The most physically active Danish adolescents are at increased risk for developing spinal pain: a two-year prospective cohort study
Bibliographic record
Abstract
BACKGROUND: The overall aim of this study was to determine to what extent objectively measured physical activity in a school-based sample aged 11-13 years predicted incident cases of spinal pain (neck pain, mid back pain or low back pain) over the following 2 years. METHODS: Data were collected at baseline (2010) and 2 years later in a school-based prospective cohort study. Spinal pain was assessed via an e-survey that the participants completed during school time. Participants who, at baseline, reported never having had spinal pain were included in the study. An incident case of spinal pain was defined as a report of pain in at least one spinal area at follow-up. Physical activity was measured objectively using the Actigraph GT3X Triaxial Activity Monitor for 1 week. RESULTS: Objectively measured sedentary activity, moderate-to-vigorous physical activity and vigorous physical activity were generally not predictive of the 2-year incidence of spinal pain. However, 10% of participants with the highest proportion of the day spent in vigorous physical activity were at increased risk of reporting spinal pain at follow-up with a relative risk (RR) of 1.44 (95% CI 1.09 to 1.91). For the overall physical activity, the RR was 1.03 (95% CI 1.01 to 1.05) for reporting spinal pain at follow-up. CONCLUSIONS: In general, physical activity did not affect the risk of spinal pain during follow-up, but the 10% most active adolescents were at increased risk of developing spinal pain. Thus, vigorous physical activity appears to be a risk factor for spinal pain in adolescents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".