How Many Days of Pedometer Use Predict the Annual Activity of the Elderly Reliably?
Bibliographic record
Abstract
PURPOSE: Daily variations of physical activity in the elderly remain unclear. We thus used a uniaxial accelerometer/pedometer to examine the variability of step counts for 1 yr, determining the minimum number of days observation needed to obtain reliable estimates of annual physical activity. METHODS: Subjects were 37 males and 44 females, healthy Japanese, aged 65-83 yr. The pedometer was worn on the waistband throughout 1 yr, accumulating information on the individual's daily step count. RESULTS: The step count spectrum showed peaks with periods of 2.3, 3.5, and 7.0 d and an aperiodic component that had a greater power at low frequencies (i.e., non-white noise). These characteristics were absent in randomly resequenced data. To ensure that 80% of total variance was attributable to between-subjects variance, 25 and 8 consecutive days of observation were needed in male and female subjects, respectively. To achieve 90% on this same measure of reliability, 105 and 37 consecutive days of observation were required. In contrast, 4 d of randomly timed observations yielded 80% reliability for both men and women, and 11 and 9 d gave 90% reliability in men and women, respectively. If sampling also took account of season and day of the week, the respective observation periods for men and women were reduced to 8 and 4 d (i.e., 2 and 1 consecutive days of sampling every 89 d) for 80% and to 16 and 12 d (i.e., 4 and 3 consecutive days every 89 d) for 90% reliability. CONCLUSION: When estimating annual step counts, seasonal and/or random sampling of data allows collection of reliable data during substantially fewer days than needed for consecutive observations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".