Postactivation Performance Enhancement With Maximal Isometric Contraction on Power-Clean Performance Across Multiple Sets

PURPOSE

This study investigated the postactivation performance-enhancement effect of maximal voluntary isometric contraction (MVIC) at the starting position on power-clean performance over a series of contrast sets.

METHODS

Eighteen male (age: 31 [3.7] y, body mass: 76.8 [9.1] kg, height: 175.0 [5.2] cm) and 2 female (age: 27.5 [3.5] y, body mass: 53.3.8 [2.0] kg, height: 158.5 [4.9] cm) resistance-trained individuals performed a contrast postactivation performance-enhancement protocol (isometric contrast training condition [ISO]) consisting of 3 sets of 3 MVICs alternated with 3 power cleans, with an intracontrast rest period of 1 minute. A control protocol consisted of 3 sets of 3 power cleans were performed in a separate session. Barbell velocity during the power clean was measured as an indicator of performance.

RESULTS

A significant time effect was observed for both mean velocity (MV; P < .001) and peak velocity (PV; P = .008). Time × group (P = .415-.444) and group (P = .158-.210) effects showed no significant difference for either MV or PV. However, differences in MV and PV between the corresponding sets of ISO and control condition exceeded the minimum worthwhile change, showing a small to moderate effect (MV: d = 0.38-0.50, PV: d = 0.35-0.50) in favor of ISO. There was no significant difference in rating of perceived exertion between conditions (P = .385, d = 0.22).

CONCLUSION

Power-clean performance was potentiated after 1 minute of rest following 3 repetitions of MVIC across 3 sets. Furthermore, the ISO protocol did not result in greater perception of exertion. These results indicate that coaches may incorporate MVICs as the postactivation performance-enhancement stimulus during contrast training involving the power-clean exercise.

Heart rate variability is reduced in COVID-19 survivors and associated with physical activity and fatigue

Reduced heart rate variability (HRV) and fatigue are common after COVID-19 infection and both are potentially influenced by physical activity (PA). We compared resting HRV, PA from accelerometers and questionnaires, and self-reported fatigue in 41 COVID-19 survivors (~8 months postinfection, 38 ± 17 years) with 41 matched controls. Differences in HRV were observed on acceleration capacity (p = 0.041), deceleration capacity (p = 0.032), high-frequency peak frequency (p = 0.019), absolute low-frequency power (p = 0.042), relative very low-frequency power (p = 0.012), SD2 (from Poincare plot; p = 0.047), and DFA2 (slope of long-term detrended fluctuation analysis; p = 0.004). Fatigue was greater in COVID-19 survivors (p < 0.001) with no differences in PA. Moderate-vigorous physical activity (MVPA) (Standardized Beta = -0.427, p = 0.003) and steps per day (Standardized Beta = -0.402, p = 0.007) were associated with DFA2 in COVID-19 survivors after controlling for age, sex, and body fat percentage. Fatigue was correlated to less MVPA (Spearman's rho = 0.342, p = 0.031) and fewer steps per day (rho = 0.329, p = 0.038) in COVID-19 survivors, and was indirectly linked to HRV through these PA mediators (Estimate = -0.20; p = 0.040). We present a model showing the complex relations between HRV, PA, and fatigue that provides the foundation for strategies to improve outcomes and rehabilitation after COVID-19 infection.

Predicting Total Back Squat Repetitions from Repetition Velocity and Velocity Loss

The purpose of this investigation was to determine if average concentric velocity (ACV) of a single repetition at 70% of one-repetition maximum (1RM), ACV of the first repetition of a set to failure at 70% of 1RM, or the velocity loss during the set could predict the number of repetitions performed in the back squat. Fifty-six resistance-trained individuals participated in the study (male = 41, age = 23 ± 3 yrs, 1RM = 162.0 ± 40.0 kg; female = 15, age = 21 ± 2 yrs, 1RM = 81.5 ± 12.5 kg). After 1RM testing, participants performed single repetition sets with 70% of 1RM and a set to failure with 70% of 1RM. ACV was recorded on all repetitions. Regression model comparisons were performed, and Akaike Information Criteria (AIC) and Standard Error of the Estimate (SEE) were calculated to determine the best model. Neither single repetition ACV at 70% of 1RM (R² = 0.004, p = 0.637) nor velocity loss (R² = 0.011, p = 0.445) were predictive of total repetitions performed in the set to failure. The simple quadratic model using the first repetition of the set to failure (Y=β0+β1XACVFirst+β2Z+ε) was identified as the best and most parsimonious model (R² = 0.259, F = 9.247, p < 0.001) due to the lowest AIC value (311.086). A SEE of 2.21 repetitions was identified with this model. This average error of ~2 repetitions warrants only cautious utilization of this method to predict total repetitions an individual can perform in a set, with additional autoregulatory or individualization strategies being necessary to finalize the training prescription.

