Journal Logo


Reducing Impact Loading in Runners: A One-Year Follow-up


Author Information
Medicine & Science in Sports & Exercise: December 2018 - Volume 50 - Issue 12 - p 2500-2506
doi: 10.1249/MSS.0000000000001710
  • Free


The Healthy People 2020 initiative and the Exercise is Medicine™ Campaign encourage people to engage in regular exercise throughout their lifetime. Running is one of the most popular fitness activities that Americans engage in with over 16.9 million Americans running in over 30 thousand races in 2016 (1). However, due to the repetitive nature of running, overuse injuries are common. It has been suggested that up to 79% of runners get injured in a given year (2), and up to 70% of these will be recurrences (3).

The etiology of running injuries is known to be multifactorial in nature, however, running mechanics certainly play a role. A number of recent studies have reported an association between vertical impact loading and running injuries. Specifically, variables, such as the vertical impact peak (VIP), vertical loading rate and tibial shock, have been linked with a variety of injuries such as tibial stress fractures, plantar fasciitis, and patellofemoral pain syndrome (4–7). Physical therapy intervention for these musculoskeletal injuries typically involves progressive strengthening with the assumption that strengthening will lead to improved mechanics. However, it has been shown that strengthening alone has no effect on mechanics, leaving the underlying cause of the injury unaddressed (8,9). This explains, at least in part, the high rate of injury recurrence that has been reported in runners and highlights the importance of retraining faulty gait mechanics to reduce these injuries.

Gait retraining is not a new concept and has historically been a component of physical therapy interventions. The use of real-time feedback is also not new. Limb-load monitors, measuring the forces under the feet, have been used to improve walking symmetry in children with cerebral palsy (10) and adults with fractures, amputations, total hip replacements, and chronic pain (11). Real-time force feedback from instrumented treadmills has been shown to acutely improve gait symmetry in trans-tibial amputees (12) and individuals with total hip replacements (13). More recently gait retraining using real-time, faded feedback (sequential reduction of real-time feedback) over multiple sessions has been implemented in runners. A number of studies have utilized this approach to address patellofemoral pain in runners that had not resolved with other approaches (14–16). Real-time feedback of tibial acceleration during running has also been used in studies to acutely reduce the impact loading. Using an eight session, faded feedback design, Crowell et al. (17) demonstrated a significant reduction in both tibial shock as well as vertical loading rates. These changes persisted at a 1-month follow-up. Clansey et al. (18) provided real-time feedback on tibial shock during six sessions over 3 wk. Their reductions in tibial shock and loading rates were smaller than those of Crowell (17), and did not persist well at the 1-month follow-up visit.

Permanently altering one’s running mechanics involves developing a new running pattern that replaces the old one. This area is where clinical interventions have generally fallen short. It is not enough to demonstrate the new pattern to the patient and have them reproduce it. The patient must be able to consistently produce this pattern on their own and without feedback. The optimal way to develop a new motor skill is to provide extrinsic feedback that is gradually removed so that an individual learns to rely on their own intrinsic feedback mechanisms to produce the correct mechanics (19). Establishing the adjusted running mechanics as a new motor skill requires a series of training sessions in which feedback is gradually removed. Studies that have utilized this approach have shown persistence (14–16,20), whereas those that did not were much less successful (18,21). The effects of using the faded feedback technique have been shown to last from 1 to 3 months after the completion of a gait retraining protocol (15,16). To our knowledge, no studies have looked at the long-term persistency of these changes in the past 3 months. Without a persistent change in mechanics, injury risk is not likely to be altered.

Therefore, the purpose of this study was to examine the short- and long-term effects of a gait retraining program using real-time feedback to reduce impact loading in runners. It was hypothesized that impact loading (including VIP, vertical loading rates and tibial shock would not be reduced following a control period but would be reduced after the retraining. Additionally, reductions in impact loading would persist over a 12-month period. We also expected that tibial shock would be significantly correlated with loading rates. Finally, we did not expect peak vertical force to change as a result of the retraining.


An a priori power analysis (alpha = 0.05, beta = 0.20) using an effect size of 0.85 (pilot data) determined that 19 participants were necessary to identify a large effect of a gait retraining program among time points on the variables of interest [tibial shock, VIP, vertical load rates, peak vertical force] (G*Power Version 3.1.4). Runners were rearfoot strikers running at least 8 miles per week and were injury free upon entrance into the study. Before any data collections, we obtained written informed consent from each participant as approved by the university’s institutional review board.

