Influence of Movement Velocity on Accuracy of Estimated Repetitions to Failure in Resistance-Trained Men

A Comparison of Subjective Estimations and Objective Velocities at Quantifying Proximity to Failure for the Bench Press in Resistance-Trained Men and Women

ABSTRACT

Hickmott, LM, Butcher, SJ, and Chilibeck, PD. A comparison of subjective estimations and objective velocities at quantifying proximity to failure for the bench press in resistance-trained men and women. J Strength Cond Res 38(7): 1206-1212, 2024-The purpose of this study was to compare the accuracy of quantifying repetitions in reserve (RIR) in the bench press among 18 men and 18 women between 2 conditions: (a) subjective estimations and (b) objective velocities. Subjects performed 4 sessions over 10 days: (a) 1 repetition maximum (1RM) test; (b) repetition-to-failure test at 80% of 1RM; (c) 3 sets to failure at 80% of 1RM; and (d) 3 sets to failure at 75, 80, and 85% of 1RM. During sessions 2, 3, and 4, subjects verbally stated their perceived 4 and 2 RIR intraset, whereas average concentric velocity was recorded on all repetitions. The dependent variable for the subjective estimations condition was the difference between the actual number of RIR and the subject's subjective estimated number of RIR at the verbally stated 4 and 2 RIR. The dependent variable for the objective velocities condition was the difference between the actual number of RIR and the number of RIR calculated from the subject's baseline individualized last repetition average concentric velocity-RIR profile. Significance was set at p ≤ 0.05. Sessions 3 and 4 had significant ( p < 0.001) condition × set and condition × load interactions, respectively, at both 4 and 2 RIR. Objective velocities were significantly more accurate than subjective estimations on set 1 and set 2 at both RIRs during session 3 and for 75 and 80% of 1RM at both RIRs during session 4. Objective velocities exhibit significantly greater accuracy than subjective estimations at quantifying RIR during initial sets and lower loads.

Feasibility and Usefulness of Repetitions-In-Reserve Scales for Selecting Exercise Intensity: A Scoping Review

The intensity of resistance training (RT) exercise is an important consideration for determining relevant health and performance-related outcomes. Yet, current objective exercise intensity measures present concerns in terms of viability or cost. In response to these concerns, repetition-in-reserve (RIR) scales may represent an adequate method of measuring and regulating intensity. However, no recent review has focused on how RIR scales have been used for this purpose in prior research. We prepared the present scoping review to analyze the feasibility and usefulness of RIR scales in selecting RT intensity. We conducted a systematic search in PubMed, SPORTDiscus, PsycINFO, and ClinicalTrials.gov databases (last search date April 2023) for experimental and non-experimental studies that utilized an RIR scale to measure proximity to failure in RT activities with apparently healthy individuals of any age. We qualitatively analyzed 31 studies (N = 855 mostly male adult participants) published between 2012-2023. RIR scales appeared to be contextually feasible and useful in prescribing and adjusting RT intensity. The most common trend in this research was to prescribe a target RIR and adjust the exercise load for a desired proximity to muscle failure. Additionally, when measuring proximity to failure as an outcome of interest, the literature suggests that the RIR prediction should be made close to task failure to increase its accuracy. Future research should further explore the impact of sex, RT experience, exercise selection, and muscle conditioning on the overall RIR approach.

Accuracy of Intraset Repetitions-in-Reserve Predictions During the Bench Press Exercise in Resistance-Trained Male and Female Subjects

