Women’s Perceptions and Experiences of Breastfeeding: A Scoping Review of the Literature
Bibliographic record
Abstract
Abstract Background Despite public health efforts to promote breastfeeding, global rates of breastfeeding continue to trail behind the goals identified by the World Health Organization. While the literature exploring breastfeeding beliefs and practices is growing, it offers various, and sometimes conflicting, explanations regarding women’s attitudes towards and experiences of breastfeeding. This research explores existing empirical literature suggestions regarding women’s perceptions about and experiences with breastfeeding. The overall goal of this research is to identify what barriers mothers face when attempting to breastfeed and what supports they need to guide their breastfeeding choices. Methods This paper uses a scoping review methodology developed by Arksey and O’Malley. PubMed, CINAHL, Sociological Abstracts, and PsychInfo databases were searched utilizing a predetermined string of key words. After removing duplicates, papers published in 2010-2020 in English were screened for eligibility. A literature extraction tool and thematic analysis were used to code and analyze the data.Results In total, 59 papers were included in the review. Thematic analysis showed that mothers tend to assume that breastfeeding will be easy and find it challenging to cope with breastfeeding challenges. A lack of partner support and social networks, as well as advice from health care professionals, play critical roles in women’s decision to breastfeed. Conclusion While breastfeeding mothers are generally aware of the benefits of breastfeeding, they experience barriers at individual, interpersonal, and organizational levels. Acknowledging that breastfeeding is associated with challenges and providing adequate institutional support can improve breastfeeding rates and have a positive impact on women’s breastfeeding experiences.
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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 | 0.018 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".