Improving Access to HIV Care for Young Mothers Living with HIV in Zimbabwe
Bibliographic record
Abstract
Background: HIV disproportionately impacts adolescent girls and young women living in Southern Africa. Rates of mother-to-child HIV transmission are also elevated in this group, highlighting the need for targeted interventions to improve the health of young mothers living with HIV. A non-profit organization in Zimbabwe, Zvandiri, founded a peer-led care model, the Young Mentor Mother (YMM) program, in response to this issue. Methods: Four University of Toronto students conducted semi-structured virtual interviews (N=29) among Zvandiri staff and YMMs to identify the benefits and challenges of the YMM program. We applied deductive and inductive thematic analyses to transcriptions and performed a qualitative analysis using Dedoose software. Results: Participant [AT1] narratives revealed several themes, including three vital benefits from the YMM program: 1) peer- support, 2) holistic care, and 3) women’s empowerment. Barriers to the success of the program identified from interviews mapped onto the social-ecological model, whereby structural factors (lack of funding, food insecurity), community-level factors (HIV-related stigma, socio-cultural differences in accepting HIV care), and interpersonal factors (intimate partner violence) were found to impact the implementation and scale-up of the program. Barriers to scaling-up the YMM program included limited funds, lack of resources, and cultural and geographic differences. We also identified socio-structural challenges to scale-up, such as intimate-partner violence, food insecurity, and HIV-related stigma. Conclusion: Zvandiri’s YMM program fills an important gap in HIV care for young women and girls and has several benefits, such as peer-support, holistic care, and women’s empowerment. Future research focused on the perspectives of clients, stakeholders, and young fathers will further inform the scaling of the program to new countries and regions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".