Should We Be More on the Ball?
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the efficacy of a 9-day accommodation protocol on reducing perceived discomfort while sitting on a stability ball (SB); trunk muscle activity levels and lumbar spinal postures were also considered. BACKGROUND: Previous studies have compared SB sitting with office chair sitting with few observed differences in muscle activity or posture; however, greater discomfort during SB sitting has been reported. These findings may indicate an accommodation period is necessary to acclimate to SB sitting. METHOD: For this study, 6 males and 6 females completed two separate, 2-hr sitting sessions on an SB. Half the participants completed a 9-day accommodation period between the visits, whereas the other half did not use an SB during the time. On both occasions, self-reported perceived discomfort ratings were collected along with erector spinae and abdominal muscle activity and lumbar spinal postures. RESULTS: Discomfort ratings were reduced in female participants following the accommodation; no effects on muscle activation or lumbar spine postures were observed. CONCLUSION: Accommodation training may reduce perceived low-back discomfort in females.Trunk muscle activity and lumbar spine postures during seated office work on an SB did not differ between groups; however, greater sample power was required to conclusively address these variables. APPLICATION: Regarding whether to use an SB in place of a standard office chair, this study indicates that females electing to use an SB can decrease discomfort by following an accommodation protocol; no evidence was found to indicate that SB chair use will improve trunk strength or posture, even following an accommodation period.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.061 | 0.027 |
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".