Do carbon plates really reduce the energy cost of running?
Learn to train smart, run fast, and be strong with this endurance performance nerd alert from Thomas Solomon, PhD.
Metabolic effects of carbon-plated running shoes: a systematic review and meta-analysis
Kobayashi et al. (2026) Front Sports Act Living (click here to open the original paper)
What type of study is this?
◦ This study is a systematic reviewA systematic review answers a specific research question by systematically collating all known experimental evidence, which is collected according to pre-specified eligibility criteria. A systematic review helps inform decisions, guidelines, and policy. with meta-analysisA meta-analysis quantifies the overall effect size of a treatment by compiling effect sizes from all studies of that treatment..
What was the authors’ hypothesis or research question?
◦ The authors aimed to quantify whether carbon plates in running shoes reduce metabolic demand during running.
What did the authors do to test the hypothesis or answer the research question?
◦ The authors searched several databases and included 14 crossoverCrossover means that all subjects completed all interventions (control and treatment) usually with a wash-out period in between. trials in healthy adults aged 18 to 60. Most participants across the included studies were men, and testing was mostly treadmill-based. The meta-analysis focused on metabolic outcomes: running economyThe rate of energy expenditure (measured in kiloJoules [KJ], kilocalories [kcal] or oxygen consumption [V̇O2]) per kilogram body mass (kg) per unit of distance, i.e. per 1 kilometre travelled. A runner with a lower energy cost per kilometre has a higher economy than a runner with a higher energy cost., oxygen consumption, and energetic cost of transport.
What did the authors find?
◦ Across outcomes, plated shoes showed statistically significantEvidence that a result is unlikely to be due to chance under a “no effect” model (or null hypothesis). Statistical significance is often judged by a p-value below 0.05 to flag that “something” is going on, but not how big or important that “something” is. One statistically significant result doesn’t mean proof; replication is needed. And, a statistically significant result doesn’t necessarily indicate clinical significance. reductions in metabolic demand, and the size of the benefit was small but potentially meaningful for performance. For running economy, the pooled result came from 4 studies and suggested about a 3 percent improvement. For metabolic cost, 9 studies showed about a 3 percent reduction. For oxygen consumption, 8 studies showed about a 3 percent reduction as well. For the energetic cost of transport, 5 studies showed a smaller but still statistically significant reduction, and the certainty of evidenceCertainty of evidence tells us how confident we are that the published results accurately reflect the true effect. It’s based on factors like study design, risk of bias, consistency, directness, precision, and publication bias. High certainty means that the current evidence is so strong and consistent that future studies are unlikely to change conclusions. Whereas, low certainty means more doubt and less confidence, and that future studies could easily change current conclusions. here was lower because the evidence was less precise. Overall certainty was rated as moderateA moderate quality of evidence means that, in general, studies in this field have some limitations. This could be due to somewhat inconsistent effects between studies, a moderate range of effect sizes between studies, and/or a moderate risk of bias (caused by a small to medium number of studies, small to medium numbers of participants, partially described randomisation processes, some missing data, some inappropriate methods/statistics). When the quality of evidence is moderate, there is some doubt and only moderate confidence in the overall effect of an intervention, and future studies could change overall conclusions. The best way to improve the quality of evidence is for scientists to conduct large, well-controlled, high-quality randomised controlled trials. for running economy, metabolic cost, and oxygen consumption, and lowA low quality of evidence means that, in general, studies in this field have several limitations. This could be due to inconsistency in effects between studies, a large range of effect sizes between studies, and/or a high risk of bias (caused by inappropriate controls, a small number of studies, small numbers of participants, poor/absent randomisation processes, missing data, inappropriate methods/statistics). When the quality of evidence is low, there is more doubt and less confidence in the overall effect of an intervention, and future studies could easily change overall conclusions. The best way to improve the quality of evidence is for scientists to conduct large, well-controlled, high-quality randomised controlled trials. for energetic cost of transport, mainly because these are lab-measured surrogates rather than real race outcomes (and because the last outcome had thinner data). Publication biasPublication bias in meta-analysis occurs when studies with significant results are more likely to be published than those with non-significant findings, leading to distorted conclusions. This bias can inflate effect sizes and misrepresent the true effectiveness of interventions, making it crucial to identify and correct for it in research. was not clearly detected, but the authors also note you can’t fully rule out small-study effects.
