Nicolas Flores
email: nicolas.flores@decathlon.com

Guillaume Rao

Eric Berton

Delattre

Increasing the longitudinal bending stiffness of runners' habitual shoes: an 2 appropriate choice for improving running performance?

Keywords: footwear, running shoes, shoe flexibility, longitudinal bending stiffness, running 18 economy, subject-specific, performance. 19

17 Purpose: This study analysed the effects of increasing the longitudinal bending stiffness 18 (LBS) of runners' habitual shoes on the metabolic energetic demand, lower limb muscle 19 activations, and stride spatiotemporal parameters during a prolonged running session through 20 classical group investigation and a more individualised approach.

1 run remain unknown. This question was recently partially addressed, 24 by showing that an 2 increased shoe LBS induced a delay in the distal-to-proximal work redistribution during 3 prolonged running. These authors suggested that using proximal muscles with greater volume 4 (i.e. quadriceps) should be more detrimental than using distal muscles with lower volume (i.e. 5 triceps surae). 25 Because the running economy was not measured in this previous study, 24 6 the metabolic benefits attributed to an increased shoe LBS during prolonged running remain 7 speculative. 8 While a lot of useful and relevant information is available regarding the LBS effects 9 on the metabolic demand and the running biomechanics during short duration, 19 only 10 assumptions can be made concerning the metabolic effects of the LBS during longer running 11 exposure where only the running biomechanics was measured. 24 The current study aimed to 12 investigate these previous independent findings in the same study. The purpose was to analyse 13 the effects of increasing the longitudinal bending stiffness of runners' habitual shoes on 14 metabolic demand, lower limb muscle activations, and stride spatiotemporal parameters 15 during a prolonged running session through classical group investigation and a more 16 individualised approach. Based on the assumption from Cigoja et al. 24 , it was hypothesised 17 that an increased shoe LBS would limit and/or delay the increase in metabolic energetic 18 demand. As highlighted in numerous studies, 12,13,17,20-22 it was expected that the benefits 19 induced by an increased shoe LBS would also be participant-specific, especially according to 20 individual characteristics and/or biomechanical changes induced by an increased LBS relative 21 to their shoe habits. 2 Eleven male novice runners (Table 1), stating running at least once a week and being able to 3 run for one hour at least at 10 km/h, volunteered to participate in the experiment. All 4 participants gave their written informed consent to all the procedures performed during the 5 experiment that were in accordance with the university ethical rules. The participants stated 6 being healthy and free from injury in the previous year.

7 Shoe conditions 8 Two shoe conditions were used in this study. The control shoe condition was the participants' 9 own running shoes (Table 1 and Supplementary material A), that they used during their usual 10 running activity (low LBS). The use of participants' own running shoes should permit 11 observation of their habitual running biomechanics without being influenced by unfamiliar 12 shoe features 26 other than the LBS investigated in the study. The second shoe condition was 13 obtained by the addition of thin (0.9 mm) stiff straight carbon plates under the insoles of the 14 participant's own running shoes (high LBS). One size of carbon plates has been used, and we 15 ensured that the plates were functionally well inserted in all the participants' shoes to not 16 induce discomfort during running. The shoe LBS (Table 1) was measured with a mechanical 17 manual bending test (see Supplementary material B for full details about the procedure) based 18 on the study of Worobets and Wannop 27 . The high LBS condition was on average 263±89% 19 stiffer than the low LBS. To answer to the current study's purpose concerning the choice to 20 increase the LBS in runners' habitual shoes (with associated advantages and disadvantages), 21 the shoe mass was not equalised between both shoe conditions. Thus the high LBS conditions 22 (317 g on average) were 20 g per shoe heavier due to the carbon plate than the low LBS 23 conditions (297 g on average). 1 near here *** 2 Experimental protocol 3 The experiment was composed of three sessions performed on three different days with at 4 least 48 hours rest between each session. From the welcome of the participant to the end of 5 the session, the first session lasted 1 hour and both subsequent sessions each lasted 2 hours.

6 On average, the three sessions were performed within 11 days.

7

In the first session, an incremental test was performed. The test started with a 5-min 8 warm-up of running at 1.94 m/s with participants' own running shoes on a treadmill (Saturn 9 300/100r, h/p/cosmos, Germany) with 1% slope gradient. The speed was then increased by 10 0.28 m/s every minute. An open-circuit expired-gas analysis system (K5, Cosmed, Italy) 11 recorded breath-by-breath the rate of oxygen uptake (VȮ 2 ) and the rate of carbon dioxide 12 production (VĊO 2 ). The device was calibrated before each test with a reference gas 13 containing known concentrations of oxygen and carbon dioxide, using a 3.0 L syringe to 14 ensure an accurate volume air measurement. The incremental running test aimed to identify 15 the ventilatory anaerobic threshold (VAT) for each participant. The VAT was identified 16 through the onset increase of ventilation versus oxygen uptake ratio (VĖ/VȮ 2 ) and end-tidal 17 partial pressure of oxygen (P ET O 2 ), in the presence of still decreasing or constant ventilation 18 versus carbon dioxide production ratio (VĖ/VĊO 2 ) and P ET CO 2 . 28 The speed equal to 95% of 19 the speed that elicited VAT was kept for each participant and was imposed in both subsequent 20 sessions of prolonged running.

