Maximising the impact of global and national physical activity guidelines: the critical role of communication strategies
Bibliographic record
Abstract
OBJECTIVES: Physical activity guidelines are evidence-based statements on recommended physical activity levels for good health. Guidelines, in isolation, are unlikely to increase population levels of physical activity; appropriate and effective communication is fundamental to maximising their impact. The aim of this paper is to provide a planning framework for physical activity guideline communication, including an overview of key audiences, aims and approaches. METHODS: All authors considered and agreed on the three broad issues to address by consensus. We identified key sources of evidence through scoping of the literature and our knowledge of the research area. RESULTS: Whether guidelines are global or national, communication of the physical activity guidelines should be informed by: (1) a situational analysis that considers the context in which the communication will take place and (2) a stakeholder analysis to determine the key target audiences for the communication and their values, needs and preferences. Audiences include policy-makers within and outside the health sector, other key stakeholders, the general public, specific population subgroups, health professionals and non-health professionals with a role in physical activity promotion. The aims and approach to communication will differ depending on the target audience. CONCLUSION: Communication to raise awareness and knowledge of the physical activity guidelines must be supported by policies, environments and opportunities for physical activity. Besides the intrinsic value of the physical activity guidelines, it is essential that substantial effort is put in to diligently planning, funding and implementing their communication from the outset.
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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 | 0.311 | 0.373 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.029 | 0.035 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.005 | 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".