Alexitimia y estilos de apego en adolescentes de una institución educativa pública de San Juan de Miraflores
Bibliographic record
Abstract
El objetivo de este estudio fue analizar las diferencias en la alexitimia según los estilos de apego en adolescentes de una institución educativa pública en San Juan de Miraflores. Participaron 258 adolescentes, evaluados mediante la Escala de Alexitimia de Toronto (TAS-20) y el Cuestionario de Apego Camir-R. Se empleó un diseño comparativo para examinar las diferencias en la alexitimia según los estilos de apego seguro, evitativo, preocupado y desorganizado. Los resultados, evidenciaron que existen diferencias en la alexitimia según los estilos de apego (F = 5.19, p=0.002, η² = 0.06). Al comparar las dimensiones de la alexitimia, se encontraron diferencias en dificultad para identificar los sentimientos y dificultad para describir los sentimientos (F = 4.79, p = 0.003, η² = 0.054; F = 3.57, p = 0.015, η² = 0.040, respectivamente). Sin embargo, no se observaron diferencias en la dimensión pensamiento orientado externamente (F = 2.04, p = 0.108, η² = 0.024). En conclusión, estos hallazgos subrayan la importancia de considerar los estilos de apego al abordar la alexitimia en adolescentes, sugiriendo que fomentar un apego seguro podría mejorar la regulación emocional. Las implicaciones de este estudio son relevantes para el diseño de intervenciones terapéuticas y programas educativos enfocados en mejorar las habilidades emocionales y de regulación en los adolescentes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".