Participants were screened to determine their vertical impact loading. An accelerometer (model 32A56; PCB Piezotronics, Depew, NY) was attached to the anteromedial aspect of the participant’s distal tibia (Fig. 1). Participants ran along a 25-m runway and traversed a forceplate (Bertec Corp., Columbus, OH) at its center. Speed was monitored via photocells and maintained at 3.70 m·s−1 ± 5%. Vertical accelerations during stance were collected at 1200 Hz using Vicon Nexus Software (Vicon, Centennial, CO). Participants completed five trials for each limb. Tibial shock (TS) represents the peak vertical acceleration during stance across the five trials for each limb. Participants with TS ≥ 8g for either limb were invited to participate in this study as this is considered >1 SD of a healthy group of runners at this speed (5). If both limbs exhibited TS ≥ 8g, the limb with the higher loading was used for the retraining portion of this study.

Accelerometer Placement for the running trials.

Runners who displayed increased tibial shock during the screening were enrolled in this study and completed a baseline gait analysis to determine baseline vertical loading rates. Data were processed with customized LabVIEW (National Instruments, Austin, TX) software. Force and accelerometer data were filtered at 50 and 75 Hz, respectively. Footstrike and toe-off were identified from the vertical ground reaction force using a 20-N threshold. Tibial shock was identified as the peak positive tibial acceleration (5). The VIP was identified as a local maximum before 25% of stance and vertical average loading rate (VALR) and instantaneous loading rate (VILR) were calculated from the slope to the VIP (5). If no VIP was identified, then the force value from 13% of stance was used as the VIP value (22). The peak vertical force (PFV) was identified as the peak vertical ground reaction force.

Participants then underwent eight control sessions. During these sessions, they ran at a self-selected pace on an instrumented treadmill (AMTI, Watertown, MA). The duration of each control session increased gradually from 15 min for the first session to 30 min in the eighth session. Post-control, the overground gait analysis was repeated. They then began the retraining sessions. With an accelerometer tightly affixed on the distal tibia of their retraining limb, they ran at their initially chosen self-selected pace on an instrumented treadmill (AMTI, Watertown, MA). Identical to the control sessions, run times were gradually increased from 15 to 30 min over the eight retraining sessions. During these sessions, the accelerometer signal was displayed in real time on a monitor. Participants were instructed to keep their TS below a line, placed at 50% of their baseline TS (Fig. 2), and to make their footfalls softer. We used a faded feedback paradigm designed to facilitate internalization and persistence of the new gait pattern (19). Participants received visual feedback for 100% of the time during the first four sessions. During the last four sessions, the feedback was gradually removed such that participants received only 3 min of feedback in the final session, with 1 min at the start, middle and end of the session (Fig. 3). For both the control and retraining sessions, participants had a minimum of 1 d off after two consecutive days of running to minimize muscle fatigue. All participants were required to complete all running sessions within a 3-wk window of time. During this 3-wk window, participants refrained from running outside the laboratory in order to minimize reinforcement of their old running pattern. Post-retraining, another gait analysis was conducted.

Set up for the retraining sessions. Real-time accelerometry data was provided on a screen as the participant ran on the treadmill.
Running and feedback times across the eight retraining sessions.

Participants returned to the lab for follow-up data collections at 1, 6, and 12 months following the retraining. Repeated measures ANOVA were calculated for the five variables of interest (TS, VIP, VALR, VILR, PFV) across six time points (baseline, postcontrol, postretraining, 1 month, 6 months, and 12 months). Skewness of the residuals was used to test the assumption of normality with skewness scores between ±2 considered normally distributed (23). Mauchly’s test was used to test the assumption of sphericity. The Greenhouse–Geisser adjustment to the degrees of freedom was used when the assumption of sphericity was violated. Planned comparisons were conducted across specific time points of interest: baseline versus postcontrol and postcontrol versus postretraining, months 1, 6, and 12. A modified Bonferroni correction was applied (P < 0.05) to the planned comparisons (24). Partial eta squared for each of the ANOVA and Cohen’s d for the planned comparisons were used to determine effect sizes. A large effect size was defined as ≥0.26, d ≥ 0.80; moderate ≥0.13, d ≥ 0.40; and small <0.02, d < 0.40 (25). Additionally, the relationships between reductions in tibial shock and the ground reaction force variables from postcontrol to post-retraining were calculated using correlation coefficients (Pearson’s r).


