The popularity of distance running has increased over the past decade. In the United States, the number of half-marathon finishers has grown from 482,000 in the year 2000 to 1,900,000 in 2016.1 Runners strike the ground 600 times per kilometer on average, increasing the incidence of running-related repetitive stress injuries.2,3 van Gent et al2 reported 19.4% to 79.3% of runners sustain at least one running-related injury per year. Due to the high prevalence and reoccurrence rates of running-related injuries, runners, coaches, and health professionals are continually searching for ways to reduce the risk of injury, increase a runner’s injury-free longevity, and improve running performance. Although several running-related injury risk factors has been proposed, the capacity of the lower limb joints to control the forces that occur when the foot initially strikes the ground is a commonly recognized factor and is a primary target of injury prevention approaches.4
Understanding how the foot makes contact with the ground has important implications, as the foot is the only body segment that has direct interaction with the ground during running. Foot strike pattern (FSP), which describes the way a runner’s foot collides with the ground, can be categorized into 3 techniques: rearfoot strike (RFS), where the heel contacts the ground first; midfoot strike (MFS), where the heel and ball of the foot land at the same time; and forefoot strike (FFS), where the ball of the foot contacts the ground first.3,5 The type of FSP used by a runner dictates the magnitude and rate of loading generated by ground reaction forces that the body must repeatedly handle during running. Some researchers have contended that higher loading rates, in general, are associated with joint cartilage degradation and lower-extremity injuries, such as patellofemoral pain syndrome, iliotibial band friction syndrome, tibial stress syndrome, plantar fasciitis, Achilles tendonitis, and meniscal injuries of the knee.6 More recently, Schmida et al reported that the vertical loading rate was not associated with running injury, suggesting that horizontal loading rates or other gait parameters, such as the magnitude of the impact force or step rate (SR), are better predictors of running injuries.7,8 Runners who habitually FFS generate impact forces, 3 times lower than RFS runners.3 Furthermore, the rate of loading is higher in the rearfoot strikers when compared to the midfoot and forefoot strikers.3,5,9 However, FFS running places an increased demand on the forefoot, arch of the foot, and Achilles tendon from the impact forces generated during running. FFS running relies on the elastic energy of tendons, ligaments, and muscles, for force absorption, which can increase a runner’s susceptibility to Achilles tendonitis or metatarsal injuries.3,5,9,10 Alternatively, a RFS pattern places increased demand on the ankle, knee, and hip joints, using the skeletal structures of the lower-extremity to absorb the impact forces created by the heel contacting the ground during running.3,10 In support of this, a retrospective study reported that rearfoot strike runners have double the rate of repetitive stress injuries than FFS runners despite inconsistent conclusions in several studies.11,12 While the kinematics and kinetics of MFS patterns can vary, they generally display characteristics that fall between those of FFS and RFS, with moderate initial impact forces and a balanced distribution of loading across the foot compared to the more localized loads seen in FFS or the distinct impact peaks in RFS.13 While there are advantages and disadvantages to different FSPs, changes to non-RFS are generally professed to be more promising as they relate to impact-related injury prevention and rehabilitation.3,5,9,14
SR, the number of steps a runner takes per minute, has also been studied as a means of reducing the risk of running-related injury and improving running performance.15,16 A small increase in one’s preferred SR has been shown to reduce step length, center of mass vertical excursion, impact loading forces, and the amount of energy the lower-extremities must absorb during running.15–19 Additionally, SR manipulation can be used as a method of retraining a runner’s FSP from RFS to MFS or FFS with as little as a 10% increase in SR.19 Furthermore, SR manipulation has been suggested as a practical method that can be used to retrain running gait in a clinical environment by utilizing cues from a metronome.19 Therefore, the adoption of an increased SR has been suggested as a strategy to reduce the risk of running-related injuries or assist in rehabilitation from an existing injury.15,20,21
In addition to injury prevention, FSPs and SRs have been examined as a means to improve running performance through changes in running economy (RE).10,22-24 RE, the oxygen cost of running at a given velocity, has a strong relationship with distance running performance and is a better predictor of running performance than VO2max.25 For example, de Ruiter et al26 reported that running cost (oxygen consumption per kg body weight per distance covered) at optimal stride frequency was higher in novice than trained runners, and the disparity between optimal and self-selected stride frequency was greater in novice versus trained runners. More elite performers are less likely to heel strike, although the effects of FSP on marathon performance are still inconclusive.27,28 Furthermore, several studies that have measured RE during different FSP conditions have reported mixed results, with some observing differences in RE between forefoot and RFS, while others have found no significant difference.10,22,23,29,30 However, we hypothesized that changing SR would result in changes to both FSP and RE due to the biomechanical implications of different FSPs. Specifically, we posited that RFS tends to result in longer ground contact times, which may require more time to manage external forces, and consequently, necessitate greater muscular activation and energy expenditure. Therefore, increasing SR and shifting FSP toward the forefoot was expected to increase RE, while decreasing SR and shifting FSP toward the rearfoot was expected to decrease RE.
