No associations between objectively measured physical activity and spinal pain in 11–15‐year‐old Danes
Bibliographic record
Abstract
BACKGROUND: Physical activity is thought to play a role in spinal pain (neck pain, mid back pain, low back pain) in children and adolescents, either as a risk or protective factor, but current evidence is conflicting. The overall aim of this study was to determine the cross-sectional and longitudinal associations between different levels of objectively measured physical activity, i.e. sedentary; moderate and vigorous; vigorous physical activity, and spinal pain in 11-15-year-old Danes. METHODS: Data were collected at baseline (2010) (n = 906) and at follow-up 2 years later (n = 625) in a school-based prospective cohort study. Physical activity was measured using the Actigraph GT3X Triaxial Activity Monitor, which measures the intensity of physical activity over time. This was worn for 1 week and spinal pain was assessed via e-survey that participants completed during school time. Potential confounders included in the multivariable analyses were sex, anthropometry, physical fitness, social status and psychosocial factors. In the longitudinal study, analyses stratified by baseline pain status were performed. RESULTS: There were neither cross-sectional nor longitudinal associations between different levels of objectively measured physical activity and spinal pain over the 2-year period. CONCLUSION: Objectively measured physical activity was not associated with spinal pain. However, it remains to be seen whether there is an association over a longer follow-up period. Future research should focus on the more qualitative aspects of physical activity, such as different sports activities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".