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.

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 Importance of Recovery in Resistance Training Microcycle Construction.

Systemic resistance training aims to enhance performance by balancing stress, fatigue and recovery. While fatigue is expected, insufficient recovery may temporarily impair performance. The aim of this review was to examine evidence regarding manipulation of resistance training variables on subsequent effects on recovery and performance. PubMed, Medline, SPORTDiscus, Scopus and CINAHL were searched. Only studies that investigated recovery between resistance training sessions were selected, with a total of 24 articles included for review. Training to failure may lengthen recovery times, potentially impairing performance; however, it may be suitable if implemented strategically ensuring adequate recovery between sessions of similar exercises or muscle groups. Higher volumes may increase recovery demands, especially when paired with training to failure, however, with wide variation in individual responses, it is suggested to start with lower volume, monitor recovery, and gradually increase training volume if appropriate. Exercises emphasising the lower body, multi-joint movements, greater muscle recruitment, eccentric contractions, and/or the lengthened position may require longer recovery times. Adjusting volume and frequency of these exercises can affect recovery demands depending on the goals and training logistics. Daily undulating programming may maximise performance on priority sessions while maintaining purposeful and productive easy days. For example, active recovery in the form of training opposing muscle groups, light aerobic cardio, or low-volume power-type training may improve recovery and potentially elicit a post activation potentiation priming effect compared to passive recovery. However, it is possible that training cessation may be adequate for allowing sufficient recovery prior to sessions of importance.

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.

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.

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.

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=ß0+ß1XACVFirst+ß2Z+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.

Accuracy of Predicted Intraset Repetitions in Reserve (RIR) in Single- and Multi-Joint Resistance Exercises Among Trained and Untrained Men and Women.

We assessed the accuracy of intraset repetitions in reserve (RIR) predictions on single-joint machine-based movements of trained and untrained men and women. Participants were 27 men (M age = 22, SE = 0.6 years; M weight = 90.8, SE = 4.0 kg; M height = 182.3, SE = 1.4 cm; M training experience = 66, SE = 9 months) and 31 women (M age = 20, SE = 0.4 years; M weight = 67.8, SE = 2.3 kg; M height = 167.6, SE = 1.1 cm; M training experience = 22, SE = 4 months). In one session, participants performed a five-repetition maximum (5RM) test on biceps curl, triceps pushdown, and seated row exercises; we then estimated one repetition maximum (1RM). Participants then performed four sets of each exercise, in a randomized order, to the point of momentary muscular failure at 72.5% of 1RM. During each set, participants indicated when they first perceived 5RIR and then predicted RIR on every repetition thereafter until failure. The difference between actual repetitions performed and predicted repetitions at each intraset prediction was determined to be the RIR difference (RIRDIFF). A 3-way repeated measures ANCOVA found that a 3-way interaction was not statistically significant (p = 0.435) and no covariates of sex (p = 0.917), training experience (p = 0.462) nor experience rating RIR significantly affected RIRDIFF (p = 0.462-0.917). There were significant main effects for the proximity to failure of the prediction and the set number (p < 0.01) but not for exercise (p = 0.688). Thus, intraset RIR predictions were more accurate when closer to failure and in later sets, but sex, training experience, and experience rating RIR did not significantly influence RIR prediction accuracy on machine-based single-joint exercises.

The Impact of Obesity on C1q/TNF-Related Protein-9 Expression and Endothelial Function following Acute High-Intensity Interval Exercise vs. Continuous Moderate-Intensity Exercise.

C1q-TNF-related protein-9 (CTRP9) increases endothelial nitric oxide synthase and reduces vasoconstrictors. There is limited information regarding exercise-mediated CTRP9 in obesity. The purpose of this study was to compare high-intensity interval exercise (HIIE) and continuous moderate-intensity exercise (CME) on the CTRP9 response and an indicator of endothelial function (FMD) in obese participants. Sixteen young male participants (9 obese and 7 normal-weight) participated in a counterbalanced and caloric equated experiment: HIIE (30 min, 4 intervals of 4 min at 80-90% of VO2 max with 3 min rest between intervals) and CME (38 min at 50-60% VO2 max). Serum CTRP9 and FMD were measured prior to, immediately following exercise, and 1 h and 2 h into recovery. CTRP9 was significantly increased immediately following acute HIIE and CME in both groups (p = 0.003). There was a greater CME-induced FMD response at 2 h into recovery in obese participants (p = 0.009). A positive correlation between CTRP9 and FMD percent change was observed in response to acute CME when combined with both obese and normal-weight participants (r = 0.589, p = 0.016). The novel results from this study provide a foundation for additional examination of the mechanisms of exercise-mediated CTRP9 on endothelial function in individuals with obesity.

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.

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.

Agreement Between Kinovea Video Analysis and The Open Barbell System for Resistance Training Movement Outcomes.