21

The subsequent sessions were performed on the field to consider realistic road running 22 conditions while keeping as much as possible of the data quality. The participants ran for a 23 prolonged duration with either the low LBS or the high LBS shoe condition, in a randomised 24 order. Due to potential fatigue accumulation, a prolonged running session was dedicated to 1 only one shoe condition, thus the low and high LBS shoe conditions were performed during 2 separate sessions. Each participant performed both sessions at the same time of day. In each 3 session, the experimental protocol was identical. The participants were equipped with the 4 expired-gas analysis system, which was calibrated before each session as described above, 5 and surface electromygrams (EMG; Trigno Avanti, Delsys, Massachusetts, USA), which were 6 used to record muscle activations at 1926 Hz. After skin preparation, the EMG electrodes 7 were located according to the recommendations of surface electromyography for the non-8 invasive assessment of muscles (SENIAM) at the level of superficial muscles vastus lateralis 9 (VL), gastrocnemius medialis (GM), and tibialis anterior (TA). The SENIAM procedure for 10 sensor placement was reproduced as accurately as possible by the same researcher between 11 both sessions. The three sensors were firmly secured with a medical adhesive strap to avoid 12 any artifacts due to sweating, vibrations, displacement, or detachment of the sensors 13 throughout the entire duration of the experiments. The EMG sensors were connected to a 14 datalogger (Trigno Personal Monitor, Delsys, Massachusetts, USA) located in an armband, 15 thus allowing wireless EMG acquisitions during the outdoor prolonged run. A watch (Fenix 3, 16 Garmin, Kansas, USA) paired with an accelerometer mounted on a heart rate strap (HRM-17 Run, Garmin, Kansas, USA) was used to measure accelerations of the upper body from which 18 were computed the stride cadence, the ground contact time, and the vertical oscillation of the 19 upper body. 29 To obtain day-specific respiratory reference values, the participants first 20 performed 5 min sitting at rest on a chair without moving or speaking. Finally, the participants 21 ran continuously for 40 min outdoor over a loop with hard concrete surface (Supplementary 22 material C) at the targeted speed identified in the first session (imposed speed visually 23 controlled with ground marks in each 20 m and a metronome). Gas exchanges data, EMG 24 data, and spatiotemporal data were recorded during the whole duration of the experiment. 1 The VȮ 2 , the VĊO 2 , the respiratory exchange ratio (RER), and the ambient temperature were 2 measured from the open-circuit expired-gas analysis system. For each subject, the averaged 3 VȮ 2 and the VĊO 2 during the last minute of the sitting rest were subtracted from those 4 measured during the prolonged run to offset the day-specific respiratory reference values of 5 the participants between both sessions. Then, the net metabolic energetic cost of running was 6 computed from caloric equivalent based on the Péronnet and Massicotte 30 equation and 7 expressed in net metabolic power (W/kg). The net energetic cost of running, the RER, and the 8 ambient temperature were averaged during 1 min for seven time intervals: from 9 to 10 min 9 (baseline measurement), from 14 to 15 min, from 19 to 20 min, from 24 to 25 min, from 29 to 10 30 min, from 34 to 35 min, and from 39 to 40 min.