Of the 261 participants screened, 44 exhibited tibial shock ≥8g and were invited to participate in the study. Of the 44 participants, 32 completed the baseline gait analysis. A total of 19 participants (9 male, 10 female; age, 26 ± 7.6 yr; height, 1.75 ± 0.1 m; mass, 76.6 ± 14.2 kg; weekly mileage, 16 ± 9.8 miles) who completed the retraining program and the gait analysis sessions remained in the study. Reasons for the reduction of participants from 32 to 19 included TS < 8g at the baseline gait analysis (11 participants), undisclosed previous injury (1 participant), and inability to complete multiple data collection sessions (1 participant) (Fig. 4).

Flow chart of participant inclusion in the study.

Evaluation of the skewness of the residuals for each variable indicated that all variables were approximately normally distributed. Apart from TS decreasing by 17%, no other impact variables displayed a significant change following the control period (baseline to postcontrol). However, following the intervention (postcontrol to postretraining), runners significantly reduced their TS by 32%, VIP by 21%, VILR by 27%, and VALR by 25% (Table 1). Tibial shock, VIP, VILR, and VALR were also found to be significantly reduced (ranging between 16% and 29%) at each of the follow-up visits (postcontrol to months 1, 6, and 12) indicating persistence of these changes for at least 12 months following gait retraining (Table 1, Fig. 5). Finally, reductions in TS from postcontrol to post-retraining were positively correlated to changes in VILR (r = 0.71, P = 0.001), and VALR (r = 0.61, P = 0.006), but not VIP or PFV (r < 0.40, P > 0.05). As expected, no changes were seen in the PFV compared to postcontrol at any of the six time points.

Vertical loading variables during running.
A comparison of tibial shock, VIP, and vertical load rates at the baseline, postcontrol, post-retraining, and 1, 6, and 12 month follow up visits. The gray line represents normal values for these measures as reported by Milner et al., (10). * and † indicates significantly different from postcontrol (p < 0.05 and 0.01 respectively).


The purpose of this study was to examine the short and long-term effect of a gait retraining program in runners with high impact loading. We hypothesized that runners would be able to significantly reduce their impact loading following training and that these reductions would persist out to the 1-yr follow-up period.

Control period

We utilized a repeated measures design where participants served as their own controls. Each participant underwent a control period where they gradually increased their run time from 15 to 30 min over eight sessions, but had no feedback provided. Tibial shock decreased was the only variable to change over the control period. However, no differences in any of the ground reaction force variables were noted during this period. Therefore, the eigth-session, progressive run program without feedback did not influence the primary outcome variables in the study.

Immediate effects

After the retraining, all the impact variables significantly decreased as hypothesized. The greatest reduction was seen in TS. This finding was not surprising as the variable provided for feedback typically demonstrates the greatest change with retraining (14,16,18,20). In support of our findings, others have reported significant TS reductions between 30% and 48% following gait retraining (20). The reductions in TS were moderately to strongly correlated (r = 0.71) to reductions in load rates, suggesting TS can be used as a surrogate for load rates when a force plate is not available. The reductions in VALR and VILR were within the ranges noted in the literature, with reports of 18% to 32% and 19% to 34% reductions for VALR (17,18,26). In terms of force magnitudes, it was not surprising that VIP was significantly reduced with the retraining because it occurs during the impact phase of running and is nearly synchronous with TS. As expected, the peak vertical force, which occurs at mid-stance, did not change. However, peak vertical force has yet to distinguish between those with a history of stress fractures and those without (27).

The post-retraining reductions in load rates were greater than those reported by Clansey et al (18). This may be related to differences in the retraining approaches. First, the type of feedback was different. Clansey et al. used a traffic light placed on a monitor in front of the treadmill. Feedback was provided every fifth step as the average TS over the five previous stance periods. A high TS was indicated by a red light, medium by a yellow light, and low by a green light. We provided a continual trace of the accelerometer data in real-time and provided a target for them to remain under. The dosage of the feedback was different. Clansey’s retraining involved six rather than eight sessions in 3 wk, and nearly half the training time of the current study (100 min vs 190 min). This may have led to less reinforcement than in the current study. They also did not slowly progress the run time. We felt this was important to allow the body time to adapt to the new motor pattern. They also did not incorporate a faded feedback design. Faded feedback has been shown to be an important training component for altering movement patterns (19). Finally, they allowed their subjects to run in between the training sessions. This, in the absence of feedback in the field, may have potentially reinforced their older, habitual pattern. Subjects in our study were not allowed to run on their own until they completed their retraining, at which time they were doing most of their 30-min run without any feedback.

