Breast milk expression knowledge of school of medicine and faculty of health sciences students
Bibliographic record
Abstract
Background: When direct breastfeeding of the mother’s breast is not possible, expressing of human milk should be provided. Education and support to the mothers for breastfeeding by health care professionals have improved breastfeeding initiation and duration. The aim of the study was to determine the knowledge of the students of Gaziantep University School of Medicine and Faculty of Health Sciences about breast milk expression. Methods: This questionnaire based, cross-sectional study was performed in 857 students between March 2012 and June 2012. Results: The mean age of the participants (493 female/364 male) was 21.1 ± 2.0 years (16-28). The eighty-six percent (736) of the participants heard something about expression of breast milk. The majority of these students agreed that breast milk can be expressed (642/736, 87.2%) and stored (595/736, 80.8%). The seventy-six percent (452/595) of the students stated that, glass container should be used to store the expressed milk. Most of the students (549/736, 74.6%) specified that breast milk expression is done by manual pump; followed by manual (277/736, 37.6%) and by electric pump (241/736, 32.7%). Most of the students mentioned to give the expressed breast milk with a bottle, by heating in warm water (440/595, 73.94%; 418/595, 70.25%; respectively). Conclusion: These findings provide insight into the educational program of the School of Medicine and Faculty of Health Sciences for breast milk expression. The knowledge level of our students for breast milk expression is encouraging, despite inadequate experience in education programs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".