11

The EMG data were band-pass filtered [10-400 Hz] with a zero time-lag fourth order 12 Butterworth filter to remove signal noise and artifacts. Then, these data were rectified and 13 low-pass filtered at 15 Hz with a critically damped filter to smooth the signal. 31 For each 14 muscle, activations were normalised by the maximal activation recorded in the seven time 15 intervals during the session. For each time interval, this normalised EMG signal was 16 integrated during the entire minute. Because of EMG sensor location (on muscles, thus on 17 wobbling masses) and the range of accelerometry measurements from EMG sensors (±2 g), 18 the accelerometer signal was too noisy to accurately identify heel strike and toe off events. 19 The integration of EMG activations thus took into account both aerial and stance phases. Data 20 of GM activations is missing for participant 3 in the low LBS condition and participant 10 in 21 both LBS conditions, likely due to the fact that the left foot in the aerial phase hit the 22 supporting right leg where the GM sensor was located, thus disconnecting this sensor. A 23 firmer protection than the medical strap or the recording of another triceps surae muscle 24 would enable avoiding such an issue. Raw data measured by the torso strap sensor were saved in the watch and then 2 imported on Garmin Connect software. This software automatically computed the stride 3 cadence, ground contact time, and vertical oscillation of the upper body from raw data, which 4 were saved on '.fit' files. These '.fit' files were imported on Golden Cheetah software (v3.3.0) 5 to extract the computed data at each second of the prolonged running in a more conventional 6 '.txt' format. The flight time (in seconds) was computed from the measured stride cadence 7 and ground contact time (in seconds), and the vertical and leg stiffnesses were also computed 8 based on ground contact and flight times. 32 The stride cadence, the ground contact time, the 9 vertical oscillation of upper body, the vertical stiffness, and the leg stiffness were averaged 10 during 1 min for the seven time intervals. Data of stride spatiotemporal parameters is missing 11 for participant 1 in the low LBS condition and participant 4 in the high LBS condition due to 12 an issue while saving raw data. 13 Individual data were then reorganised to allow the investigation of the individual 14 beneficial or detrimental metabolic effects induced by the increase of the LBS in the 15 participant's habitual shoes during a prolonged run. For each participant, the metabolic, EMG, 16 and stride spatiotemporal data induced by the high LBS condition were subtracted to those 17 induced by the low LBS condition. This procedure has been done for the seven time intervals 18 for all the variables. At a given time interval, negative or positive values thus respectively 19 indicated that an increased LBS in the participant's habitual shoes induced decreased (i.e. 1 Due to some issues during the experiments, statistical analyses were performed on 9 2 participants for the GM activations and spatiotemporal parameters, and on 11 participants for 3 all other variables. 4 Classical group-based investigation 5 ANOVA assumptions (normality and homogeneity of residuals) were met for the VL 6 activations, the cadence, and the ground contact time, thus a two-way repeated measures 7 ANOVA (α=0.05) was used to evaluate the main effects of 'LBS' and 'running duration' 8 factors, and the interaction of these factors, on these variables. All other variables were non-9 parametrically analysed with a permutation procedure (α=0.05), which was performed 10 through the Matlab open-source code (v.0.4.3, http://www.spm1d.org). The permutation 11 procedure consists of calculating the test statistic F values for a large number of re-orderings 12 (i.e. permutations) of the observations (i.e. data). For example in our data, one permutation 13 consists in permuting an observation induced by a given shoe condition for a given participant 14 at a given time interval with another observation induced by the other shoe condition for a 15 given participant at a given time interval. For each permutation, the test statistic F value is 16 computed. This results in a number of F values equal to the total number of permutations, 17 which tends to generate a Gaussian distribution of the frequency of F values. Then, the critical 18 test statistic threshold (F*) is computed as the 95 th percentile of this distribution to ensure that 19 only α=5% of all permutations exceed the F*. If the F value computed from the original 20 observations exceed F*, this provides sufficient evidence to reject the null hypothesis (i.e. 21 observing a significant effect). 33 The partial omega squared (ω p ²) effect size was finally 22 computed and interpreted as: trivial effect ≤ 0.02 < small effect ≤ 0.13 < medium effect ≤ 0.26 23 < large effect. 34 When a significant main effect of running duration or the interaction between the LBS 2 and the running duration was observed, post-hoc pairwise comparisons were made between 3 the baseline and subsequent time intervals through the 'emmeans' package on RStudio 4 (v.3.4.1, Massachusset, USA). This resulted in six post hoc comparisons, thus the alpha level 5 was corrected as α=0.05/6=0.008.

6

All the statistical results (two main factors and interaction) are presented in the results 7 section, but for the purpose of the study, only those concerning the LBS main factor and the 8 interaction between the LBS and the running duration are discussed. 9 Individual approach 10 A correlation approach was used in an exploratory way by screening for potential candidate 11 variables partially involved in the variation of the net energetic cost of prolonged running 12 when the shoe LBS was investigated. This enabled to understand in which conditions a given 13 individual was more able to benefit from a shoe LBS intervention. 2 The speed equal to 95% of the speed that elicited VAT in the incremental test, which was 3 imposed during the prolonged running, was 3.11±0.19 m/s on average (Table 1). The RER 4 was lower than 1 for all the participants indicating that the aerobic metabolism was the main 5 contributor of the energetic cost of running. The ambient temperature was not significantly 6 different between both sessions (low LBS session: 26.9±0.2°C; high LBS session: 7 27.3±0.2°C; p=0.704). The running duration induced a significant decrease in TA activations (F 6,60 =4.18; 13 p=0.003; ω p ²=0.22, medium effect; Figure 2), where TA activations were significantly lower 14 from 39 to 40 min compared to baseline from 9 to 10 min (p=0.006). No significant main 15 effect of the running duration was observed on all other variables (p>0.05; Figure 1, Figure 2, 16 and Figure 3). The simplest view of the individual metabolic results (both last lines in Table 2) 21 showed that an increased LBS in the runners' habitual shoes was detrimental for most of the 22 participants (7 vs. 4) in two time intervals at the beginning and in two time intervals at the end 1 of the run, whereas in three middle time intervals of the run the number of participants 2 benefiting from an increased LBS was slightly greater (6 vs. 5). Furthermore, 2 runners 3 always benefited from an increased LBS of their habitual shoes (participants 2 and 4), 4 4 runners always benefited from their habitual shoes (participants 8, 9, 10, and 11), and 5 5 runners randomly benefited either from their habitual shoes or an increased LBS throughout 6 the prolonged running duration (right column in Table 2). This non-homogeneous 7 participants' responses was revealed by a non-significant Chi-Square test (χ²=0.09; p>0.05) 8 indicating that the number of participants benefiting from the low or high LBS (n=6) or those 9 uncleared (n=5) was not different than what would be expected if there was no effect of shoe 10 LBS (50% of beneficiaries and 50% of unclear in the sample of participants). This result 11 strengthens the individual approach to highlight in which conditions a given individual was 12 more able to benefit from a shoe LBS intervention. An increase of the LBS in runners' habitual shoes did not induce a significant effect 15 on the net energetic cost during the prolonged running. This result was not in line with the 16 initial hypothesis, which was based on the only one study 24 that has investigated the shoe 17 LBS effect during prolonged running. By measuring a delay in the distal-to-proximal joint 18 work redistribution during a prolonged submaximal run under the anaerobic threshold, this 19 previous study suggested that an increased shoe LBS might have beneficial repercussions on 20 the metabolic demand. At similar running intensity (95% of the VAT), we did not observe 21 such supposed metabolic benefits on the mean group of participants. This running intensity 22 may have been too low to increase the net energetic cost of prolonged running (i.e. inducing 23 fatigue). As previously recommended, 36 the used running intensity allowed an appropriate 1 calculation of the energetic cost of running, while taking account the aerobic metabolism as 2 the main contributor to the metabolic demand (RER < 1). If an increased shoe LBS really acts 3 in a beneficial way by limiting or delaying the onset of the energetic cost increase, this 4 putative beneficial effect could be observed in presence of fatigue. Future studies using 5 similar running intensity than in the current one should thus consider longer running duration 6 (> 40 min) to potentially induce VȮ 2 drift and thus fatigue. As it is, the lack of average effect 7 of the shoe LBS on the metabolic demand was in line with almost all the previous studies 8 using shorter duration of running. 13-17 9 All the variables were analysed from a baseline set to 9 min of running (about 1.7 km 10 based on the imposed speed of 3.11 m/s on average). This baseline was set to only measure an 11 eventual effect of the LBS in the duration of the prolonged running, while avoiding measuring 12 the adaptation effects due to reaching a steady-state VȮ 2 , 37 a stable biomechanical 13 pattern, 38,39 a stable neuromuscular system, 40 or stable mechanical shoe properties. 41 14 Likely stabilised following this adaptation period, all the measured variables were unaffected 15 by the shoe LBS. This is different from what can be expected from previous studies as an 16 increased shoe LBS was known to have several influences on the running biomechanics. 19 17 Therefore, at the group level, further assumptions can be made from the current prolonged 18 running. The physiological and biomechanical effects of an increased LBS may not occur at 19 all, or occur too early during this adaptation period, or be too subtle to be measured with 20 enough resolution on the field, or may not be systematic between the participants.

