Do the effects last? A comparison between internal and external focus of attention instructions on golf putting accuracy over multiple days.

Background: The role of attentional focus is a well-explored topic in exercise sciences. Studies generally indicate that external focus (EF) enhances motor performance and learning compared with internal focus (IF). However, most studies only included one or two experimental days which limits participants' exposure to the focus conditions. This raises the question of whether the superiority of EF varies over time. Methods: Accordingly, in this pre-registered within-subject study, we examined the effects of focus instructions on golf-putting performance over four days, with 48-72 h between them. On each day, participants performed 15 putts under three instructional conditions: (1) EF, (2) IF, and (3) control, in a randomized and counterbalanced order. Results: We observed trivial differences in performance between conditions but considerable improvements from day 1 to day 4. When using an exploratory analysis, we found that participants performed better under EF and control conditions compared with the IF condition on day 1, but not on subsequent days. Conclusions: Since IF instructions are more commonly used in practice, we speculate that the two other focus conditions were experienced as more novel, potentially accounting for their superiority on Day 1. Nevertheless, our results question the significance of employing EF to enhance performance.

An Integrated Perspective of Effort and Perception of Effort.

Effort and the perception of effort (PE) have been extensively studied across disciplines, resulting in multiple definitions. These inconsistencies block scientific progress by impeding effective communication between and within fields. Here, we present an integrated perspective of effort and PE that is applicable to both physical and cognitive activities. We define effort as the energy utilized to perform an action. This definition can be applied to biological entities performing various voluntary or involuntary activities, irrespective of whether the effort contributes to goal achievement. Then, we define PE as the instantaneous experience of utilizing energy to perform an action. This definition builds on that of effort without conflating it with other subjective experiences. We explore the nature of effort and PE as constructs and variables and highlight key considerations in their measurement. Our integrated perspective aims to facilitate a deeper understanding of these constructs, refine research methodologies, and promote interdisciplinary collaborations.

The relationship between prescribed ratings of perceived exertion and force production in repeated isometric contractions.

Ratings of perceived exertion (RPE) are frequently used to monitor and prescribe exercise intensity. However, studies examining the shape and robustness of how feelings of effort map onto objective outputs are limited and report inconsistent results. To address this, we investigated whether (1) producing isometric forces according to RPE levels reliably leads to differences in force output, (2) if feelings of effort map linearly or non-linearly onto force output, and (3) if this mapping is robust when visual feedback and social facilitation are present. In a counterbalanced repeated measures design, N = 26 participants performed isometric handgrip contractions prescribed by ten levels of the Borg CR-10 scale. They did so either with or without the availability of concurrent visual feedback regarding their force production, and in the presence or absence of another person performing the same task simultaneously. We found that subjects reliably produced different force outputs that corresponded to each RPE level. Furthermore, concurrent visual feedback led to a linearization of force output, while in the absence of feedback, the produced forces could also be described by quadratic and cubic functions. Exploratory post-hoc analyses revealed that participants perceived moderate RPE levels to be more challenging to produce. By shedding light on the dynamic nature of the mapping between RPE and objective performance, our findings provide helpful insights regarding the utility of RPE scales.

The impact of task (un)certainty on repeated grip force production.

Many studies found that in physical tasks, reducing certainty regarding their endpoints hinders performance. However, the impact of reducing certainty regarding other aspects of physical tasks is unknown. Here we manipulated the certainty of the required effort on an unrelated, parallel task (i.e., off-task uncertainty) and examined how it impacts force production in two within-subject experiments (N = 79). In two sessions, subjects completed 20 repetitions composed of maximal forces using a gripper with their dominant hand. Between repetitions, participants applied either submaximal constant or varied grip forces, with their non-dominant arm, matched for total forces across repetitions. While we observed trivial differences in total forces between conditions, under the varied condition, participants produced a steeper decrease in forces, suggesting that off-task uncertainty impacted their effort allocation strategy. We speculate that this pattern can be attributed to cognitive overload and/or changes in motivation stemming from the imposed uncertainty.

