Human Movement Science 42 (2015) 183–192
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Eight weeks gait retraining in minimalist footwear has no effect on running economy Joe P. Warne ⇑, Kieran A. Moran, Giles D. Warrington School of Health and Human Performance, Applied Sports Performance Research Group, Dublin City University, Dublin 9, Ireland
a r t i c l e
i n f o
PsycINFO classification: 3720 Keywords: Performance Footwear Running technique Barefoot running
a b s t r a c t Purpose: To evaluate the effects of an eight week combined minimalist footwear (MFW) and gait-retraining intervention on running economy (RE) and kinematics in conventional footwear runners. Methods: Twenty-three trained male runners (age: 43 ± 10 years, _ 2max : stature: 177.2 ± 9.2 cm, body mass: 72.8 ± 10.2 kg, VO 56.5 ± 7.0 mL min 1 kg 1) were recruited. Participants were assigned to either an intervention group (n = 13) who gradually increased exposure to MFW and also implemented gait-retraining over an eight week period. RE and kinematics were measured in both MFW and conventional running shoes (CRS) at pre-tests and eight weeks, in a random order. In contrast the control group (n = 10) had no MFW exposure or gait retraining and were only tested in CRS. Results: The MFW and gait re-training intervention had no effect on RE (p < .001). However, RE was significantly better in MFW (mean difference 2.72%; p = .002) at both pre and post-tests compared to CRS. Step frequency increased as a result of the intervention (+5.7 steps per minute [spm]; p < .001), and was also significantly higher in MFW vs. CRS (+7.5 spm; p < .001). Conclusion: Whilst a better RE in MFW was observed when compared to CRS due to shoe mass, familiarization to MFW with gait-retraining was not found to influence RE. Ó 2015 Elsevier B.V. All rights reserved.
⇑ Corresponding author. Tel.: +353 17008472; fax: +353 17008888. E-mail address: [email protected] (J.P. Warne). http://dx.doi.org/10.1016/j.humov.2015.05.005 0167-9457/Ó 2015 Elsevier B.V. All rights reserved.
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Recent scientific interest in barefoot and minimalist running has resulted in an increasing body of research in this area in relation to running performance (e.g. Divert et al., 2008; Hanson, Berg, Deka, Meendering, & Ryan, 2011; Perl, Daoud, & Lieberman, 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013). In a homogenous group of runners, running economy (RE) has been considered a strong predictor of endurance performance (Lucia, Esteve-Lanao, Olivan, Gomez-Gallego, & Foster, 2006). With regard to footwear, several studies have reported significant differences in RE between barefoot or minimalist footwear when compared to conventional footwear (Divert et al., 2008; Lussiana, Fabre, Hébert-Losier, & Mourot, 2013; Perl et al., 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013) and so it appears that changing footwear may be a means to influence performance. Despite these reported improvements in RE, only limited research has investigated the process and effects of the footwear transition in athletes when moving from habitual conventional running shoe wear into minimalist or barefoot running, as this is now a popular trend among runners (Rothschild, 2012). Rather, the findings of the majority of studies are based on results from acute interventions or using previously habituated barefoot or minimalist runners (Divert et al., 2008; Hanson et al., 2011; Lussiana et al., 2013; Perl et al., 2012; Squadrone & Gallozzi, 2009). Recently published data by our research group observed significant improvements in running economy (8.09%) following a four week familiarization to minimalist footwear (MFW) with no gait-retraining, when compared with conventional running shoes (CRS) (Warne & Warrington, 2013). This study did not include any suggestions for changes in the running gait, but recently some authors have recommended the use of a barefoot running style (gait retraining) in light of purported benefits to RE and a reduction in injury risk (Goss & Gross, 2013; Jenkins & Cauthon, 2011), largely in combination with the use of MFW, but also just in CRS (Goss & Gross, 2013). Gait retraining has now become a popular intervention for runners (Dallam, Wilber, Jadelis, Fletcher, & Romanov, 2005; Fletcher, Bartlett, Romanov, & Futouhi, 2008; Goss & Gross, 2013) and manufacturers (www.merell.com), although long term prospective studies are still required. This gait retraining proposes increasing step frequency and adopting a mid or forefoot strike (Fletcher et al., 2008; Goss & Gross, 2013), but these factors examined individually or in combination have been found to have no effect on RE (Ardigo, Lafortuna, Minetti, Mognoni, & Saibene, 1995; Fletcher et al., 2008; Gruber, Umberger, Braun, & Hamill, 2013). To date, there are no reported studies that have examined if the use of both a gait retraining intervention and MFW transition can influence RE. The aims of the present study were therefore twofold; (1) to determine the effects of a combined eight week MFW and gait-retraining intervention on RE and simple kinematic changes (step frequency and foot strike patterns) in both MFW and CRS when compared to a control group in CRS with no intervention; (2) to examine if differences exist in RE and kinematics between MFW and CRS, both before and after exposure to the MFW and gait retraining intervention. Within these aims, we adopted both a within-group control (the CRS condition) as well as a between-group control (the control group) to examine these factors. Based on our previous findings (Warne & Warrington, 2013), we hypothesized that the MFW and gait-retraining intervention would improve RE in the MFW condition.
1. Methods 1.1. Participants Twenty-three moderately trained male runners (age: 43 ± 10 years, stature: 177.2 ± 9.2 cm, body _ 2max : 56.54 ± 6.97 mL min 1 kg 1) were recruited from local athletic clubs. mass: 72.8 ± 10.2 kg, VO Participants typically ran 4–6 days per week with a mean weekly running distance of 52 (±10) km at the time of the study. Participants were excluded if they had reported any running related injuries in the last three months, or had previous barefoot or minimalist running experience. Only male athletes were used to eliminate gender differences in running mechanics (Ferber, Irene, & Dorsey, 2003). All participants had previous experience with treadmill running. The participants gave informed
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consent at the beginning of testing. Ethical approval for this study was granted by the Dublin City University Research Ethics Committee. 1.2. Experimental design Twenty-three participants were recruited for the study and were randomly assigned into 2 groups. Table 1 presents anthropometric and descriptive data for the groups following dropout (see Section 2). Group 1: the intervention group comprised of 12 participants. This group was tested in both MFW and CRS at pre-test and eight weeks (post), and were required to gradually increase exposure to MFW as well as incorporate gait retraining into their running over this period (The MFW and gait-retraining will be summarized as MFW). It has been suggested that a minimum of one month is required for any observable change related to MFW kinematics (Giandolini, Horvais, Farges, Samozino, & Morin, 2013). Group 2: the control group consisted of 8 participants, and were only tested in the CRS condition at both pre and post-tests. In addition to controlling for any potential learning effects related to the tests, or changes related to training season, the control group was included to examine if RE changes in the intervention CRS condition were as a result of a ‘‘crossover’’ effect from the MFW or gait-retraining intervention (comparing the intervention CRS and control CRS). The testing protocol can be observed in Fig. 1. The control group were required to train as normal in CRS, and had no exposure to MFW or gait-retraining at any point. Groups were similarly matched in their foot strike patterns at pre-tests (70% rearfoot strikers in the intervention group, and 75% rearfoot striking in the control group). In order to avoid any potential diurnal effect, tests took place at the same time of day. Dietary intake, sleeping patterns, and training were recorded directly prior to the initial test and included all food and fluid consumed on that day for replication at post-tests. To balance order effects, a Latin square design was used to determine which footwear condition (MFW or CRS) was tested first in the intervention group between the pre and post-tests. On the first visit, foot size was measured and participants in the intervention group were provided with one pair of MFW (VibramÒ Five Finger ‘‘KSO’’; 150 g), and all participants were provided with a neutral CRS (AsicsÒ ‘‘GEL-Cumulus’’ 2012; 400 g). 1.3. Testing procedure Resting blood lactate (Lactate Plus, Nova Biomedical, Waltham, Massachusetts, USA) was sampled from the earlobe prior to the testing sessions. Respiratory data were measured using a Viasys Vmax Encore 299 online gas analysis system (Viasys Healthcare, Yorba Linda, California, USA). The system was calibrated according to the manufacturer guidelines, including atmospheric pressure and temperature, before each new test. For this system, accuracy has been reported at 0.02% for O2 measures, following a 15 min warm-up period and calibrated within 5% of absolute operating range. A treadmill (Cosmed T170, Sport Med, Weil am Rhein, Germany) RE test was then conducted in the assigned footwear. Treadmill incline was set at 1% to account for air resistance (Jones & Poole, 2005). Participants ran two trials lasting 6 min at 11 km/h. Since we cannot be sure that changes in running velocity will affect differences in RE between CRS and MFW, we controlled treadmill speed at 11 km h. Eleven km/h has previously been considered an appropriate steady state ‘‘endurance running’’ velocity (Hatala, Dingwall, Wunderlich, & Richmond, 2013). At the end of each 6-min stage, participants were asked to stand to the side of the treadmill and a blood lactate sample was collected within 30 s. The next
Table 1 Anthropometric and descriptive data for the intervention and control groups.
