‘Management of a spoiled identity’: systematic review of interventions to address self-stigma among people living with and affected by HIV
Bibliographic record
Abstract
BACKGROUND: Self-stigma, also known as internalised stigma, is a global public health threat because it keeps people from accessing HIV and other health services. By hampering HIV testing, treatment and prevention, self-stigma can compromise the sustainability of health interventions and have serious epidemiological consequences. This review synthesised existing evidence of interventions aiming to reduce self-stigma experienced by people living with HIV and key populations affected by HIV in low-income and middle-income countries. METHODS: Studies were identified through bibliographic databases, grey literature sites, study registries, back referencing and contacts with researchers, and synthesised following Cochrane guidelines. RESULTS: Of 5880 potentially relevant titles, 20 studies were included in the review. Represented in these studies were 9536 people (65% women) from Ethiopia, India, Kenya, Lesotho, Malawi, Nepal, South Africa, Swaziland, Tanzania, Thailand, Uganda and Vietnam. Seventeen of the studies recruited people living with HIV (of which five focused specifically on pregnant women). The remaining three studies focused on young men who have sex with men, female sex workers and men who inject drugs. Studies were clustered into four categories based on the socioecological level of risk or resilience that they targeted: (1) individual level only, (2) individual and relational levels, (3) individual and structural levels and (4) structural level only. Thirteen studies targeting structural risks (with or without individual components) consistently produced significant reductions in self-stigma. The remaining seven studies that did not include a component to address structural risks produced mixed effects. CONCLUSION: Structural interventions such as scale-up of antiretroviral treatment, prevention of medication stockouts, social empowerment and economic strengthening may help substantially reduce self-stigma among individuals. More research is urgently needed to understand how to reduce self-stigma among young people and key populations, as well as how to tackle intersectional self-stigma.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".