The association between self-reported low back pain and lower limb disability as well as the association between neck pain and upper limb disability
Bibliographic record
Abstract
OBJECTIVES: To investigate the association between self-reported low back pain (LBP) and lower limb disability as well as the association between neck pain and upper limb disability. METHODS: A hundred twenty-six participants registered as a healthcare staff member were included in this cross-sectional study. The presence of neck and LBP were determined using the Nordic Musculoskeletal Questionnaire. Neck and LBP/disability were measured with the Neck Pain and Disability Scale (NPDS) and Oswestry Disability Index (ODI), respectively. Upper and lower limb disability were measured with the Quick Disabilities of Arm, Shoulder, and Hand (Quick-DASH) and Western Ontario and McMaster Osteoarthritis Index (WOMAC), respectively. RESULTS: Participants reporting LBP had more musculoskeletal complaints in the lower limbs (p<0.001) and similarly participants reporting neck pain also reported more musculoskeletal complaints in the upper limbs (p<0.001). There was a correlation between the ODI and WOMAC in the participant reporting LBP during the 12 months (ρ=0.510, p<0.001) and during the last 7 days (ρ=0.674, p<0.001). The NPAD was correlated with the Quick-DASH in the participants reporting neck pain during the last 12 months (ρ=0.659, p<0.001) and the last 7 days (ρ=0.734, p<0.001). CONCLUSION: People reporting more severe LBP also reported high levels of lower limb disability. This association was also existing between the neck pain and upper limb disability.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".