Injury and performance related biomechanical differences between recreational and collegiate runners
Bibliographic record
Abstract
Introduction Running related injuries (RRI) are common, but factors contributing to running performance and RRIs are not commonly compared between different types of runners. Methods We compared running biomechanics previously linked to RRIs and performance between 27 recreational and 35 collegiate runners. Participants completed 5 overground running trials with their dominant limb striking a force plate, while outfitted with standardised footwear and 3-dimensional motion capture markers. Results Post hoc comparisons revealed recreational runners had a larger vertical loading rate (194.5 vs. 111.5 BW/s, p < 0.001) and shank angle (6.80 vs. 2.09, p < 0.001) compared with the collegiate runners who demonstrated greater vertical impulse (0.349 vs. 0.233 BWs, p < 0.001), negative impulse (−0.022 vs. −0.013 BWs, p < 0.001), positive impulse (0.024 vs. 0.014 BWs, p < 0.001), and propulsive force (0.390 vs. 0.333 BW, p = 0.002). Adjusted for speed, collegiate runners demonstrated greater total support moment (TSM), plantar flexor moment, knee extensor moment, hip extensor moment, and had greater proportional plantar flexor moment contribution and less knee extensor moment contribution to the TSM compared with recreational runners. Unadjusted for speed, collegiate runners compared with recreational had greater TSM and plantar flexor moment but similar joint contributions to the TSM. Discussion Greater ankle joint contribution may be more efficient and allow for greater capacity to increase speed. Improving plantarflexor function during running provides a strategy to improve running speed among recreational runners. Moreover, differences in joint kinetics and ground reaction force characteristics suggests that recreational and collegiate runners may experience different types of RRI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".