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 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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".