Effects of the insert to plantar contacct area and pressure distribution
Bibliographic record
Abstract
Purpose: The purpose of this study is to investigate the effects of inserts that are used for conservative treatment of excessive foot pronation, on plantar contact areas and pressure distribution.Methods: 27 subjects consisting of 6 men and 21 women, mean age 25.88±5.92, and having excessive foot pronation were included in this study. Demographic data were recorded. Short Form McGill Questionnaire, Navicular Drop Test, Foot Posture Index and Foot Function Index were performed for each subject. Subjects were evaluated with dynamic pedobarography (Rs Scan-Footscan ®), first barefoot, than with spesific inserts, to assess plantar contact area and pressure distribution.Results: Findings from dynamic pedobarography indicated that there were significant increase at total contact area, contact area percents of midfoot, significant decrease at contact area percents of fore and rearfoot, at maximum plantar pressures on 2., 3., 4. metatars areas of left foot and on 2. and 3. metatars areas of right foot, on medial and lateral heel with insert according to barefoot (p=0.007, p=0.001, p=0.003, p0,05).Discussion: Excessive foot pronation, causes pathologic changes on proximal and distal subtalar joint, effects plantar pressures destroying load distribution. Using insert is the most common method to correct this deformity. The results of our study emphasizes, spesific inserts are effective to distribute plantar pressures and prevent excessive loading of specific areas increasing contact area
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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 | 0.002 |
| 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) | 0.003 | 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".