A phenomenological study of the breastfeeding experiences of African American women and the implications of societal racialization
Bibliographic record
Abstract
Background. UNICEF & The World Health Organization (WHO) recommend exclusive breastfeeding for the first 6 months of life (UNICEF & WHO, 2017). Research has reported reduced risk for all selected pediatric diseases with breastfeeding durations meeting this recommendation. Despite the proven benefits, breastfeeding rates for low-income African American mothers remain far below the guidelines established by Healthy People 2030. Purpose. The purpose of this research study was to explore the socio-cultural barriers and assets of breastfeeding experienced by African American mothers. The study was designed to elicit responses focused on barriers and facilitators of breastfeeding, specifically focusing on race as a key upstream determinant for both positive and negative experiences. Methods. In this study, a hermeneutic phenomenological qualitative approach was used conducting focus groups and in-depth interviews. Eight African American WIC eligible mothers consented to participate in the study. Results. Data was analyzed using two coders, who looked for themes within the text derived from participants’ experiences. Four main themes emerged from the experiences of the participants: (a) Healthcare provider bias, (b) Distrust/Fear, (c) Agency/Control, and (d) Support Networks. Conclusion. This study offers a novel approach to examining disparities in breastfeeding rates, duration, and exclusivity through directly engaging low-income African American mothers. This study suggests culturally appropriate training for providers, increasing the diversity of providers, providing peer coaches, and support groups for African American women would be beneficial for African American WIC eligible women wanting to be successful at breastfeeding.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".