Does slow tempo strength training help runners race faster?
Learn to train smart, run fast, and be strong with this endurance performance nerd alert from Thomas Solomon, PhD.
Effect of high time under tension strength training on different muscular actions in the performance of runners: A randomized controlled trial
Martins et al. (2026) PLoS One (click here to open the original paper)
How can you apply this paper's findings to your training or coaching practice?
◦ For coaches and runners, this paper provides a decent argument that high time-under-tension bodyweight strength work can improve strength and jump performance without wrecking running performance. But if your only performance indicator is “did my 3,000-meter time improve in 4 weeks”, then… there’s nothing to see here, move along, move along. Still, the neuromuscular gains might matter later, especially if they help durability (physiological resilience)Durability is a measure of how “durable” your physiological performance metrics are during prolonged fatigue-inducing exercise. I.e., can you still produce your maximal power at the end of a hard 2 hour run? or set the stage for heavier or more explosive work. But, based on 1 small, short study, we cannot be completely certain about the effects — larger, longer studies in more diverse populations (e.g., in males and females) are needed.
What is my Rating of Perceived scientific Enjoyment (RPsE)?
7 out of 10 → I experienced moderate scientific enjoyment because the study used a good approach (randomisationRandomization means assigning people to different parts of a study (e.g., groups in a randomised controlled trial) by chance, not by choice. This helps make the groups similar at the start and reduces bias, so any differences you see are more likely due to the treatment, not background differences. In a crossover study, randomization usually decides the order in which each person gets the treatments (for example, Treatment A first then B, or B first then A). This way, order effects—like learning, fatigue, or simple time passing—are less likely to skew the results., a control group, protocol pre-registrationPreregistration 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., clear protocol descriptions), but the short duration and male-only sample kept me from going into full fanboy mode.
Remember: 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 if the study is poor quality (e.g., has a 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 a 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.). Always check what other trials in this field (link opens a new tab) have shown. Do they confirm the findings of this study? If there is a high-quality meta-analysis(link opens a new tab) evaluating the entirety of the evidence in this field, what does it say about the effect sizeA standardised measure of the magnitude of an effect of an intervention. Unlike p-values, effect sizes show the size of the effect and how meaningful it might be. Common effect size measures include standardised mean difference (SMD), Cohen’s d, Hedges’ g, eta-squared, and correlation coefficients., 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., and the quality/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.?
What type of study is this?
◦ This study is a randomised controlled trialThe “gold standard” approach for determining whether a treatment has a causal effect on an outcome of interest. In such a study, a sample of people representing the population of interest is randomised to receive the treatment or a no-treatment placebo (control), and the outcome of interest is measured before and after exposure to the treatment and control..
What was the authors’ hypothesis or research question?
◦ The authors aimed to test whether high time-under-tension strength training, done with mostly dynamic or mostly isometric contractions, improves running performance and performance-related neuromuscular and biomechanical measures in runners.
What did the authors do to test the hypothesis or answer the research question?
◦ The researchers recruited 34 physically active young adult males (Brazilian Army soldiers) and used randomisationRandomization means assigning people to different parts of a study (e.g., groups in a randomised controlled trial) by chance, not by choice. This helps make the groups similar at the start and reduces bias, so any differences you see are more likely due to the treatment, not background differences. In a crossover study, randomization usually decides the order in which each person gets the treatments (for example, Treatment A first then B, or B first then A). This way, order effects—like learning, fatigue, or simple time passing—are less likely to skew the results. to assign them to 1 of 3 groups: predominantly dynamic strength training, predominantly isometric strength training, or control (no extra training).
◦ Training lasted 4 weeks (2 sessions per week) and used lower-body bodyweight exercises.
◦ The dynamic strength training followed a 3/1/3/0 tempo (3 seconds concentric, 1 second isometric, and 3 seconds eccentric). The isometric strength training used a 1/5/1/0 tempo (1 second eccentric, 5 seconds isometric, and 1 second concentric). Both protocols used the same number of exercises, sets, rest intervals, and total session time, and achieved 84 seconds of time-under-tension per set.