Torso kinematic patterns associated with throwing shoulder joint loading and ball velocity in Little League pitchers

The purpose of this study was to investigate the associations between kinematic patterns of the torso segment and shoulder joint loading as well as pitching performance in youth pitchers. Twenty-four Little League pitchers threw fastballs while motion capture and force plate data were collected and ball speed was measured with a radar gun. Three-dimensional torso segment kinematics (absolute angles and angular velocities) and shoulder net joint moments (NJM) and forces were calculated. The time-series kinematic data were used as inputs to a principal components analysis to extract torso movement patterns. Associations between torso movement patterns and discrete peak shoulder NJM, compressive force, and ball speed were investigated with nonparametric correlations. Torso segment motion patterns related to forward flexion, lateral flexion (away from pitching arm), and axial rotation and rotational velocities were associated with shoulder joint kinetics and ball speed. In addition, excessive axial (transverse plane) torso rotation at ball release correlated positively with shoulder joint loads but not ball speed, which may indicate the prospect for decreasing joint kinetics while maintaining pitching performance through targeted interventions. These results provide a deeper understanding about the interrelationships between torso kinematic patterns, shoulder kinetics, and pitching performance.

Gender differences in perceived stress and coping among college students

Background

Many college students register each semester for courses, leading to productive careers and fulfilled lives. During this time, the students have to manage many stressors stemming from academic, personal, and, sometimes, work lives. Students, who lack appropriate stress management skills, may find it difficult to balance these responsibilities.

Objectives

This study examined stress, coping mechanisms, and gender differences in undergraduate students towards the end of the semester.

Design and method

University students (n = 448) enrolled in three different undergraduate exercise science courses were assessed. Two instruments, the Perceived Stress Scale and Brief Cope, were administered during the twelfth week of the semester, four weeks prior to final exams. T-tests were used to detect gender differences for the stress levels and coping strategies.

Results

Overall, females indicated higher levels of stress than their male counterparts. Gender differences were evident in both coping dimensions and individual coping strategies used. Females were found to utilize the emotion-focused coping dimension and endorsed the use of four coping strategies more often than males. These included self-distraction, emotional support, instrumental support, and venting.

Conclusions

This research adds to the existing literature by illuminating the level of perceived stress and different coping strategies used by undergraduate female and male students. In turn, students may need educational interventions to develop effective and healthy coping strategies to last a lifetime. Faculty and other university officials may want to highlight and understand these various factors to protect the students’ wellbeing in their classes.

Technological advances in elite marathon performance

There is scientific and legal controversy about recent technological advances in performance running shoes that reduce the energetic cost of running and may provide a distinct competitive advantage. To better understand the potential performance-enhancing effects of technological advancements in marathon racing shoes, we examined the finishing times and racing shoes of the top 50 male and 50 female runners from the World Marathon Major series in the 2010s before and after the introduction of new Nike shoe models (4%, NEXT%, Alphafly, and other prototypes; herein referred to as "neoteric Nikes"). Data for racing shoes were available for 3,886 of the 3,900 performances recorded at the four annual marathons in Boston, London, Chicago, and New York. In full cohort analyses, marathon finishing times were 2.0% or 2.8 min (138.5 ± 8.1 min vs. 141.3 ± 7.4 min, P < 0.001) faster for male runners wearing neoteric Nikes compared with other shoes. For females, marathon finishing times were 2.6% or 4.3 min (159.1 ± 10.0 min vs. 163.4 ± 10.7 min, P < 0.001) faster for runners wearing neoteric Nikes. In a subset of within-runner changes in marathon performances (males, n = 138; females, n = 101), marathon finishing times improved by 0.8% or 1.2 min for males wearing neoteric Nikes relative to the most recent marathon in which other shoes were worn, and this performance-enhancing effect was greater among females who demonstrated 1.6% or 3.7 min improvement (P = 0.002). Our results demonstrate that marathon performances are substantially faster when world-class athletes, and particularly females, wear marathon racing shoes with technological advancements.NEW & NOTEWORTHY World-class athletes are substantively faster, wearing marathon racing shoes with technological advancements than other shoes when competing in the marathon. Our findings suggest that technological advances in footwear contributed to the recent improvements in marathon finishing times among elite runners and in record-setting marathon performances. This investigation highlights the importance of sports analytics and may have broad implications for the regulation of running footwear during competition.

