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

Estimating repetitions in reserve through movement velocity: Applicability across bench press exercise modes and sexes

This study explored the accuracy of using the relationship between repetitions in reserve (RIR) and mean velocity (MV) to predict proximity to failure in bench press exercises across two modes (Smith machine and free-weight) and sexes (men and women). Twenty-eight recreationally trained individuals completed two sessions of each exercise mode, with sets performed to failure at 65% and 75% of one-repetition maximum. Individualized RIR-MV relationships showed a higher goodness-of-fit for the Smith machine compared to the free-weight bench press (R2 = 0.79-0.87 vs. 0.41-0.78), without significant sex differences (p = 0.880). MV values were mostly similar between exercise modes across different RIRs (p > 0.077), but men demonstrated higher MV values than women for RIR 5-1 (p ≤ 0.013). Individualized RIR-MV relationships were more accurate at estimating RIR 5 at 65%1RM in subsequent sessions than generalized RIR-MV relationships (absolute errors = 0.64-1.36 vs. 1.25-2.00 repetitions; p < 0.001), regardless of sex. However, the prediction accuracy was similar for both relationships at RIRs 2 and 0 (absolute errors ≤ 1 repetition; p ≥ 0.164). These results suggest that RIR-MV relationships can effectively estimate proximity to failure across exercise modes and sexes, with individualized relationships offering greater accuracy.

A practical framework for the design of resistance exercise interventions in oncology research settings-a narrative review

Resistance exercise (RE) has been demonstrated to result in a myriad of benefits for individuals treated for cancer, including improvements in muscle mass, strength, physical function, and quality of life. Though this has resulted in the development of recommendations for RE in cancer management from various international governing bodies, there is also increasing recognition of the need to improve the design of RE interventions in oncology. The design and execution of RE trials are notoriously complex, attempting to account for numerous cancer/treatment related symptoms/side effects. Further, the design of exercise trials in oncology also present numerous logistical challenges, particularly those that are scaled for effectiveness, where multi-site trials with numerous exercise facilities are almost a necessity. As such, this review paper highlights these considerations, and takes evidence from relevant areas (RE trials/recommendations in oncology, older adults, and other clinical populations), and provide a practical framework for consideration in the design and delivery of RE trials. Ultimately, the purpose of this framework is to provide suggestions for researchers on how to design/conduct RE trials for individuals with cancer, rather than synthesizing evidence for guidelines/recommendations on the optimal RE dose/program.

Acute Responses of Low-Load Resistance Exercise with Blood Flow Restriction

Blood flow restriction (BFR) is a popular resistance exercise technique purported to increase metabolic stress and augment training adaptations over time. However, short-term use may lead to acute neuromuscular fatigue and higher exertion ratings. Objective: The purpose of the current study was to examine acute physiological responses to low-load resistance exercise utilizing BFR compared to higher-load, non-BFR resistance exercise. Methods: Recreationally trained males (n = 6) and females (n = 7) (mean ± standard deviation, age: 20 ± 1 yrs.; height: 172 ± 8 cm; weight: 73 ± 11 kg; BMI: 24.4 ± 2.2 kg·m-2; training experience: 4 ± 2 yrs.) had limb occlusion pressure determined (50%; right leg: 118 ± 11 mmHg; left leg: 121 ± 13 mmHg) using an automated, self-inflating cuff system during baseline testing. In subsequent sessions, using a randomized, cross-over design, participants completed one of two experimental conditions: (1) Low-load + BFR and (2) High load + non-BFR. In both conditions, participants completed one set of back squats at either 30% (BFR) or 60% (non-BFR) of an estimated 1RM for a max of 30 repetitions, followed by three additional sets with the same loads and a target of 15 repetitions per set. Blood lactate and countermovement jump (CMJ) height were measured pre- and post-back squat. Ratings of perceived exertion (RPE) were assessed following each set. Results: When collapsed across all sets, participants completed significantly more total repetitions in the BFR condition compared to non-BFR (75.0 ± 0.0 vs. 68.23 ± 9.27 reps; p = 0.015; ES: 1.03), but a lower training load volume (2380 ± 728 vs. 4756 ± 1538 kg; p < 0.001; ES: 1.97). There was a significant time-by-condition interaction (p < 0.001), with a greater increase in blood lactate occurring from baseline to post-back squat in the non-BFR condition (11.61 mmol/L, 95%CI: 9.93, 13.28 mmol/L) compared to BFR (5.98 mmol/L, 95%CI: 4.30, 7.65 mmol/L). There was another significant time-by-condition interaction (p = 0.043), with a greater reduction in CMJ occurring in the non-BFR condition (-6.01, 95%CI: -9.14, -2.88 cm; p < 0.001) compared to BFR (-1.50, 95%CI: -1.50, 4.51 cm; p = 0.312). Conclusions: Utilizing a low-load BFR protocol may allow for a higher training volume, yet lower metabolic stress and reduce neuromuscular fatigue compared to lifting at a higher load without the use of BFR.

The effects of resistance training to near volitional failure on motor unit recruitment during neuromuscular fatigue

Background

It is unclear whether chronically training close to volitional failure influences motor unit recruitment strategies during fatigue.

Purpose

We compared resistance training to near volitional failure vs. non-failure on individual motor unit action potential amplitude (MUAP) and surface electromyographic excitation (sEMG) during fatiguing contractions.