Rating of perceived effort but relative to what? A comparison between imposed and self-selected anchors.

PURPOSE: Collecting reliable and valid rating of perceived effort (RPE) data requires properly anchoring the scales' upper limits (i.e., the meaning of 10 on a 0-10 scale). Yet, despite their importance, anchoring procedures remain understudied and theoretically underdeveloped. Here we propose a new task-based anchoring procedure that distinguishes between imposed and self-selected anchors. In the former, researchers impose on participants a specific task as the anchor; in the latter, participants choose the most effortful task experienced or imaginable as the anchor. We compared the impact of these conceptually different anchoring procedures on RPE. METHODS: Twenty-five resistance-trained participants (13 females) attended a familiarization and two randomized experimental sessions. In both experimental sessions, participants performed non-fatiguing and fatiguing isometric maximal voluntary contraction (MVC) protocols with the squat followed by the gripper or vice versa. After each MVC, participants reported their RPE on a 0-10 scale relative to an imposed anchor of the performed task (e.g., gripper MVCs anchored to a gripper MVC) or to a self-selected anchor. RESULTS: In the non-fatiguing condition, imposed anchors yielded greater RPEs than self-selected anchors for both the squat [on average, 9.4 vs. 5.5; Δ(CI95%) = 3.9 (3.2, 4.5)] and gripper [9.4 vs. 3.9; Δ = 5.5 (4.7, 6.3)]. Similar results were observed in the fatiguing condition for both the squat [9.7 vs. 6.9; Δ = 2.8 (2.1, 3.5)] and gripper [9.7 vs. 4.5; Δ = 5.2 (4.3, 5.9)]. CONCLUSIONS: We found large differences in RPE between the two anchors, independent of exercises and fatigue state. These findings provide a basis for further development and refinement of anchoring procedures and highlight the importance of selecting, justifying, and consistently applying the chosen anchors.

Should I Rest or Should I Go Now? A Randomized Cross-Over Trial Comparing Fixed and Self-Selected Rest Durations in High-Intensity Interval Training Cycling Sessions.

BACKGROUND: In high-intensity interval training (HIIT), the rest durations between intervals are commonly prescribed using a fixed approach (e.g., 30 s between intervals). An alternative is the self-selected (SS) approach, in which trainees select their resting durations. Studies comparing the two approaches report mixed results. However, in these studies, trainees in the SS condition rested for as little or as long as they wished, leading to dissimilar total rest durations between conditions. Here, for the first time, we compare the two approaches while controlling for total rest duration. METHODS: Twenty-four amateur adult male cyclists completed a familiarization session, followed by two counterbalanced cycling HIIT sessions. Each session was composed of nine, 30-s intervals, in which the goal was to accumulate as many watts as possible on an SRM ergometer. In the fixed condition, cyclists rested for 90 s between intervals. In the SS condition, cyclists had 720 s (i.e., 8 × 90 s) of rest to allocate in any way they wished. We measured and compared watts, heart rate, electromyography of the knee flexors and extensors, rating of perceived effort and fatigue, perception of autonomy and enjoyment. Additionally, a subsample of ten cyclists completed a retest of the SS condition. RESULTS: With the exception of perception of autonomy, which was higher in the SS condition, outcomes were highly similar in both conditions. For example, the average aggregated differences were: 0.57 (95% CI - 8.94, 10.09) for watts; - 0.85 (95% CI - 2.89, 1.18) for heart rate; and 0.01 (95% CI - 0.29, 0.30) for rating of perceived effort (on a 0-10 scale). Additionally, the retest of the SS condition resulted in a similar rest allocation pattern across the intervals and in similar outcomes. CONCLUSION: Given the similarities in performance, physiological and psychological outcomes between the fixed and SS conditions, both can be equally utilized based on coaches' and cyclists' preferences and training goals.

