Overcoming structural violence through community-based safe-spaces: Qualitative insights from young women on oral HIV pre-exposure prophylaxis (PrEP) in Kisumu, Kenya
Bibliographic record
Abstract
Biomedical and behavioral interventions have led to significant success in the prevention of HIV/AIDS. However, in rural communities, structural violence persists and continues to create barriers to the uptake and utilization of health services, especially among young women. To overcome these barriers, community-led initiatives have provided a range of interventions, including safe spaces (i.e., vetted meeting venues where girls come together to discuss issues affecting their wellbeing and access health services, such as PreP) for young women. Although these spaces provide a safe haven for at-risk girls and young women, the role of community safe spaces in overcoming structural violence remains under-explored in literature. Using the structural violence framework, this study explored how community-led safe spaces for HIV prevention programs can overcome structural forces - policies, norms, or practices - that perpetuate structural violence and prevent access to healthcare services among young girls and women in Kisumu, Kenya. We purposively recruited young women (n = 36) enrolled in the Pamoja Community-Based Organization's DREAMS program in Kisumu, Kenya. Data were collected from the 2022-2023 cohort between June and July 2023 using semi-structured, in-depth interviews (n = 20) and two focused group discussions (n = 16). Guided by thematic analysis, data were analyzed in Atlas.Ti and organized into themes. This study found that community approaches such as safe spaces are instrumental in overcoming structural violence among young women by addressing three forms of barriers - institutional, sociocultural, and economic barriers - that limit HIV support service access. Institutional barriers encompassed distance and time to health facilities and provider attitude, while sociocultural barriers included knowledge gaps, stigma, cultural norms, beliefs, and practices, limiting health service access. Lastly, the socioeconomic barriers highlighted inadequate income, financial literacy, and financial dependency. Community safe spaces are vital for decreasing vulnerability and serve as critical points for accessing services and building capacity for young women. This is particularly important in rural areas where retrogressive societal norms create obstacles to obtaining essential health services. To effectively overcome structural violence, however, government support and a suitable policy environment are essential for implementing interventions to address the underlying root causes of structural violence and sustaining community-based safe spaces.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".