Previous research indicates that between 88.9% and up to 95.1% of all recreational runners are RFSs, underscoring the importance of considering running mechanics and techniques for injury prevention and performance enhancement.31–33 Changing FSP through SR manipulation may be helpful in reducing running-related injuries in recreational runners and simultaneously optimizing RE. However, previous research is lacking in regard to the effect that SR has on FSPs in recreational runners with various FSPs, and it is unclear if a shift in FSP takes place as a result of increases or decreases in SR from each individual’s preferred SR. Moreover, the concomitant effects of SR and FSP on RE in recreational runners has not been previously tested.15,16 Therefore, the objective of this study was to examine the acute effects of manipulating a runner’s preferred SR by a magnitude of −10%, −5%, +5%, and + 10% on their FSP and RE in recreational runners. We hypothesized that FSP would shift toward the front of the foot and RE would improve (ie, decrease) as the SR increases, and FSP would shift toward the heel of the foot and RE would worsen (ie, increase) as the SR decreases. The results of this study will help address the utility of including SR manipulation as part of a gait retraining program in recreational runners.
Methods
Participants
A total of 18 healthy recreational runners were recruited from the local community and university setting via campus flyers and word of mouth. A power analysis was performed using the G*Power software (version 3.1.9.7, Kiel University). Based on data from a previous study which examined the effects of SR manipulation on joint mechanics during running,16 an a priori power calculation was conducted using foot contact angle as the primary outcome variable with the following parameters: α = .05, 1 − β = 0.80, and Cohen d = 0.71. The expected effect size was determined based on the outcome values reported in the previous study, and the effect size corresponds to a medium-to-large effect, according to Cohen guidelines. The power analysis indicated that a total of 14 participants would be required. To account for an anticipated dropout rate of approximately 25%, it was determined that 18 participants would be required.
Participants were eligible for inclusion in the study if they could be classified as recreational runners with at least 3 months of running experience and were not competing for any team in marathon or distance running races.34,35 Those who sustained any running-related lower-extremity injury preventing them from running in the previous 3 months were excluded. Before involvement in this study, all participants provided written informed consent, and demographic data were collected. Participants’ demographic and training characteristics are presented in Table 1. The study protocol was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board.
Participants’ Demographic and Training Characteristics
| Mean (SD) | |
|---|---|
| Age, y | 30.2 (7.6) |
| Gender (male:female) | 9:9 |
| Height, cm | 171.7 (11.4) |
| Mass, kg | 71.8 (13.6) |
| Shoe type | |
| Neutral | 7 (38.9%) |
| Lightweight/neutral | 1 (5.6%) |
| Minimalist/neutral | 3 (16.7%) |
| Stability | 7 (38.9%) |
| FSP | |
| RFS | 10 (55.6%) |
| MFS | 6 (33.3%) |
| FFS | 2 (11.1%) |
| SR, steps/min | 168.8 (11.3) |
| Run experience, y | 2.4 (1.4) |
| Miles per week | 15.6 (6.2) |
| Days per week | 3.4 (1.0) |
Abbreviations: Days per week, number of days each participant runs per week; FFS, fore-foot strike; FSA, foot strike angle; FSP, foot strike pattern; MFS, mid-foot strike; miles per week, number of miles run per week; RFS, rear-foot strike; run experience, cumulative total number of years running; shoe type, type of shoe worn during training and during experiment, which was determined from manufacturers description of shoe type; SI, strike index; SR, step rate.
