The immediate effects of foot orthoses on functional performance in individuals with patellofemoral pain syndrome
Bibliographic record
Abstract
OBJECTIVE: Patellofemoral pain syndrome (PFPS) often results in reduced functional performance. There is growing evidence for the use of foot orthoses to treat this multifactorial condition. In this study, the immediate effects of foot orthoses on functional performance and the association of foot posture and footwear with improvements in function were evaluated. METHODS: Fifty-two individuals with PFPS (18-35 years) were prescribed prefabricated foot orthoses (Vasyli Pro; Vasyli International, Labrador, Australia). Functional outcome measures evaluated included the change in (1) pain and (2) ease of a single-leg squat on a five-point Likert scale, and change in the number of (3) pain-free step downs and (4) single-leg rises from sitting. The association of foot posture using the Foot Posture Index, navicular drop and calcaneal angle relative to subtalar joint neutral; and the footwear motion control properties scale score with improved function were evaluated using Spearman's ρ statistics. RESULTS: Prefabricated foot orthoses produced significant improvements (p<0.05) for all functional outcome measures. A more pronated foot type and poorer footwear motion control properties were found to be associated with reduced pain during the single-leg squat and improvements in the number of pain-free single-leg rises from sitting when wearing foot orthoses. In addition, a more pronated foot type was also found to be associated with improved ease of completing a single-leg squat when wearing foot orthoses. CONCLUSION: Prefabricated foot orthoses provide immediate improvements in functional performance, and these improvements are associated with a more pronated foot type and poorer footwear motion control properties.
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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) | 0.001 | 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".