Running science nerd alert.
by Thomas Solomon PhD and Matt Laye PhD
January 2021.
Each month we compile a short-list of recently-published papers (full list here) in the world of running science and break them into bite-sized chunks so you can digest them as food for thought to help optimise your training. To help wash it all down, we even review our favourite beer of the month.
Welcome to this month's installment of our "Nerd Alert". We hope you enjoy it.
Welcome to this month's installment of our "Nerd Alert". We hope you enjoy it.
Click the title of each article to "drop-down" the summary.
Full paper access: click here
What was the hypothesis or research question?
Transcranial direct current stimulation (tDCS) is a weak constant electrical current (1-3 mA) between two electrodes placed over the scalp that modifies the resting membrane potential and consequently increases (anodal) or decreases (cathodal) the excitability of the targeted brain area for up to 90 minutes after stimulation. The authors aimed to determine the effect of anodal-tDCS on endurance (time to exhaustion or endurance time trial) and sprint performance during cycling and running tasks.
What did they do to test the hypothesis or answer the research question?
— The authors completed a systematic review of randomized controlled trials in healthy folks in which an anodal-tDCS protocol was used prior to cycling or running tests.
— The effect of anodal-tDCS was compared against sham stimulation (i.e. wearing all the gear but no stimulation).
What did they find?
— A total of 15 interventions from 13 randomized controlled trials were included.
— Sub-group analysis found a statistically-significant (P = 0.01) positive effect of anodal-tDCS on endurance time-to-exhaustion with a small effect size (standardized mean differences) of 0.37 with a 90% confidence interval of 0.13 to 0.61.
— tDCS had no effect on endurance time trial (effect size = 0.00; 90% CI = -0.29, 0.30; P = 1.00) or sprint performance (SMD = 0.19; 90% CI = -0.23, 0.60; P = 0.46).
What were the strengths?
— The authors used Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines.
— Articles were screened independently by two authors using the PICOS approach (population, intervention, comparators, outcome, and study design, and authors of experimental studies were contacted if data were unavailable.
— Methods were clearly described and data quality were evaluated and clearly presented using the physiotherapy evidence database (PEDro) scale.
— All study characteristics were clearly presented.
— A meta-analysis was conducted and standardized mean differences (effect sizes; calculated by dividing the raw difference by the within-group standard deviation) were pooled with a random effect model and interpreted according to Cohen’s rules. Heterogeneity between studies was assessed using I² statistics and these were presented along with effect sizes.
What were the weaknesses?
— The review protocol was not published prior to commencing the systematic review.
— All studies were single blinded (to the subject) and group allocations were not concealed, so investigators and analysers knew the trial allocations and treatments being administered.
— No funnel plot was presented to show symmetry (or homogeneity) between the standard error (precision) and the size of the effect in the different randomized controlled trials, to therefore rule-out publication bias.
Are the findings useful in application to training/coaching practice?
Yes.
Some, but not all, studies have found performance enhancing benefits of using transcranial direct current stimulation prior to exercise, along with lower ratings of perceived exertion (RPE) by reducing the physical effort needed to perform exercise. This meta-analysis finds that anodal tDCS (which increases the excitability of the targeted brain area) prior to exercise can prolong time-to-exhaustion during exercise performance at 70-80% of peak power, which is a low-to-moderate intensity for most athletes. But coaches and athletes should place this in ecological context — running or cycling until failure at a low-to-moderate intensity is not reflective of what occurs in a race. Coaches and athletes should also take heed that this meta-analysis also shows that anodal-tDCS does not enhance cycling sprint performance or cycling time-trial performance. However, it is important to know that only 2 sprint studies exist and no running time-trial or sprint studies have yet been completed. Another important observation from this meta-analysis is the large range in response to tDCS — many subjects have a negative effective on time-to-exhaustion, TT performance, and sprinting — so if you do use it, make sure you gain from it and that it doesn’t blunt all your hard work.
Transcranial direct current stimulation is an emerging performance enhancement tool for which more research is needed, mechanisms are not understood, and safety has not been fully evaluated. tDCS is also not currently prohibited by WADA despite its “neurological doping” potential. For a nice overview of the topic, I can recommend reading a 2019 commentary by Zhu et al. published in Front Physiol.