Impulse-Based Dynamic Strength Index: Considering Time-Dependent Force Expression

ABSTRACT

Haischer, MH, Krzyszkowski, J, Roche, S, and Kipp, K. Impulse-based dynamic strength index: considering time-dependent force expression. J Strength Cond Res 35(5): 1177-1181, 2021-The dynamic strength index (DSI) is a useful tool to assess an athlete's capacity to effectively use maximum strength during dynamic tasks. Although DSI is traditionally calculated based on peak forces, the ability to express force over time (i.e., impulse) is a better predictor of dynamic performance. The purpose of this study was to investigate the association between DSI calculated based on peak force (fDSI) and impulse (iDSI). Nineteen female collegiate lacrosse players performed countermovement jumps (CMJs) and isometric midthigh pulls (IMTPs). Peak force and impulse were extracted from CMJ and IMTP force-time data. Countermovement jump impulse was calculated by integrating force over the concentric movement time, whereas IMTP impulse was calculated by integrating force over the CMJ-matched movement time. Ratios between CMJ and IMTP peak force and impulse were used to calculate fDSI and iDSI, respectively. A moderate positive correlation existed between iDSI and fDSI (ρ = 0.644 [0.283-0.840], p = 0.003). Based on thresholds established in the literature, the 2 indices suggest conflicting training recommendations for 37% of athletes. Because impulse is a better predictor of dynamic performance, iDSI may represent a more valid method for assessing an athlete's capacity to effectively use maximum strength during dynamic tasks. Practitioners and researchers may want to consider augmenting current training and research practices with an impulse-based DSI.

Impact of Cognitive Measures and Sleep on Acute Squat Strength Performance and Perceptual Responses Among Well-Trained Men and Women

ABSTRACT

Haischer, MH, Cooke, DM, Carzoli, JP, Johnson, TK, Shipherd, AM, Zoeller, RF, Whitehurst, M, and Zourdos, MC. Impact of cognitive measures and sleep on acute squat strength performance and perceptual responses among well-trained men and women. J Strength Cond Res 35(2S): S16-S22, 2021-This study assessed the efficacy of currently used assessments for sleep, anxiety, and stress in predicting 1-repetition maximum (1RM) back squat performance. Fifty-three men (age, 23 ± 3 years; body mass, 86.67 ± 13.93 kg; training age, 6.0 ± 2.5 years; 1RM = 163.5 ± 39.5 kg) and 15 women (age, 21 ± 1.5 years; body mass, 63.34 ± 9.6 kg; training age, 4 ± 1.5 years; 1RM = 81.5 ± 12.5 kg) participated. Subjects completed the Daily Analysis of Life Demands for Athletes (DALDA), the revised Competitive State Anxiety Inventory-2 (CSAI-2R), and Oviedo Sleep Questionnaire (OSQ) to evaluate stress, anxiety, and sleep, respectively. Subjects then completed the perceived self-efficacy (PSE) scale, to predict what loads they were 100, 75, and 50% confident that they could lift for a 1RM; then completed 1RM testing with rating of perceived exertion (RPE) and average concentric velocity (ACV) obtained on each attempt. The performance-dependent variable was calculated by subtracting the PSE responses from the actual 1RM (1RM-PSE difference). Bootstrapping with 1,000 replicate samples was used with linear regression to increased robustness of the statistical analyses, and 95% confidence intervals (CIs) were calculated. Hours of sleep was an inverse predictor of ACV (p = 0.014; 95% CI = 0.046 to-0.011) and a positive predictor of RPE (p = 0.005; 95% CI = 0.068-0.342). Furthermore, the hypersomnia subscale of the OSQ was a negative predictor of 1RM-PSE difference at 50% confidence (p = 0.028; 95% CI = -3.507 to -0.528), and CSAI-2R total score was a negative predictor of RPE at 1RM (p = 0.043; 95% CI = -0.041 to -0.003); however, the DALDA did not exhibit any significant relationships. These data highlight the importance of monitoring anxiety and sleep when assessing readiness for maximal strength performance.

Proximity to Failure and Total Repetitions Performed in a Set Influences Accuracy of Intraset Repetitions in Reserve-Based Rating of Perceived Exertion

