Objectives: This study aimed to explore the effects of four days of Rhodiola Rosea (RR) supplementation on bench-press and bench-pull exercises under resting or mental fatigue conditions in young healthy individuals. Methods: Eighteen participants (seven women) visited the laboratory on five occasions separated by 7 days—one preliminary session and four experimental sessions. In the preliminary session, participants were familiarised with the Stroop and Multiple Object Tracking tests, after which their one-repetition maximum loads for bench presses and bench pulls were determined. The four experimental sessions had the same protocol, differing only in the supplement (RR or placebo) and mental task conditions (Stroop test or control video). Participants were assigned randomly and counterbalanced to each experimental condition: (I) RR and Stroop test, (II) RR and control video, (III) placebo and Stroop test, and (IV) placebo and control video. Results: The main findings indicate that RR supplementation has trivial-to-small effects in terms of mental fatigue, visuo-cognitive processing, or perceived exertion. However, RR was significantly superior to placebo on strength performance in the control video condition during some sets, as it increased the number of repetitions performed in the bench press and the fastest velocity in the bench pull. Out of 52 comparisons, 17 small effect sizes were observed, with 14 favouring RR and 3 favouring placebo, with the remaining differences being trivial. Conclusions: These results suggest that short-term RR supplementation is safe and provides its main ergogenic effects on physical performance rather than in visuo-cognitive or mental outcomes.

This systematic review with meta-analysis evaluated whether individualized training programs tailored to an athlete’s F-V profile were more effective than non-individualized programs (i.e., without considering the athlete´s F-V profile) in decreasing F-V imbalances and enhancing jump height and maximal power (Pmax). A literature search was conducted in PubMed, Web of Science, EBSCO and Cochrane Library databases from inception until April 19th 2024. Pooled meta-analysis and subgroup meta-analysis were performed using the random-effects and fixed-effects models. The individualized training program was more effective at reducing the F-V imbalance compared to the non-individualized training program (SMD = 0.59 [95%, p < 0.001), but no significant differences were reached for jump height (SMD = 0.50, p = 0.059) and Pmax (SMD = 0.10, p = 0.543). Regarding subgroup analyses, differences were found only between the velocity-deficit subgroup and the non-individualized group with the former showing greater reductions in the F-V imbalance (SMD = 1.28, p < 0.001) and greater improvements in jump height (SMD = 0.77, p = 0.010), but no significant differences were noted for Pmax (SMD = 0.40, p = 0.165). No significant differences in the F-V imbalance, jump height or Pmax were obtained between force-deficit and well-balanced subgroups compared to the non-individualized group. Individualized training programs are more effective at reducing F-V imbalances than non-individualized programs because they target specific segments of the F-V profile. However, pooled evidence suggests that individualized training is only more effective at enhancing jump height for athletes experiencing a velocity-deficit at the start of the training program.

Since the load-velocity relationship was validated as a useful tool for assessing fatigue, its reliability and reproducibility have yet to be established, which are crucial for programming training plans and monitoring athletes’ physiological status. Therefore, this study aimed to explore the acute effects of resistance training fatigue on load-velocity (L-V) relationship variables (maximal theoretical force capacity [ L ₀ ], maximal theoretical velocity capacity [ v ₀ ], and maximal theoretical power capacity [A _line ]) under different set configurations and whether the fatigue was reproducible. Fourteen male athletes performed back squats at 80% of their one repetition maximum under 20% velocity loss across three sets configurations (6, 4, and 3 sets), with each configuration performed twice. L-V relationship variables were established in pre-fatigue and 15 min post-fatigue for all sessions. Fatigue resulted in significant decline in v ₀ （F = 27.084, p < 0.001）and A _line （F = 72.552, p < 0.001）, but not in L ₀ (F = 0.466, p = 0.508). The three set configurations produced similar fatigue levels for all L-V relationship variables. The effects of fatigue on L-V relationship variables were reproducible in all set configurations for all variables (ICC ≥ 0.759, CV ≤ 9.3%). The findings suggest that, under a fixed 20% VL, the acute effects of L-V relationship variables were reproducible from resistance training fatigue, no matter how many training sets were applied. Hence, the L-V relationship variables are a reliable tool to measure acute resistance training fatigue.

This study aimed to determine which task (jumping or sprinting) and which force-velocity (F-V) relationship parameter (maximal force [F0], maximal velocity [v0], or maximal power [Pmax]) is the most sensitive indicator of fatigue induced by a basketball-specific protocol. Following a familiarization session, 19 junior male basketball players completed an experimental session in which both vertical (jumping) and horizontal (sprinting) F-V profiles were measured before, during and after undergoing a basketball-specific fatigue protocol (modified version of the Loughborough Intermittent Shuttle Test). All F-V relationship parameters, except horizontal F0 (p = .328), were significantly reduced after fatigue (p ≤ .042). The vertical Pmax (ES = -0.48 to -0.80), horizontal Pmax (ES = -0.58 to -1.28), and horizontal v0 (ES = -0.81 to -0.98) showed larger reductions compared to the pre-fatigue assessment than the vertical v0 (ES = -0.19 to -0.27), vertical F0 (ES = -0.16 to -0.25), and horizontal F0 (ES = -0.11 to -0.30). When the percentage changes with respect to the pre-fatigue assessment were compared between the jumping and sprinting tasks, no significant differences in their magnitude (p ≥ .364) and trivial to small correlations (-0.23 ≤ r ≤ 0.19) were detected. The results suggest that Pmax is the most suitable parameter to detect fatigue following a basketball-specific fatigue protocol, while the lack of significant correlations for the changes in F-V relationship parameters highlight the importance of measuring both the vertical and horizontal F-V profiles to gain comprehensive understanding of the changes in the mechanical properties of lower-body muscles following fatigue protocols.

Introduction: The purpose of this study was to assess whether bench press load-velocity (L-V) relationship variables serving as indicators of maximal theoretical force capacity ( L ₀ ), maximal theoretical velocity capacity ( v ₀ ), and maximal theoretical power capacity (A _line ), as well as the softball-specific performance metrics (hit and throw distance), could be used to effectively monitor the selective fatigue induced by two different bench press training protocols. Methods: The bench press L-V relationship variables and softball-specific performance metrics of 12 professional female softball players were measured on three separate occasions: (I) following passive rest (non-fatigue condition), (II) after light-load ballistic bench press throw (LLB), and (III) after heavy-load traditional bench press (HLT). Additionally, blood lactate and rating of perceived exertion (RPE) were assessed after LLB and HLT training protocols. Results: A significantly lower v ₀ , A _line and hit distance were found after both training protocols ( p ≤ 0.008), with the LLB protocol revealing a higher fatigue compared with the HLT protocol. However, the change of L-V relationship variables and softball-specific performance metrics (0.15 ≤ ES ≤ 1.05) were not as sensitive as that of blood lactate and RPE (1.30 ≤ ES ≤ 1.78). Discussion: Hence, changes in mechanical performance could be applied as a supplementary monitoring tool to be integrated into athletes’ daily routines, but should not be considered replacements for traditional fatigue indicators.