Long-term results

The reductions found immediately post-retraining are less impactful if the gait alterations do not persist over time. The long-term success of the retraining program in our study was extremely encouraging. Runners demonstrated a persistence of the loading rate reductions following the retraining, with no differences noted between the 1-, 6-, and 12-month follow ups. These findings were in contrast to those reported Clansey and colleagues (18) who reported that reductions in vertical loading noted following the retraining did not persist at the 1-month follow up. This, again, may be due to the differences in the retraining protocols noted previously. Four other studies that have incorporated a similar approach as used in our study (14–16,28) reported greater improvements in mechanics, greater persistence of the mechanics and greater reduction of symptoms in patients than studies that have not (18,20). This suggests that the components of the current retraining study are important for altering faulty mechanics and achieving persistence of these changes. The importance of adhering to these motor control principles was further underscored by the successful retention of the gait changes at the 1 yr follow-up.

Implications for injury

The reduction in loading rates is an important finding in this study, as these have been strongly correlated to running-related injuries in the literature. Most of these studies have been retrospective in nature (4–6). However, a prospective study of 242 runners demonstrated that those with high loading rates were at a 3× greater risk of developing a running-related injury than those with low loading rates (4). Even more compelling is the recent large RCT that found that runners retrained to reduce their impact loading had 62% fewer injuries at the 1-yr follow-up than runners in the control group (26). This study, along with ours, suggests that gait retraining aimed at reducing load rates can be a powerful way to help reduce injuries in runners.

Unintended consequences

It must be noted that changing running mechanics to reduce impact loading may have unintended consequences. A reduction in running economy has been suggested to be one of those consequences. However, Clansey et al. reported no changes in running economy immediately following gait retraining for runners who significantly reduced impact loading (18). They also reported no changes in running economy at the 1-month follow-up; however, changes in running mechanics did not persist. Future studies may need to explore the long-term effects of gait retraining on running economy. Another unintended consequence of changing a runner’s gait pattern is the potential increased risk for developing a different injury. Similar to other gait retraining studies, our protocol did not appear to cause any injuries (17,18). Participants did report mild soreness, but the soreness did not persist beyond a few sessions.


In summary, this is the first study to demonstrate the long-term (1 yr) retention of retrained gait patterns. The recent emergence of wearable sensors and the correlation noted between TS and loadrates provides for the translation of this retraining into the clinical environment where force plates are less accessible. These wearable sensors also allow the monitoring of running gait out in the community, which will increase the ecological validity of the retraining approach implemented in our study.

The authors would like to acknowledge the contributions of Richard Willy, Allison Altman, Phillip Crowell, and Joaquin Barrios in collecting and processing data for this study. Funding for this study was provided by the Department of Defense (DOD W911NF-05-1-0097 and W81XWH-07-1-0395) and the National Institutes of Health (NIH 1S10 RR022396 and 5R01HD50679-2). The authors report no conflicts of interest. The results of this study do not constitute endorsement by the American College of Sports Medicine. The authors declare that the results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.


