Effect of a ‘spine offloading’ chair design on seated height and posture
Bibliographic record
Abstract
A prototype chair with anterior chest and arm supports has been designed to reduce compressive spine loads. The purpose of this study was to compare the effects of this offloading design on seated height compared to a control configuration of the same chair. 20 males sat on each configuration for 1 hour. Seated height, perceived pain, spine angles, seat pressure, and participant experience were measured. Spine height loss was significantly reduced in the offloading (–0.75 ± 3.79 mm) compared to the control configuration (–6.16 ± 4.27 mm, p < 0.001), and participants sat significantly more anterior on the seat pan in the offloading (20.56 ± 1.67 cm) compared to control configuration (18.03 ± 1.92 cm, p < 0.001). There were no differences in spine angles or perceived back and gluteal pain between configurations. This design appears to be a promising approach to protecting the back during sitting when engaging in forward leaning tasks where the offloading effect of a backrest may be minimised. Practitioner summary: A prototype chair with anterior chest and arm supports designed to offload the spine was shown to significantly reduce seated height loss during 1-hour of sitting compared to a control configuration. While participants perceived the offloading design to be more supportive, no differences in perceived pain or posture were found.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".