The purpose of this study was to examine the agreement between Kinovea video analysis software and the previously validated Open Barbell System (OBS) for assessing average concentric and eccentric velocity, eccentric duration, peak concentric velocity, height of peak concentric velocity, and concentric and eccentric range of motion. Sixteen resistance-trained males performed 11 repetitions at various intensities (between 60-100% of one-repetition maximum) on both the back squat and the bench press. For each repetition, all outcome measures were assessed with Kinovea and the OBS. Agreement between devices for each outcome measure was analyzed with paired t-tests, intraclass correlation coefficients with 95% confidence intervals, Bland-Altman plots, and folded empirical cumulative distribution plots (Mountain plots). All outcome variables were found to be statistically different (i.e. they did not agree) between the two devices (p < 0.001), except for average eccentric velocity (p = 0.315), as determined by the paired t-tests. Mountain plots had long tails for every outcome measure and Bland-Altman plots showed large limits of agreement for all outcome measures except concentric range of motion and the height of peak concentric velocity, demonstrating low agreement between devices. Based upon these findings and the previous validation of the OBS, these devices should not be used interchangeably.

The Short Grit Scale (GRIT-S) Does Not Relate to Acute Muscular Endurance Performance.

Grit has been previously presented as a personality trait that reflects an individual's perseverance of effort and consistency of interest for achieving their long-term goals. In resistance training this could mean that a "grittier" individual may perform more repetitions at a given intensity as they are better able to overcome metabolic and neuromuscular fatigue. Thus, the purpose of this study was to examine if grit was related to back squat muscular endurance performance. Fifty-eight resistance-trained males and females volunteered for participation (age = 23±3 yrs; body height = 172.53 ± 8.64 cm; body mass = 80.64 ± 6.49 kg). The grit of each participant was assessed via the Short Grit Scale (GRIT-S), and muscular endurance performance was tested via completion of a back squat set to volitional failure at 70% of the participant's one-repetition maximum. Spearman rho or Pearson's correlations, depending on normality, were used with 1000 bootstrapped replicate samples and revealed no relationship between GRIT-S scores (3.78 ± 0.52) and repetitions performed (14 ± 4) in a combined cohort of all 58 individuals (ρ = -0.051), males only (r = 0.057) or females only (ρ = -0.441). Supplementary investigation of the data also showed that the five "best" performers (i.e. the five individuals who performed the most repetitions) tended to have lower GRIT-S scores than the five "worst" performers. The results of the current study suggest that the GRIT-S has limited value in the context of muscular endurance performance. The skewed range of GRIT-S scores (2.75-5.0) observed in this investigation, also highlights the potential for social desirability to bias one's self-perception of grit.

Agreement Between the Iron Path App and a Linear Position Transducer for Measuring Average Concentric Velocity and Range of Motion of Barbell Exercises.

ABSTRACT: Kasovic, J, Martin, B, Carzoli, JP, Zourdos, MC, and Fahs, CA. Agreement between the Iron Path app and a linear position transducer for measuring average concentric velocity and range of motion of barbell exercises. J Strength Cond Res 35(2S): S95-S101, 2021-The purpose of this study was to compare average concentric velocity (ACV) and range of motion (ROM) values measured by the Iron Path (IP) app to the previously validated Open Barbell System (OBS) linear position transducer during the front and back squat and conventional and sumo deadlift. Twenty-seven men and women (21 ± 3 years old; 76.7 ± 14.5 kg; 1.72 ± 0.09 m) with squat and deadlift training experience completed a modified one repetition maximum protocol on 4 separate occasions in a randomized order. The IP app and OBS device recorded ACV and ROM during each protocol. The level of statistical significant was set at p ≤ 0.05. Bland-Altman plots showed fairly large limits of agreement for both ACV and ROM. Furthermore, 95% confidence intervals for the intraclass correlation coefficients indicated the agreement in ACV between the devices for each of the 4 lifts to range from 0.648-0.876 to 0.849-0.930 and for agreement in ROM between devices to range from -0.053-0.480 to 0.545-0.770. Compared with the OBS, the IP app recorded significantly (p < 0.05) lower ACV values for the front squat and back squat and greater ROM values for the sumo deadlift. We suggest the IP app should not be used in place of a validated linear position transducer for measuring ACV or ROM for barbell lifts.

Rating of Perceived Exertion and Velocity Relationships Among Trained Males and Females in the Front Squat and Hexagonal Bar Deadlift.

