Risk factors for development of lower limb pain in adolescents.
Bibliographic record
Abstract
OBJECTIVE: Although many clinicians believe high growth leads to inflexibility, which may lead to lower extremity pain, the only prospective data suggest growth is unrelated to flexibility. However, it is still possible that growth and/or flexibility are related to pain even if they are not related to each other. We investigated the incidence of leg pain in adolescents to determine whether high growth spurt and/or poor flexibility are risk factors for the development of lower extremity pain. METHODS: Repeated measures, prospective cohort study of urban high school students aged 12-18. Subjects were measured at baseline and at 6 and 12 months for flexibility of hamstrings and quadriceps and with the sit-and-reach test. Participants completed a detailed questionnaire on recreational activity, occupational activities, psychosocial variables, and musculoskeletal pain. RESULTS: Poor hamstring flexibility (odds ratio 0.99, confidence interval 0.97-1.01), poor quadriceps flexibility (OR 1.01, CI 0.99-1.03), poor sit-and-reach flexibility (OR 0.99, CI 0.99-1.01), and growth (OR 0.93, CI 0.50-1.71) were not related to the development of lower extremity pain. There was an association between lower extremity pain and occupational activities (OR 2.08, CI 1.45-2.98) and poor mental health (per 1 SD change, OR 1.41, CI 1.19-1.67). CONCLUSION: Neither growth nor flexibility is related to the development of lower extremity pain in adolescents. A poor mental health score and occupational activities may be associated with the development of lower extremity pain.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".