◦ The authors concluded that carbon-plated shoes are associated with about a 3 percent reduction in metabolic demand during submaximal running, but the independent contribution of the carbon plate cannot be cleanly separated from other shoe features.
What were the strengths?
◦ Methodologically, this was a pretty solid build. The authors searched 4 major databases, pre-registered their protocolPreregistration is when a detailed description of a study plan is deposited in an open-access repository before collecting the study data. It promotes transparency and accountability, and boosts research integrity. Without preregistration, it is easier for scientists to change outcomes after seeing the data, selectively report “exciting” results, or run many analyses and only show the ones that work, which can introduce bias and weaken the trustworthiness of the findings., assessed risk of biasRisk of bias in a meta-analysis refers to the potential for systematic errors in the studies included in the analysis. Such errors can lead to misleading/invalid results and unreliable conclusions. This can arise because of issues with the way participants are selected (randomisation), how data is collected and analysed, and how the results are reported. using a structured tool, and graded the certainty of evidenceCertainty of evidence tells us how confident we are that the published results accurately reflect the true effect. It’s based on factors like study design, risk of bias, consistency, directness, precision, and publication bias. High certainty means that the current evidence is so strong and consistent that future studies are unlikely to change conclusions. Whereas, low certainty means more doubt and less confidence, and that future studies could easily change current conclusions. with GRADEGRADE, which stands for Grading of Recommendations Assessment, Development and Evaluation, is a standardised and structured approach used to assess the certainty of evidence in meta-analyses. It evaluates how “confident” researchers are in the results of studies and the recommendations that follow from them. GRADE rates a body of evidence as “high”, “moderate”, “low”, or “very low” certainty using a set of standardised criteria.. They also used a random-effects meta-analytical approach (appropriate when studies vary in protocols) and clearly reported study flow and why 1 study could not be meta-analysed due to missing extractable data.
What were the limitations?
◦ Despite the strengths, here’s the messy part: Most “carbon plated vs non-plated” comparisons were also “super-foam and rocker geometry vs not,” so attribution to the plate is kinda squishy — pun fully intended. However, the authors explicitly say that the observed effects reflect modern advanced-shoe packages, not a pure plate-only experiment. But, the evidence is also indirect: treadmill metabolic surrogates dominate, with limited overground data, so generalisabilityGeneralisability is about how far you can confidently stretch a study’s findings beyond the specific people, place, and conditions that were tested. to real races is not guaranteed. Several outcomes (notably running economy and energetic cost of transport) are based on fewer than 10 studies, and the participant pool was mostly male, which limits how confidently we can apply the average effect to females. One more nerdy snag: shoe mass and design reporting were inconsistent across studies, and even small mass differences can matter, so some of the “plate” signal might be drifting in from elsewhere. Consequently, it’s unclear whether the plate is the hero or whether it is just riding shotgun while the foam does the heavy lifting.
How was the study funded, and are there any conflicts of interest that may influence the findings?
◦ The authors stated that they did not receive financial support for this work or its publication. The authors do not provide any information about their potential conflicts of interest.
How can you apply these findings to your training or coaching practice?
◦ For athletes and coaches, this paper is useful because a roughly 2 to 3 percent drop in energy cost can be the difference between “holding pace” and “being hit by Palpatine’s lightning at mile 23”. The force is strong with this one. But you probably shouldn’t treat that average as a personal guarantee: the studies varied, many shoe comparisons bundled multiple shoe design upgrades, and we still don’t know who benefits most by body mass, speed, or mechanics. Also, if you’re choosing shoes mainly for injury risk or durability, this paper basically doesn’t answer that — metabolic cost is the focus here. Should everyone train and race in plated shoes all the time? Maybe, but I’m only halfway convinced; comfort, rules, cost, and adaptation must still be considered.
