Risk Factors for the Development of Neck and Upper Limb Pain in Adolescents
Bibliographic record
Abstract
STUDY DESIGN: A prospective, repeated measures cohort study with high school students was conducted in Montreal, Canada. OBJECTIVE: To determine the incidence of neck and upper limb pain and associated risk factors in a cohort of adolescents. SUMMARY OF BACKGROUND DATA: Neck and upper limb pain is frequent in adolescents and may be associated with repetitive motion from certain activities such as playing music, working, and engaging in sports activities. METHODS: For this study, 502 students in the seventh to ninth grades in three schools were assessed. Data were collected at three times 6 months apart over a 12-month period. Students responded to a questionnaire addressing musculoskeletal health and lifestyle factors and were measured for height and weight. Neck or upper limb pain occurring at least once a week in the preceding 6 months was defined as the outcome. Multivariate methods were used to model the repeated measures dichotomous outcome as a function of engaging in physical activity, working, or playing a musical instrument, adjusted for covariates. RESULTS: The cumulative annual incidence of neck and upper limb pain was 28.4%. The risk factors for neck and upper limb pain were working (adjusted odds ratio, 1.89; 95% confidence interval, 1.11-3.32) and lower mental health score (adjusted odds ratio, 1.68; 95% confidence interval, 1.19-2). Students involved in childcare were at a higher risk for the development of pain (adjusted odds ratio, 2.25; 95% confidence interval, 1.18-4.29). CONCLUSIONS: Neck and upper limb pain is common in teenagers. Sports involvement and music participation were not risk factors for the development of neck and upper limb pain. However, pain was more likely to develop in adolescents who worked than in students who had a lower mental health score.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".