Evidence-informed recommendations for constructing and disseminating messages supplementing the new Canadian Physical Activity Guidelines
Bibliographic record
Abstract
BACKGROUND: Few validated guidelines exist for developing messages in health promotion practice. In clinical practice, the Appraisal of Guidelines, Research, and Evaluation II (AGREE II) Instrument is the international gold standard for guideline assessment, development, and reporting. In a case study format, this paper describes the application of the AGREE II principles to guide the development of health promotion guidelines for constructing messages to supplement the new Canadian Physical Activity Guidelines (CPAG) released in 2011. METHODS: The AGREE II items were modified to suit the objectives of developing messages that (1) clarify key components of the new CPAG and (2) motivate Canadians to meet the CPAG. The adapted AGREE II Instrument was used as a systematic guide for the recommendation development process. Over a two-day meeting, five workgroups (one for each CPAG - child, youth, adult, older adult - and one overarching group) of five to six experts (including behavior change, messaging, and exercise physiology researchers, key stakeholders, and end users) reviewed and discussed evidence for creating and targeting messages to supplement the new CPAG. Recommendations were summarized and reviewed by workgroup experts. The recommendations were pilot tested among end users and then finalized by the workgroup. RESULTS: The AGREE II was a useful tool in guiding the development of evidence-based specific recommendations for constructing and disseminating messages that supplement and increase awareness of the new CPAG (child, youth, adults, and older adults). The process also led to the development of sample messages and provision of a rationale alongside the recommendations. CONCLUSIONS: To our knowledge, these are the first set of evidence-informed recommendations for constructing and disseminating messages supplementing physical activity guidelines. This project also represents the first application of international standards for guideline development (i.e., AGREE II) to the creation of practical recommendations specifically aimed to inform health promotion and public health practice. The messaging recommendations have the potential to increase the public health impact of evidence-based guidelines.
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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 | 0.184 | 0.404 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".