Introduction/purpose: Previous results about shoe longitudinal bending stiffness (LBS) and running economy (RE) show high variability. This study aimed to assess the effects of shoes with increased LBS on RE and performance in trained and national runners. Methods: Twenty-eight male runners were divided into two groups according to their 10-km performance times (trained, 38–45 min and national runners, <34 min). Subjects ran 2 × 3 min (at 9 and 13 km·h⁻¹ for trained, and 13 and 17 km·h⁻¹ for national runners) with an experimental shoe with carbon fiber plate to increase the LBS (Increased LBS) and a control shoe (without carbon fiber plate). We measured energy cost of running (W·kg⁻¹) and spatiotemporal parameters in visit one and participants performed a 3000 m time trial (TT) in two successive visits. Results: Increased LBS improved RE in the trained group at slow (11.41 ± 0.93 W·kg⁻¹ vs 11.86 ± 0.93 W·kg⁻¹) and fast velocity (15.89 ± 1.24 W·kg⁻¹ vs 16.39 ± 1.24 W·kg⁻¹) and only at the fast velocity in the national group (20.35 ± 1.45 W·kg⁻¹ vs 20.78 ± 1.18 W·kg⁻¹). The improvements in RE were accompanied by different changes in biomechanical variables between groups. There were a similar improvement in the 3000 m TT test in Increased LBS for trained (639 ± 59 vs 644 ± 61 s in control shoes) and national runners (569 ± 21 vs 574 ± 21 s in control shoes) with more constant pace in increased LBS compared with control shoes in both groups. Conclusions: Increasing shoe LBS improved RE at slow and fast velocities in trained runners and only at fast velocity in national runners. However, the 3000 m TT test improved similarly in both levels of runners with increased LBS. The improvements in RE are accompanied by small modifications in running kinematics that could explain the difference between the different levels of runners.

A breakpoint in a portable near-infrared spectroscopy (NIRS) derived deoxygenated haemoglobin (deoxy[Hb]) signal during an incremental VO2max running test has been associated with the second ventilatory threshold (VT2) in healthy participants. Thus, the aim was to examine the association between this breakpoint (NIRS) and VT₂ in well-trained runners. Gas exchange and NIRS data were collected during an incremental VO_2max running test for 10 well-trained runners. The breakpoint calculated in oxygen saturation (StO₂) and the VT₂ were determined and compared in terms relative to %VO_2max, absolute speed, VO₂, and maximum heart rate (HRmax). There were no significant differences (p>0.05) between the breakpoint in StO₂ and VT₂ relative to %VO_2max (87.00±6.14 and 88.28 ± 3.98 %), absolute speed (15.70±1.42 and 16.10±1.66 km·h⁻¹), VO₂ (53.71±15.17 and 54.66±15.57 ml·kg⁻¹·min⁻¹), and%HRmax (90.90±4.17 and 91.84±3.70%). There were large and significant correlations between instruments relative to%VO_2max (r=0.68, p<0.05), absolute speed (r=0.86, p<0.001), VO₂ (r=0.86, p<0.001), and %HR_max (r=0.69; p<0.05). A Bland and Altman analysis of agreement between instruments resulted in a mean difference of − 1.27±4.49%, −0.40±0.84 km·h⁻¹,−0.90±3.07 ml·kg⁻¹·min⁻¹, and − 0.94±3.14 for %VO_2max, absolute speed, VO_2, and %HR_max, respectively. We conclude that a portable NIRS determination of the StO₂ breakpoint is comparable with VT₂ using gas exchange and therefore appropriate for use in determining exercise training above VT₂ intensity. This is the first study to analyze the validity with the running mode using a NIRS portable device. Received: 01 August 2020 Accepted: 14 December 2020 Publication Date: 01 February 2021 (online) © 2021. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany

We analysed the effects of the Nike ZoomX Vaporfly (VPF) on long‐interval training performance, kinematic parameters, running power and fatigue compared to a traditional running shoe. Twelve well‐trained men (mean ± SD: 32.91 ± 7.50 years; 69.29 ± 7.55 kg and 172.73 ± 5.97 cm) performed two long‐interval training sessions (5 × 1000 m with 90s recovery period) 7 days apart, with the VPF shoe or a traditional running shoe (CON) in random order. The countermovement jump (CMJ) height was measured before and after the training sessions and heart rate, spatiotemporal parameters, running power and leg stiffness was measured during training sessions. Running‐related pain was assessed prior and post‐24 h of each training session. Long‐interval training performance improved 2.4% using the VPF shoe compared to CON (p = 0.009; ES = 0.482). Step length, contact time and leg stiffness were higher (p < 0.05; ES = 0.51, ES = 0.677, ES = 0.356) while flight time was lower (p < 0.001; ES = 0.756) when using VPF. Running power decreased in a similar way in both conditions throughout the training session. Vertical power was significantly higher in the VPF condition (p = 0.023, ES = 0.388). CMJ height decreased in both conditions after training (4.7 vs. 7.2%, for the VPF and control, respectively, p < 0.001; ES = 0.573). Finally, the perceived muscle pain was influenced by the shoe model condition (chi‐square 5.042, P = 0.025). VPF shoes improved the long‐interval training performance with similar running power, heart rate and neuromuscular fatigue, and reduced subjective perceived muscle pain compared to regular training shoes.

