Effects of custom-made foot orthoses on lower limb kinematics and kinetics during step-up and step-down tasks in individuals with progressive collapsing foot deformity
Bibliographic record
Abstract
Progressive collapsing foot deformity (PCFD) is a debilitating condition causing significant biomechanical impairments. Custom-made foot orthoses (FOs) provide a non-invasive treatment by supporting the medial longitudinal arch and improving foot and ankle biomechanics. While previous studies on PCFD have predominantly investigated the biomechanical effects of FOs during walking, their impact on more demanding dynamic tasks remains unclear. This study aimed to investigate the effects of custom-made FOs on lower limb kinematics and kinetics during step-up (SU), step-down (SD), and step-down on a medially inclined surface (SDI) in individuals with PCFD. Twenty participants with flexible PCFD performed SU, SD and SDI tasks with and without FOs. Hip, knee, ankle and midfoot angles and moments were calculated and compared across conditions using one-dimensional statistical parametric mapping. Custom-made FOs reduced midfoot dorsiflexion across all tasks (SU: 4.9°; SD: 4.6°; SDI: 5.4°) and decreased ankle eversion during SU (2.9°) and SD (3.5°), but the reduction during SDI was non-significant. Custom FOs also reduced ankle inversion moments while increasing knee abduction moments during all step tasks. These findings indicate that custom-made FOs effectively support the medial longitudinal arch and limit foot pronation during dynamic movements, likely reducing loading on the medial ankle structures. However, their biomechanical efficacy was less pronounced when individuals with PCFD landed on a medially inclined surface. These findings highlight FOs potential as a conservative intervention for flexible PCFD to improve lower limb biomechanics.
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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 | 0.001 |
| 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".