Development and evaluation of a Chinese-language newborn feeding hotline: A prospective cohort study
Bibliographic record
Abstract
Background: Preference for formula versus breast feeding among women of Chinese descent remains a concern in North America. The goal of this study was to develop an intervention targeting Chinese immigrant mothers to increase their rates of exclusive breastfeeding. Methods We convened a focus group of immigrant women of Chinese descent in Vancouver, British Columbia to explore preferences for method of infant feeding. We subsequently surveyed 250 women of Chinese descent to validate focus group findings. Using a participatory approach, our focus group participants reviewed survey findings and developed a priority list for attributes of a community-based intervention to support exclusive breastfeeding in the Chinese community. The authors and focus group participants worked as a team to plan, implement and evaluate a Chinese language newborn feeding information telephone service staffed by registered nurses fluent in Chinese languages. Results Participants in the focus group reported a strong preference for formula feeding. Telephone survey results revealed that while pregnant Chinese women understood the benefits of breastfeeding, only 20.8% planned to breastfeed exclusively. Only 15.6% were breastfeeding exclusively at two months postpartum. After implementation of the feeding hotline, 20% of new Chinese mothers in Vancouver indicated that they had used the hotline. Among these women, the rate of exclusive breastfeeding was 44.1%; OR 3.02, (95% CI 1.78–5.09) compared to women in our survey. Conclusion Initiation of a language-specific newborn feeding telephone hotline reached a previously underserved population and may have contributed to improved rates of exclusive breastfeeding.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".