A CHOICE-BASED PHYSICAL ACTIVITY AND ACTIVE TRAVEL INTERVENTION FOR OLDER MEN
Bibliographic record
Abstract
Low levels of physical activity contribute to loss of mobility and independence in older men. We conducted a 12-week randomized controlled feasibility trial of choice-based physical activity (PA) and active travel. Participants were community-dwelling ‘low active’ men aged 60+ (n=29 intervention (INT), n=29 waitlist control). Trained activity coaches delivered: 1) one-on-one participant consultations to develop personal action plans for PA and active travel; 2) monthly group-based motivational meetings; 3) weekly telephone support; 4) complimentary recreation and transit passes; and 5) pedometers and diaries for self-monitoring. INT chose a wide range of group-based and individual PAs (e.g., group exercise classes, walking, cycling) and destinations (e.g., parks, cities, shops/restaurants) for their personal action plans. At 12 weeks, INT achieved 9.0 more minutes/day of moderate-to-vigorous PA (p=0.06) and 1140 more steps/day (p=0.04), engaged in 5.2 more moderate intensity PAs/week (p<0.01), and expended 1493 more kcal of energy/week from moderate PAs (p=0.02). INT was 4.2 times more likely to take at least one transit trip/week (95%CI:1.2–18.0) and 3.3 times more likely to meet national guidelines of ≥150 minutes/week of moderate-to-vigorous PA in bouts of ≥10 minutes (95%CI:0.75–16.3). At 24 weeks follow-up (12 weeks after intervention end), INT benefits relative to baseline were sustained for minutes/day of moderate-to-vigorous PA, number of moderate intensity PAs/week, and kcal of energy/week from moderate PAs. In conclusion, a choice-based model of PA paired with active travel may be an effective approach to promote PA among older men.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".