Perception of Bar Velocity Loss in Resistance Exercises: Accuracy Across Loads and Velocity Loss Thresholds in the Bench Press.

PURPOSE: Velocity-based training is used to prescribe and monitor resistance training based on velocity outputs measured with tracking devices. When tracking devices are unavailable or impractical to use, perceived velocity loss (PVL) can be used as a substitute, assuming sufficient accuracy. Here, we investigated the accuracy of PVL equal to 20% and 40% relative to the first repetition in the bench-press exercise. METHODS: Following a familiarization session, 26 resistance-trained men performed 4 sets of the bench-press exercise using 4 different loads based on their individual load-velocity relationships (∼40%-90% of 1-repetition maximum [1RM]), completed in a randomized order. Participants verbally reported their PVL at 20% and 40% velocity loss during the sets. PVL accuracy was calculated as the absolute difference between the timing of reporting PVL and the actual repetition number corresponding to 20% and 40% velocity loss measured with a linear encoder. RESULTS: Linear mixed-effects model analysis revealed 4 main findings. First, across all conditions, the absolute average PVL error was 1 repetition. Second, the PVL accuracy was not significantly different between the PVL thresholds (ß = 0.16, P = .267). Third, greater accuracy was observed in loads corresponding to the midportion of the individual load-velocity relationships (∼50%-60% 1RM) compared with lighter (<50% 1RM, ß = 0.89, P < .001) and heavier loads (>60% 1RM, 0.63 ≤ ß ≤ 0.84, all P values < .001). Fourth, PVL accuracy decreased with consecutive repetitions (ß = 0.05, P = .017). CONCLUSIONS: PVL can be implemented as a monitoring and prescription method when velocity-tracking devices are impractical or absent.

Seeing Effort: Assessing Coaches' Prediction of the Number of Repetitions in Reserve Before Task-Failure.

BACKGROUND: A key role of resistance training (RT) coaches is to personalize programs based on their trainees' abilities and goals. Specifically, coaches often assess how many repetitions in reserve (RIR) their trainees have until task-failure. Coaches can then modify the number of repetitions assigned per set accordingly. However, coaches' ability to predict the number of RIR is unknown. METHODS: Certified RT coaches (n = 259) were randomly assigned to watch a video of one of eight trainees. The trainees performed two sets of barbell squats and preacher biceps-curls, using 70% or 80% of their 1RM, to task-failure. The coaches predicted trainees' RIR at 33%, 66%, and 90% of the total number of repetitions the trainees completed in each set. We fitted a linear mixed model with various predictors to the prediction errors as the outcomes (i.e., signed and unsigned values of the predicted minus actual repetitions to task-failure). RESULTS: The overall average number of repetitions completed by the trainees was 13.9. The average absolute errors were 4.8, 2.0, and 1.2 repetitions for the 33%, 66%, and 90% time-points, respectively. The absolute prediction error increased for the biceps-curl compared to the squat (1.43, 95% CI [1.13, 1.74]), but decreased for heavier loads (- 1.17, 95% CI [- 2.16, - 0.19]), and in the second set of each exercise (- 1.20, 95% CI [- 1.38, - 1.02]). Surprisingly, coaches' years of experience had a negligible effect on the absolute error (- 0.020, 95% CI [- 0.039, - 0.0007]). Finally, coaches underpredicted the RIR at early time-points but reverted to slight overprediction at later time-points. CONCLUSIONS: Prior coaching experience seems to play a minor role in RIR predictions. However, even short-term exposures to new trainees performing different exercises can substantially improve coaches' RIR predictions.

The isometric horizontal push test correlates with jumping and sprinting performance among athletes and recreationally active controls.