21 Individual approach 22 The time-courses of all the measured variables during the prolonged running were 23 highly participant-specific within-session and between-session (Figure 1, Figure 2, and Figure At baseline of the prolonged run, the correlations showed that an increased shoe LBS 12 was less able to induce detrimental metabolic effect if this shoe intervention decreased (or did 13 not increase) the ground contact time, increased (or did not decrease) the body vertical 14 oscillation, or increased (or did not decrease) the TA activations relative to the runners' 15 habitual shoes with lower LBS. These results were surprising as an increased shoe LBS was 16 reported to induce longer ground contact time, 19 and because the metabolic demand has been 17 shown to be inversely proportional to the ground contact time 42 (regardless of any shoe 18 intervention). Willwacher et al. 43 suggested that an increased ground contact time with an 19 increased shoe LBS may reflect a weakness of strength capability of the ankle plantarflexors. 20 On this basis, the current runners might not be strong enough to benefit from such LBS 21 increase in their habitual shoes. On the other hand, the change of LBS may be functionally too 22 different from the habitual shoes of some runners to maintain their habitual biomechanical 23 pattern. As a result, unusual adjustments in the stride spatiotemporal parameters may have 24 occurred to meet the requirements of the experiment, while inducing a greater energetic cost. The ground contact time is generally inversely associated with the body vertical 2 oscillation and the aerial time. 44 This may explain why the variations of the ground contact 3 time and the body vertical oscillations were simultaneously identified as explanatory variables 4 in the correlations. This may explain why the variation of TA activations was also an 5 explanatory variable. Indeed, with the TA muscle being mainly activated during the aerial 6 phase (Supplementary material E), the greater TA activations identified as less detrimental in 7 the correlations should be due to a consequence of longer activation durations during longer 8 aerial phases (due to shorter ground stance phases) rather than greater activation magnitudes. 9 At the last time interval of the prolonged run, the greater the participants' height, the 10 lower the detrimental metabolic effects induced by an increased shoe LBS. Why the 11 participants' height may potentiate the metabolic effects of an increased shoe LBS was 12 unknown, but some hypotheses are presented. Greater height may imply greater mass and/or 13 greater body segment lengths. Additional correlation analyses confirmed this for the mass 14 (p=0.002; r=0.82) and the shoe size used as surrogate indicator of foot length (p=0.034; 15 r=0.64), although both these variables did not directly correlate with the variation of the net 16 energetic cost induced by an increased shoe LBS in the current study. It has been shown that 17 the greater the participants' mass, the greater the metabolic benefits induced by an 18 intermediate increase of shoe LBS. 12 The taller runners, and also the heavier, were thus less 19 affected by an increased LBS. Greater shoe size may imply greater forefoot bone length, 20 likely resulting in a greater lever arm of the ground reaction force relative to MTP and ankle 21 joint centers (i.e., gearing effect) during push-off. 45 This gearing effect, amplified by the high 22 LBS shoes, 43 may favour lower excursion of muscle fibres and slower shortening velocity of 23 the triceps surae muscle. 17,46 These muscle responses have been associated with lower According to the instant of the prolonged run, different explanatory variables were 4 involved in the participant-specific metabolic effects induced by an increased shoe LBS. This 5 could be due to the observed variability in the time-courses of the physiological and 6 biomechanical variables between the participants. Similar variability has previously been 7 reported during prolonged running where spatiotemporal parameters can either increase, 8 decrease, or remain constant over time depending on the runner. 48,49 Because there was no 9 unique time-course of the biomechanical pattern over time (with or without shoe 10 intervention), a given correlation observed at an initial time interval of the run may not remain 11 at a later time interval because the correlated variables did not evolve similarly for each 12 runner. Furthermore, an increased shoe LBS may affect runners differently in a fatigue state 13 than in a non-fatigue state. This induced even more variability in the time-courses of the 14 physiological and biomechanical variables between the participants. This assumption seemed 15 to be corroborated with the number of participants benefiting from an increased shoe LBS 16 throughout the prolonged run. This number of participants followed an inverted "U-shape" 17 where the greatest number of participants benefiting from an increased LBS (n=6) occurred at 18 the half of the prolonged running. Before and after, a lower number of participants benefited 19 from an increased shoe LBS (n=4).

