Journal Logo


Influence of Step Rate on Shin Injury and Anterior Knee Pain in High School Runners


Author Information
Medicine & Science in Sports & Exercise: July 2016 - Volume 48 - Issue 7 - p 1244-1250
doi: 10.1249/MSS.0000000000000890
  • Free


Cross country running is among the most popular high school sports in the United States with 470,668 participants during the 2013–2014 school year (24). However, cross-country runners have relatively high injury rates compared with other sports with 13.1–17.0 injuries per 1000 athletic exposures (AE) or 29% to 38.5% of runners sustaining an injury (27,30). Most injuries occurring during cross-country running result in 1–7 d lost from participation and occur during practice (26,27,30). The shin (medial tibial stress syndromes, stress fractures, and compartment syndromes) and knee (anterior knee pain (AKP)) are the most frequently reported injury locations representing 48% of new injuries and 59% of reinjuries (27,33).

Of the many intrinsic and extrinsic risk factors potentially related to running injury (27), the amount and rate of vertical loading during stance appears to contribute to the development of some running injuries to the shin and knee (7,34,40). In prospective studies of adult distance running populations, excessive peak vertical impact forces have been linked with a higher risk of knee injury (18,34). Thijs et al. (34) reported higher rates of knee pain in runners with greater peak vertical forces at the lateral heel and second and third metatarsals. Higher average vertical loading rates have been associated with AKP and shin injury in female recreational runners (7) and female runners with a history of tibial stress fractures (23). Thus, reducing impacts during running may result in a reduction of knee and shin injury risk (7). One suggested strategy to accomplish this is to run with an increased step rate (16).

Step rate, or cadence, is the total number of steps per minute. Higher step rates during running are associated with lower peak ground reaction forces, vertical displacement of the center of mass, and joint loads (5,16,17,20,32). Adult male runners demonstrated decreased peak impact forces when running at 105%–110% of their preferred step rate at 3.8 m·s−1 (5). At 110% of their preferred step rate, 45 healthy male and female runners were able to decrease the mechanical energy absorbed at the hip and knee (16). A 15% increase from preferred step rate reduced the vertical impact peak and instantaneous and average loading rates in 10 male runners (17). The shorter step lengths associated with higher step rates at a given speed reduce tibial shock attenuation (22).

Mechanisms for step rate’s influence on AKP may be related to lower extremity joint loading and kinematics. Peak patellofemoral joint force is often increased in individuals with patellofemoral pain syndrome (11); however, a 10% increase in running step rate reduces peak patellofemoral joint force and stress by 14% (19,20). This effect is due in part to the heel landing closer to the body’s center of mass when step rate is increased (16). Peak hip adduction, which has been prospectively associated with risk of AKP (25), has been shown to decrease when step rate is increased by 10% (16).

Although the use of step rate manipulation is promising for the treatment of injured runners (2,37), there is limited information on whether step rate has value as a screening tool to identify those at greater risk for sustaining a lower extremity injury (32). Thus, the purpose of this study was to examine step rate as a risk factor for the occurrence of shin injury and AKP. We hypothesized that runners with a lower step rate would have a higher incidence of shin injury or AKP.



Sixty-eight high school cross-country runners (47 females and 21 males; age = 16.2 ± 1.3 yr, mass = 59.6 ± 9.0 kg, height = 168.1 ± 8.7 cm) were prospectively followed during an interscholastic season. Members of one northeastern Wisconsin high school’s boys’ and girls’ cross-country teams without a current running-related injury were recruited for the study. The study protocol was approved by the Rocky Mountain University of Health Professions Institutional Review Board. All subjects provided informed consent and guardian/parental consent when required.