Methods

Nineteen resistance-trained adults (11 males, 8 females) underwent 5 weeks (3×/week) of either low repetitions-in-reserve (RIR; 0-1 RIR) or high RIR training (4-6 RIR). Before and after the intervention, participants performed isometric contractions of the knee extensors at 30% of maximal peak torque until exhaustion while vastus lateralis sEMG signals were recorded and later decomposed. MUAP and sEMG excitation for the vastus lateralis were quantified at the beginning, middle, and end of the fatigue assessment.

Results

Both training groups improved time-to-task failure (mean change = 43.3 s, 24.0%), with no significant differences between low and high RIR training groups (low RIR = 28.7%, high RIR = 19.4%). Our fatigue assessment revealed reduced isometric torque steadiness and increased MUAP amplitude and sEMG excitation during the fatiguing task, but these changes were consistent between groups.

Conclusion

Both low and high RIR training improved time-to-task failure, but resulted in comparable motor unit recruitment during fatiguing contractions. Our findings indicate that both low and high RIR training can be used to enhance fatiguability among previously resistance-trained adults.

A Survey of Resistance Training Practices Among Physique Competitors During Peak Week

ABSTRACT

Homer, KA, Cross, MR, and Helms, ER. A survey of resistance training practices among physique competitors during peak week. J Strength Cond Res 38(10): 1745-1752, 2024-Physique athletes are ranked by their on-stage presentation of muscle size, proportionality, and leanness. To acutely maximize muscle size, competitors manipulate resistance training (RT) variables in the days before the contest, commonly referred to as peak week (PW). Resistance training manipulations during PW may act synergistically with nutrition strategies such as carbohydrate loading. However, because little information exists on changes made to RT during PW, the purpose of this research was to determine the current practices of physique athletes and whether competitor characteristics were predictive of the RT variables manipulated. A total of 104 responses to the RT section of a survey on PW nutrition and training were analyzed through a series of multiple logistic regression models to examine the relationship between RT manipulations and competitor characteristics. Furthermore, to determine the magnitude of differences between PW and the week before PW (WBPW) for these variables, a McNemar-Bowker test, paired t-tests, and Wilcoxon signed-rank tests were conducted for nominal, continuous, and discrete outcomes, respectively. For all statistical analyses, p <0.05 was deemed significant. Competitors generally adjusted RT in a variety of ways, where proximity-to-failure was the most frequently manipulated and training frequency was the least; however, no competitor characteristic predicted any of the RT variables manipulated. Within those who manipulated RT variables during PW, frequency, volume, and intensity decreased while repetition ranges of compound exercises increased, empirically confirming that competitors seek to reduce training stress during PW. Such findings can be incorporated in future experimental designs examining the efficacy of peaking strategies to enhance the generalizability of results.

Exploring the Dose-Response Relationship Between Estimated Resistance Training Proximity to Failure, Strength Gain, and Muscle Hypertrophy: A Series of Meta-Regressions

BACKGROUND

The proximity to failure in which sets are terminated has gained attention in the scientific literature as a potentially key resistance training variable. Multiple meta-analyses have directly (i.e., failure versus not to failure) or indirectly (e.g., velocity loss, alternative set structures) evaluated the effect of proximity to failure on strength and muscle hypertrophy outcomes categorically; however, the dose-response effects of proximity to failure have not been analyzed collectively in a continuous manner.

OBJECTIVE

To meta-analyze the aforementioned areas of relevant research, proximity to failure was quantified as the number of repetitions in reserve (RIR). Importantly, the RIR associated with each effect in the analysis was estimated on the basis of the available descriptions of the training interventions in each study. Data were extracted and a series of exploratory multilevel meta-regressions were performed for outcomes related to both strength and muscle hypertrophy. A range of sensitivity analyses were also performed. All models were adjusted for the effects of load, method of volume equating, duration of intervention, and training status.

RESULTS

The best fit models for both strength and muscle hypertrophy outcomes demonstrated modest quality of overall fit. In all of the best-fit models for strength, the confidence intervals of the marginal slopes for estimated RIR contained a null point estimate, indicating a negligible relationship with strength gains. However, in all of the best-fit models for muscle hypertrophy, the marginal slopes for estimated RIR were negative and their confidence intervals did not contain a null point estimate, indicating that changes in muscle size increased as sets were terminated closer to failure.

CONCLUSIONS

The dose-response relationship between proximity to failure and strength gain appears to differ from the relationship with muscle hypertrophy, with only the latter being meaningfully influenced by RIR. Strength gains were similar across a wide range of RIR, while muscle hypertrophy improves as sets are terminated closer to failure. Considering the RIR estimation procedures used, however, the exact relationship between RIR and muscle hypertrophy and strength remains unclear. Researchers and practitioners should be aware that optimal proximity to failure may differ between strength and muscle hypertrophy outcomes, but caution is warranted when interpreting the present analysis due to its exploratory nature. Future studies deliberately designed to explore the continuous nature of the dose-response effects of proximity to failure in large samples should be considered.

Enhancing lower limb and core muscle activation with blood flow restriction training: a randomized crossover study on high-intensity squat exercises

Objective

The primary objective of this study was to assess the impact of high-intensity deep squat training integrated with various blood flow restriction (BFR) modalities on the activation of lower limb and core muscles.

