The effect of educational program on nurse's knowledge and practices about nasogastric tube feeding at neonatal intensive care units
Bibliographic record
Abstract
Objective: This study was to assess the effectiveness of educational program on nurses’ knowledge level and their practices about nasogastric tube feeding at neonatal intensive care units.Methods: Settings: The study was conducted at Banha Specialized Pediatric Hospital and Banha University Hospital, from neonatal intensive care units. Research design: A quasi-experimental design. Sample: A convenient sample method of eighty three (83) as a one study group. Tools: The questionnaire format, the observation checklist and construction of educational program which were developed by the researchers to assessment for the knowledge and practice for nurses’ related to nasogastric tube feeding. The educational program was designed serves as a referral instructional for nurses.Results: Implied that the educational program was having a positive effect, on enhance nurses’ knowledge and practice related to nasogastric tube feeding at neonatal intensive care units.Conclusions: The present study recommended that an administrating a written protocol of nasogastric tube feeding to assure sufficient knowledge, and saved practices are really needed at neonatal intensive care units.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".