Waiting to be weighed: a pilot study of the effect of delayed newborn weighing on breastfeeding outcomes.
Bibliographic record
Abstract
Although breastfeeding initiation rates are rising in Canada, rates of continued breastfeeding remain far below international recommendations. Two factors that can have a positive influence on breastfeeding outcomes are maternal confidence and support and education provided by public health nurses (PHNs). The weighing of newborns by PHNs within the first days after birth is standard practice in monitoring neonatal health. However, little is known about the effect of the timing of PHN neonatal weighing on maternal confidence or on outcomes such as intended duration of breastfeeding and formula supplementation rates. This pilot study compared breastfeeding self-efficacy, intended duration of breastfeeding and formula supplementation rates in two groups of mothers and newborns randomly assigned to different weighing protocols. Newborns in the standard care group were weighed post hospital discharge on day 2 or 3 after birth (n = 23), while those in the experimental group were weighed on day 5 (n = 26). No statistically significant differences were found between the two groups. However, a statistically significant increase in formula supplementation over the two-week study period was observed in the standard-weighing group and not in the delayed-weighing group. This finding suggests that further research is needed to assess the impact of PHN infant weighing protocols on breastfeeding outcomes.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".