Are super shoes a super placebo? A randomised crossover trial in female recreational runners
Bibliographic record
Abstract
We examined the potential placebo effect of advanced footwear technology (AFT) on running economy (RE) and perceptual measures while monitoring biomechanics. Twenty-four female recreational runners completed 4 × 6-minute RE trials in two pairs of women’s Nike ZoomX Vaporfly Next% 2. One pair was described as performance-enhancing super shoes with AFT worn by elite athletes, and the other pair was spray-painted black and described as ‘knock-off’ AFT shoes. Oxygen consumption (difference: −0.05 ± 0.47 mL·kg−1·min−1, d = −0.02), energy cost (difference: −0.02 ± 0.17 W·kg−1, d = −0.03), and discrete biomechanical variables were not significantly different between conditions. There were no significant differences between shoes in lower-extremity angular and angular velocity curves based on statistical parametric mapping. Overall comfort (100-mm visual analogue scale) was significantly greater (14.6 ± 15.0 mm, d = 0.94) in the performance-enhancing than ‘knock-off’ condition, with most runners (87.5%) preferring the former. Runners perceived running as more enjoyable and less difficult and perceived an improved running performance and lower injury risk in the performance-enhancing shoe (d = 0.72–1.16). While no significant physiological or biomechanical differences were observed, a significant placebo effect was apparent for both perceived comfort and perceived performance based on shoe description alone.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".