Methods

A randomized, self-controlled crossover experimental design was employed with 12 participants. The exercise protocol consisted of squat training at 75% of one-repetition maximum (1RM), performed in 3 sets of 8 repetitions with a 2-min inter-set rest period. This was conducted under four distinct BFR conditions: continuous low BFR (T1), intermittent medium BFR (T2), intermittent high BFR (T3), and a non-restricted control (C). Surface electromyography (EMG) was utilized to collect EMG signals from the target muscles during the BFR and squat training sessions. The root mean square (RMS) amplitude standard values were calculated for each squat set to quantify muscle activation levels, with these values expressed as a percentage of the maximum voluntary contraction (%MVC). Rating of Perceived Exertion was evaluated after each squat set, and leg circumference measurements were taken.

Results

1) During the first two sets of deep squats, the %MVC of the vastus lateralis and vastus medialis in all compression groups was significantly higher than that in the control group (p < 0.05). Furthermore, in the first set, the %MVC of the vastus lateralis in Group T3 was significantly higher than in Group T2 (p < 0.05). In the third set, the %MVC of the vastus medialis in Groups T1 and T3 was significantly lower than in the first two sets (p < 0.05). 2) Group T1 showed an increased activation of the biceps femoris and semitendinosus muscles in the second and third sets, with %MVC values significantly greater than in the first set (p < 0.05). Group T2 only showed an increase in biceps femoris activation in the third set (p < 0.05). Group T3 significantly increased the activation of the biceps femoris and semitendinosus muscles only in the first set (p < 0.05). 3) No significant differences were observed in the changes of rectus abdominis %MVC among the groups (p > 0.05). In the first set, Group T3's erector spinae %MVC was significantly higher than the control group's; in the second set, it was significantly higher than both Group T2 and the control group's (p < 0.05). 4) After training, a significant increase in thigh circumference was observed in all groups compared to before training (p < 0.05). 5) For RPE values, Group T2's post-squat values were significantly higher than the control group's after all three sets (p < 0.05). Group T1's RPE values were also significantly higher than the control group's after the third set (p < 0.05). Groups T1, T2, and C all had significantly higher RPE values in the second and third sets compared to the first set (p < 0.05).

Conclusion

All BFR modalities significantly enhanced the activation level of the anterior thigh muscles, with the continuous low BFR mode demonstrating a more stable effect. No significant differences were found in the activation level of the rectus abdominis among the groups. However, the intermittent high BFR mode was the most effective in increasing the activation level of the erector spinae muscles. While BFR did not further augment leg circumference changes, it did elevate subjective fatigue levels. The RPE was lowest during squatting under the intermittent high BFR condition.

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.

Maximal Number of Repetitions at Percentages of the One Repetition Maximum: A Meta-Regression and Moderator Analysis of Sex, Age, Training Status, and Exercise

The maximal number of repetitions that can be completed at various percentages of the one repetition maximum (1RM) [REPS ~ %1RM relationship] is foundational knowledge in resistance exercise programming. The current REPS ~ %1RM relationship is based on few studies and has not incorporated uncertainty into estimations or accounted for between-individuals variation. Therefore, we conducted a meta-regression to estimate the mean and between-individuals standard deviation of the number of repetitions that can be completed at various percentages of 1RM. We also explored if the REPS ~ %1RM relationship is moderated by sex, age, training status, and/or exercise. A total of 952 repetitions-to-failure tests, completed by 7289 individuals in 452 groups from 269 studies, were identified. Study groups were predominantly male (66%), healthy (97%), < 59 years of age (92%), and resistance trained (60%). The bench press (42%) and leg press (14%) were the most commonly studied exercises. The REPS ~ %1RM relationship for mean repetitions and standard deviation of repetitions were best described using natural cubic splines and a linear model, respectively, with mean and standard deviation for repetitions decreasing with increasing %1RM. More repetitions were evident in the leg press than bench press across the loading spectrum, thus separate REPS ~ %1RM tables were developed for these two exercises. Analysis of moderators suggested little influences of sex, age, or training status on the REPS ~ %1RM relationship, thus the general main model REPS ~ %1RM table can be applied to all individuals and to all exercises other than the bench press and leg press. More data are needed to develop REPS ~ %1RM tables for other exercises.

Effects of High-Load Bench Press Training with Different Blood Flow Restriction Pressurization Strategies on the Degree of Muscle Activation in the Upper Limbs of Bodybuilders

Background: The aim of this study was to investigate the effects of different pressurization modes during high-load bench press training on muscle activation and subjective fatigue in bodybuilders. Methods: Ten bodybuilders participated in a randomized, self-controlled crossover experimental design, performing bench press training under three different pressurization modes: T1 (low pressure, high resistance), T2 (high pressure, high resistance), and C (non-pressurized conventional). Surface EMG signals were recorded from the pectoralis major, deltoid, and triceps muscles using a Delsys Trigno wireless surface EMG during bench presses. Subjective fatigue was assessed immediately after the training session. Results: (1) Pectoralis major muscle: The muscle activation degree of the T1 group was significantly higher than that of the blank control group during the bench press (p < 0.05). The muscle activation degree of the T2 group was significantly higher than that of the C group during the bench press (p < 0.05). In addition, the muscle activation degree of the T2 group was significantly higher than that of the T1 group during the first group bench press (p < 0.05). (2) Deltoid muscle: The muscle activation degree of the T2 group during the third group bench press was significantly lower than the index values of the first two groups (p < 0.05). The muscle activation degree in the experimental group was significantly higher than that in the C group (p < 0.05). The degree of muscle activation in the T2 group was significantly higher than that in the T1 group during the first bench press (p < 0.05). (3) Triceps: The muscle activation degree of the T1 group was significantly higher than the index value of the third group during the second group bench press (p < 0.05), while the muscle activation degree of the T2 group was significantly lower than the index value of the first two groups during the third group bench press (p < 0.05). The degree of muscle activation in all experimental groups was significantly higher than that in group C (p < 0.05). (5) RPE index values in all groups were significantly increased (p < 0.05). The RPE value of the T1 group was significantly higher than that of the C group after bench press (p < 0.05). The RPE value of the T1 group was significantly higher than that of the C group after bench press (p < 0.05). In the third group, the RPE value of the T1 group was significantly higher than that of the C and T2 groups (p = 0.002) (p < 0.05). Conclusions: The activation of the pectoralis major, triceps brachii, and deltoid muscles is significantly increased by high-intensity bench press training with either continuous or intermittent pressurization. However, continuous pressurization results in a higher level of perceived fatigue. The training mode involving high pressure and high resistance without pressurization during sets but with 180 mmHg occlusion pressure and pressurization during rest intervals yields the most pronounced overall effect on muscle activation.

