Effect of a Commercially Available Footwear Insole on Biomechanical Variables Associated With Common Running Injuries
Bibliographic record
Abstract
OBJECTIVE: To determine whether Dr. Scholl's Active Series (DSAS) footwear insoles alter biomechanical variables associated with running injuries. DESIGN: Randomized, controlled experiment. SETTING: Sport medicine and biomechanics gait analysis laboratory. PARTICIPANTS: Fifteen healthy adults. INTERVENTIONS: The control condition was the participant's own athletic footwear. The experimental condition was the participant's own athletic footwear plus a DSAS insole. Participants completed running gait analysis trials with each condition. MAIN OUTCOME MEASURES: Peak vertical loading rates (VLRs), peak ankle eversion velocities (AEVs), peak ankle eversion angles (AEAs), and knee abduction angular impulses (KAAIs) were calculated and compared between the control and DSAS conditions because these variables have been associated with plantar fasciitis (VLRs), tibial stress syndrome (AEVs, AEAs), and patellofemoral pain syndrome (KAAIs). RESULTS: Dr. Scholl's Active Series insoles reduced VLRs across participants by 16% (P < 0.001) but had no consistent influence on AEVs, AEAs, or KAAIs. Participant-specific responses showed that most runners either experienced AEA and KAAI reductions or no change with the DSAS insole, whereas AEVs commonly increased with the DSAS insole. CONCLUSIONS: Dr. Scholl's Active Series insoles demonstrate efficacy in reducing VLRs, which are associated with plantar fasciitis. Biomechanical changes to variables associated with tibial stress syndrome (AEVs, AEAs) and patellofemoral pain syndrome (KAAIs) were inconsistent.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".