Escala Argentina de Dificultades Alimentarias en Niños (EADAN): Propiedades Psicométricas
Bibliographic record
Abstract
El objetivo de esta investigación fue adaptar y validar en Argentina un cuestionario para padres que detecta dificultades en la alimentación, las cuales son muy comunes entre los niños pequeños. Se analizaron las propiedades psicométricas de la Escala Argentina de Dificultades Alimentarias en Niños (EADAN) en una muestra argentina de 263 niños de entre los 6 meses y los 6 años 11 meses de edad. Existen diferencias significativas entre la media por ítem y la media del puntaje total en los grupos con dificultades y sin dificultades en la alimentación. La confiabilidad de la escala es buena, con un valor ? = .79. Se realizó un análisis factorial exploratorio que arrojó dos factores que representan el 49.4% de la varianza. Se compararon los puntajes obtenidos por niños prematuros y nacidos a término. Se concluye acerca de la validez del instrumento para la detección de dificultades en la alimentación en niños argentinos.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".