Disclosure of human immunodeficiency virus status to children in South Africa: A comprehensive analysis
Bibliographic record
Abstract
Background: The extent of disclosure of HIV status to children and adolescents and the context facilitating their disclosure process have received little attention. Objectives: To assess disclosure and provide a comprehensive analysis of characteristics associated with disclosure to children (3–14 years) receiving antiretroviral treatment in a South African semi-urban clinic. Methods: This cross-sectional study used structured interview administered questionnaires which were supplemented with medical record data. Predictors included child, caregiver, clinical and socio-economic characteristics, viral suppression, immune response, adherence, health-related quality of life and family functioning. Results: We included 190 children of whom 45 (23.7%) received disclosure about their HIV status, of whom 28 (14.7%) were partially disclosed and 17 (8.9%) were fully disclosed. Older age of the child and higher education of the caregiver were strongly associated with disclosure. Female caregivers, detectable viral load, syrup formulation, protease inhibitor (PI) regimens with stavudine and didanosine, and self-reported non-adherence were strongly associated with non-disclosure. Conclusion: When children do well on treatment, caregivers feel less stringent need to disclose. Well-functioning families, higher educated caregivers and better socio-economic status enabled and promoted disclosure. Non-disclosure can indicate a sub-optimal social structure which could negatively affect adherence and viral suppression. There is an urgent need to address disclosure thoughtfully and proactively in the long-term disease management. For the disclosure process to be beneficial, an enabling supportive context is important, which will provide a great opportunity for future interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".