Applying the RE-AIM conceptual framework for the promotion of physical activity in low- and middle-income countries
Bibliographic record
Abstract
ABSTRACT Objective: the RE-AIM framework has been widely used to evaluate internal and external validity of interventions aimed to promote physical activity, helping to provide comprehensive evaluation of the reach, efficacy, adoption, implementation and maintenance of research and programming. Despite this progress, the RE-AIM framework has not been used widely in Latin America. The purpose of this manuscript is to describe the RE-AIM framework, the process and materials developed for a one-day workshop in Guadalajara, and the acceptability and satisfaction of participants that attended the workshop. Methods: lecture, interactive examples and an agenda were developed for a one-day RE-AIM workshop over a three month period. Results: thirty two health care practitioners (M age = 30.6, SD=9.9 years) attended the workshop. Most (100%) rated the workshop as credible, useful (100%) and intended to apply it in current or future research (95%). Conclusion: results suggest intuitive appeal of the RE-AIM framework, and provide a strategy for introducing the utility and practical application of the framework in practice settings in Mexico and Latin America.
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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 | 0.090 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".