CHOOSE TO MOVE: IMPLEMENTATION OF A PHYSICAL ACTIVITY INTERVENTION AT SCALE ACROSS BRITISH COLUMBIA, CANADA
Bibliographic record
Abstract
Abstract Despite the many benefits of physical activity (PA), older adults remain among the least active Canadians. Regular PA effectively enhances social connectedness which in turn, is linked to positive health benefits. PA also promotes older adult’s physical mobility which is “the best guarantee of retaining independence and being able to cope” in later years. Although effective PA interventions exist, all but five were conducted at small scale. None were effectively scaled up and sustained over the longer term. To improve population health, effective interventions must be scaled-up. In 2015, BC Ministry of Health released a PA strategy and action plan--older adults were identified as one priority area. In partnership with government and community stakeholders we were entrusted to co-design, implement and evaluate a 6 month, evidence- and choice-based PA intervention (Choose to Move; CTM) across BC, Canada. Implementation and adaptation frameworks and processes we adopted were embedded within socioecological models. We evaluated CTM at scale-up in 26 communities with 458 low active older adults. Our implementation evaluation showed that relationships and infrastructure were key facilitators to delivering CTM at scale. Our impact evaluation showed that PA and social connectedness were enhanced; mental health (loneliness/happiness), grip strength and mobility all improved following participation in CTM. A flexible, adaptable PA model, designed with scalability in mind is key to enhance health indicators in low active older adults. Effectively engaging stakeholders at multiple levels in the implementation process is essential to success.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".