Procedures
This study used a single-blind within-group research design. Two pieces of athletic tape were placed on each participant’s left shoe in the following locations: forefoot (fifth metatarsal head) and rear foot (calcaneus, slightly lateral to the most posterior bony prominence), to be used as an anatomical reference point used to calculate FSP. A high-speed digital camera (Casio, Exilim EX-F1; sample rate = 60 Hz) was positioned at 8.5 m from the object points, and at an approximate height of each participant’s left foot to record the lateral side of the left lower leg. The video camera was scaled and zoomed for each condition so that images of interest were as large as possible. In this study, we analyzed the left foot, assuming healthy participants with no injury or disease would have no significant biomechanical differences between the left and right legs during running, as supported by pervious research.36
A treadmill speed of 6 mph (2.68 m/s), which was used for all testing conditions, was selected as it falls within the moderate-intensity range commonly used in studies of recreational runners.37 To avoid any potential impact from sudden footwear changes, participants were instructed to wear the running shoes they typically used during their regular training sessions. Prior to testing, participants were asked to run on a treadmill (NordicTrack 9600, ICON Health & Fitness) for 6 minutes, at a speed of 2.68 m/s, serving as a warm-up/familiarization session. The participant’s preferred SR was calculated during the third and sixth minutes of the warm-up session by visually counting left foot strikes for 30 seconds and then multiplying the number by 4. After the warm-up/familiarization session, a rest period of 5 minutes was provided, and a Hans Rudolph breathing valve and headgear were fitted to measure VO2. For the data collection phase, participants ran under 5 SR conditions, which were randomly assigned using Random Allocation Software: preferred, −10%, −5%, +5%, and +10%.38 Each SR condition was 6 minutes in duration and separated by a 5-minute rest period. The SR was adjusted by having participants match each step to a digital audio metronome created in MatLab (MathWorks). A researcher provided feedback if a participant was poorly matching the step to the metronome sound. Submaximal VO2 data were collected for the last 3 minutes of each SR condition using a metabolic cart (TrueOne 2400, ParvoMedics Inc).
Data Analysis
Once testing was completed, video data for each participant and condition were analyzed twice by 2 researchers independent of each other to determine the interassessor consistency for computing the foot strike angle (FSA). FSA is defined as the angle of the foot in the sagittal plane with respect to the ground at initial foot contact while running, minus the foot angle at standing.5 A video recorded for 5 seconds before the warm-up session was used to capture each participant’s standing FSA. FSA in each SR condition was analyzed during minutes 2:50 to 3:00 and 5:50 to 6:00 during each 6-minute SR condition using a video analysis software (Kinovea version 0.9.5, Kinovea) that utilizes a digital goniometer positioned on the shoe markers to compute angles with a precision of 1° increments (Figure 1). The excellent test–retest reliability (intraclass correlation coefficients [ICC] = .98–.99) was determined via a pilot study, and intrarater reliability (ICC = .96–.99) of Kinovea software used for measuring FSA have been reported in previous studies.39,40 To determine the FSP, a regression equation developed by Altman and Davis (predicted strike index = [FSA − 27.4]/−0.39) was used to calculate the strike index (SI), the gold standard in quantifying FSP.5 SI is a measure of the location of the center of pressure from the heel of the foot as a percentage of total foot length at initial foot contact with the ground. A SI of 0% to 33%, 34% to 67%, and 68% to 100% indicates RFS, MFS, and FFS, respectively (Figure 1). Ten FSAs for each SR condition were averaged for further analysis to predict a single SI. Measures of submaximal VO2 (mL·kg−1·min−1) were computed between minutes 3:30 and 5:30 of each 6-minute SR condition and averaged within each condition to determine RE.
FSA and SI. (A) FSA measured using the Kinovea software; (B) SI to quantify FSP (RFS: 0%–33%, MFS: 34%–67%, FFS: 68%–100%). FFS indicates fore-foot strike; FSA, foot strike angle; FSP, foot strike pattern; MFS, mid-foot strike; SI, strike index; RFS, rear-foot strike.