◦ The control group did not undergo any training and was instructed to maintain their usual daily activities throughout the intervention period.
◦ The main outcomes included a 3,000-meter time to completion test (time trial)A test where you cover a set distance (or set amount of work) as fast as you can. The score is your finish time. It mirrors real-world performance and is easy to compare over time., peak knee-extensor torque (max isometric strength), countermovement jump height, neuromuscular fatigue (change in jump height after the run), internal running load (time multiplied by rating of perceived exertion (RPE)Rating of perceived exertion (RPE) is a simple way to score how hard exercise feels to you, not to a machine. You pick a number on a scale (often 1–10), where low numbers mean “this feels easy” and high numbers mean “I’m really pushing it.” It blends how heavy your breathing is, how tired your muscles feel, and how much effort you think you’re putting in.), and wearable-derived ground contact time and vertical oscillation.
What did the authors find?
◦ The 3,000-meter time trial did not clearly improve in either training group compared with control over 4 weeks (34 participants total). The direction of change favored training a bit, but it was not statistically convincing, and weekly running mileage appeared to influence the model—so, basically, the “real” performance signal here is messy. Is that because strength work truly doesn’t help race time over 4 weeks, or because the study was too short to let the physiology cash the check? Both are plausible.
◦ Neuromuscular strength (peak torque) improved meaningfully in the isometric-focused group (34 participants total), with changes that looked moderate to large compared with control. The dynamic-focused group also improved on average, but the cleanest statistical separation from control showed up for the isometric protocol. In plain English: slow, grinding isometrics made the knee extensors stronger in a way that is hard to ignore.
◦ Jump height (countermovement jump) improved in both training groups (34 participants total), again with effects that looked moderate to large versus control. This is the part that will make coaches nod: the legs got bouncier even though the program was slow and high-volume per set.
◦ Running mechanics (ground contact time and vertical oscillation) did not show clear between-group differences, even though average values tended to move in a favorable direction.
◦ The authors concluded that high time-under-tension strength training improved neuromuscular measures in runners, but these changes did not translate into clear improvements in running performance over the intervention period.
What were the strengths?
◦ The study did a lot of the “boring but important” things right: it used randomisationRandomization means assigning people to different parts of a study (e.g., groups in a randomised controlled trial) by chance, not by choice. This helps make the groups similar at the start and reduces bias, so any differences you see are more likely due to the treatment, not background differences. In a crossover study, randomization usually decides the order in which each person gets the treatments (for example, Treatment A first then B, or B first then A). This way, order effects—like learning, fatigue, or simple time passing—are less likely to skew the results. with a control group, described allocation concealmentAllocation concealment is the step that hides the next treatment assignment before a patient enters a trial. It prevents staff from guessing or peeking, so they can’t steer patients to one group or another. It happens at enrollment, before blinding, and guards against selection bias., and pre-registration the 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.. The time-under-tension was tightly controlled with a metronome and equalized across protocols, which is exactly what you want when you’re isolating “time-under-tension” as the main lever. The outcomes were practical and runner-relevant (a 3,000-meter time to completion test (time trial)A test where you cover a set distance (or set amount of work) as fast as you can. The score is your finish time. It mirrors real-world performance and is easy to compare over time., strength, jumping, wearables), and the paper includes a data availability statementWhen authors make their data available, this increases transparency and data integrity, and allows other to check the statistical analyses..
What were the limitations?
◦ The big limitation is the study duration: 4 weeks is short for endurance-performance translation, and the authors themselves flag that. The final sample size (N)N is how many participants or observations are analyzed. A bigger N usually means more precise estimates and more power (ability to detect a true effect). A smaller N results in a study that is less likely to detect a true effect (false negative/type II error) and is more likely to report false positives (type I error). Of course, a badly designed study is still bad even if it has a big N. was also 34 rather than the planned 36, and the 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. to determine the samepl size was based on the primary outcome, which may have left other outcomes underpowered to find meaningful effects. The sample was also male only (in a military setting), which limits generalisabilityGeneralisability is about how far you can confidently stretch a study’s findings beyond the specific people, place, and conditions that were tested.. Strength testing focused on isometric knee extensors only, and biomechanics were indirect assessed using wearables, which have not been validated.
