Exploring the consequences of housing insecurity on HIV treatment outcomes: Qualitative insights from Kisumu, Kenya
Bibliographic record
Abstract
Housing insecurity (HI) is inextricably linked to poor health outcomes. Evidence suggests people living with HIV are more likely to experience poor psychological, physical, and nutritional health challenges. However, how housing insecurity might impact treatment outcomes among people living with HIV is under-explored. We examined the consequences of HI on treatment outcomes among people living with HIV in rural Kenya. Between July and August 2023. we purposively recruited and conducted 30 in-depth interviews and four focus group discussions (n = 35) with adult men and women living with HIV. Guided by grounded theory, the data were analyzed in Dedoose and organised into themes. The structural violence framework was then used to contextualise the findings. We found that HI exacerbated poor health outcomes through perceived adherence challenges and increased occurrence of opportunistic diseases such as malaria, diarrhoea, and cough due to housing conditions. Additionally, we found that the cost of rebuilding and maintaining took away resources from other household needs. Improving HI thus may play a critical role in enhancing HIV treatment outcomes. Given the variety of ways housing, food, water, and HIV affect health, gaining insight into the relationships between these factors has tremendous implications for care and treatment.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".