Unequal access to ART: exploratory results from rural and urban case studies of ART use
Bibliographic record
Abstract
INTRODUCTION: South Africa has the world's largest antiretroviral treatment (ART) programme. While services in the public sector are free at the point of use, little is known about overall access barriers. This paper explores these barriers from the perspective of ART users enrolled in services in two rural and two urban settings. METHODS: Using a comprehensive framework of access, interviews were conducted with over 1200 ART users to assess barriers along three dimensions: availability, affordability and acceptability. Summary statistics were computed and comparisons of access barriers between sites were explored using multivariate linear and logistic regressions. RESULTS: While availability access barriers in rural settings were found to be mitigated through a more decentralised model of service provision in one site, affordability barriers were considerably higher in rural versus urban settings. 50% of respondents incurred catastrophic healthcare expenditure and 36% borrowed money to cover these expenses in one rural site. On acceptability, rural users were less likely to report feeling respected by health workers. Stigma was reported to be lowest in the two sites with the most decentralised services and the highest coverage of those in need. CONCLUSIONS: While results suggest inequitable access to ART for rural relative to urban users, nurse-led services offered through primary healthcare facilities mitigated these barriers in one rural site. This is an important finding given current policy emphasis on decentralised and nurse-led ART in South Africa. This study is one of the first to present comprehensive evidence on access barriers to assist in the design of policy solutions.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".