20

This study had some limitations highlighted for readers. While the current protocol 21 included a prolonged running session close to the VAT, the running duration and/or intensity 22 were not important enough to induce an increase in the net energetic cost (i.e. inducing 23 fatigue) in any of the shoe LBS conditions. The habitual shoe of the runners have been used, 24 which may differ in several features not measured, such as midsole foam viscoelasticity, sole 1 geometry, or shoe mileage. Thus, the beneficial (or detrimental) effects of an increased LBS 2 for some runners may have been potentiated by the appropriate (or not) interaction with these 3 other shoe features. 50 The difference in mass between both shoe LBS conditions (20 g on 4 average) may have slightly influenced the metabolic results by about 0.2% based on the 5 relationship between shoe mass and metabolic demand. 51 A point of awareness was that the 6 results came from two different prolonged running sessions performed in two different days 7 with low or high LBS shoes. In order to offset the results obtained from two different days, 8 physiological data were normalised by the day-specific respiratory reference values of the 9 participants recorded during a sitting rest before each running session. Nevertheless, it cannot 10 be ensured that the current results, while reflecting individual variations in responses to LBS 11 interventions, were not influenced by other unwanted effects. Furthermore, EMG results may 12 have been influenced by EMG placement between sessions thus it cannot be definitively 13 ensured that the sensors were exactly placed in the same location between both sessions.

14 Although firmly secured with medical straps, the sensors' abilities to record muscle 15 activations could have been affected by the accumulation of sweat. This study had a small 16 sample size resulting in low statistical power regarding the net energetic cost of prolonged 17 running (1-β=0.28 for the LBS main effect; 1-β=0.40 for the interaction effect). A post hoc 18 power analysis (G*Power v3.1.9.4) showed that, for achieving at least 0.80 power, 45 and 24 19 participants would have been needed to rule-out the Type II error possibilities for the LBS 20 main effect and the interaction effect, respectively. In correlation analyses, considering large 21 correlations (r<-0.5 or r>0.5) on 11 participants with an alpha level set to 0.1 resulted in 0.50 22 statistical power (while 23 participants would have been needed to achieve at least 0.80 23 power). 35 Therefore, findings from this study should be considered with caution. We would 24 suggest the future studies to include the explanatory variables highlighted in the current study 25 (i.e. ground contact time and height). This would enable to investigate shoe LBS effects with 1 more powerful experimental designs on the explanatory variables highlighted in the current 2 study. As it is, the current findings are suitable for male novice/recreational runners. As the 3 height (in this study) and the mass 12 are explanatory variables of the metabolic demand, it is 4 hypothesised that female runners may require a shoe LBS tuning different from males due to 5 their morphological specificities.

7 Conclusion

8 To the question: "is it an appropriate choice to increase the longitudinal bending stiffness in 9 habitual shoes of runners for improving performance?", the answer from this study would be: 10 "it depends". At a mean group level, an increased shoe LBS did not limit and/or delay the 11 increase of the net metabolic energetic cost during a prolonged running. However, participant-12 specific metabolic (beneficial or detrimental) effects induced by an increased LBS have been 13 highlighted. These participant-specific metabolic effects were associated with the variation of 14 the ground contact time at the beginning and the height of the participants at the end of the 15 prolonged run. The results of this study increased the body of knowledge concerning the 16 potential explanatory variables associated with specific metabolic effects of shoe LBS. 17 However, future studies are still needed to be able to recommend, with more certainty, the 18 appropriate increase of shoe LBS to a given runner who needs it, based on his individual 19 characteristics and/or biomechanics. Indeed, the metabolic effects of an increased LBS were 20 more detrimental than the use of habitual shoes with lower LBS for most of the participants in 21 the current study. This study thus suggested that a shoe LBS intervention was likely not 22 beneficial for performance purposes if the runners' shoe habits were too much disrupted. 1 Authors would thank Romain Hardouin for his help during the configuration of EMG record 2 and during EMG data export. Authors also thank all the participants for taking part to these 3 three sessions of running. Finally, authors thank Dr. Eleni Grimpampi for her English review 4 of the manuscript.

