Vulnerable mothers' experiences breastfeeding with an enhanced community lactation support program
Bibliographic record
Abstract
The Canada Prenatal Nutrition Program (CPNP) provides a variety of health and nutrition supports to vulnerable mothers and strongly promotes breastfeeding but does not have a formal framework for postnatal lactation support. Breastfeeding duration and exclusivity rates in Canada fall well below global recommendations, particularly among socially and economically vulnerable women. We aimed to explore CPNP participant experiences with breastfeeding and with a novel community lactation support program in Toronto, Canada that included access to certified lactation consultants and an electric breast pump, if needed. Four semistructured focus groups and 21 individual interviews (n = 46 women) were conducted between September and December 2017. Data were analysed using inductive thematic analysis. Study participants reported a strong desire to breastfeed but a lack of preparation for breastfeeding-associated challenges. Three main challenges were identified by study participants: physical (e.g., pain and low milk supply), practical (e.g., cost of breastfeeding support and maternal time pressures), and breastfeeding self-efficacy (e.g., concern about milk supply and conflicting information). Mothers reported that the free lactation support helped to address breastfeeding challenges. In their view, the key element of success with the new program was the in-home visit by the lactation consultant, who was highly skilled and provided care in a non-judgmental manner. They reported this support would have been otherwise unavailable due to cost or travel logistics. This study suggests value in exploring the addition of postnatal lactation support to the well-established national CPNP as a means to improve breastfeeding duration and exclusivity among vulnerable women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".