Implementation and adherence issues in a workplace treadmill desk intervention
Bibliographic record
Abstract
We report experiences, observations, and general lessons learned, specifically with regards to participant recruitment and adherence, while implementing a 6-month randomized controlled treadmill desk intervention (the WorkStation Pilot Study) in a real-world office-based health insurance workplace. Despite support from the company's upper administration, relatively few employees responded to the company-generated e-mail to participate in the study. Ultimately only 41 overweight/obese participants were deemed eligible and enrolled from a recruitment pool of 728 workers. Participants allocated to the Treadmill Desk Group found the treadmill desk difficult to use for 45 min twice a day as scheduled. Overall attendance averaged 45%-50% of all possible scheduled sessions. The most frequently reported reasons for missing sessions included work conflict (35%), out of office (30%), and illness/injury/drop-out (20%). Although focus groups indicated consistently positive comments about treadmill desks, an apparent challenge was fitting a rigid schedule of shared use to an equally rigid and demanding work schedule punctuated with numerous tasks and obligations that could not easily be interrupted. Regardless, we documented that sedentary office workers average ∼43 min of light-intensity (∼2 METs) treadmill walking daily in response to a scheduled, facilitated, and shared access workplace intervention. Workstation alternatives that combine computer-based work with light-intensity physical activity are a potential solution to health problems associated with excessive sedentary behavior; however, there are numerous administrative, capital, and human resource challenges confronting employers considering providing treadmill desks to workers in a cost-effective and equitable manner.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".