The aim of this study was two-fold: (i) to examine the relationships between force outputs measured in the isometric horizontal push test (IHPT) and athletic performances; (ii) to compare IHPT outputs between football players and recreationally active controls. Thirty-two male subjects (football players, n = 16; university students, n = 16) completed the IHPT, countermovement jump (CMJ), standing long jump (SLJ), 5 m, 10 m and 20 m sprint tests, randomly across two testing sessions. Multivariate linear regression analysis was used to examine the relationships between IHPT outputs and athletic performances by accounting for the subjects' athletic background. An independent sample t-test was used to compare the IHPT outputs between groups. Moderate to very strong linear relationships (r2 range: 0.16-0.56) were found between the IHPT and all athletic performances (all p < .026). Percent variance explained by the IHPT outputs after accounting for groups difference was 16%, 56%, 54%, 48% and 40% for CMJ height, SLJ distance, 5 m, 10 m and 20 m sprint performances, respectively. Compared to controls (6.18 ± 0.89 N/kg), football players (10.09 ± 1.57 N/kg) achieved greater IHPT force outputs (p < .001, Hedges' g = 3.2, large ES). The IHPT is clearly correlated to horizontal and vertical athletic performances and can adequately distinguish between athletes and recreationally active controls based on their IHPT results. Future studies should examine the usefulness of the IHPT as a testing tool informing training prescription and performance monitoring practices.

Are Trainees Lifting Heavy Enough? Self-Selected Loads in Resistance Exercise: A Scoping Review and Exploratory Meta-analysis.

BACKGROUND: Traditionally, the loads in resistance training are prescribed as a percentage of the heaviest load that can be successfully lifted once (i.e., 1 Repetition Maximum [1RM]). An alternative approach is to allow trainees to self-select the training loads. The latter approach has benefits, such as allowing trainees to exercise according to their preferences and negating the need for periodic 1RM tests. However, in order to better understand the utility of the self-selected load prescription approach, there is a need to examine what loads trainees select when given the option to do so. OBJECTIVE: Examine what loads trainees self-select in resistance training sessions as a percentage of their 1RM. DESIGN: Scoping review and exploratory meta-analysis. SEARCH AND INCLUSION: We conducted a systematic literature search with PubMed, Web of Science, and Google Scholar in September 2021. We included studies that (1) were published in English in a peer-reviewed journal or as a MSc or Ph.D. thesis; (2) had healthy trainees complete at least one resistance-training session, composed of at least one set of one exercise in which they selected the loads; (3) trainees completed a 1RM test for the exercises that they selected the loads for. Eighteen studies were included in our main meta-analysis model with 368 participants. RESULTS: Our main model indicated that on average participants select loads equal to 53% of their 1RM (95% credible interval [CI] 49-58%). There was little moderating effect of training experience, age, sex, timing of the 1RM test (before or after the selected load RT session), number of sets, number of repetitions, and lower versus upper body exercises. Participants did tend to select heavier loads when prescribed lower repetitions, and vice versa (logit(yi) = - 0.09 [95% CI - 0.16 to - 0.03]). Note that in most of the analyzed studies, participants received vague instructions regarding how to select the loads, and only completed a single session with the self-selected loads. CONCLUSIONS: Participants selected loads equal to an average of 53% of 1RM across exercises. Lifting such a load coupled with a low-medium number of repetitions (e.g., 5-15) can sufficiently stimulate hypertrophy and increase maximal strength for novices but may not apply for more advanced trainees. Lifting such a load coupled with a higher number of repetitions and approaching or reaching task failure can be sufficient for muscle hypertrophy, but less so for maximal strength development, regardless of trainees' experience. The self-selected load prescription approach may bypass certain limitations of the traditional approach, but requires thought and further research regarding how, for what purposes, and with which populations it should be implemented.

Age Differences in Recovery Rate Following an Aerobic-Based Exercise Protocol Inducing Muscle Damage Among Amateur, Male Athletes.