An a priori power analysis was performed. On the basis of prior studies of injuries among cross-country runners, we expected that 48%–60% of the injuries would be shin and knee related (27,30). There has been little reported on the distribution of step rate in a running population. Thus, using conservative estimated distributions (26,28), we hypothesized that those in the low step rate (high risk) group would have twice the risk or incidence of shin injury or AKP than those in the high step rate (low risk) referent group (29). Using an alpha value of 0.05, a power of 0.80, and a conservative expected relative risk of 2.0, a sample of 121 runners was estimated to show a statistically significant relationship between step rate and shin injury or AKP (21,26–30).

Classification of injuries

Runners were tracked during the interscholastic season to identify occurrences of shin injury and AKP, and days lost to any injury. Before the season, team coaches and athletic trainers were instructed in the use of the Daily Injury Report for tracking AE and days lost to injury (31). AE is a total of all attended practices and competitive events during the season. If an athlete skipped a day of practice or competitive event or missed a day because of illness or schedule conflict, that day was not counted as an AE or as a day missed to injury. An injury was defined as a medical problem resulting from athletic participation that required a runner to be removed from a practice or competitive event or to miss a subsequent practice or competitive event (30). Runners able to return to full, unrestricted participation before the end of the practice or meet were not considered injured in this study (30). Coaches and athletic trainers recorded absences or limitations due to injuries and the injury site (30). Injury severity was based on days lost and classified as mild (1–7 d lost), moderate (8–21 d lost), or major (≥22 d lost) (29).

If a runner reported shin or knee pain, a licensed physical therapist or licensed athletic trainer examined the athlete to determine whether criteria were met for shin injury—1) continuous or intermittent pain in the tibial region, 2) exacerbation with repetitive weight-bearing activity, and 3) localized pain with palpation along the tibia (26,36)—or AKP—1) pain around the anterior aspect of the knee, 2) insidious onset, and 3) no evidence of trauma (e.g., falls and twists) (38).

Study protocol

Within the first 3 wk of the season, after an 800-m warm-up of running on an outdoor track, each subject’s running step rate was assessed at a fixed speed of 3.3 m·s−1 and at self-selected speed (mean, 3.8 ± 0.5 m·s−1). For the fixed speed trial, runners performed a 400-m run at 3.3 m·s−1 after a pacing runner traveling at the required speed. After 2 min of rest, a second 400-m trial was performed at a self-selected speed corresponding to approximately 80% of their 5-km race effort or a 15-point Borg Rating of Perceived Exertion scale score of 16 (1). The self-selected speed trials were run individually to minimize the influence of other runners. To minimize the inclusion of speed changes within the trials, subjects began running approximately 10 m before the start line, and data collection began as they crossed the start line. The average step rate during each of these runs was determined for each individual using a Polar RCX5 wristwatch with S3+ Stride Sensor™ secured to the shoelaces (Polar Electro Inc., Lake Success, NY). The Polar S3+ Stride Sensor™ has been shown to accurately and reliably measure step rate with a 1.4% error rate (two to three steps per minute) (15).

Subjects also ran in a 3.22-km (2-mile) cross-country time trial during the first week of the season as part of their normal team training plan. Their finish times were recorded for the study to provide demographic information on running performance.


Subjects completed a preseason questionnaire that included age, school grade, sex, height, weight, and prior running injuries.

Data analysis

Injury rates were calculated based on an injury to the shin or AKP, and injury severity. The initial injury rate was defined as the number of initial injuries per 1000 AE, counting only AE up to the initial shin injury or AKP. An initial injury was defined as the athlete’s first injury incident during the season (27,30). The subsequent injury rate was defined as the number of shin injuries or AKP cases occurring after the initial injury per 1000 AE, counting only AE that occurred after the initial injury in the denominator. The total injury rate was defined as the total number of shin injuries and AKP cases per 1000 AE (30).

The likelihood of injury by step rate was analyzed by categorizing the 3.3 m·s−1 and self-selected speed distributions into dichotomous (i.e., high/low) and tertile groups because there were no known reported step rate thresholds available to categorize runners.

Univariate odds ratios (OR) and 95% confidence intervals (CI) were calculated for shin injuries and AKP based on step rate at 3.3 m·s−1 and self-selected speeds. Separate univariate OR and 95% CI were also calculated for female and male runners to allow for comparison with previous studies reporting sex-specific data (27,33).