ABSTRACT

Refalo, MC, Remmert, JF, Pelland, JC, Robinson, ZP, Zourdos, MC, Hamilton, DL, Fyfe, JJ, and Helms, ER. Accuracy of intraset repetitions-in-reserve predictions during the bench press exercise in resistance-trained male and female subjects. J Strength Cond Res 38(3): e78-e85, 2024-This study assessed the accuracy of intraset repetitions-in-reserve (RIR) predictions to provide evidence for the efficacy of RIR prescription as a set termination method to inform proximity to failure during resistance training (RT). Twenty-four resistance trained male ( n = 12) and female ( n = 12) subjects completed 2 experimental sessions involving 2 sets performed to momentary muscular failure (barbell bench press exercise) with 75% of 1 repetition maximum (1RM), whereby subjects verbally indicated when they perceived to had reached either 1 RIR or 3 RIR. The difference between the predicted RIR and the actual RIR was defined as the "RIR accuracy" and was quantified as both raw (i.e., direction of error) and absolute (i.e., magnitude of error) values. High raw and absolute mean RIR accuracy (-0.17 ± 1.00 and 0.65 ± 0.78 repetitions, respectively) for 1-RIR and 3-RIR predictions were observed (including all sets and sessions completed). We identified statistical equivalence (equivalence range of ±1 repetition, thus no level of statistical significance was set) in raw and absolute RIR accuracy between (a) 1-RIR and 3-RIR predictions, (b) set 1 and set 2, and (c) session 1 and session 2. No evidence of a relationship was found between RIR accuracy and biological sex, years of RT experience, or relative bench press strength. Overall, resistance-trained individuals are capable of high absolute RIR accuracy when predicting 1 and 3 RIR on the barbell bench press exercise, with a minor tendency for underprediction. Thus, RIR prescriptions may be used in research and practice to inform the proximity to failure achieved upon set termination.

Effect of Blood Flow Restriction during the Rest Periods of Squats on Accuracy of Estimated Repetitions to Failure

This study investigated the impact of resistance training with blood flow restriction during rest (BFRrest) on the accuracy of estimated repetitions to failure (ERF). It also explored associations between error in ERF and mean concentric velocity (MCV) along with physiological responses. In a randomised cross-over study, 18 male trainers (23.4 ± 2.7 years) performed three sets of squats at 70% of their one-repetition maximum until failure. One session integrated BFRrest, while another employed traditional passive inter-set rest (TRAD) during the 3 min inter-set rest intervals. Cardiorespiratory and metabolic measures were taken in the inter-set recovery periods. The results revealed no significant differences between BFRrest and TRAD in terms of ERF and error in ERF. A notable set effect for ERF was observed, with a greater ERF during set 1 compared to sets 2 and 3 (p < 0.001). Additionally, a lower error in ERF was observed during sets 2 and 3 compared to set 1 (p < 0.001). Error in ERF were strongly associated with the respiratory exchange ratio, and moderately associated with end-tidal carbon dioxide partial pressure, carbon dioxide output, and MCV variables. Notably, the precision of ERF seems to be predominantly influenced by indicators of physiological stress rather than the incorporation of BFRrest.

The velocity of resistance exercise does not accurately assess repetitions-in-reserve

This study assessed the reliability of mean concentric bar velocity from 3- to 0-repetitions in reserve (RIR) across four sets in different exercises (bench press and prone row) and with different loads (60 and 80% 1-repetition maximum; 1RM). Whether velocity values from set one could be used to predict RIR in subsequent sets was also examined. Twenty recreationally active males performed baseline 1RM testing before two randomised sessions of four sets to failure with 60 or 80% 1RM. A linear position transducer measured mean concentric velocity of repetitions, and the velocity associated with each RIR value up to 0-RIR. For both exercises, velocity decreased between each repetition from 3- to 0-RIR (p ≤ 0.010). Mean concentric velocity of RIR values was not reliable across sets in the bench press (mean intraclass correlation coefficient [ICC] = 0.40, mean coefficient of variation [CV] = 21.3%), despite no significant between-set differences (p = 0.530). Better reliability was noted in the prone row (mean ICC = 0.80, mean CV = 6.1%), but velocity declined by 0.019-0.027 m·s-1 (p = 0.032) between sets. Mean concentric velocity was 0.050-0.058 m·s-1 faster in both exercises with 60% than 80% 1RM with (p < 0.001). At the individual level, the velocity of specific RIR values from set one accurately predicted RIR from 5- to 0-RIR for 30.9% of repetitions in subsequent sets. These findings suggest that velocity of specific RIR values vary across exercises, loads and sets. As velocity-based RIR estimates were not accurate for 69.1% of repetitions, alternative methods to should be considered for autoregulating of resistance exercise in recreationally active individuals.

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.

