The role of internalised HIV stigma in disclosure of maternal HIV serostatus to children perinatally HIV‐exposed but uninfected: a prospective study in the United States
Bibliographic record
Abstract
INTRODUCTION: Decisions to disclose HIV serostatus may be complicated by internalised HIV stigma. We evaluated the association of internalised HIV stigma in biological mothers living with HIV with disclosure of their serostatus to their children perinatally HIV-exposed but uninfected (CHEU). METHODS: Mothers and their CHEU were enrolled in the United States (U.S.)-based Surveillance Monitoring for Antiretroviral Therapy (ART) Toxicities (SMARTT) study of the Pediatric HIV/AIDS Cohort Study (PHACS), a longitudinal study of outcomes related to in utero exposure to HIV and ART among CHEU. Mothers completing at least one stigma and disclosure assessment starting at the child's age 11-, 13-, 15- and/or 17-year study visits between 16 August 2016 and 1 October 2020 were eligible. Stigma was measured with the 28-item Internalised HIV Stigma Scale (IHSS). Mean stigma scores were linearly transformed to a range of 0-100, with higher scores indicating greater levels of stigma. At each visit, mothers were asked if their child was aware of their HIV diagnosis and at what age the child became aware. The Kaplan-Meier estimator evaluated the cumulative probability of disclosure at each child age. Logistic regression models with generalised estimating equations to account for repeated measures were fit to examine the association between stigma and disclosure, controlling for relevant socio-demographic variables. RESULTS: Included were 438 mothers of 576 children (mean age 41.5 years, 60% U.S.-born, 60% Black/African American and 37% with household income ≤$10,000). The prevalence of disclosure across all visits was 29%. Mothers whose children were aware versus not aware of their serostatus reported lower mean IHSS scores (38.2 vs. 45.6, respectively). The cumulative proportion of disclosure by age 11 was 18.4% (95% CI: 15.5%, 21.8%) and 41% by age 17 (95% CI: 35.2%, 47.4%). At all child ages, disclosure was higher among children of U.S.-born versus non-U.S.-born mothers. After adjusting for age, marital status and years since HIV diagnosis, higher IHSS scores were associated with lower odds of disclosure (OR = 0.985, 95% CI: 0.975, 0.995). CONCLUSIONS: Providing support to women as they make decisions about serostatus disclosure to their children may entail addressing internalised HIV stigma and consideration of community-level factors, particularly for non-U.S.-born mothers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".