For multivariable analyses, the measure of association was the adjusted OR estimated from multivariable logistic regression analysis. For the overall sample, sex, prior injury, and body mass index (BMI) were included in the final multiple logistic modeling because of their potential confounding effects. These factors have been previously associated with increased risk of running-related injury (29,35). An alpha level of 0.05 was used to determine statistical significance for all tests. Epi Info™ (CDC, Atlanta, GA) was used for all incidence rate analyses, and SPSS Version 22.0 (SPSS Inc., Chicago, IL) was used for all other statistical analyses.


Baseline characteristics

At baseline, although males were significantly taller (P < 0.001) and heavier (P = 0.001) than females, there was no significant difference in BMI (P = 0.81) (Table 1). Females ran with a higher step rate than males at 3.3 m·s−1 (P = 0.001) and self-selected speeds (P = 0.04). No significant differences were found between female and male runners for history of prior running injury (P > 0.05). Overall, 57.4% of runners reported a prior running injury (55.3% of females and 61.9% of males). No significant differences in step rate were found between runners with and without prior running injury at 3.3 m·s−1 (169.7 ± 6.8 and 169.8 ± 7.6 steps per minute for runners with and without prior running injury, respectively; P = 0.95) or self-selected speeds (171.7 ± 9.0 and 170.6 ± 7.4 steps per minute for runners with and without prior running injury, respectively; P = 0.59).

Baseline characteristics of high school cross-country runners.

Injury incidence

During the season, 19.1% of runners experienced a shin injury and 4.4% experienced AKP. Initial injury rates per 1000 AE were 5.0 for shin injury (1.9 for females and 12.1 for males) and 1.4 for AKP (1.3 for females and 1.5 for males) (Table 2). Although males had a higher likelihood of shin injury (OR, 8.06; 95% CI, 2.11–30.80) than females, the rates for AKP were similar. Most shin and knee injuries (63.6%) experienced were classified as minor (1–7 d lost) (Table 2).

Initial and subsequent AKP and shin injury rates among high school cross-country runners.

Step rate and injury

Runners in the lowest tertile for step rate at the fixed speed (≤164 steps per minute) were more likely (OR, 6.67; 95% CI, 1.2–36.7; P = 0.03) to experience a shin injury compared with runners in the highest tertile (≥174 steps per minute). In our dichotomous analysis, runners in the lower half of the step rate values (≤170 compared with ≥171) at 3.3 m·s−1 were more likely to experience a shin injury (OR, 5.3; 95% CI, 1.1–26.2) (Table 3). Likewise, at self-selected speed, runners in the lowest tertile (≤166 steps per minute) (OR, 5.85; 95% CI, 1.1–32.1; P = 0.04) (Table 4) were more likely to experience a shin injury compared with runners in the highest tertile (≥178 steps per minute). Runners in the lower half of the step rate values at self-selected speed also had a higher likelihood of shin injury (≤172 compared with ≥173) (OR, 5.70; 95% CI, 1.2–28.2). No significant relationships were found between step rate and AKP at either speed.

Likelihood of injury and step rate at 3.3 m·s−1 among high school cross-country runners.
Likelihood of injury by step rate at self-selected speed (mean, 3.8 m·s−1) among high school cross-country runners.

For all runners, after adjusting for prior injury and BMI, a lower step rate was associated with shin injury at 3.3 m·s−1 (≤170 compared with ≥171, P = 0.03; ≤164 compared with ≥174; P = 0.03) and self-selected speed (≤172 compared with ≥173, P = 0.02; ≤166 compared with ≥178; P = 0.04) (Table 5). As we observed a sex bias with shin injury, we then adjusted for sex in the multivariable logistic model. After controlling for sex, prior injury, and BMI, shin injury was not significantly associated with step rate at 3.3 m·s−1 (P = 0.26) or self-selected speed (P = 0.06).

