Preventing HIV transmission to children: Quality of counselling of mothers in South Africa
Bibliographic record
Abstract
AIM: To assess the quality of counselling provided to mothers through the programme to prevent mother-to-child transmission (PMTCT) of HIV in South Africa. METHODS: Structured observations of consultations and exit interviews with 60 mothers attending clinics at three purposively selected PMTCT sites across South Africa were conducted. RESULTS: Twenty-two counsellors were observed. The general quality of communication skills was very good, and 73% of HIV-negative mothers were informed of the advantages of exclusive breastfeeding (EBF). However, only one of 34 HIV-positive mothers was informed about the possible side effects of nevirapine, and none was told what to do when it occurred. Only two HIV-positive mothers were asked about essential conditions for safe formula feeding before a decision about an infant feeding option was made. None of the 12 mothers choosing to breastfeed was shown how to position the baby correctly on the breast or asked whether they thought EBF was feasible. Fewer than a quarter of mothers expressed confidence in performing the actions required, and 85% could not define the term EBF. CONCLUSION: The poor quality of counselling in the PMTCT programme will reduce the effectiveness of these programmes. As they are being scaled up, there needs to be far more attention paid towards the counselling of mothers, especially with regards to optimal infant feeding.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".