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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".