The black box of large-scale dissemination: Building an evidence base documenting the complexity of national movement behaviour guideline dissemination to inform research, practice, and policy
Bibliographic record
Abstract
National movement behaviour guidelines are important for public health. However, they have had little influence on practice and policy. This dissertation is composed of four studies that aim to build an understanding of the multi-level influences on the large-scale dissemination of national movement behaviour guidelines. Manuscript 1 assessed the (1) awareness and knowledge of national movement behaviour guideline recommendations among adults living in Canada and (2) the demographic correlates associated with guideline awareness. Findings highlight that the short-term dissemination efforts for the Canadian 24-Hour Movement Guidelines for Adults Aged 18-64 Years and Adults Aged 65 Years or Older (24HMG) had a modest impact on awareness (i.e., 31% at a population level). Long-term dissemination efforts may be needed to observe further increases. Manuscript 2 applied the Reach Effectiveness Adoption Implementation and Maintenance framework to evaluate the dissemination of the 24HMG. The approach used to disseminate the 24HMG resulted in a large reach to target audiences and short-term improvements in guideline awareness. At an organizational level, the dissemination performed for the 24HMG peaked in the first 4-months post-guideline release. Findings yield insight into the process and impact of national movement behaviour guideline dissemination and suggest that more coordinated and scalable approaches may be needed. Manuscript 3 explored the potential barriers and facilitators experienced by intermediary organizations to disseminating national movement behaviour guidelines using the Consolidated Framework for Implementation Research. Multi-level factors were identified as having an influence on guideline dissemination. Capacity-building strategies may be needed if intermediary organizations are to play a central role in future guideline initiatives. Lastly, Manuscript 4 used social network analysis to explore network features that may influence the dissemination of national movement behaviour guidelines. Findings demonstrate the potential for constrained information sharing among organizations. Efforts to improve information sharing among this network may be needed to enhance future guideline dissemination. The studies within this dissertation serve as a possible explanation for why national movement behaviour guidelines have had a limited influence on important dissemination outcomes. Future initiatives may benefit from embracing the complexity of guideline dissemination and working in partnership to facilitate the integration of guidelines into practice and policy.
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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 | 0.510 | 0.683 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.029 | 0.042 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 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".