The Influence of Anticipated HIV Stigma on Health-related Behaviors, Self-rated Health, and Treatment Preferences Among People Living with HIV in East Asia
Bibliographic record
Abstract
Long-acting injectable regimens for HIV treatment have been developed which are less frequent, more discreet, and more desirable for some people living with HIV (PLHIV) and may help reduce stigma-related barriers to HIV treatment. However, there is little information on the relationship between reported stigma and preference for these newer treatments. We characterized anticipated, experienced, and internalized HIV stigma and examined the associations with treatment preferences among an international sample of PLHIV. Data came from the international, web-based, cross-sectional study called "Positive Perspectives" conducted among PLHIV aged ≥ 18 years in 25 geographic locations during 2019 (n = 2389). Descriptive analyses were stratified among East Asian (n = 230) vs. non-Asian (n = 2159) participants. Results showed that prevalence of anticipated stigma was significantly higher among East Asian than non-Asian participants (72.2%[166/230] vs. 63.8%[1377/2159], p = 0.011). A significantly higher percentage of East Asian (68.7%[158/230]) than non-Asian participants (43.3%[935/2159] indicated that someone finding their HIV pills would cause them much "stress or anxiety" (p < 0.001). Actions taken by some PLHIV to prevent unwanted disclosure included restricting who they shared their HIV status with, hiding their HIV pills, or even skipping a dose altogether because of privacy concerns. Overall, 50.0%[115/230] East Asian participants believed HIV would reduce their lifespan and 43.0%[99/230] no longer planned for their old age because of HIV. Anticipated stigma was strongly associated with receptivity to non-daily regimens. Concerted efforts to reduce stigma and deliver flexible treatment options that address the unmet treatment needs of PLHIV, including confidentiality concerns, may improve their health-related quality of life.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".