Purpose: Compare recovery rates between active young (Y) and middle-aged (MA) males up to 48H post aerobically based, exercise-induced muscle damage (EIMD) protocol. A secondary aim was to explore the relationships between changes in indices associated with EIMD and recovery throughout this timeframe. Methods: Twenty-eight Y (n = 14, 26.1 ± 2.9y, 74.5 ± 9.3 kg) and MA (n = 14, 43.6 ± 4.1y, 77.3 ± 12.9 kg) physically active males, completed a 60-min downhill running (DHR) on a treadmill at -10% incline and at 65% of maximal heart rate (HR). Biochemical, biomechanical, psychological, force production and muscle integrity (using MRI diffusion tensor imaging) markers were measured at baseline, immediately-post, and up to 48H post DHR. Results: During the DHR, HR was lower (p < 0.05) in MA compared to Y, but running pace and distance covered were comparable between groups. No statistical or meaningful differences were observed between groups for any of the outcomes. Yet, Significant (p < 0.05) time-effects within each group were observed: markers of muscle damage, cadence and perception of pain increased, while TNF-a, isometric and dynamic force production and stride-length decreased. Creatine-kinase at 24H-post and 48H-post were correlated (p < 0.05, r range = -0.57 to 0.55) with pain perception, stride-length, and cadence at 24H-post and 48H-post. Significant (p < 0.05) correlations were observed between isometric force production at all time-points and IL-6 at 48H-post DHR (r range = -0.62 to (-0.74). Conclusion: Y and MA active male amateur athletes recover in a comparable manner following an EIMD downhill protocol. These results indicate that similar recovery strategies can be used by trainees from both age groups following an aerobic-based EIMD protocol.

Prescribing Intensity in Resistance Training Using Rating of Perceived Effort: A Randomized Controlled Trial.

Introduction: Rating of perceived effort (RPE) scales are used to prescribe intensity in resistance training (RT) in several ways. For instance, trainees can reach a specific RPE value by modifying the number of repetitions, lifted loads, or other training variables. Given the multiple approaches of prescribing intensity using RPE and its growing popularity, we compared the effects of two RPE prescription approaches on adherence rates, body composition, performance and psychological outcomes, in an online RT intervention. Methods: We randomly assigned 57 healthy participants without RT experience (60% females, age range: 18-45) to one of two groups that received two weekly RT sessions using a resistance-band for 8 weeks. In the fixed-repetition group, participants adjusted the band resistance with the goal of completing 10 repetitions and reaching a 7-RPE on a 0-10 scale by the 10th repetition. In the open-repetition group, participants selected their preferred band resistance and completed repetitions until reaching a 7-RPE by the final repetition. We measured body composition, performance, and program satisfaction rates. Results: We assessed 46 participants at post-test, 24 from the fixed-repetition group and 22 from the open-repetition group. We observed non-significant and trivial differences between groups in all outcomes (p > 0.05). We then combined the pre-post change scores of the two groups. We found that adherence rates began at 89% and gradually decreased to 42%. On average, participants increased their fat-free mass [0.3 kg (95% CI: 0.1-0.6)], isometric mid-thigh pull [5.5 kg (95% CI: 0.8-10.4)], isometric knee-extension [2.2 kg (95% CI: 0.8-3.7)], and push-ups [6.3 repetitions (95% CI: 4.5-8.2)]. We observed non-significant and trivial changes in bodyweight, grip-force, and countermovement jump. Participants reported high satisfaction rates with all components of the program. Conclusion: Participants in both groups improved their body composition and physical capacity to a similar extent, and reported comparable satisfaction rates with the programs they followed. Accordingly, either prescription approach can be used to deliver online RT sessions based on personal preferences and logistical constraints. However, since adherences rates declined over the course of the study, future research should test additional strategies aiming to maintain adherence rates.

Longing for a Longitudinal Proxy: Acutely Measured Surface EMG Amplitude is not a Validated Predictor of Muscle Hypertrophy.

Surface electromyography amplitudes are commonly measured in acute sports and exercise science studies to make inferences about muscular strength, performance, and hypertrophic adaptations that may result from different exercises or exercise-related variables. Here, we discuss the presumptive logic and assumptions underlying these inferences, focusing on hypertrophic adaptations for simplicity's sake. We present counter-evidence for each of its premises and discuss evidence both for and against the logical conclusion. Given the limited evidence validating the amplitude of surface electromyograms as a predictor of longitudinal hypertrophic adaptations, coupled with its weak mechanistic foundation, we suggest that acute comparative studies that wish to assess stimulus potency be met with scrutiny.