Citation: Journal of Sport Rehabilitation 2025; 10.1123/jsr.2024-0261
Statistical Analysis
Interassessor consistency was calculated using the ICC2,k. A minimal acceptable ICC value of .80 was set to meet FSA agreement standards from previous research.41 The effects of SR conditions (preferred, −10%, −5%, +5%, and + 10%) on SI and VO2 were separately examined. Given the small sample size of this study, the Shapiro–Wilk test was performed to assess the normality of the data. Because some of the variables did not follow a normal distribution, nonparametric statistical tests were employed. Specifically, the Friedman test was used to examine differences among the SR conditions for these variables. If the Friedman test showed significant results, post hoc pairwise comparisons were conducted using Wilcoxon signed-rank tests, focusing only on the comparisons involving the preferred SR. To control for multiple comparisons a Bonferroni correction was applied, adjusting the significance threshold to 0.0125. To evaluate the significance of statistical differences, effect sizes for the Friedman test were computed using Kendall W, while rank-biserial correlation (r) was used for the post hoc Wilcoxon signed-rank tests. In both cases, effect sizes were interpreted as 0.1 = small effect, 0.3 = moderate effect, and 0.5 or above = large effect. The alpha level was set to .05, and all statistical analyses were performed in RStudio (version 1.2.5033).
Results
The interassessor consistency analyses revealed a mean ICC(2,k) of .97 (P < .001), suggesting excellent agreement between assessors for computing the FSA. The Friedman test revealed a statistically significant difference in SI across the 5 SR conditions (preferred, −10%, −5%, +5%, and + 10%), χ2(4) = 52.89, P < .001, with a large effect size of Kendall W = 0.73, indicating a substantial impact of SR manipulation on SI. After applying a Bonferroni correction (adjusted alpha = .0125), pairwise comparisons revealed significant differences between the preferred SR and the −10% SR (z = −3.11, P = .002, r = .73), −5% SR (z = −3.07, P = .002, r = .72), and +10% SR (z = −3.59, P < .001, r = .85) conditions. However, the difference between the preferred SR and the +5% SR was no longer statistically significant after the correction (z = −1.98, P = .05, r = .47). The FSAs, predicted SIs, and FSPs in all SR conditions are presented in Table 2 and Figure 2.
Foot Strike Characteristics
| FSA | SI | FSP | |
|---|---|---|---|
| −10% SR | 15.96 (8.94) | 29.33 (22.92) | RFS |
| −5% SR | 14.29 (7.92) | 33.61 (20.31) | MFS |
| Preferred SR | 12.32 (7.91) | 38.66 (20.27) | MFS |
| +5% SR | 11.22 (8.08) | 41.50 (20.73) | MFS |
| +10 SR | 8.57 (9.02) | 48.29 (23.13) | MFS |
Abbreviations: FSA, foot strike angle; FSP, foot strike pattern; MFS, mid-foot strike; RFS, rear-foot strike; SI, strike index; SR, step rate.
SI for each SR condition. *Significantly different from preferred SR; P < .05. SI indicates strike index; SR, step rate.
Citation: Journal of Sport Rehabilitation 2025; 10.1123/jsr.2024-0261
The Friedman test revealed a statistically significant difference in RE across the 5 SR conditions (preferred, −10%, −5%, +5%, and +10%), χ2(4) = 32.70, P < .001, with a large effect size of Kendall W = 0.45, indicating a substantial impact of SR manipulation on RE. Pairwise comparisons showed a significant decrease in RE between the preferred SR and the −10% SR (z = −3.64, P < .001, r = .86) and −5% SR conditions (z = −3.03, P = .002, r = .71). However, there were no significant differences between the preferred SR and the +5% SR (z = −.90, P = .37, r = .21) and +10% SR conditions (z = −.63, P = .53, r = .15). Oxygen consumptions in all SR conditions are presented in Figure 3.
Oxygen consumption during each SR condition. *Significantly different from preferred SR; P < .05. SR indicates step rate.
Citation: Journal of Sport Rehabilitation 2025; 10.1123/jsr.2024-0261
Discussion
To our knowledge, this is the first study to examine the concurrent effects of SR on SI, FSP, and RE in recreational runners. The main objective was to examine whether a SR manipulation by ±5% or ±10% of recreational runners preferred SR was sufficient to shift their SIs and FSPs and produce changes in the rate of submaximal VO2 (RE). We hypothesized that SI may increase and RE may decrease, as SR increases and vice versa. Our findings partially supported the hypothesis as SI was significantly lower at −10% and −5% and higher at + 10% SR conditions, and submaximal VO2 was significantly higher at −10% and −5% SR conditions.