  22

  20 better running economy) or increased (i.e. poorer running economy) net energetic cost of 21 running, and decreased or increased muscle activations and spatiotemporal responses, 22 compared to a lower habitual LBS.

14

  Pearson correlations were performed, at the first and the last time interval of the 15 prolonged run, between the individual variations of the net energetic cost of running induced 16 by an increased LBS and ten potential explanatory variables. These potential explanatory 17 variables were the individual variations of the cadence, the body vertical oscillation, and the 18 ground contact time induced by an increased LBS, the individual variations of the TA, the 19 GM, and the VL activations induced by an increased LBS, the participants' mass, height, 20 speed and the relative increase of the shoe LBS.21The correlations kept for results and discussion sections should combine p<0.1 with a 22 large effect size. A large effect size was identified by a Pearson regression coefficient (r) 23 lower than -0.5 or greater than 0.5. 35

8*

  ** Figure 1 near here *** 9 Classical group-based investigation 10 No significant main effect of LBS or interaction effect of LBS and running duration was 11 observed on any of the variables (p>0.05; Figure 1, Figure 2, and Figure 3).

  12

  17 *** Figure 2 near here *** 18 *** Figure 3 near here *** 19 Individual approach 20

  13*** Table2near here *** 14 Based on the criteria set in the statistical section, four significant correlations were 15 identified during the prolonged running (Figure4; see Supplementary Material D for more 16 results).

  17

  At baseline (from 9 to 10 min), the individual variation of the net energetic cost of 18 running induced by an increased LBS was correlated with the individual variation of the 19 ground contact time (p=0.067; r=0.63), the individual variation of the body vertical oscillation 20 (p=0.070; r=-0.63), and the individual variation of TA activations (p=0.094; r=-0.53) induced 21 by an increased LBS. 22 At the last time interval (from 39 to 40 min), the individual variation of the net 23 energetic cost of running induced by an increased LBS was correlated with the height of the 24 participants (p=0.019; r=-0.69).

4

  For the first time, this study investigated the effects of increasing the LBS of runners' habitual 5 shoes on metabolic demand, lower limb muscle activations, and stride spatiotemporal 6 parameters during a prolonged running session, through classical group investigation and a 7 more individualised approach. Over the mean group of participants, the shoe LBS had no 8 effect on the metabolic energetic demand. Nevertheless, participant-specific metabolic 9 energetic responses to an increased LBS have been highlighted. Depending on the time 10 interval of the prolonged run, these participant-specific metabolic responses were correlated 11 with the variations of spatiotemporal parameters or muscle activations induced by an 12 increased LBS, and with the participant's height.13 Classical group-based investigation 14

  . This lack of non-systematic individual responses might be one explanation to the non-2 significant effects of the shoe LBS at the group level. The observed individual variability was 3 in line with several studies highlighting participant-specific effects of the shoe LBS according 4 to the task characteristics, 18 the participants' characteristics 12,20 and biomechanics. 13,21,22 5 In the current study, correlation analyses were used on individual variations induced by an 6 increased shoe LBS to highlight such potential associations. It can be noted that in our sample 7 of participants, an increased LBS mainly induced unclear (5 out of 11 runners) and 8 detrimental (4 out of 11 runners) metabolic effects. The correlations were thus interpreted in 9 terms of « less detrimental metabolic effect » rather than « more beneficial metabolic effect » 10 induced by an increased shoe LBS. 11

  cost, 47 especially in participants benefiting from an increased shoe LBS 2 when surrogate measures were used. 13,22 3

5 6

 5 Declaration of interest statement7 NF and ND are members of the company Decathlon TM in the research department. NF, GR, 8 EB, and ND declared that the results of the study are presented clearly, honestly, and without 9 fabrication, falsification, nor inappropriate data manipulation. Nigg BM. Influence of midsole bending stiffness on joint energy and 13 jump height performance.

89 13 Figure 3 .Figure 4 .

 1334 Figure 2. Time-course of the activations of TA, GM, and VL muscles during the prolonged 10 running duration with low (left) and high (right) LBS shoes. Data of GM activations is 11 missing for participants 3 and 10. * indicated a significant main effect of the running duration.12 Time-courses of the stride cadence, the body vertical oscillation, the ground contact 14 time, the leg stiffness, and the vertical stiffness during the prolonged running duration with 15 low (left) and high (right) LBS shoes. Data is missing for participants 1 and 4. 16 17 Correlations between the individual variations of the net energetic cost induced by 18 an increased LBS in participants' habitual shoes and the individual variations of the ground 19 contact time (top left), the body vertical oscillation (top right), the TA activations (bottom 20 left) induced by an increased LBS, and the participants' height (bottom right). Dark and grey 21 points respectively indicated the participants benefiting from the high LBS and low LBS 22 condition, while white points indicated unclear participants (based on Table2). Data is 23 missing for participants 1 and 4 for spatiotemporal variables.

