Walk@work: A feasibility study of a web-based tool to support workplace walking
Bibliographic record
Abstract
Web-based physical activity programs have the capacity to reach populations where prolonged sitting is a concern. The aim of this study was to implement and evaluate a university-wide, workplace walking intervention (Walk@Work) targeting sedentary staff. 96 university staff ( M age = 44.0 yrs; M BMI = 29.7 kg/m 2 ) were recruited. All participants received a pedometer and access to an interactive website containing support strategies and a walking program. The program aimed to incrementally increase steps over a 6-week period (Phases I-III), followed by a 4-week maintenance period (Phases IV and V). Primary outcome was change in step counts, which was analyzed using repeated measures ANCOVA. Secondary outcomes were changes in quality of life, and measures of intervention feasibility and acceptability. Descriptive statistics and paired-samples t -test were used to analyze secondary outcomes. Results indicated a significant main effect for phase, F = 4.15, p = .006. Posthoc comparisons revealed higher mean step counts during the maintenance phases (Phase IV: M = 9354, p M = 9591, p = .01) vs. Phase I ( M = 8782). Secondary analysis revealed a trend for improved scores on the vitality quality of life subscale, t = -1.96, p = .056. 130 employees expressed interest in the program, 96 registered for the program, and 53 (55%) completed the full 10 weeks. Majority (96%) of participants was female. Overall, Walk@Work was a feasible and effective short-term program for increasing and maintaining workplace walking. Ongoing work will use process evaluations to improve website functionality prior to larger, multi-site trials. Acknowledgments: University of Toronto's Health and Well-Being Programs and Services and the Organizational Development and Learning Centre for their assistance with study recruitment.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".