Intervention group (n = 12) Control group (n = 8) (M ± SD).
Age (years)
Stature (cm)
Body mass (kg)
_ 2max (mL min VO
41 (±9) 46 (±10)
177.2 (±10.4) 177.1 (±7.5)
72.6 (±10.2) 73.1 (±11.0)
52.1 (±7.5) 56.3 (±6.7)
1
kg
1
)
Kilometers per week (km) 52 (±11) 52 (±10)
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Fig. 1. Schematic representation of the testing procedure, including the intervention (Int), and control (Cnt) group.
stage was started after 3 min of rest to allow the shoe type to be swapped over. At 5-min in each stage, step frequency was collected by counting the left foot contact with the treadmill belt for 60 s duration. This procedure was repeated by the same investigator for validity in each subject and also filmed for a second assessment and accuracy (R2 = .95; Sony HDR-CX210, 60FPS; Sony, San Diego, CA, USA). Rudimentary foot strike pattern (FSP) analysis was undertaken using a low-cost video camera, in which participants were filmed in the sagittal plane at foot level over a 15 s period during the fourth minute of testing. The video footage was then used to assign 1, 2, or 3 (1 = forefoot strike, 2 = midfoot strike, 3 = rearfoot strike) to the participants’ foot strike pattern using Dartfish video analysis software (Dartfish 5.5, Fribourg, Switzerland). A midfoot strike was classified when there was no clear forefoot or heel initial contact. The validity of this method has been previously discussed by Altman and Davis (2012) and highly correlated to the strike index (R2 = .85). 1.4. Interventon Immediately after pre-tests, each subject in the intervention group was provided with a structured progression of MFW use over the eight week familiarization period, a training diary to record their training, and relevant injury prevention exercises (Tenforde et al., 2011) (Table 2). The gait retraining program was provided based on current findings in the literature (Crowell & Davis, 2011; Daoud et al., 2012; Divert, Mornieux, Baur, Mayer, & Belli, 2005; Lieberman et al., 2010; Robbins & Hanna, 1987; Squadrone & Gallozzi, 2009); adopting a non rearfoot strike and increasing step frequency have also become the main kinematic changes promoted in established running gait-retraining programmes (e.g. Chumanov, Wille, Michalski, & Heiderscheit, 2012; Dallam et al., 2005; Fletcher et al., 2008; Goss & Gross, 2013; Lenhart, Thelen, Wille, Chumanov, & Heiderscheit, 2014). Both the gait-retraining and exercises were fully demonstrated during a 30 min session until changes to step frequency (+10% steps per minute – spm), a mid/forefoot strike, more upright posture and a softer landing were adopted by the participants. This was implemented using feedback from an experienced tester in line with the simple instructions provided in Table 2. The programme incorporated MFW into the subject’s normal training routines, where it was required that the MFW took place at the beginning of any training session, and then participants were allowed to continue their normal training load in their own preferred conventional running footwear, thus not reducing their overall training workload. The participants were asked to work on the gait retraining changes both in MFW and CRS, gradually incorporating them into longer runs. The control group received no intervention or feedback, and were asked to not research or include any changes to running technique into their regular training for the duration of the testing.
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Table 2 Eight week familiarization to MFW including running technique guidelines and simple exercises for injury prevention. Week
MFW training programme
Week 1
Throughout: wearing MFW and going barefoot as much as possible in normal daily routines 3 days: 5–8 min easy running on the spot or in corridors/garden at home 3 days: prescribed exercises*
Week 2
3 days: 10–15 min running on grass, 3 min on pavement 3 days: prescribed exercises*
Week 3
2 days: 20 min running on grass, 5–8 min on pavement 1 day: 25 min running on grass 3 days: Prescribed exercises*
Week 4
2 days: 20 min on grass, 10 min on pavement 1 day: 30 min on grass 2 days: prescribed exercises*
Week 5 + 6
2 days: 20 min on grass, 15 min on pavement 1 day: 35 min on grass 2 days: prescribed exercises*
Week 7 + 8
2 days: 30 min on grass, 15 min on pavement 1 day: 40 min on grass 2 days: prescribed exercises*
Running technique guidelines Keep stride short and increase cadence. (Chumanov et al, 2012; Divert et al, 2005; Lenhart et al, 2014; Lieberman et al, 2010) Run as light and quiet as possible. (Crowell and Davis, 2011)
*
Exercise programme (10 min)
Plantar Fascia and Triceps Surae Rolling x 5 mins
Land on the forefoot, allowing heel to Contact immediately afterwards. (Daoud et al, 2012; Lieberman et al, 2010; Robbins and Hanna, 1987)
Ankle Mobility (3 x 15)
Keep hips forward and head up, running as tall and proud as possible. (Lieberman et al, 2010)
Toe “Grabs” (3 x 15)
Calf Raises (3 x 15)
Single leg balance (60secs)
No specification was made as to whether the exercises were completed on the same days as the running intervention or not.
