Patterns of HIV Status Disclosure to Perinatally HIV-Infected Children and Subsequent Mental Health Outcomes
Bibliographic record
Abstract
Increasing numbers of perinatally HIV-infected children are surviving into their teens and beyond. Research and clinical reports suggest that many HIV-infected children, particularly those younger than 13 years, do not know they are HIV infected owing to parental concerns about the impact on their mental health. This study examines patterns of HIV status disclosure to 77 perinatally HIV-infected ethnic minority children (aged 3–13 years), and explores the association between knowledge of HIV status and emotional and behavioral outcomes. The majority of children in this study (70%) did not know their HIV status. On average, children who knew their HIV status were older and tended to have lower CD4%. Child knowledge of HIV status was not associated with gender, ethnicity, caregiver education, parent–child relationship factors, type of placement (biological vs adoptive), or other health status indicators. As hypothesized, HIV status disclosure to infected children did not result in increased mental health problems. There was a statistical trend for children who knew their HIV status to be less depressed than children who did not know. Also, greater social disclosure (e.g. communication of child’s status to family and friends) was found when the child had an AIDS diagnosis or lower CD4%, as well as when the caregiver was HIV negative, African American and not the child’s biological parent. In conclusion, pediatric HIV infection remains a highly stigmatized issue that is difficult to discuss with the infected child and others. Yet, contrary to the beliefs of many caregivers, disclosure did not result in increased mental health problems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".