Kinetic Differences Associated with Minimalist Shoe and Reduced Stride Length Running
Bibliographic record
Abstract
Running is a popular activity with over 2 million half-marathon finishers in the US each year. Unfortunately, running is associated with a high incidence of injury ranging from 24% to 77% per annum. Minimalist shoes have been developed to mimic barefoot running while protecting the foot. Common injuries in minimalist runners include plantar fasciitis, Achilles tendinopathy, and metatarsal stress fractures. It is known that changing a runner’s preferred stride length (PSL) can alter joint kinetics, however these effects have not been studied in minimalist runners. PURPOSE: To examine changes in metatarsophalangeal (MTP), ankle, and knee joint kinetics when running in minimalist shoes and at reduced stride length. METHODS: Fourteen male recreational runners (26.2 ± 4.2 yr; 178.4 ± 5.4 cm; 75.6 ± 5.6 kg) ran 10 trials overground at preferred running speed during four conditions: control shoe at PSL and 90% PSL; minimalist shoe at PSL and 90% PSL. Markers were placed on the pelvis and right lower extremity, and motion capture and force platform data were recorded at 240 and 2400 Hz, respectively. A 2 x 2 factor repeated measures ANOVA was used to compare trial-averaged peak moments, angular impulse, and eccentric and concentric work among the four conditions (α = 0.05). A cumulative impulse was also calculated by multiplying impulse with the number of steps associated with a 5 km run. RESULTS: Increased eccentric work at the MTP (12.8 ± 4.9 vs. 8.9 ± 3.2 J/kg) and ankle joint (30.0 ± 6.7 vs. 26.4 ± 7.7 J/kg) was observed when running in minimalist shoes. Minimalist shoe running was also associated with reduced knee impulse (17.1 ± 3.7 vs. 18.7 ± 4.8 Nm·s/kg), while 90% PSL was associated with reduced knee impulse (15.0 ± 5.2 vs. 18.7 ± 4.8 Nm·s/kg), eccentric work (30.8 ± 10.8 vs. 39.8 ± 13.6 J/kg), and cumulative impulse (33.3 ± 5.6 vs. 29.3 ± 7.9 x103 Ns/kg). 90% PSL also illustrated a lower ankle impulse (37.1 ± 4.9 vs. 38.6 ± 4.8 Nm·s/kg). CONCLUSIONS: Running in minimalist footwear was beneficial for knee joint loading, however increased loads were observed at the MTP and ankle joints, which may help to explain the running injuries seen in minimalist shoe users. Running at 90% PSL lowered ankle and knee joint impulse and eccentric work, suggesting that a combination of the control shoe and 90% PSL may provide a good compromise for minimizing injury.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".