Efecto de la implantación de turnos de enfermería «a demanda» sobre las horas de absentismo
Bibliographic record
Abstract
El objetivo de esta experiencia es estudiar la influencia en el absentismo del personal de enfermería de un nuevo sistema de turnos rotatorios, con la novedad de que tanto la distribución horaria como la planificación y la adjudicación de los turnos se ha hecho según las demandas del propio personal. El lugar de realización ha sido el Hospital Infanta Margarita, de Cabra (Córdoba, España), y la implementación de los nuevos turnos fue durante el primer trimestre de 2011. De un total de 5551 horas absolutas de ausencia por semestre, se ha pasado a 3289 horas. La implantación de este nuevo sistema de turnos «a demanda» parece haber conseguido una reducción notable en el número de horas de ausencia del trabajo. Se trata de una estrategia para tratar de conciliar al máximo la jornada laboral con la vida personal y familiar. The objective of this study was to analyze the effect of the introduction of a new system of rotating shifts on nursing absenteeism. The novelty of this system is that both the time distribution and the planning and allocation of shifts is carried out according to the wishes of the participating nurses. This study was performed in the Infanta Margarita Hospital (Cordoba, Spain) and the new shift system was introduced in the first quarter of 2011. The total number of absolute hours of absence decreased from 5551 to 3289 per semester. The implementation of this new “on demand” shift system seems to have significantly reduced hours of absence. This strategy aims to reconcile nurses’ working hours with their personal and family lives.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".