Physical activity guides for Canadians: messaging strategies, realistic expectations for change, and evaluationThis article is part of a supplement entitled<i>Advancing physical activity measurement and guidelines in Canada: a scientific review and evidence-based foundation for the future of Canadian physical activity guidelines</i>co-published by<i>Applied Physiology, Nutrition, and Metabolism</i>and the<i>Canadian Journal of Public Health</i>. It may be cited as Appl. Physiol. Nutr. Metab. 32(Suppl. 2E) or as Can. J. Public Health 98(Suppl. 2).
Bibliographic record
Abstract
Physical activity guidelines offer evidence-based behavioural benchmarks that relate to reduced risk of morbidity and mortality if people adhere to them. Essentially, the guidelines tell people what to do, but not why and how they should do it. Thus, to motivate adherence, messages that translate guidelines should convey not only how much physical activity one should attempt and why it is recommended, but also how to achieve such a recommendation. Canada's physical activity guides exemplify how guidelines can be translated. This paper (i) provides a brief overview of the challenges encountered in creating the existing guides and (ii) highlights important practical issues and empirical evidence that should be considered in the future when translating guidelines into messages and disseminating these messages. We draw on the successes of past efforts to translate the goals of physical activity guidelines and on recent literature on messages and media campaigns to make recommendations. Information to motivate people to move toward the goals in physical activity guidelines should be translated into a set of messages that are informative, thought provoking, and persuasive. These messages should be disseminated to the public via a multi-phase social-marketing campaign that is carefully planned and thoroughly evaluated.
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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 | 0.063 | 0.166 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".