ABSTRACT

Zourdos, MC, Goldsmith, JA, Helms, ER, Trepeck, C, Halle, JL, Mendez, KM, Cooke, DM, Haischer, MH, Sousa, CA, Klemp, A, and Byrnes, RK. Proximity to failure and total repetitions performed in a set influences accuracy of intraset repetitions in reserve-based rating of perceived exertion. J Strength Cond Res 35(2S): S158-S165, 2021-The aim of this study was to assess the accuracy of predicting repetitions in reserve (RIR) intraset using the RIR-based rating of perceived exertion (RPE) scale. Twenty-five men (age: 25.3 ± 3.3 years, body mass: 89.0 ± 14.7 kg, height: 174.69 ± 6.7 cm, and training age: 4.7 ± 3.2 years) reported to the laboratory. Subjects performed a 1 repetition maximum (1RM) squat followed by one set to failure at 70% of 1RM. During the 70% set, subjects verbally indicated when they believed they were at a 5RPE (5RIR), 7RPE (3RIR), or 9RPE (1RIR), and then continued to failure. The difference between actual repetitions performed and participant-predicted repetitions was calculated as the RIR difference (RIRDIFF). The average load used for the 70% set was 123.10 ± 24.25 kg and the average repetitions performed were 16 ± 4. The RIRDIFF was lower (RPEs were more accurate) closer to failure (RIRDIFF at 9RPE = 2.05 ± 1.73; RIRDIFF at 7RPE = 3.65 ± 2.46; and RIRDIFF at 5RPE = 5.15 ± 2.92 repetitions). There were significant relationships between total repetitions performed and RIRDIFF at 5RPE (r = 0.65, p = 0.001) and 7RPE (r = 0.56, p = 0.004), but not at 9RPE (r = 0.01, p = 0.97). Thus, being farther from failure and performing more repetitions in a set were associated with more inaccurate predictions. Furthermore, a multiple linear regression revealed that more repetitions performed per set was a significant predictor of RIR prediction inaccuracy at the called 5 (p = 0.003) and 7 (p = 0.011) RPEs, while training age (p > 0.05) was not predictive of rating accuracy. These data indicate RIR predictions are improved during low to moderate repetition sets and when there is close proximity to failure.

Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic

Masks are an effective tool in combatting the spread of COVID-19, but some people still resist wearing them and mask-wearing behavior has not been experimentally studied in the United States. To understand the demographics of mask wearers and resistors, and the impact of mandates on mask-wearing behavior, we observed shoppers (n = 9935) entering retail stores during periods of June, July, and August 2020. Approximately 41% of the June sample wore a mask. At that time, the odds of an individual wearing a mask increased significantly with age and was also 1.5x greater for females than males. Additionally, the odds of observing a mask on an urban or suburban shopper were ~4x that for rural areas. Mask mandates enacted in late July and August increased mask-wearing compliance to over 90% in all groups, but a small percentage of resistors remained. Thus, gender, age, and location factor into whether shoppers in the United States wear a mask or face covering voluntarily. Additionally, mask mandates are necessary to increase mask wearing among the public to a level required to mitigate the spread of COVID-19.

RPE vs. Percentage 1RM Loading in Periodized Programs Matched for Sets and Repetitions

Purpose: To investigate differences between rating of perceived exertion (RPE) and percentage one-repetition maximum (1RM) load assignment in resistance-trained males (19-35 years) performing protocols with matched sets and repetitions differentiated by load-assignment. Methods: Participants performed squats then bench press 3x/weeks in a daily undulating format over 8-weeks. Participants were counterbalanced by pre-test 1RM then assigned to percentage 1RM (1RMG, n = 11); load-assignment via percentage 1RMs, or RPE groups (RPEG, n = 10); participant-selected loads to reach target RPE ranges. Ultrasonography determined pre and post-test pectoralis (PMT), and vastus lateralis muscle thickness at 50 (VLMT50) and 70% (VLMT70) femur-length. Results: Bench press (1RMG +9.64 ± 5.36; RPEG + 10.70 ± 3.30 kg), squat (1RMG + 13.91 ± 5.89; RPEG + 17.05 ± 5.44 kg) and their combined-total 1RMs (1RMG + 23.55 ± 10.38; RPEG + 27.75 ± 7.94 kg) increased (p < 0.05) in both groups as did PMT (1RMG + 1.59 ± 1.33; RPEG +1.90 ± 1.91 mm), VLMT50 (1RMG +2.13 ± 1.95; RPEG + 1.85 ± 1.97 mm) and VLMT70 (1RMG + 2.40 ± 2.22; RPEG + 2.31 ± 2.27 mm). Between-group differences were non-significant (p > 0.05). Magnitude-based inferences revealed 79, 57, and 72% chances of mean small effect size (ES) advantages for squat; ES 90% confidence limits (CL) = 0.50 ± 0.63, bench press; ES 90% CL = 0.28 ± 0.73, and combined-total; ES 90% CL = 0.48 ± 0.68 respectively, in RPEG. There were 4, 14, and 6% chances 1RMG had a strength advantage of the same magnitude, and 18, 29, and 22% chances, respectively of trivial differences between groups. Conclusions: Both loading-types are effective. However, RPE-based loading may provide a small 1RM strength advantage in a majority of individuals.