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_ 2max 1.5. Testing procedure – VO _ 2max test was completed at the end of the final testing day for subject characterization. This A VO involved a ramped treadmill protocol at 12 km/h for a 5-min warm-up before increasing to 14 km/h at 1% incline. The incline was then increased every minute until volitional exhaustion, and correlated with participants achieving a respiratory quotient (RQ) of 1.1 or above. Participants con_ 2max was recorded as the highest breath-by-breath value ducted this test in their own shoe choice. VO averaged over 60 s. 1.6. Data processing The RE values were determined from the mean data over the last 2 min of each stage when partic_ 2 . This was verified by less than a 1 mmol increase in blood ipants had reached a true steady-state VO lactate (post trial minus resting lactate) as this is considered well below maximal lactate steady state (Svedahl & MacIntosh, 2003), and an RQ of less than 1.0 (Brooks, Fahey, & White, 1996). Foot strike patterns were reported as frequencies. 1.7. Data analysis In order to examine aim 1 and 2, the effect of time (aim 1; pre–post-tests) and condition (aim 2; MFW vs. CRS) with regard to RE and step frequency were examined using two-way repeated measures analyses of variance (ANOVA) for within-subjects effects. Differences between the intervention and control group were established with a two-way (group [CRS intervention and CRS control], and time [pre to post-tests]) mixed ANOVA for between-subject effects, and changes over time in the control group were examined using paired t-tests. (Statistical Package for the Social Sciences data analysis software V16.0, SPSS Inc, Chicago, Illinois, USA). Statistical significance was accepted at a 6 0.05. Foot strike pattern changes have been presented as frequencies. Effect sizes are reported as eta squared (g2) for ANOVA tests and Cohen’s d for t tests. To make inferences about true (population) values for the effect of an MFW and gait retraining intervention on RE, the uncertainty of the effect was expressed as 95% confidence limits and the likelihood that the true value of the effect represents substantial change (harm or benefit) (Batterham & Hopkins, 2006). The smallest worthwhile change in RE was calculated as 2.4% of the shod RE at pre-tests (Saunders, Pyne, Telford, & Hawley, 2004). For the remaining variables, the smallest standardized change that is considered meaningful was assumed to be an effect size of 0.20 for Cohen’s d and 0.01 for g2 (Cohen, 1988). 2. Results No participants were excluded based on any ‘‘slow component’’ for submaximal VO2 consumption, an increase in blood lactate of >1 mmol (mean change from resting = .44 mmol), and an RQ greater than 1.0. During testing, one participant from the intervention group became injured (metatarsal stress fracture), and two participants from the control group became ill and were removed from the final data analysis (remaining n = 20; Table 1). Seven out of 13 participants in the intervention group also reported mild triceps surae soreness in the first two weeks, but this did not result in any reduction in training or intervention compliance. Participant compliance with the intervention schedule was good (mean compliance 78%, as recorded by feedback of missed runs or exercise sessions during intervention); all participants were able to complete the longer runs in the latter weeks and were well exposed to MFW running by week 8. Results are reported as (p value; mean change [95% CI]; uncertainty of effect; effect size). Mean values for RE and step frequency are presented in Table 3. Mean step frequency results were comparable to previous work investigating the same MFW (Squadrone & Gallozzi, 2009). Aim one: over the course of the eight week trial there was no significant change in the intervention group for RE (p = .99; 0.02 mL min 1 kg 1 [ 2.3 to 2.3]; 18.9% – unlikely beneficial; g2 = 0.00) (Table 3). No difference for the change in RE over time was observed between the intervention and
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J.P. Warne et al. / Human Movement Science 42 (2015) 183–192 Table 3 Running economy (RE) and step frequency (SF) results for the MFW and CRS condition, and the control group. Intervention group (n = 12)
MFW
Time
Pre
Post
Pre
Post
40.60 ± 4.29 178.7 ± 10.1
40.72 ± 4.08 184.2 ± 10.6
42.13 ± 4.25 171.0 ± 10.3
42.04 ± 4.68 176.8 ± 10.5
42.74 ± 4.07 166.3 ± 6.1
42.39 ± 2.06 168.0 ± 5.2
RE (mL min 1 kg SF (steps/min)
1
)
CRS
Control Group (n = 8) RE (mL min 1 kg 1) SF (steps/min) Data presented as mean ± SD.
control group (p = .78). No change in RE was observed in the control group from pre to post-tests (p = .95; 0.1 mL min 1 kg 1 [ 2.7 to 2.9]; Cohen’s d = 0.00). There was a significant increase in step frequency as a result of the intervention (p < .001; 5.7 spm [7.6–3.8], g2 = 0.077). Step frequency in the control group did not change (p = .078; 1.7 spm [3.7 to 0.3]; Cohen’s d = 0.43) (Table 3). The distribution of foot strike patterns are displayed in Fig. 2 for the intervention group. 75% of participants adopted a rearfoot strike in both CRS and MFW at pre-tests. At post-tests only 50% of participants in CRS used a rearfoot strike, and 33% of participants in MFW used a rearfoot strike. In the control group, 6/7 participants used a rearfoot strike, and 1/7 used a midfoot strike. This did not change from pre to post-tests. Aim 2: RE was significantly better in MFW (2.72%) when compared to CRS (p = .002; 1.4 mL min 1 kg 1 [ 2.2 to 0.7]; 86.5% – likely beneficial; g2 = 0.035) irrespective of the intervention (Table 3). There was a significantly higher step frequency observed in MFW when compared to CRS (p < .001; 7.5 spm [6.0–9.0], g2 = 0.129). 3. Discussion The main finding of the present study revealed that an eight week MFW and gait retraining intervention did not result in any significant change in RE, when assessed in both MFW and CRS conditions and this rejects the study hypothesis. Whilst it is possible that a familiarization to MFW does enhance RE (Warne & Warrington, 2013), this was not the case in the present study with a similar intervention that included gait retraining. This finding is in accordance with previous research which reported that
10 9 Occurrence of FSP
8 7 6 5
FFS
4
MFS
3
RFS
2
1 0 Pre MFW
Post MFW
Pre CRS
Post CRS
Time Fig. 2. Foot strike patterns of both the MFW and CRS condition during the eight week intervention.
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gait retraining had no effect on RE (Ardigo et al., 1995; Fletcher et al., 2008; Gruber et al., 2013; Messier & Cirillo, 1989), or may even make RE worse (Cavanagh & Williams, 1982; Dallam et al., 2005; Tseh, Caputo, & Morgan, 2008). To support these studies, Nigg and Enders (2013) and Saunders et al. (2004) have suggested that self-selected running kinematics rather than deliberate changes are more appropriate for optimizing RE. This may be because deliberate changes result in deviations from the preferred movement pathway that has been dictated by physiological and neuromuscular adaptations to repeated training (Saunders et al., 2004) that will not be optimized immediately (Bonacci, Chapman, Blanch, & Vicenzino, 2009). One example why deliberate changes may decrease RE may be the recruitment of different muscle fibers at different speeds of contraction that will increase metabolic cost (Bonacci et al., 2009; Kaneko, 1990). This may also be due to changes in running mechanics such as leg stiffness (Butler, Crowell, & Davis, 2003) and requires further investigation. Regardless, this study compliments the already available body of literature suggesting RE cannot be improved with deliberate changes to running kinematics. This is however the first study to investigate both MFW and gait retraining combined, and suggests that the inclusion of MFW to the gait retraining intervention did not have any effect on RE either. The kinematic changes observed as a result of the intervention provide important information on the incorporation of the gait retraining. Step frequency was found to significantly increase during the eight weeks. Likewise with regard to the foot strike patterns there was a higher prevalence of non-rearfoot strikes in MFW and CRS, although to a lesser extent in the CRS. This observed difference in foot strike pattern between MFW and CRS was observed in previous studies (Warne & Warrington, 2013; Warne et al., 2013). Given that the present participants were asked to adopt a forefoot strike pattern, these results suggest that CRS may result in a lower prevalence of midfoot or forefoot strike patterns. This may be due to the elevated profile of the shoe or a reduction of sensory feedback from the foot (De Wit, De Clercq, & Aerts, 2000; Divert et al., 2005). In the present work, step frequency and foot strike changes can provide an indication of kinematic change