Impact of in shoe and barefoot placed frontal wedges on plantar loading: A systematic review
Bibliographic record
Abstract
PURPOSE: The main aim of this review is to report the effect of different types of in-shoe and barefoot wedges on the distribution of the plantar loading of the human foot. We hypothesise that frontal plane wedges modify this parameter. METHODS: A systematic review was performed, using the PubMed, CINAHL, Prospero and Scopus databases, consulted from their date of first publication to May 2020. Only observational (cross-over studies), randomised controlled trials (RCTs) and quasi-experimental studies addressing the effects of in-shoe and barefoot frontal plane wedges on plantar loading were included. All articles were subjected to quality assessment, using the Newcastle-Ottawa scale for the observational (cross-over) studies, TREND for quasi-experimental studies and the Cochrane Collaboration's tool for the RCTs. RESULTS: Eleven papers were included in the final review. Four were cross-over studies, other four were quasi-experimental studies and three were RCTs. These eleven studies included 320 patients, with ages ranging from 20 to 60 years. Regarding the risk of bias, most of the observational studies and RCTs had a moderate level of quality. CONCLUSIONS: The results suggest that lateral wedges are more effective, producing a lateral shift of the centre of pressure and increasing the pressure. Regarding the impact on the peak impact force there seems to be less consensus among the published data.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".