Background: Change-of-direction (CoD) speed is a physical fitness attribute in many field-based team and individual sports. To date, no systematic review with meta-analysis available has examined the effects of resistance training (RT) on CoD speed in youth and adults. Objective: To aggregate the effects of RT on CoD speed in youth and young physically active and athletic adults, and to identify the key RT programme variables for training prescription. Data sources: A systematic literature search was conducted with PubMed, Web of Science, and Google Scholar, with no date restrictions, up to October 2019, to identify studies related to the effects of RT on CoD speed. Study Eligibility Criteria: Only controlled studies with baseline and follow-up measures were included if they examined the effects of RT (i.e., muscle actions against external resistances) on CoD speed in healthy youth (8–18 years) and young physically active/athletic male or female adults (19–28 years). Study Appraisal and Synthesis Methods: A random-effects model was used to calculate weighted standardised mean differences (SMD) between intervention and control groups. In addition, an independent single training factor analysis (i.e., RT frequency, intensity, volume) was undertaken. Further, to verify if any RT variable moderated effects on CoD speed, a multivariate random-effects meta-regression was conducted. The methodological quality of the included studies was assessed using the physiotherapy evidence database (PEDro) scale. Results: Fifteen studies, comprising 19 experimental groups, were included. The methodological quality of the studies was acceptable with a median PEDro score of 6. There was a significant large effect size of RT on CoD speed across all studies (SMD = − 0.82 [− 1.14 to − 0.49]). Subgroup analyses showed large effect sizes on CoD speed in males (SMD = − 0.95) contrasting with moderate improvements in females (SMD = − 0.60). There were large effect sizes on CoD speed in children (SMD = − 1.28) and adolescents (SMD = − 1.21) contrasting with moderate effects in adults (SMD = − 0.63). There was a moderate effect in elite athletes (SMD = − 0.69) contrasting with a large effect in subelite athletes (SMD = − 0.86). Differences between subgroups were not statistically significant. Similar improvements were observed regarding the effects of independently computed training variables. In terms of RT frequency, our results indicated that two sessions per week induced large effects on CoD speed (SMD = − 1.07) while programmes with three sessions resulted in moderate effects (SMD = − 0.53). For total training intervention duration, we observed large effects for ≤ 8 weeks (SMD = − 0.81) and > 8 weeks (SMD = − 0.85). For single session duration, we found large effects for ≤ 30 min and ≥ 45 min (both SMD = − 1.00). In terms of number of training sessions, we identified large effects for ≤ 16 sessions (SMD = − 0.83) and > 16 sessions (SMD = − 0.81). For training intensity, we found moderate effects for light-to-moderate (SMD = − 0.76) and vigorous-to-near maximal intensities (SMD = − 0.77). With regards to RT type, we observed large effects for free weights (SMD = − 0.99) and machine-based training (SMD = − 0.80). For combined free weights and machine-based training, moderate effects were identified (SMD = − 0.77). The meta-regression outcomes showed that none of the included training variables significantly predicted the effects of RT on CoD speed (R² = 0.00). Conclusions: RT seems to be an effective means to improve CoD speed in youth and young physically active and athletic adults. Our findings indicate that the impact of RT on CoD speed may be more prominent in males than in females and in youth than in adults. Additionally, independently computed single factor analyses for different training variables showed that higher compared with lower RT intensities, frequencies, and volumes appear not to have an advantage on the magnitude of CoD speed improvements. In terms of RT type, similar improvements were observed following machine-based and free weights training.

The literature offers limited information on the effect of obesity on the rate of force development (RFD), a critical parameter for mobility in older adults. The objectives of this study were to explore the influence of obesity on the RFD in older adults and to examine the association between this neuromuscular parameter and walking speed. The participants (42 older adults) were classified into two groups: the control group (CG, n = 22; mean age = 81.13 ± 4.02 years; body mass index (BMI) = 25.13 ± 3.35 kg/m²), and the obese group (OG, n = 20; mean age = 77.71 ± 2.95 years; BMI = 34.46 ± 3.25 kg/m²). Walking speed (m/s) was measured using the 10 m walking test. Neuromuscular parameters of the plantar flexors were evaluated during a maximal voluntary contraction test using a dynamometer. The RFD was calculated from the linear slop of the force–time curve in the following two phases: from the onset of the contraction to 50 ms (RFD_0–50) and from 100 to 200 ms (RFD_100–200). The gait speed was lower in the OG compared to the CG (p < 0.001). The RFD_50/100 and RFD_100/200 were lower in the OG compared to the CG (p < 0.001). The RFD_50/100 was found to be the predominant influencer on gait speed in the OG. In conclusion, obesity negatively impacts the RFD in older adults and RFD stands out as the primary factor among the studied parameters influencing gait speed.