Adjusted models for the likelihood of shin injury by step rate at 3.3 m·s−1 and step rate at self-selected speed (mean 3.8 m·s−1) among high school cross-country runners (N = 68).


The primary purpose of this study was to examine whether step rate was associated with shin injury or AKP among high school cross-country runners. We evaluated this relationship by assessing the runners’ step rate at two different speeds while they ran overground and followed them throughout the season to see who would incur an injury. Overall, our results suggest that runners with lower step rate values at either speed were at higher likelihood of shin injury.

We observed a higher incidence for shin injury and lower incidence of AKP than previously reported. Rauh et al. (30) reported rates of 3.6/1000 AE for shin and 2.5/1000 AE for knee injury, whereas our rates were 6.8/1000 AE and 1.1/1000 AE for shin and knee injury, respectively. Unlike their findings and others (26,27,30), we observed a higher rate of shin injury among males (15.7/1000 AE) than among females (2.7/1000 AE) and equal rates of AKP in males and females (1.1/1000 AE). This is in contrast to prior prospective studies that reported significantly higher rates of shin injuries in females (30) and a retrospective study noting slightly higher rates for tibial injuries and patellofemoral pain in females (33). The higher rate of shin injury for the males in our sample may be partially due to a higher percent of males in our study completing workouts at higher training loads and mileage than that of the females throughout the season because most team practices were time rather than distance based.

To fulfill our sample size estimate, we made every effort to include all 154 cross-country runners from the participating high school. However, only 68 (44.2%) decided to volunteer for the study. Despite the smaller sample size, even after controlling for BMI and prior injury, runners in the lowest tertile for step rates at both fixed and self-selected speeds were found to be at a higher likelihood of shin injury. Higher BMI values have been associated with shin injury risk in high school cross-country runners (26), and a history of prior injury has been linked with higher risk of subsequent running injury (27). Our findings suggest that step rate was not significantly minimized as a result of prior injury. When we included sex in the modeling, the associations with lower step rate were no longer statistically significant. However, this finding may be more attributed to a small sample size studied where males were found to have a higher incidence of shin injury. Prior studies of adolescent runners with larger sample sizes have consistently shown that females were more likely to incur shin injuries such as medial tibial stress syndrome or other exercise-related leg pain (26,27,30).

Our finding that lower step rates were associated with shin injury might be partially related to longer step lengths and higher shock attenuation. At a given velocity, step rate and step length are inversely related; thus, lower step rates coincide with longer step lengths. Edwards et al. (9) determined that reducing stride length by 10% reduced peak tibial contact force and likelihood of tibial stress fracture by 3%–6%. Shock attenuation and energy absorbed at the tibia increased during the impact phase of running when step length was increased (22) or step rate decreased (5). Increasing stride length by 30% resulted in a 43% increase in shock attenuation (22).

In addition to shorter step lengths, higher running step rates are associated with decreased ground reaction forces, impact shock, attenuation, and loading (32). This may be a result of less vertical displacement of the center of mass (10,16), a more vertical leg posture at initial contact (10), or a decreased angle of foot inclination, the angle between the foot and the ground. Decreasing the angle of foot inclination may reduce or eliminate the distinct impact transient in vertical ground reaction force at initial contact (16).

There were fewer cases of AKP than anticipated on the basis of prior research. However, this may be partially attributed to the overall sample size studied. As only three runners experienced time loss secondary to AKP, the study was not adequately powered to demonstrate a risk relationship for step rate. At 3.3 m·s−1, all three cases were in the lower half of the step rate values and two of the three were in the lowest tertile at self-selected pace. As step rate modification is a successful adjunct to treatment of runners with AKP (37), a larger prospective cohort sample is recommended because it may help to appropriately examine this risk relationship based on kinematics and kinetics associated with knee injury.