What was the hypothesis or research question?
Transcranial direct current stimulation (tDCS) is a weak constant electrical current (1-3 mA) between two electrodes placed over the scalp that modifies the resting membrane potential and consequently increases (anodal) or decreases (cathodal) the excitability of the targeted brain area for up to 90 minutes after stimulation. The authors aimed to determine the effect of anodal-tDCS on endurance (time to exhaustion or endurance time trial) and sprint performance during cycling and running tasks.
What did they do to test the hypothesis or answer the research question?
— The authors completed a systematic review of randomized controlled trials in healthy folks in which an anodal-tDCS protocol was used prior to cycling or running tests.
— The effect of anodal-tDCS was compared against sham stimulation (i.e. wearing all the gear but no stimulation).
What did they find?
— A total of 15 interventions from 13 randomized controlled trials were included.
— Sub-group analysis found a statistically-significant (P = 0.01) positive effect of anodal-tDCS on endurance time-to-exhaustion with a small effect size (standardized mean differences) of 0.37 with a 90% confidence interval of 0.13 to 0.61.
— tDCS had no effect on endurance time trial (effect size = 0.00; 90% CI = -0.29, 0.30; P = 1.00) or sprint performance (SMD = 0.19; 90% CI = -0.23, 0.60; P = 0.46).
What were the strengths?
— The authors used Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines.
— Articles were screened independently by two authors using the PICOS approach (population, intervention, comparators, outcome, and study design, and authors of experimental studies were contacted if data were unavailable.
— Methods were clearly described and data quality were evaluated and clearly presented using the physiotherapy evidence database (PEDro) scale.
— All study characteristics were clearly presented.
— A meta-analysis was conducted and standardized mean differences (effect sizes; calculated by dividing the raw difference by the within-group standard deviation) were pooled with a random effect model and interpreted according to Cohen’s rules. Heterogeneity between studies was assessed using I² statistics and these were presented along with effect sizes.
What were the weaknesses?
— The review protocol was not published prior to commencing the systematic review.
— All studies were single blinded (to the subject) and group allocations were not concealed, so investigators and analysers knew the trial allocations and treatments being administered.
— No funnel plot was presented to show symmetry (or homogeneity) between the standard error (precision) and the size of the effect in the different randomized controlled trials, to therefore rule-out publication bias.
Are the findings useful in application to training/coaching practice?
Yes.
Some, but not all, studies have found performance enhancing benefits of using transcranial direct current stimulation prior to exercise, along with lower ratings of perceived exertion (RPE) by reducing the physical effort needed to perform exercise. This meta-analysis finds that anodal tDCS (which increases the excitability of the targeted brain area) prior to exercise can prolong time-to-exhaustion during exercise performance at 70-80% of peak power, which is a low-to-moderate intensity for most athletes. But coaches and athletes should place this in ecological context — running or cycling until failure at a low-to-moderate intensity is not reflective of what occurs in a race. Coaches and athletes should also take heed that this meta-analysis also shows that anodal-tDCS does not enhance cycling sprint performance or cycling time-trial performance. However, it is important to know that only 2 sprint studies exist and no running time-trial or sprint studies have yet been completed. Another important observation from this meta-analysis is the large range in response to tDCS — many subjects have a negative effective on time-to-exhaustion, TT performance, and sprinting — so if you do use it, make sure you gain from it and that it doesn’t blunt all your hard work.
Transcranial direct current stimulation is an emerging performance enhancement tool for which more research is needed, mechanisms are not understood, and safety has not been fully evaluated. tDCS is also not currently prohibited by WADA despite its “neurological doping” potential. For a nice overview of the topic, I can recommend reading a 2019 commentary by Zhu et al. published in Front Physiol.
Full paper access: click here
What was the hypothesis or research question?
Concurrent strength and running training within the same mesocycle can improve endurance performance in middle- and long-distance events but little is known about what happens when concurrent training is ceased. No hypothesis was stated but the authors “expected that the training-related benefits on the energy cost of running would be maintained after training cessation despite reductions in lower-body maximal power”. The authors aim was vague: “to describe the effects of 4 weeks of explosive strength training cessation after an 8-week concurrent training protocol”.