associated with the intervention, however there is no strong evidence that either step frequency or the foot striking pattern can influence RE (e.g. Cavanagh & Williams, 1982; Gruber et al., 2013). Given that we observed no change in RE, but a change in step frequency and foot strike, our results support these previous studies. With regard to the second study aim, a significant and worthwhile improvement in RE was observed in the MFW condition when compared to CRS irrespective of the intervention (86.5% likely beneficial). Differences in RE between MFW and CRS have been reported previously (Perl et al., 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013). Several authors have described a better RE in the barefoot condition to be solely related to the mass of traditional shoes (Divert et al., 2008; Flaherty, 1994), where a 1% increase in the oxygen cost of running has been observed for every 100 g of added mass (Divert et al., 2008; Saunders et al., 2004). Given that the difference in shoe mass in the present study was 250 g which was not controlled for, this may explain the majority (2.5%) of the observed difference in RE (2.7%) between the MFW and CRS conditions. Also, the MFW used in our study was found to result in a better RE than barefoot in Squadrone and Gallozzi (2009), and this may be due to the small protective layer of rubber that reduces the metabolic cost of cushioning the body (Franz, Wierzbinski, & Kram, 2012). Saunders et al. (2004) have suggested that anything above a 2.4% change in RE is a worthwhile improvement in performance. Likewise Di Prampero et al. (1993) concluded that a 5% improvement in RE elicited a 3.8% increase in run performance, suggesting that even changes due to shoe mass are worthwhile. Our study suggests that there is a meaningful and likely benefit to wearing MFW, irrespective of whether the participants are familiarized to this footwear or not. We acknowledge that this intervention combines both MFW and gait retraining without concern for the individual effects of either factor. Ideally this study should include two further groups with only a MFW or gait retraining exposure, but this would require a very large body of participants. A limitation of the present study was the lack of any kinematic measurements throughout the intervention period to ensure that the gait retraining changes were being effectively executed. Whilst we measured step frequency and foot strike patterns and observed a change, a more comprehensive analysis to monitor the incorporation of the gait retraining elements is recommended. Indeed previous work has found that participants cannot correctly report their running pattern (Goss, 2012), and so may not be incorporating the ‘‘correct’’ changes, despite being under the impression that they were. In
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addition, the study design allowed participants to continue their normal training in CRS. This was in order to safely maintain training volume without excessive exposure to MFW running that may increase injury risk due to the novel footwear condition. Therefore, a transition to MFW with no CRS training allowed may result in very different findings. Finally, we only examined RE at 11 km h in the present work and therefore future work should examine higher velocities. 4. Conclusion This study suggests that gait-retraining coupled with MFW use is not an effective means to improve RE. However, the use of MFW in itself can result in a significantly better RE (2.72%) when compared to CRS irrespective of whether subjects are familiarized or not. This is most likely to be due to mass differences, but this factor may improve running performance. There was a significant increase in step frequency, and a higher tendency to forefoot strike observed as a result of the intervention. Conflicts of interest The authors have received a donation of footwear for the present study from VibramÒ (Milan, Italy). No honoraria or conditions have been attached to this donation, and the company has no direction or involvement in the research. Acknowledgements The authors would like to thank Professor Alan M. Nevill (School of Sport, Performing Arts and Leisure, University of Wolverhampton, Walsall, UK) for his continued support and guidance with regard to statistical procedures. References Altman, A. R., & Davis, I. S. (2012). A kinematic method for footstrike pattern detection in barefoot and shod runners. Gait and Posture, 35(2), 298–300. Ardigo, L. P., Lafortuna, C., Minetti, A. E., Mognoni, P., & Saibene, F. (1995). Metabolic and mechanical aspects of foot landing type, forefoot and rearfoot strike, in human running. Acta Physiologica Scandinavica, 155(1), 17–22. Batterham, A. M., & Hopkins, W. G. (2006). Making meaningful inferences about magnitudes. International Journal of Sports Physiology and Performance, 1(1). Bonacci, J., Chapman, A., Blanch, P., & Vicenzino, B. (2009). Neuromuscular adaptations to training, injury and passive interventions. Implications for running economy. Sports Medicine, 39(11), 903–921. Brooks, G. A., Fahey, T. D., & White, T. P. (1996). Exercise physiology: Human bioenergetics and its applications (2nd ed.). Mayfield Publishing Company. Butler, R. J., Crowell, H. P., III, & Davis, I. M. (2003). Lower extremity stiffness: Implications for performance and injury. Clinical Biomechanics, 18(6), 511–517. Cavanagh, P. R., & Williams, K. R. (1982). The effect of step length variation on oxygen uptake during distance running. Medicine and Science in Sports and Exercise, 14(1), 30–35. Chumanov, E. S., Wille, C. M., Michalski, M. P., & Heiderscheit, B. C. (2012). Changes in muscle activation patterns when running step rate is increased. Gait and Posture, 36(2), 231–235. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Psychology Press. Crowell, H. P., & Davis, I. S. (2011). Gait retraining to reduce lower extremity loading in runners. Clinical Biomechanics, 26(1), 78–83. Dallam, G. M., Wilber, R. L., Jadelis, K., Fletcher, G., & Romanov, N. (2005). Effects of global alteration of running technique on kinematics and economy. Journal of Sports Sciences, 23(7), 757–764. Daoud, A. I., Geissler, G. J., Wang, F., Saretsky, J., Daoud, Y. A., & Lieberman, D. E. (2012). Foot strike and injury rates in endurance runners: A retrospective study. Medicine and Science in Sports and Exercise, 44(7), 1325–1334. De Wit, B., De Clercq, D., & Aerts, P. (2000). Biomechanical analysis of the stance phase during barefoot and shod running. Journal of Biomechanics, 33(3), 269–278. Di Prampero, P. E., Capelli, C., Pagliaro, P., Antonutto, G., Girardis, M., Zamparo, P., et al (1993). Energetics of best performances in middle distance running. Journal of Applied Physiology, 74(5), 2318–2324. Divert, C., Mornieux, G., Freychat, P., Baly, L., Mayer, F., & Belli, A. (2008). Barefoot-Shod running differences: Shoe or mass effect? International Journal of Sports Medicine, 29, 512–518. Divert, C., Mornieux, G., Baur, H., Mayer, F., & Belli, A. (2005). Mechanical comparison of barefoot and shod running. International Journal of Sports Medicine, 26(7), 593–598.
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Impact reduction through long-term intervention in recreational runners: Midfoot strike pattern versus low-drop/low-heel height footwear. European Journal of Applied Physiology, 1–14. Goss, D. L. (2012). A comparison of lower extremity joint work and initial loading rates among four different running styles (Ph.D. thesis). University of North Carolina. UMI: 3526126. Goss, D. L., & Gross, M. T. (2013). A Comparison of negative joint work and vertical ground reaction force loading rates between chi runners and rearfoot striking runners. Journal of Orthopaedic and Sports Physical Therapy. Early Access, 1–27. Gruber, A. H., Umberger, B. R., Braun, B., & Hamill, J. (2013). Economy and rate of carbohydrate oxidation during running with rearfoot and forefoot strike patterns. Journal of Applied Physiology, 115(2), 194–201. Hanson, N., Berg, K., Deka, P., Meendering, J., & Ryan, C. (2011). Oxygen cost of running barefoot vs. Running shod. International Journal of Sports Medicine, 32(06), 401–406. Hatala, K. G., Dingwall, H. L., Wunderlich, R. E., & Richmond, B. G. (2013). Variation in foot strike patterns during running among habitually barefoot populations. PloS One, 8(1), 1–6. Jenkins, D. W., & Cauthon, D. J. (2011). Barefoot running claims and controversies. Journal of the American Podiatric Medical Association, 101(3), 231–246. Jones, A. M., & Poole, D. C. (2005). Oxygen uptake kinetics in sport, exercise and medicine. London: Routledge. 83–88. Kaneko, M. (1990). Mechanics and energetics in running with special reference to efficiency. Journal Biomechanics, 23(1), 57–63. Lenhart, R. L., Thelen, D. G., Wille, C. M., Chumanov, E. S., & Heiderscheit, B. C. (2014). Increasing running step rate reduces patellofemoral joint forces. Medicine and Science in Sports and Exercise, 46(3), 557–564. Lieberman, D. E., Venkadesan, M., Werbel, W. A., Daoud, A. I., D’andrea, S., Davis, I. S., Mang’eni, R. O., & Pitsiladis, Y. (2010). Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature, 463(7280), 531–535. Lucia, A., Esteve-Lanao, J., Olivan, J., Gomez-Gallego, F., & Foster, C. (2006). Physiological characteristics of the best Eritrean runners – Exceptional running economy. Applied Physiology, Nutrition, and Metabolism, 31, 530–540. Lussiana, T., Fabre, N., Hébert-Losier, K., & Mourot, L. (2013). Effect of slope and footwear on running economy and kinematics. Scandinavian Journal of Medicine and Science in Sports, 23(4), e246–e253. Messier, S. P., & Cirillo, K. J. (1989). Effects of a verbal and visual feedback system on running technique, perceived exertion and running economy in female novice runners. Journal of Sports Sciences, 7(2), 113–126. Nigg, B., & Enders, H. (2013). Barefoot running – some critical considerations. Footwear Science, 5(1), 1–7. Perl, D. P., Daoud, A. I., & Lieberman, D. E. (2012). Effects of footwear and strike type on running economy. Medicine and Science in Sports and Exercise, 44(7), 1335–1343. Robbins, S. E., & Hanna, A. M. (1987). Running-related injury prevention through barefoot adaptations. Medicine and Science in Sports and Exercise, 19(2), 148–156. Rothschild, C. E. (2012). Primitive running: a survey analysis of runners’ interest, participation, and implementation. The Journal of Strength and Conditioning Research, 26(8), 2021–2026. Saunders, P. U., Pyne, D. B., Telford, R. D., & Hawley, J. A. (2004). Factors affecting running economy in trained distance runners. Sports Medicine, 34(7), 464–485. Squadrone, R., & Gallozzi, C. (2009). Biomechanical and physiological comparison of barefoot and two shod conditions in experienced barefoot runners. The Journal of Sports Medicine and Physical Fitness, 49(1), 6–13. Svedahl, K., & MacIntosh, B. R. (2003). Anaerobic threshold: the concept and methods of measurement. Canadian Journal of Applied Physiology, 28(2), 299–323. Tenforde, A. S., Sayres, L. C., McCurdy, M. L., Collado, H., Sainani, K. L., & Fredericson, M. (2011). Overuse injuries in high school runners: Lifetime prevalence and prevention strategies. Physical Medicine and Rehabilitation, 3, 125–131. Tseh, W., Caputo, J. L., & Morgan, D. W. (2008). Influence of gait manipulation on running economy in female distance runners. Journal of Sports Science and Medicine, 7, 91–95. Warne, J., & Warrington, G. (2013). Four weeks habituation to simulated barefoot running improves running economy when compared to shod running. Scandinavian Journal of Medicine and Science in Sports. http://dx.doi.org/10.1111/sms.12032 [Epub ahead of print]. Warne, J. P., Kilduff, S. M., Gregan, B. C., Nevill, A. M., Moran, K. A., & Warrington, G. D. (2013). A four week instructed minimalist running transition and gait-retraining changes plantar pressure and force. Scandinavian Journal of Medicine and Science in Sports. http://dx.doi.org/10.1111/sms.12121 [Epub ahead of print]. www.merell.com. 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Contents lists available at ScienceDirect
Human Movement Science journal homepage: www.elsevier.com/locate/humov
Eight weeks gait retraining in minimalist footwear has no effect on running economy Joe P. Warne ⇑, Kieran A. Moran, Giles D. Warrington School of Health and Human Performance, Applied Sports Performance Research Group, Dublin City University, Dublin 9, Ireland
a r t i c l e
i n f o
PsycINFO classification: 3720 Keywords: Performance Footwear Running technique Barefoot running
a b s t r a c t Purpose: To evaluate the effects of an eight week combined minimalist footwear (MFW) and gait-retraining intervention on running economy (RE) and kinematics in conventional footwear runners. Methods: Twenty-three trained male runners (age: 43 ± 10 years, _ 2max : stature: 177.2 ± 9.2 cm, body mass: 72.8 ± 10.2 kg, VO 56.5 ± 7.0 mL min 1 kg 1) were recruited. Participants were assigned to either an intervention group (n = 13) who gradually increased exposure to MFW and also implemented gait-retraining over an eight week period. RE and kinematics were measured in both MFW and conventional running shoes (CRS) at pre-tests and eight weeks, in a random order. In contrast the control group (n = 10) had no MFW exposure or gait retraining and were only tested in CRS. Results: The MFW and gait re-training intervention had no effect on RE (p < .001). However, RE was significantly better in MFW (mean difference 2.72%; p = .002) at both pre and post-tests compared to CRS. Step frequency increased as a result of the intervention (+5.7 steps per minute [spm]; p < .001), and was also significantly higher in MFW vs. CRS (+7.5 spm; p < .001). Conclusion: Whilst a better RE in MFW was observed when compared to CRS due to shoe mass, familiarization to MFW with gait-retraining was not found to influence RE. Ó 2015 Elsevier B.V. All rights reserved.
⇑ Corresponding author. Tel.: +353 17008472; fax: +353 17008888. E-mail address: [email protected] (J.P. Warne). http://dx.doi.org/10.1016/j.humov.2015.05.005 0167-9457/Ó 2015 Elsevier B.V. All rights reserved.
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Recent scientific interest in barefoot and minimalist running has resulted in an increasing body of research in this area in relation to running performance (e.g. Divert et al., 2008; Hanson, Berg, Deka, Meendering, & Ryan, 2011; Perl, Daoud, & Lieberman, 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013). In a homogenous group of runners, running economy (RE) has been considered a strong predictor of endurance performance (Lucia, Esteve-Lanao, Olivan, Gomez-Gallego, & Foster, 2006). With regard to footwear, several studies have reported significant differences in RE between barefoot or minimalist footwear when compared to conventional footwear (Divert et al., 2008; Lussiana, Fabre, Hébert-Losier, & Mourot, 2013; Perl et al., 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013) and so it appears that changing footwear may be a means to influence performance. Despite these reported improvements in RE, only limited research has investigated the process and effects of the footwear transition in athletes when moving from habitual conventional running shoe wear into minimalist or barefoot running, as this is now a popular trend among runners (Rothschild, 2012). Rather, the findings of the majority of studies are based on results from acute interventions or using previously habituated barefoot or minimalist runners (Divert et al., 2008; Hanson et al., 2011; Lussiana et al., 2013; Perl et al., 2012; Squadrone & Gallozzi, 2009). Recently published data by our research group observed significant improvements in running economy (8.09%) following a four week familiarization to minimalist footwear (MFW) with no gait-retraining, when compared with conventional running shoes (CRS) (Warne & Warrington, 2013). This study did not include any suggestions for changes in the running gait, but recently some authors have recommended the use of a barefoot running style (gait retraining) in light of purported benefits to RE and a reduction in injury risk (Goss & Gross, 2013; Jenkins & Cauthon, 2011), largely in combination with the use of MFW, but also just in CRS (Goss & Gross, 2013). Gait retraining has now become a popular intervention for runners (Dallam, Wilber, Jadelis, Fletcher, & Romanov, 2005; Fletcher, Bartlett, Romanov, & Futouhi, 2008; Goss & Gross, 2013) and manufacturers (www.merell.com), although long term prospective studies are still required. This gait retraining proposes increasing step frequency and adopting a mid or forefoot strike (Fletcher et al., 2008; Goss & Gross, 2013), but these factors examined individually or in combination have been found to have no effect on RE (Ardigo, Lafortuna, Minetti, Mognoni, & Saibene, 1995; Fletcher et al., 2008; Gruber, Umberger, Braun, & Hamill, 2013). To date, there are no reported studies that have examined if the use of both a gait retraining intervention and MFW transition can influence RE. The aims of the present study were therefore twofold; (1) to determine the effects of a combined eight week MFW and gait-retraining intervention on RE and simple kinematic changes (step frequency and foot strike patterns) in both MFW and CRS when compared to a control group in CRS with no intervention; (2) to examine if differences exist in RE and kinematics between MFW and CRS, both before and after exposure to the MFW and gait retraining intervention. Within these aims, we adopted both a within-group control (the CRS condition) as well as a between-group control (the control group) to examine these factors. Based on our previous findings (Warne & Warrington, 2013), we hypothesized that the MFW and gait-retraining intervention would improve RE in the MFW condition.