The predicted SI measurements in the current study displayed an overall tendency for recreational runners to use anterior foot contact as SR increases and vice versa. It indicates that acute SR manipulations may be an effective gait retraining tool for shifting the location of center of pressure during foot strike. This observation was especially prominent during SRs at −10%, −5%, and +10% from the preferred SR where −24.14%, −13.06%, and +24.91% changes in SI from the preferred SI were observed. While these percentage changes in SI may or may not represent categorical shifts in FSP due to the broad range of each FSP category, the consistent trend observed indicates that SR manipulation does influence foot strike behavior in a predictable manner. These findings are in line with several previous studies that reported a decreased FSA during increased SR conditions and an increased FSA during decreased SR conditions.16,19 Not only did the observed changes in FSA follow the same directional trends, but the magnitude of these changes was also comparable to those reported in previous work, demonstrating similar levels of variation in FSA across different SR manipulations. For example, in the study by Heiderscheit et al,16 changes in FSA were reported as −43.64%, −20%, +40%, and + 78% for the −10%, −5%, +5%, and + 10% SR conditions, respectively.16 Similarly, Allen et al19 observed changes of +24.25% and +35.51% in FSA for the +5% and +10% SR conditions, respectively.19 Furthermore, according to the predicted SIs, 8 out of 18 participants (44%) shifted their preferred FSP to a new FSP (eg, rearfoot to midfoot or midfoot to rearfoot) with SR manipulations. It was also identified that the magnitude of change in FSP was greater in the decreased SR conditions than in the increased SR conditions. Thus, if a change in FSP is desired, a more drastic SR manipulation may be required to shift a runner’s foot strike more forward and a less drastic change in SR may be required to move a runner’s foot strike more toward the heels of their feet.
A recent meta-analysis reported that rearfoot strikes place significantly higher biomechanical loads on the knee and patellofemoral joints, whereas FFSs impose higher biomechanical loads on the ankle joint and Achilles tendon.42 Thus, a change in FSP induced by SR manipulations may help reduce injury risk, especially if a runner is predisposed to certain injuries due to their running technique. However, this should be approached carefully and only after determining the etiology of each individual’s running-related injuries. Novice recreational runners with training errors (eg, excessive mileage, rapid change in intensity, a sudden increase in running distance) are particularly vulnerable to running-related injuries.43 In such cases, manipulating SR to alter their FSP may reduce the strain on the injured or vulnerable structures, thereby allowing the runners to recover more effectively continue participating in running activities. Although over 95% of recreational runners are RFSs, current evidence does not sufficiently support the relationship between FSPs and risks of running-related injuries.12,31 Thus, running retraining programs with SR manipulations need to be developed on a case-by-case basis. Furthermore, it is important to note that sudden changes in FSP may also lead to musculoskeletal issues during the adaptation phase. Therefore, careful monitoring and a gradual adjustment based on the individual’s specific needs and injury history are essential to ensure safe and effective outcomes.
Our findings may have implications in regard to fatigue and performance in the final stages of a distance race. Runners tend to lengthen their stride, decrease SR, and adopt more of a rearfoot strike pattern in the later stages of a race.32 Therefore, increased focus on producing a preferred or slightly greater SR as fatigue sets in may help the runner avoid increasing the amount of oxygen needed to perform the running, which may result in better running performance.
In regard to recreational runners’ RE, a manipulation of SR to their preferred or slightly higher SR may be warranted if, based on their measurements of submaximal VO2 during each condition of SR, they appear to be uneconomical at a lower SR condition, and a shift in SR would improve their RE enough to produce significant changes in performance. Similarly, in the study by Vercruyssen et al,30 a decrease in FSA (shift from RFS to MFS) during level running was found to lower VO2 by approximately 0.31 to 0.32 mL·kg−1·min−1 for every 1° reduction in FSA, highlighting the close relationship between foot strike mechanics and RE. This finding aligns with the current study, where shifts in SR showed significant potential to alter metabolic cost, reinforcing the importance of biomechanical factors in optimizing running performance. Morgan et al44 defined uneconomical VO2 measurements as a deviation in VO2 between optimal stride length and self-selected stride length that was greater than or equal to 0.5 mL·kg−1·min−1. Therefore, a large difference in VO2 may be required to justify the need of SR manipulations, and further research including more running biomechanics and possible repercussions regarding changes in SR is needed. However, the novel task with a greater SR manipulation could increase attentional focus rather than a true metabolic cost.16,19 Thus, a sufficient practice/familiarization session may be imperative to prevent the unnecessarily perceived increase in effort caused by attentional focus.
