The Effect of New Shower Facilities on Physical Activity Behaviors of Employees: A Quasi-experiment
Bibliographic record
Abstract
BACKGROUND: This quasi-experimental study assessed the effects of new workplace showers on physical activity behaviors in a sample of downtown employees in Austin, TX. METHODS: The study design was quasi-experimental with 2 comparison groups. Data were collected via internet-based surveys before and 4 months after shower installation at 1 worksite. Differences across study groups in the ranks of change in past-week minutes of physical activity from baseline to follow-up were assessed. Adjusted odds ratios and 95% confidence intervals for reporting an increase of ≥10 min past-week physical activity and workday physical activity among those with new showers and existing showers relative to those with no showers were also assessed. RESULTS: No significant differences in changes in physical activity from baseline to follow-up across study groups were found. One-quarter of participants with new workplace showers and 46.9% of those with existing workplace showers at baseline reported ever using the showers. CONCLUSIONS: This prospective study did not find significant changes in employee physical activity 4 months after installation of worksite showers. Worksite shower users were highly active at baseline, suggesting a possible early adopter effect, with potential for diffusion. Future studies may benefit from longer exposure times and larger samples.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".