Barriers to accessing highly active antiretroviral therapy by HIV‐positive women attending an antenatal clinic in a regional hospital in western Uganda
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to describe barriers to accessing and accepting highly active antiretroviral therapy (HAART) by HIV-positive mothers in the Ugandan Kabarole District's Programme for the Prevention of Mother to Child Transmission-Plus (PMTCT-Plus). METHODS: Our study was a qualitative descriptive exploratory study using thematic analysis. Individual in-depth interviews (n = 45) were conducted with randomly selected HIV-positive mothers who attended this programme, and who: (a) never enrolled in HAART (n = 17); (b) enrolled but did not come back to receive HAART (n = 2); (c) defaulted/interrupted HAART (n = 14); and (d) are currently adhering to HAART (n = 12). A focus group was also conducted to verify the results from the interviews. RESULTS: Results indicated that economic concerns, particularly transport costs from residences to the clinics, represented the greatest barrier to accessing treatment. In addition, HIV-related stigma and non-disclosure of HIV status to clients' sexual partners, long waiting times at the clinic and suboptimal provider-patient interactions at the hospital emerged as significant barriers. CONCLUSIONS: These barriers to antiretroviral treatment of pregnant and post-natal women need to be addressed in order to improve HAART uptake and adherence for this group of the population. This would improve their survival and, at the same time, drastically reduce HIV transmission from mother to child.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".