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.

Terminating RT sets with a close proximity-to-failure (e.g., 1- to 2-RIR) can be sufficient to promote similar hypertrophy of the quadriceps as reaching momentary muscular failure in resistance-trained individuals over eight weeks, but the overall influence of proximity-to-failure on muscle-specific hypertrophy may also depend on other factors (e.g., exercise selection, order, and subsequent musculature targeted).Due to high repetition loss (from the first to final set) when sets are terminated at momentary muscular failure, performing RT with 1- to 2-RIR allows for similar volume load and repetition volume accumulation as reaching momentary muscular failure across eight weeks, possibly influencing the overall RT stimulus achieved.Performing RT to momentary muscular failure consistently induces higher levels of acute neuromuscular fatigue versus RT performed with 1- to 2-RIR; however, improved fatigue resistance overtime may attenuate acute neuromuscular fatigue and subsequent repetition loss (but may depend on the exercise performed).

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.

N of 1: Optimizing Methodology for the Detection of Individual Response Variation in Resistance Training.

Most resistance training research focuses on inference from average intervention effects from observed group-level change scores (i.e., mean change of group A vs group B). However, many practitioners are more interested in training responses (i.e., causal effects of an intervention) on the individual level (i.e., causal effect of intervention A vs intervention B for individual X). To properly examine individual response variation, multiple confounding sources of variation (e.g., random sampling variability, measurement error, biological variability) must be addressed. Novel study designs where participants complete both interventions and at least one intervention twice can be leveraged to account for these sources of variation (i.e., n of 1 trials). Specifically, the appropriate statistical methods can separate variability into the signal (i.e., participant-by-training interaction) versus the noise (i.e., within-participant variance). This distinction can allow researchers to detect evidence of individual response variation. If evidence of individual response variation exists, researchers can explore predictors of the more favorable intervention, potentially improving exercise prescription. This review outlines the methodology necessary to explore individual response variation to resistance training, predict favorable interventions, and the limitations thereof.

The Effect of Time-Equated Concurrent Training Programs in Resistance-Trained Men.

The purpose of this investigation was to compare the effects of three different concurrent training (CT) programs and a resistance training (RT) program. Twenty-three resistance trained men (age: 24 ± 3 years) were randomized into four groups: concurrent RT and high intensity interval cycling (CTH, n = 6), concurrent RT and moderate intensity continuous cycling (CTM, n = 5), RT and barbell circuit training (RTC, n = 6), or RT only (RT, n = 6). Back squat and bench press strength, quadriceps, and pectoralis muscle thickness, VO2peak, and maximum workload (Wmax, Watts) were assessed. Squat strength gains were meaningful in all groups and comparable among CTH (16.88 kg [95% CrI: 11.15, 22.63]), CTM (25.54 kg [95% CrI: 19.24, 31.96]), RTC (17.5 kg [95% CrI: 11.66, 23.39]), and RT (20.36 kg [95% CrI: 15.29, 25.33]) groups. Bench press strength gains were meaningful in all groups and comparable among CTH (11.86 kg [95% CrI: 8.28, 15.47]), CTM (10.3 kg [95% CrI: 6.49, 14.13]), RTC (4.84 kg [95% CrI: 1.31, 8.47]), and RT (10.16 kg [95% CrI: 7.02, 13.22]) groups. Quadriceps hypertrophy was meaningful in all groups and comparable among CTH (2.29 mm [95% CrI: 0.84, 3.76]), CTM (3.41 mm [95% CrI: 1.88, 4.91]), RTC (2.6 mm [95% CrI: 1.17, 4.05]), and RT (2.83 mm [95% CrI: 1.55, 4.12]) groups. Pectoralis hypertrophy was meaningful in CTH (2.29 mm [95% CrI: -0.52, 5.1]), CTM (5.14 mm [95% CrI: 2.1, 8.15]), and RTC (7.19 mm [95% CrI: 4.26, 10.02]) groups, but not in the RT group (1 mm [95% CrI: -1.59, 3.59]); further, between-group contrasts indicated less pectoralis growth in the RT compared to the RTC group. Regarding cardiovascular outcomes, only the RTH and RTM groups experienced meaningful improvements in either measure (VO2peak or Wmax). These data suggest that the interference effect on maximal strength and hypertrophy can be avoided when the aerobic training is moderate intensity cycling, high intensity cycling, or a novel barbell circuit for ~one hour per week and on non-RT days. However, the barbell circuit failed to elicit meaningful cardiovascular adaptations.

