Adicción al internet asociado a alexitimia en estudiantes de Medicina
Bibliographic record
Abstract
determinar si la adicción al internet está asociada a alexitimia en estudiantes de medicina. Material y Métodos: se diseñó un estudio observacional, transversal analítico, en el cual se incluyó a 190 estudiantes de la Facultad de Medicina Humana de la Universidad Privada Antenor Orrego a los cuales se les realizó una encuesta virtual que incluyó preguntas de la escala de adicción a internet de Lima y la escala de alexitimia de Toronto (TAS 20) junto con datos sociodemográficos y de salud. El análisis estadístico se realizó utilizando el paquete estadístico SPSS 25.0, usando la prueba de Chi-cuadrado para determinar la significancia estadística de asociación entre las variables de estudio, aceptándose una diferencia estadística menor al 5% (p<0.05). Resultados: el 42.4% de los estudiantes de medicina presentaron adicción al internet y alexitimia, OR 6.3, p =0.0. Conclusiones: la adicción al internet, se asoció significativamente a alexitimia en estudiantes de medicina
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".