Modelos sobre promoción de salud en medicina familiar internacional e implicaciones en medicina general integral
Bibliographic record
Abstract
Introduccion: los conceptos de salud y promocion de salud han evolucionado en los ultimos anos, oscilan desde una concepcion medica hasta una mas general lo cual ha conllevado a nuevas redefiniciones. Objetivo: identificar los diferentes modelos/enfoques en promocion de salud en la medicina familiar contemporanea internacional para proponer un modelo integrador sobre la base de lo mejor de cada modelo identificado. Metodos: se realizo una revision bibliografica de enero a marzo del 2019 en las bases de datos: MEDLINE y SciELO, usando palabras claves como: health promotion , y family medicine, family physician, general practice, general practitioner ; se consultaron libros de texto de Medicina Familiar y Comunitaria de paises como Estados Unidos, Canada, Espana, Brasil, Argentina, y capitulos de libros y bibliografia basica sobre promocion de salud de reconocidos autores, utilizando como criterio de inclusion la practica y ensenanza de la promocion de salud en la medicina familiar. Resultados : se exponen los diferentes modelos de la promocion de salud en la medicina familiar internacional: biomedico, educativo, de comportamientos/estilos de vida, de empoderamiento, de etapas de vida, socioambiental, de desigualdades sociales en salud, ecologico y salutogenico, los que fueron analizados a partir de diferentes puntos de vista de varios autores. Conclusiones: luego de un proceso de induccion, deduccion, de analisis y sintesis, se propone un modelo integrador que recoge lo mejor de los identificados y que pudiera aplicarse a la medicina general integral cubana.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".