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.

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.

Accuracy of Predicting One-Repetition Maximum from Submaximal Velocity in The Barbell Back Squat and Bench Press.

This study examined the accuracy of predicting a free-weight back squat and a bench press one-repetition maximum (1RM) using both 2- and 4-point submaximal average concentric velocity (ACV) methods. Seventeen resistance trained men performed a warm-up and a 1RM test on the squat and bench press with ACV assessed on all repetitions. The ACVs during the warm-up closest to 1.0 and 0.5m.s-1 were used in the 2-point linear regression forecast of the 1RM and the ACVs established at loads closest to 20, 50, 70, and 80% of the 1RM were used in the 4-point 1RM prediction. Repeated measures ANOVA and Bland-Altman and Mountain plots were used to analyze agreement between predicted and actual 1RMs. ANOVA indicated significant differences between the predicted and the actual 1RM for both the 2- and 4-point equations in both exercises (p<0.001). The 2-point squat prediction overestimated the 1RM by 29.12±0.07kg and the 4-point squat prediction overestimated the 1RM by 38.53±5.01kg. The bench press 1RM was overestimated by 9.32±4.68kg with the 2-point method and by 7.15±6.66kg using the 4-point method. Bland-Altman and Mountain plots confirmed the ANOVA findings as data were not tightly conformed to the respective zero difference lines and Bland-Altman plots showed wide limits of agreement. These data demonstrate that both 2- and 4-point velocity methods predicted the bench press 1RM more accurately than the squat 1RM. However, a lack of agreement between the predicted and the actual 1RM was observed for both exercises when volitional velocity was used.

Reporting of Resistance Training Dose, Adherence, and Tolerance in Exercise Oncology.

PURPOSE: While general guidelines (such as CONSORT or Consensus on Exercise Reporting Template) exist to enhance the reporting of exercise interventions in the field of exercise science, there is inadequate detail facilitating the standardized reporting of resistance training adherence in the oncology setting. The purpose of this study was to apply a novel method to report resistance training dose, adherence, and tolerance in patients with cancer. METHODS: A total of 47 prostate cancer patients (70.1 ± 8.9 yr, body mass index, 28.6 ± 4.0) with bone metastatic disease completed an exercise program for 12 wk. We assessed traditional metrics of adherence (attendance and loss to follow-up), in addition to novel proposed metrics (exercise-relative dose intensity, dose modification, and exercise interruption). Total training volume in kilograms (repetitions × sets × training load (weight)) was calculated for each patient. RESULTS: Attendance assessed from traditional metrics was 79.5% ± 17.0% and four patients (9%) were lost to follow-up. The prescribed and actual cumulative total dose of resistance training was 139,886 ± 69,150 kg and 112,835 ± 83,499 kg, respectively, with a mean exercise-relative dose intensity of 77.4% ± 16.6% (range: 19.4% -99.4%). Resistance training was missed (1-2 consecutive sessions) or interrupted (missed ≥3 consecutive sessions) in 41 (87%) and 24 (51%) participants, respectively. Training dose was modified (reduction in sets, repetitions, or weight) in 40 (85%) of patients. Importantly, using attendance as a traditional metric of adherence, these sessions would have all counted as adherence to the protocol. CONCLUSIONS: Traditional reporting metrics of resistance training in exercise oncology may overestimate exercise adherence. Our proposed metrics to capture resistance training dose, adherence, and tolerance may have important applications for future studies and clinical practice.