Our recreational runners’ oxygen consumption in response to SR manipulations aligns with the findings of Morgan et al44 for recreational runners and Cavanagh and Williams45 for well-trained athletes, but a key difference arises at the −10% SR condition, where Cavanagh and Williams observed significantly larger increases in submaximal VO2 (Figure 4). This difference likely stems from the well-trained runners’ optimized biomechanics, which makes them more sensitive to SR deviations. In well-trained runners, even a slight reduction in SR can disrupt their finely tuned neuromuscular coordination and metabolic efficiency, leading to a greater metabolic cost.26,45 Mercer et al46 also reported that well-trained runners presented increased energy consumption when SRs were deviated from their preferred SR. In contrast, recreational runners, whose biomechanics are not as rigidly established, may exhibit more flexibility in adapting to SR changes, resulting in a smaller increase in VO2 at the −10% SR condition in the current study and the study by Morgan et al. This flexibility may reflect their broader training range, which allows them to adjust to changes in SR without a significant disruption to their oxygen consumption.
Comparisons of the changes in oxygen consumption from preferred SR. SR indicates step rate.
Citation: Journal of Sport Rehabilitation 2025; 10.1123/jsr.2024-0261
Clinically, these findings emphasize the need for individualized SR manipulation strategies. For well-trained runners, small SR deviations could cause inefficiencies, so rehabilitation programs should make cautious adjustments to avoid increasing fatigue or metabolic strain. Conversely, recreational runners may benefit from a wider range of SR manipulation, which could help improve their RE and FSP. However, when implementing larger changes in SR, it is crucial to introduce the adjustments gradually to minimize the risk of potential injuries during the adaptation process. This suggests that tailored SR interventions based on training experience could optimize both performance and injury prevention, highlighting the importance of personalized approaches in gait retraining.
The current study had several limitations. Although we utilized effective measures, such as visual observation and audible feedback, to identify the participants’ adherence to the adjusted SR for each condition, it may be helpful to include additional verification (eg, visual feedback) for determining adherence. Furthermore, in cases where a runner produces less pronounced shifts in FSP as a result of SR manipulations, future research may want to include further running kinematics to determine what other adaptations besides shifts in SI the runner utilized. Also, habitual SR manipulation may change the results as this study examined the acute effect of SR manipulations. Thus, future research may want to additionally investigate the experience of training with SR manipulations. Although the number of participants in each FSP group was not a focus of this study, future research should examine whether different FSP characteristics produce varying responses to SR manipulation.
Clinical Implications
The findings of this study highlight the potential of SR manipulation as a valuable tool in gait retraining for recreational runners. By adjusting SR within a range of ±10%, runners can effectively alter their FSP, which may be beneficial for addressing running-related injuries and optimizing RE. For instance, runners experiencing heel strike-related injuries could increase their SR to shift toward a more FFS pattern, potentially reducing the impact forces associated with heel striking. Conversely, decreasing SR might be considered for runners needing to manage specific MFS and FFS-related issues. These insights can inform practitioners, trainers, and clinicians in developing individualized training programs that enhance running performance and reduce injury risk through simple and measurable SR adjustments.
Moreover, SR manipulation offers a noninvasive, easy-to-implement approach that can be tailored to a runner’s specific biomechanical needs, making it particularly valuable in both performance enhancement and injury rehabilitation settings. Integrating SR manipulation into routine training or recovery programs has the potential not only to improve running efficiency but also to alleviate stress on vulnerable musculoskeletal structures. This could support more effective injury prevention and recovery, reducing the likelihood of recurrent injuries while promoting optimal biomechanics.
When running outside of the lab, recreational runners could implement SR manipulations by using a metronome app on their mobile devices to provide auditory cues for maintaining their target SR, which can help facilitate changes in FSA and improve RE.
Conclusions
The present study examined the effects of SR manipulations on FSP and RE. The recreational runners in this study tended to adopt a FSP more toward their heels and the RE decreased as SR decreased to −10% and −5% of preferred SR. Also, the FSP tended to shift more toward the front of their feet at the +10% SR condition. SR changes within ±10% of preferred SR were associated with modest to significant changes in FSP and RE in recreational runners. The findings of this study may serve as a guide for gait retraining in recreational runners who wish to make acute changes to their FSP, which may help to minimize some running-related injuries or improve RE.
Acknowledgments
The authors remember Dr. Dennis Dolny with deep gratitude for his invaluable support and guidance during this research. This work was supported by both the Soonchunhyang University and Utah State University Research Fund.
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