Similar muscle hypertrophy following eight weeks of resistance training to momentary muscular failure or with repetitions-in-reserve in resistance-trained individuals

This study examined the influence of resistance training (RT) proximity-to-failure, determined by repetitions-in-reserve (RIR), on quadriceps hypertrophy and neuromuscular fatigue. Resistance-trained males (n = 12) and females (n = 6) completed an 8-week intervention involving two RT sessions per week. Lower limbs were randomised to perform the leg press and leg extension exercises either to i) momentary muscular failure (FAIL), or ii) a perceived 2-RIR and 1-RIR, respectively (RIR). Muscle thickness of the quadriceps [rectus femoris (RF) and vastus lateralis (VL)] and acute neuromuscular fatigue (i.e., repetition and lifting velocity loss) were assessed. Data was analysed with Bayesian linear mixed-effect models. Increases in quadriceps thickness (average of RF and VL) from pre- to post-intervention were similar for FAIL [0.181 cm (HDI: 0.119 to 0.243)] and RIR [0.182 cm (HDI: 0.115 to 0.247)]. Between-protocol differences in RF thickness slightly favoured RIR [-0.036 cm (HDI: -0.113 to 0.047)], but VL thickness slightly favoured FAIL [0.033 cm (HDI: -0.046 to 0.116)]. Mean volume was similar across the RT intervention between FAIL and RIR. Lifting velocity and repetition loss were consistently greater for FAIL versus RIR, with the magnitude of difference influenced by the exercise and the stage of the RT intervention.

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.

Changes in Intraset Repetitions in Reserve Prediction Accuracy During Six Weeks of Bench Press Training in Trained Men

In this study we investigated whether the accuracy of intraset repetitions in reserve (RIR) predictions changes over time. Nine trained men completed three bench press training sessions per week for 6 weeks (following a 1-week familiarization). The final set of each session was performed until momentary muscular failure, with participants verbally indicating their perceived 4RIR and 1RIR. RIR prediction errors were calculated as raw differences (RIRDIFF), with positive and negative values indicating directionality, and absolute RIRDIFF (absolute value of raw RIRDIFF) indicating error scores. We constructed mixed effect models with time (i.e., session) and proximity to failure as fixed effects, repetitions as a covariate, and random intercepts per participant to account for repeated measures, with statistical significance set at p ≤ .05. We observed a significant main effect for time on raw RIRDIFF (p < .001), with an estimated marginal slope of -.077 repetitions, indicating a slight decrease in raw RIRDIFF over time. Further, the estimated marginal slope of repetitions was -.404 repetitions, indicating a decrease in raw RIRDIFF as more repetitions were performed. There were no significant effects on absolute RIRDIFF. Thus, RIR rating accuracy did not significantly improve over time, though there was a greater tendency to underestimate RIR in later sessions and during higher repetition sets.

Physiological Responses and Adaptations to Lower Load Resistance Training: Implications for Health and Performance

Resistance training is a method of enhancing strength, gait speed, mobility, and health. However, the external load required to induce these benefits is a contentious issue. A growing body of evidence suggests that when lower load resistance training [i.e., loads < 50% of one-repetition maximum (1RM)] is completed within close proximity to concentric failure, it can serve as an effective alternative to traditional higher load (i.e., loads > 70% of 1RM) training and in many cases can promote similar or even superior physiological adaptations. Such findings are important given that confidence with external loads and access to training facilities and equipment are commonly cited barriers to regular resistance training. Here, we review some of the mechanisms and physiological changes in response to lower load resistance training. We also consider the evidence for applying lower loads for those at risk of cardiovascular and metabolic diseases and those with reduced mobility. Finally, we provide practical recommendations, specifically that to maximize the benefits of lower load resistance training, high levels of effort and training in close proximity to concentric failure are required. Additionally, using lower loads 2-3 times per week with 3-4 sets per exercise, and loads no lower than 30% of 1RM can enhance muscle hypertrophy and strength adaptations. Consequently, implementing lower load resistance training can be a beneficial and viable resistance training method for a wide range of fitness- and health-related goals.