How was the study funded, and are there any conflicts of interest that may influence the findings?
◦ The study was supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project (PNURSP2026R424), and the acknowledgments also mention support from research groups and institutions in Sergipe and Prince Sultan University. The authors state that they have no competing interests.
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Other papers I reviewed this month:
Does slow tempo strength training help runners race faster?
Does carbohydrate periodization boost running performance?
Does heavy lifting make cyclists faster?
Should athletes use antioxidant supplements for performance?
Niche Peach Connoisseur 5000 (from Sudden Death Brewing)
Additional papers I read that you might find interesting:
Whey protein intakes up to 0.4g/kg body mass are well tolerated before a 10km run at 85% of race pace: a clinical trial. Shaw et al. (2026) J Int Soc Sports Nutr.
Lower limb neuromotor control during perturbed and unperturbed gait conditions in male runners with Achilles tendinopathy: an exploratory analysis. Quarmby et al. (2026) Int Biomech.
National-Standard Middle-Distance Runners Maintain 1500 m Time Trial Running Performance on Successive Days. Birdsey et al. (2026) Eur J Sport Sci.
Dual-task effects on spatiotemporal, kinematic, and kinetic parameters and their variability during running. Teng et al. (2026) Gait Posture.
Morphological Changes and MRI Characteristics of the Achilles Tendon in Amateur Marathon Runners With Different Running Experience. Yao et al. (2026) J Foot Ankle Res.
Association between bone mineral density and ground reaction force in male and female runners. Smith et al. (2026) Gait Posture.
Effect of gait retraining in minimalist footwear or barefoot on running footstrike and cadence: a systematic review. DesRochers et al. (2026) Res Sports Med.
Does preferred technique influence how kinematics change during a run to exhaustion?-A cluster based approach. Rivadulla et al. (2026) PeerJ.
Biomechanical insights into Achilles tendinopathy risk and protection in runners: a large prospective study 4HAIE. Jandacka et al. (2026) Br J Sports Med.
Sprint running mechanics are associated with hamstring strain injury: a 6-month prospective cohort study of 126 elite male footballers. Bramah et al. (2026) Br J Sports Med.
Effect of high time under tension strength training on different muscular actions in the performance of runners: A randomized controlled trial. Martins et al. (2026) PLoS One.
The effect of a familiarization critical speed testing session on critical speed determination during treadmill running. Micheli et al. (2026) PLoS One.
Baseline Inflammatory Markers as Predictors of Running-Related Injuries: A One-Year Prospective 4HAIE Cohort Study. Cipryan et al. (2026) Scand J Med Sci Sports.
Stride-to-Stride Fluctuations and Temporal Patterns of Muscle Activity Exhibit a Stronger Relationship in Running-Induced Fatigue. Chalitsios et al. (2026) Scand J Med Sci Sports.
Examining attention- deficit/ hyperactivity disorder in endurance and ultra-endurance runners. Scheer et al. (2026) Acta Psychol (Amst).
"Running in circles": Breastfeeding experiences in women who have had bariatric surgery before pregnancy: A qualitative study. Mokhlesi et al. (2026) Women Birth.
Acute effects of dynamic stretching on knee joint position sense and dynamic balance in recreational runners: A randomized controlled trial. Simões et al. (2026) Gait Posture.
Carryover effects of treadmill-based footstrike modification gait retraining on overground running biomechanics. Chan et al. (2026) J Sports Sci.
Agreement and Reliability Between Urine Reagent Strips and Refractometry for Field Assessment of Hydration in Ultra-Trail Runners. Rojas-Valverde et al. (2026) Nutrients.
Effects of Marathon Running on Skin and Plasma Carotenoids in Endurance Runners. Joyner et al. (2026) Nutrients.
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