Fitbit Activity Trackers Interrupt Workplace Sedentary Behavior: A New Application
Bibliographic record
Abstract
This study investigated whether Fitbit devices can reduce sedentary behavior among employees in the workplace. Participants were asked to wear Fitbits during 8-hour work shifts, 5 days per week, for 8 weeks. They were instructed to stand at least once every 30 minutes throughout the workday. The goal of the study was to determine whether standing once every 30 minutes was a feasible strategy for reducing sedentary workplace behavior. On average, participants completed 36 of 40 workdays using Fitbits. The number of times participants stood during an 8-hour workday averaged 12 stands per day (maximum 16 stands per day). These results indicate that Fitbit technology is effective for recording and tracking interruptions in sitting time; however, to reduce sitting behavior, alternate approaches are required to motivate larger numbers of workers to participate.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".