The effects of resistance training to near failure on strength, hypertrophy, and motor unit adaptations in previously trained adults

Limited research exists examining how resistance training to failure affects applied outcomes and single motor unit characteristics in previously trained individuals. Herein, resistance-trained adults (24 ± 3 years old, self-reported resistance training experience was 6 ± 4 years, 11 men and 8 women) were randomly assigned to either a low-repetitions-in-reserve (RIR; i.e., training near failure, n = 10) or high-RIR (i.e., not training near failure, n = 9) group. All participants implemented progressive overload during 5 weeks where low-RIR performed squat, bench press, and deadlift twice weekly and were instructed to end each training set with 0-1 RIR. high-RIR performed identical training except for being instructed to maintain 4-6 RIR after each set. During week 6, participants performed a reduced volume-load. The following were assessed prior to and following the intervention: (i) vastus lateralis (VL) muscle cross-sectional area (mCSA) at multiple sites; (ii) squat, bench press, and deadlift one-repetition maximums (1RMs); and (iii) maximal isometric knee extensor torque and VL motor unit firing rates during an 80% maximal voluntary contraction. Although RIR was lower in the low- versus high-RIR group during the intervention (p < 0.001), total training volume did not significantly differ between groups (p = 0.222). There were main effects of time for squat, bench press, and deadlift 1RMs (all p-values < 0.05), but no significant condition × time interactions existed for these or proximal/middle/distal VL mCSA data. There were significant interactions for the slope and y-intercept of the motor unit mean firing rate versus recruitment threshold relationship. Post hoc analyses indicated low-RIR group slope values decreased and y-intercept values increased after training suggesting low-RIR training increased lower-threshold motor unit firing rates. This study provides insight into how resistance training in proximity to failure affects strength, hypertrophy, and single motor unit characteristics, and may inform those who aim to program for resistance-trained 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 = β 0 + β 1 X A C V F i r s t + β 2 Z + 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.

Effect of High-Volume Cluster Sets vs. Lower-Volume Traditional Sets on Accuracy of Estimated Repetitions to Failure

ABSTRACT

Davies, TB, Li, J, and Hackett, DA. Effect of high-volume cluster sets vs. lower-volume traditional sets on accuracy of estimated repetitions to failure. J Strength Cond Res XX(X): 000-000, 2022-This study investigated the effects of resistance training using cluster (CLUS) vs. traditional (TRAD) set structures on the accuracy of estimated repetitions to failure (ERF). Nineteen healthy male resistance trainers (age 21.0 ± 4.4 years) were randomized into 1 of the 2 bench press training routines performed for 6 weeks. Cluster (n = 10) performed 6 sets of 5 repetitions at 85% of 1 repetition maximum (1RM) with 30-second interrepetition rest and 3 minutes of interset rest. Traditional (n = 9) performed 3 sets of 5 repetitions at 85% 1RM with 5 minutes of interset rest. Maximum repetitions at 85% 1RM was performed before and after intervention to assess error in ERF and mean concentric velocity (MCV). The ERF, rating of perceived exertion, and maintenance of MCV were assessed throughout the intervention. Rating of perceived exertion was lower for sets 1-3 in CLUS compared with TRAD from weeks 1 to 4 (effect size [ES] = 0.8-2.4, p ≤ 0.04). The ERF was greater for sets 1-3 in CLUS than in TRAD during all intervention weeks (ES = 1.0-5.1, p ≤ 0.04). Maintenance of MCV was greater in CLUS compared with TRAD for all sets at week 1 (ES = 0.76, p = 0.002) and sets 4-6 at week 6 (ES = 0.77, p = 0.006). After the intervention, error in ERF did not change, and no differences were found between the groups. Findings indicate that accuracy of ERF does not improve after resistance training using set structures that induce different transient fatigue-related effects when using high loads in experienced resistance trainers.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00526-8.

Repetitions in Reserve Is a Reliable Tool for Prescribing Resistance Training Load

ABSTRACT

Lovegrove, S, Hughes, L, Mansfield, S, Read, P, Price, P, and Patterson, SD. Repetitions in reserve is a reliable tool for prescribing resistance training load. J Strength Cond Res 36(10): 2696-2700, 2022-This study investigated the reliability of repetitions in reserve (RIR) as a method for prescribing resistance training load for the deadlift and bench press exercises. Fifteen novice trained men (age: 17.3 ± 0.9 years, height: 176.0 ± 8.8 cm, body mass: 71.3 ± 10.7 kg) were assessed for 1 repetition maximum (1RM) for deadlift (118.1 ± 27.3 kg) and bench press (58.2 ± 18.6 kg). Subsequently, they completed 3 identical sessions (one familiarization session and 2 testing sessions) comprising sets of 3, 5, and 8 repetitions. For each repetition scheme, the load was progressively increased in successive sets until subjects felt they reached 1-RIR at the end of the set. Test-retest reliability of load prescription between the 2 testing sessions was determined using intraclass correlation coefficient (ICC) and coefficient of variation (CV). A 2-way analysis of variance with repeated measures was used for each exercise to assess differences in the load corresponding to 1-RIR within each repetition scheme. All test-retest comparisons demonstrated a high level of reliability (deadlift: ICC = 0.95-0.99, CV = 2.7-5.7% and bench press: ICC = 0.97-0.99, CV = 3.8-6.2%). Although there were no differences between time points, there was a difference for load corresponding to 1-RIR across the 3 repetition schemes (deadlift: 88.2, 84.3, and 79.2% 1RM; bench press: 93.0, 87.3, and 79.6% 1RM for the 3-, 5-, and 8-repetition sets, respectively). These results suggest that RIR is a reliable tool for load prescription in a young novice population. Furthermore, the between-repetition scheme differences highlight that practitioners can effectively manipulate load and volume (repetitions in a set) throughout a training program to target specific resistance training adaptations.