Accuracy in Predicting Repetitions to Task Failure in Resistance Exercise: A Scoping Review and Exploratory Meta-analysis.

BACKGROUND: Prescribing repetitions relative to task failure is an emerging approach to resistance training. Under this approach, participants terminate the set based on their prediction of the remaining repetitions left to task failure. While this approach holds promise, an important step in its development is to determine how accurate participants are in their predictions. That is, what is the difference between the predicted and actual number of repetitions remaining to task failure, which ideally should be as small as possible. OBJECTIVE: The aim of this study was to examine the accuracy in predicting repetitions to task failure in resistance exercises. DESIGN: Scoping review and exploratory meta-analysis. SEARCH AND INCLUSION: A systematic literature search was conducted in January 2021 using the PubMed, SPORTDiscus, and Google Scholar databases. Inclusion criteria included studies with healthy participants who predicted the number of repetitions they can complete to task failure in various resistance exercises, before or during an ongoing set, which was performed to task failure. Sixteen publications were eligible for inclusion, of which 13 publications covering 12 studies, with a total of 414 participants, were included in our meta-analysis. RESULTS: The main multilevel meta-analysis model including all effects sizes (262 across 12 clusters) revealed that participants tended to underpredict the number of repetitions to task failure by 0.95 repetitions (95% confidence interval [CI] 0.17-1.73), but with considerable heterogeneity (Q(261) = 3060, p < 0.0001, I2 = 97.9%). Meta-regressions showed that prediction accuracy slightly improved when the predictions were made closer to set failure (ß = - 0.025, 95% CI - 0.05 to 0.0014) and when the number of repetitions performed to task failure was lower (≤ 12 repetitions: ß = 0.06, 95% CI 0.04-0.09; > 12 repetitions: ß = 0.47, 95% CI 0.44-0.49). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (ß = - 0.07 repetitions, 95% CI - 0.14 to - 0.005). In contrast, participants' training status did not seem to influence prediction accuracy (ß = - 0.006 repetitions, 95% CI - 0.02 to 0.007) and neither did the implementation of upper or lower body exercises (upper body - lower body = - 0.58 repetitions; 95% CI - 2.32 to 1.16). Furthermore, there was minimal between-participant variation in predictive accuracy (standard deviation 1.45 repetitions, 95% CI 0.99-2.12). CONCLUSIONS: Participants were imperfect in their ability to predict proximity to task failure independent of their training background. It remains to be determined whether the observed degree of inaccuracy should be considered acceptable. Despite this, prediction accuracies can be improved if they are provided closer to task failure, when using heavier loads, or in later sets. To reduce the heterogeneity between studies, future studies should include a clear and detailed account of how task failure was explained to participants and how it was confirmed.

Exploring the acute affective responses to resistance training: A comparison of the predetermined and the estimated repetitions to failure approaches.

BACKGROUND: In resistance-training (RT), the number of repetitions is traditionally prescribed using a predetermined approach (e.g., three sets of 10 repetitions). An emerging alternative is the estimated repetitions to failure (ERF) approach (e.g., terminating sets two repetitions from failure). Despite the importance of affective responses experienced during RT, a comparison between the two approaches on such outcomes is lacking. METHODS: Twenty women (age range: 23-45 years) without RT experience completed estimated one repetition maximum (RM) tests in four exercises. In the next two counterbalanced sessions, participants performed the exercises using 70%1RM. Participants completed ten repetitions in all three sets (predetermined condition) or terminated the sets when perceived to be two repetitions away from task-failure (ERF condition). Primary outcomes were affective-valence, enjoyment, and approach-preference and secondary outcomes were repetition-numbers completed in each exercise. RESULTS: We observed trivial differences in the subjective measures and an approximately even approach-preference split. Under the ERF condition, we observed greater variability in repetition-numbers between participants and across exercises. Specifically, the mean number of repetitions was slightly lower in the chest-press, knee-extension, and lat-pulldown (~1 repetition) but considerably higher in the leg-press (17 vs. 10, p<0.01). CONCLUSIONS: Both approaches led to comparable affective responses and to an approximately even approach preference. Hence, prior to prescribing either approach, coaches should consider trainee's preferences. Moreover, under the ERF condition participants completed a dissimilar number of repetitions across exercises while presumably reaching a similar proximity to task-failure. This finding suggests that ERF allows for better effort regulation between exercises.