Aim: This study analyzed the concurrent validity of the Optojump infrared photocell system for estimating lower limb peak power by comparing it with the 15 s Wingate anaerobic test (WAnT) and examining relationships with sprint performance indicators. Methods: Twelve physically active university students (ten males, two females; age: 23.39 ± 1.47 years; body mass: 73.08 ± 9.19 kg; height: 173.67 ± 6.97 cm; BMI: 24.17 ± 1.48 kg·m⁻²) completed a cross-sectional validation protocol. Participants performed WAnT on a calibrated Monark ergometer (7.5% body weight for males, 5.5% for females), 30 s continuous jump tests using the Optojump system (Microgate, Italy), and 30 m sprint assessments with 10 m and 20 m split times. Peak power was expressed in absolute (W), relative (W·kg⁻¹), and allometric (W·kg^−0.67) terms. Results: Thirty-second continuous jump testing produced systematically higher peak power values across all metrics (p < 0.001). Mean differences indicated large effect sizes: relative power (Cohen’s d = 0.99; 18.263 ± 4.243 vs. 10.99 ± 1.58 W·kg⁻¹), absolute power (d = 0.86; 1381.71 ± 393.44 vs. 807.28 ± 175.45 W), and allometric power (d = 0.79). Strong correlations emerged between protocols, with absolute power showing the strongest association (r = 0.842, p < 0.001). Linear regression analysis revealed that 30 s continuous jump-derived measurements explained 71% of the variance in Wingate outcomes (R² = 0.710, p < 0.001). Sprint performance showed equivalent predictive capacity for both tests (Wingate: R² = 0.66; 30 s continuous jump: R² = 0.67). Conclusions: The Optojump infrared photocell system provides a valid and practical alternative to laboratory-based ergometry for assessing lower limb anaerobic power. While it systematically overestimates absolute values compared with the Wingate anaerobic test, its strong concurrent validity (r > 0.80), large effect sizes, and equivalent predictive ability for sprint performance (R² = 0.66–0.71) confirm its reliability as a field-based assessment tool. These findings underscore the importance of sport-specific, weight-bearing assessment technologies in modern sports biomechanics, providing coaches, practitioners, and clinicians with a feasible method for monitoring performance, talent identification, and training optimization. The results further suggest that Optojump-based protocols can bridge the gap between laboratory precision and ecological validity, supporting both athletic performance enhancement and injury prevention strategies.

The purpose of the study was to evaluate the reproducibility of the medicine ball explosive power test to assess explosive power in young volleyball players. Materials and methods. Data were collected using twelve volleyball players (age = 16.5 ± 0.52 years; body mass = 72.05 ± 7.9 kg; height = 182 ± 0.06 cm and body mass index = 21.63 ± 1.85) volunteered for this study. They completed a test and retest of the medicine ball explosive power test on two separate days. The medicine ball explosive power test was conducted using a 3 kg medicine ball. Testing was carried out in two separated testing session preceded by a standardized warming up protocol. The paired-sample t-test was conducted to determine the differences signification observed between the test and the retest of the medicine-ball explosive power test. The intraclass correlation coefficient (ICC1,1) aims to assess relative reliability of the test. The coefficient of variation between test and retest performance was used to check the absolute reproducibility. The Bland and Altman method was used to evaluate the relative and absolute reproducibility of the medicine ball explosive power test. Results and discussion. Explosive power is often considered as one of the main determinants of a successful high-level performance in many team sports including volleyball. It is frequently measured in different occasion during competitive season using field‐based tests. Thus, it is mandatory that strength and conditioning coaches have to use valid and reliable tests to evaluate the power for their athletes. However, contestation regarding test selection still exists grounded upon the particularity of the explosive power evaluation tests in volleyball. There was no significant difference between medicine ball explosive power test (11.08 ± 0.72 meter) and retest (11.27 ± 0.93 meter) performance. The T-paired Sample test did not show any statistically significant difference (t= 1.035; p =0.393), while the intraclass correlation coefficient aimed to assess relative reliability of the test was of 0.83. The coefficient of variation between test and retest performance was of 5.7% which is near to the 5% confidence interval level. The intraclass correlation coefficient was situated between 0.9 and 0.8 (ICC1,1 = 0.83) Thus this study suggests that the medicine ball explosive power test has moderate relative reliability level. Conclusion. The medicine ball explosive power test is reliable regardless to the age. The Bland and Altman method confirmed our finding suggesting the medicine ball explosive power test is a reliable test

The literature offers limited information on the effect of obesity on the rate of force development, a critical parameter for mobility in older adults. The objectives of this study were; to explore the influence of obesity on RFD in older adults and to examine the association between this neuromuscular parameter and walking speed. 42 older adults were classified into two groups: the control group (CG, n=22; age=81.13±4.02 years; Body mass index (BMI)=25.13±3.35 kg/m²), and the obese group (OG, n=20; age=77.71±2.95 years; BMI=34.46±3.25 kg/m²). Walking speed (m/s) was measured using the 10-meter walking test. Neuromuscular parameters of the plantar flexors were evaluated during a maximal voluntary contraction test using a dynamometer. The RFD was calculated from the linear slop of the force – time curve in two phases: from the onset of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200). The gait speed was lower in the OG compared to the CG (p

Background: The rate of force development (RFD) plays a pivotal role not only in preventing falls but also in ensuring successful completion of many functional tasks that demand swift muscle power rather than prolonged strength. Despite its importance, there is limited compre-hensive research on the relationship between RFD and walking speed, especially in older adults with Sarcopenic Obesity (SO). Objective: to investigate the influence of obesity on neuromuscular markers in older adults with SO and to assess the relationship between neuromuscular markers and gait speed in older adults with SO. Methods: a cohort of 42 participants was categorized based on their BMI into two groups: the sarcopenic non-obese group (CG, n=22; age=81.13±4.02; BMI=25.13±3.35) and the sarcopenic obese group (SOG, n=20; age=77.71±2.95; BMI=34.46±3.25). Gait speed was measured using a 10-meter test. Additionally, the isometric strength of the plantar flexor muscles was assessed during maximal voluntary contractions. Absolute Peak force (aPeak, N) were documented at intervals of 50 ms (a50, N), 100 ms (a100, N), and 200 ms (a200, N), subsequently normalized to body mass (r50, r100, r200, N). The RFD was derived in two phases: from the start of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200) and calculated from the linear slop of the force – time curve (Δ force/Δ time). Conclusion: Obesity negatively impacts neuromuscular markers in older adults. Notably, RFD emerges as the dominant factor influencing gait speed, accounting for an impressive 51% of its variability, far surpassing the impact of relative peak force. This underscores the imperative of evaluating neuromuscular health in older adults with SO to provide insights into mobility out-comes.