Runners’ self-selected step rates and lengths appear to be based more on metabolic efficiency rather than injury prevention (4). Adult runners’ preferred step rates minimized their oxygen consumption but not their shock attenuation (14). Absorbing shock with active structures like muscle has a higher metabolic cost than shock absorption by passive structures like ligaments, articular cartilage, and bone (14). However, shock absorption via passive structures likely increases injury risk as these structures can be overloaded (14). Although small increases in step rate to reduce joint loads may initially increase oxygen consumption or RPE (4,16), a recent study demonstrated that recreational runners did not compromise their running efficiency after 6 wk of training with 5%–10% increases in step rate (13).

The major strength of this study was the use of a prospective design because it allowed the risk profile of each runner to be established before the injury occurred, thus reducing the likelihood of recall or measurement bias (27). In addition, to our knowledge, this was the first study to examine step rate as a risk factor for running-related injuries in competitive adolescent runners. Because of the study’s small sample size, the CI values for OR were fairly wide. The relationship between step rate and AKP could not be examined adequately, and further analysis of this relationship needs to be done in larger cohort studies.

Although runners who increase their step rates from preferred values reduce impact forces (5,16,17,20,32), there is limited evidence supporting ideal or abnormal step rate values with respect to injury. Step rates around 180 steps per minute are often recommended. For example, Chi Running suggests 170–180 steps per minute as part of their training recommendations, whereas the Pose Method advises step rates of 180 steps per minute or greater (8,12). However, this advice is not based on injury incidence but more so on Daniels’s (6) observations of 1984 Olympic distance runners. Although a target step rate of 180 steps per minute may have merit for elite level distance runners during competition, the findings from our study suggest that injury risk reduction may occur at step rates as low as 171 steps per minute.

Without established normative values or commonly used step rate thresholds for injury risk, we grouped runners on the basis of the sample population’s step rate distribution. In the dichotomous groupings (i.e., ≤170 vs ≥171, ≤172 vs ≥173), runners in the low step rate group had step rates below the mean, whereas those in the lowest step rate group for tertiles had step rates less than 1 SD below the mean of Heiderscheit et al.’s (16) sample (172.6 ± 8.8 at their self-selected speed of 2.9 ± 0.5 m·s−1). Heiderscheit et al.’s population is used for comparison because there are no known sources reporting step rate in high school runners, and other studies assessing the influence of step rate on running parameters used smaller samples of 4–10 runners (32). Additional studies with larger samples sizes are recommended to further validate these step rate cut points and their association with injury.

Some possible limitations with respect to data collection should be considered. The use of a pacing runner during the 3.3 m·s−1 condition may have influenced the high school runners’ step rates. However, this would not have occurred during the self-selected runner speed condition, because a pacer was not used. Also, although an individual’s leg length or height may influence self-selected step rate, we did not attempt to scale step rate values based upon these anthropometric variables because they have been found to explain less than 10% of the variance in stride length (step rate) during running (3).

Although a single variable like step rate may not explain the majority of the risk relationship for a specific injury, it may be an important variable to consider because it can be easily assessed outside of the laboratory. Biomechanics are considered a potentially modifiable intrinsic risk factor for sports injuries in adolescents. Although some reports suggest that running technique is automatic or inherent, both healthy and injured adult runners have demonstrated the ability to quickly make modifications to their running technique with various forms of gait retraining including audio and visual cueing (13,16,37,39). Any change to the preferred running style typically increases metabolic costs initially (4,14), but oxygen consumption during an initial 6-min bout of running at 110% of preferred step rate was not significantly different than at the preferred rate (14). This suggests that there may be potential to modify self-selected step rate at minor metabolic costs to reduce injury risk in a sport with high injury rates (9,14,22).


In the current prospective investigation, high school cross-country runners with the lowest step rates during running at both fixed and self-selected speeds were at a greater likelihood of shin injury. Future studies are needed to determine whether step rate manipulation may be incorporated for high school distance runners to reduce shin injury risk and time lost during the cross-country season.

The authors would like to thank Lara Bleck, P.T., for her contribution to data collection.