What did they do to test the hypothesis or answer the research question?
— Eight well-trained male distance runners completed 8 weeks of concurrent training including either plyometric (n = 4) or dynamic weight training (n = 4) in addition to their usual running. Then, strength training was stopped for 4 weeks during which running training continued.
— Energy cost of running, VO2max, lower-body maximal power, countermovement jumps (CMJ) performance, and 3000 m time trial performance was measured in all subjects at baseline, after the concurrent period and after the strength cessation period.
— Strength training included 1 explosive strength session per week in addition to their normal running regimen. Strength training load was equivalent for both experimental groups (plyometric and dynamic weight groups) with 3 to 6 sets of 8 reps completed during each session — but no more details are provided.
— Running training included 3 sessions per week with “an emphasis on maximal aerobic speed, intermittent aerobic endurance, and continuous aerobic endurance” — but no more details are provided.
— Individual data for each participant were reported and effect sizes (Hedges’ g) and percent-changes were calculated to compare the time-points during the intervention. The 95% CI (confidence interval) of the percent changes were reported, which is an estimate of likely percent-change values that would be found in 95% of all people). Note that if the 95%CI of the percent change crosses zero (i.e. the range includes both positive and negative changes), the finding would not be deemed statistically significant.
What did they find?
— Following the concurrent 8-week period, the energy cost of running decreased (improved running economy) with a moderate effect size of −0.57 (95% CI −8.47 to −3.03). In the 4 subjects who undertook plyometric training, the decrease in the energy cost of running was large (g = −0.95; 95% CI of the percent change = −8.97 to −7.38 whereas the effect was small in 4 who undertook dynamic weight training (g = −0.38; 95% CI = −7.68 to +1.02).
— At 12-weeks, 4-weeks after strength cessation, the improved running economy was maintained (effect size vs. baseline = −0.61; 95% CI = −10.30 to −2.32). The maintenance was similar between plyometric (g = −0.42; 95% CI = −15.82 to +0.13) and dynamic weights subjects (g = −0.55; 95% CI = −10.01 to +0.45) when compared to baseline.
— A small improvement was found in maximal power (g = 0.33; 95% CI = −3.10 to +19.07) and counter-movement jump performance (g = 0.46; 95% CI = +5.46 to +12.78) after concurrent training (8-wk vs. baseline).
— Improved maximal power was maintained (g = 0.20, 95% CI = −5.96 to +15.86) and counter-movement jump performance (g = 0.28; 95% CI = +4.42 to +11.17) after the cessation of strength training (12-wk vs. baseline).
— A trivial change (i.e. very little effect of intervention) was found for VO2max (g = −0.31 for 8-wk vs. baseline, i.e. after concurrent training; g = −0.20 for 12-wk vs. baseline, i.e. after cessation of strength training).
— A small improvement was observed for 3000 m performance after concurrent training (g = −0.24, 95% CI = −4.65 to −0.16) and after cessation of strength training (g = −0.48, 95% CI = −6.83 to −2.03).
What were the strengths?
— Given the small sample size, the authors chose to use descriptive stats and presented individual data for each participant as well as effect size (Hedges’ g) estimates to compare the time-points during the intervention.
What were the weaknesses?
— The study is not original but a case-report of participants who completed the training cessation intervention in their previous study which had a 40% attrition rate.
— While effect sizes were reported as the standardised mean difference, the range of effect size estimates (the 95% CI) was reported as the percentage change. No CI for the Hedge’s G effect size was calculated so we cannot estimate the range of likely effect sizes in all people.
— Only male subjects were included.
— No control (non-cessation) intervention group was included.
— The sample size of 8 is small and not justified.
— The strength training included either plyometric or dynamic weight training — it is not clear why nor is it clear whether they intended to independently study the effects of each.
— Detailed training plans or training load measurements are not provided.
Are the findings useful in application to training/coaching practice?
No.
The authors conclude that the improved running economy observed after an 8-week concurrent strength + running training period in well-trained distance runners was maintained following 4-weeks cessation of strength training. However, the paper is not useful because it is an incomplete study of only 8 subjects that lacks a non-cessation control group and, among the 8 subjects, 4 engaged in plyometric strength training while the other 4 used “dynamic” strength training (which is not explained).
