Accessing Trauma- and Violence-Informed Breastfeeding Support from Primary Care Providers among Women with Histories of Intimate Partner Violence: An Exploratory Interpretive Description Study
Bibliographic record
Abstract
Background Intimate partner violence (IPV) is a wicked social problem affecting women of all social strata and geographical location, globally. Pregnancy may be a time of heightened risk of IPV and more deleterious outcomes. Breastfeeding – a protective factor for maternal and child well-being – may be jeopardized or more challenging for women experiencing IPV. This study explored the experiences of postpartum women with histories of IPV who sought trauma- and violence-informed breastfeeding support from primary care providers. Methods Using interpretive description and philosophically underpinned by intersectionality, in-depth semi-structured interviews were completed at 12-weeks postpartum with five breastfeeding mothers with a history of IPV who sought breastfeeding support from a family physician clinic employing a trauma- and violence-informed (TVIC) model of care. Findings Four themes and two sub-themes shed light onto the experience of accessing breastfeeding support for women with a history of IPV and the perceived barriers that they faced when attempting to accesses this support, including: 1) The (demoralizing) navigation of the perinatal system ; 2) Fostering trust : i) “ It's support, but it's also knowledge” ; and ii) TVIC: feeling safe and feeling “I mattered” ; 3) Informal support: partners, family, and friends ; and 4) Baby in focus: overcoming challenges and building confidence . Conclusions TVIC may aid in the development of trusting therapeutic relationships, in turn improving access to breastfeeding support, breastfeeding self-efficacy, and breastfeeding success for women who experience violence. Further research on the implementation and evaluation of TVIC for perinatal breastfeeding education and care among women is required.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".