There was no funding received for this project.

The authors have no conflicts of interests to disclose.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.


1. Borg G. Borg’s Perceived Exertion and Pain Scales. Champaign (IL): Human Kinetics; 1998. p. 49.
2. Breen DT, Foster J, Falvey E, Franklyn-Miller A. Gait re-training to alleviate the symptoms of anterior exertional lower leg pain: a case series. Int J Sports Phys Ther. 2015;10(1):85–94.
3. Cavanagh PR, Kram R. Stride length in distance running: velocity, body dimensions, and added mass effects. Med Sci Sports Exerc. 1989;21(4):467–79.
4. Cavanagh PR, Williams KR. The effect of stride length variation on oxygen uptake during distance running. Med Sci Sports Exerc. 1982;14(1):30–5.
5. Clarke TE, Cooper LB, Hamill CL, Clark DE. The effect of varied stride rate upon shank deceleration in running. J Sports Sci. 1985;3(1):41–9.
6. Daniels J. Daniels’ Running Formula. 3rd ed. Champaign (IL): Human Kinetics; 2014, xiv, 306 pp., p. 27.
7. Davis I, Bowser B, Mullineaux D. Do Impacts Cause Running Injuries? In: A Prospective Investigation. ASB 2010: Accessed January 13, 2015.
8. Dreyer D, Dreyer K. ChiRunning: A Revolutionary Approach to Effortless, Injury-Free Running. New York: Simon & Schuster; 2004, xv, 236 pp., pp. 81–2.
9. Edwards WB, Taylor D, Rudolphi TJ, Gillette JC, Derrick TR. Effects of stride length and running mileage on a probabilistic stress fracture model. Med Sci Sports Exerc. 2009;41(12):2177–84.
10. Farley CT, Gonzalez O. Leg stiffness and stride frequency in human running. J Biomech. 1996;29(2):181–6.
11. Farrokhi S, Keyak JH, Powers CM. Individuals with patellofemoral pain exhibit greater patellofemoral joint stress: a finite element analysis study. Osteoarthritis Cartilage. 2011;19(3):287–94.
12. Goss DL, Gross MT. A review of mechanics and injury trends among various running styles. US Army Med Dep J. 2012;62–71.
13. Hafer JF, Brown AM, deMille P, Hillstrom HJ, Garber CE. The effect of a cadence retraining protocol on running biomechanics and efficiency: a pilot study. J Sports Sci. 2015;33(7):724–31.
14. Hamill J, Derrick TR, Holt KG. Shock attenuation and stride frequency during running. Hum Mov Sci. 1995;14(1):45–60.
15. Hausswirth C, Le Meur Y, Couturier A, Bernard T, Brisswalter J. Accuracy and repeatability of the Polar RS800sd to evaluate stride rate and running speed. Int J Sports Med. 2009;30(5):354–9.
16. Heiderscheit BC, Chumanov ES, Michalski MP, Wille CM, Ryan MB. Effects of step rate manipulation on joint mechanics during running. Med Sci Sports Exerc. 2011;43(2):296–302.
17. Hobara H, Sato T, Sakaguchi M, Nakazawa K. Step frequency and lower extremity loading during running. Int J Sports Med. 2012;33(4):310–3.
18. Hreljac A. Impact and overuse injuries in runners. Med Sci Sports Exerc. 2004;36(5):845–9.
19. Lenhart RL, Smith CR, Vignos MF, Kaiser J, Heiderscheit BC, Thelen DG. Influence of step rate and quadriceps load distribution on patellofemoral cartilage contact pressures during running. J Biomech. 2015;48(11):2871–8.
20. Lenhart RL, Thelen DG, Wille CM, Chumanov ES, Heiderscheit BC. Increasing running step rate reduces patellofemoral joint forces. Med Sci Sports Exerc. 2014;46(3):557–64.
21. Lwanga S, Lemeshow S. Sample Size Determination in Health Studies: A Practical Manual. Geneva, Switzerland: World Health Organization; 1991:88.