The effects of technological and traditional feedback on back squat performance in untrained women

BACKGROUND

Recently, a novel method for improving movement quality called open-ended augmented feedback has been introduced. However, the effects of using such feedback in a training intervention have not yet been examined. The aim of this study was to assess the changes in performance and movement quality following a five-week resistance-training program with either (1) technological feedback or (2) traditional, verbal feedback from an experienced trainer.

METHODS

Nineteen untrained females (age: 21.84 ± 2.24 years, height: 169.95 ± 5.92 cm, body mass: 65.05 ± 7.93 kg) randomly allocated to one of the two conditions completed five weeks of training with two weekly sessions. Pre- and post-intervention, participants were tested for physical performance (i.e., back squat and isometric mid-thigh pull strength) and movement quality parameters (weight distribution, center of gravity variation, and subjective rating of the back squat technique).

RESULTS

Both groups similarly increased the training resistance throughout the intervention (p < 0.01), as well as strength in the back squat (technological feedback group: effect size (ES) = 1.31, p = 0.002; traditional feedback group: ES = 1.48, p = 0.002). Only the traditional feedback group increased isometric mid-thigh pull strength (ES = 1.11, p = 0.008) and subjectively rated lifting technique at the same load (p = 0.046). No changes in force distribution (p = 0.062-0.993) or center of gravity variation (p = 0.160-0.969) occurred in either group when lifting the same absolute loads at post-test. However, both groups displayed a greater variation in center of gravity when lifting the same relative load at post-test (technological feedback group: p < 0.001; traditional feedback group: p = 0.006). No differences were found between the groups for any of the observed changes (p = 0.205-0.401).

CONCLUSIONS

Five weeks of back-squat training with verbal feedback increased isometric mid-thigh pull strength and subjectively rated lifting technique from pre- to post-test, whereas technological feedback did not. Both methods improved back squat strength and training resistance. For resistance-training beginners, the choice between feedback methods should be based on the desired outcomes and the availability of expertise and equipment.

Towards an improved understanding of proximity-to-failure in resistance training and its influence on skeletal muscle hypertrophy, neuromuscular fatigue, muscle damage, and perceived discomfort: A scoping review

While proximity-to-failure is considered an important resistance training (RT) prescription variable, its influence on physiological adaptations and short-term responses to RT is uncertain. Given the ambiguity in the literature, a scoping review was undertaken to summarise evidence for the influence of proximity-to-failure on muscle hypertrophy, neuromuscular fatigue, muscle damage and perceived discomfort. Literature searching was performed according to PRISMA-ScR guidelines and identified three themes of studies comparing either: i) RT performed to momentary muscular failure versus non-failure, ii) RT performed to set failure (defined as anything other than momentary muscular failure) versus non-failure, and iii) RT performed to different velocity loss thresholds. The findings highlight that no consensus definition for "failure" exists in the literature, and the proximity-to-failure achieved in "non-failure" conditions is often ambiguous and variable across studies. This poses challenges when deriving practical recommendations for manipulating proximity-to-failure in RT to achieve desired outcomes. Based on the limited available evidence, RT to set failure is likely not superior to non-failure RT for inducing muscle hypertrophy, but may exacerbate neuromuscular fatigue, muscle damage, and post-set perceived discomfort versus non-failure RT. Together, these factors may impair post-exercise recovery and subsequent performance, and may also negatively influence long-term adherence to RT.KEY POINTS This scoping review identified three broad themes of studies investigating proximity-to-failure in RT, based on the specific definition of set failure used (and therefore the research question being examined), to improve the validity of study comparisons and interpretations.There is no consensus definition for set failure in RT, and the proximity-to-failure achieved during non-failure RT is often unclear and varies both within and between studies, which together poses challenges when interpreting study findings and deriving practical recommendations regarding the influence of RT proximity-to-failure on muscle hypertrophy and other short-term responses.Based on the limited available evidence, performing RT to set failure is likely not superior to non-failure RT to maximise muscle hypertrophy, but the optimal proximity to failure in RT for muscle hypertrophy is unclear and may be moderated by other RT variables (e.g., load, volume-load). Also, RT performed to set failure likely induces greater neuromuscular fatigue, muscle damage, and perceived discomfort than non-failure RT, which may negatively influence RT performance, post-RT recovery, and long-term adherence.

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.

The Effect of Load and Volume Autoregulation on Muscular Strength and Hypertrophy: A Systematic Review and Meta-Analysis

Background

Autoregulation has emerged as a potentially beneficial resistance training paradigm to individualize and optimize programming; however, compared to standardized prescription, the effects of autoregulated load and volume prescription on muscular strength and hypertrophy adaptations are unclear. Our objective was to compare the effect of autoregulated load prescription (repetitions in reserve-based rating of perceived exertion and velocity-based training) to standardized load prescription (percentage-based training) on chronic one-repetition maximum (1RM) strength and cross-sectional area (CSA) hypertrophy adaptations in resistance-trained individuals. We also aimed to investigate the effect of volume autoregulation with velocity loss thresholds ≤ 25% compared to > 25% on 1RM strength and CSA hypertrophy.

Methods

This review was performed in accordance with the PRISMA guidelines. A systematic search of MEDLINE, Embase, Scopus, and SPORTDiscus was conducted. Mean differences (MD), 95% confidence intervals (CI), and standardized mean differences (SMD) were calculated. Sub-analyses were performed as applicable.

