Can cadence tweaks shift foot strike?
Learn to train smart, run fast, and be strong with this endurance performance nerd alert from Thomas Solomon, PhD.
Influence of Step Rate Manipulation on Foot Strike Pattern and Running Economy
Kim et al. (2025) J Sport Rehabil (click here to open the original paper)
What type of study is this?
◦ This study is a cross-sectional studyA cross-sectional study is a type of observational study where the exposure and outcome are measured at a single point in time, giving a snapshot of a population—what’s happening right now. Cross-sectional studies are used in health surveys, prevalence studies, or for hypothesis generation, and can show prevalence (how common something is) and associations (but not cause and effect). E.g., What percentage of runners currently report using recovery supplements, and is use linked to age or training volume?.
What was the authors’ hypothesis or research question?
◦ The authors aimed to test whether small step-rate changes (−10%, −5%, +5%, +10%) in preferred) shift foot strike pattern can alter 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. in recreational runners.
What did the authors do to test the hypothesis or answer the research question?
◦ Eighteen healthy recreational runners (mean age 30 years; sex not reported) ran on a treadmill at 2.68 metres per second across 5 step-rate conditions, paced by a metronome, in randomized order with 5-minute rests. Foot strike angle from video was used to estimate strike index and, therefore, classify foot strike pattern. (NOTE: Strike index is a way to locate where your foot first loads the ground, foot strike angle, expressed as a % of your foot length from the heel at initial contact. An increase in strik index means a move toward forefoot strike.). Submaximal V̇O2V̇O2 is the rate of oxygen uptake/consumption. was measured between 3:30 and 5:30 of each 6-minute bout to estimate 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.. A power calculationA power calculation is a way to figure out how many people or data points you need in a study so you can reliably spot a real effect if it exists. It balances four things: the size of the effect you care about, how much random variation there is, how strict you are about false alarms, and how likely you want to be to detect the effect. In plain terms: it helps you avoid running a study that’s too small to be useful or so big that it wastes time and money. suggested that n=14 would be sufficient to achieve adequate statistical powerStatistical power is the probability that a statistical test will correctly detect a real effect if there is one: a true positive. (In jargon: power is the probability that a statistical test correctly rejects a false null hypothesis). Higher statistical power reduces the risk of a false negative (failing to detect a true effect; or a Type II error). Power is typically influenced by sample size, effect size, significance level, and variability in the data, with a common target being at least 80% (or 0.8).; 18 people were recruited to allow for dropout.
What did the authors find?
◦ Step-rate manipulation produced large overall differences in predicted strike index. Compared with preferred cadence, strike index shifted downwards at −10% & −5% (more rearfoot strike), and upwards +10% (more forefoot strike). Running economy worsened at −10% and −5% (as indicated by a higher submaximal V̇O₂ at the constant speed of 2.68 metres per second), with no differences at +5% or +10%. Inter-assessor reliability (measured using ICC coefficient)The ICC is a measure of the reliability or agreement between multiple measurements or raters assessing the same target. It reflects both the degree of correlation and the agreement between measurements, with values ranging from 0 (no agreement) to 1 (perfect agreement).. for foot strike angle was excellent.
◦ The authors concluded that small, acute step-rate changes within ±10% of preferred cadence can meaningfully shift foot strike pattern, and intentionally decreasing step rate by 5–10% impairs running economy.
What were the strengths?
◦ The study prespecified the outcomes and performed a pre-study power calculationA power calculation is a way to figure out how many people or data points you need in a study so you can reliably spot a real effect if it exists. It balances four things: the size of the effect you care about, how much random variation there is, how strict you are about false alarms, and how likely you want to be to detect the effect. In plain terms: it helps you avoid running a study that’s too small to be useful or so big that it wastes time and money., used randomized condition order with single-blindingBlinding is when people in a study don’t know which treatment they’re getting. It stops expectations or beliefs (from patients or researchers) from skewing the results. “Single-blind” means participants don’t know; “double-blind” means participants and researchers don’t know; “triple-blind” means that the participants, researchers, and data analysts are kept in the dark. The goal is simple: fair tests and trustworthy findings., and reported robust statistics with effect sizes and controls for multiple comparisonsMultiple comparisons happen when you test many hypotheses or look at many outcomes in the same data set. Each test has some chance of a “false alarm” just by luck. When you do lots of tests, those chances add up. That means you’re more likely to find something that looks “significant” but is actually just noise.; measurement reliability for foot strike angle was high. For a cross-sectional lab study, the instrumentation and protocols were clear and replicable.
What were the limitations?
◦ The sample was small (n=18), which limits precision and increases the risk of false negative findingsWhen a statistical test fails to detect an effect or difference when there actually is one. I.e, “a missed detection”. Studies with a small sample size (N, number of participants) are more likely to produce false negative results. for subtler effects. The design tested only acute responses at one speed in a treadmill setting, so transfer to outdoor running and to longer runs and speeds relative to the person is unknown. Sex distribution and several descriptive details are unreported, and only the left foot was analyzed so we must assume that all participants had symmetrical running gait between feet.
How was the study funded, and are there any conflicts of interest that may influence the findings?
◦ The study was supported by the Soonchunhyang University and Utah State University Research Fund. No conflict-of-interest statement was provided.
How can you apply these findings to your training or coaching practice?
◦ Practically, cadence is a simple, coachable lever. These findings suggest that dropping cadence by 5–10% from your natural rhythm, will likely shift you toward a more rearfoot strike and burn a bit more oxygen per minute, worsening running economy — not the droids you are looking for. The data also show that If you bump cadence up by 10%, you can shift the foot strike towards the forefoot but without any change in economy. That’s useful to know because of the “gait-retraining” nudge that some coaches and social media gurus tout. Are they worth it?
◦ One last thought: Should we be nudging runners toward +10% cadence to adjust strike without any energy gain. Based on these findings, nope. But, it’s a small study and we really need to know how such factors change when fatigue sets in, such as at the deep end of a long race. Dear scientists, please explore that.
What is my Rating of Perceived scientific Enjoyment (RPsE)?
6 out of 10 → I experienced low to moderate scientific enjoyment because the question is practical, the within-subject randomization and reliability are solid, and the stats are transparently reported; however, the small sample, fixed speed treadmill setup, and some reporting gaps (e.g., sex of participants) limit generalisabilityGeneralisability is about how far you can confidently stretch a study’s findings beyond the specific people, place, and conditions that were tested. In simple terms, it asks: “If this result is true here, how likely is it to also be true in other groups or real-world settings?” It’s closely linked to external validity, which is the overall strength of those broader conclusions. and reduce confidence in ther findings.
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 bias 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?.
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