Staying physically active during the COVID-19 quarantine: exploring the feasibility of live, online, group training sessions among older adults.

The COVID-19 outbreak has led to recurring quarantines resulting in drastic reductions in physical activity (PA) levels. Given its health benefits, there is a need to explore strategies to increase PA rates during this period. Video-conferencing platforms can be used to deliver live, online, group PA sessions. However, there are only few established PA protocols on how to use such platforms. Hence, the purposes of this study were to (a) design an online PA protocol and (b) explore its feasibility among older adults during a quarantine. A group of exercise specialists developed a PA protocol while accounting for challenges that may arise when using a video-conferencing platform ("Zoom"). A special focus was placed on safety, individualization, and motivational aspects. Then, 31 community dwelling older adults (71.5 ± 4 years) were recruited via social media to follow this protocol twice a week for 8 weeks. Outcome measures included adverse events, adherence rates, and satisfaction with the protocol, its delivery, and technological aspects. Twenty-eight participants completed the protocol. No adverse events occurred, and adherence rates were high (90%). Most participants (97%) indicated they would participate in such a program in the future and highly rated all aspects of the protocol (median score >6 in 1-7 Likert scales). The PA protocol delivered live via a video-conferencing platform was found to be safe and feasible with this cohort. It can therefore be implemented in practice, and in future studies planning to utilize home-based PA sessions for older adults.

Perception of changes in bar velocity as a resistance training monitoring tool for athletes.

PURPOSE: To investigate if perception of changes in bar velocity (PCV) can be used as a substitute for velocity tracking devices commonly used to monitor resistance-exercises. METHODS: Twenty-one professional male soccer athletes (21±4 years) first went through a load-power profile assessment to determine their optimal power load in the back-squat. In the next three experimental sessions, athletes completed four sets of six repetitions loaded with optimal power load. Starting from the second repetition, athletes reported their PCV of each repetition as a percentage of the first repetition. Accuracy of PCV was calculated as the absolute difference between PCV and the actual percentage change from the first repetition in bar velocity measured with a linear-encoder. The second and fourth sessions served as the pre- and post-intervention sessions, in which athletes received no feedback about their PCV accuracy. The third session served as the intervention session, in which athletes received verbal and visual feedback about their PCV accuracy levels after each set. RESULTS: The estimated accuracy of PCV decreased from an average error of 7% in the pre-intervention to an average error of 4.7% in the post-intervention session (95% confidence levels of difference: 1.5, 3.0). CONCLUSION: Athletes with velocity based training experience begin with a reasonable PCV accuracy rates which can be meaningfully improved after a single session that includes accuracy feedback. When velocity tracking devices are impractical or absent, PCV can be implemented as a resistance training monitoring tool.

The effect of self-selecting the number of repetitions on motor performance and psychological outcomes.

