Significant differences were found between all the 3 groups. For moderator variables, resistance training concurrently with running, but not cycling, resulted in significant decrements in both hypertrophy and strength. Correlational analysis identified significant negative relationships between frequency (-0.26 to -0.35) and duration (-0.29 to -0.75) of endurance training for hypertrophy, strength, and power. Significant relationships (p < 0.05) between ES for decreased body fat and % maximal heart rate (r = -0.60) were also found. Our results indicate that interference effects of endurance training are a factor of the modality, frequency, and duration of the endurance training selected.

Methods A three-phase double-blind, placebo-and dietcontrolled randomized intervention study was conducted. Phase 1 was an 8-week-periodized resistance-training program; Phase 2 was a 2-week overreaching cycle; and Phase 3 was a 2-week taper. Muscle mass, strength, and power were examined at weeks 0, 4, 8, and 12 to assess the chronic effects of HMB-FA; and assessment of these, as well as cortisol, testosterone, and creatine kinase (cK) was performed at weeks 9 and 10 of the overreaching cycle. Results HMB-FA resulted in increased total strength (bench press, squat, and deadlift combined) over the 12-week training (77.1 ± 18.4 vs. 25.3 ± 22.0 kg, p < 0.001); a greater increase in vertical jump power (991 ± 168 vs. 630 ± 167 W, p < 0.001); and increased lean body mass gain (7.4 ± 4.2 vs. 2.1 ± 6.1 kg, p < 0.001) in HMB-FA-and placebo-supplemented groups, AbstractIntroduction Studies utilizing beta-hydroxy-beta-methylbutyrate (HMB) supplementation in trained populations are limited. no long-term studies utilizing HMB free acid (HMB-FA) have been conducted. therefore, we investigated the effects of 12 weeks of HMB-FA supplementation on skeletal muscle hypertrophy, body composition, strength, and power in trained individuals. We also determined the effects of HMB-FA on muscle damage and performance during an overreaching cycle. respectively. During the overreaching cycle, HMB-FA attenuated increases in cK (−6 ± 91 vs. 277 ± 229 IU/l, p < 0.001) and cortisol (−0.2 ± 2.9 vs. 4.5 ± 1.7 μg/dl, p < 0.003) in the HMB-FA-and placebo-supplemented groups, respectively. Conclusions these results suggest that HMB-FA enhances hypertrophy, strength, and power following chronic resistance training, and prevents decrements in performance following the overreaching.

BackgroundConsumption of moderate amounts of animal-derived protein has been shown to differently influence skeletal muscle hypertrophy during resistance training when compared with nitrogenous and isoenergetic amounts of plant-based protein administered in small to moderate doses. Therefore, the purpose of the study was to determine if the post-exercise consumption of rice protein isolate could increase recovery and elicit adequate changes in body composition compared to equally dosed whey protein isolate if given in large, isocaloric doses.Methods24 college-aged, resistance trained males were recruited for this study. Subjects were randomly and equally divided into two groups, either consuming 48 g of rice or whey protein isolate (isocaloric and isonitrogenous) on training days. Subjects trained 3 days per week for 8 weeks as a part of a daily undulating periodized resistance-training program. The rice and whey protein supplements were consumed immediately following exercise. Ratings of perceived recovery, soreness, and readiness to train were recorded prior to and following the first training session. Ultrasonography determined muscle thickness, dual emission x-ray absorptiometry determined body composition, and bench press and leg press for upper and lower body strength were recorded during weeks 0, 4, and 8. An ANOVA model was used to measure group, time, and group by time interactions. If any main effects were observed, a Tukey post-hoc was employed to locate where differences occurred.ResultsNo detectable differences were present in psychometric scores of perceived recovery, soreness, or readiness to train (p > 0.05). Significant time effects were observed in which lean body mass, muscle mass, strength and power all increased and fat mass decreased; however, no condition by time interactions were observed (p > 0.05).ConclusionBoth whey and rice protein isolate administration post resistance exercise improved indices of body composition and exercise performance; however, there were no differences between the two groups.

Eye-tracking research is increasingly used to supplement usability tests in both commercial and academic practice. However, while there has been research into links between eyetracking metrics and usability problems, this has so far fallen short of establishing a general correlation scheme between the two. Consequently, practitioners are left to make subjective judgements when interpreting eye-tracking data. We address the lack of general guidance by proposing an initial correlation scheme based on data from an exploratory study which aimed to find a wide range of possible correlations between usability problems and eye-tracking patterns. User testing of two websites was conducted and a set of diverse usability problems was extracted from the data; these were then analysed and some were correlated with users' eye-tracking patterns. In addition to this initial correlation scheme, a further finding from this study is that usability problems are connected to not just a single eyetracking pattern, but to a specific sequence of patterns. This sequence of patterns seems to arise from different coping strategies that users develop when a problem is experienced.