[Factors associated with breastfeeding continuation in young Canadian mothers].
Bibliographic record
Abstract
OBJECTIVES: Breastfeeding continuation rates are lower among young mothers, while few studies have specifically focused on this population. This study describes the factors related to continued breastfeeding beyond two months among young Canadian mothers. METHODS: A descriptive and correlational design was used to identify and quantify the impact offactors affecting continued breast-feeding beyond two months. Data were derived from a selection of mothers 15-19 years who responded to The Maternity Experiences Survey. RESULTS: The difference between subgroups (15-18 vs 19 years old) in terms of breastfeeding continuation was not significant, but non-smoking (OR 2.78, 95% C, 1.351 - 5.682), living with a partner (OR 1.96, 95% CI, 1.087 to 3.597), vaginal delivery (OR 2.22, 95% CI, 1.012 to 4.878) and experiencing a large number of stressful situations (RC 0.42, 95% CI, 0.221 to 0.788) promotes continued breastfeeding beyond two months. No significant relationship wasfound with pregnancy planning, prenatal preparation, the violence suffered, depressive symptoms and the availability of social support. CONCLUSION: Some factors related to pre-and postnatal periods, in addition to sociodemographic factors influence the choice of young Canadian mothers to continue or not continue breastfeeding beyond two months. Our results will be used to guide specific interventions for young mothers in breastfeeding protection, promotion and support programmes.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".