For coaches and athletes, understanding the effects of concurrent training for runners is important since strength training, particularly explosive training can improve economy and race performance. Understanding what happens when strength training is stopped is also important for helping inform the design of tapering periods. This paper does nothing to help educate that and, unfortunately, does nothing but contaminates the literature with incomplete data that could misinform. There are many other resources that can help. I suggest checking out other systematic reviews of this field for further info (examples here and here)
What was the hypothesis or research question?
Concurrent strength and running training within the same mesocycle can improve endurance performance in middle- and long-distance events but little is known about what happens when concurrent training is ceased. No hypothesis was stated but the authors “expected that the training-related benefits on the energy cost of running would be maintained after training cessation despite reductions in lower-body maximal power”. The authors aim was vague: “to describe the effects of 4 weeks of explosive strength training cessation after an 8-week concurrent training protocol”.
What did they do to test the hypothesis or answer the research question?
— Eight well-trained male distance runners completed 8 weeks of concurrent training including either plyometric (n = 4) or dynamic weight training (n = 4) in addition to their usual running. Then, strength training was stopped for 4 weeks during which running training continued.
— Energy cost of running, VO2max, lower-body maximal power, countermovement jumps (CMJ) performance, and 3000 m time trial performance was measured in all subjects at baseline, after the concurrent period and after the strength cessation period.
— Strength training included 1 explosive strength session per week in addition to their normal running regimen. Strength training load was equivalent for both experimental groups (plyometric and dynamic weight groups) with 3 to 6 sets of 8 reps completed during each session — but no more details are provided.
— Running training included 3 sessions per week with “an emphasis on maximal aerobic speed, intermittent aerobic endurance, and continuous aerobic endurance” — but no more details are provided.
— Individual data for each participant were reported and effect sizes (Hedges’ g) and percent-changes were calculated to compare the time-points during the intervention. The 95% CI (confidence interval) of the percent changes were reported, which is an estimate of likely percent-change values that would be found in 95% of all people). Note that if the 95%CI of the percent change crosses zero (i.e. the range includes both positive and negative changes), the finding would not be deemed statistically significant.
What did they find?
— Following the concurrent 8-week period, the energy cost of running decreased (improved running economy) with a moderate effect size of −0.57 (95% CI −8.47 to −3.03). In the 4 subjects who undertook plyometric training, the decrease in the energy cost of running was large (g = −0.95; 95% CI of the percent change = −8.97 to −7.38 whereas the effect was small in 4 who undertook dynamic weight training (g = −0.38; 95% CI = −7.68 to +1.02).
— At 12-weeks, 4-weeks after strength cessation, the improved running economy was maintained (effect size vs. baseline = −0.61; 95% CI = −10.30 to −2.32). The maintenance was similar between plyometric (g = −0.42; 95% CI = −15.82 to +0.13) and dynamic weights subjects (g = −0.55; 95% CI = −10.01 to +0.45) when compared to baseline.
— A small improvement was found in maximal power (g = 0.33; 95% CI = −3.10 to +19.07) and counter-movement jump performance (g = 0.46; 95% CI = +5.46 to +12.78) after concurrent training (8-wk vs. baseline).
— Improved maximal power was maintained (g = 0.20, 95% CI = −5.96 to +15.86) and counter-movement jump performance (g = 0.28; 95% CI = +4.42 to +11.17) after the cessation of strength training (12-wk vs. baseline).
— A trivial change (i.e. very little effect of intervention) was found for VO2max (g = −0.31 for 8-wk vs. baseline, i.e. after concurrent training; g = −0.20 for 12-wk vs. baseline, i.e. after cessation of strength training).
— A small improvement was observed for 3000 m performance after concurrent training (g = −0.24, 95% CI = −4.65 to −0.16) and after cessation of strength training (g = −0.48, 95% CI = −6.83 to −2.03).
What were the strengths?
— Given the small sample size, the authors chose to use descriptive stats and presented individual data for each participant as well as effect size (Hedges’ g) estimates to compare the time-points during the intervention.