1. Methods 1.1. Participants Twenty-three moderately trained male runners (age: 43 ± 10 years, stature: 177.2 ± 9.2 cm, body _ 2max : 56.54 ± 6.97 mL min 1 kg 1) were recruited from local athletic clubs. mass: 72.8 ± 10.2 kg, VO Participants typically ran 4–6 days per week with a mean weekly running distance of 52 (±10) km at the time of the study. Participants were excluded if they had reported any running related injuries in the last three months, or had previous barefoot or minimalist running experience. Only male athletes were used to eliminate gender differences in running mechanics (Ferber, Irene, & Dorsey, 2003). All participants had previous experience with treadmill running. The participants gave informed
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consent at the beginning of testing. Ethical approval for this study was granted by the Dublin City University Research Ethics Committee. 1.2. Experimental design Twenty-three participants were recruited for the study and were randomly assigned into 2 groups. Table 1 presents anthropometric and descriptive data for the groups following dropout (see Section 2). Group 1: the intervention group comprised of 12 participants. This group was tested in both MFW and CRS at pre-test and eight weeks (post), and were required to gradually increase exposure to MFW as well as incorporate gait retraining into their running over this period (The MFW and gait-retraining will be summarized as MFW). It has been suggested that a minimum of one month is required for any observable change related to MFW kinematics (Giandolini, Horvais, Farges, Samozino, & Morin, 2013). Group 2: the control group consisted of 8 participants, and were only tested in the CRS condition at both pre and post-tests. In addition to controlling for any potential learning effects related to the tests, or changes related to training season, the control group was included to examine if RE changes in the intervention CRS condition were as a result of a ‘‘crossover’’ effect from the MFW or gait-retraining intervention (comparing the intervention CRS and control CRS). The testing protocol can be observed in Fig. 1. The control group were required to train as normal in CRS, and had no exposure to MFW or gait-retraining at any point. Groups were similarly matched in their foot strike patterns at pre-tests (70% rearfoot strikers in the intervention group, and 75% rearfoot striking in the control group). In order to avoid any potential diurnal effect, tests took place at the same time of day. Dietary intake, sleeping patterns, and training were recorded directly prior to the initial test and included all food and fluid consumed on that day for replication at post-tests. To balance order effects, a Latin square design was used to determine which footwear condition (MFW or CRS) was tested first in the intervention group between the pre and post-tests. On the first visit, foot size was measured and participants in the intervention group were provided with one pair of MFW (VibramÒ Five Finger ‘‘KSO’’; 150 g), and all participants were provided with a neutral CRS (AsicsÒ ‘‘GEL-Cumulus’’ 2012; 400 g). 1.3. Testing procedure Resting blood lactate (Lactate Plus, Nova Biomedical, Waltham, Massachusetts, USA) was sampled from the earlobe prior to the testing sessions. Respiratory data were measured using a Viasys Vmax Encore 299 online gas analysis system (Viasys Healthcare, Yorba Linda, California, USA). The system was calibrated according to the manufacturer guidelines, including atmospheric pressure and temperature, before each new test. For this system, accuracy has been reported at 0.02% for O2 measures, following a 15 min warm-up period and calibrated within 5% of absolute operating range. A treadmill (Cosmed T170, Sport Med, Weil am Rhein, Germany) RE test was then conducted in the assigned footwear. Treadmill incline was set at 1% to account for air resistance (Jones & Poole, 2005). Participants ran two trials lasting 6 min at 11 km/h. Since we cannot be sure that changes in running velocity will affect differences in RE between CRS and MFW, we controlled treadmill speed at 11 km h. Eleven km/h has previously been considered an appropriate steady state ‘‘endurance running’’ velocity (Hatala, Dingwall, Wunderlich, & Richmond, 2013). At the end of each 6-min stage, participants were asked to stand to the side of the treadmill and a blood lactate sample was collected within 30 s. The next
Table 1 Anthropometric and descriptive data for the intervention and control groups.
Intervention group (n = 12) Control group (n = 8) (M ± SD).
Age (years)
Stature (cm)
Body mass (kg)
_ 2max (mL min VO
41 (±9) 46 (±10)
177.2 (±10.4) 177.1 (±7.5)
72.6 (±10.2) 73.1 (±11.0)
52.1 (±7.5) 56.3 (±6.7)
1
kg
1
)
Kilometers per week (km) 52 (±11) 52 (±10)
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Fig. 1. Schematic representation of the testing procedure, including the intervention (Int), and control (Cnt) group.
stage was started after 3 min of rest to allow the shoe type to be swapped over. At 5-min in each stage, step frequency was collected by counting the left foot contact with the treadmill belt for 60 s duration. This procedure was repeated by the same investigator for validity in each subject and also filmed for a second assessment and accuracy (R2 = .95; Sony HDR-CX210, 60FPS; Sony, San Diego, CA, USA). Rudimentary foot strike pattern (FSP) analysis was undertaken using a low-cost video camera, in which participants were filmed in the sagittal plane at foot level over a 15 s period during the fourth minute of testing. The video footage was then used to assign 1, 2, or 3 (1 = forefoot strike, 2 = midfoot strike, 3 = rearfoot strike) to the participants’ foot strike pattern using Dartfish video analysis software (Dartfish 5.5, Fribourg, Switzerland). A midfoot strike was classified when there was no clear forefoot or heel initial contact. The validity of this method has been previously discussed by Altman and Davis (2012) and highly correlated to the strike index (R2 = .85). 1.4. Interventon Immediately after pre-tests, each subject in the intervention group was provided with a structured progression of MFW use over the eight week familiarization period, a training diary to record their training, and relevant injury prevention exercises (Tenforde et al., 2011) (Table 2). The gait retraining program was provided based on current findings in the literature (Crowell & Davis, 2011; Daoud et al., 2012; Divert, Mornieux, Baur, Mayer, & Belli, 2005; Lieberman et al., 2010; Robbins & Hanna, 1987; Squadrone & Gallozzi, 2009); adopting a non rearfoot strike and increasing step frequency have also become the main kinematic changes promoted in established running gait-retraining programmes (e.g. Chumanov, Wille, Michalski, & Heiderscheit, 2012; Dallam et al., 2005; Fletcher et al., 2008; Goss & Gross, 2013; Lenhart, Thelen, Wille, Chumanov, & Heiderscheit, 2014). Both the gait-retraining and exercises were fully demonstrated during a 30 min session until changes to step frequency (+10% steps per minute – spm), a mid/forefoot strike, more upright posture and a softer landing were adopted by the participants. This was implemented using feedback from an experienced tester in line with the simple instructions provided in Table 2. The programme incorporated MFW into the subject’s normal training routines, where it was required that the MFW took place at the beginning of any training session, and then participants were allowed to continue their normal training load in their own preferred conventional running footwear, thus not reducing their overall training workload. The participants were asked to work on the gait retraining changes both in MFW and CRS, gradually incorporating them into longer runs. The control group received no intervention or feedback, and were asked to not research or include any changes to running technique into their regular training for the duration of the testing.
