Hospital Staff’s Perceptions with Regards to the Baby-Friendly Initiative
Bibliographic record
Abstract
BACKGROUND: Adherence to Baby Friendly Initiative (BFI) practices is low in Canadian hospitals, despite evidence showing a positive impact of BFI practices on breastfeeding rates and duration. In 2012, the provincial Ontario Ministry of Health and Long Term Care added BFI status to its progress indicators for Public Health Units, which are now required to begin BFI implementation. OBJECTIVE: This study aims to explore health care workers' self-reported knowledge of the BFI and their perceptions of the importance of its components. METHODS: A questionnaire was electronically sent to 2237 employees working at our institution. RESULTS: Questionnaires were completed by 651 participants, of which 110 (16.9%) and 87 (13.5%) participants reported having good knowledge of the BFI and the Ten Steps to Successful Breastfeeding, respectively. Multiple logistic regression showed that having children and having received formal breastfeeding education were associated with higher self-reported knowledge. Additionally, 481 (75%) participants reported that it was important or very important to them that the institution adopt the BFI. Having children and being an allied health professional were associated with perceiving the implementation of the BFI as important. CONCLUSION: The results of our study have allowed us to identify potential barriers to implementation of the BFI, which can be targeted through system changes and staff education. Through this approach, we hope to facilitate acceptance of the BFI at our institution and increase support for optimal breastfeeding practices among our patients.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".