Results

Fifteen studies were included in the meta-analysis: six studies on load autoregulation and nine studies on volume autoregulation. No significant differences between autoregulated and standardized load prescription were demonstrated for 1RM strength (MD = 2.07, 95% CI – 0.32 to 4.46 kg, p = 0.09, SMD = 0.21). Velocity loss thresholds ≤ 25% demonstrated significantly greater 1RM strength (MD = 2.32, 95% CI 0.33 to 4.31 kg, p = 0.02, SMD = 0.23) and significantly lower CSA hypertrophy (MD = 0.61, 95% CI 0.05 to 1.16 cm², p = 0.03, SMD = 0.28) than velocity loss thresholds > 25%. No significant differences between velocity loss thresholds > 25% and 20–25% were demonstrated for hypertrophy (MD = 0.36, 95% CI – 0.29 to 1.00 cm², p = 0.28, SMD = 0.13); however, velocity loss thresholds > 25% demonstrated significantly greater hypertrophy compared to thresholds ≤ 20% (MD = 0.64, 95% CI 0.07 to 1.20 cm², p = 0.03, SMD = 0.34).

Conclusions

Collectively, autoregulated and standardized load prescription produced similar improvements in strength. When sets and relative intensity were equated, velocity loss thresholds ≤ 25% were superior for promoting strength possibly by minimizing acute neuromuscular fatigue while maximizing chronic neuromuscular adaptations, whereas velocity loss thresholds > 20–25% were superior for promoting hypertrophy by accumulating greater relative volume.

Protocol Registration The original protocol was prospectively registered (CRD42021240506) with the PROSPERO (International Prospective Register of Systematic Reviews).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-021-00404-9.

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.

Training for Muscular Strength: Methods for Monitoring and Adjusting Training Intensity

Linear loading, the two-for-two rule, percent of one repetition maximum (1RM), RM zones, rate of perceived exertion (RPE), repetitions in reserve, set-repetition best, autoregulatory progressive resistance exercise (APRE), and velocity-based training (VBT) are all methods of adjusting resistance training intensity. Each method has advantages and disadvantages that strength and conditioning practitioners should be aware of when measuring and monitoring strength characteristics. The linear loading and 2-for-2 methods may be beneficial for novice athletes; however, they may be limited in their capacity to provide athletes with variation and detrimental if used exclusively for long periods of time. The percent of 1RM and RM zone methods may provide athletes with more variation and greater potential for strength-power adaptations; however, they fail to account for daily changes in athlete's performance capabilities. An athlete's daily readiness can be addressed to various extents by both subjective (e.g., RPE, repetitions in reserve, set-repetition best, and APRE) and objective (e.g., VBT) load adjustment methods. Future resistance training monitoring may aim to include a combination of measures that quantify outcome (e.g., velocity, load, time, etc.) with process (e.g., variability, coordination, efficiency, etc.) relevant to the stage of learning or the task being performed. Load adjustment and monitoring methods should be used to supplement and guide the practitioner, quantify what the practitioner 'sees', and provide longitudinal data to assist in reviewing athlete development and providing baselines for the rate of expected development in resistance training when an athlete returns to sport from injury or large training load reductions.

Rating of Perceived Effort: Methodological Concerns and Future Directions

Rating of perceived effort (RPE) scales are the most frequently used single-item scales in exercise science. They offer an easy and useful way to monitor and prescribe exercise intensity. However, RPE scales suffer from methodological limitations stemming from multiple perceived effort definitions and measurement strategies. In the present review, we attend these issues by covering (1) two popular perceived effort definitions, (2) the terms included within these definitions and the reasons they can impede validity, (3) the problems associated with using different effort scales and instructions, and (4) measuring perceived effort from specific body parts and the body as a whole. We pose that the large number of interactions between definitions, scales, instructions and applications strategies, threatens measurement validity of RPE. We suggest two strategies to overcome these limitations: (1) to reinforce consistency by narrowing the number of definitions of perceived effort, the number of terms included within them, and the number of scales and instructions used. (2) Rather than measuring solely RPE as commonly done, exercise sciences will benefit from incorporating other single-item scales that measure affect, fatigue and discomfort, among others. By following these two recommendations, we expect the field will increase measurement validity and become more comprehensive.

Effects of subjective and objective autoregulation methods for intensity and volume on enhancing maximal strength during resistance-training interventions: a systematic review

Background

Maximal strength is a critical determinant of performance in numerous sports. Autoregulation is a resistance training prescription approach to adjust training variables based on the individuals’ daily fluctuations in performance, which are a result of training-induced fitness and fatigue, together with readiness from daily non-training stressors.

Objective

This review aimed to summarise the effects of different subjective and objective autoregulation methods for intensity and volume on enhancing maximal strength.

Materials and Methods

A comprehensive literature search was conducted through SPORTDiscus, PubMed and Google Scholar. Studies had to meet the following criteria to be included in the review: (1) estimation of 1-RM or a 1-RM test for both pre-test and post-test to measure progression in strength assessment during the training intervention, (2) a training comparison group, (3) participants were healthy, (4) the article had a detailed description of training intensity, training volume, and training frequency during the training intervention, (5) the training intervention lasted for more than four weeks, (6) studies with objective autoregulation methods utilised a validated measuring tool to monitor velocity, (7) English-language studies.

Results

Fourteen studies met the inclusion criteria, comprising 30 training groups and 356 participants. Effect size and percentage differences were calculated for 13 out of 14 studies to compare the effects of different training interventions. All autoregulation training protocols resulted in an increase in 1-RM, from small ES to large ES.