Figure 1 .

 1 Figure captions

Figure 2 .

 2 Figure 2. Time-course of the activations of TA, GM, and VL muscles during the prolonged running duration with low (left) and high (right) LBS shoes. Data of GM activations is missing for participants 3 and 10. * indicated a significant main effect of the running duration.

Figure 3 .

 3 Figure 3. Time-courses of the stride cadence, the body vertical oscillation, the ground contact time, the leg stiffness, and the vertical stiffness during the prolonged running duration with low (left) and high (right) LBS shoes. Data is missing for participants 1 and 4.

Figure 4 .

 4 Figure 4. Correlations between the individual variations of the net energetic cost induced by an increased LBS in participants' habitual shoes and the individual variations of the ground contact time (top left), the body vertical oscillation (top right), the TA activations (bottom left) induced by an increased LBS, and the participants' height (bottom right). Dark and grey points respectively indicated the participants benefiting from the high LBS and low LBS condition, while white points indicated unclear participants (based on Table2). Data is missing for participants 1 and 4 for spatiotemporal variables.

Figure A .

 A Figure A. Pictures of the participant's habitual running shoes. The order of the shoes corresponds to the order of participants in each Table or Figure of the main document. The last picture is the stiff carbon plate used in this study.

  Procedure of the mechanical bending testA shoe last was cut at the metatarsophalangeal joint level (70% of the shoe last length) to remove the anterior part. This shoe last was inserted inside the shoe. The shoe was then secure upside down on a horizontal plate from its posterior part with a clamp. The anterior ending of the shoe last inside the shoe (B) was identified and marked on the external part of the shoe (FigureB), and then marked on a graph paper perpendicularly located to the bending axis of the shoe forefoot. A horizontal straight line was drawn through B on the graph paper. A hook was then set on the shoe outsole at the anterior ending of the shoe. Either no mass (m=0 kg), or m masses of 1 kg, 2 kg, and 3 kg were hung along the hook. The location of the hook (H) was also marked on the graph paper (Figure B). A vertical straight line was drawn through H on the graph paper, which cut perpendicularly the horizontal straight line in a point O (Figure B). The length of [BO] m , in meters, was the lever arm of the force applied by each m mass relative to the bending axis. The moment (M m , in Nm, equation B1) applied to the anterior part of the shoe was thus computed as: (B1) g being the gravity constant value equal to 9.81 m/s² and m being the mass equal to 0 kg, 1 kg, 2 kg, and 3 kg. The length of [OH] m , in meters, was the vertical displacement of the anterior part of the shoe due to the applied moment of force (for m=0 kg, the length [OH] 0 was the height of the curvature of the anterior part of the shoe, i.e. the toe spring). The bending angle (, in deg, equation B2) of the shoe was computed as: (B2) Finally, the bending stiffness value (in Nm/deg) was obtained through the slope of a linear regression fitting the four force moments (M m ) and bending angles ( ) plotted on a 𝐵 𝑚 moment-angle graph.

Figure B .Figure C .

 BC Figure B. Schema illustrating the identification of the point of the anterior ending of the shoe last inside the shoe (or bending axis, B), the location of the hook after a mass was hung (H), and the lever arm of the force applied by the mass relative to the bending axis (O) for the low (grey) and high (dark) longitudinal bending stiffness shoe conditions.

  Figure E. Typical VL (yellow), GM (red), and TA (blue) raw activations during a running cycle. Vertical doted lines represented estimations of instants of heel strike (HS) and toe-off (TO).

  Med Sci Sports Exerc 2000; 32: 471-476. Franz JR, Wierzbinski CM, Kram R. Metabolic Cost of Running Barefoot versus Shod. Time-course of the net metabolic energetic cost during the prolonged running 3 duration with low (left) and high (right) LBS shoes. Participants with long dotted lines had 4 lower energetic cost during the prolonged run with the low LBS shoes, those with full lines 5 had lower energetic cost during the prolonged run with the high LBS shoes, and those with 6 short dotted lines had randomly lower energetic cost during the prolonged run either with low 7 or high LBS shoes (see Table2for corresponding data).

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21 5. Hébert-Losier K, Finlayson SJ, Driller MW, et al. Metabolic and performance 22 responses of male runners wearing 3 types of footwear: Nike Vaporfly 4%, Saucony http://mc.manuscriptcentral.com/(site) 8 17. Cigoja S, Fletcher JR, Esposito M, et al. Increasing the midsole bending stiffness of 9 shoes alters gastrocnemius medialis muscle function during running. Sci Rep 2021; 11: 10 749. 11 18. Day E, Hahn M. Optimal footwear longitudinal bending stiffness to improve running 12 economy is speed dependent. Footwear Sci 2019; 1-11. 13 19. Ortega JA, Healey LA, Swinnen W, et al. Energetics and Biomechanics of Running 14 Footwear with Increased Longitudinal Bending Stiffness: A Narrative Review. Sport 15 Med 2021; 51: 873-894. 16 20. Oh K, Park S. The bending stiffness of shoes is beneficial to running energetics if it 17 does not disturb the natural MTP joint flexion. J Biomech. Epub ahead of print 18 2 Figure 1.

