Prevalencia de factores de riesgo asociados a trastornos alimentarios en estudiantes universitarios hidalguenses
Bibliographic record
Abstract
El objetivo de este estudio consistio en determinar la prevalencia de factores de riesgo asociados a trastornos de la conducta alimentaria, por sexo y por indice de masa corporal, asi como identificar su correlacion en una muestra representativa de universitarios hidalguenses (Mexico). Se trabajo con 774 sujetos (67% mujeres y 33% hombres) de 18 a 25 anos de edad. Se emplearon cuatro instrumentos autoaplicables: el Cuestionario de Influencias sobre el Modelo Estetico Corporal, la Escala de Factores de Riesgo Asociados a Trastornos Alimentarios, el Cuestionario Breve para medir Conductas Alimentarias de Riesgo y la Escala de Actitudes hacia la Figura Corporal. La satisfaccion corporal se midio con un continuum de nueve figuras. Para obtener el indice de masa corporal, se peso y midio a cada sujeto. En la muestra total, la insatisfaccion con la imagen corporal fue muy considerable; pocos estudiantes reportaron riesgo de desarrollar un trastorno de la conducta alimentaria o habian interiorizado una figura delgada como la ideal. Hombres con obesidad y mujeres con sobrepeso registraron las prevalencias mas altas en los factores de riesgo evaluados. Se obtuvieron correlaciones positivas y significativas entre el indice de masa corporal y todos los factores de riesgo. Caracterizar el comportamiento de los factores de riesgo asociados a los trastornos de la conducta alimentaria en esta comunidad abre la oportunidad para el diseno de mejores y mas especificos programas de prevencion.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".