OUP accepted manuscript
Bibliographic record
Abstract
Background: Exposure to whole body vibration (WBV) is common in construction, agriculture, mining, and transportation. There is strong epidemiological evidence linking WBV with adverse health outcomes in the long-term, including low back pain. Fortunately, WBV exposure guidelines to prevent long-term musculoskeletal disorders and discomfort exist. In the shorter-term, it has been speculated that occupational levels of WBV may lead to increased risk of vehicle accidents and falls during egress; however, the acute effects of different vibration intensities remain poorly understood and it is uncertain whether established standards protect the worker from injurious short-term effects. Objective: The aim of this study was to investigate the acute sensorimotor, physical, and cognitive effects of occupationally-relevant, simulated whole body vibration (WBV) at levels equivalent to international standard guideline thresholds for long-term discomfort and musculoskeletal disorder risk. Method: Eighteen participants were recruited to perform four, 60-min conditions: (i) Control-no vibration, (ii) Low vibration-equivalent to the exposure action value, (iii) Shock-transient impacts at 1-min intervals superimposed on the Low condition, and (iv) High vibration-equivalent to the exposure limit value. Whole body vibration was simulated using data based on field-collected accelerations experienced by rural workers while operating an all-terrain vehicle. This vibration signal was manipulated to achieve required intensities for each condition and simulated with a 6 degree-of-freedom hexapod platform. Before and after each condition, we collected: rating of perceived body discomfort, rating of perceived headache, postural sway, blink frequency, King-Devick test, and psychomotor vigilance task. Pre- and post-condition data in each condition were submitted to either a paired t-test (parametric) or Wilcoxon signed-rank test (non-parametric). To determine differences between conditions, each condition's post-condition data was normalized to its pre-condition value and entered as the dependent variable in a repeated measures analysis of variance. Results: All conditions, including Control, led to increased upper body discomfort when compared to pre-exposure baseline. The Low condition led to increased discomfort in seven body locations, headache (91% increase from baseline; t = -2.44, P = 0.03), and postural imbalance (53% increase from baseline; t = -2.88, P = 0.01), but the effect on cognitive functioning was less clear. Shock condition led to whole body discomfort, specifically at nine upper body and lower body locations. The High condition led to increased whole body discomfort at all 10 body locations, headache (154% increase from baseline; t = -2.91, P = 0.01), postural imbalance (61% increase from baseline; t = -2.57, P = 0.02), and decrements in vigilance (mean reaction time: 6% increase from baseline, t = -3.27, P = 0.005; Number of lapses: 100% increase from baseline, S = -42.5, P = 0.002). Conclusion: Although the number of pre-post condition effects increased with higher vibration intensity, these effects were not significantly different from sitting without vibration. Therefore, current guideline thresholds might not protect the worker from acute WBV effects. However, further research is needed to discern these effects from other sources of WBV. Based on this study, future WBV interventions and action controls should not only address vibration reduction, but also consider potential effects from prolonged sitting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.844 | 0.790 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".