What were the weaknesses?
— The study is not original but a case-report of participants who completed the training cessation intervention in their previous study which had a 40% attrition rate.
— While effect sizes were reported as the standardised mean difference, the range of effect size estimates (the 95% CI) was reported as the percentage change. No CI for the Hedge’s G effect size was calculated so we cannot estimate the range of likely effect sizes in all people.
— Only male subjects were included.
— No control (non-cessation) intervention group was included.
— The sample size of 8 is small and not justified.
— The strength training included either plyometric or dynamic weight training — it is not clear why nor is it clear whether they intended to independently study the effects of each.
— Detailed training plans or training load measurements are not provided.
Are the findings useful in application to training/coaching practice?
No.
The authors conclude that the improved running economy observed after an 8-week concurrent strength + running training period in well-trained distance runners was maintained following 4-weeks cessation of strength training. However, the paper is not useful because it is an incomplete study of only 8 subjects that lacks a non-cessation control group and, among the 8 subjects, 4 engaged in plyometric strength training while the other 4 used “dynamic” strength training (which is not explained).
For coaches and athletes, understanding the effects of concurrent training for runners is important since strength training, particularly explosive training can improve economy and race performance. Understanding what happens when strength training is stopped is also important for helping inform the design of tapering periods. This paper does nothing to help educate that and, unfortunately, does nothing but contaminates the literature with incomplete data that could misinform. There are many other resources that can help. I suggest checking out other systematic reviews of this field for further info (examples here and here)
What was the beer called?
Chocolate clouds.
Which brewery made it? Basqueland brewing.
What type of beer is it? Imperial double-pastry stout.
How strong is the beer (ABV)? 12.5% ABV.
How would I describe this beer? Aroma of a very tasty medicine. Light but strong flavour on the tongue with hints of chocolate and licorice. Tastes like a liquid version of the Bohemian Rhapsody. Smooth aftertaste. Splendid.
What is my Rating of Perceived beer Enjoyment? RP(be)E(r) = 9 out of 10.
Which brewery made it? Basqueland brewing.
What type of beer is it? Imperial double-pastry stout.
How strong is the beer (ABV)? 12.5% ABV.
How would I describe this beer? Aroma of a very tasty medicine. Light but strong flavour on the tongue with hints of chocolate and licorice. Tastes like a liquid version of the Bohemian Rhapsody. Smooth aftertaste. Splendid.
What is my Rating of Perceived beer Enjoyment? RP(be)E(r) = 9 out of 10.
Full paper access: click here
What was the hypothesis or research question?
Running downhill and uphill are clearly very different activities. However, the research comparing the adaption to each of these is sparse and no studies have examined whether downhill or uphill result in similar adaptations, either the amount or the type of adaptation. The researchers sought to see whether downhill versus uphill high intensity interval training would induce different muscular adaptations. They hypothesized that downhill running would preferentially improve muscle strength and power (due to the enhanced eccentric component) and that uphill running would preferentially increase muscle endurance.
What did they do to test the hypothesis or answer the research question?
— They recruited 14 healthy college students (11 males) with a recreational training background and had them train for 8 weeks with 2 high intensity interval workouts per a week.
— Supervised workouts were 10 x 30 seconds with 60 seconds rest at 90% of maximal aerobic speed (MAS). MAS was determined by adjusting the speed 1km/h every 2 minutes until exhaustion during pretesting and readjusted halfway through the training program.
— Additional measures of muscle function included 3 countermeasure jumps, squat jumps, maximal isometric knee extension/flexion, maximal voluntary contraction, isokinetic knee extension force production, and fatigability via 50 maximal isokinetic efforts. Muscle architecture was characterized by ultrasound for muscle thickness, fascicle angle, and fascicle length (images were blinded for analysis).
What did they find?
— The rate of force development for knee extension improved over the first 300msec of contraction in the downhill group but not the uphill group, but no difference between groups was found.
— No changes in maximal force development, isokinetic force production, nor countermeasure jumps between groups occurred while the downhill group did improve their squat jumps (9.5%, p = 0.42, d = -0.31).
