The effects of stand-up desks: A one year follow up with academic office staff
Bibliographic record
Abstract
There have been multiple studies with clear evidence of the long-term health benefits of the implementation of a sit-stand workstation (Biswas et al., 2015; Chau et al., 2013; Wilmot et al., 2012). The aim of this study was to further understand the long-term efficacy and benefits of the adoption of a sit-stand workstation in a typical office environment. Twelve participants from a larger study involving staff from Mount Royal University were recruited via email and interviewed individually by a trained RA. The interviews were guided by several questions related to the effects of a sit-stand desk to physical and mental health, ergonomics of the desk, and thoughts about sitting and standing. During the interviews, data was collected in the form of written notes and inputted into QSR International's NVIVO (version 11.0, 2015) qualitative analysis software. An iterative approach was used to derive the predominant themes reflected in the participants' perceptions, until theoretical saturation of themes was achieved after analysis of all interviews. The following themes were identified: previous familiarity to sit-stand desk, work efficiency when using desk, adjustment and usage of desk, strategies to increase usage of desk, motivation to use desk, desk enjoyment, and changed thoughts about sitting and standing. Participants indicated that they enjoyed the desk and have experienced positive physical and mental health when using it. Most participants used timers or app to remind them to use the desk regularly. Space concerns were also reported including not enough room to spread out to do other work.Acknowledgments: MRU President's Executive Committee
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".