In resistance-training, the number of repetitions can be either fixed and predetermined (e.g., 3 sets of 10 repetitions), or selected by the trainee during ongoing sets (e.g., 3 sets of 8-12 repetitions). The first approach is more goal-focused while the latter is more autonomy-focused. Here we compared these two approaches in motor performance and psychological outcomes. Nineteen resistance-trained participants (10-males) first completed one repetition-maximum (RM) tests in the barbell-squat and bench-press, and were familiarized with the isometric mid-thigh pull (IMTP). In the next two counterbalanced sessions, participants completed two sets of the squat and bench-press using 70%1RM, and two sets of the IMTP. In the predetermined session, participants completed 10 repetitions in all sets, and in the self-selected session, participants chose how many repetitions to complete out of an 8-12 range. Bar-velocity was measured in the squat and bench-press, and force production in the IMTP. Enjoyment, perceived-autonomy, and approach-preferences were collected post-sessions. We observed comparable bar-velocity, force production, and enjoyment in both conditions (all BF01 > 2.1), and an even approach-preferences split. However, in the self-selected condition, participants demonstrated considerable variability in the number of repetitions and reported greater perceived-autonomy. Given the similarities between approaches, both can be used with this cohort based on their personal-preference.

How One Feels During Resistance Exercises: A Repetition-by-Repetition Analysis Across Exercises and Loads.

CONTEXT: The Feeling Scale (FS) is a unique and underexplored scale in sport sciences that measures affective valence. The FS has the potential to be used in athletic environments as a monitoring and prescription tool. PURPOSE: To examine whether FS ratings, as measured on a repetition-by-repetition basis, can predict proximity to task failure and bar velocity across different exercises and loads. METHODS: On the first day, 20 trained participants (10 females) completed 1-repetition-maximum (1-RM) tests in the barbell bench and squat exercises and were introduced to the FS. In the following 3 sessions, participants completed 3 sets to task failure with either (1) 70% 1-RM bench press, (2) 70% 1-RM squat (squat-70%), or (3) 80% 1-RM squat (squat-80%). Sessions were completed in a randomized, counterbalanced order. After every completed repetition, participants verbally reported their FS ratings. Bar velocity was measured via a linear position transducer. RESULTS: FS ratings predicted failure proximity and bar velocity in all 3 conditions (P < .001, R2 .66-.85). Based on the analysis, which included over 2400 repetitions, a reduction of 1 unit in the FS corresponded to approaching task failure by 14%, 11%, and 11%, and to a reduction in bar velocity of 10%, 4%, and 3%, in the bench, squat-70%, and squat-80%, respectively. CONCLUSION: This is the first study to investigate whether the FS can be used in resistance-training environments among resistance-trained participants on a repetition-by-repetition basis. The results indicate that the FS can be used to monitor and prescribe resistance training and that its benefits should be further explored.

Barbell Hip-Thrust Exercise: Test-Retest Reliability and Correlation With Isokinetic Performance.

ABSTRACT: Dello Iacono, A, Padulo, J, Beslija, T, and Halperin, I. Barbell hip-thrust exercise: Test-retest reliability and correlation with isokinetic performance. J Strength Cond Res 35(3): 659-667, 2021-The barbell hip-thrust (BHT) exercise is growing in popularity as evident by the large increase in research outputs investigating its utility as a training intervention and a testing tool. The aim of this study was to examine the test-retest reliability of the BHT and its correlation with isokinetic performance. Test-retest reliability was established by correlating the peak force and power outcomes measured with the BHT force-velocity profile test of 20 handball athletes on 2 separate days. The peak force and power measured with the BHT force-velocity profile test of 49 handball athletes were correlated with peak concentric force of the knee flexors and hip extensors measured with an isokinetic device at 2 different velocities (60-180°·s-1). The correlation between the isokinetic testing scores and the BHT force-velocity profile tests were moderate to large (Pearson r ranges: 0.45-0.86, all p values <0.001). Test-retest reliability of the BHT force-velocity profile was very high as shown with intraclass correlations of 0.94 and 0.99 for peak force and 0.97 and 0.99 for peak power measures. The BHT force-velocity profile can serve as a tentative substitute in cases that athletes do not have access to an isokinetic device, given the moderate to large correlations between them. Moreover, the BHT force-velocity profile was shown to be very reliable, thus providing coaches and scientists a range of day-to-day performance variability in this exercise.