Dissemination and implementation strategies for physical activity guidelines among adults with disability, chronic conditions, and pregnancy: a systematic scoping review
Bibliographic record
Abstract
BACKGROUND: Physical activity guidelines for adults with disability, chronic conditions, and pregnancy (i.e., specific populations) have been developed to provide guidance for engaging in physical activity. However, specific populations remain considerably less physically active compared to the general population, presenting a knowledge-practice gap. PURPOSE: The purpose of this systematic scoping review was to identify and evaluate strategies for disseminating and implementing physical activity guidelines among specific populations and/or stakeholders (e.g., healthcare professionals) in Canada. METHODS: Five search approaches (peer-reviewed literature databases, grey literature database, custom Google search engines, targeted web-based searches, and content expert consultation) identified records documenting and/or evaluating strategies that had been used to disseminate or implement guidelines from a predetermined list. Systematic and scoping review protocols were followed. Risk of bias assessments were conducted for all studies that evaluated strategies. RESULTS: Eighty-one records reported dissemination strategies (n = 42), implementation strategies (n = 28), or both (n = 11). Twenty-two studies reporting on 29 evaluated strategies were deemed "serious" or "high" risk of bias. Common guideline dissemination and implementation strategies are deliberated and recommendations for future practice are made. CONCLUSIONS: Findings may inform future dissemination and implementation efforts for physical activity guidelines in Canada or similar countries.
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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 | 0.146 | 0.393 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.024 | 0.027 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".