Methods for Controlling and Reporting Resistance Training Proximity to Failure: Current Issues and Future Directions

Resistance training variables such as volume, load, and frequency are well defined. However, the variable proximity to failure does not have a consistent quantification method, despite being defined as the number of repetitions in reserve (RIR) upon completion of a resistance training set. Further, there is between-study variability in the definition of failure itself. Studies have defined failure as momentary (inability to complete the concentric phase despite maximal effort), volitional (self-termination), or have provided no working definition. Methods to quantify proximity to failure include percentage-based prescription, repetition maximum zone training, velocity loss, and self-reported RIR; each with positives and negatives. Specifically, applying percentage-based prescriptions across a group may lead to a wide range of per-set RIR owing to interindividual differences in repetitions performed at specific percentages of 1 repetition maximum. Velocity loss is an objective method; however, the relationship between velocity loss and RIR varies set-to-set, across loading ranges, and between exercises. Self-reported RIR is inherently individualized; however, its subjectivity can lead to inaccuracy. Further, many studies, regardless of quantification method, do not report RIR. Consequently, it is difficult to make specific recommendations for per-set proximity to failure to maximize hypertrophy and strength. Therefore, this review aims to discuss the strengths and weaknesses of the current proximity to failure quantification methods. Further, we propose future directions for researchers and practitioners to quantify proximity to failure, including implementation of absolute velocity stops using individual average concentric velocity/RIR relationships. Finally, we provide guidance for reporting self-reported RIR regardless of the quantification method.

The Influence of Muscular Strength and Local Muscular Endurance on Accuracy of Estimated Repetitions to Failure in Resistance-Trained Males

This study investigated whether muscular strength and local muscular endurance (LME) influences accuracy of estimated repetitions to failure (ERF) during resistance exercise. Twenty resistance-trained males (age 26.3 ± 6.9 years) completed five sets of 10 repetitions at 70% 1RM for the bench press and squat. Following the 10th repetition of each set, participants reported ERF and then continued to concentric failure. Participants were separated into one of two groups based on muscular strength and LME. There were no significant differences between strength groups for error in ERF, ERF, and actual repetitions to failure (ARF). High-LME compared to Low-LME had greater ERF for all sets of bench press (p < 0.05) and two sets of squat (p < 0.05). Greater ARF was observed in High-LME for two of five sets for bench press (p < 0.05) and squat (p < 0.05). High-LME had greater error in ERF for bench press set 1 (p < 0.01) and set 4 (p = 0.04), while for set 1 only for squat (p = 0.01). Findings indicate that LME influences accuracy of ERF during the initial set of bench press and squat as well as a latter set for the bench press. Future studies with larger sample sizes are warranted to explore whether LME affects accuracy of ERF across multiple sets.

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 (β =  - 0.025, 95% CI - 0.05 to 0.0014) and when the number of repetitions performed to task failure was lower (≤ 12 repetitions: β = 0.06, 95% CI 0.04-0.09; > 12 repetitions: β = 0.47, 95% CI 0.44-0.49). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (β =  - 0.07 repetitions, 95% CI - 0.14 to - 0.005). In contrast, participants' training status did not seem to influence prediction accuracy (β =  - 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.

Effect of 10 sets versus 5 sets of resistance training on muscular endurance

BACKGROUND

A paucity of research exists examining whether resistance training with a greater number of sets per exercise enhances the development of muscular endurance. The aim of this study was to investigate the effects of ten sets versus five sets of resistance training on muscle endurance.

METHODS

Fifteen healthy males (age 23.7 ± 4.6 y) with at least 1 year resistance training experience were randomly assigned to 6 weeks of 10 sets (10-SET) or 5 sets (5-SET) of 10 repetitions at 60-80% one-repetition maximum (1RM) for specific compound resistance exercises with rest intervals between sets of 60-90 s and 60 s between exercises, performed 3 times per week. Relative muscle endurance test was assessed via maximal repetitions using 70% 1RM for the bench press, lat pulldown and leg press.

RESULTS

There was a significant increase in the number of repetitions to failure in the muscle endurance test for the leg press in 10-SET (40.9%, p = 0.04) and 5-SET (27.9%; p = 0.03), although no statistical differences between groups in the post-intervention results. Both groups increased volume-load in the muscle endurance test for the bench press (≥14.3%, p<0.05) and leg press (≥36.7%, p<0.05), but there were no statistical differences between groups in the post-intervention results.

CONCLUSIONS

Findings suggest that performing 10 sets compared to 5 sets of resistance training does not enhance the development of relative muscle endurance. The volume-load accrued within an individual set rather than across sets may be of greater importance when targeting muscular endurance.