22. Mercer JA, Devita P, Derrick TR, Bates BT. Individual effects of stride length and frequency on shock attenuation during running. Med Sci Sports Exerc. 2003;35(2):307–13.
23. 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.
24. National Federation of State High School Associations. In: 2013–2014 High School Athletics Participation Survey. Kansas City (MO): National Federation of State High School Associations; 2014. pp. 53–5.
25. Noehren B, Hamill J, Davis I. Prospective evidence for a hip etiology in patellofemoral pain. Med Sci Sports Exerc. 2013;45(6):1120–4.
26. Plisky MS, Rauh MJ, Heiderscheit B, Underwood FB, Tank RT. Medial tibial stress syndrome in high school cross-country runners: incidence and risk factors. J Orthop Sports Phys Ther. 2007;37(2):40–7.
27. Rauh MJ, Koepsell TD, Rivara FP, Margherita AJ, Rice SG. Epidemiology of musculoskeletal injuries among high school cross-country runners. Am J Epidemiol. 2006;163(2):151–9.
28. Rauh MJ, Koepsell TD, Rivara FP, Rice SG, Margherita AJ. Quadriceps angle and risk of injury among high school cross-country runners. J Orthop Sports Phys Ther. 2007;37(12):725–33.
29. Rauh MJ, Macera CA, Marshall SW. Applied Sports Injury Epidemiology In: Magee DJ, Manske RC, Zachazewski JE, Quillen WS, editors. Athletic and Sports Issues Is Musculoskeletal Rehabilitation. St. Louis (MO): Elsevier/Saunders; 2011. pp. 730–72.
30. Rauh MJ, Margherita AJ, Rice SG, Koepsell TD, Rivara FP. High school cross country running injuries: a longitudinal study. Clin J Sport Med. 2000;10(2):110–6.
31. Rice SG, Schlotfeldt JD, Foley WE. The Athletic Health Care and Training Program. A comprehensive approach to the prevention and management of athletic injuries in high schools. West J Med. 1985;142(3):352–7.
32. Schubert AG, Kempf J, Heiderscheit B. Influence of stride frequency and length on running mechanics: a systematic review. Sports Health. 2013 1941738113508544.
33. Tenforde AS, Sayres LC, McCurdy ML, Collado H, Sainani KL, Fredericson M. Overuse injuries in high school runners: lifetime prevalence and prevention strategies. PM R. 2011;3(2):125–31 quiz 31.
34. Thijs Y, De Clercq D, Roosen P, Witvrouw E. Gait-related intrinsic risk factors for patellofemoral pain in novice recreational runners. Br J Sports Med. 2008;42(6):466–71.
35. Verhagen E, Van Mechelen W. Sports injury research. Oxford; New York: Oxford University Press; 2010, xvi, 243 pp.
36. Wilder RP, Sethi S. Overuse injuries: tendinopathies, stress fractures, compartment syndrome, and shin splints. Clin Sports Med. 2004;23(1):55–81 vi.
37. Wille C, Chumanov E, Schubert A, Kempf J, Heiderscheit B. Running Step Rate Modification to Reduce Anterior Knee Pain in Runners. Proceedings of the APTA Combined Section Meeting. 2013:A119–20.
38. Wills AK, Ramasamy A, Ewins DJ, Etherington J. The incidence and occupational outcome of overuse anterior knee pain during army recruit training. J R Army Med Corps. 2004;150(4):264–9.
39. Willy RW, Buchenic L, Rogacki K, Ackerman J, Schmidt A, Willson JD. In-field gait retraining and mobile monitoring to address running biomechanics associated with tibial stress fracture. Scand J Med Sci Sports [Internet]. 2015. Available from: doi:10.1111/sms.12413.
40. Zifchock RA, Davis I, Hamill J. Kinetic asymmetry in female runners with and without retrospective tibial stress fractures. J Biomech. 2006;39(15):2792–7.


© 2016 American College of Sports Medicine