Conclusion

Overall, our findings suggest that using both subjective autoregulation methods for intensity, such as repetitions in reserve rating of perceived exertion and flexible daily undulation periodisation, together with objective autoregulation methods for autoregulation intensity and volume, such as velocity targets and velocity loss, could be effective methods for enhancing maximal strength. It is speculated that this is because the implementation of autoregulation into a periodised plan may take into account the athletes’ daily fluctuations, such as fluctuations in fitness, fatigue, and readiness to train. When training with a validated measuring tool to monitor velocity, this may provide objective augmented intra- and interset feedback during the resistance exercise who could be beneficial for increasing maximal strength. Coaches, practitioners, and athletes are encouraged to implement such autoregulation methods into a periodised plan when the goal is to enhance maximal strength.

"Just One More Rep!" - Ability to Predict Proximity to Task Failure in Resistance Trained Persons

In resistance training, the use of predicting proximity to momentary task failure (MF, i.e., maximum effort), and repetitions in reserve scales specifically, is a growing approach to monitoring and controlling effort. However, its validity is reliant upon accuracy in the ability to predict MF which may be affected by congruence of the perception of effort compared with the actual effort required. The present study examined participants with at least 1 year of resistance training experience predicting their proximity to MF in two different experiments using a deception design. Within each experiment participants performed four trials of knee extensions with single sets (i.e., bouts of repetitions) to their self-determined repetition maximum (sdRM; when they predicted they could not complete the next repetition if attempted and thus would reach MF if they did) and MF (i.e., where despite attempting to do so they could not complete the current repetition). For the first experiment (n = 14) participants used loads equal to 70% of a one repetition maximum (1RM; i.e., the heaviest load that could be lifted for a single repetition) performed in a separate baseline session. Aiming to minimize participants between day variability in repetition performances, in the second separate experiment (n = 24) they used loads equal to 70% of their daily isometric maximum voluntary contraction (MVC). Results suggested that participants typically under predicted the number of repetitions they could perform to MF with a meta-analytic estimate across experiments of 2.0 [95%CIs 0.0 to 4.0]. Participants with at least 1 year of resistance training experience are likely not adequately accurate at gauging effort in submaximal conditions. This suggests that perceptions of effort during resistance training task performance may not be congruent with the actual effort required. This has implications for controlling, programming, and manipulating the actual effort in resistance training and potentially on the magnitude of desired adaptations such as improvements in muscular hypertrophy and strength.

Methods for Regulating and Monitoring Resistance Training

Individualisation can improve resistance training prescription. This is accomplished via monitoring or autoregulating training. Autoregulation adjusts variables at an individualised pace per performance, readiness, or recovery. Many autoregulation and monitoring methods exist; therefore, this review’s objective was to examine approaches intended to optimise adaptation. Up to July 2019, PubMed, Medline, SPORTDiscus, Scopus and CINAHL were searched. Only studies on methods of athlete monitoring useful for resistance-training regulation, or autoregulated training methods were included. Eleven monitoring and regulation themes emerged across 90 studies. Some physiological, performance, and perceptual measures correlated strongly (r ≥ 0.68) with resistance training performance. Testosterone, cortisol, catecholamines, cell-free DNA, jump height, throwing distance, barbell velocity, isometric and dynamic peak force, maximal voluntary isometric contractions, and sessional, repetitions in reserve-(RIR) based, and post-set Borg-scale ratings of perceived exertion (RPE) were strongly associated with training performance, respectively. Despite strong correlations, many physiological and performance methods are logistically restrictive or limited to lab-settings, such as blood markers, electromyography or kinetic measurements. Some practical performance tests such as jump height or throw distance may be useful, low-risk stand-ins for maximal strength tests. Performance-based individualisation of load progression, flexible training configurations, and intensity and volume modifications based on velocity and RIR-based RPE scores are practical, reliable and show preliminary utility for enhancing performance.

Perception of changes in bar velocity in resistance training: Accuracy levels within and between exercises

Velocity-based training is a method used to monitor resistance-training programs based on repetition velocities measured with tracking devices. Since velocity measuring devices can be expensive and impractical, trainee's perception of changes in velocity (PCV) may be used as a possible substitute. Here, 20 resistance-trained males first completed 1 Repetition Maximum (RM) tests in the bench-press and squat. Then, in three counterbalanced sessions, participants completed four sets of eight repetitions in both exercises using 60%1RM (two-sessions) or 70%1RM. Starting from the second repetition, participants reported their PCV of each repetition as a percentage of the first repetition. Accuracy of PCV was calculated as the difference between PCV and actual changes in velocity measured with a linear-encoder. Three key findings emerged. First, the absolute error in the bench-press and squat was ≈5.8 percentage-points in the second repetition, and increased to 13.2 and 16.7 percentage-points, respectively, by the eighth repetition. Second, participants reduced the absolute error in the second 60%1RM session compared to the first by ≈1.7 in both exercises (p ≤ 0.007). Third, participants were 4.2 times more likely to underestimate changes velocity in the squat compared to the bench-press. The gradual increments in the absolute error suggest that PCV may be better suited for sets of fewer repetitions (e.g., 4-5) and wider velocity-loss threshold ranges (e.g., 5-10%). The reduced absolute error in the second 60%1RM session suggests that PCV accuracy can be improved with practice. The systematic underestimation error in the squat suggests that a correction factor may increase PCV accuracy in this exercise.