Real-World Evaluation of a Community-Based Pedometer Intervention
Bibliographic record
Abstract
BACKGROUND: We evaluated a pedometer-based community intervention under real-world conditions. METHODS: Participants (n=559) provided demographic and health information using surveys and steps/d at baseline and during the last week the participants were in the program. A 1-year follow-up was conducted, but in keeping with real-world conditions, no incentives were offered to participate. RESULTS: Participants (89% female, age 48.1 [SD=12] years) took 7864 (3114) steps/d at baseline. Postprogram voluntary response rates to mailed surveys were 41.3% at 12 weeks and 22.8% at 1 year. Program completers reported significantly higher steps/d at 12 weeks (approximately 12,000 steps/d) and 1 year (approximately 11,000 steps/d) compared with baseline. CONCLUSIONS: The improvement in steps/d in this real-world implementation was consistent with more controlled studies of pedometer-based interventions. Low response to voluntary follow-up is a study limitation but is expected of real-world evaluations.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".