— The uphill group was able to increase the amount of force produced during the isokinetic fatigue protocol by 15% and was 20% less fatigued than pre-training levels.
— Fascicle length and thickness was decreased in the downhill running group, but not the uphill group.
What were the strengths?
— Supervised training sessions.
— Relatively little training stimulus (10 x 30seconds, 2x a week)
What were the weaknesses?
— No flat group control.
— No real measure of running performance. A countermeasure jump does not determine performance.
— Unequal, inadequate number of females. .
— No actual differences between the training groups.
— Power was calculated on chances of seeing one group change without consideration of the other group and therefore the study was likely underpowered.
Are the findings useful in application to training/coaching practice?
Most coaches know that uphill and downhill running work different aspects of physiology and help an athlete prepare for different demands. This study furthers that knowledge and suggests that a mixture of workouts would be necessary for maximal adaptation (this could be tested in the future). However, it provides very little guidance as to what to do and the magnitude of the effects. The primary outcomes in this study don’t necessarily translate to improved performance or reduced injury risk and therefore over interpretation is cautioned against.
What was the hypothesis or research question?
Running downhill and uphill are clearly very different activities. However, the research comparing the adaption to each of these is sparse and no studies have examined whether downhill or uphill result in similar adaptations, either the amount or the type of adaptation. The researchers sought to see whether downhill versus uphill high intensity interval training would induce different muscular adaptations. They hypothesized that downhill running would preferentially improve muscle strength and power (due to the enhanced eccentric component) and that uphill running would preferentially increase muscle endurance.
What did they do to test the hypothesis or answer the research question?
— They recruited 14 healthy college students (11 males) with a recreational training background and had them train for 8 weeks with 2 high intensity interval workouts per a week.
— Supervised workouts were 10 x 30 seconds with 60 seconds rest at 90% of maximal aerobic speed (MAS). MAS was determined by adjusting the speed 1km/h every 2 minutes until exhaustion during pretesting and readjusted halfway through the training program.
— Additional measures of muscle function included 3 countermeasure jumps, squat jumps, maximal isometric knee extension/flexion, maximal voluntary contraction, isokinetic knee extension force production, and fatigability via 50 maximal isokinetic efforts. Muscle architecture was characterized by ultrasound for muscle thickness, fascicle angle, and fascicle length (images were blinded for analysis).
What did they find?
— The rate of force development for knee extension improved over the first 300msec of contraction in the downhill group but not the uphill group, but no difference between groups was found.
— No changes in maximal force development, isokinetic force production, nor countermeasure jumps between groups occurred while the downhill group did improve their squat jumps (9.5%, p = 0.42, d = -0.31).
— The uphill group was able to increase the amount of force produced during the isokinetic fatigue protocol by 15% and was 20% less fatigued than pre-training levels.
— Fascicle length and thickness was decreased in the downhill running group, but not the uphill group.
What were the strengths?
— Supervised training sessions.
— Relatively little training stimulus (10 x 30seconds, 2x a week)
What were the weaknesses?
— No flat group control.
— No real measure of running performance. A countermeasure jump does not determine performance.
— Unequal, inadequate number of females. .
— No actual differences between the training groups.
— Power was calculated on chances of seeing one group change without consideration of the other group and therefore the study was likely underpowered.
Are the findings useful in application to training/coaching practice?
Most coaches know that uphill and downhill running work different aspects of physiology and help an athlete prepare for different demands. This study furthers that knowledge and suggests that a mixture of workouts would be necessary for maximal adaptation (this could be tested in the future). However, it provides very little guidance as to what to do and the magnitude of the effects. The primary outcomes in this study don’t necessarily translate to improved performance or reduced injury risk and therefore over interpretation is cautioned against.
Full paper access: click here
What was the hypothesis or research question?
As you fatigue during increasing duration of running how you do the work changes locations within the body. Typically, you shift from distal joints (such as your foot and ankle) to more proximal joints (such as the knee and hip). This may explain the decrease in running economy seen with increasing duration. The researchers wanted to examine whether running in a racing shoe (with minimal cushioning, but lightweight) would increase the demand on the distal joints with an accompanying reduction in running economy compared to a more cushioned shoe.
