Ergonomics training coupled with new Sit-Stand workstation implementation influences usage
Bibliographic record
Abstract
Currently, there is no guidance on the training programme approach that should be provided to new sit-stand workstation users to optimally integrate workstation usage patterns into their working day. The objective of this research study was to determine if a training programme could influence long-term usage of sit-stand workstations. Thirty-five employees from the University of Waterloo volunteered to participate in this longitudinal study. Two different types of training programmes were delivered: (1) an example from industry and (2) based on current literature. There was an influence of training programme on the frequency of sit to stand transitions made each day. Those who received the additional training programme also reported sitting less, standing more and used their sit-stand workstations more consistently day-to-day than those who did not. Practitioner Summary: A longitudinal study was conducted to assess the impact of training programmes on sit-stand workstation usage. A training programme based on current literature resulted in more consistent sit-stand usage than an industry example.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".