What is my Rating of Perceived scientific Enjoyment (RPsE)?
9 out of 10 → I experienced high scientific enjoyment because the authors searched 4 databases, pre-registeredPreregistration is when a detailed description of a study plan is deposited in an open-access repository before collecting the study data. It promotes transparency and accountability, and boosts research integrity. Without preregistration, it is easier for scientists to change outcomes after seeing the data, selectively report “exciting” results, or run many analyses and only show the ones that work, which can introduce bias and weaken the trustworthiness of the findings. their protocol, assessed risk of biasRisk of bias in a meta-analysis refers to the potential for systematic errors in the studies included in the analysis. Such errors can lead to misleading/invalid results and unreliable conclusions. This can arise because of issues with the way participants are selected (randomisation), how data is collected and analysed, and how the results are reported., discussed publication biasPublication bias in meta-analysis occurs when studies with significant results are more likely to be published than those with non-significant findings, leading to distorted conclusions. This bias can inflate effect sizes and misrepresent the true effectiveness of interventions, making it crucial to identify and correct for it in research., and graded the certainty of evidenceCertainty of evidence tells us how confident we are that the published results accurately reflect the true effect. It’s based on factors like study design, risk of bias, consistency, directness, precision, and publication bias. High certainty means that the current evidence is so strong and consistent that future studies are unlikely to change conclusions. Whereas, low certainty means more doubt and less confidence, and that future studies could easily change current conclusions. with GRADEGRADE, which stands for Grading of Recommendations Assessment, Development and Evaluation, is a standardised and structured approach used to assess the certainty of evidence in meta-analyses. It evaluates how “confident” researchers are in the results of studies and the recommendations that follow from them. GRADE rates a body of evidence as “high”, “moderate”, “low”, or “very low” certainty using a set of standardised criteria. — basically, they did the grown-up paperwork that makes a meta-analysis trustworthy.
Important: Don’t make any major changes to your daily habits based on the findings of one study, especially if the study is small (e.g., less than 30 participants in a randomised controlled trial or less than 5 studies in a meta-analysis) or poor quality (e.g., high risk of biasRisk of bias in meta-analysis refers to the potential for systematic errors in the studies included in the analysis, which can lead to misleading or invalid results. Assessing this risk is crucial to ensure the conclusions drawn from the combined data are reliable. or low quality of evidenceA low quality of evidence means that, in general, studies in this field have several limitations. This could be due to inconsistency in effects between studies, a large range of effect sizes between studies, and/or a high risk of bias (caused by inappropriate controls, a small number of studies, small numbers of participants, poor/absent randomization processes, missing data, inappropriate methods/statistics). When the quality of evidence is low, there is more doubt and less confidence in the overall effect of an intervention, and future studies could easily change overall conclusions. The best way to improve the quality of evidence is for scientists to conduct large, well-controlled, high-quality randomized controlled trials.). What do other trials in this field show? (opens in new tab) Do they confirm the findings of this study or have mixed outcomes? Is there a high-quality systematic review and meta-analysis evaluating the entirety of the evidence in this field? (opens in new tab) If so, what does the analysis show? What is the risk of biasRisk of bias in a meta-analysis refers to the potential for systematic errors in the studies included in the analysis. Such errors can lead to misleading/invalid results and unreliable conclusions. This can arise because of issues with the way participants are selected (randomisation), how data is collected and analysed, and how the results are reported. or certainty of evidenceCertainty of evidence tells us how confident we are that the results reflect the true effect. It’s based on factors like study design, risk of bias, consistency, directness, and precision. Low certainty means more doubt and less confidence, and that future studies could easily change the conclusions. High certainty means that the current evidence is so strong and consistent that future studies are unlikely to change conclusions. across the included studies? I’ve written opinion articles on this topic; check them out at here and here.
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