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Table 2 Eight week familiarization to MFW including running technique guidelines and simple exercises for injury prevention. Week
MFW training programme
Week 1
Throughout: wearing MFW and going barefoot as much as possible in normal daily routines 3 days: 5–8 min easy running on the spot or in corridors/garden at home 3 days: prescribed exercises*
Week 2
3 days: 10–15 min running on grass, 3 min on pavement 3 days: prescribed exercises*
Week 3
2 days: 20 min running on grass, 5–8 min on pavement 1 day: 25 min running on grass 3 days: Prescribed exercises*
Week 4
2 days: 20 min on grass, 10 min on pavement 1 day: 30 min on grass 2 days: prescribed exercises*
Week 5 + 6
2 days: 20 min on grass, 15 min on pavement 1 day: 35 min on grass 2 days: prescribed exercises*
Week 7 + 8
2 days: 30 min on grass, 15 min on pavement 1 day: 40 min on grass 2 days: prescribed exercises*
Running technique guidelines Keep stride short and increase cadence. (Chumanov et al, 2012; Divert et al, 2005; Lenhart et al, 2014; Lieberman et al, 2010) Run as light and quiet as possible. (Crowell and Davis, 2011)
*
Exercise programme (10 min)
Plantar Fascia and Triceps Surae Rolling x 5 mins
Land on the forefoot, allowing heel to Contact immediately afterwards. (Daoud et al, 2012; Lieberman et al, 2010; Robbins and Hanna, 1987)
Ankle Mobility (3 x 15)
Keep hips forward and head up, running as tall and proud as possible. (Lieberman et al, 2010)
Toe “Grabs” (3 x 15)
Calf Raises (3 x 15)
Single leg balance (60secs)
No specification was made as to whether the exercises were completed on the same days as the running intervention or not.
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_ 2max 1.5. Testing procedure – VO _ 2max test was completed at the end of the final testing day for subject characterization. This A VO involved a ramped treadmill protocol at 12 km/h for a 5-min warm-up before increasing to 14 km/h at 1% incline. The incline was then increased every minute until volitional exhaustion, and correlated with participants achieving a respiratory quotient (RQ) of 1.1 or above. Participants con_ 2max was recorded as the highest breath-by-breath value ducted this test in their own shoe choice. VO averaged over 60 s. 1.6. Data processing The RE values were determined from the mean data over the last 2 min of each stage when partic_ 2 . This was verified by less than a 1 mmol increase in blood ipants had reached a true steady-state VO lactate (post trial minus resting lactate) as this is considered well below maximal lactate steady state (Svedahl & MacIntosh, 2003), and an RQ of less than 1.0 (Brooks, Fahey, & White, 1996). Foot strike patterns were reported as frequencies. 1.7. Data analysis In order to examine aim 1 and 2, the effect of time (aim 1; pre–post-tests) and condition (aim 2; MFW vs. CRS) with regard to RE and step frequency were examined using two-way repeated measures analyses of variance (ANOVA) for within-subjects effects. Differences between the intervention and control group were established with a two-way (group [CRS intervention and CRS control], and time [pre to post-tests]) mixed ANOVA for between-subject effects, and changes over time in the control group were examined using paired t-tests. (Statistical Package for the Social Sciences data analysis software V16.0, SPSS Inc, Chicago, Illinois, USA). Statistical significance was accepted at a 6 0.05. Foot strike pattern changes have been presented as frequencies. Effect sizes are reported as eta squared (g2) for ANOVA tests and Cohen’s d for t tests. To make inferences about true (population) values for the effect of an MFW and gait retraining intervention on RE, the uncertainty of the effect was expressed as 95% confidence limits and the likelihood that the true value of the effect represents substantial change (harm or benefit) (Batterham & Hopkins, 2006). The smallest worthwhile change in RE was calculated as 2.4% of the shod RE at pre-tests (Saunders, Pyne, Telford, & Hawley, 2004). For the remaining variables, the smallest standardized change that is considered meaningful was assumed to be an effect size of 0.20 for Cohen’s d and 0.01 for g2 (Cohen, 1988). 2. Results No participants were excluded based on any ‘‘slow component’’ for submaximal VO2 consumption, an increase in blood lactate of >1 mmol (mean change from resting = .44 mmol), and an RQ greater than 1.0. During testing, one participant from the intervention group became injured (metatarsal stress fracture), and two participants from the control group became ill and were removed from the final data analysis (remaining n = 20; Table 1). Seven out of 13 participants in the intervention group also reported mild triceps surae soreness in the first two weeks, but this did not result in any reduction in training or intervention compliance. Participant compliance with the intervention schedule was good (mean compliance 78%, as recorded by feedback of missed runs or exercise sessions during intervention); all participants were able to complete the longer runs in the latter weeks and were well exposed to MFW running by week 8. Results are reported as (p value; mean change [95% CI]; uncertainty of effect; effect size). Mean values for RE and step frequency are presented in Table 3. Mean step frequency results were comparable to previous work investigating the same MFW (Squadrone & Gallozzi, 2009). Aim one: over the course of the eight week trial there was no significant change in the intervention group for RE (p = .99; 0.02 mL min 1 kg 1 [ 2.3 to 2.3]; 18.9% – unlikely beneficial; g2 = 0.00) (Table 3). No difference for the change in RE over time was observed between the intervention and
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J.P. Warne et al. / Human Movement Science 42 (2015) 183–192 Table 3 Running economy (RE) and step frequency (SF) results for the MFW and CRS condition, and the control group. Intervention group (n = 12)
MFW
Time
Pre
Post
Pre
Post
40.60 ± 4.29 178.7 ± 10.1
40.72 ± 4.08 184.2 ± 10.6
42.13 ± 4.25 171.0 ± 10.3
42.04 ± 4.68 176.8 ± 10.5
42.74 ± 4.07 166.3 ± 6.1
42.39 ± 2.06 168.0 ± 5.2
RE (mL min 1 kg SF (steps/min)
1
)
CRS
Control Group (n = 8) RE (mL min 1 kg 1) SF (steps/min) Data presented as mean ± SD.
control group (p = .78). No change in RE was observed in the control group from pre to post-tests (p = .95; 0.1 mL min 1 kg 1 [ 2.7 to 2.9]; Cohen’s d = 0.00). There was a significant increase in step frequency as a result of the intervention (p < .001; 5.7 spm [7.6–3.8], g2 = 0.077). Step frequency in the control group did not change (p = .078; 1.7 spm [3.7 to 0.3]; Cohen’s d = 0.43) (Table 3). The distribution of foot strike patterns are displayed in Fig. 2 for the intervention group. 75% of participants adopted a rearfoot strike in both CRS and MFW at pre-tests. At post-tests only 50% of participants in CRS used a rearfoot strike, and 33% of participants in MFW used a rearfoot strike. In the control group, 6/7 participants used a rearfoot strike, and 1/7 used a midfoot strike. This did not change from pre to post-tests. Aim 2: RE was significantly better in MFW (2.72%) when compared to CRS (p = .002; 1.4 mL min 1 kg 1 [ 2.2 to 0.7]; 86.5% – likely beneficial; g2 = 0.035) irrespective of the intervention (Table 3). There was a significantly higher step frequency observed in MFW when compared to CRS (p < .001; 7.5 spm [6.0–9.0], g2 = 0.129). 3. Discussion The main finding of the present study revealed that an eight week MFW and gait retraining intervention did not result in any significant change in RE, when assessed in both MFW and CRS conditions and this rejects the study hypothesis. Whilst it is possible that a familiarization to MFW does enhance RE (Warne & Warrington, 2013), this was not the case in the present study with a similar intervention that included gait retraining. This finding is in accordance with previous research which reported that
10 9 Occurrence of FSP
8 7 6 5
FFS
4
MFS
3
RFS
2
1 0 Pre MFW
Post MFW
Pre CRS
Post CRS
Time Fig. 2. Foot strike patterns of both the MFW and CRS condition during the eight week intervention.
