A mixed-methods assessment of disclosure of HIV status among expert mothers living with HIV in rural Nigeria
Bibliographic record
Abstract
BACKGROUND: Peer support provided by experienced and/or trained "expert" women living with HIV has been adopted by prevention of mother-to-child transmission of HIV (PMTCT) programs across sub-Saharan Africa. While there is ample data on HIV status disclosure among non-expert women, there is little data on disclosure among such expert women, who support other women living with HIV. OBJECTIVE: This study compared HIV disclosure rates between expert and non-expert mothers living with HIV, and contextualized quantitative findings with qualitative data from expert women. METHODS: We compared survey data on HIV disclosure to male partners and family/friends from 37 expert and 100 non-expert mothers living with HIV in rural North-Central Nigeria. Four focus group discussions with expert mothers provided further context on disclosure to male partners, extended family and peers. Chi square and Fisher's exact tests were applied to quantitative data. Qualitative data were manually analyzed using a Grounded Theory approach. RESULTS: Two-thirds of the 137 participants were 21-30 years old; 89.8% were married, and 52.3% had secondary-level education. Disclosure to male partners was higher among expert (100.0%) versus non-expert mothers (85.0%), p = 0.035. Disclosure to anyone (93.1% vs 80.8%, p = 0.156), and knowledge of male partners' HIV status were similar (75.7% versus 66.7%, p = 0.324) between expert and non-expert mothers, respectively. With respect to male partners, HIV serodiscordance rates were also similar (46.4% vs 55.6%, p = 0.433). Group discussions indicated that expert mothers did not consistently disclose to their mentored clients, with community-level stigma and discrimination stated as major reasons for this non-disclosure. CONCLUSIONS: Expert mothers experience similar disclosure barriers as their non-expert peers, especially regarding disclosure outside of intimate relationships. Thus, attention to expert mothers' coping skills and disclosure status, particularly to mentored clients is important to maximize the impact of peer support in PMTCT. CLINICAL TRIALS REGISTRATION: Clinicaltrials.gov registration number NCT01936753 (retrospective), September 3, 2013.
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".