What did they do to test the hypothesis or answer the research question?
— 18 male runners (mixture of competitive and recreational) performed two 10k time trial efforts on the treadmill. All runners showed a rearfoot strike pattern presumably because they would be most affected by the rearfoot cushioning.
— The runners ran in two different shoes. The “flat” footwear was the Adidas Adizero Pro 4. The cushioned shoe was the Brooks Glycerin 10. Shoe mechanical properties were measured.
— Kinematic and kinetic parameters were performed on the right leg at 13 different distances throughout the 10k runner. Joint angles, footfall patterns, and joint torques (ankle, knee, hip) were calculated from data collected via a 13 camera infrared camera motion capture system along with a force plate embedded in the treadmill.
What did they find?
— They confirmed that there was a redistribution of the positive work done during running as the distance increased. Specifically, work shifted from the distal locations (53% at ankle, 28.1% knee, 19% hip) to more proximal locations at the end of the run (46.9% ankle, 31.2% knee, 21.9% hip).
— Runners wearing the racing shoe has more plantarflexed foot strike at the beginning of the run, which was associated with more mechanical demand on the plantar and more work done at the ankle.
— No differences in torque nor for the amount of work done at the various joint angles was found between the different shoe types.
— Insert text.
What were the strengths?
— They actually tested the mechanical properties of the shoes themselves.
— Ability to capture actual forces via a force plate measurement.
What were the weaknesses?
— Only examined one type of racing flat and cushioned shoe.
— Did not directly measure the running economy.
— Maximal strength was not characterized before conducting the test and thus the relative amount of fatigue is unknown.
Are the findings useful in application to training/coaching practice?
For ultrarunners these findings are not particularly useful. The distance run, 10k, is not relevant to longer distance trail races. The fact that there were no major differences hints that despite changes in running mechanics with distance the shoe type makes little difference in those running mechanics changes. Given what we know about the new shoe technology and the benefits to the running economy as directly measured it seems that small changes in running “form” are unlikely to be as important as large changes in running economy which have been documented elsewhere. Perhaps one piece of practical advice is to run in the shoes that you are going to race in. Make sure your body is accustomed to those specific forces on the body.
What was the hypothesis or research question?
As you fatigue during increasing duration of running how you do the work changes locations within the body. Typically, you shift from distal joints (such as your foot and ankle) to more proximal joints (such as the knee and hip). This may explain the decrease in running economy seen with increasing duration. The researchers wanted to examine whether running in a racing shoe (with minimal cushioning, but lightweight) would increase the demand on the distal joints with an accompanying reduction in running economy compared to a more cushioned shoe.
What did they do to test the hypothesis or answer the research question?
— 18 male runners (mixture of competitive and recreational) performed two 10k time trial efforts on the treadmill. All runners showed a rearfoot strike pattern presumably because they would be most affected by the rearfoot cushioning.
— The runners ran in two different shoes. The “flat” footwear was the Adidas Adizero Pro 4. The cushioned shoe was the Brooks Glycerin 10. Shoe mechanical properties were measured.
— Kinematic and kinetic parameters were performed on the right leg at 13 different distances throughout the 10k runner. Joint angles, footfall patterns, and joint torques (ankle, knee, hip) were calculated from data collected via a 13 camera infrared camera motion capture system along with a force plate embedded in the treadmill.
What did they find?
— They confirmed that there was a redistribution of the positive work done during running as the distance increased. Specifically, work shifted from the distal locations (53% at ankle, 28.1% knee, 19% hip) to more proximal locations at the end of the run (46.9% ankle, 31.2% knee, 21.9% hip).
— Runners wearing the racing shoe has more plantarflexed foot strike at the beginning of the run, which was associated with more mechanical demand on the plantar and more work done at the ankle.
— No differences in torque nor for the amount of work done at the various joint angles was found between the different shoe types.
— Insert text.
What were the strengths?
— They actually tested the mechanical properties of the shoes themselves.
— Ability to capture actual forces via a force plate measurement.
What were the weaknesses?
— Only examined one type of racing flat and cushioned shoe.
— Did not directly measure the running economy.
— Maximal strength was not characterized before conducting the test and thus the relative amount of fatigue is unknown.