This study aimed to evaluate the validity and reliability of a wearable device and a phone application for measuring spatiotemporal parameters and their relationship with running economy (RE) by comparing them with photocell data in runners of different abilities. Twenty-three male runners were divided into well-trained and recreational groups and performed a 4-min running bout at 17 and 13 km·h^-1 respectively. During the bout, were measured the spatiotemporal parameters with three devices (Stryd, Runmatic, and Optojump) and RE with a gas analyser. Pearson correlation showed perfect relationships for stride frequency (SF) and stride length (SL) between the devices, and moderate for flight time (FT) and contact time (CT). There were no correlations between the spatiotemporal parameters and RE measurements. Coefficient of variation was ~ 5% in all devices for CT, SF, and SL, and higher for FT (15-24%). CT was underestimated (15-16% with Runmatic and Stryd, respectively) and FT was overestimated (36-40%) compared to Optojump. Bland-Altman plots revealed that Runmatic could be a more accurate system than Stryd. In conclusion, both devices were valid tools for measuring spatiotemporal parameters during running at RE speed. Runmatic was more valid and reliable in comparison with Stryd. In addition, at lower running speeds the devices showed less reliability.

Objective: This study aims to evaluate the effects of a 20-week endurance and strength training program on running economy and physiological, spatiotemporal, and neuromuscular variables in trained runners. Methods: A total of 18 runners (13 males and 5 females) completed a running economy test (2 bouts of 5 min at 3.06 m·s⁻¹ for females and at 3.61 m·s⁻¹ for males) and a graded exercise test (5 min at 2.78 m⋅s⁻¹, with speed increasing by 0.28 m⋅s−1 every 1 min until volitional exhaustion). During the training program, the participants completed different low-intensity continuous running sessions, high-intensity interval running sessions, and auxiliary strength training sessions. Results: Running economy, measured as oxygen cost and energy cost, increased by 4% (p = 0.011) and 3.4% (p = 0.011), respectively. Relative maximal oxygen uptake (VO_2max) increased by 4.6%. There was an improvement in the speed associated with the first (VT₁) and the second ventilatory threshold and with the maximal aerobic speed by 9.4, 3.7, and 2.8% (p = 0.000, p = 0.004, and p = 0.004, respectively). The %VO_2max value of VT₁ increased by 4.8% (p = 0.014). Conclusions: These findings suggest that a 20-week endurance and strength training program significantly improves performance and physiological factors without changing the runner’s biomechanics.

Objective: This study evaluated the effects of advanced footwear technology (AFT) spikes on running performance measures, spatiotemporal variables, and perceptive parameters on different surfaces (track and grass). Methods: Twenty-seven male trained runners were recruited for this study. In Experiment 1, participants performed 12 × 200 m at a self-perceived 3000 m running pace with a recovery of 5 min. Performance (time in each repetition), spatiotemporal, and perceptive parameters were measured. In Experiment 2, participants performed 8 × 5 min at 4.44 m/s while energy cost of running (W/kg), spatiotemporal, and perceptive parameters were measured. In both experiments the surface was randomized and mirror order between spike conditions (Polyether Block Amide (PEBA) and PEBA + Plate) was used. Results: Experiment 1: Runners were faster on the track (p = 0.002) and using PEBA + Plate spike (p = 0.049). Experiment 2: Running on grass increased energy cost (p = 0.03) and heart rate (p < 0.001) regardless of the spike used, while PEBA + Plate spike reduced respiratory exchange ratio (RER) (p = 0.041). Step frequency was different across surfaces (p < 0.001) and spikes (p = 0.002), with increased performance and comfort perceived with PEBA + Plate spikes (p < 0.001; p = 0.049). Conclusions: Running on the track surface with PEBA + Plate spikes enhanced auto-perceived 3000 m running performance, showed lower RER, and improved auto-perceptive comfort and performance. Running on grass surfaces increased energy cost and heart rate without differences between spike conditions.