1. Runing USA Web site [Internet]. U.S. Road Race Trends. [cited 1/25/2018]. Available from:
2. van Gent RN, Siem D, van Middelkoop M, van Os AG, Bierma-Zeinstra SM, Koes BW. Incidence and determinants of lower extremity running injuries in long distance runners: a systematic review. Brit J Sport Med. 2007;41(8):469–80.
3. van Mechelen W, Hlobil H, Zijlstra WP, de Ridder M, Kemper HC. Is range of motion of the hip and ankle joint related to running injuries? a case control study. Int J Sports Med. 1992;13(8): 605–10.
4. Davis IS, Bowser BJ, Mullineaux DR. Greater vertical impact loading in female runners with medically diagnosed injuries: a prospective investigation. Br J Sports Med. 2016;50(14):887–92.
5. Milner CE, Ferber R, Pollard CD, Hamill J, Davis IS. Biomechanical factors associated with tibial stress fracture in female runners. Med Sci Sports Exerc. 2006;38(2):323–8.
6. Pohl MB, Hamill J, Davis IS. Biomechanical and anatomic factors associated with a history of plantar fasciitis in female runners. Clin J Sport Med. 2009;19(5):372–6.
7. van der Worp H, Vrielink JW, Bredeweg SW. Do runners who suffer injuries have higher vertical ground reaction forces than those who remain injury-free? A systematic review and meta-analysis. Brit J Sport Med. 2016;50(8):450–7.
8. Snyder KR, Earl JE, O’Connor KM, Ebersole KT. Resistance training is accompanied by increases in hip strength and changes in lower extremity biomechanics during running. Clin Biomech (Bristol, Avon). 2009;24(1):26–34.
9. Willy RW, Davis IS. The effect of a hip-strengthening program on mechanics during running and during a single-leg squat. J Orthop Sports Phys Ther. 2011;41(9):625–32.
10. Seeger BR, Caudrey DJ, Scholes JR. Biofeedback therapy to achieve symmetrical gait in hemiplegic cerebral palsied children. Arch Phys Med Rehabil. 1981;62(8):364–8.
11. Gapsis JJ, Grabois M, Borrell RM, Menken SA, Kelly M. Limb load monitor: evaluation of a sensory feedback device for controlled weight bearing. Arch Phys Med Rehabil. 1982;63(1):38–41.
12. Dingwell JB, Davis BL, Frazier DM. Use of an instrumented treadmill for real-time gait symmetry evaluation and feedback in normal and trans-tibial amputee subjects. Prosthet Orthot Int. 1996;20(2):101–10.
13. White SC, Lifeso RM. Altering asymmetric limb loading after hip arthroplasty using real-time dynamic feedback when walking. Arch Phys Med Rehabil. 2005;86(10):1958–63.
14. Noehren B, Scholz J, Davis I. The effect of real-time gait retraining on hip kinematics, pain and function in subjects with patellofemoral pain syndrome. Br J Sports Med. 2011;45(9):691–6.
15. Roper JL, Harding EM, Doerfler D, et al. The effects of gait retraining in runners with patellofemoral pain: A randomized trial. Clin Biomech (Bristol, Avon). 2016;35:14–22.
16. Willy RW, Scholz JP, Davis IS. Mirror gait retraining for the treatment of patellofemoral pain in female runners. Clin Biomech (Bristol, Avon). 2012;27(10):1045–51.
17. Crowell HP, Davis IS. Gait retraining to reduce lower extremity loading in runners. Clin Biomech (Bristol, Avon). 2011;26(1):78–83.
18. Clansey AC, Hanlon M, Wallace ES, Nevill A, Lake MJ. Influence of tibial shock feedback training on impact loading and running economy. Med Sci Sports Exerc. 2014;46(5):973–81.
19. Winstein C. Knowledge of results and motor learning–implications for physical therapy. Phys Ther. 1991;71(2):10.
20. Crowell HP, Milner CE, Hamill J, Davis IS. Reducing impact loading during running with the use of real-time visual feedback. J Orthop Sports Phys Ther. 2010;40(4):206–13.
21. Esculier JF, Bouyer LJ, Roy JS. The effects of a multimodal rehabilitation program on symptoms and ground-reaction forces in runners with patellofemoral pain syndrome. J Sport Rehabil. 2016;25(1):23–30.
22. Willy RW, Pohl MB, Davis IS. Calculation of vertical load rates in the absence of vertical impact peaks. In: Proceedings of the 32nd Annual Conference of the American Society of Biomechanics Conference; 2008 Aug 9–12. Ann Arbor, Michigan; 2008. pp. 875–6.
23. Gravetter FJ, Wallnau LB. Statistics for the Behavioral Sciences: Wadsworth Cengage Learning; 2013.
24. Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;6:65–70.
25. Cohen J. A power primer. Psychol Bull. 1992;112(1):155–9.
26. Chan ZYS, Zhang JH, Au IPH, et al. Gait retraining for the reduction of injury occurrence in novice distance runners: 1-year follow-up of a randomized controlled trial. Am J Sports Med. 2018;46(2):388–95.
27. Zadpoor AA, Nikooyan AA. The relationship between lower-extremity stress fractures and the ground reaction force: a systematic review. Clin Biomech (Bristol, Avon). 2011;26(1):23–8.
28. Cheung RT, Davis IS. Landing pattern modification to improve patellofemoral pain in runners: a case series. J Orthop Sports Phys Ther. 2011;41(12):914–9.


Copyright © 2018 by the American College of Sports Medicine