THE EFFECTS OF VARIOUS HEEL SLOPES ON LUMBOSACRAL BIOMECHANICAL ANGLES IN STUDENTS WITH HYPER LORDOSIS
Bibliographic record
Abstract
Posture disorders in school-age children are highly frequent. Poor movement and lack of physical mobility are the main causes of physical weaknesses. Thus, corrective exercises with the aim of solving these problems are significant. The aim of this study was an evaluation of the effects of various heel slopes on lumbosacral biomechanical angles in students with hyperlordosis. In this quasi-experimental study, 15 female students who were di- agnosed with hyperlordosis, participated in this study. They were divided into 3 groups (n=5) and performed corrective exercises on +3.7°, 0°, and -3.7° slopes for 8 weeks, 3 times a week. The changes in the lumbar lordosis angle (LLA), sacral based angle (SBA), and lumbosacral angle (LSA) were determined. Data were analyzed by SPSS 18 software using non-parametric test followed by the Krus- cal-wallis test. P<0.05 was considered significant. The results indicated no significant difference regarding the changes in LLA, SBA, and LSA in students with hyperlordosis (p>0.05) de- spite the decrease in the means of the angles in all groups. The results showed that by increasing the heel slope, the lumbo - sacral slope decreases also the lumbosacral angle decreases by decreasing the heel slope, this may indicate an association between these angles.The findings can help parents choose more appropriate shoes for their children to both prevent the incidence of posture dis- orders during childhood and spinal disorders in adulthood.
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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) | 0.002 | 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".