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.
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 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".