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Record W2777512401 · doi:10.1590/1518-8345.1894.2923

Applying the RE-AIM conceptual framework for the promotion of physical activity in low- and middle-income countries

2017· article· en· W2777512401 on OpenAlexaff
Rebecca E. Lee, Karla I. Galavíz, Erica G. Soltero, Jose‐Benito Rosales Chavez, Edtna Jáuregui, Lucie Lévesque, Luis Ortiz-Hernández, Juan López y Taylor, Paul A. Estabrooks

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsQueen's University
Fundersnot available
KeywordsLatin AmericansAppealConceptual frameworkPsychological interventionPromotion (chess)Medical educationProcess (computing)Health promotionLow and middle income countriesPsychologyManagement scienceMedicineProcess managementPolitical scienceNursingComputer scienceDeveloping countryEngineeringPublic healthSociologyEconomic growthSocial science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.417
GPT teacher head0.590
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2017
Admission routes1
Has abstractyes

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