The Impact of Structured Mentor Mother Programs on 6-Month Postpartum Retention and Viral Suppression among HIV-Positive Women in Rural Nigeria: A Prospective Paired Cohort Study
Bibliographic record
Abstract
BACKGROUND: Peer support (PS) has reportedly improved Prevention of mother-to-child transmission (PMTCT) outcomes in high HIV-burden settings; however, evidence of impact on retention in care is limited. Retention in care implies consistent engagement and treatment adherence. The MoMent study evaluated the impact of structured vs unstructured PS on postpartum retention and viral load suppression among rural Nigerian women. METHODS: A total of 497 HIV-positive pregnant women were consecutively enrolled at 10 primary health care centers with structured mentor mother (MM) support, and at 10 pair-matched primary health care centers with routine, ad hoc PS. The structured MM intervention comprised an outcome-specific scope of work, close MM supervision, standardized documentation, performance evaluations, and retraining as appropriate. Retention was defined by clinic attendance during the first 6-month postpartum. Participants with ≥3 of 6 expected monthly visits were considered retained. Women with a 6-month postpartum plasma viral load of <20 copies/mL were considered suppressed. A logistic regression model with generalized estimating equation was used to assess the effect of MMs on retention and viral suppression. RESULTS: Exposure to structured MM support was associated with higher odds of retention than routine PS (adjusted odds ratio = 5.9, 95% confidence interval: 3.0 to 11.6). Similarly, the odds of viral suppression at 6-month postpartum were higher for MM-supported women (adjusted odds ratio = 4.9, 95% confidence interval: 2.6 to 9.2). CONCLUSIONS: Structured PS significantly improved postpartum PMTCT retention and viral suppression rates among women in rural Nigeria. Introduction of structure can enhance the impact of PS interventions on PMTCT outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".