Effectiveness of foot orthoses and foot exercises in the management of lower back pain in patients with flexible pes planus – A randomized controlled trial
Bibliographic record
Abstract
Background: Lower back pain poses a significant burden on the economy and can be approximated to be around £2.8 billion in countries like the UK.Studies indicate that young Indian adults, aged 18 to 35 years, have a high prevalence of lower back pain (LBP), with rates reported at 42.4% per year and 22.8% per week.We aimed to study the impact of Standardized Foot Orthoses, with and without Foot Exercises, in the management of Chronic Lower Back Pain in people with Pes Planus. Materials and Methods:The study involved 85 participants who were randomly assigned to two groups, one group (FE, n=42) received foot exercises only, while the other group (FEO, n=43) received both foot exercises and foot orthoses.The level of Lower Back pain was measured using Quebec Disability Scale and Visual Analogue Scale, at the time of inclusion and the conclusion of the duration of eight weeks.Results: Analysis indicated that participants who received both foot exercises and standard foot orthoses experienced a significantly greater reduction in chronic lower back pain (CLBP), with a large effect size (d = 0.89), compared to those who performed foot exercises alone, who showed a medium effect size (d = 0.46) (p < 0.001, Quebec Scale). Conclusion:The results indicate that correcting flat foot using foot exercises alone, as well as in combination with foot orthoses, is an effective measure in the management of chronic lower back pain, with the combination demonstrating a superior effect.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".