The one-week prevalence of neck pain and low back pain in post-secondary students at two Canadian institutions
Bibliographic record
Abstract
BACKGROUND: Low back and neck pain are common in the general population, but the prevalence among Canadian post-secondary students is not well known. We aimed to determine the one-week prevalence of neck pain (NP) and low back pain (LBP) among postsecondary students in Canada. METHODS: We conducted a cross-sectional study of students enrolled in the Faculty of Health Sciences and Faculty of Education at Ontario Tech University, and the Canadian Memorial Chiropractic College (CMCC) in the Fall of 2017. Neck and low back pain intensity in the past week were measured with the 11-point numerical rating scale. We report the cumulative, gender- and institution-specific one-week prevalence (95% CI) of any pain (1-10/10) and moderate to severe pain (≥ 3/10). RESULTS: The one-week prevalence of any neck pain ranged from 45.4% (95% CI: 38.4, 52.4) in the Faculty of Education to 76.9% (95% CI: 72.9, 80.4) at CMCC. The one-week prevalence of neck pain ≥3/10 ranged from 44.4% (95% CI: 37.5, 51.4) in the Faculty of Education to 58.4% (95% CI: 54.0, 62.7) at CMCC. The one-week prevalence of any low back pain ranged from 60.9% (95% CI: 53.8, 67.5) in the Faculty of Education to 69.0% (95% CI: 64.8, 73.0) at CMCC, and the one-week prevalence of low back pain ≥ 3/10 ranged from 47.8% (95% CI: 43.4, 52.2) at CMCC to 55.1% (95% CI: 51.2, 58.9) in the Faculty of Health Sciences. The prevalence of any back or neck pain and pain ≥ 3/10 was consistently higher in females than males, with the largest difference seen for neck pain at CMCC. CONCLUSION: Most post-secondary students in our samples experienced LBP and NP in the past week. Overall, the one-week prevalence of NP and LBP was higher among chiropractic students and among females. This study should draw attention to school administrators about the burden of NP and LBP in post-secondary students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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) | 0.000 | 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 teacher head, 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".