Impact of UTT on anticipated stigma among patients newly diagnosed with HIV in Johannesburg, South Africa
Bibliographic record
Abstract
ABSTRACT Background Anticipated stigma – the fear that HIV diagnosis and status disclosure could have negative social implications – may adversely affect engagement with HIV care and treatment, despite universal eligibility for treatment under universal-test-and-treat (UTT). We aimed to determine the prevalence and predictors of anticipated stigma among newly HIV-diagnosed individuals in the context of universal access to treatment in Johannesburg, South Africa. Methods We conducted a cross-sectional survey of 652 newly HIV-diagnosed adults (≥18 years) (64.1% female, with a median age of 33 years and an interquartile range [IQR] of 28–39 years) enrolled from October 2017 to August 2018 at four primary healthcare clinics in Johannesburg. Participants were interviewed immediately after receiving their HIV test results. We used an adapted five-item, four-point scale measuring agreement with statements regarding HIV disclosure concerns and HIV status concealment (Cronbach’s alpha =.82). Mean scores were categorized as “low-to-medium” (score<=2.5), or “high” (score>2.5). We used Modified Poisson regression to assess predictors of high anticipated stigma and report adjusted risk ratios (aRR) with 95% confidence intervals (CIs). Results Overall, 55% of study participants had high anticipated stigma; 55.8% for males, 61.1% for 18–29-year-olds, and 43% for those married. Individuals in an unmarried relationship were more likely to experience high anticipated stigma than those married (aRR 1.10, 95% CI: 1.01-1.18). High anticipated stigma was lower among: older individuals (aRR 0.94 for being 30-39 vs 18-29 years, 95% CI: 0.88-0.99), those with a primary home in another province/rural area (aRR 0.82 another province vs current house, 95% CI: 0.78-0.87) or another country (aRR 0.83 another country vs current house, 95% CI: 0.78-0.88), those living in current homes for ≥5 years (aRR 0.93 for >5 years vs <1 year, 95% CI: 0.88-0.99), those with low ART concerns (aRR 0.86, 95 % CI: 0.82-0.90), and those with low perceived social-support (aRR 0.79 for low vs high, 95 % CI: 0.70-0.88). Conclusion Over 50% of adults diagnosed with HIV in the UTT era had high anticipated stigma. Findings highlight the need to address factors that continue to drive anticipated stigma, to improve social integration and mitigate the potential impact on engagement in HIV care. In addition, enhancing coping skills among individuals living with HIV is crucial.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".