Integrating trauma- and violence-informed care for adolescent mothers in Rwanda: a qualitative study with community health workers
Bibliographic record
Abstract
Abstract Introduction In Rwanda, maternal community health workers play a critical role to improving maternal, newborn and child health, but little is known about their specific experiences with adolescent mothers, who face unique challenges, including trauma, ongoing violence, stigma, ostracism, mental health issues, barriers within the healthcare system, and lack of access to the social determinants of health. This study explored the experiences of maternal community health workers when caring for adolescent mothers in Rwanda to inform the delivery of trauma- and violence-informed care in community maternal services. Methods Interpretive Description methodology was used to understand the experiences of 12 community health workers purposively recruited for interviews due to their management roles. To gain additional insights about the context, seven key informants were also interviewed. Findings Maternal community health workers provided personalized support to adolescent mothers through the provision of continuity of care, acting as a liaison, engaging relationally and tailoring home visits. They reported feeling passionate about their work, supporting each other, and receiving support from their leaders as facilitators in caring for adolescent mothers. Challenges in their work included handling disclosures of violence, dealing with adolescent mothers’ financial constraints, difficulties accessing these young mothers, and transportation issues. Adolescent mothers’ circumstances are generally difficult, leading to self-reports of vicarious trauma among this sample of workers. Conclusion Maternal community health workers play a key role in addressing the complex needs of adolescent mothers in Rwanda. However, they face individual and structural challenges highlighting the complexities of their work. To sustain and enhance their roles, it is imperative for government and other stakeholders to invest in resources, mentorship, and support. Additionally, training in equity-oriented approaches, particularly trauma- and violence-informed care, is essential to ensure safe and effective care for adolescent mothers and to mitigate vicarious trauma among maternal community health workers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".