ABSTRACT: Odgers, JB, Zourdos, MC, Helms, ER, Candow, DG, Dahlstrom, B, Bruno, P, and Sousa, CA. Rating of perceived exertion and velocity relationships among trained males and females in the front squat and hexagonal bar deadlift. J Strength Cond Res 35(2S): S23-S30, 2021-This study examined the accuracy of intraset rating of perceived exertion (RPE) to predict repetitions in reserve (RIR) during sets to failure at 80% of 1 repetition maximum (1RM) on the front squat and high-handle hexagonal bar deadlift (HHBD). Furthermore, the relationship between RPE and average concentric velocity (ACV) during the sets to failure was also determined. Fourteen males (29 ± 6 years, front squat relative 1RM: 1.78 ± 0.2 kg·kg-1, and HHBD relative 1RM: 3.0 ± 0.1 kg·kg-1) and 13 females (30 ± 5 years, front squat relative 1RM: 1.60 ± 0.2 kg·kg-1, and HHBD relative 1RM: 2.5 ± 0.3 kg·kg-1) visited the laboratory 3 times. The first visit tested 1RM on both exercises. During visits 2 and 3, which were performed in a counterbalanced order, subjects performed 4 sets to failure at 80% of 1RM for both exercises. During each set, subjects verbally indicated when they believed they were at "6" and "9" on the RIR-based RPE scale, and ACV was assessed during every repetition. The difference between the actual and predicted repetitions performed was recorded as the RPE difference (RPEDIFF). The RPEDIFF was significantly (p < 0.001) lower at the called 9 RPE versus the called 6 RPE in the front squat for males (9 RPE: 0.09 ± 0.19 versus 6 RPE: 0.71 ± 0.70) and females (9 RPE: 0.19 ± 0.36 versus 6 RPE: 0.86 ± 0.88) and in the HHBD for males (9 RPE: 0.25 ± 0.46 versus 6 RPE: 1.00 ± 1.12) and females (9 RPE: 0.21 ± 0.44 versus 6 RPE: 1.19 ± 1.16). Significant inverse relationships existed between RPE and ACV during both exercises (r = -0.98 to -1.00). These results indicate that well-trained males and females can gauge intraset RPE accurately during moderate repetition sets on the front squat and HHBD.

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

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

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

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

Weight Selection Attempts of Elite Classic Powerlifters.

This study provides the first comparison of weight selection attempt strategies used by powerlifters competing at the international level. We observed attempts selected by elite male and female classic powerlifters and compared weight selection attempts between sexes. Male (n = 66) and female (n = 43) powerlifters who completed all lifts successfully at an International Powerlifting Federation Classic World Championship between 2012-2019 were included in the analysis. We calculated the percentage weight increase from first attempts (A1) to second attempts (A2) and from A2 to third attempts (A3). For purposes of comparison, A1 values were expressed as a percentage of A3 values. We calculated non-parametric statistics with effect sizes for between and within-group comparisons. Relative to A3, males selected greater A1s compared to females for bench press (η2 = 0.16; p = 0.004) and deadlift (η2 = 0.06; p = 0.036) for each lift. Alternatively, females selected greater A1 to A2 and A2 to A3 progressions for bench press (η2 = 0.06; p = 0.026; η2 = 0.21; p = 0.005, respectively), and A2 to A3 for deadlift (η2 = 0.04; p = 0.035) compared to males. Within-group comparisons showed that males selected greater A1s on bench press compared to deadlift (η2 = 0.06; p = 0.046), whereas females selected greater A1s on squat compared to deadlift (η2 = 0.13; p = 0.038) relative to A3. Males also selected greater A2 to A3 progressions on deadlift compared to bench press (η2 = 0.10; p = 0.044), whereas females selected greater A2 to A3 progressions for bench press (η2 = 0.15; p = 0.039) and deadlift compared to squat (η2 = 0.10; p = 0.041). In conclusion, selecting an opener of ∼91% of the expected A3 weight, followed by ∼5% increase from A1 to A2, and ∼3% increase from A2 to A3 represent the typical weight selection attempts used across lifts by elite classic powerlifters competing in the World Championships. The results of this study provide novel insight into the weight selection attempts of elite classic powerlifters.

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.

Low-volume acute multi-joint resistance exercise elicits a circulating brain-derived neurotrophic factor response but not a cathepsin B response in well-trained men.

This study examined if acute multi-joint resistance exercises (RE; back squat, bench press, and deadlift) to volitional failure elicited a postexercise increase in the circulating response of biomarkers associated with neuroprotection. Thirteen males (age: 24.5 ± 3.8 years, body mass: 84.01 ± 15.44 kg, height: 173.43 ± 8.57 cm, training age: 7.1 ± 4.2 years) performed 4 sets to failure at 80% of a 1-repetition maximum on the squat, bench press, and deadlift in successive weeks. The measured biomarkers were brain-derived neurotrophic factor (BDNF), insulin-like growth factor 1 (IGF-1), cathepsin B (CatB), and interleukin 6 (IL-6). Biomarkers were assessed immediately before and 10-min after exercise. There was a main time effect (pre-exercise: 24.00 ± 0.61 to postexercise: 27.38 ± 0.48 ng/mL; p < 0.01) for BDNF with increases in the deadlift (p = 0.01) and bench press (p = 0.01) conditions, but not in the squat condition (p = 0.21). There was a main time effect (pre-exercise: 0.87 ± 0.16 to postexercise: 2.03 ± 0.32 pg/mL; p < 0.01) for IL-6 with a significant increase in the squat (p < 0.01), but not the bench press (p = 0.88) and deadlift conditions (p = 0.24). No main time effect was observed for either CatB (p = 0.62) or IGF-1 (p = 0.56). In summary, acute multi-joint RE increases circulating BDNF. Further, this investigation is the first to report the lack of a transient change of CatB to an acute RE protocol. Novelty Low-volume RE to failure can increase BDNF. Resistance training does not confer an acute Cat B response.