Effects of museum-based art activities on older community dwellers’ physical activity: The A-health randomized controlled trial results
Bibliographic record
Abstract
Abstract Purpose. Museum-based art activities have demonstrated health benefits in older adults. Few clinical trials, however, have examined physical health benefits. This randomized controlled trial (RCT) aims to compare changes in daily step count over a 3-month period in older adults participating in museum art-based activities and their control counterparts. Methods. Using a subset of 53 participants recruited in the A-health RCT, the daily step count of 28 participants in the intervention group and 25 in the control group were recorded with a Fitbit Alta HR. Weekly art-based activities were carried out at the Montreal Museum of Fine Art (MMFA, Quebec, Canada) over a 3-month period. The outcomes were the mean step count per active hours (i.e., between noon and 6pm), inactive hours (i.e., between midnight and 6am) and full day (i.e., 24h), and the change of step count following the 3-month (M3) intervention of art activities at the MMFA (M3). Results. The intervention group had greater daily step count compared to the control group at M3, regardless of the step parameters examined (P ≤ 0.026). The change in daily step count for active hours (P = 0.023) and full day (P = 0.011) increased significantly with the MMFA art-based activities. Conclusion. MMFA-based art activities improved daily physical activity in older community-dwellers who participated in the RCT, confirming health benefits and suggesting a potential of museums in health promotion and prevention.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".