Are the findings useful in application to training/coaching practice?
For ultrarunners these findings are not particularly useful. The distance run, 10k, is not relevant to longer distance trail races. The fact that there were no major differences hints that despite changes in running mechanics with distance the shoe type makes little difference in those running mechanics changes. Given what we know about the new shoe technology and the benefits to the running economy as directly measured it seems that small changes in running “form” are unlikely to be as important as large changes in running economy which have been documented elsewhere. Perhaps one piece of practical advice is to run in the shoes that you are going to race in. Make sure your body is accustomed to those specific forces on the body.
What was the beer called?
Peppermint Bark Stout
Which brewery made it? Barbarian Brewery
What type of beer is it? Golden Stout
How strong is the beer (ABV)? 8% ABV.
How would I describe this beer? This thing messes with your senses. It's a gold stout but is more apricot in color. The body itself is medium light and the sweetness is overpowered by the peppermint and chocolate (it tastes more like a peppermint patty than a beer). enjoyable, but odd.
What is my Rating of Perceived beer Enjoyment? RP(be)E(r) = 7 out of 10.
Which brewery made it? Barbarian Brewery
What type of beer is it? Golden Stout
How strong is the beer (ABV)? 8% ABV.
How would I describe this beer? This thing messes with your senses. It's a gold stout but is more apricot in color. The body itself is medium light and the sweetness is overpowered by the peppermint and chocolate (it tastes more like a peppermint patty than a beer). enjoyable, but odd.
What is my Rating of Perceived beer Enjoyment? RP(be)E(r) = 7 out of 10.
That is all for this month's nerd alert. We hope to have succeeded in helping you learn a little more about the developments in the world of running science. If not, we hope you enjoyed a nice beer…
Until next month, keep active, stay nerdy, and train smart.
Until next month, keep active, stay nerdy, and train smart.
Everyday is a school day.
Empower yourself to train smart.
Think critically. Be informed. Stay educated.
Empower yourself to train smart.
Think critically. Be informed. Stay educated.
Disclaimer: Any interpretations and recommendations we make are, and always will be, based on our own views and opinions shaped by the evidence available to us. Before making any changes to your training based on any information we provide, always ensure it is safe for you to do so and consult your doctor if you are unsure.
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About the authors:
Matt and Thomas are both passionate about making science accessible and helping folks meet their fitness and performance goals. They both have PhDs in exercise science, are widely published, have had their own athletic careers, and are both performance coaches alongside their day jobs. Originally from different sides of the Atlantic, their paths first crossed in Copenhagen in 2010 as research scientists at the Centre for Inflammation and Metabolism at Rigshospitalet (Copenhagen University Hospital). After discussing lots of science, spending many a mile pounding the trails, and frequent micro brew pub drinking sessions, they became firm friends. Thomas even got a "buy one get one free" deal out of the friendship, marrying one of Matt's best friends from home after a chance encounter during a training weekend for the CCC in Schwartzwald. Although they are once again separated by the Atlantic, Matt and Thomas meet up about once a year and have weekly video chats about science, running, and beer. This "nerd alert" was created as an outlet for some of the hundreds of scientific papers they read each month.
Matt and Thomas are both passionate about making science accessible and helping folks meet their fitness and performance goals. They both have PhDs in exercise science, are widely published, have had their own athletic careers, and are both performance coaches alongside their day jobs. Originally from different sides of the Atlantic, their paths first crossed in Copenhagen in 2010 as research scientists at the Centre for Inflammation and Metabolism at Rigshospitalet (Copenhagen University Hospital). After discussing lots of science, spending many a mile pounding the trails, and frequent micro brew pub drinking sessions, they became firm friends. Thomas even got a "buy one get one free" deal out of the friendship, marrying one of Matt's best friends from home after a chance encounter during a training weekend for the CCC in Schwartzwald. Although they are once again separated by the Atlantic, Matt and Thomas meet up about once a year and have weekly video chats about science, running, and beer. This "nerd alert" was created as an outlet for some of the hundreds of scientific papers they read each month.
To read more about the authors, click the buttons:
Copyright © Thomas Solomon and Matt Laye. All rights reserved.