Personalized Walking Cadence to Increase Time at Moderate-Vigorous Intensity in Inactive Older Adults
Bibliographic record
Abstract
PURPOSE: The main goal of this study was to identify if older inactive adults using a pedometer, giving walking cadence required to reach moderate intensity, significantly increased total time spent at moderate to vigorous intensity and 10-minute bouts at moderate to vigorous intensity. METHODS: Inactive older adults (N = 42) were instructed to walk 150 minutes/week at no specified intensity during phase 1 (week 1-6). In phase 2 (week 7-12), the intervention group (N = 20) received instructions on how to reach moderate intensity, using a pedometer and individualized walking cadence, while the control group (N = 22) did not. The individualized cadence was based on the number of steps per minute required to reach 40% of VO2peak. RESULTS: During phase 1, total time spent at moderate to vigorous intensity increased from 100 ± 6 to 117 ± 64 min. (p≤ 0.05) and time spent in moderate to vigorous intensity in 10-minute bouts significantly increased from 10 (25th-75th percentile: 0-32 min.) to 19 (25th-75th percentile: 8-53 min.; p≤ 0.01). During phase 2, total time spent at moderate to vigorous intensity increased from 129 ± 67 to 203 ± 91min. (p≤ 0.01) and time spent at moderate to vigorous intensity in 10-minute bouts increased from 31(25th-75th percentile:11-55) to 88 (25th-75th percentile: 52-143); p≤ 0.01, while the control group significantly decreased both variables (p≤ 0.01). In addition, 35% of inactive older adults in the intervention group reached the common prescription of a minimum of 150 minutes of aerobic exercise per week in 10-minute bouts (p≤ 0.01). No one in the control group reached 150 minutes of aerobic exercise per week in 10-minute bouts. CONCLUSION: Inactive older adults can increase total time and 10-minute bouts at moderate to vigorous intensity by using individualized walking cadence. These results are of great importance as it suggests that walking cadence might be a useful strategy to promote exercise at the target intensity recommended for older adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".