Impact And Perceptions Of A Workplace Wellness Initiative Providing A Standing Desk Converter To Academic Staff
Bibliographic record
Abstract
The negative health consequences of a sedentary lifestyle are well-documented, but many workplace environments are characterized by prolonged periods of uninterrupted sitting. Standing desk interventions have shown promise in decreasing sedentary time. Stand Up for Your Health Dalhousie is a workplace initiative that provides University staff with a standing desk converter for 4-weeks. PURPOSE: To evaluate the initial impact of Stand Up for Your Health Dalhousie and test the hypothesis that the intervention will decrease sedentary time at work. The impact of the initiative on fatigue and staff’s perceptions were determined. METHODS: Ten healthy participants who worked at Dalhousie University (8 females, 32.8 ± 11.8 years, body mass index: 25.8 ± 4.8 kg/m2) were provided a standing desk converter for four-weeks. Habitual moderate-vigorous physical activity, sedentary time at work, sedentary time during leisure were assessed via the Physical Activity and Sedentary Behaviour Questionnaire before and after the intervention. Fatigue was assessed via the Fatigue Assessment Scale (1 = Never, 5 = Always) and a self-reflection questionnaire ascertained their perceptions on the standing desk converter (1 = Strongly Disagree, 7 = Strongly Agree). Cohen’s d was determined for pre-post comparisons. RESULTS: Sedentary time at work decreased (5.9 ± 0.2 to 4.7 ± 1.6 hours/day, p = 0.03, d = 1.06), but neither sedentary time during leisure (2.3 ± 1.7 to 3.7 ± 2.2 hours/day, p = 0.14, d = 0.73) nor moderate-vigorous physical activity changed (172 ± 158 to 259 ± 340 mins/week, p = 0.123, d = 0.33). Physical exhaustion decreased (2.2 ± 0.4 to 1.8 ± 0.4, p = 0.03, d = 1.00), but there was no effect on mental exhaustion (2.2 ± 0.6, post: 2.1 ± 0.6, p = 0.17, d = 0.17). Participants agreed they would use the standing desk converter in the future (6.3 ± 1.0), would recommend it to others (6.1 ± 0.6), and would purchase a standing desk converter (5.6 ± 1.4). CONCLUSIONS: Our early findings from a standing desk converter intervention provided to university staff members reduced their self-reported sedentary time at work, decreased reported physical exhaustion, and introduced staff to a tool that was perceived favorably and that they would use in the future. Support Provided by a Dalhousie Workplace Wellness Grant. Support provided via a Workplace Wellness Grant
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".