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gait retraining had no effect on RE (Ardigo et al., 1995; Fletcher et al., 2008; Gruber et al., 2013; Messier & Cirillo, 1989), or may even make RE worse (Cavanagh & Williams, 1982; Dallam et al., 2005; Tseh, Caputo, & Morgan, 2008). To support these studies, Nigg and Enders (2013) and Saunders et al. (2004) have suggested that self-selected running kinematics rather than deliberate changes are more appropriate for optimizing RE. This may be because deliberate changes result in deviations from the preferred movement pathway that has been dictated by physiological and neuromuscular adaptations to repeated training (Saunders et al., 2004) that will not be optimized immediately (Bonacci, Chapman, Blanch, & Vicenzino, 2009). One example why deliberate changes may decrease RE may be the recruitment of different muscle fibers at different speeds of contraction that will increase metabolic cost (Bonacci et al., 2009; Kaneko, 1990). This may also be due to changes in running mechanics such as leg stiffness (Butler, Crowell, & Davis, 2003) and requires further investigation. Regardless, this study compliments the already available body of literature suggesting RE cannot be improved with deliberate changes to running kinematics. This is however the first study to investigate both MFW and gait retraining combined, and suggests that the inclusion of MFW to the gait retraining intervention did not have any effect on RE either. The kinematic changes observed as a result of the intervention provide important information on the incorporation of the gait retraining. Step frequency was found to significantly increase during the eight weeks. Likewise with regard to the foot strike patterns there was a higher prevalence of non-rearfoot strikes in MFW and CRS, although to a lesser extent in the CRS. This observed difference in foot strike pattern between MFW and CRS was observed in previous studies (Warne & Warrington, 2013; Warne et al., 2013). Given that the present participants were asked to adopt a forefoot strike pattern, these results suggest that CRS may result in a lower prevalence of midfoot or forefoot strike patterns. This may be due to the elevated profile of the shoe or a reduction of sensory feedback from the foot (De Wit, De Clercq, & Aerts, 2000; Divert et al., 2005). In the present work, step frequency and foot strike changes can provide an indication of kinematic change associated with the intervention, however there is no strong evidence that either step frequency or the foot striking pattern can influence RE (e.g. Cavanagh & Williams, 1982; Gruber et al., 2013). Given that we observed no change in RE, but a change in step frequency and foot strike, our results support these previous studies. With regard to the second study aim, a significant and worthwhile improvement in RE was observed in the MFW condition when compared to CRS irrespective of the intervention (86.5% likely beneficial). Differences in RE between MFW and CRS have been reported previously (Perl et al., 2012; Squadrone & Gallozzi, 2009; Warne & Warrington, 2013). Several authors have described a better RE in the barefoot condition to be solely related to the mass of traditional shoes (Divert et al., 2008; Flaherty, 1994), where a 1% increase in the oxygen cost of running has been observed for every 100 g of added mass (Divert et al., 2008; Saunders et al., 2004). Given that the difference in shoe mass in the present study was 250 g which was not controlled for, this may explain the majority (2.5%) of the observed difference in RE (2.7%) between the MFW and CRS conditions. Also, the MFW used in our study was found to result in a better RE than barefoot in Squadrone and Gallozzi (2009), and this may be due to the small protective layer of rubber that reduces the metabolic cost of cushioning the body (Franz, Wierzbinski, & Kram, 2012). Saunders et al. (2004) have suggested that anything above a 2.4% change in RE is a worthwhile improvement in performance. Likewise Di Prampero et al. (1993) concluded that a 5% improvement in RE elicited a 3.8% increase in run performance, suggesting that even changes due to shoe mass are worthwhile. Our study suggests that there is a meaningful and likely benefit to wearing MFW, irrespective of whether the participants are familiarized to this footwear or not. We acknowledge that this intervention combines both MFW and gait retraining without concern for the individual effects of either factor. Ideally this study should include two further groups with only a MFW or gait retraining exposure, but this would require a very large body of participants. A limitation of the present study was the lack of any kinematic measurements throughout the intervention period to ensure that the gait retraining changes were being effectively executed. Whilst we measured step frequency and foot strike patterns and observed a change, a more comprehensive analysis to monitor the incorporation of the gait retraining elements is recommended. Indeed previous work has found that participants cannot correctly report their running pattern (Goss, 2012), and so may not be incorporating the ‘‘correct’’ changes, despite being under the impression that they were. In
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addition, the study design allowed participants to continue their normal training in CRS. This was in order to safely maintain training volume without excessive exposure to MFW running that may increase injury risk due to the novel footwear condition. Therefore, a transition to MFW with no CRS training allowed may result in very different findings. Finally, we only examined RE at 11 km h in the present work and therefore future work should examine higher velocities. 4. Conclusion This study suggests that gait-retraining coupled with MFW use is not an effective means to improve RE. However, the use of MFW in itself can result in a significantly better RE (2.72%) when compared to CRS irrespective of whether subjects are familiarized or not. This is most likely to be due to mass differences, but this factor may improve running performance. There was a significant increase in step frequency, and a higher tendency to forefoot strike observed as a result of the intervention. Conflicts of interest The authors have received a donation of footwear for the present study from VibramÒ (Milan, Italy). No honoraria or conditions have been attached to this donation, and the company has no direction or involvement in the research. Acknowledgements The authors would like to thank Professor Alan M. Nevill (School of Sport, Performing Arts and Leisure, University of Wolverhampton, Walsall, UK) for his continued support and guidance with regard to statistical procedures. References Altman, A. R., & Davis, I. S. (2012). A kinematic method for footstrike pattern detection in barefoot and shod runners. Gait and Posture, 35(2), 298–300. Ardigo, L. P., Lafortuna, C., Minetti, A. E., Mognoni, P., & Saibene, F. (1995). Metabolic and mechanical aspects of foot landing type, forefoot and rearfoot strike, in human running. Acta Physiologica Scandinavica, 155(1), 17–22. Batterham, A. M., & Hopkins, W. G. (2006). Making meaningful inferences about magnitudes. International Journal of Sports Physiology and Performance, 1(1). Bonacci, J., Chapman, A., Blanch, P., & Vicenzino, B. (2009). Neuromuscular adaptations to training, injury and passive interventions. Implications for running economy. Sports Medicine, 39(11), 903–921. Brooks, G. A., Fahey, T. D., & White, T. P. (1996). Exercise physiology: Human bioenergetics and its applications (2nd ed.). Mayfield Publishing Company. Butler, R. J., Crowell, H. P., III, & Davis, I. M. (2003). Lower extremity stiffness: Implications for performance and injury. Clinical Biomechanics, 18(6), 511–517. Cavanagh, P. R., & Williams, K. R. (1982). The effect of step length variation on oxygen uptake during distance running. Medicine and Science in Sports and Exercise, 14(1), 30–35. Chumanov, E. S., Wille, C. M., Michalski, M. P., & Heiderscheit, B. C. (2012). Changes in muscle activation patterns when running step rate is increased. Gait and Posture, 36(2), 231–235. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Psychology Press. Crowell, H. P., & Davis, I. S. (2011). Gait retraining to reduce lower extremity loading in runners. Clinical Biomechanics, 26(1), 78–83. Dallam, G. M., Wilber, R. L., Jadelis, K., Fletcher, G., & Romanov, N. (2005). Effects of global alteration of running technique on kinematics and economy. Journal of Sports Sciences, 23(7), 757–764. Daoud, A. I., Geissler, G. J., Wang, F., Saretsky, J., Daoud, Y. A., & Lieberman, D. E. (2012). Foot strike and injury rates in endurance runners: A retrospective study. Medicine and Science in Sports and Exercise, 44(7), 1325–1334. De Wit, B., De Clercq, D., & Aerts, P. (2000). Biomechanical analysis of the stance phase during barefoot and shod running. Journal of Biomechanics, 33(3), 269–278. Di Prampero, P. E., Capelli, C., Pagliaro, P., Antonutto, G., Girardis, M., Zamparo, P., et al (1993). Energetics of best performances in middle distance running. Journal of Applied Physiology, 74(5), 2318–2324. Divert, C., Mornieux, G., Freychat, P., Baly, L., Mayer, F., & Belli, A. (2008). Barefoot-Shod running differences: Shoe or mass effect? International Journal of Sports Medicine, 29, 512–518. Divert, C., Mornieux, G., Baur, H., Mayer, F., & Belli, A. (2005). Mechanical comparison of barefoot and shod running. International Journal of Sports Medicine, 26(7), 593–598.
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