Nurse’s impressions and changes after the workshops using the pediatric nursing care model
Bibliographic record
Abstract
For children undergoing medical examinations/procedures and nursing care, medical settings are unfamiliar environments where they are surrounded by unfamiliar people, so they often experience more fears and anxieties than adults would expect. To reduce them, nurses practice various types of patient care related to preparation, and pay adequate attention to providing psychological preparation when involved with children and their families. The workshops were conducted with the aims of: interpreting the meaning of the responses of children and their families, reflecting on daily nursing practice, exchanging information on nursing practice provided at other hospitals, and helping participants achieve new insights, by using the pediatric nursing care model. To hold workshops using a pediatric nursing care model demonstrating the basic attitudes towards ethical practice of nursing, including psychological preparation provided in medical settings, and investigate nurses’ impressions of and changes observed after the workshops. 12 pediatric nurses working at medical institutions in Japan were participated with informed consent. As a result of this workshops using the pediatric nursing care model, the original goals were accomplished. Furthermore, the implementation rate has improved in most of the care model items after the third workshop, showing the positive outcome of the workshops. We would like to further refine the model, and hold more workshops by improving its content and methods.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".