Examining students’ knowledge of infant feeding: A non-experimental descriptive study
Bibliographic record
Abstract
Introduction: Breastfeeding rates in Canada are suboptimal, putting mothers and their infants’ health at risk. Understanding breastfeeding knowledge and attitudes in the university student population is important as many are likely to become parents in the future. University students’ knowledge and attitudes regarding infant feeding has been studied internationally; however, no studies including both female and male students have been conducted in Canada. The purpose of this study was to determine breastfeeding experiences, education, knowledge, infant feeding attitude and perceptions of the difference in mode of infant feeding among university students which can be used to inform future health promotion campaigns and school curriculum. Methods: A non-experimental, descriptive cross-sectional study was conducted in which data from university students was collected to to identify knowledge and attitude toward breastfeeding identify differences in knowledge of breast and bottle feeding. Results: Findings suggest 65% (n=117) of university students had no previous knowledge of breastfeeding practices. Conclusion: Breastfeeding information within the high school curriculum is needed to support evidence-informed preconception infant feeding choices and increase future parents' understanding of how breastfeeding works to assist them in meeting their future infant feeding goals and increase breastfeeding rates.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".