Does a break from sitting change biomechanical outcome measures or transient pain? A laboratory-based experimental study
Bibliographic record
Abstract
BACKGROUND: Sitting can induce transient low back pain (LBP) in healthy individuals. A rest from sitting should provide relief, however, the parameters of breaks (activity type, intensity, duration, and timing) are not currently known. OBJECTIVE: The purpose of this study was to examine the effect of 2-minute walking breaks at 40-minute intervals on sitting-induced LBP. METHODS: Thirty-two healthy participants were recruited for a within-control study: two randomly presented sessions of sitting for 2 hours with and without breaks. Outcome measures were compared between condition and pain group using a three-way ANOVA with significance atp > 0.05. RESULTS: Walking breaks at 40-minute intervals result in significantly lower pain ratings than those taken immediately before the break for sitting-induced back pain developers. However, this relief is short lived (<10 minutes), with ratings increasing to pre-break levels once the sitting exposure resumes. There were no differences in biomechanical factors between sessions. Regardless of session type, pain developers displayed higher spine fidget frequency than non-pain developers, females sat with less spine flexion, with greater gluteal activation levels, and with their center of pressure approximately half a centimeter to the left and forward compared to males, and males had significantly greater peak pressures over a smaller area compared to females. CONCLUSION: Walking breaks at 40-minute intervals provide significant, but temporary, relief of sitting-induced back pain for pain developers. Future work should optimize break parameters and examine the longer-term benefit of breaks, especially for individuals that are not able to tolerate sitting for extended durations.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".