Integrating Trauma and Violence Informed Care in Primary Health Care Settings for First Nations Women Experiencing Violence: A Systematic Review
Bibliographic record
Abstract
It is imperative that access to primary health care services is equitable as health care practitioners are often the first responders to women who experience violence. This is of particular importance for First Nations women who disproportionately experience interpersonal and structural violence when compared to non-First Nations women, as well as the ongoing impact of colonization, racism, and intergenerational trauma. To understand how primary health care services can provide equitable and effective care for First Nations women, we explored how trauma and violence informed care is integrated in primary health care settings through the lens of an equity-oriented framework. A systematic search of electronic databases included Medline (via Ovid), Scopus, Informit, and PubMed and grey literature. Six studies were included in the review and we undertook a narrative synthesis using the equity-oriented framework to draw together the intersection of trauma and violence informed care with culturally safe and contextually tailored care. This review demonstrates how equity-oriented primary health care settings respond to the complex and multiple forms of violence and intergenerational trauma experienced by First Nations women and thus mitigate shame and stigma to encourage disclosure and help seeking. Key attributes include responding to women's individual contexts by centering family, engaging elders, encouraging community ownership, which is driven by a culturally competent workforce that builds trust, reduces retraumatization, and respects confidentiality. This review highlights the importance of strengthening and supporting the workforce, as well as embedding cultural safety within intersectoral partnerships and ensuring adequate resourcing and sustainability of initiatives.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".