Pilot study: can older inactive adults learn how to reach the required intensity of physical activity guideline?
Bibliographic record
Abstract
Most individuals do not reach the recommended physical activity level of at least 150 minutes of aerobic exercise (AE) at moderate-to-vigorous intensity per week. For example, only 13% of older Canadian adults reach World Health Organization physical activity guideline (PAG). One of the reasons might be a difficulty identifying the required intensity. Twenty-five inactive older adults received one session about the AE-PAG and how to use a tool or strategy to help them identify AE intensity: heart-rate (HR) monitor (% of maximal HR; N = 9); manual pulse (% of maximal HR; N = 8); or pedometer (walking cadence; N = 8). Participants had 8 weeks to implement their specific tool with the aim of reaching the PAG by walking at home. At pre- and post-intervention, the capacity to identify AE intensity and AE time spent at moderate-to-vigorous intensity were evaluated. Only the two groups using a tool increased total AE time (both P < 0.01), but no group improved the time spent at moderate-to-vigorous intensity. No significant improvement was observed in the ability to correctly identify AE intensity in any of the groups, but a tendency was observed in the pedometer group (P = 0.07). Using walking cadence with a pedometer should be explored as a tool to reach the PAG as it is inexpensive, easy to use, and seemed the best tool to improve both AE time and perception of intensity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".