Online Perceptions of Mothers About Breastfeeding and Introducing Formula: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Although the benefits of breastfeeding are well established for babies and their mothers, many women give formula to their infants. Whether to breastfeed or to give infant formula is a complex decision to make. Many parents use the Internet to find information and support that relate to infant feeding decisions. OBJECTIVE: The aim of this study was to analyze the perceptions of mothers, who are discussing the topic on Web forums, about introducing infant formula. METHODS: This is a qualitative, descriptive, and cross-sectional study on online data from parenting Web forums. The text was analyzed using qualitative content analysis. RESULTS: The analysis resulted in 1 main theme, "balancing between social expectations and confidence in your parental ability," which is further divided into 3 themes: "striving to be a good mother," "striving for your own well-being," and "striving to discover your own path." CONCLUSIONS: Breastfeeding is complex, and health care personnel can, with a more open approach toward formula, create better support for mothers by helping them to be more confident in their parental ability.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".