Table 2 )

 2 . Data is missing for participants 1 and 4 for spatiotemporal variables.

	1
	F
	o r
	P
	e e r
	R e v
	i e w

Table 1 .

 1 Characteristics of the participants and participants' own running shoes (see 2 supplementary material A for pictures of the shoes).

	Participant	Height (cm)	Mass (kg)	Speed at 95% of VAT (m/s)	Shoe brand and version	Shoe size (EU size)	Shoe mass (g)	Low LBS (Nm/deg)	High LBS (Nm/deg)
	1	172.1	63.1	3.19	Nike Lunar Launch	44	246	0.070	0.233 (+231%)
	2	177.2	75.6	2.92	Mizuno Wave Inspire 9	44	312	0.114	0.306 (+168%)
	3	176.0	74.2	3.19	Nike Air Max	45	325	0.043	0.156 (+260%)
	4	182.1	82.3	3.33	Nike Free Run 2	44	343	0.027	0.148 (+454%)
	5	175.3	67.8	3.19	Asics Gel Innovate	44	286	0.057	0.206 (+263%)
	6	177.0	68.3	3.19	Adidas Tubular	43	268	0.038	0.124 (+225%)
	7	170.2	61.0	2.92	Kalenji Active Trail	41	257	0.099	0.398 (+304%)
	8	180.4	78.4	3.19	Adidas Boost Supernova 9	44	338	0.067	0.162 (+143%)
	9	168.2	58.2	2.78	Brooks Aduro 4	42	278	0.083	0.287 (+246%)
	10	176.0	86.8	2.92	Adidas Terrex	45	352	0.047	0.149 (+220%)
	11	170.0	64.9	3.33	Mizuno Wave Elixir 7	42.5	257	0.041	0.196 (+377%)
	Mean	175.0	71.0	3.11		43.5	297	0.062	0.215 (+263%)
	SD	4.4	9.2	0.19		1.5	39	0.027	0.084 (89%)
	3

Table 2 .

 2 Individual (absolute and relative) variations of the net energetic cost of running 2 induced by an increased LBS at each time interval of the prolonged running. Negative (dark 3 grey cell) or positive (light grey cell) values respectively indicated that an increased LBS in 4 the participant's habitual shoes induced decreased or increased net energetic cost of running 5 compared to their lower habitual LBS. A beneficial shoe condition was unclear if negative 6 and positive values were combined for a given participant.

				∆ net energetic cost (W/kg)
	Participants	From 9 to 10 min	From 14 to 15 min	From 19 to 20 min	From 24 to 25 min	From 29 to 30 min	From 34 to 35 min	From 39 to 40 min	Beneficial shoe condition
	1	0.16 1.1%	-0.98 -6.5%	-0.80 -5.2%	-0.94 -6.1%	-0.45 -3.0%	-0.23 -1.5%	-0.15 -0.9%	Unclear
	2	-1.94 -14.4%	-0.74 -5.8%	-1.17 -9.0%	-1.15 -8.7%	-1.07 -8.2%	-0.71 -5.4%	-0.69 -5.4%	High LBS
	3	0.76 5.4%	0.24 1.7%	-0.43 -2.9%	0.19 1.3%	-0.24 -1.7%	0.25 1.7%	0.19 1.2%	Unclear
	4	-0.60 -4.3%	-1.03 -7.4%	-1.62 -11.3%	-1.78 -12.2%	-3.18 -21.9%	-3.13 -20.9%	-3.95 -26.2%	High LBS
	5	-0.28 -1.8%	0.19 1.2%	-0.47 -2.8%	-0.02 -0.2%	-0.26 -1.6%	0.56 3.6%	0.96 6.5%	Unclear
	6	1.61 11.1%	1.29 8.8%	0.27 1.7%	-0.20 -1.3%	0.09 0.6%	-0.19 -1.3%	-0.11 -0.8%	Unclear
	7	-1.31 -8.5%	-0.68 -4.4%	-0.25 -1.6%	-0.06 -0.4%	-0.47 -2.9%	0.50 3.5%	1.34 9.4%	Unclear
	8	0.82 6.3%	1.06 8.4%	1.68 13.1%	0.49 3.8%	1.33 10.9%	0.38 3.0%	0.46 3.8%	Low LBS
	9	3.11 30.3%	3.08 29.1%	3.11 28.9%	2.51 22.6%	1.85 16.2%	1.46 12.7%	1.25 10.3%	Low LBS
	10	0.89 8.3%	1.17 10.8%	0.84 7.7%	1.18 10.8%	1.47 13.5%	1.54 14.1%	1.58 14.6%	Low LBS
	11	1.02 7.1%	1.67 11.7%	1.74 12.5%	1.86 13.1%	1.99 13.9%	1.24 8.7%	1.74 12.1%	Low LBS
	Number of
	participants
	benefiting from low	7	7	5	5	5	7	7
	LBS (∆ net energetic
	cost>0)
	Number of
	participants
	benefiting from high	4	4	6	6	6	4	4
	LBS (∆ net energetic
	cost<0)

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