Lateral Pelvis and Lumbar Motion in Seated and Standing Office Work and Their Association With Transient Low Back Pain
Bibliographic record
Abstract
Objective To assess frontal plane motion of the pelvis and lumbar spine during 2 h of seated and standing office work and evaluate associations with transient low back pain. Background Although bending and twisting motions are cited as risk factors for low back injuries in occupational tasks, few studies have assessed frontal plane motion during sedentary exposures. Methods Twenty-one participants completed 2 h of seated and standing office work while pelvic obliquity, lumbar lateral bending angles, and ratings of perceived low back pain were recorded. Mean absolute angles were compared across 15-min blocks, amplitude probability distribution functions were calculated, and associations between lateral postures and low back pain were evaluated. Results Mean pelvic obliquity (sit = 4.0 ± 2.8°, stand = 3.5 ± 1.7°) and lumbar lateral bending (sit = 4.5 ± 2.5°, stand = 4.1 ± 1.6°) were consistently asymmetrical. Pelvic obliquity range of motion was 4.7° larger in standing (13.6 ± 7.5°) than sitting (8.9 ± 8.7°). In sitting, 52% (pelvis) and 71% (lumbar) of participants, and in standing, 71% (pelvis and lumbar) of participants, were considered asymmetric for >90% of the protocol. Lateral postures displayed weak to low correlations with peak low back pain ( R ≤ 0.388). Conclusion The majority of participants displayed lateral asymmetries for the pelvis and lumbar spine within 5° of their upright standing posture. Application In short-term sedentary exposures, associations between lateral postures and pain indicated that as the range in lateral postures increases there may be an increased possibility of pain.
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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 | 0.002 |
| 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) | 0.002 | 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".